Date: 2022-03-04T17:39:32+00:00

Actual source code: ts.c

      1: #include <petsc/private/tsimpl.h>
      2: #include <petscdmshell.h>
      3: #include <petscdmda.h>
      4: #include <petscviewer.h>
      5: #include <petscdraw.h>
      6: #include <petscconvest.h>

      8: #define SkipSmallValue(a,b,tol) if (PetscAbsScalar(a)< tol || PetscAbsScalar(b)< tol) continue;

     10: /* Logging support */
     11: PetscClassId  TS_CLASSID, DMTS_CLASSID;
     12: PetscLogEvent TS_Step, TS_PseudoComputeTimeStep, TS_FunctionEval, TS_JacobianEval;

     14: const char *const TSExactFinalTimeOptions[] = {"UNSPECIFIED","STEPOVER","INTERPOLATE","MATCHSTEP","TSExactFinalTimeOption","TS_EXACTFINALTIME_",NULL};

     16: static PetscErrorCode TSAdaptSetDefaultType(TSAdapt adapt,TSAdaptType default_type)
     17: {

     23:   if (!((PetscObject)adapt)->type_name) {
     24:     TSAdaptSetType(adapt,default_type);
     25:   }
     26:   return(0);
     27: }

     29: /*@
     30:    TSSetFromOptions - Sets various TS parameters from user options.

     32:    Collective on TS

     34:    Input Parameter:
     35: .  ts - the TS context obtained from TSCreate()

     37:    Options Database Keys:
     38: +  -ts_type <type> - TSEULER, TSBEULER, TSSUNDIALS, TSPSEUDO, TSCN, TSRK, TSTHETA, TSALPHA, TSGLLE, TSSSP, TSGLEE, TSBSYMP, TSIRK
     39: .  -ts_save_trajectory - checkpoint the solution at each time-step
     40: .  -ts_max_time <time> - maximum time to compute to
     41: .  -ts_max_steps <steps> - maximum number of time-steps to take
     42: .  -ts_init_time <time> - initial time to start computation
     43: .  -ts_final_time <time> - final time to compute to (deprecated: use -ts_max_time)
     44: .  -ts_dt <dt> - initial time step
     45: .  -ts_exact_final_time <stepover,interpolate,matchstep> - whether to stop at the exact given final time and how to compute the solution at that time
     46: .  -ts_max_snes_failures <maxfailures> - Maximum number of nonlinear solve failures allowed
     47: .  -ts_max_reject <maxrejects> - Maximum number of step rejections before step fails
     48: .  -ts_error_if_step_fails <true,false> - Error if no step succeeds
     49: .  -ts_rtol <rtol> - relative tolerance for local truncation error
     50: .  -ts_atol <atol> Absolute tolerance for local truncation error
     51: .  -ts_rhs_jacobian_test_mult -mat_shell_test_mult_view - test the Jacobian at each iteration against finite difference with RHS function
     52: .  -ts_rhs_jacobian_test_mult_transpose -mat_shell_test_mult_transpose_view - test the Jacobian at each iteration against finite difference with RHS function
     53: .  -ts_adjoint_solve <yes,no> After solving the ODE/DAE solve the adjoint problem (requires -ts_save_trajectory)
     54: .  -ts_fd_color - Use finite differences with coloring to compute IJacobian
     55: .  -ts_monitor - print information at each timestep
     56: .  -ts_monitor_cancel - Cancel all monitors
     57: .  -ts_monitor_lg_solution - Monitor solution graphically
     58: .  -ts_monitor_lg_error - Monitor error graphically
     59: .  -ts_monitor_error - Monitors norm of error
     60: .  -ts_monitor_lg_timestep - Monitor timestep size graphically
     61: .  -ts_monitor_lg_timestep_log - Monitor log timestep size graphically
     62: .  -ts_monitor_lg_snes_iterations - Monitor number nonlinear iterations for each timestep graphically
     63: .  -ts_monitor_lg_ksp_iterations - Monitor number nonlinear iterations for each timestep graphically
     64: .  -ts_monitor_sp_eig - Monitor eigenvalues of linearized operator graphically
     65: .  -ts_monitor_draw_solution - Monitor solution graphically
     66: .  -ts_monitor_draw_solution_phase  <xleft,yleft,xright,yright> - Monitor solution graphically with phase diagram, requires problem with exactly 2 degrees of freedom
     67: .  -ts_monitor_draw_error - Monitor error graphically, requires use to have provided TSSetSolutionFunction()
     68: .  -ts_monitor_solution [ascii binary draw][:filename][:viewerformat] - monitors the solution at each timestep
     69: .  -ts_monitor_solution_vtk <filename.vts,filename.vtu> - Save each time step to a binary file, use filename-%%03D.vts (filename-%%03D.vtu)
     70: -  -ts_monitor_envelope - determine maximum and minimum value of each component of the solution over the solution time

     72:    Notes:
     73:      See SNESSetFromOptions() and KSPSetFromOptions() for how to control the nonlinear and linear solves used by the time-stepper.

     75:      Certain SNES options get reset for each new nonlinear solver, for example -snes_lag_jacobian <its> and -snes_lag_preconditioner <its>, in order
     76:      to retain them over the multiple nonlinear solves that TS uses you mush also provide -snes_lag_jacobian_persists true and
     77:      -snes_lag_preconditioner_persists true

     79:    Developer Note:
     80:      We should unify all the -ts_monitor options in the way that -xxx_view has been unified

     82:    Level: beginner

     84: .seealso: TSGetType()
     85: @*/
     86: PetscErrorCode  TSSetFromOptions(TS ts)
     87: {
     88:   PetscBool              opt,flg,tflg;
     89:   PetscErrorCode         ierr;
     90:   char                   monfilename[PETSC_MAX_PATH_LEN];
     91:   PetscReal              time_step;
     92:   TSExactFinalTimeOption eftopt;
     93:   char                   dir[16];
     94:   TSIFunction            ifun;
     95:   const char             *defaultType;
     96:   char                   typeName[256];

    101:   TSRegisterAll();
    102:   TSGetIFunction(ts,NULL,&ifun,NULL);

    104:   PetscObjectOptionsBegin((PetscObject)ts);
    105:   if (((PetscObject)ts)->type_name) defaultType = ((PetscObject)ts)->type_name;
    106:   else defaultType = ifun ? TSBEULER : TSEULER;
    107:   PetscOptionsFList("-ts_type","TS method","TSSetType",TSList,defaultType,typeName,256,&opt);
    108:   if (opt) {
    109:     TSSetType(ts,typeName);
    110:   } else {
    111:     TSSetType(ts,defaultType);
    112:   }

    114:   /* Handle generic TS options */
    115:   PetscOptionsDeprecated("-ts_final_time","-ts_max_time","3.10",NULL);
    116:   PetscOptionsReal("-ts_max_time","Maximum time to run to","TSSetMaxTime",ts->max_time,&ts->max_time,NULL);
    117:   PetscOptionsInt("-ts_max_steps","Maximum number of time steps","TSSetMaxSteps",ts->max_steps,&ts->max_steps,NULL);
    118:   PetscOptionsReal("-ts_init_time","Initial time","TSSetTime",ts->ptime,&ts->ptime,NULL);
    119:   PetscOptionsReal("-ts_dt","Initial time step","TSSetTimeStep",ts->time_step,&time_step,&flg);
    120:   if (flg) {TSSetTimeStep(ts,time_step);}
    121:   PetscOptionsEnum("-ts_exact_final_time","Option for handling of final time step","TSSetExactFinalTime",TSExactFinalTimeOptions,(PetscEnum)ts->exact_final_time,(PetscEnum*)&eftopt,&flg);
    122:   if (flg) {TSSetExactFinalTime(ts,eftopt);}
    123:   PetscOptionsInt("-ts_max_snes_failures","Maximum number of nonlinear solve failures","TSSetMaxSNESFailures",ts->max_snes_failures,&ts->max_snes_failures,NULL);
    124:   PetscOptionsInt("-ts_max_reject","Maximum number of step rejections before step fails","TSSetMaxStepRejections",ts->max_reject,&ts->max_reject,NULL);
    125:   PetscOptionsBool("-ts_error_if_step_fails","Error if no step succeeds","TSSetErrorIfStepFails",ts->errorifstepfailed,&ts->errorifstepfailed,NULL);
    126:   PetscOptionsReal("-ts_rtol","Relative tolerance for local truncation error","TSSetTolerances",ts->rtol,&ts->rtol,NULL);
    127:   PetscOptionsReal("-ts_atol","Absolute tolerance for local truncation error","TSSetTolerances",ts->atol,&ts->atol,NULL);

    129:   PetscOptionsBool("-ts_rhs_jacobian_test_mult","Test the RHS Jacobian for consistency with RHS at each solve ","None",ts->testjacobian,&ts->testjacobian,NULL);
    130:   PetscOptionsBool("-ts_rhs_jacobian_test_mult_transpose","Test the RHS Jacobian transpose for consistency with RHS at each solve ","None",ts->testjacobiantranspose,&ts->testjacobiantranspose,NULL);
    131:   PetscOptionsBool("-ts_use_splitrhsfunction","Use the split RHS function for multirate solvers ","TSSetUseSplitRHSFunction",ts->use_splitrhsfunction,&ts->use_splitrhsfunction,NULL);
    132: #if defined(PETSC_HAVE_SAWS)
    133:   {
    134:     PetscBool set;
    135:     flg  = PETSC_FALSE;
    136:     PetscOptionsBool("-ts_saws_block","Block for SAWs memory snooper at end of TSSolve","PetscObjectSAWsBlock",((PetscObject)ts)->amspublishblock,&flg,&set);
    137:     if (set) {
    138:       PetscObjectSAWsSetBlock((PetscObject)ts,flg);
    139:     }
    140:   }
    141: #endif

    143:   /* Monitor options */
    144:   PetscOptionsInt("-ts_monitor_frequency", "Number of time steps between monitor output", "TSMonitorSetFrequency", ts->monitorFrequency, &ts->monitorFrequency, NULL);
    145:   TSMonitorSetFromOptions(ts,"-ts_monitor","Monitor time and timestep size","TSMonitorDefault",TSMonitorDefault,NULL);
    146:   TSMonitorSetFromOptions(ts,"-ts_monitor_extreme","Monitor extreme values of the solution","TSMonitorExtreme",TSMonitorExtreme,NULL);
    147:   TSMonitorSetFromOptions(ts,"-ts_monitor_solution","View the solution at each timestep","TSMonitorSolution",TSMonitorSolution,NULL);
    148:   TSMonitorSetFromOptions(ts,"-ts_dmswarm_monitor_moments","Monitor moments of particle distribution","TSDMSwarmMonitorMoments",TSDMSwarmMonitorMoments,NULL);

    150:   PetscOptionsString("-ts_monitor_python","Use Python function","TSMonitorSet",NULL,monfilename,sizeof(monfilename),&flg);
    151:   if (flg) {PetscPythonMonitorSet((PetscObject)ts,monfilename);}

    153:   PetscOptionsName("-ts_monitor_lg_solution","Monitor solution graphically","TSMonitorLGSolution",&opt);
    154:   if (opt) {
    155:     PetscInt       howoften = 1;
    156:     DM             dm;
    157:     PetscBool      net;

    159:     PetscOptionsInt("-ts_monitor_lg_solution","Monitor solution graphically","TSMonitorLGSolution",howoften,&howoften,NULL);
    160:     TSGetDM(ts,&dm);
    161:     PetscObjectTypeCompare((PetscObject)dm,DMNETWORK,&net);
    162:     if (net) {
    163:       TSMonitorLGCtxNetwork ctx;
    164:       TSMonitorLGCtxNetworkCreate(ts,NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,600,400,howoften,&ctx);
    165:       TSMonitorSet(ts,TSMonitorLGCtxNetworkSolution,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxNetworkDestroy);
    166:       PetscOptionsBool("-ts_monitor_lg_solution_semilogy","Plot the solution with a semi-log axis","",ctx->semilogy,&ctx->semilogy,NULL);
    167:     } else {
    168:       TSMonitorLGCtx ctx;
    169:       TSMonitorLGCtxCreate(PETSC_COMM_SELF,NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);
    170:       TSMonitorSet(ts,TSMonitorLGSolution,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);
    171:     }
    172:   }

    174:   PetscOptionsName("-ts_monitor_lg_error","Monitor error graphically","TSMonitorLGError",&opt);
    175:   if (opt) {
    176:     TSMonitorLGCtx ctx;
    177:     PetscInt       howoften = 1;

    179:     PetscOptionsInt("-ts_monitor_lg_error","Monitor error graphically","TSMonitorLGError",howoften,&howoften,NULL);
    180:     TSMonitorLGCtxCreate(PETSC_COMM_SELF,NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);
    181:     TSMonitorSet(ts,TSMonitorLGError,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);
    182:   }
    183:   TSMonitorSetFromOptions(ts,"-ts_monitor_error","View the error at each timestep","TSMonitorError",TSMonitorError,NULL);

    185:   PetscOptionsName("-ts_monitor_lg_timestep","Monitor timestep size graphically","TSMonitorLGTimeStep",&opt);
    186:   if (opt) {
    187:     TSMonitorLGCtx ctx;
    188:     PetscInt       howoften = 1;

    190:     PetscOptionsInt("-ts_monitor_lg_timestep","Monitor timestep size graphically","TSMonitorLGTimeStep",howoften,&howoften,NULL);
    191:     TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);
    192:     TSMonitorSet(ts,TSMonitorLGTimeStep,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);
    193:   }
    194:   PetscOptionsName("-ts_monitor_lg_timestep_log","Monitor log timestep size graphically","TSMonitorLGTimeStep",&opt);
    195:   if (opt) {
    196:     TSMonitorLGCtx ctx;
    197:     PetscInt       howoften = 1;

    199:     PetscOptionsInt("-ts_monitor_lg_timestep_log","Monitor log timestep size graphically","TSMonitorLGTimeStep",howoften,&howoften,NULL);
    200:     TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);
    201:     TSMonitorSet(ts,TSMonitorLGTimeStep,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);
    202:     ctx->semilogy = PETSC_TRUE;
    203:   }

    205:   PetscOptionsName("-ts_monitor_lg_snes_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGSNESIterations",&opt);
    206:   if (opt) {
    207:     TSMonitorLGCtx ctx;
    208:     PetscInt       howoften = 1;

    210:     PetscOptionsInt("-ts_monitor_lg_snes_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGSNESIterations",howoften,&howoften,NULL);
    211:     TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);
    212:     TSMonitorSet(ts,TSMonitorLGSNESIterations,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);
    213:   }
    214:   PetscOptionsName("-ts_monitor_lg_ksp_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGKSPIterations",&opt);
    215:   if (opt) {
    216:     TSMonitorLGCtx ctx;
    217:     PetscInt       howoften = 1;

    219:     PetscOptionsInt("-ts_monitor_lg_ksp_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGKSPIterations",howoften,&howoften,NULL);
    220:     TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);
    221:     TSMonitorSet(ts,TSMonitorLGKSPIterations,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);
    222:   }
    223:   PetscOptionsName("-ts_monitor_sp_eig","Monitor eigenvalues of linearized operator graphically","TSMonitorSPEig",&opt);
    224:   if (opt) {
    225:     TSMonitorSPEigCtx ctx;
    226:     PetscInt          howoften = 1;

    228:     PetscOptionsInt("-ts_monitor_sp_eig","Monitor eigenvalues of linearized operator graphically","TSMonitorSPEig",howoften,&howoften,NULL);
    229:     TSMonitorSPEigCtxCreate(PETSC_COMM_SELF,NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);
    230:     TSMonitorSet(ts,TSMonitorSPEig,ctx,(PetscErrorCode (*)(void**))TSMonitorSPEigCtxDestroy);
    231:   }
    232:   PetscOptionsName("-ts_monitor_sp_swarm","Display particle phase from the DMSwarm","TSMonitorSPSwarm",&opt);
    233:   if (opt) {
    234:     TSMonitorSPCtx  ctx;
    235:     PetscInt        howoften = 1;
    236:     PetscOptionsInt("-ts_monitor_sp_swarm","Display particles phase from the DMSwarm","TSMonitorSPSwarm",howoften,&howoften,NULL);
    237:     TSMonitorSPCtxCreate(PETSC_COMM_SELF, NULL, NULL, PETSC_DECIDE, PETSC_DECIDE, 300, 300, howoften, &ctx);
    238:     TSMonitorSet(ts, TSMonitorSPSwarmSolution, ctx, (PetscErrorCode (*)(void**))TSMonitorSPCtxDestroy);
    239:   }
    240:   opt  = PETSC_FALSE;
    241:   PetscOptionsName("-ts_monitor_draw_solution","Monitor solution graphically","TSMonitorDrawSolution",&opt);
    242:   if (opt) {
    243:     TSMonitorDrawCtx ctx;
    244:     PetscInt         howoften = 1;

    246:     PetscOptionsInt("-ts_monitor_draw_solution","Monitor solution graphically","TSMonitorDrawSolution",howoften,&howoften,NULL);
    247:     TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),NULL,"Computed Solution",PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);
    248:     TSMonitorSet(ts,TSMonitorDrawSolution,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);
    249:   }
    250:   opt  = PETSC_FALSE;
    251:   PetscOptionsName("-ts_monitor_draw_solution_phase","Monitor solution graphically","TSMonitorDrawSolutionPhase",&opt);
    252:   if (opt) {
    253:     TSMonitorDrawCtx ctx;
    254:     PetscReal        bounds[4];
    255:     PetscInt         n = 4;
    256:     PetscDraw        draw;
    257:     PetscDrawAxis    axis;

    259:     PetscOptionsRealArray("-ts_monitor_draw_solution_phase","Monitor solution graphically","TSMonitorDrawSolutionPhase",bounds,&n,NULL);
    260:     if (n != 4) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Must provide bounding box of phase field");
    261:     TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,300,300,1,&ctx);
    262:     PetscViewerDrawGetDraw(ctx->viewer,0,&draw);
    263:     PetscViewerDrawGetDrawAxis(ctx->viewer,0,&axis);
    264:     PetscDrawAxisSetLimits(axis,bounds[0],bounds[2],bounds[1],bounds[3]);
    265:     PetscDrawAxisSetLabels(axis,"Phase Diagram","Variable 1","Variable 2");
    266:     TSMonitorSet(ts,TSMonitorDrawSolutionPhase,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);
    267:   }
    268:   opt  = PETSC_FALSE;
    269:   PetscOptionsName("-ts_monitor_draw_error","Monitor error graphically","TSMonitorDrawError",&opt);
    270:   if (opt) {
    271:     TSMonitorDrawCtx ctx;
    272:     PetscInt         howoften = 1;

    274:     PetscOptionsInt("-ts_monitor_draw_error","Monitor error graphically","TSMonitorDrawError",howoften,&howoften,NULL);
    275:     TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),NULL,"Error",PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);
    276:     TSMonitorSet(ts,TSMonitorDrawError,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);
    277:   }
    278:   opt  = PETSC_FALSE;
    279:   PetscOptionsName("-ts_monitor_draw_solution_function","Monitor solution provided by TSMonitorSetSolutionFunction() graphically","TSMonitorDrawSolutionFunction",&opt);
    280:   if (opt) {
    281:     TSMonitorDrawCtx ctx;
    282:     PetscInt         howoften = 1;

    284:     PetscOptionsInt("-ts_monitor_draw_solution_function","Monitor solution provided by TSMonitorSetSolutionFunction() graphically","TSMonitorDrawSolutionFunction",howoften,&howoften,NULL);
    285:     TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),NULL,"Solution provided by user function",PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);
    286:     TSMonitorSet(ts,TSMonitorDrawSolutionFunction,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);
    287:   }

    289:   opt  = PETSC_FALSE;
    290:   PetscOptionsString("-ts_monitor_solution_vtk","Save each time step to a binary file, use filename-%%03D.vts","TSMonitorSolutionVTK",NULL,monfilename,sizeof(monfilename),&flg);
    291:   if (flg) {
    292:     const char *ptr,*ptr2;
    293:     char       *filetemplate;
    294:     if (!monfilename[0]) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"-ts_monitor_solution_vtk requires a file template, e.g. filename-%%03D.vts");
    295:     /* Do some cursory validation of the input. */
    296:     PetscStrstr(monfilename,"%",(char**)&ptr);
    297:     if (!ptr) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"-ts_monitor_solution_vtk requires a file template, e.g. filename-%%03D.vts");
    298:     for (ptr++; ptr && *ptr; ptr++) {
    299:       PetscStrchr("DdiouxX",*ptr,(char**)&ptr2);
    300:       if (!ptr2 && (*ptr < '0' || '9' < *ptr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Invalid file template argument to -ts_monitor_solution_vtk, should look like filename-%%03D.vts");
    301:       if (ptr2) break;
    302:     }
    303:     PetscStrallocpy(monfilename,&filetemplate);
    304:     TSMonitorSet(ts,TSMonitorSolutionVTK,filetemplate,(PetscErrorCode (*)(void**))TSMonitorSolutionVTKDestroy);
    305:   }

    307:   PetscOptionsString("-ts_monitor_dmda_ray","Display a ray of the solution","None","y=0",dir,sizeof(dir),&flg);
    308:   if (flg) {
    309:     TSMonitorDMDARayCtx *rayctx;
    310:     int                  ray = 0;
    311:     DMDirection          ddir;
    312:     DM                   da;
    313:     PetscMPIInt          rank;

    315:     if (dir[1] != '=') SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Unknown ray %s",dir);
    316:     if (dir[0] == 'x') ddir = DM_X;
    317:     else if (dir[0] == 'y') ddir = DM_Y;
    318:     else SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Unknown ray %s",dir);
    319:     sscanf(dir+2,"%d",&ray);

    321:     PetscInfo2(((PetscObject)ts),"Displaying DMDA ray %c = %d\n",dir[0],ray);
    322:     PetscNew(&rayctx);
    323:     TSGetDM(ts,&da);
    324:     DMDAGetRay(da,ddir,ray,&rayctx->ray,&rayctx->scatter);
    325:     MPI_Comm_rank(PetscObjectComm((PetscObject)ts),&rank);
    326:     if (rank == 0) {
    327:       PetscViewerDrawOpen(PETSC_COMM_SELF,NULL,NULL,0,0,600,300,&rayctx->viewer);
    328:     }
    329:     rayctx->lgctx = NULL;
    330:     TSMonitorSet(ts,TSMonitorDMDARay,rayctx,TSMonitorDMDARayDestroy);
    331:   }
    332:   PetscOptionsString("-ts_monitor_lg_dmda_ray","Display a ray of the solution","None","x=0",dir,sizeof(dir),&flg);
    333:   if (flg) {
    334:     TSMonitorDMDARayCtx *rayctx;
    335:     int                 ray = 0;
    336:     DMDirection         ddir;
    337:     DM                  da;
    338:     PetscInt            howoften = 1;

    340:     if (dir[1] != '=') SETERRQ1(PetscObjectComm((PetscObject) ts), PETSC_ERR_ARG_WRONG, "Malformed ray %s", dir);
    341:     if      (dir[0] == 'x') ddir = DM_X;
    342:     else if (dir[0] == 'y') ddir = DM_Y;
    343:     else SETERRQ1(PetscObjectComm((PetscObject) ts), PETSC_ERR_ARG_WRONG, "Unknown ray direction %s", dir);
    344:     sscanf(dir+2, "%d", &ray);

    346:     PetscInfo2(((PetscObject) ts),"Displaying LG DMDA ray %c = %d\n", dir[0], ray);
    347:     PetscNew(&rayctx);
    348:     TSGetDM(ts, &da);
    349:     DMDAGetRay(da, ddir, ray, &rayctx->ray, &rayctx->scatter);
    350:     TSMonitorLGCtxCreate(PETSC_COMM_SELF,NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,600,400,howoften,&rayctx->lgctx);
    351:     TSMonitorSet(ts, TSMonitorLGDMDARay, rayctx, TSMonitorDMDARayDestroy);
    352:   }

    354:   PetscOptionsName("-ts_monitor_envelope","Monitor maximum and minimum value of each component of the solution","TSMonitorEnvelope",&opt);
    355:   if (opt) {
    356:     TSMonitorEnvelopeCtx ctx;

    358:     TSMonitorEnvelopeCtxCreate(ts,&ctx);
    359:     TSMonitorSet(ts,TSMonitorEnvelope,ctx,(PetscErrorCode (*)(void**))TSMonitorEnvelopeCtxDestroy);
    360:   }
    361:   flg  = PETSC_FALSE;
    362:   PetscOptionsBool("-ts_monitor_cancel","Remove all monitors","TSMonitorCancel",flg,&flg,&opt);
    363:   if (opt && flg) {TSMonitorCancel(ts);}

    365:   flg  = PETSC_FALSE;
    366:   PetscOptionsBool("-ts_fd_color", "Use finite differences with coloring to compute IJacobian", "TSComputeJacobianDefaultColor", flg, &flg, NULL);
    367:   if (flg) {
    368:     DM   dm;
    369:     DMTS tdm;

    371:     TSGetDM(ts, &dm);
    372:     DMGetDMTS(dm, &tdm);
    373:     tdm->ijacobianctx = NULL;
    374:     TSSetIJacobian(ts, NULL, NULL, TSComputeIJacobianDefaultColor, NULL);
    375:     PetscInfo(ts, "Setting default finite difference coloring Jacobian matrix\n");
    376:   }

    378:   /* Handle specific TS options */
    379:   if (ts->ops->setfromoptions) {
    380:     (*ts->ops->setfromoptions)(PetscOptionsObject,ts);
    381:   }

    383:   /* Handle TSAdapt options */
    384:   TSGetAdapt(ts,&ts->adapt);
    385:   TSAdaptSetDefaultType(ts->adapt,ts->default_adapt_type);
    386:   TSAdaptSetFromOptions(PetscOptionsObject,ts->adapt);

    388:   /* TS trajectory must be set after TS, since it may use some TS options above */
    389:   tflg = ts->trajectory ? PETSC_TRUE : PETSC_FALSE;
    390:   PetscOptionsBool("-ts_save_trajectory","Save the solution at each timestep","TSSetSaveTrajectory",tflg,&tflg,NULL);
    391:   if (tflg) {
    392:     TSSetSaveTrajectory(ts);
    393:   }

    395:   TSAdjointSetFromOptions(PetscOptionsObject,ts);

    397:   /* process any options handlers added with PetscObjectAddOptionsHandler() */
    398:   PetscObjectProcessOptionsHandlers(PetscOptionsObject,(PetscObject)ts);
    399:   PetscOptionsEnd();

    401:   if (ts->trajectory) {
    402:     TSTrajectorySetFromOptions(ts->trajectory,ts);
    403:   }

    405:   /* why do we have to do this here and not during TSSetUp? */
    406:   TSGetSNES(ts,&ts->snes);
    407:   if (ts->problem_type == TS_LINEAR) {
    408:     PetscObjectTypeCompareAny((PetscObject)ts->snes,&flg,SNESKSPONLY,SNESKSPTRANSPOSEONLY,"");
    409:     if (!flg) { SNESSetType(ts->snes,SNESKSPONLY); }
    410:   }
    411:   SNESSetFromOptions(ts->snes);
    412:   return(0);
    413: }

    415: /*@
    416:    TSGetTrajectory - Gets the trajectory from a TS if it exists

    418:    Collective on TS

    420:    Input Parameters:
    421: .  ts - the TS context obtained from TSCreate()

    423:    Output Parameters:
    424: .  tr - the TSTrajectory object, if it exists

    426:    Note: This routine should be called after all TS options have been set

    428:    Level: advanced

    430: .seealso: TSGetTrajectory(), TSAdjointSolve(), TSTrajectory, TSTrajectoryCreate()

    432: @*/
    433: PetscErrorCode  TSGetTrajectory(TS ts,TSTrajectory *tr)
    434: {
    437:   *tr = ts->trajectory;
    438:   return(0);
    439: }

    441: /*@
    442:    TSSetSaveTrajectory - Causes the TS to save its solutions as it iterates forward in time in a TSTrajectory object

    444:    Collective on TS

    446:    Input Parameter:
    447: .  ts - the TS context obtained from TSCreate()

    449:    Options Database:
    450: +  -ts_save_trajectory - saves the trajectory to a file
    451: -  -ts_trajectory_type type

    453: Note: This routine should be called after all TS options have been set

    455:     The TSTRAJECTORYVISUALIZATION files can be loaded into Python with $PETSC_DIR/lib/petsc/bin/PetscBinaryIOTrajectory.py and
    456:    MATLAB with $PETSC_DIR/share/petsc/matlab/PetscReadBinaryTrajectory.m

    458:    Level: intermediate

    460: .seealso: TSGetTrajectory(), TSAdjointSolve()

    462: @*/
    463: PetscErrorCode  TSSetSaveTrajectory(TS ts)
    464: {

    469:   if (!ts->trajectory) {
    470:     TSTrajectoryCreate(PetscObjectComm((PetscObject)ts),&ts->trajectory);
    471:   }
    472:   return(0);
    473: }

    475: /*@
    476:    TSResetTrajectory - Destroys and recreates the internal TSTrajectory object

    478:    Collective on TS

    480:    Input Parameters:
    481: .  ts - the TS context obtained from TSCreate()

    483:    Level: intermediate

    485: .seealso: TSGetTrajectory(), TSAdjointSolve()

    487: @*/
    488: PetscErrorCode  TSResetTrajectory(TS ts)
    489: {

    494:   if (ts->trajectory) {
    495:     TSTrajectoryDestroy(&ts->trajectory);
    496:     TSTrajectoryCreate(PetscObjectComm((PetscObject)ts),&ts->trajectory);
    497:   }
    498:   return(0);
    499: }

    501: /*@
    502:    TSComputeRHSJacobian - Computes the Jacobian matrix that has been
    503:       set with TSSetRHSJacobian().

    505:    Collective on TS

    507:    Input Parameters:
    508: +  ts - the TS context
    509: .  t - current timestep
    510: -  U - input vector

    512:    Output Parameters:
    513: +  A - Jacobian matrix
    514: -  B - optional preconditioning matrix

    516:    Notes:
    517:    Most users should not need to explicitly call this routine, as it
    518:    is used internally within the nonlinear solvers.

    520:    Level: developer

    522: .seealso:  TSSetRHSJacobian(), KSPSetOperators()
    523: @*/
    524: PetscErrorCode  TSComputeRHSJacobian(TS ts,PetscReal t,Vec U,Mat A,Mat B)
    525: {
    526:   PetscErrorCode   ierr;
    527:   PetscObjectState Ustate;
    528:   PetscObjectId    Uid;
    529:   DM               dm;
    530:   DMTS             tsdm;
    531:   TSRHSJacobian    rhsjacobianfunc;
    532:   void             *ctx;
    533:   TSRHSFunction    rhsfunction;

    539:   TSGetDM(ts,&dm);
    540:   DMGetDMTS(dm,&tsdm);
    541:   DMTSGetRHSFunction(dm,&rhsfunction,NULL);
    542:   DMTSGetRHSJacobian(dm,&rhsjacobianfunc,&ctx);
    543:   PetscObjectStateGet((PetscObject)U,&Ustate);
    544:   PetscObjectGetId((PetscObject)U,&Uid);

    546:   if (ts->rhsjacobian.time == t && (ts->problem_type == TS_LINEAR || (ts->rhsjacobian.Xid == Uid && ts->rhsjacobian.Xstate == Ustate)) && (rhsfunction != TSComputeRHSFunctionLinear)) return(0);

    548:   if (ts->rhsjacobian.shift && ts->rhsjacobian.reuse) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Should not call TSComputeRHSJacobian() on a shifted matrix (shift=%lf) when RHSJacobian is reusable.",ts->rhsjacobian.shift);
    549:   if (rhsjacobianfunc) {
    550:     PetscLogEventBegin(TS_JacobianEval,ts,U,A,B);
    551:     PetscStackPush("TS user Jacobian function");
    552:     (*rhsjacobianfunc)(ts,t,U,A,B,ctx);
    553:     PetscStackPop;
    554:     ts->rhsjacs++;
    555:     PetscLogEventEnd(TS_JacobianEval,ts,U,A,B);
    556:   } else {
    557:     MatZeroEntries(A);
    558:     if (B && A != B) {MatZeroEntries(B);}
    559:   }
    560:   ts->rhsjacobian.time  = t;
    561:   ts->rhsjacobian.shift = 0;
    562:   ts->rhsjacobian.scale = 1.;
    563:   PetscObjectGetId((PetscObject)U,&ts->rhsjacobian.Xid);
    564:   PetscObjectStateGet((PetscObject)U,&ts->rhsjacobian.Xstate);
    565:   return(0);
    566: }

    568: /*@
    569:    TSComputeRHSFunction - Evaluates the right-hand-side function.

    571:    Collective on TS

    573:    Input Parameters:
    574: +  ts - the TS context
    575: .  t - current time
    576: -  U - state vector

    578:    Output Parameter:
    579: .  y - right hand side

    581:    Note:
    582:    Most users should not need to explicitly call this routine, as it
    583:    is used internally within the nonlinear solvers.

    585:    Level: developer

    587: .seealso: TSSetRHSFunction(), TSComputeIFunction()
    588: @*/
    589: PetscErrorCode TSComputeRHSFunction(TS ts,PetscReal t,Vec U,Vec y)
    590: {
    592:   TSRHSFunction  rhsfunction;
    593:   TSIFunction    ifunction;
    594:   void           *ctx;
    595:   DM             dm;

    601:   TSGetDM(ts,&dm);
    602:   DMTSGetRHSFunction(dm,&rhsfunction,&ctx);
    603:   DMTSGetIFunction(dm,&ifunction,NULL);

    605:   if (!rhsfunction && !ifunction) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSFunction() and / or TSSetIFunction()");

    607:   if (rhsfunction) {
    608:     PetscLogEventBegin(TS_FunctionEval,ts,U,y,0);
    609:     VecLockReadPush(U);
    610:     PetscStackPush("TS user right-hand-side function");
    611:     (*rhsfunction)(ts,t,U,y,ctx);
    612:     PetscStackPop;
    613:     VecLockReadPop(U);
    614:     ts->rhsfuncs++;
    615:     PetscLogEventEnd(TS_FunctionEval,ts,U,y,0);
    616:   } else {
    617:     VecZeroEntries(y);
    618:   }
    619:   return(0);
    620: }

    622: /*@
    623:    TSComputeSolutionFunction - Evaluates the solution function.

    625:    Collective on TS

    627:    Input Parameters:
    628: +  ts - the TS context
    629: -  t - current time

    631:    Output Parameter:
    632: .  U - the solution

    634:    Note:
    635:    Most users should not need to explicitly call this routine, as it
    636:    is used internally within the nonlinear solvers.

    638:    Level: developer

    640: .seealso: TSSetSolutionFunction(), TSSetRHSFunction(), TSComputeIFunction()
    641: @*/
    642: PetscErrorCode TSComputeSolutionFunction(TS ts,PetscReal t,Vec U)
    643: {
    644:   PetscErrorCode     ierr;
    645:   TSSolutionFunction solutionfunction;
    646:   void               *ctx;
    647:   DM                 dm;

    652:   TSGetDM(ts,&dm);
    653:   DMTSGetSolutionFunction(dm,&solutionfunction,&ctx);

    655:   if (solutionfunction) {
    656:     PetscStackPush("TS user solution function");
    657:     (*solutionfunction)(ts,t,U,ctx);
    658:     PetscStackPop;
    659:   }
    660:   return(0);
    661: }
    662: /*@
    663:    TSComputeForcingFunction - Evaluates the forcing function.

    665:    Collective on TS

    667:    Input Parameters:
    668: +  ts - the TS context
    669: -  t - current time

    671:    Output Parameter:
    672: .  U - the function value

    674:    Note:
    675:    Most users should not need to explicitly call this routine, as it
    676:    is used internally within the nonlinear solvers.

    678:    Level: developer

    680: .seealso: TSSetSolutionFunction(), TSSetRHSFunction(), TSComputeIFunction()
    681: @*/
    682: PetscErrorCode TSComputeForcingFunction(TS ts,PetscReal t,Vec U)
    683: {
    684:   PetscErrorCode     ierr, (*forcing)(TS,PetscReal,Vec,void*);
    685:   void               *ctx;
    686:   DM                 dm;

    691:   TSGetDM(ts,&dm);
    692:   DMTSGetForcingFunction(dm,&forcing,&ctx);

    694:   if (forcing) {
    695:     PetscStackPush("TS user forcing function");
    696:     (*forcing)(ts,t,U,ctx);
    697:     PetscStackPop;
    698:   }
    699:   return(0);
    700: }

    702: static PetscErrorCode TSGetRHSVec_Private(TS ts,Vec *Frhs)
    703: {
    704:   Vec            F;

    708:   *Frhs = NULL;
    709:   TSGetIFunction(ts,&F,NULL,NULL);
    710:   if (!ts->Frhs) {
    711:     VecDuplicate(F,&ts->Frhs);
    712:   }
    713:   *Frhs = ts->Frhs;
    714:   return(0);
    715: }

    717: PetscErrorCode TSGetRHSMats_Private(TS ts,Mat *Arhs,Mat *Brhs)
    718: {
    719:   Mat            A,B;
    721:   TSIJacobian    ijacobian;

    724:   if (Arhs) *Arhs = NULL;
    725:   if (Brhs) *Brhs = NULL;
    726:   TSGetIJacobian(ts,&A,&B,&ijacobian,NULL);
    727:   if (Arhs) {
    728:     if (!ts->Arhs) {
    729:       if (ijacobian) {
    730:         MatDuplicate(A,MAT_DO_NOT_COPY_VALUES,&ts->Arhs);
    731:         TSSetMatStructure(ts,SAME_NONZERO_PATTERN);
    732:       } else {
    733:         ts->Arhs = A;
    734:         PetscObjectReference((PetscObject)A);
    735:       }
    736:     } else {
    737:       PetscBool flg;
    738:       SNESGetUseMatrixFree(ts->snes,NULL,&flg);
    739:       /* Handle case where user provided only RHSJacobian and used -snes_mf_operator */
    740:       if (flg && !ijacobian && ts->Arhs == ts->Brhs) {
    741:         PetscObjectDereference((PetscObject)ts->Arhs);
    742:         ts->Arhs = A;
    743:         PetscObjectReference((PetscObject)A);
    744:       }
    745:     }
    746:     *Arhs = ts->Arhs;
    747:   }
    748:   if (Brhs) {
    749:     if (!ts->Brhs) {
    750:       if (A != B) {
    751:         if (ijacobian) {
    752:           MatDuplicate(B,MAT_DO_NOT_COPY_VALUES,&ts->Brhs);
    753:         } else {
    754:           ts->Brhs = B;
    755:           PetscObjectReference((PetscObject)B);
    756:         }
    757:       } else {
    758:         PetscObjectReference((PetscObject)ts->Arhs);
    759:         ts->Brhs = ts->Arhs;
    760:       }
    761:     }
    762:     *Brhs = ts->Brhs;
    763:   }
    764:   return(0);
    765: }

    767: /*@
    768:    TSComputeIFunction - Evaluates the DAE residual written in implicit form F(t,U,Udot)=0

    770:    Collective on TS

    772:    Input Parameters:
    773: +  ts - the TS context
    774: .  t - current time
    775: .  U - state vector
    776: .  Udot - time derivative of state vector
    777: -  imex - flag indicates if the method is IMEX so that the RHSFunction should be kept separate

    779:    Output Parameter:
    780: .  Y - right hand side

    782:    Note:
    783:    Most users should not need to explicitly call this routine, as it
    784:    is used internally within the nonlinear solvers.

    786:    If the user did did not write their equations in implicit form, this
    787:    function recasts them in implicit form.

    789:    Level: developer

    791: .seealso: TSSetIFunction(), TSComputeRHSFunction()
    792: @*/
    793: PetscErrorCode TSComputeIFunction(TS ts,PetscReal t,Vec U,Vec Udot,Vec Y,PetscBool imex)
    794: {
    796:   TSIFunction    ifunction;
    797:   TSRHSFunction  rhsfunction;
    798:   void           *ctx;
    799:   DM             dm;

    807:   TSGetDM(ts,&dm);
    808:   DMTSGetIFunction(dm,&ifunction,&ctx);
    809:   DMTSGetRHSFunction(dm,&rhsfunction,NULL);

    811:   if (!rhsfunction && !ifunction) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSFunction() and / or TSSetIFunction()");

    813:   PetscLogEventBegin(TS_FunctionEval,ts,U,Udot,Y);
    814:   if (ifunction) {
    815:     PetscStackPush("TS user implicit function");
    816:     (*ifunction)(ts,t,U,Udot,Y,ctx);
    817:     PetscStackPop;
    818:     ts->ifuncs++;
    819:   }
    820:   if (imex) {
    821:     if (!ifunction) {
    822:       VecCopy(Udot,Y);
    823:     }
    824:   } else if (rhsfunction) {
    825:     if (ifunction) {
    826:       Vec Frhs;
    827:       TSGetRHSVec_Private(ts,&Frhs);
    828:       TSComputeRHSFunction(ts,t,U,Frhs);
    829:       VecAXPY(Y,-1,Frhs);
    830:     } else {
    831:       TSComputeRHSFunction(ts,t,U,Y);
    832:       VecAYPX(Y,-1,Udot);
    833:     }
    834:   }
    835:   PetscLogEventEnd(TS_FunctionEval,ts,U,Udot,Y);
    836:   return(0);
    837: }

    839: /*
    840:    TSRecoverRHSJacobian - Recover the Jacobian matrix so that one can call TSComputeRHSJacobian() on it.

    842:    Note:
    843:    This routine is needed when one switches from TSComputeIJacobian() to TSComputeRHSJacobian() because the Jacobian matrix may be shifted or scaled in TSComputeIJacobian().

    845: */
    846: static PetscErrorCode TSRecoverRHSJacobian(TS ts,Mat A,Mat B)
    847: {
    848:   PetscErrorCode   ierr;

    852:   if (A != ts->Arhs) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Invalid Amat");
    853:   if (B != ts->Brhs) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Invalid Bmat");

    855:   if (ts->rhsjacobian.shift) {
    856:     MatShift(A,-ts->rhsjacobian.shift);
    857:   }
    858:   if (ts->rhsjacobian.scale == -1.) {
    859:     MatScale(A,-1);
    860:   }
    861:   if (B && B == ts->Brhs && A != B) {
    862:     if (ts->rhsjacobian.shift) {
    863:       MatShift(B,-ts->rhsjacobian.shift);
    864:     }
    865:     if (ts->rhsjacobian.scale == -1.) {
    866:       MatScale(B,-1);
    867:     }
    868:   }
    869:   ts->rhsjacobian.shift = 0;
    870:   ts->rhsjacobian.scale = 1.;
    871:   return(0);
    872: }

    874: /*@
    875:    TSComputeIJacobian - Evaluates the Jacobian of the DAE

    877:    Collective on TS

    879:    Input
    880:       Input Parameters:
    881: +  ts - the TS context
    882: .  t - current timestep
    883: .  U - state vector
    884: .  Udot - time derivative of state vector
    885: .  shift - shift to apply, see note below
    886: -  imex - flag indicates if the method is IMEX so that the RHSJacobian should be kept separate

    888:    Output Parameters:
    889: +  A - Jacobian matrix
    890: -  B - matrix from which the preconditioner is constructed; often the same as A

    892:    Notes:
    893:    If F(t,U,Udot)=0 is the DAE, the required Jacobian is

    895:    dF/dU + shift*dF/dUdot

    897:    Most users should not need to explicitly call this routine, as it
    898:    is used internally within the nonlinear solvers.

    900:    Level: developer

    902: .seealso:  TSSetIJacobian()
    903: @*/
    904: PetscErrorCode TSComputeIJacobian(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat A,Mat B,PetscBool imex)
    905: {
    907:   TSIJacobian    ijacobian;
    908:   TSRHSJacobian  rhsjacobian;
    909:   DM             dm;
    910:   void           *ctx;

    921:   TSGetDM(ts,&dm);
    922:   DMTSGetIJacobian(dm,&ijacobian,&ctx);
    923:   DMTSGetRHSJacobian(dm,&rhsjacobian,NULL);

    925:   if (!rhsjacobian && !ijacobian) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSJacobian() and / or TSSetIJacobian()");

    927:   PetscLogEventBegin(TS_JacobianEval,ts,U,A,B);
    928:   if (ijacobian) {
    929:     PetscStackPush("TS user implicit Jacobian");
    930:     (*ijacobian)(ts,t,U,Udot,shift,A,B,ctx);
    931:     ts->ijacs++;
    932:     PetscStackPop;
    933:   }
    934:   if (imex) {
    935:     if (!ijacobian) {  /* system was written as Udot = G(t,U) */
    936:       PetscBool assembled;
    937:       if (rhsjacobian) {
    938:         Mat Arhs = NULL;
    939:         TSGetRHSMats_Private(ts,&Arhs,NULL);
    940:         if (A == Arhs) {
    941:           if (rhsjacobian == TSComputeRHSJacobianConstant) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Unsupported operation! cannot use TSComputeRHSJacobianConstant"); /* there is no way to reconstruct shift*M-J since J cannot be reevaluated */
    942:           ts->rhsjacobian.time = PETSC_MIN_REAL;
    943:         }
    944:       }
    945:       MatZeroEntries(A);
    946:       MatAssembled(A,&assembled);
    947:       if (!assembled) {
    948:         MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
    949:         MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
    950:       }
    951:       MatShift(A,shift);
    952:       if (A != B) {
    953:         MatZeroEntries(B);
    954:         MatAssembled(B,&assembled);
    955:         if (!assembled) {
    956:           MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
    957:           MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
    958:         }
    959:         MatShift(B,shift);
    960:       }
    961:     }
    962:   } else {
    963:     Mat Arhs = NULL,Brhs = NULL;
    964:     if (rhsjacobian) { /* RHSJacobian needs to be converted to part of IJacobian if exists */
    965:       TSGetRHSMats_Private(ts,&Arhs,&Brhs);
    966:     }
    967:     if (Arhs == A) { /* No IJacobian matrix, so we only have the RHS matrix */
    968:       PetscObjectState Ustate;
    969:       PetscObjectId    Uid;
    970:       TSRHSFunction    rhsfunction;

    972:       DMTSGetRHSFunction(dm,&rhsfunction,NULL);
    973:       PetscObjectStateGet((PetscObject)U,&Ustate);
    974:       PetscObjectGetId((PetscObject)U,&Uid);
    975:       if ((rhsjacobian == TSComputeRHSJacobianConstant || (ts->rhsjacobian.time == t && (ts->problem_type == TS_LINEAR || (ts->rhsjacobian.Xid == Uid && ts->rhsjacobian.Xstate == Ustate)) && rhsfunction != TSComputeRHSFunctionLinear)) && ts->rhsjacobian.scale == -1.) { /* No need to recompute RHSJacobian */
    976:         MatShift(A,shift-ts->rhsjacobian.shift); /* revert the old shift and add the new shift with a single call to MatShift */
    977:         if (A != B) {
    978:           MatShift(B,shift-ts->rhsjacobian.shift);
    979:         }
    980:       } else {
    981:         PetscBool flg;

    983:         if (ts->rhsjacobian.reuse) { /* Undo the damage */
    984:           /* MatScale has a short path for this case.
    985:              However, this code path is taken the first time TSComputeRHSJacobian is called
    986:              and the matrices have not been assembled yet */
    987:           TSRecoverRHSJacobian(ts,A,B);
    988:         }
    989:         TSComputeRHSJacobian(ts,t,U,A,B);
    990:         SNESGetUseMatrixFree(ts->snes,NULL,&flg);
    991:         /* since -snes_mf_operator uses the full SNES function it does not need to be shifted or scaled here */
    992:         if (!flg) {
    993:           MatScale(A,-1);
    994:           MatShift(A,shift);
    995:         }
    996:         if (A != B) {
    997:           MatScale(B,-1);
    998:           MatShift(B,shift);
    999:         }
    1000:       }
    1001:       ts->rhsjacobian.scale = -1;
    1002:       ts->rhsjacobian.shift = shift;
    1003:     } else if (Arhs) {          /* Both IJacobian and RHSJacobian */
    1004:       if (!ijacobian) {         /* No IJacobian provided, but we have a separate RHS matrix */
    1005:         MatZeroEntries(A);
    1006:         MatShift(A,shift);
    1007:         if (A != B) {
    1008:           MatZeroEntries(B);
    1009:           MatShift(B,shift);
    1010:         }
    1011:       }
    1012:       TSComputeRHSJacobian(ts,t,U,Arhs,Brhs);
    1013:       MatAXPY(A,-1,Arhs,ts->axpy_pattern);
    1014:       if (A != B) {
    1015:         MatAXPY(B,-1,Brhs,ts->axpy_pattern);
    1016:       }
    1017:     }
    1018:   }
    1019:   PetscLogEventEnd(TS_JacobianEval,ts,U,A,B);
    1020:   return(0);
    1021: }

    1023: /*@C
    1024:     TSSetRHSFunction - Sets the routine for evaluating the function,
    1025:     where U_t = G(t,u).

    1027:     Logically Collective on TS

    1029:     Input Parameters:
    1030: +   ts - the TS context obtained from TSCreate()
    1031: .   r - vector to put the computed right hand side (or NULL to have it created)
    1032: .   f - routine for evaluating the right-hand-side function
    1033: -   ctx - [optional] user-defined context for private data for the
    1034:           function evaluation routine (may be NULL)

    1036:     Calling sequence of f:
    1037: $     PetscErrorCode f(TS ts,PetscReal t,Vec u,Vec F,void *ctx);

    1039: +   ts - timestep context
    1040: .   t - current timestep
    1041: .   u - input vector
    1042: .   F - function vector
    1043: -   ctx - [optional] user-defined function context

    1045:     Level: beginner

    1047:     Notes:
    1048:     You must call this function or TSSetIFunction() to define your ODE. You cannot use this function when solving a DAE.

    1050: .seealso: TSSetRHSJacobian(), TSSetIJacobian(), TSSetIFunction()
    1051: @*/
    1052: PetscErrorCode  TSSetRHSFunction(TS ts,Vec r,PetscErrorCode (*f)(TS,PetscReal,Vec,Vec,void*),void *ctx)
    1053: {
    1055:   SNES           snes;
    1056:   Vec            ralloc = NULL;
    1057:   DM             dm;

    1063:   TSGetDM(ts,&dm);
    1064:   DMTSSetRHSFunction(dm,f,ctx);
    1065:   TSGetSNES(ts,&snes);
    1066:   if (!r && !ts->dm && ts->vec_sol) {
    1067:     VecDuplicate(ts->vec_sol,&ralloc);
    1068:     r = ralloc;
    1069:   }
    1070:   SNESSetFunction(snes,r,SNESTSFormFunction,ts);
    1071:   VecDestroy(&ralloc);
    1072:   return(0);
    1073: }

    1075: /*@C
    1076:     TSSetSolutionFunction - Provide a function that computes the solution of the ODE or DAE

    1078:     Logically Collective on TS

    1080:     Input Parameters:
    1081: +   ts - the TS context obtained from TSCreate()
    1082: .   f - routine for evaluating the solution
    1083: -   ctx - [optional] user-defined context for private data for the
    1084:           function evaluation routine (may be NULL)

    1086:     Calling sequence of f:
    1087: $     PetscErrorCode f(TS ts,PetscReal t,Vec u,void *ctx);

    1089: +   t - current timestep
    1090: .   u - output vector
    1091: -   ctx - [optional] user-defined function context

    1093:     Options Database:
    1094: +  -ts_monitor_lg_error - create a graphical monitor of error history, requires user to have provided TSSetSolutionFunction()
    1095: -  -ts_monitor_draw_error - Monitor error graphically, requires user to have provided TSSetSolutionFunction()

    1097:     Notes:
    1098:     This routine is used for testing accuracy of time integration schemes when you already know the solution.
    1099:     If analytic solutions are not known for your system, consider using the Method of Manufactured Solutions to
    1100:     create closed-form solutions with non-physical forcing terms.

    1102:     For low-dimensional problems solved in serial, such as small discrete systems, TSMonitorLGError() can be used to monitor the error history.

    1104:     Level: beginner

    1106: .seealso: TSSetRHSJacobian(), TSSetIJacobian(), TSComputeSolutionFunction(), TSSetForcingFunction(), TSSetSolution(), TSGetSolution(), TSMonitorLGError(), TSMonitorDrawError()
    1107: @*/
    1108: PetscErrorCode  TSSetSolutionFunction(TS ts,PetscErrorCode (*f)(TS,PetscReal,Vec,void*),void *ctx)
    1109: {
    1111:   DM             dm;

    1115:   TSGetDM(ts,&dm);
    1116:   DMTSSetSolutionFunction(dm,f,ctx);
    1117:   return(0);
    1118: }

    1120: /*@C
    1121:     TSSetForcingFunction - Provide a function that computes a forcing term for a ODE or PDE

    1123:     Logically Collective on TS

    1125:     Input Parameters:
    1126: +   ts - the TS context obtained from TSCreate()
    1127: .   func - routine for evaluating the forcing function
    1128: -   ctx - [optional] user-defined context for private data for the
    1129:           function evaluation routine (may be NULL)

    1131:     Calling sequence of func:
    1132: $     PetscErrorCode func (TS ts,PetscReal t,Vec f,void *ctx);

    1134: +   t - current timestep
    1135: .   f - output vector
    1136: -   ctx - [optional] user-defined function context

    1138:     Notes:
    1139:     This routine is useful for testing accuracy of time integration schemes when using the Method of Manufactured Solutions to
    1140:     create closed-form solutions with a non-physical forcing term. It allows you to use the Method of Manufactored Solution without directly editing the
    1141:     definition of the problem you are solving and hence possibly introducing bugs.

    1143:     This replaces the ODE F(u,u_t,t) = 0 the TS is solving with F(u,u_t,t) - func(t) = 0

    1145:     This forcing function does not depend on the solution to the equations, it can only depend on spatial location, time, and possibly parameters, the
    1146:     parameters can be passed in the ctx variable.

    1148:     For low-dimensional problems solved in serial, such as small discrete systems, TSMonitorLGError() can be used to monitor the error history.

    1150:     Level: beginner

    1152: .seealso: TSSetRHSJacobian(), TSSetIJacobian(), TSComputeSolutionFunction(), TSSetSolutionFunction()
    1153: @*/
    1154: PetscErrorCode  TSSetForcingFunction(TS ts,TSForcingFunction func,void *ctx)
    1155: {
    1157:   DM             dm;

    1161:   TSGetDM(ts,&dm);
    1162:   DMTSSetForcingFunction(dm,func,ctx);
    1163:   return(0);
    1164: }

    1166: /*@C
    1167:    TSSetRHSJacobian - Sets the function to compute the Jacobian of G,
    1168:    where U_t = G(U,t), as well as the location to store the matrix.

    1170:    Logically Collective on TS

    1172:    Input Parameters:
    1173: +  ts  - the TS context obtained from TSCreate()
    1174: .  Amat - (approximate) Jacobian matrix
    1175: .  Pmat - matrix from which preconditioner is to be constructed (usually the same as Amat)
    1176: .  f   - the Jacobian evaluation routine
    1177: -  ctx - [optional] user-defined context for private data for the
    1178:          Jacobian evaluation routine (may be NULL)

    1180:    Calling sequence of f:
    1181: $     PetscErrorCode f(TS ts,PetscReal t,Vec u,Mat A,Mat B,void *ctx);

    1183: +  t - current timestep
    1184: .  u - input vector
    1185: .  Amat - (approximate) Jacobian matrix
    1186: .  Pmat - matrix from which preconditioner is to be constructed (usually the same as Amat)
    1187: -  ctx - [optional] user-defined context for matrix evaluation routine

    1189:    Notes:
    1190:    You must set all the diagonal entries of the matrices, if they are zero you must still set them with a zero value

    1192:    The TS solver may modify the nonzero structure and the entries of the matrices Amat and Pmat between the calls to f()
    1193:    You should not assume the values are the same in the next call to f() as you set them in the previous call.

    1195:    Level: beginner

    1197: .seealso: SNESComputeJacobianDefaultColor(), TSSetRHSFunction(), TSRHSJacobianSetReuse(), TSSetIJacobian()

    1199: @*/
    1200: PetscErrorCode  TSSetRHSJacobian(TS ts,Mat Amat,Mat Pmat,TSRHSJacobian f,void *ctx)
    1201: {
    1203:   SNES           snes;
    1204:   DM             dm;
    1205:   TSIJacobian    ijacobian;

    1214:   TSGetDM(ts,&dm);
    1215:   DMTSSetRHSJacobian(dm,f,ctx);
    1216:   DMTSGetIJacobian(dm,&ijacobian,NULL);
    1217:   TSGetSNES(ts,&snes);
    1218:   if (!ijacobian) {
    1219:     SNESSetJacobian(snes,Amat,Pmat,SNESTSFormJacobian,ts);
    1220:   }
    1221:   if (Amat) {
    1222:     PetscObjectReference((PetscObject)Amat);
    1223:     MatDestroy(&ts->Arhs);
    1224:     ts->Arhs = Amat;
    1225:   }
    1226:   if (Pmat) {
    1227:     PetscObjectReference((PetscObject)Pmat);
    1228:     MatDestroy(&ts->Brhs);
    1229:     ts->Brhs = Pmat;
    1230:   }
    1231:   return(0);
    1232: }

    1234: /*@C
    1235:    TSSetIFunction - Set the function to compute F(t,U,U_t) where F() = 0 is the DAE to be solved.

    1237:    Logically Collective on TS

    1239:    Input Parameters:
    1240: +  ts  - the TS context obtained from TSCreate()
    1241: .  r   - vector to hold the residual (or NULL to have it created internally)
    1242: .  f   - the function evaluation routine
    1243: -  ctx - user-defined context for private data for the function evaluation routine (may be NULL)

    1245:    Calling sequence of f:
    1246: $     PetscErrorCode f(TS ts,PetscReal t,Vec u,Vec u_t,Vec F,ctx);

    1248: +  t   - time at step/stage being solved
    1249: .  u   - state vector
    1250: .  u_t - time derivative of state vector
    1251: .  F   - function vector
    1252: -  ctx - [optional] user-defined context for matrix evaluation routine

    1254:    Important:
    1255:    The user MUST call either this routine or TSSetRHSFunction() to define the ODE.  When solving DAEs you must use this function.

    1257:    Level: beginner

    1259: .seealso: TSSetRHSJacobian(), TSSetRHSFunction(), TSSetIJacobian()
    1260: @*/
    1261: PetscErrorCode  TSSetIFunction(TS ts,Vec r,TSIFunction f,void *ctx)
    1262: {
    1264:   SNES           snes;
    1265:   Vec            ralloc = NULL;
    1266:   DM             dm;

    1272:   TSGetDM(ts,&dm);
    1273:   DMTSSetIFunction(dm,f,ctx);

    1275:   TSGetSNES(ts,&snes);
    1276:   if (!r && !ts->dm && ts->vec_sol) {
    1277:     VecDuplicate(ts->vec_sol,&ralloc);
    1278:     r  = ralloc;
    1279:   }
    1280:   SNESSetFunction(snes,r,SNESTSFormFunction,ts);
    1281:   VecDestroy(&ralloc);
    1282:   return(0);
    1283: }

    1285: /*@C
    1286:    TSGetIFunction - Returns the vector where the implicit residual is stored and the function/context to compute it.

    1288:    Not Collective

    1290:    Input Parameter:
    1291: .  ts - the TS context

    1293:    Output Parameters:
    1294: +  r - vector to hold residual (or NULL)
    1295: .  func - the function to compute residual (or NULL)
    1296: -  ctx - the function context (or NULL)

    1298:    Level: advanced

    1300: .seealso: TSSetIFunction(), SNESGetFunction()
    1301: @*/
    1302: PetscErrorCode TSGetIFunction(TS ts,Vec *r,TSIFunction *func,void **ctx)
    1303: {
    1305:   SNES           snes;
    1306:   DM             dm;

    1310:   TSGetSNES(ts,&snes);
    1311:   SNESGetFunction(snes,r,NULL,NULL);
    1312:   TSGetDM(ts,&dm);
    1313:   DMTSGetIFunction(dm,func,ctx);
    1314:   return(0);
    1315: }

    1317: /*@C
    1318:    TSGetRHSFunction - Returns the vector where the right hand side is stored and the function/context to compute it.

    1320:    Not Collective

    1322:    Input Parameter:
    1323: .  ts - the TS context

    1325:    Output Parameters:
    1326: +  r - vector to hold computed right hand side (or NULL)
    1327: .  func - the function to compute right hand side (or NULL)
    1328: -  ctx - the function context (or NULL)

    1330:    Level: advanced

    1332: .seealso: TSSetRHSFunction(), SNESGetFunction()
    1333: @*/
    1334: PetscErrorCode TSGetRHSFunction(TS ts,Vec *r,TSRHSFunction *func,void **ctx)
    1335: {
    1337:   SNES           snes;
    1338:   DM             dm;

    1342:   TSGetSNES(ts,&snes);
    1343:   SNESGetFunction(snes,r,NULL,NULL);
    1344:   TSGetDM(ts,&dm);
    1345:   DMTSGetRHSFunction(dm,func,ctx);
    1346:   return(0);
    1347: }

    1349: /*@C
    1350:    TSSetIJacobian - Set the function to compute the matrix dF/dU + a*dF/dU_t where F(t,U,U_t) is the function
    1351:         provided with TSSetIFunction().

    1353:    Logically Collective on TS

    1355:    Input Parameters:
    1356: +  ts  - the TS context obtained from TSCreate()
    1357: .  Amat - (approximate) Jacobian matrix
    1358: .  Pmat - matrix used to compute preconditioner (usually the same as Amat)
    1359: .  f   - the Jacobian evaluation routine
    1360: -  ctx - user-defined context for private data for the Jacobian evaluation routine (may be NULL)

    1362:    Calling sequence of f:
    1363: $    PetscErrorCode f(TS ts,PetscReal t,Vec U,Vec U_t,PetscReal a,Mat Amat,Mat Pmat,void *ctx);

    1365: +  t    - time at step/stage being solved
    1366: .  U    - state vector
    1367: .  U_t  - time derivative of state vector
    1368: .  a    - shift
    1369: .  Amat - (approximate) Jacobian of F(t,U,W+a*U), equivalent to dF/dU + a*dF/dU_t
    1370: .  Pmat - matrix used for constructing preconditioner, usually the same as Amat
    1371: -  ctx  - [optional] user-defined context for matrix evaluation routine

    1373:    Notes:
    1374:    The matrices Amat and Pmat are exactly the matrices that are used by SNES for the nonlinear solve.

    1376:    If you know the operator Amat has a null space you can use MatSetNullSpace() and MatSetTransposeNullSpace() to supply the null
    1377:    space to Amat and the KSP solvers will automatically use that null space as needed during the solution process.

    1379:    The matrix dF/dU + a*dF/dU_t you provide turns out to be
    1380:    the Jacobian of F(t,U,W+a*U) where F(t,U,U_t) = 0 is the DAE to be solved.
    1381:    The time integrator internally approximates U_t by W+a*U where the positive "shift"
    1382:    a and vector W depend on the integration method, step size, and past states. For example with
    1383:    the backward Euler method a = 1/dt and W = -a*U(previous timestep) so
    1384:    W + a*U = a*(U - U(previous timestep)) = (U - U(previous timestep))/dt

    1386:    You must set all the diagonal entries of the matrices, if they are zero you must still set them with a zero value

    1388:    The TS solver may modify the nonzero structure and the entries of the matrices Amat and Pmat between the calls to f()
    1389:    You should not assume the values are the same in the next call to f() as you set them in the previous call.

    1391:    Level: beginner

    1393: .seealso: TSSetIFunction(), TSSetRHSJacobian(), SNESComputeJacobianDefaultColor(), SNESComputeJacobianDefault(), TSSetRHSFunction()

    1395: @*/
    1396: PetscErrorCode  TSSetIJacobian(TS ts,Mat Amat,Mat Pmat,TSIJacobian f,void *ctx)
    1397: {
    1399:   SNES           snes;
    1400:   DM             dm;

    1409:   TSGetDM(ts,&dm);
    1410:   DMTSSetIJacobian(dm,f,ctx);

    1412:   TSGetSNES(ts,&snes);
    1413:   SNESSetJacobian(snes,Amat,Pmat,SNESTSFormJacobian,ts);
    1414:   return(0);
    1415: }

    1417: /*@
    1418:    TSRHSJacobianSetReuse - restore RHS Jacobian before re-evaluating.  Without this flag, TS will change the sign and
    1419:    shift the RHS Jacobian for a finite-time-step implicit solve, in which case the user function will need to recompute
    1420:    the entire Jacobian.  The reuse flag must be set if the evaluation function will assume that the matrix entries have
    1421:    not been changed by the TS.

    1423:    Logically Collective

    1425:    Input Parameters:
    1426: +  ts - TS context obtained from TSCreate()
    1427: -  reuse - PETSC_TRUE if the RHS Jacobian

    1429:    Level: intermediate

    1431: .seealso: TSSetRHSJacobian(), TSComputeRHSJacobianConstant()
    1432: @*/
    1433: PetscErrorCode TSRHSJacobianSetReuse(TS ts,PetscBool reuse)
    1434: {
    1436:   ts->rhsjacobian.reuse = reuse;
    1437:   return(0);
    1438: }

    1440: /*@C
    1441:    TSSetI2Function - Set the function to compute F(t,U,U_t,U_tt) where F = 0 is the DAE to be solved.

    1443:    Logically Collective on TS

    1445:    Input Parameters:
    1446: +  ts  - the TS context obtained from TSCreate()
    1447: .  F   - vector to hold the residual (or NULL to have it created internally)
    1448: .  fun - the function evaluation routine
    1449: -  ctx - user-defined context for private data for the function evaluation routine (may be NULL)

    1451:    Calling sequence of fun:
    1452: $     PetscErrorCode fun(TS ts,PetscReal t,Vec U,Vec U_t,Vec U_tt,Vec F,ctx);

    1454: +  t    - time at step/stage being solved
    1455: .  U    - state vector
    1456: .  U_t  - time derivative of state vector
    1457: .  U_tt - second time derivative of state vector
    1458: .  F    - function vector
    1459: -  ctx  - [optional] user-defined context for matrix evaluation routine (may be NULL)

    1461:    Level: beginner

    1463: .seealso: TSSetI2Jacobian(), TSSetIFunction(), TSCreate(), TSSetRHSFunction()
    1464: @*/
    1465: PetscErrorCode TSSetI2Function(TS ts,Vec F,TSI2Function fun,void *ctx)
    1466: {
    1467:   DM             dm;

    1473:   TSSetIFunction(ts,F,NULL,NULL);
    1474:   TSGetDM(ts,&dm);
    1475:   DMTSSetI2Function(dm,fun,ctx);
    1476:   return(0);
    1477: }

    1479: /*@C
    1480:   TSGetI2Function - Returns the vector where the implicit residual is stored and the function/context to compute it.

    1482:   Not Collective

    1484:   Input Parameter:
    1485: . ts - the TS context

    1487:   Output Parameters:
    1488: + r - vector to hold residual (or NULL)
    1489: . fun - the function to compute residual (or NULL)
    1490: - ctx - the function context (or NULL)

    1492:   Level: advanced

    1494: .seealso: TSSetIFunction(), SNESGetFunction(), TSCreate()
    1495: @*/
    1496: PetscErrorCode TSGetI2Function(TS ts,Vec *r,TSI2Function *fun,void **ctx)
    1497: {
    1499:   SNES           snes;
    1500:   DM             dm;

    1504:   TSGetSNES(ts,&snes);
    1505:   SNESGetFunction(snes,r,NULL,NULL);
    1506:   TSGetDM(ts,&dm);
    1507:   DMTSGetI2Function(dm,fun,ctx);
    1508:   return(0);
    1509: }

    1511: /*@C
    1512:    TSSetI2Jacobian - Set the function to compute the matrix dF/dU + v*dF/dU_t  + a*dF/dU_tt
    1513:         where F(t,U,U_t,U_tt) is the function you provided with TSSetI2Function().

    1515:    Logically Collective on TS

    1517:    Input Parameters:
    1518: +  ts  - the TS context obtained from TSCreate()
    1519: .  J   - Jacobian matrix
    1520: .  P   - preconditioning matrix for J (may be same as J)
    1521: .  jac - the Jacobian evaluation routine
    1522: -  ctx - user-defined context for private data for the Jacobian evaluation routine (may be NULL)

    1524:    Calling sequence of jac:
    1525: $    PetscErrorCode jac(TS ts,PetscReal t,Vec U,Vec U_t,Vec U_tt,PetscReal v,PetscReal a,Mat J,Mat P,void *ctx);

    1527: +  t    - time at step/stage being solved
    1528: .  U    - state vector
    1529: .  U_t  - time derivative of state vector
    1530: .  U_tt - second time derivative of state vector
    1531: .  v    - shift for U_t
    1532: .  a    - shift for U_tt
    1533: .  J    - Jacobian of G(U) = F(t,U,W+v*U,W'+a*U), equivalent to dF/dU + v*dF/dU_t  + a*dF/dU_tt
    1534: .  P    - preconditioning matrix for J, may be same as J
    1535: -  ctx  - [optional] user-defined context for matrix evaluation routine

    1537:    Notes:
    1538:    The matrices J and P are exactly the matrices that are used by SNES for the nonlinear solve.

    1540:    The matrix dF/dU + v*dF/dU_t + a*dF/dU_tt you provide turns out to be
    1541:    the Jacobian of G(U) = F(t,U,W+v*U,W'+a*U) where F(t,U,U_t,U_tt) = 0 is the DAE to be solved.
    1542:    The time integrator internally approximates U_t by W+v*U and U_tt by W'+a*U  where the positive "shift"
    1543:    parameters 'v' and 'a' and vectors W, W' depend on the integration method, step size, and past states.

    1545:    Level: beginner

    1547: .seealso: TSSetI2Function(), TSGetI2Jacobian()
    1548: @*/
    1549: PetscErrorCode TSSetI2Jacobian(TS ts,Mat J,Mat P,TSI2Jacobian jac,void *ctx)
    1550: {
    1551:   DM             dm;

    1558:   TSSetIJacobian(ts,J,P,NULL,NULL);
    1559:   TSGetDM(ts,&dm);
    1560:   DMTSSetI2Jacobian(dm,jac,ctx);
    1561:   return(0);
    1562: }

    1564: /*@C
    1565:   TSGetI2Jacobian - Returns the implicit Jacobian at the present timestep.

    1567:   Not Collective, but parallel objects are returned if TS is parallel

    1569:   Input Parameter:
    1570: . ts  - The TS context obtained from TSCreate()

    1572:   Output Parameters:
    1573: + J  - The (approximate) Jacobian of F(t,U,U_t,U_tt)
    1574: . P - The matrix from which the preconditioner is constructed, often the same as J
    1575: . jac - The function to compute the Jacobian matrices
    1576: - ctx - User-defined context for Jacobian evaluation routine

    1578:   Notes:
    1579:     You can pass in NULL for any return argument you do not need.

    1581:   Level: advanced

    1583: .seealso: TSGetTimeStep(), TSGetMatrices(), TSGetTime(), TSGetStepNumber(), TSSetI2Jacobian(), TSGetI2Function(), TSCreate()

    1585: @*/
    1586: PetscErrorCode  TSGetI2Jacobian(TS ts,Mat *J,Mat *P,TSI2Jacobian *jac,void **ctx)
    1587: {
    1589:   SNES           snes;
    1590:   DM             dm;

    1593:   TSGetSNES(ts,&snes);
    1594:   SNESSetUpMatrices(snes);
    1595:   SNESGetJacobian(snes,J,P,NULL,NULL);
    1596:   TSGetDM(ts,&dm);
    1597:   DMTSGetI2Jacobian(dm,jac,ctx);
    1598:   return(0);
    1599: }

    1601: /*@
    1602:   TSComputeI2Function - Evaluates the DAE residual written in implicit form F(t,U,U_t,U_tt) = 0

    1604:   Collective on TS

    1606:   Input Parameters:
    1607: + ts - the TS context
    1608: . t - current time
    1609: . U - state vector
    1610: . V - time derivative of state vector (U_t)
    1611: - A - second time derivative of state vector (U_tt)

    1613:   Output Parameter:
    1614: . F - the residual vector

    1616:   Note:
    1617:   Most users should not need to explicitly call this routine, as it
    1618:   is used internally within the nonlinear solvers.

    1620:   Level: developer

    1622: .seealso: TSSetI2Function(), TSGetI2Function()
    1623: @*/
    1624: PetscErrorCode TSComputeI2Function(TS ts,PetscReal t,Vec U,Vec V,Vec A,Vec F)
    1625: {
    1626:   DM             dm;
    1627:   TSI2Function   I2Function;
    1628:   void           *ctx;
    1629:   TSRHSFunction  rhsfunction;

    1639:   TSGetDM(ts,&dm);
    1640:   DMTSGetI2Function(dm,&I2Function,&ctx);
    1641:   DMTSGetRHSFunction(dm,&rhsfunction,NULL);

    1643:   if (!I2Function) {
    1644:     TSComputeIFunction(ts,t,U,A,F,PETSC_FALSE);
    1645:     return(0);
    1646:   }

    1648:   PetscLogEventBegin(TS_FunctionEval,ts,U,V,F);

    1650:   PetscStackPush("TS user implicit function");
    1651:   I2Function(ts,t,U,V,A,F,ctx);
    1652:   PetscStackPop;

    1654:   if (rhsfunction) {
    1655:     Vec Frhs;
    1656:     TSGetRHSVec_Private(ts,&Frhs);
    1657:     TSComputeRHSFunction(ts,t,U,Frhs);
    1658:     VecAXPY(F,-1,Frhs);
    1659:   }

    1661:   PetscLogEventEnd(TS_FunctionEval,ts,U,V,F);
    1662:   return(0);
    1663: }

    1665: /*@
    1666:   TSComputeI2Jacobian - Evaluates the Jacobian of the DAE

    1668:   Collective on TS

    1670:   Input Parameters:
    1671: + ts - the TS context
    1672: . t - current timestep
    1673: . U - state vector
    1674: . V - time derivative of state vector
    1675: . A - second time derivative of state vector
    1676: . shiftV - shift to apply, see note below
    1677: - shiftA - shift to apply, see note below

    1679:   Output Parameters:
    1680: + J - Jacobian matrix
    1681: - P - optional preconditioning matrix

    1683:   Notes:
    1684:   If F(t,U,V,A)=0 is the DAE, the required Jacobian is

    1686:   dF/dU + shiftV*dF/dV + shiftA*dF/dA

    1688:   Most users should not need to explicitly call this routine, as it
    1689:   is used internally within the nonlinear solvers.

    1691:   Level: developer

    1693: .seealso:  TSSetI2Jacobian()
    1694: @*/
    1695: PetscErrorCode TSComputeI2Jacobian(TS ts,PetscReal t,Vec U,Vec V,Vec A,PetscReal shiftV,PetscReal shiftA,Mat J,Mat P)
    1696: {
    1697:   DM             dm;
    1698:   TSI2Jacobian   I2Jacobian;
    1699:   void           *ctx;
    1700:   TSRHSJacobian  rhsjacobian;

    1711:   TSGetDM(ts,&dm);
    1712:   DMTSGetI2Jacobian(dm,&I2Jacobian,&ctx);
    1713:   DMTSGetRHSJacobian(dm,&rhsjacobian,NULL);

    1715:   if (!I2Jacobian) {
    1716:     TSComputeIJacobian(ts,t,U,A,shiftA,J,P,PETSC_FALSE);
    1717:     return(0);
    1718:   }

    1720:   PetscLogEventBegin(TS_JacobianEval,ts,U,J,P);

    1722:   PetscStackPush("TS user implicit Jacobian");
    1723:   I2Jacobian(ts,t,U,V,A,shiftV,shiftA,J,P,ctx);
    1724:   PetscStackPop;

    1726:   if (rhsjacobian) {
    1727:     Mat Jrhs,Prhs;
    1728:     TSGetRHSMats_Private(ts,&Jrhs,&Prhs);
    1729:     TSComputeRHSJacobian(ts,t,U,Jrhs,Prhs);
    1730:     MatAXPY(J,-1,Jrhs,ts->axpy_pattern);
    1731:     if (P != J) {MatAXPY(P,-1,Prhs,ts->axpy_pattern);}
    1732:   }

    1734:   PetscLogEventEnd(TS_JacobianEval,ts,U,J,P);
    1735:   return(0);
    1736: }

    1738: /*@C
    1739:    TSSetTransientVariable - sets function to transform from state to transient variables

    1741:    Logically Collective

    1743:    Input Parameters:
    1744: +  ts - time stepping context on which to change the transient variable
    1745: .  tvar - a function that transforms to transient variables
    1746: -  ctx - a context for tvar

    1748:     Calling sequence of tvar:
    1749: $     PetscErrorCode tvar(TS ts,Vec p,Vec c,void *ctx);

    1751: +   ts - timestep context
    1752: .   p - input vector (primative form)
    1753: .   c - output vector, transient variables (conservative form)
    1754: -   ctx - [optional] user-defined function context

    1756:    Level: advanced

    1758:    Notes:
    1759:    This is typically used to transform from primitive to conservative variables so that a time integrator (e.g., TSBDF)
    1760:    can be conservative.  In this context, primitive variables P are used to model the state (e.g., because they lead to
    1761:    well-conditioned formulations even in limiting cases such as low-Mach or zero porosity).  The transient variable is
    1762:    C(P), specified by calling this function.  An IFunction thus receives arguments (P, Cdot) and the IJacobian must be
    1763:    evaluated via the chain rule, as in

    1765:      dF/dP + shift * dF/dCdot dC/dP.

    1767: .seealso: DMTSSetTransientVariable(), DMTSGetTransientVariable(), TSSetIFunction(), TSSetIJacobian()
    1768: @*/
    1769: PetscErrorCode TSSetTransientVariable(TS ts,TSTransientVariable tvar,void *ctx)
    1770: {
    1772:   DM             dm;

    1776:   TSGetDM(ts,&dm);
    1777:   DMTSSetTransientVariable(dm,tvar,ctx);
    1778:   return(0);
    1779: }

    1781: /*@
    1782:    TSComputeTransientVariable - transforms state (primitive) variables to transient (conservative) variables

    1784:    Logically Collective

    1786:    Input Parameters:
    1787: +  ts - TS on which to compute
    1788: -  U - state vector to be transformed to transient variables

    1790:    Output Parameters:
    1791: .  C - transient (conservative) variable

    1793:    Developer Notes:
    1794:    If DMTSSetTransientVariable() has not been called, then C is not modified in this routine and C=NULL is allowed.
    1795:    This makes it safe to call without a guard.  One can use TSHasTransientVariable() to check if transient variables are
    1796:    being used.

    1798:    Level: developer

    1800: .seealso: DMTSSetTransientVariable(), TSComputeIFunction(), TSComputeIJacobian()
    1801: @*/
    1802: PetscErrorCode TSComputeTransientVariable(TS ts,Vec U,Vec C)
    1803: {
    1805:   DM             dm;
    1806:   DMTS           dmts;

    1811:   TSGetDM(ts,&dm);
    1812:   DMGetDMTS(dm,&dmts);
    1813:   if (dmts->ops->transientvar) {
    1815:     (*dmts->ops->transientvar)(ts,U,C,dmts->transientvarctx);
    1816:   }
    1817:   return(0);
    1818: }

    1820: /*@
    1821:    TSHasTransientVariable - determine whether transient variables have been set

    1823:    Logically Collective

    1825:    Input Parameters:
    1826: .  ts - TS on which to compute

    1828:    Output Parameters:
    1829: .  has - PETSC_TRUE if transient variables have been set

    1831:    Level: developer

    1833: .seealso: DMTSSetTransientVariable(), TSComputeTransientVariable()
    1834: @*/
    1835: PetscErrorCode TSHasTransientVariable(TS ts,PetscBool *has)
    1836: {
    1838:   DM             dm;
    1839:   DMTS           dmts;

    1843:   TSGetDM(ts,&dm);
    1844:   DMGetDMTS(dm,&dmts);
    1845:   *has = dmts->ops->transientvar ? PETSC_TRUE : PETSC_FALSE;
    1846:   return(0);
    1847: }

    1849: /*@
    1850:    TS2SetSolution - Sets the initial solution and time derivative vectors
    1851:    for use by the TS routines handling second order equations.

    1853:    Logically Collective on TS

    1855:    Input Parameters:
    1856: +  ts - the TS context obtained from TSCreate()
    1857: .  u - the solution vector
    1858: -  v - the time derivative vector

    1860:    Level: beginner

    1862: @*/
    1863: PetscErrorCode  TS2SetSolution(TS ts,Vec u,Vec v)
    1864: {

    1871:   TSSetSolution(ts,u);
    1872:   PetscObjectReference((PetscObject)v);
    1873:   VecDestroy(&ts->vec_dot);
    1874:   ts->vec_dot = v;
    1875:   return(0);
    1876: }

    1878: /*@
    1879:    TS2GetSolution - Returns the solution and time derivative at the present timestep
    1880:    for second order equations. It is valid to call this routine inside the function
    1881:    that you are evaluating in order to move to the new timestep. This vector not
    1882:    changed until the solution at the next timestep has been calculated.

    1884:    Not Collective, but Vec returned is parallel if TS is parallel

    1886:    Input Parameter:
    1887: .  ts - the TS context obtained from TSCreate()

    1889:    Output Parameters:
    1890: +  u - the vector containing the solution
    1891: -  v - the vector containing the time derivative

    1893:    Level: intermediate

    1895: .seealso: TS2SetSolution(), TSGetTimeStep(), TSGetTime()

    1897: @*/
    1898: PetscErrorCode  TS2GetSolution(TS ts,Vec *u,Vec *v)
    1899: {
    1904:   if (u) *u = ts->vec_sol;
    1905:   if (v) *v = ts->vec_dot;
    1906:   return(0);
    1907: }

    1909: /*@C
    1910:   TSLoad - Loads a KSP that has been stored in binary  with KSPView().

    1912:   Collective on PetscViewer

    1914:   Input Parameters:
    1915: + newdm - the newly loaded TS, this needs to have been created with TSCreate() or
    1916:            some related function before a call to TSLoad().
    1917: - viewer - binary file viewer, obtained from PetscViewerBinaryOpen()

    1919:    Level: intermediate

    1921:   Notes:
    1922:    The type is determined by the data in the file, any type set into the TS before this call is ignored.

    1924:   Notes for advanced users:
    1925:   Most users should not need to know the details of the binary storage
    1926:   format, since TSLoad() and TSView() completely hide these details.
    1927:   But for anyone who's interested, the standard binary matrix storage
    1928:   format is
    1929: .vb
    1930:      has not yet been determined
    1931: .ve

    1933: .seealso: PetscViewerBinaryOpen(), TSView(), MatLoad(), VecLoad()
    1934: @*/
    1935: PetscErrorCode  TSLoad(TS ts, PetscViewer viewer)
    1936: {
    1938:   PetscBool      isbinary;
    1939:   PetscInt       classid;
    1940:   char           type[256];
    1941:   DMTS           sdm;
    1942:   DM             dm;

    1947:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
    1948:   if (!isbinary) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid viewer; open viewer with PetscViewerBinaryOpen()");

    1950:   PetscViewerBinaryRead(viewer,&classid,1,NULL,PETSC_INT);
    1951:   if (classid != TS_FILE_CLASSID) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Not TS next in file");
    1952:   PetscViewerBinaryRead(viewer,type,256,NULL,PETSC_CHAR);
    1953:   TSSetType(ts, type);
    1954:   if (ts->ops->load) {
    1955:     (*ts->ops->load)(ts,viewer);
    1956:   }
    1957:   DMCreate(PetscObjectComm((PetscObject)ts),&dm);
    1958:   DMLoad(dm,viewer);
    1959:   TSSetDM(ts,dm);
    1960:   DMCreateGlobalVector(ts->dm,&ts->vec_sol);
    1961:   VecLoad(ts->vec_sol,viewer);
    1962:   DMGetDMTS(ts->dm,&sdm);
    1963:   DMTSLoad(sdm,viewer);
    1964:   return(0);
    1965: }

    1967: #include <petscdraw.h>
    1968: #if defined(PETSC_HAVE_SAWS)
    1969: #include <petscviewersaws.h>
    1970: #endif

    1972: /*@C
    1973:    TSViewFromOptions - View from Options

    1975:    Collective on TS

    1977:    Input Parameters:
    1978: +  A - the application ordering context
    1979: .  obj - Optional object
    1980: -  name - command line option

    1982:    Level: intermediate
    1983: .seealso:  TS, TSView, PetscObjectViewFromOptions(), TSCreate()
    1984: @*/
    1985: PetscErrorCode  TSViewFromOptions(TS A,PetscObject obj,const char name[])
    1986: {

    1991:   PetscObjectViewFromOptions((PetscObject)A,obj,name);
    1992:   return(0);
    1993: }

    1995: /*@C
    1996:     TSView - Prints the TS data structure.

    1998:     Collective on TS

    2000:     Input Parameters:
    2001: +   ts - the TS context obtained from TSCreate()
    2002: -   viewer - visualization context

    2004:     Options Database Key:
    2005: .   -ts_view - calls TSView() at end of TSStep()

    2007:     Notes:
    2008:     The available visualization contexts include
    2009: +     PETSC_VIEWER_STDOUT_SELF - standard output (default)
    2010: -     PETSC_VIEWER_STDOUT_WORLD - synchronized standard
    2011:          output where only the first processor opens
    2012:          the file.  All other processors send their
    2013:          data to the first processor to print.

    2015:     The user can open an alternative visualization context with
    2016:     PetscViewerASCIIOpen() - output to a specified file.

    2018:     In the debugger you can do "call TSView(ts,0)" to display the TS solver. (The same holds for any PETSc object viewer).

    2020:     Level: beginner

    2022: .seealso: PetscViewerASCIIOpen()
    2023: @*/
    2024: PetscErrorCode  TSView(TS ts,PetscViewer viewer)
    2025: {
    2027:   TSType         type;
    2028:   PetscBool      iascii,isstring,isundials,isbinary,isdraw;
    2029:   DMTS           sdm;
    2030: #if defined(PETSC_HAVE_SAWS)
    2031:   PetscBool      issaws;
    2032: #endif

    2036:   if (!viewer) {
    2037:     PetscViewerASCIIGetStdout(PetscObjectComm((PetscObject)ts),&viewer);
    2038:   }

    2042:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
    2043:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSTRING,&isstring);
    2044:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
    2045:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
    2046: #if defined(PETSC_HAVE_SAWS)
    2047:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSAWS,&issaws);
    2048: #endif
    2049:   if (iascii) {
    2050:     PetscObjectPrintClassNamePrefixType((PetscObject)ts,viewer);
    2051:     if (ts->ops->view) {
    2052:       PetscViewerASCIIPushTab(viewer);
    2053:       (*ts->ops->view)(ts,viewer);
    2054:       PetscViewerASCIIPopTab(viewer);
    2055:     }
    2056:     if (ts->max_steps < PETSC_MAX_INT) {
    2057:       PetscViewerASCIIPrintf(viewer,"  maximum steps=%D\n",ts->max_steps);
    2058:     }
    2059:     if (ts->max_time < PETSC_MAX_REAL) {
    2060:       PetscViewerASCIIPrintf(viewer,"  maximum time=%g\n",(double)ts->max_time);
    2061:     }
    2062:     if (ts->ifuncs) {
    2063:       PetscViewerASCIIPrintf(viewer,"  total number of I function evaluations=%D\n",ts->ifuncs);
    2064:     }
    2065:     if (ts->ijacs) {
    2066:       PetscViewerASCIIPrintf(viewer,"  total number of I Jacobian evaluations=%D\n",ts->ijacs);
    2067:     }
    2068:     if (ts->rhsfuncs) {
    2069:       PetscViewerASCIIPrintf(viewer,"  total number of RHS function evaluations=%D\n",ts->rhsfuncs);
    2070:     }
    2071:     if (ts->rhsjacs) {
    2072:       PetscViewerASCIIPrintf(viewer,"  total number of RHS Jacobian evaluations=%D\n",ts->rhsjacs);
    2073:     }
    2074:     if (ts->usessnes) {
    2075:       PetscBool lin;
    2076:       if (ts->problem_type == TS_NONLINEAR) {
    2077:         PetscViewerASCIIPrintf(viewer,"  total number of nonlinear solver iterations=%D\n",ts->snes_its);
    2078:       }
    2079:       PetscViewerASCIIPrintf(viewer,"  total number of linear solver iterations=%D\n",ts->ksp_its);
    2080:       PetscObjectTypeCompareAny((PetscObject)ts->snes,&lin,SNESKSPONLY,SNESKSPTRANSPOSEONLY,"");
    2081:       PetscViewerASCIIPrintf(viewer,"  total number of %slinear solve failures=%D\n",lin ? "" : "non",ts->num_snes_failures);
    2082:     }
    2083:     PetscViewerASCIIPrintf(viewer,"  total number of rejected steps=%D\n",ts->reject);
    2084:     if (ts->vrtol) {
    2085:       PetscViewerASCIIPrintf(viewer,"  using vector of relative error tolerances, ");
    2086:     } else {
    2087:       PetscViewerASCIIPrintf(viewer,"  using relative error tolerance of %g, ",(double)ts->rtol);
    2088:     }
    2089:     if (ts->vatol) {
    2090:       PetscViewerASCIIPrintf(viewer,"  using vector of absolute error tolerances\n");
    2091:     } else {
    2092:       PetscViewerASCIIPrintf(viewer,"  using absolute error tolerance of %g\n",(double)ts->atol);
    2093:     }
    2094:     PetscViewerASCIIPushTab(viewer);
    2095:     TSAdaptView(ts->adapt,viewer);
    2096:     PetscViewerASCIIPopTab(viewer);
    2097:   } else if (isstring) {
    2098:     TSGetType(ts,&type);
    2099:     PetscViewerStringSPrintf(viewer," TSType: %-7.7s",type);
    2100:     if (ts->ops->view) {(*ts->ops->view)(ts,viewer);}
    2101:   } else if (isbinary) {
    2102:     PetscInt    classid = TS_FILE_CLASSID;
    2103:     MPI_Comm    comm;
    2104:     PetscMPIInt rank;
    2105:     char        type[256];

    2107:     PetscObjectGetComm((PetscObject)ts,&comm);
    2108:     MPI_Comm_rank(comm,&rank);
    2109:     if (rank == 0) {
    2110:       PetscViewerBinaryWrite(viewer,&classid,1,PETSC_INT);
    2111:       PetscStrncpy(type,((PetscObject)ts)->type_name,256);
    2112:       PetscViewerBinaryWrite(viewer,type,256,PETSC_CHAR);
    2113:     }
    2114:     if (ts->ops->view) {
    2115:       (*ts->ops->view)(ts,viewer);
    2116:     }
    2117:     if (ts->adapt) {TSAdaptView(ts->adapt,viewer);}
    2118:     DMView(ts->dm,viewer);
    2119:     VecView(ts->vec_sol,viewer);
    2120:     DMGetDMTS(ts->dm,&sdm);
    2121:     DMTSView(sdm,viewer);
    2122:   } else if (isdraw) {
    2123:     PetscDraw draw;
    2124:     char      str[36];
    2125:     PetscReal x,y,bottom,h;

    2127:     PetscViewerDrawGetDraw(viewer,0,&draw);
    2128:     PetscDrawGetCurrentPoint(draw,&x,&y);
    2129:     PetscStrcpy(str,"TS: ");
    2130:     PetscStrcat(str,((PetscObject)ts)->type_name);
    2131:     PetscDrawStringBoxed(draw,x,y,PETSC_DRAW_BLACK,PETSC_DRAW_BLACK,str,NULL,&h);
    2132:     bottom = y - h;
    2133:     PetscDrawPushCurrentPoint(draw,x,bottom);
    2134:     if (ts->ops->view) {
    2135:       (*ts->ops->view)(ts,viewer);
    2136:     }
    2137:     if (ts->adapt) {TSAdaptView(ts->adapt,viewer);}
    2138:     if (ts->snes)  {SNESView(ts->snes,viewer);}
    2139:     PetscDrawPopCurrentPoint(draw);
    2140: #if defined(PETSC_HAVE_SAWS)
    2141:   } else if (issaws) {
    2142:     PetscMPIInt rank;
    2143:     const char  *name;

    2145:     PetscObjectGetName((PetscObject)ts,&name);
    2146:     MPI_Comm_rank(PETSC_COMM_WORLD,&rank);
    2147:     if (!((PetscObject)ts)->amsmem && rank == 0) {
    2148:       char       dir[1024];

    2150:       PetscObjectViewSAWs((PetscObject)ts,viewer);
    2151:       PetscSNPrintf(dir,1024,"/PETSc/Objects/%s/time_step",name);
    2152:       PetscStackCallSAWs(SAWs_Register,(dir,&ts->steps,1,SAWs_READ,SAWs_INT));
    2153:       PetscSNPrintf(dir,1024,"/PETSc/Objects/%s/time",name);
    2154:       PetscStackCallSAWs(SAWs_Register,(dir,&ts->ptime,1,SAWs_READ,SAWs_DOUBLE));
    2155:     }
    2156:     if (ts->ops->view) {
    2157:       (*ts->ops->view)(ts,viewer);
    2158:     }
    2159: #endif
    2160:   }
    2161:   if (ts->snes && ts->usessnes)  {
    2162:     PetscViewerASCIIPushTab(viewer);
    2163:     SNESView(ts->snes,viewer);
    2164:     PetscViewerASCIIPopTab(viewer);
    2165:   }
    2166:   DMGetDMTS(ts->dm,&sdm);
    2167:   DMTSView(sdm,viewer);

    2169:   PetscViewerASCIIPushTab(viewer);
    2170:   PetscObjectTypeCompare((PetscObject)ts,TSSUNDIALS,&isundials);
    2171:   PetscViewerASCIIPopTab(viewer);
    2172:   return(0);
    2173: }

    2175: /*@
    2176:    TSSetApplicationContext - Sets an optional user-defined context for
    2177:    the timesteppers.

    2179:    Logically Collective on TS

    2181:    Input Parameters:
    2182: +  ts - the TS context obtained from TSCreate()
    2183: -  usrP - optional user context

    2185:    Fortran Notes:
    2186:     To use this from Fortran you must write a Fortran interface definition for this
    2187:     function that tells Fortran the Fortran derived data type that you are passing in as the ctx argument.

    2189:    Level: intermediate

    2191: .seealso: TSGetApplicationContext()
    2192: @*/
    2193: PetscErrorCode  TSSetApplicationContext(TS ts,void *usrP)
    2194: {
    2197:   ts->user = usrP;
    2198:   return(0);
    2199: }

    2201: /*@
    2202:     TSGetApplicationContext - Gets the user-defined context for the
    2203:     timestepper.

    2205:     Not Collective

    2207:     Input Parameter:
    2208: .   ts - the TS context obtained from TSCreate()

    2210:     Output Parameter:
    2211: .   usrP - user context

    2213:    Fortran Notes:
    2214:     To use this from Fortran you must write a Fortran interface definition for this
    2215:     function that tells Fortran the Fortran derived data type that you are passing in as the ctx argument.

    2217:     Level: intermediate

    2219: .seealso: TSSetApplicationContext()
    2220: @*/
    2221: PetscErrorCode  TSGetApplicationContext(TS ts,void *usrP)
    2222: {
    2225:   *(void**)usrP = ts->user;
    2226:   return(0);
    2227: }

    2229: /*@
    2230:    TSGetStepNumber - Gets the number of steps completed.

    2232:    Not Collective

    2234:    Input Parameter:
    2235: .  ts - the TS context obtained from TSCreate()

    2237:    Output Parameter:
    2238: .  steps - number of steps completed so far

    2240:    Level: intermediate

    2242: .seealso: TSGetTime(), TSGetTimeStep(), TSSetPreStep(), TSSetPreStage(), TSSetPostStage(), TSSetPostStep()
    2243: @*/
    2244: PetscErrorCode TSGetStepNumber(TS ts,PetscInt *steps)
    2245: {
    2249:   *steps = ts->steps;
    2250:   return(0);
    2251: }

    2253: /*@
    2254:    TSSetStepNumber - Sets the number of steps completed.

    2256:    Logically Collective on TS

    2258:    Input Parameters:
    2259: +  ts - the TS context
    2260: -  steps - number of steps completed so far

    2262:    Notes:
    2263:    For most uses of the TS solvers the user need not explicitly call
    2264:    TSSetStepNumber(), as the step counter is appropriately updated in
    2265:    TSSolve()/TSStep()/TSRollBack(). Power users may call this routine to
    2266:    reinitialize timestepping by setting the step counter to zero (and time
    2267:    to the initial time) to solve a similar problem with different initial
    2268:    conditions or parameters. Other possible use case is to continue
    2269:    timestepping from a previously interrupted run in such a way that TS
    2270:    monitors will be called with a initial nonzero step counter.

    2272:    Level: advanced

    2274: .seealso: TSGetStepNumber(), TSSetTime(), TSSetTimeStep(), TSSetSolution()
    2275: @*/
    2276: PetscErrorCode TSSetStepNumber(TS ts,PetscInt steps)
    2277: {
    2281:   if (steps < 0) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Step number must be non-negative");
    2282:   ts->steps = steps;
    2283:   return(0);
    2284: }

    2286: /*@
    2287:    TSSetTimeStep - Allows one to reset the timestep at any time,
    2288:    useful for simple pseudo-timestepping codes.

    2290:    Logically Collective on TS

    2292:    Input Parameters:
    2293: +  ts - the TS context obtained from TSCreate()
    2294: -  time_step - the size of the timestep

    2296:    Level: intermediate

    2298: .seealso: TSGetTimeStep(), TSSetTime()

    2300: @*/
    2301: PetscErrorCode  TSSetTimeStep(TS ts,PetscReal time_step)
    2302: {
    2306:   ts->time_step = time_step;
    2307:   return(0);
    2308: }

    2310: /*@
    2311:    TSSetExactFinalTime - Determines whether to adapt the final time step to
    2312:      match the exact final time, interpolate solution to the exact final time,
    2313:      or just return at the final time TS computed.

    2315:   Logically Collective on TS

    2317:    Input Parameters:
    2318: +   ts - the time-step context
    2319: -   eftopt - exact final time option

    2321: $  TS_EXACTFINALTIME_STEPOVER    - Don't do anything if final time is exceeded
    2322: $  TS_EXACTFINALTIME_INTERPOLATE - Interpolate back to final time
    2323: $  TS_EXACTFINALTIME_MATCHSTEP - Adapt final time step to match the final time

    2325:    Options Database:
    2326: .   -ts_exact_final_time <stepover,interpolate,matchstep> - select the final step at runtime

    2328:    Warning: If you use the option TS_EXACTFINALTIME_STEPOVER the solution may be at a very different time
    2329:     then the final time you selected.

    2331:    Level: beginner

    2333: .seealso: TSExactFinalTimeOption, TSGetExactFinalTime()
    2334: @*/
    2335: PetscErrorCode TSSetExactFinalTime(TS ts,TSExactFinalTimeOption eftopt)
    2336: {
    2340:   ts->exact_final_time = eftopt;
    2341:   return(0);
    2342: }

    2344: /*@
    2345:    TSGetExactFinalTime - Gets the exact final time option.

    2347:    Not Collective

    2349:    Input Parameter:
    2350: .  ts - the TS context

    2352:    Output Parameter:
    2353: .  eftopt - exact final time option

    2355:    Level: beginner

    2357: .seealso: TSExactFinalTimeOption, TSSetExactFinalTime()
    2358: @*/
    2359: PetscErrorCode TSGetExactFinalTime(TS ts,TSExactFinalTimeOption *eftopt)
    2360: {
    2364:   *eftopt = ts->exact_final_time;
    2365:   return(0);
    2366: }

    2368: /*@
    2369:    TSGetTimeStep - Gets the current timestep size.

    2371:    Not Collective

    2373:    Input Parameter:
    2374: .  ts - the TS context obtained from TSCreate()

    2376:    Output Parameter:
    2377: .  dt - the current timestep size

    2379:    Level: intermediate

    2381: .seealso: TSSetTimeStep(), TSGetTime()

    2383: @*/
    2384: PetscErrorCode  TSGetTimeStep(TS ts,PetscReal *dt)
    2385: {
    2389:   *dt = ts->time_step;
    2390:   return(0);
    2391: }

    2393: /*@
    2394:    TSGetSolution - Returns the solution at the present timestep. It
    2395:    is valid to call this routine inside the function that you are evaluating
    2396:    in order to move to the new timestep. This vector not changed until
    2397:    the solution at the next timestep has been calculated.

    2399:    Not Collective, but Vec returned is parallel if TS is parallel

    2401:    Input Parameter:
    2402: .  ts - the TS context obtained from TSCreate()

    2404:    Output Parameter:
    2405: .  v - the vector containing the solution

    2407:    Note: If you used TSSetExactFinalTime(ts,TS_EXACTFINALTIME_MATCHSTEP); this does not return the solution at the requested
    2408:    final time. It returns the solution at the next timestep.

    2410:    Level: intermediate

    2412: .seealso: TSGetTimeStep(), TSGetTime(), TSGetSolveTime(), TSGetSolutionComponents(), TSSetSolutionFunction()

    2414: @*/
    2415: PetscErrorCode  TSGetSolution(TS ts,Vec *v)
    2416: {
    2420:   *v = ts->vec_sol;
    2421:   return(0);
    2422: }

    2424: /*@
    2425:    TSGetSolutionComponents - Returns any solution components at the present
    2426:    timestep, if available for the time integration method being used.
    2427:    Solution components are quantities that share the same size and
    2428:    structure as the solution vector.

    2430:    Not Collective, but Vec returned is parallel if TS is parallel

    2432:    Parameters :
    2433: +  ts - the TS context obtained from TSCreate() (input parameter).
    2434: .  n - If v is PETSC_NULL, then the number of solution components is
    2435:        returned through n, else the n-th solution component is
    2436:        returned in v.
    2437: -  v - the vector containing the n-th solution component
    2438:        (may be PETSC_NULL to use this function to find out
    2439:         the number of solutions components).

    2441:    Level: advanced

    2443: .seealso: TSGetSolution()

    2445: @*/
    2446: PetscErrorCode  TSGetSolutionComponents(TS ts,PetscInt *n,Vec *v)
    2447: {

    2452:   if (!ts->ops->getsolutioncomponents) *n = 0;
    2453:   else {
    2454:     (*ts->ops->getsolutioncomponents)(ts,n,v);
    2455:   }
    2456:   return(0);
    2457: }

    2459: /*@
    2460:    TSGetAuxSolution - Returns an auxiliary solution at the present
    2461:    timestep, if available for the time integration method being used.

    2463:    Not Collective, but Vec returned is parallel if TS is parallel

    2465:    Parameters :
    2466: +  ts - the TS context obtained from TSCreate() (input parameter).
    2467: -  v - the vector containing the auxiliary solution

    2469:    Level: intermediate

    2471: .seealso: TSGetSolution()

    2473: @*/
    2474: PetscErrorCode  TSGetAuxSolution(TS ts,Vec *v)
    2475: {

    2480:   if (ts->ops->getauxsolution) {
    2481:     (*ts->ops->getauxsolution)(ts,v);
    2482:   } else {
    2483:     VecZeroEntries(*v);
    2484:   }
    2485:   return(0);
    2486: }

    2488: /*@
    2489:    TSGetTimeError - Returns the estimated error vector, if the chosen
    2490:    TSType has an error estimation functionality.

    2492:    Not Collective, but Vec returned is parallel if TS is parallel

    2494:    Note: MUST call after TSSetUp()

    2496:    Parameters :
    2497: +  ts - the TS context obtained from TSCreate() (input parameter).
    2498: .  n - current estimate (n=0) or previous one (n=-1)
    2499: -  v - the vector containing the error (same size as the solution).

    2501:    Level: intermediate

    2503: .seealso: TSGetSolution(), TSSetTimeError()

    2505: @*/
    2506: PetscErrorCode  TSGetTimeError(TS ts,PetscInt n,Vec *v)
    2507: {

    2512:   if (ts->ops->gettimeerror) {
    2513:     (*ts->ops->gettimeerror)(ts,n,v);
    2514:   } else {
    2515:     VecZeroEntries(*v);
    2516:   }
    2517:   return(0);
    2518: }

    2520: /*@
    2521:    TSSetTimeError - Sets the estimated error vector, if the chosen
    2522:    TSType has an error estimation functionality. This can be used
    2523:    to restart such a time integrator with a given error vector.

    2525:    Not Collective, but Vec returned is parallel if TS is parallel

    2527:    Parameters :
    2528: +  ts - the TS context obtained from TSCreate() (input parameter).
    2529: -  v - the vector containing the error (same size as the solution).

    2531:    Level: intermediate

    2533: .seealso: TSSetSolution(), TSGetTimeError)

    2535: @*/
    2536: PetscErrorCode  TSSetTimeError(TS ts,Vec v)
    2537: {

    2542:   if (!ts->setupcalled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call TSSetUp() first");
    2543:   if (ts->ops->settimeerror) {
    2544:     (*ts->ops->settimeerror)(ts,v);
    2545:   }
    2546:   return(0);
    2547: }

    2549: /* ----- Routines to initialize and destroy a timestepper ---- */
    2550: /*@
    2551:   TSSetProblemType - Sets the type of problem to be solved.

    2553:   Not collective

    2555:   Input Parameters:
    2556: + ts   - The TS
    2557: - type - One of TS_LINEAR, TS_NONLINEAR where these types refer to problems of the forms
    2558: .vb
    2559:          U_t - A U = 0      (linear)
    2560:          U_t - A(t) U = 0   (linear)
    2561:          F(t,U,U_t) = 0     (nonlinear)
    2562: .ve

    2564:    Level: beginner

    2566: .seealso: TSSetUp(), TSProblemType, TS
    2567: @*/
    2568: PetscErrorCode  TSSetProblemType(TS ts, TSProblemType type)
    2569: {

    2574:   ts->problem_type = type;
    2575:   if (type == TS_LINEAR) {
    2576:     SNES snes;
    2577:     TSGetSNES(ts,&snes);
    2578:     SNESSetType(snes,SNESKSPONLY);
    2579:   }
    2580:   return(0);
    2581: }

    2583: /*@C
    2584:   TSGetProblemType - Gets the type of problem to be solved.

    2586:   Not collective

    2588:   Input Parameter:
    2589: . ts   - The TS

    2591:   Output Parameter:
    2592: . type - One of TS_LINEAR, TS_NONLINEAR where these types refer to problems of the forms
    2593: .vb
    2594:          M U_t = A U
    2595:          M(t) U_t = A(t) U
    2596:          F(t,U,U_t)
    2597: .ve

    2599:    Level: beginner

    2601: .seealso: TSSetUp(), TSProblemType, TS
    2602: @*/
    2603: PetscErrorCode  TSGetProblemType(TS ts, TSProblemType *type)
    2604: {
    2608:   *type = ts->problem_type;
    2609:   return(0);
    2610: }

    2612: /*
    2613:     Attempt to check/preset a default value for the exact final time option. This is needed at the beginning of TSSolve() and in TSSetUp()
    2614: */
    2615: static PetscErrorCode TSSetExactFinalTimeDefault(TS ts)
    2616: {
    2618:   PetscBool      isnone;

    2621:   TSGetAdapt(ts,&ts->adapt);
    2622:   TSAdaptSetDefaultType(ts->adapt,ts->default_adapt_type);

    2624:   PetscObjectTypeCompare((PetscObject)ts->adapt,TSADAPTNONE,&isnone);
    2625:   if (!isnone && ts->exact_final_time == TS_EXACTFINALTIME_UNSPECIFIED) {
    2626:     ts->exact_final_time = TS_EXACTFINALTIME_MATCHSTEP;
    2627:   } else if (ts->exact_final_time == TS_EXACTFINALTIME_UNSPECIFIED) {
    2628:     ts->exact_final_time = TS_EXACTFINALTIME_INTERPOLATE;
    2629:   }
    2630:   return(0);
    2631: }

    2633: /*@
    2634:    TSSetUp - Sets up the internal data structures for the later use of a timestepper.

    2636:    Collective on TS

    2638:    Input Parameter:
    2639: .  ts - the TS context obtained from TSCreate()

    2641:    Notes:
    2642:    For basic use of the TS solvers the user need not explicitly call
    2643:    TSSetUp(), since these actions will automatically occur during
    2644:    the call to TSStep() or TSSolve().  However, if one wishes to control this
    2645:    phase separately, TSSetUp() should be called after TSCreate()
    2646:    and optional routines of the form TSSetXXX(), but before TSStep() and TSSolve().

    2648:    Level: advanced

    2650: .seealso: TSCreate(), TSStep(), TSDestroy(), TSSolve()
    2651: @*/
    2652: PetscErrorCode  TSSetUp(TS ts)
    2653: {
    2655:   DM             dm;
    2656:   PetscErrorCode (*func)(SNES,Vec,Vec,void*);
    2657:   PetscErrorCode (*jac)(SNES,Vec,Mat,Mat,void*);
    2658:   TSIFunction    ifun;
    2659:   TSIJacobian    ijac;
    2660:   TSI2Jacobian   i2jac;
    2661:   TSRHSJacobian  rhsjac;

    2665:   if (ts->setupcalled) return(0);

    2667:   if (!((PetscObject)ts)->type_name) {
    2668:     TSGetIFunction(ts,NULL,&ifun,NULL);
    2669:     TSSetType(ts,ifun ? TSBEULER : TSEULER);
    2670:   }

    2672:   if (!ts->vec_sol) {
    2673:     if (ts->dm) {
    2674:       DMCreateGlobalVector(ts->dm,&ts->vec_sol);
    2675:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call TSSetSolution() first");
    2676:   }

    2678:   if (!ts->Jacp && ts->Jacprhs) { /* IJacobianP shares the same matrix with RHSJacobianP if only RHSJacobianP is provided */
    2679:     PetscObjectReference((PetscObject)ts->Jacprhs);
    2680:     ts->Jacp = ts->Jacprhs;
    2681:   }

    2683:   if (ts->quadraturets) {
    2684:     TSSetUp(ts->quadraturets);
    2685:     VecDestroy(&ts->vec_costintegrand);
    2686:     VecDuplicate(ts->quadraturets->vec_sol,&ts->vec_costintegrand);
    2687:   }

    2689:   TSGetRHSJacobian(ts,NULL,NULL,&rhsjac,NULL);
    2690:   if (rhsjac == TSComputeRHSJacobianConstant) {
    2691:     Mat Amat,Pmat;
    2692:     SNES snes;
    2693:     TSGetSNES(ts,&snes);
    2694:     SNESGetJacobian(snes,&Amat,&Pmat,NULL,NULL);
    2695:     /* Matching matrices implies that an IJacobian is NOT set, because if it had been set, the IJacobian's matrix would
    2696:      * have displaced the RHS matrix */
    2697:     if (Amat && Amat == ts->Arhs) {
    2698:       /* we need to copy the values of the matrix because for the constant Jacobian case the user will never set the numerical values in this new location */
    2699:       MatDuplicate(ts->Arhs,MAT_COPY_VALUES,&Amat);
    2700:       SNESSetJacobian(snes,Amat,NULL,NULL,NULL);
    2701:       MatDestroy(&Amat);
    2702:     }
    2703:     if (Pmat && Pmat == ts->Brhs) {
    2704:       MatDuplicate(ts->Brhs,MAT_COPY_VALUES,&Pmat);
    2705:       SNESSetJacobian(snes,NULL,Pmat,NULL,NULL);
    2706:       MatDestroy(&Pmat);
    2707:     }
    2708:   }

    2710:   TSGetAdapt(ts,&ts->adapt);
    2711:   TSAdaptSetDefaultType(ts->adapt,ts->default_adapt_type);

    2713:   if (ts->ops->setup) {
    2714:     (*ts->ops->setup)(ts);
    2715:   }

    2717:   TSSetExactFinalTimeDefault(ts);

    2719:   /* In the case where we've set a DMTSFunction or what have you, we need the default SNESFunction
    2720:      to be set right but can't do it elsewhere due to the overreliance on ctx=ts.
    2721:    */
    2722:   TSGetDM(ts,&dm);
    2723:   DMSNESGetFunction(dm,&func,NULL);
    2724:   if (!func) {
    2725:     DMSNESSetFunction(dm,SNESTSFormFunction,ts);
    2726:   }
    2727:   /* If the SNES doesn't have a jacobian set and the TS has an ijacobian or rhsjacobian set, set the SNES to use it.
    2728:      Otherwise, the SNES will use coloring internally to form the Jacobian.
    2729:    */
    2730:   DMSNESGetJacobian(dm,&jac,NULL);
    2731:   DMTSGetIJacobian(dm,&ijac,NULL);
    2732:   DMTSGetI2Jacobian(dm,&i2jac,NULL);
    2733:   DMTSGetRHSJacobian(dm,&rhsjac,NULL);
    2734:   if (!jac && (ijac || i2jac || rhsjac)) {
    2735:     DMSNESSetJacobian(dm,SNESTSFormJacobian,ts);
    2736:   }

    2738:   /* if time integration scheme has a starting method, call it */
    2739:   if (ts->ops->startingmethod) {
    2740:     (*ts->ops->startingmethod)(ts);
    2741:   }

    2743:   ts->setupcalled = PETSC_TRUE;
    2744:   return(0);
    2745: }

    2747: /*@
    2748:    TSReset - Resets a TS context and removes any allocated Vecs and Mats.

    2750:    Collective on TS

    2752:    Input Parameter:
    2753: .  ts - the TS context obtained from TSCreate()

    2755:    Level: beginner

    2757: .seealso: TSCreate(), TSSetup(), TSDestroy()
    2758: @*/
    2759: PetscErrorCode  TSReset(TS ts)
    2760: {
    2761:   TS_RHSSplitLink ilink = ts->tsrhssplit,next;
    2762:   PetscErrorCode  ierr;

    2767:   if (ts->ops->reset) {
    2768:     (*ts->ops->reset)(ts);
    2769:   }
    2770:   if (ts->snes) {SNESReset(ts->snes);}
    2771:   if (ts->adapt) {TSAdaptReset(ts->adapt);}

    2773:   MatDestroy(&ts->Arhs);
    2774:   MatDestroy(&ts->Brhs);
    2775:   VecDestroy(&ts->Frhs);
    2776:   VecDestroy(&ts->vec_sol);
    2777:   VecDestroy(&ts->vec_dot);
    2778:   VecDestroy(&ts->vatol);
    2779:   VecDestroy(&ts->vrtol);
    2780:   VecDestroyVecs(ts->nwork,&ts->work);

    2782:   MatDestroy(&ts->Jacprhs);
    2783:   MatDestroy(&ts->Jacp);
    2784:   if (ts->forward_solve) {
    2785:     TSForwardReset(ts);
    2786:   }
    2787:   if (ts->quadraturets) {
    2788:     TSReset(ts->quadraturets);
    2789:     VecDestroy(&ts->vec_costintegrand);
    2790:   }
    2791:   while (ilink) {
    2792:     next = ilink->next;
    2793:     TSDestroy(&ilink->ts);
    2794:     PetscFree(ilink->splitname);
    2795:     ISDestroy(&ilink->is);
    2796:     PetscFree(ilink);
    2797:     ilink = next;
    2798:   }
    2799:   ts->num_rhs_splits = 0;
    2800:   ts->setupcalled = PETSC_FALSE;
    2801:   return(0);
    2802: }

    2804: /*@C
    2805:    TSDestroy - Destroys the timestepper context that was created
    2806:    with TSCreate().

    2808:    Collective on TS

    2810:    Input Parameter:
    2811: .  ts - the TS context obtained from TSCreate()

    2813:    Level: beginner

    2815: .seealso: TSCreate(), TSSetUp(), TSSolve()
    2816: @*/
    2817: PetscErrorCode  TSDestroy(TS *ts)
    2818: {

    2822:   if (!*ts) return(0);
    2824:   if (--((PetscObject)(*ts))->refct > 0) {*ts = NULL; return(0);}

    2826:   TSReset(*ts);
    2827:   TSAdjointReset(*ts);
    2828:   if ((*ts)->forward_solve) {
    2829:     TSForwardReset(*ts);
    2830:   }
    2831:   /* if memory was published with SAWs then destroy it */
    2832:   PetscObjectSAWsViewOff((PetscObject)*ts);
    2833:   if ((*ts)->ops->destroy) {(*(*ts)->ops->destroy)((*ts));}

    2835:   TSTrajectoryDestroy(&(*ts)->trajectory);

    2837:   TSAdaptDestroy(&(*ts)->adapt);
    2838:   TSEventDestroy(&(*ts)->event);

    2840:   SNESDestroy(&(*ts)->snes);
    2841:   DMDestroy(&(*ts)->dm);
    2842:   TSMonitorCancel((*ts));
    2843:   TSAdjointMonitorCancel((*ts));

    2845:   TSDestroy(&(*ts)->quadraturets);
    2846:   PetscHeaderDestroy(ts);
    2847:   return(0);
    2848: }

    2850: /*@
    2851:    TSGetSNES - Returns the SNES (nonlinear solver) associated with
    2852:    a TS (timestepper) context. Valid only for nonlinear problems.

    2854:    Not Collective, but SNES is parallel if TS is parallel

    2856:    Input Parameter:
    2857: .  ts - the TS context obtained from TSCreate()

    2859:    Output Parameter:
    2860: .  snes - the nonlinear solver context

    2862:    Notes:
    2863:    The user can then directly manipulate the SNES context to set various
    2864:    options, etc.  Likewise, the user can then extract and manipulate the
    2865:    KSP, KSP, and PC contexts as well.

    2867:    TSGetSNES() does not work for integrators that do not use SNES; in
    2868:    this case TSGetSNES() returns NULL in snes.

    2870:    Level: beginner

    2872: @*/
    2873: PetscErrorCode  TSGetSNES(TS ts,SNES *snes)
    2874: {

    2880:   if (!ts->snes) {
    2881:     SNESCreate(PetscObjectComm((PetscObject)ts),&ts->snes);
    2882:     PetscObjectSetOptions((PetscObject)ts->snes,((PetscObject)ts)->options);
    2883:     SNESSetFunction(ts->snes,NULL,SNESTSFormFunction,ts);
    2884:     PetscLogObjectParent((PetscObject)ts,(PetscObject)ts->snes);
    2885:     PetscObjectIncrementTabLevel((PetscObject)ts->snes,(PetscObject)ts,1);
    2886:     if (ts->dm) {SNESSetDM(ts->snes,ts->dm);}
    2887:     if (ts->problem_type == TS_LINEAR) {
    2888:       SNESSetType(ts->snes,SNESKSPONLY);
    2889:     }
    2890:   }
    2891:   *snes = ts->snes;
    2892:   return(0);
    2893: }

    2895: /*@
    2896:    TSSetSNES - Set the SNES (nonlinear solver) to be used by the timestepping context

    2898:    Collective

    2900:    Input Parameters:
    2901: +  ts - the TS context obtained from TSCreate()
    2902: -  snes - the nonlinear solver context

    2904:    Notes:
    2905:    Most users should have the TS created by calling TSGetSNES()

    2907:    Level: developer

    2909: @*/
    2910: PetscErrorCode TSSetSNES(TS ts,SNES snes)
    2911: {
    2913:   PetscErrorCode (*func)(SNES,Vec,Mat,Mat,void*);

    2918:   PetscObjectReference((PetscObject)snes);
    2919:   SNESDestroy(&ts->snes);

    2921:   ts->snes = snes;

    2923:   SNESSetFunction(ts->snes,NULL,SNESTSFormFunction,ts);
    2924:   SNESGetJacobian(ts->snes,NULL,NULL,&func,NULL);
    2925:   if (func == SNESTSFormJacobian) {
    2926:     SNESSetJacobian(ts->snes,NULL,NULL,SNESTSFormJacobian,ts);
    2927:   }
    2928:   return(0);
    2929: }

    2931: /*@
    2932:    TSGetKSP - Returns the KSP (linear solver) associated with
    2933:    a TS (timestepper) context.

    2935:    Not Collective, but KSP is parallel if TS is parallel

    2937:    Input Parameter:
    2938: .  ts - the TS context obtained from TSCreate()

    2940:    Output Parameter:
    2941: .  ksp - the nonlinear solver context

    2943:    Notes:
    2944:    The user can then directly manipulate the KSP context to set various
    2945:    options, etc.  Likewise, the user can then extract and manipulate the
    2946:    KSP and PC contexts as well.

    2948:    TSGetKSP() does not work for integrators that do not use KSP;
    2949:    in this case TSGetKSP() returns NULL in ksp.

    2951:    Level: beginner

    2953: @*/
    2954: PetscErrorCode  TSGetKSP(TS ts,KSP *ksp)
    2955: {
    2957:   SNES           snes;

    2962:   if (!((PetscObject)ts)->type_name) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_NULL,"KSP is not created yet. Call TSSetType() first");
    2963:   if (ts->problem_type != TS_LINEAR) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Linear only; use TSGetSNES()");
    2964:   TSGetSNES(ts,&snes);
    2965:   SNESGetKSP(snes,ksp);
    2966:   return(0);
    2967: }

    2969: /* ----------- Routines to set solver parameters ---------- */

    2971: /*@
    2972:    TSSetMaxSteps - Sets the maximum number of steps to use.

    2974:    Logically Collective on TS

    2976:    Input Parameters:
    2977: +  ts - the TS context obtained from TSCreate()
    2978: -  maxsteps - maximum number of steps to use

    2980:    Options Database Keys:
    2981: .  -ts_max_steps <maxsteps> - Sets maxsteps

    2983:    Notes:
    2984:    The default maximum number of steps is 5000

    2986:    Level: intermediate

    2988: .seealso: TSGetMaxSteps(), TSSetMaxTime(), TSSetExactFinalTime()
    2989: @*/
    2990: PetscErrorCode TSSetMaxSteps(TS ts,PetscInt maxsteps)
    2991: {
    2995:   if (maxsteps < 0) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Maximum number of steps must be non-negative");
    2996:   ts->max_steps = maxsteps;
    2997:   return(0);
    2998: }

    3000: /*@
    3001:    TSGetMaxSteps - Gets the maximum number of steps to use.

    3003:    Not Collective

    3005:    Input Parameters:
    3006: .  ts - the TS context obtained from TSCreate()

    3008:    Output Parameter:
    3009: .  maxsteps - maximum number of steps to use

    3011:    Level: advanced

    3013: .seealso: TSSetMaxSteps(), TSGetMaxTime(), TSSetMaxTime()
    3014: @*/
    3015: PetscErrorCode TSGetMaxSteps(TS ts,PetscInt *maxsteps)
    3016: {
    3020:   *maxsteps = ts->max_steps;
    3021:   return(0);
    3022: }

    3024: /*@
    3025:    TSSetMaxTime - Sets the maximum (or final) time for timestepping.

    3027:    Logically Collective on TS

    3029:    Input Parameters:
    3030: +  ts - the TS context obtained from TSCreate()
    3031: -  maxtime - final time to step to

    3033:    Options Database Keys:
    3034: .  -ts_max_time <maxtime> - Sets maxtime

    3036:    Notes:
    3037:    The default maximum time is 5.0

    3039:    Level: intermediate

    3041: .seealso: TSGetMaxTime(), TSSetMaxSteps(), TSSetExactFinalTime()
    3042: @*/
    3043: PetscErrorCode TSSetMaxTime(TS ts,PetscReal maxtime)
    3044: {
    3048:   ts->max_time = maxtime;
    3049:   return(0);
    3050: }

    3052: /*@
    3053:    TSGetMaxTime - Gets the maximum (or final) time for timestepping.

    3055:    Not Collective

    3057:    Input Parameters:
    3058: .  ts - the TS context obtained from TSCreate()

    3060:    Output Parameter:
    3061: .  maxtime - final time to step to

    3063:    Level: advanced

    3065: .seealso: TSSetMaxTime(), TSGetMaxSteps(), TSSetMaxSteps()
    3066: @*/
    3067: PetscErrorCode TSGetMaxTime(TS ts,PetscReal *maxtime)
    3068: {
    3072:   *maxtime = ts->max_time;
    3073:   return(0);
    3074: }

    3076: /*@
    3077:    TSSetInitialTimeStep - Deprecated, use TSSetTime() and TSSetTimeStep().

    3079:    Level: deprecated

    3081: @*/
    3082: PetscErrorCode  TSSetInitialTimeStep(TS ts,PetscReal initial_time,PetscReal time_step)
    3083: {
    3087:   TSSetTime(ts,initial_time);
    3088:   TSSetTimeStep(ts,time_step);
    3089:   return(0);
    3090: }

    3092: /*@
    3093:    TSGetDuration - Deprecated, use TSGetMaxSteps() and TSGetMaxTime().

    3095:    Level: deprecated

    3097: @*/
    3098: PetscErrorCode TSGetDuration(TS ts, PetscInt *maxsteps, PetscReal *maxtime)
    3099: {
    3102:   if (maxsteps) {
    3104:     *maxsteps = ts->max_steps;
    3105:   }
    3106:   if (maxtime) {
    3108:     *maxtime = ts->max_time;
    3109:   }
    3110:   return(0);
    3111: }

    3113: /*@
    3114:    TSSetDuration - Deprecated, use TSSetMaxSteps() and TSSetMaxTime().

    3116:    Level: deprecated

    3118: @*/
    3119: PetscErrorCode TSSetDuration(TS ts,PetscInt maxsteps,PetscReal maxtime)
    3120: {
    3125:   if (maxsteps >= 0) ts->max_steps = maxsteps;
    3126:   if (maxtime != PETSC_DEFAULT) ts->max_time = maxtime;
    3127:   return(0);
    3128: }

    3130: /*@
    3131:    TSGetTimeStepNumber - Deprecated, use TSGetStepNumber().

    3133:    Level: deprecated

    3135: @*/
    3136: PetscErrorCode TSGetTimeStepNumber(TS ts,PetscInt *steps) { return TSGetStepNumber(ts,steps); }

    3138: /*@
    3139:    TSGetTotalSteps - Deprecated, use TSGetStepNumber().

    3141:    Level: deprecated

    3143: @*/
    3144: PetscErrorCode TSGetTotalSteps(TS ts,PetscInt *steps) { return TSGetStepNumber(ts,steps); }

    3146: /*@
    3147:    TSSetSolution - Sets the initial solution vector
    3148:    for use by the TS routines.

    3150:    Logically Collective on TS

    3152:    Input Parameters:
    3153: +  ts - the TS context obtained from TSCreate()
    3154: -  u - the solution vector

    3156:    Level: beginner

    3158: .seealso: TSSetSolutionFunction(), TSGetSolution(), TSCreate()
    3159: @*/
    3160: PetscErrorCode  TSSetSolution(TS ts,Vec u)
    3161: {
    3163:   DM             dm;

    3168:   PetscObjectReference((PetscObject)u);
    3169:   VecDestroy(&ts->vec_sol);
    3170:   ts->vec_sol = u;

    3172:   TSGetDM(ts,&dm);
    3173:   DMShellSetGlobalVector(dm,u);
    3174:   return(0);
    3175: }

    3177: /*@C
    3178:   TSSetPreStep - Sets the general-purpose function
    3179:   called once at the beginning of each time step.

    3181:   Logically Collective on TS

    3183:   Input Parameters:
    3184: + ts   - The TS context obtained from TSCreate()
    3185: - func - The function

    3187:   Calling sequence of func:
    3188: .   PetscErrorCode func (TS ts);

    3190:   Level: intermediate

    3192: .seealso: TSSetPreStage(), TSSetPostStage(), TSSetPostStep(), TSStep(), TSRestartStep()
    3193: @*/
    3194: PetscErrorCode  TSSetPreStep(TS ts, PetscErrorCode (*func)(TS))
    3195: {
    3198:   ts->prestep = func;
    3199:   return(0);
    3200: }

    3202: /*@
    3203:   TSPreStep - Runs the user-defined pre-step function.

    3205:   Collective on TS

    3207:   Input Parameters:
    3208: . ts   - The TS context obtained from TSCreate()

    3210:   Notes:
    3211:   TSPreStep() is typically used within time stepping implementations,
    3212:   so most users would not generally call this routine themselves.

    3214:   Level: developer

    3216: .seealso: TSSetPreStep(), TSPreStage(), TSPostStage(), TSPostStep()
    3217: @*/
    3218: PetscErrorCode  TSPreStep(TS ts)
    3219: {

    3224:   if (ts->prestep) {
    3225:     Vec              U;
    3226:     PetscObjectState sprev,spost;

    3228:     TSGetSolution(ts,&U);
    3229:     PetscObjectStateGet((PetscObject)U,&sprev);
    3230:     PetscStackCallStandard((*ts->prestep),(ts));
    3231:     PetscObjectStateGet((PetscObject)U,&spost);
    3232:     if (sprev != spost) {TSRestartStep(ts);}
    3233:   }
    3234:   return(0);
    3235: }

    3237: /*@C
    3238:   TSSetPreStage - Sets the general-purpose function
    3239:   called once at the beginning of each stage.

    3241:   Logically Collective on TS

    3243:   Input Parameters:
    3244: + ts   - The TS context obtained from TSCreate()
    3245: - func - The function

    3247:   Calling sequence of func:
    3248: .    PetscErrorCode func(TS ts, PetscReal stagetime);

    3250:   Level: intermediate

    3252:   Note:
    3253:   There may be several stages per time step. If the solve for a given stage fails, the step may be rejected and retried.
    3254:   The time step number being computed can be queried using TSGetStepNumber() and the total size of the step being
    3255:   attempted can be obtained using TSGetTimeStep(). The time at the start of the step is available via TSGetTime().

    3257: .seealso: TSSetPostStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext()
    3258: @*/
    3259: PetscErrorCode  TSSetPreStage(TS ts, PetscErrorCode (*func)(TS,PetscReal))
    3260: {
    3263:   ts->prestage = func;
    3264:   return(0);
    3265: }

    3267: /*@C
    3268:   TSSetPostStage - Sets the general-purpose function
    3269:   called once at the end of each stage.

    3271:   Logically Collective on TS

    3273:   Input Parameters:
    3274: + ts   - The TS context obtained from TSCreate()
    3275: - func - The function

    3277:   Calling sequence of func:
    3278: . PetscErrorCode func(TS ts, PetscReal stagetime, PetscInt stageindex, Vec* Y);

    3280:   Level: intermediate

    3282:   Note:
    3283:   There may be several stages per time step. If the solve for a given stage fails, the step may be rejected and retried.
    3284:   The time step number being computed can be queried using TSGetStepNumber() and the total size of the step being
    3285:   attempted can be obtained using TSGetTimeStep(). The time at the start of the step is available via TSGetTime().

    3287: .seealso: TSSetPreStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext()
    3288: @*/
    3289: PetscErrorCode  TSSetPostStage(TS ts, PetscErrorCode (*func)(TS,PetscReal,PetscInt,Vec*))
    3290: {
    3293:   ts->poststage = func;
    3294:   return(0);
    3295: }

    3297: /*@C
    3298:   TSSetPostEvaluate - Sets the general-purpose function
    3299:   called once at the end of each step evaluation.

    3301:   Logically Collective on TS

    3303:   Input Parameters:
    3304: + ts   - The TS context obtained from TSCreate()
    3305: - func - The function

    3307:   Calling sequence of func:
    3308: . PetscErrorCode func(TS ts);

    3310:   Level: intermediate

    3312:   Note:
    3313:   Semantically, TSSetPostEvaluate() differs from TSSetPostStep() since the function it sets is called before event-handling
    3314:   thus guaranteeing the same solution (computed by the time-stepper) will be passed to it. On the other hand, TSPostStep()
    3315:   may be passed a different solution, possibly changed by the event handler. TSPostEvaluate() is called after the next step
    3316:   solution is evaluated allowing to modify it, if need be. The solution can be obtained with TSGetSolution(), the time step
    3317:   with TSGetTimeStep(), and the time at the start of the step is available via TSGetTime()

    3319: .seealso: TSSetPreStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext()
    3320: @*/
    3321: PetscErrorCode  TSSetPostEvaluate(TS ts, PetscErrorCode (*func)(TS))
    3322: {
    3325:   ts->postevaluate = func;
    3326:   return(0);
    3327: }

    3329: /*@
    3330:   TSPreStage - Runs the user-defined pre-stage function set using TSSetPreStage()

    3332:   Collective on TS

    3334:   Input Parameters:
    3335: . ts          - The TS context obtained from TSCreate()
    3336:   stagetime   - The absolute time of the current stage

    3338:   Notes:
    3339:   TSPreStage() is typically used within time stepping implementations,
    3340:   most users would not generally call this routine themselves.

    3342:   Level: developer

    3344: .seealso: TSPostStage(), TSSetPreStep(), TSPreStep(), TSPostStep()
    3345: @*/
    3346: PetscErrorCode  TSPreStage(TS ts, PetscReal stagetime)
    3347: {
    3350:   if (ts->prestage) {
    3351:     PetscStackCallStandard((*ts->prestage),(ts,stagetime));
    3352:   }
    3353:   return(0);
    3354: }

    3356: /*@
    3357:   TSPostStage - Runs the user-defined post-stage function set using TSSetPostStage()

    3359:   Collective on TS

    3361:   Input Parameters:
    3362: . ts          - The TS context obtained from TSCreate()
    3363:   stagetime   - The absolute time of the current stage
    3364:   stageindex  - Stage number
    3365:   Y           - Array of vectors (of size = total number
    3366:                 of stages) with the stage solutions

    3368:   Notes:
    3369:   TSPostStage() is typically used within time stepping implementations,
    3370:   most users would not generally call this routine themselves.

    3372:   Level: developer

    3374: .seealso: TSPreStage(), TSSetPreStep(), TSPreStep(), TSPostStep()
    3375: @*/
    3376: PetscErrorCode  TSPostStage(TS ts, PetscReal stagetime, PetscInt stageindex, Vec *Y)
    3377: {
    3380:   if (ts->poststage) {
    3381:     PetscStackCallStandard((*ts->poststage),(ts,stagetime,stageindex,Y));
    3382:   }
    3383:   return(0);
    3384: }

    3386: /*@
    3387:   TSPostEvaluate - Runs the user-defined post-evaluate function set using TSSetPostEvaluate()

    3389:   Collective on TS

    3391:   Input Parameters:
    3392: . ts          - The TS context obtained from TSCreate()

    3394:   Notes:
    3395:   TSPostEvaluate() is typically used within time stepping implementations,
    3396:   most users would not generally call this routine themselves.

    3398:   Level: developer

    3400: .seealso: TSSetPostEvaluate(), TSSetPreStep(), TSPreStep(), TSPostStep()
    3401: @*/
    3402: PetscErrorCode  TSPostEvaluate(TS ts)
    3403: {

    3408:   if (ts->postevaluate) {
    3409:     Vec              U;
    3410:     PetscObjectState sprev,spost;

    3412:     TSGetSolution(ts,&U);
    3413:     PetscObjectStateGet((PetscObject)U,&sprev);
    3414:     PetscStackCallStandard((*ts->postevaluate),(ts));
    3415:     PetscObjectStateGet((PetscObject)U,&spost);
    3416:     if (sprev != spost) {TSRestartStep(ts);}
    3417:   }
    3418:   return(0);
    3419: }

    3421: /*@C
    3422:   TSSetPostStep - Sets the general-purpose function
    3423:   called once at the end of each time step.

    3425:   Logically Collective on TS

    3427:   Input Parameters:
    3428: + ts   - The TS context obtained from TSCreate()
    3429: - func - The function

    3431:   Calling sequence of func:
    3432: $ func (TS ts);

    3434:   Notes:
    3435:   The function set by TSSetPostStep() is called after each successful step. The solution vector X
    3436:   obtained by TSGetSolution() may be different than that computed at the step end if the event handler
    3437:   locates an event and TSPostEvent() modifies it. Use TSSetPostEvaluate() if an unmodified solution is needed instead.

    3439:   Level: intermediate

    3441: .seealso: TSSetPreStep(), TSSetPreStage(), TSSetPostEvaluate(), TSGetTimeStep(), TSGetStepNumber(), TSGetTime(), TSRestartStep()
    3442: @*/
    3443: PetscErrorCode  TSSetPostStep(TS ts, PetscErrorCode (*func)(TS))
    3444: {
    3447:   ts->poststep = func;
    3448:   return(0);
    3449: }

    3451: /*@
    3452:   TSPostStep - Runs the user-defined post-step function.

    3454:   Collective on TS

    3456:   Input Parameters:
    3457: . ts   - The TS context obtained from TSCreate()

    3459:   Notes:
    3460:   TSPostStep() is typically used within time stepping implementations,
    3461:   so most users would not generally call this routine themselves.

    3463:   Level: developer

    3465: @*/
    3466: PetscErrorCode  TSPostStep(TS ts)
    3467: {

    3472:   if (ts->poststep) {
    3473:     Vec              U;
    3474:     PetscObjectState sprev,spost;

    3476:     TSGetSolution(ts,&U);
    3477:     PetscObjectStateGet((PetscObject)U,&sprev);
    3478:     PetscStackCallStandard((*ts->poststep),(ts));
    3479:     PetscObjectStateGet((PetscObject)U,&spost);
    3480:     if (sprev != spost) {TSRestartStep(ts);}
    3481:   }
    3482:   return(0);
    3483: }

    3485: /*@
    3486:    TSInterpolate - Interpolate the solution computed during the previous step to an arbitrary location in the interval

    3488:    Collective on TS

    3490:    Input Parameters:
    3491: +  ts - time stepping context
    3492: -  t - time to interpolate to

    3494:    Output Parameter:
    3495: .  U - state at given time

    3497:    Level: intermediate

    3499:    Developer Notes:
    3500:    TSInterpolate() and the storing of previous steps/stages should be generalized to support delay differential equations and continuous adjoints.

    3502: .seealso: TSSetExactFinalTime(), TSSolve()
    3503: @*/
    3504: PetscErrorCode TSInterpolate(TS ts,PetscReal t,Vec U)
    3505: {

    3511:   if (t < ts->ptime_prev || t > ts->ptime) SETERRQ3(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Requested time %g not in last time steps [%g,%g]",t,(double)ts->ptime_prev,(double)ts->ptime);
    3512:   if (!ts->ops->interpolate) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"%s does not provide interpolation",((PetscObject)ts)->type_name);
    3513:   (*ts->ops->interpolate)(ts,t,U);
    3514:   return(0);
    3515: }

    3517: /*@
    3518:    TSStep - Steps one time step

    3520:    Collective on TS

    3522:    Input Parameter:
    3523: .  ts - the TS context obtained from TSCreate()

    3525:    Level: developer

    3527:    Notes:
    3528:    The public interface for the ODE/DAE solvers is TSSolve(), you should almost for sure be using that routine and not this routine.

    3530:    The hook set using TSSetPreStep() is called before each attempt to take the step. In general, the time step size may
    3531:    be changed due to adaptive error controller or solve failures. Note that steps may contain multiple stages.

    3533:    This may over-step the final time provided in TSSetMaxTime() depending on the time-step used. TSSolve() interpolates to exactly the
    3534:    time provided in TSSetMaxTime(). One can use TSInterpolate() to determine an interpolated solution within the final timestep.

    3536: .seealso: TSCreate(), TSSetUp(), TSDestroy(), TSSolve(), TSSetPreStep(), TSSetPreStage(), TSSetPostStage(), TSInterpolate()
    3537: @*/
    3538: PetscErrorCode  TSStep(TS ts)
    3539: {
    3540:   PetscErrorCode   ierr;
    3541:   static PetscBool cite = PETSC_FALSE;
    3542:   PetscReal        ptime;

    3546:   PetscCitationsRegister("@article{tspaper,\n"
    3547:                                 "  title         = {{PETSc/TS}: A Modern Scalable {DAE/ODE} Solver Library},\n"
    3548:                                 "  author        = {Abhyankar, Shrirang and Brown, Jed and Constantinescu, Emil and Ghosh, Debojyoti and Smith, Barry F. and Zhang, Hong},\n"
    3549:                                 "  journal       = {arXiv e-preprints},\n"
    3550:                                 "  eprint        = {1806.01437},\n"
    3551:                                 "  archivePrefix = {arXiv},\n"
    3552:                                 "  year          = {2018}\n}\n",&cite);

    3554:   TSSetUp(ts);
    3555:   TSTrajectorySetUp(ts->trajectory,ts);

    3557:   if (!ts->ops->step) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSStep not implemented for type '%s'",((PetscObject)ts)->type_name);
    3558:   if (ts->max_time >= PETSC_MAX_REAL && ts->max_steps == PETSC_MAX_INT) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"You must call TSSetMaxTime() or TSSetMaxSteps(), or use -ts_max_time <time> or -ts_max_steps <steps>");
    3559:   if (ts->exact_final_time == TS_EXACTFINALTIME_UNSPECIFIED) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"You must call TSSetExactFinalTime() or use -ts_exact_final_time <stepover,interpolate,matchstep> before calling TSStep()");
    3560:   if (ts->exact_final_time == TS_EXACTFINALTIME_MATCHSTEP && !ts->adapt) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Since TS is not adaptive you cannot use TS_EXACTFINALTIME_MATCHSTEP, suggest TS_EXACTFINALTIME_INTERPOLATE");

    3562:   if (!ts->steps) ts->ptime_prev = ts->ptime;
    3563:   ptime = ts->ptime; ts->ptime_prev_rollback = ts->ptime_prev;
    3564:   ts->reason = TS_CONVERGED_ITERATING;

    3566:   PetscLogEventBegin(TS_Step,ts,0,0,0);
    3567:   (*ts->ops->step)(ts);
    3568:   PetscLogEventEnd(TS_Step,ts,0,0,0);

    3570:   if (ts->reason >= 0) {
    3571:     ts->ptime_prev = ptime;
    3572:     ts->steps++;
    3573:     ts->steprollback = PETSC_FALSE;
    3574:     ts->steprestart  = PETSC_FALSE;
    3575:   }

    3577:   if (!ts->reason) {
    3578:     if (ts->steps >= ts->max_steps) ts->reason = TS_CONVERGED_ITS;
    3579:     else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME;
    3580:   }

    3582:   if (ts->reason < 0 && ts->errorifstepfailed && ts->reason == TS_DIVERGED_NONLINEAR_SOLVE) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s, increase -ts_max_snes_failures or make negative to attempt recovery",TSConvergedReasons[ts->reason]);
    3583:   if (ts->reason < 0 && ts->errorifstepfailed) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s",TSConvergedReasons[ts->reason]);
    3584:   return(0);
    3585: }

    3587: /*@
    3588:    TSEvaluateWLTE - Evaluate the weighted local truncation error norm
    3589:    at the end of a time step with a given order of accuracy.

    3591:    Collective on TS

    3593:    Input Parameters:
    3594: +  ts - time stepping context
    3595: -  wnormtype - norm type, either NORM_2 or NORM_INFINITY

    3597:    Input/Output Parameter:
    3598: .  order - optional, desired order for the error evaluation or PETSC_DECIDE;
    3599:            on output, the actual order of the error evaluation

    3601:    Output Parameter:
    3602: .  wlte - the weighted local truncation error norm

    3604:    Level: advanced

    3606:    Notes:
    3607:    If the timestepper cannot evaluate the error in a particular step
    3608:    (eg. in the first step or restart steps after event handling),
    3609:    this routine returns wlte=-1.0 .

    3611: .seealso: TSStep(), TSAdapt, TSErrorWeightedNorm()
    3612: @*/
    3613: PetscErrorCode TSEvaluateWLTE(TS ts,NormType wnormtype,PetscInt *order,PetscReal *wlte)
    3614: {

    3624:   if (wnormtype != NORM_2 && wnormtype != NORM_INFINITY) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]);
    3625:   if (!ts->ops->evaluatewlte) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSEvaluateWLTE not implemented for type '%s'",((PetscObject)ts)->type_name);
    3626:   (*ts->ops->evaluatewlte)(ts,wnormtype,order,wlte);
    3627:   return(0);
    3628: }

    3630: /*@
    3631:    TSEvaluateStep - Evaluate the solution at the end of a time step with a given order of accuracy.

    3633:    Collective on TS

    3635:    Input Parameters:
    3636: +  ts - time stepping context
    3637: .  order - desired order of accuracy
    3638: -  done - whether the step was evaluated at this order (pass NULL to generate an error if not available)

    3640:    Output Parameter:
    3641: .  U - state at the end of the current step

    3643:    Level: advanced

    3645:    Notes:
    3646:    This function cannot be called until all stages have been evaluated.
    3647:    It is normally called by adaptive controllers before a step has been accepted and may also be called by the user after TSStep() has returned.

    3649: .seealso: TSStep(), TSAdapt
    3650: @*/
    3651: PetscErrorCode TSEvaluateStep(TS ts,PetscInt order,Vec U,PetscBool *done)
    3652: {

    3659:   if (!ts->ops->evaluatestep) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSEvaluateStep not implemented for type '%s'",((PetscObject)ts)->type_name);
    3660:   (*ts->ops->evaluatestep)(ts,order,U,done);
    3661:   return(0);
    3662: }

    3664: /*@C
    3665:   TSGetComputeInitialCondition - Get the function used to automatically compute an initial condition for the timestepping.

    3667:   Not collective

    3669:   Input Parameter:
    3670: . ts        - time stepping context

    3672:   Output Parameter:
    3673: . initConditions - The function which computes an initial condition

    3675:    Level: advanced

    3677:    Notes:
    3678:    The calling sequence for the function is
    3679: $ initCondition(TS ts, Vec u)
    3680: $ ts - The timestepping context
    3681: $ u  - The input vector in which the initial condition is stored

    3683: .seealso: TSSetComputeInitialCondition(), TSComputeInitialCondition()
    3684: @*/
    3685: PetscErrorCode TSGetComputeInitialCondition(TS ts, PetscErrorCode (**initCondition)(TS, Vec))
    3686: {
    3690:   *initCondition = ts->ops->initcondition;
    3691:   return(0);
    3692: }

    3694: /*@C
    3695:   TSSetComputeInitialCondition - Set the function used to automatically compute an initial condition for the timestepping.

    3697:   Logically collective on ts

    3699:   Input Parameters:
    3700: + ts        - time stepping context
    3701: - initCondition - The function which computes an initial condition

    3703:   Level: advanced

    3705:   Calling sequence for initCondition:
    3706: $ PetscErrorCode initCondition(TS ts, Vec u)

    3708: + ts - The timestepping context
    3709: - u  - The input vector in which the initial condition is to be stored

    3711: .seealso: TSGetComputeInitialCondition(), TSComputeInitialCondition()
    3712: @*/
    3713: PetscErrorCode TSSetComputeInitialCondition(TS ts, PetscErrorCode (*initCondition)(TS, Vec))
    3714: {
    3718:   ts->ops->initcondition = initCondition;
    3719:   return(0);
    3720: }

    3722: /*@
    3723:   TSComputeInitialCondition - Compute an initial condition for the timestepping using the function previously set.

    3725:   Collective on ts

    3727:   Input Parameters:
    3728: + ts - time stepping context
    3729: - u  - The Vec to store the condition in which will be used in TSSolve()

    3731:   Level: advanced

    3733: .seealso: TSGetComputeInitialCondition(), TSSetComputeInitialCondition(), TSSolve()
    3734: @*/
    3735: PetscErrorCode TSComputeInitialCondition(TS ts, Vec u)
    3736: {

    3742:   if (ts->ops->initcondition) {(*ts->ops->initcondition)(ts, u);}
    3743:   return(0);
    3744: }

    3746: /*@C
    3747:   TSGetComputeExactError - Get the function used to automatically compute the exact error for the timestepping.

    3749:   Not collective

    3751:   Input Parameter:
    3752: . ts         - time stepping context

    3754:   Output Parameter:
    3755: . exactError - The function which computes the solution error

    3757:   Level: advanced

    3759:   Calling sequence for exactError:
    3760: $ PetscErrorCode exactError(TS ts, Vec u)

    3762: + ts - The timestepping context
    3763: . u  - The approximate solution vector
    3764: - e  - The input vector in which the error is stored

    3766: .seealso: TSGetComputeExactError(), TSComputeExactError()
    3767: @*/
    3768: PetscErrorCode TSGetComputeExactError(TS ts, PetscErrorCode (**exactError)(TS, Vec, Vec))
    3769: {
    3773:   *exactError = ts->ops->exacterror;
    3774:   return(0);
    3775: }

    3777: /*@C
    3778:   TSSetComputeExactError - Set the function used to automatically compute the exact error for the timestepping.

    3780:   Logically collective on ts

    3782:   Input Parameters:
    3783: + ts         - time stepping context
    3784: - exactError - The function which computes the solution error

    3786:   Level: advanced

    3788:   Calling sequence for exactError:
    3789: $ PetscErrorCode exactError(TS ts, Vec u)

    3791: + ts - The timestepping context
    3792: . u  - The approximate solution vector
    3793: - e  - The input vector in which the error is stored

    3795: .seealso: TSGetComputeExactError(), TSComputeExactError()
    3796: @*/
    3797: PetscErrorCode TSSetComputeExactError(TS ts, PetscErrorCode (*exactError)(TS, Vec, Vec))
    3798: {
    3802:   ts->ops->exacterror = exactError;
    3803:   return(0);
    3804: }

    3806: /*@
    3807:   TSComputeExactError - Compute the solution error for the timestepping using the function previously set.

    3809:   Collective on ts

    3811:   Input Parameters:
    3812: + ts - time stepping context
    3813: . u  - The approximate solution
    3814: - e  - The Vec used to store the error

    3816:   Level: advanced

    3818: .seealso: TSGetComputeInitialCondition(), TSSetComputeInitialCondition(), TSSolve()
    3819: @*/
    3820: PetscErrorCode TSComputeExactError(TS ts, Vec u, Vec e)
    3821: {

    3828:   if (ts->ops->exacterror) {(*ts->ops->exacterror)(ts, u, e);}
    3829:   return(0);
    3830: }

    3832: /*@
    3833:    TSSolve - Steps the requested number of timesteps.

    3835:    Collective on TS

    3837:    Input Parameters:
    3838: +  ts - the TS context obtained from TSCreate()
    3839: -  u - the solution vector  (can be null if TSSetSolution() was used and TSSetExactFinalTime(ts,TS_EXACTFINALTIME_MATCHSTEP) was not used,
    3840:                              otherwise must contain the initial conditions and will contain the solution at the final requested time

    3842:    Level: beginner

    3844:    Notes:
    3845:    The final time returned by this function may be different from the time of the internally
    3846:    held state accessible by TSGetSolution() and TSGetTime() because the method may have
    3847:    stepped over the final time.

    3849: .seealso: TSCreate(), TSSetSolution(), TSStep(), TSGetTime(), TSGetSolveTime()
    3850: @*/
    3851: PetscErrorCode TSSolve(TS ts,Vec u)
    3852: {
    3853:   Vec               solution;
    3854:   PetscErrorCode    ierr;

    3860:   TSSetExactFinalTimeDefault(ts);
    3861:   if (ts->exact_final_time == TS_EXACTFINALTIME_INTERPOLATE && u) {   /* Need ts->vec_sol to be distinct so it is not overwritten when we interpolate at the end */
    3862:     if (!ts->vec_sol || u == ts->vec_sol) {
    3863:       VecDuplicate(u,&solution);
    3864:       TSSetSolution(ts,solution);
    3865:       VecDestroy(&solution); /* grant ownership */
    3866:     }
    3867:     VecCopy(u,ts->vec_sol);
    3868:     if (ts->forward_solve) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Sensitivity analysis does not support the mode TS_EXACTFINALTIME_INTERPOLATE");
    3869:   } else if (u) {
    3870:     TSSetSolution(ts,u);
    3871:   }
    3872:   TSSetUp(ts);
    3873:   TSTrajectorySetUp(ts->trajectory,ts);

    3875:   if (ts->max_time >= PETSC_MAX_REAL && ts->max_steps == PETSC_MAX_INT) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"You must call TSSetMaxTime() or TSSetMaxSteps(), or use -ts_max_time <time> or -ts_max_steps <steps>");
    3876:   if (ts->exact_final_time == TS_EXACTFINALTIME_UNSPECIFIED) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"You must call TSSetExactFinalTime() or use -ts_exact_final_time <stepover,interpolate,matchstep> before calling TSSolve()");
    3877:   if (ts->exact_final_time == TS_EXACTFINALTIME_MATCHSTEP && !ts->adapt) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Since TS is not adaptive you cannot use TS_EXACTFINALTIME_MATCHSTEP, suggest TS_EXACTFINALTIME_INTERPOLATE");

    3879:   if (ts->forward_solve) {
    3880:     TSForwardSetUp(ts);
    3881:   }

    3883:   /* reset number of steps only when the step is not restarted. ARKIMEX
    3884:      restarts the step after an event. Resetting these counters in such case causes
    3885:      TSTrajectory to incorrectly save the output files
    3886:   */
    3887:   /* reset time step and iteration counters */
    3888:   if (!ts->steps) {
    3889:     ts->ksp_its           = 0;
    3890:     ts->snes_its          = 0;
    3891:     ts->num_snes_failures = 0;
    3892:     ts->reject            = 0;
    3893:     ts->steprestart       = PETSC_TRUE;
    3894:     ts->steprollback      = PETSC_FALSE;
    3895:     ts->rhsjacobian.time  = PETSC_MIN_REAL;
    3896:   }

    3898:   /* make sure initial time step does not overshoot final time */
    3899:   if (ts->exact_final_time == TS_EXACTFINALTIME_MATCHSTEP) {
    3900:     PetscReal maxdt = ts->max_time-ts->ptime;
    3901:     PetscReal dt = ts->time_step;

    3903:     ts->time_step = dt >= maxdt ? maxdt : (PetscIsCloseAtTol(dt,maxdt,10*PETSC_MACHINE_EPSILON,0) ? maxdt : dt);
    3904:   }
    3905:   ts->reason = TS_CONVERGED_ITERATING;

    3907:   {
    3908:     PetscViewer       viewer;
    3909:     PetscViewerFormat format;
    3910:     PetscBool         flg;
    3911:     static PetscBool  incall = PETSC_FALSE;

    3913:     if (!incall) {
    3914:       /* Estimate the convergence rate of the time discretization */
    3915:       PetscOptionsGetViewer(PetscObjectComm((PetscObject) ts),((PetscObject)ts)->options, ((PetscObject) ts)->prefix, "-ts_convergence_estimate", &viewer, &format, &flg);
    3916:       if (flg) {
    3917:         PetscConvEst conv;
    3918:         DM           dm;
    3919:         PetscReal   *alpha; /* Convergence rate of the solution error for each field in the L_2 norm */
    3920:         PetscInt     Nf;
    3921:         PetscBool    checkTemporal = PETSC_TRUE;

    3923:         incall = PETSC_TRUE;
    3924:         PetscOptionsGetBool(((PetscObject)ts)->options, ((PetscObject) ts)->prefix, "-ts_convergence_temporal", &checkTemporal, &flg);
    3925:         TSGetDM(ts, &dm);
    3926:         DMGetNumFields(dm, &Nf);
    3927:         PetscCalloc1(PetscMax(Nf, 1), &alpha);
    3928:         PetscConvEstCreate(PetscObjectComm((PetscObject) ts), &conv);
    3929:         PetscConvEstUseTS(conv, checkTemporal);
    3930:         PetscConvEstSetSolver(conv, (PetscObject) ts);
    3931:         PetscConvEstSetFromOptions(conv);
    3932:         PetscConvEstSetUp(conv);
    3933:         PetscConvEstGetConvRate(conv, alpha);
    3934:         PetscViewerPushFormat(viewer, format);
    3935:         PetscConvEstRateView(conv, alpha, viewer);
    3936:         PetscViewerPopFormat(viewer);
    3937:         PetscViewerDestroy(&viewer);
    3938:         PetscConvEstDestroy(&conv);
    3939:         PetscFree(alpha);
    3940:         incall = PETSC_FALSE;
    3941:       }
    3942:     }
    3943:   }

    3945:   TSViewFromOptions(ts,NULL,"-ts_view_pre");

    3947:   if (ts->ops->solve) { /* This private interface is transitional and should be removed when all implementations are updated. */
    3948:     (*ts->ops->solve)(ts);
    3949:     if (u) {VecCopy(ts->vec_sol,u);}
    3950:     ts->solvetime = ts->ptime;
    3951:     solution = ts->vec_sol;
    3952:   } else { /* Step the requested number of timesteps. */
    3953:     if (ts->steps >= ts->max_steps) ts->reason = TS_CONVERGED_ITS;
    3954:     else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME;

    3956:     if (!ts->steps) {
    3957:       TSTrajectorySet(ts->trajectory,ts,ts->steps,ts->ptime,ts->vec_sol);
    3958:       TSEventInitialize(ts->event,ts,ts->ptime,ts->vec_sol);
    3959:     }

    3961:     while (!ts->reason) {
    3962:       TSMonitor(ts,ts->steps,ts->ptime,ts->vec_sol);
    3963:       if (!ts->steprollback) {
    3964:         TSPreStep(ts);
    3965:       }
    3966:       TSStep(ts);
    3967:       if (ts->testjacobian) {
    3968:         TSRHSJacobianTest(ts,NULL);
    3969:       }
    3970:       if (ts->testjacobiantranspose) {
    3971:         TSRHSJacobianTestTranspose(ts,NULL);
    3972:       }
    3973:       if (ts->quadraturets && ts->costintegralfwd) { /* Must evaluate the cost integral before event is handled. The cost integral value can also be rolled back. */
    3974:         if (ts->reason >= 0) ts->steps--; /* Revert the step number changed by TSStep() */
    3975:         TSForwardCostIntegral(ts);
    3976:         if (ts->reason >= 0) ts->steps++;
    3977:       }
    3978:       if (ts->forward_solve) { /* compute forward sensitivities before event handling because postevent() may change RHS and jump conditions may have to be applied */
    3979:         if (ts->reason >= 0) ts->steps--; /* Revert the step number changed by TSStep() */
    3980:         TSForwardStep(ts);
    3981:         if (ts->reason >= 0) ts->steps++;
    3982:       }
    3983:       TSPostEvaluate(ts);
    3984:       TSEventHandler(ts); /* The right-hand side may be changed due to event. Be careful with Any computation using the RHS information after this point. */
    3985:       if (ts->steprollback) {
    3986:         TSPostEvaluate(ts);
    3987:       }
    3988:       if (!ts->steprollback) {
    3989:         TSTrajectorySet(ts->trajectory,ts,ts->steps,ts->ptime,ts->vec_sol);
    3990:         TSPostStep(ts);
    3991:       }
    3992:     }
    3993:     TSMonitor(ts,ts->steps,ts->ptime,ts->vec_sol);

    3995:     if (ts->exact_final_time == TS_EXACTFINALTIME_INTERPOLATE && ts->ptime > ts->max_time) {
    3996:       TSInterpolate(ts,ts->max_time,u);
    3997:       ts->solvetime = ts->max_time;
    3998:       solution = u;
    3999:       TSMonitor(ts,-1,ts->solvetime,solution);
    4000:     } else {
    4001:       if (u) {VecCopy(ts->vec_sol,u);}
    4002:       ts->solvetime = ts->ptime;
    4003:       solution = ts->vec_sol;
    4004:     }
    4005:   }

    4007:   TSViewFromOptions(ts,NULL,"-ts_view");
    4008:   VecViewFromOptions(solution,(PetscObject)ts,"-ts_view_solution");
    4009:   PetscObjectSAWsBlock((PetscObject)ts);
    4010:   if (ts->adjoint_solve) {
    4011:     TSAdjointSolve(ts);
    4012:   }
    4013:   return(0);
    4014: }

    4016: /*@
    4017:    TSGetTime - Gets the time of the most recently completed step.

    4019:    Not Collective

    4021:    Input Parameter:
    4022: .  ts - the TS context obtained from TSCreate()

    4024:    Output Parameter:
    4025: .  t  - the current time. This time may not corresponds to the final time set with TSSetMaxTime(), use TSGetSolveTime().

    4027:    Level: beginner

    4029:    Note:
    4030:    When called during time step evaluation (e.g. during residual evaluation or via hooks set using TSSetPreStep(),
    4031:    TSSetPreStage(), TSSetPostStage(), or TSSetPostStep()), the time is the time at the start of the step being evaluated.

    4033: .seealso:  TSGetSolveTime(), TSSetTime(), TSGetTimeStep(), TSGetStepNumber()

    4035: @*/
    4036: PetscErrorCode  TSGetTime(TS ts,PetscReal *t)
    4037: {
    4041:   *t = ts->ptime;
    4042:   return(0);
    4043: }

    4045: /*@
    4046:    TSGetPrevTime - Gets the starting time of the previously completed step.

    4048:    Not Collective

    4050:    Input Parameter:
    4051: .  ts - the TS context obtained from TSCreate()

    4053:    Output Parameter:
    4054: .  t  - the previous time

    4056:    Level: beginner

    4058: .seealso: TSGetTime(), TSGetSolveTime(), TSGetTimeStep()

    4060: @*/
    4061: PetscErrorCode  TSGetPrevTime(TS ts,PetscReal *t)
    4062: {
    4066:   *t = ts->ptime_prev;
    4067:   return(0);
    4068: }

    4070: /*@
    4071:    TSSetTime - Allows one to reset the time.

    4073:    Logically Collective on TS

    4075:    Input Parameters:
    4076: +  ts - the TS context obtained from TSCreate()
    4077: -  time - the time

    4079:    Level: intermediate

    4081: .seealso: TSGetTime(), TSSetMaxSteps()

    4083: @*/
    4084: PetscErrorCode  TSSetTime(TS ts, PetscReal t)
    4085: {
    4089:   ts->ptime = t;
    4090:   return(0);
    4091: }

    4093: /*@C
    4094:    TSSetOptionsPrefix - Sets the prefix used for searching for all
    4095:    TS options in the database.

    4097:    Logically Collective on TS

    4099:    Input Parameters:
    4100: +  ts     - The TS context
    4101: -  prefix - The prefix to prepend to all option names

    4103:    Notes:
    4104:    A hyphen (-) must NOT be given at the beginning of the prefix name.
    4105:    The first character of all runtime options is AUTOMATICALLY the
    4106:    hyphen.

    4108:    Level: advanced

    4110: .seealso: TSSetFromOptions()

    4112: @*/
    4113: PetscErrorCode  TSSetOptionsPrefix(TS ts,const char prefix[])
    4114: {
    4116:   SNES           snes;

    4120:   PetscObjectSetOptionsPrefix((PetscObject)ts,prefix);
    4121:   TSGetSNES(ts,&snes);
    4122:   SNESSetOptionsPrefix(snes,prefix);
    4123:   return(0);
    4124: }

    4126: /*@C
    4127:    TSAppendOptionsPrefix - Appends to the prefix used for searching for all
    4128:    TS options in the database.

    4130:    Logically Collective on TS

    4132:    Input Parameters:
    4133: +  ts     - The TS context
    4134: -  prefix - The prefix to prepend to all option names

    4136:    Notes:
    4137:    A hyphen (-) must NOT be given at the beginning of the prefix name.
    4138:    The first character of all runtime options is AUTOMATICALLY the
    4139:    hyphen.

    4141:    Level: advanced

    4143: .seealso: TSGetOptionsPrefix()

    4145: @*/
    4146: PetscErrorCode  TSAppendOptionsPrefix(TS ts,const char prefix[])
    4147: {
    4149:   SNES           snes;

    4153:   PetscObjectAppendOptionsPrefix((PetscObject)ts,prefix);
    4154:   TSGetSNES(ts,&snes);
    4155:   SNESAppendOptionsPrefix(snes,prefix);
    4156:   return(0);
    4157: }

    4159: /*@C
    4160:    TSGetOptionsPrefix - Sets the prefix used for searching for all
    4161:    TS options in the database.

    4163:    Not Collective

    4165:    Input Parameter:
    4166: .  ts - The TS context

    4168:    Output Parameter:
    4169: .  prefix - A pointer to the prefix string used

    4171:    Notes:
    4172:     On the fortran side, the user should pass in a string 'prifix' of
    4173:    sufficient length to hold the prefix.

    4175:    Level: intermediate

    4177: .seealso: TSAppendOptionsPrefix()
    4178: @*/
    4179: PetscErrorCode  TSGetOptionsPrefix(TS ts,const char *prefix[])
    4180: {

    4186:   PetscObjectGetOptionsPrefix((PetscObject)ts,prefix);
    4187:   return(0);
    4188: }

    4190: /*@C
    4191:    TSGetRHSJacobian - Returns the Jacobian J at the present timestep.

    4193:    Not Collective, but parallel objects are returned if TS is parallel

    4195:    Input Parameter:
    4196: .  ts  - The TS context obtained from TSCreate()

    4198:    Output Parameters:
    4199: +  Amat - The (approximate) Jacobian J of G, where U_t = G(U,t)  (or NULL)
    4200: .  Pmat - The matrix from which the preconditioner is constructed, usually the same as Amat  (or NULL)
    4201: .  func - Function to compute the Jacobian of the RHS  (or NULL)
    4202: -  ctx - User-defined context for Jacobian evaluation routine  (or NULL)

    4204:    Notes:
    4205:     You can pass in NULL for any return argument you do not need.

    4207:    Level: intermediate

    4209: .seealso: TSGetTimeStep(), TSGetMatrices(), TSGetTime(), TSGetStepNumber()

    4211: @*/
    4212: PetscErrorCode  TSGetRHSJacobian(TS ts,Mat *Amat,Mat *Pmat,TSRHSJacobian *func,void **ctx)
    4213: {
    4215:   DM             dm;

    4218:   if (Amat || Pmat) {
    4219:     SNES snes;
    4220:     TSGetSNES(ts,&snes);
    4221:     SNESSetUpMatrices(snes);
    4222:     SNESGetJacobian(snes,Amat,Pmat,NULL,NULL);
    4223:   }
    4224:   TSGetDM(ts,&dm);
    4225:   DMTSGetRHSJacobian(dm,func,ctx);
    4226:   return(0);
    4227: }

    4229: /*@C
    4230:    TSGetIJacobian - Returns the implicit Jacobian at the present timestep.

    4232:    Not Collective, but parallel objects are returned if TS is parallel

    4234:    Input Parameter:
    4235: .  ts  - The TS context obtained from TSCreate()

    4237:    Output Parameters:
    4238: +  Amat  - The (approximate) Jacobian of F(t,U,U_t)
    4239: .  Pmat - The matrix from which the preconditioner is constructed, often the same as Amat
    4240: .  f   - The function to compute the matrices
    4241: - ctx - User-defined context for Jacobian evaluation routine

    4243:    Notes:
    4244:     You can pass in NULL for any return argument you do not need.

    4246:    Level: advanced

    4248: .seealso: TSGetTimeStep(), TSGetRHSJacobian(), TSGetMatrices(), TSGetTime(), TSGetStepNumber()

    4250: @*/
    4251: PetscErrorCode  TSGetIJacobian(TS ts,Mat *Amat,Mat *Pmat,TSIJacobian *f,void **ctx)
    4252: {
    4254:   DM             dm;

    4257:   if (Amat || Pmat) {
    4258:     SNES snes;
    4259:     TSGetSNES(ts,&snes);
    4260:     SNESSetUpMatrices(snes);
    4261:     SNESGetJacobian(snes,Amat,Pmat,NULL,NULL);
    4262:   }
    4263:   TSGetDM(ts,&dm);
    4264:   DMTSGetIJacobian(dm,f,ctx);
    4265:   return(0);
    4266: }

    4268: #include <petsc/private/dmimpl.h>
    4269: /*@
    4270:    TSSetDM - Sets the DM that may be used by some nonlinear solvers or preconditioners under the TS

    4272:    Logically Collective on ts

    4274:    Input Parameters:
    4275: +  ts - the ODE integrator object
    4276: -  dm - the dm, cannot be NULL

    4278:    Notes:
    4279:    A DM can only be used for solving one problem at a time because information about the problem is stored on the DM,
    4280:    even when not using interfaces like DMTSSetIFunction().  Use DMClone() to get a distinct DM when solving
    4281:    different problems using the same function space.

    4283:    Level: intermediate

    4285: .seealso: TSGetDM(), SNESSetDM(), SNESGetDM()
    4286: @*/
    4287: PetscErrorCode  TSSetDM(TS ts,DM dm)
    4288: {
    4290:   SNES           snes;
    4291:   DMTS           tsdm;

    4296:   PetscObjectReference((PetscObject)dm);
    4297:   if (ts->dm) {               /* Move the DMTS context over to the new DM unless the new DM already has one */
    4298:     if (ts->dm->dmts && !dm->dmts) {
    4299:       DMCopyDMTS(ts->dm,dm);
    4300:       DMGetDMTS(ts->dm,&tsdm);
    4301:       if (tsdm->originaldm == ts->dm) { /* Grant write privileges to the replacement DM */
    4302:         tsdm->originaldm = dm;
    4303:       }
    4304:     }
    4305:     DMDestroy(&ts->dm);
    4306:   }
    4307:   ts->dm = dm;

    4309:   TSGetSNES(ts,&snes);
    4310:   SNESSetDM(snes,dm);
    4311:   return(0);
    4312: }

    4314: /*@
    4315:    TSGetDM - Gets the DM that may be used by some preconditioners

    4317:    Not Collective

    4319:    Input Parameter:
    4320: . ts - the preconditioner context

    4322:    Output Parameter:
    4323: .  dm - the dm

    4325:    Level: intermediate

    4327: .seealso: TSSetDM(), SNESSetDM(), SNESGetDM()
    4328: @*/
    4329: PetscErrorCode  TSGetDM(TS ts,DM *dm)
    4330: {

    4335:   if (!ts->dm) {
    4336:     DMShellCreate(PetscObjectComm((PetscObject)ts),&ts->dm);
    4337:     if (ts->snes) {SNESSetDM(ts->snes,ts->dm);}
    4338:   }
    4339:   *dm = ts->dm;
    4340:   return(0);
    4341: }

    4343: /*@
    4344:    SNESTSFormFunction - Function to evaluate nonlinear residual

    4346:    Logically Collective on SNES

    4348:    Input Parameters:
    4349: + snes - nonlinear solver
    4350: . U - the current state at which to evaluate the residual
    4351: - ctx - user context, must be a TS

    4353:    Output Parameter:
    4354: . F - the nonlinear residual

    4356:    Notes:
    4357:    This function is not normally called by users and is automatically registered with the SNES used by TS.
    4358:    It is most frequently passed to MatFDColoringSetFunction().

    4360:    Level: advanced

    4362: .seealso: SNESSetFunction(), MatFDColoringSetFunction()
    4363: @*/
    4364: PetscErrorCode  SNESTSFormFunction(SNES snes,Vec U,Vec F,void *ctx)
    4365: {
    4366:   TS             ts = (TS)ctx;

    4374:   (ts->ops->snesfunction)(snes,U,F,ts);
    4375:   return(0);
    4376: }

    4378: /*@
    4379:    SNESTSFormJacobian - Function to evaluate the Jacobian

    4381:    Collective on SNES

    4383:    Input Parameters:
    4384: + snes - nonlinear solver
    4385: . U - the current state at which to evaluate the residual
    4386: - ctx - user context, must be a TS

    4388:    Output Parameters:
    4389: + A - the Jacobian
    4390: - B - the preconditioning matrix (may be the same as A)

    4392:    Notes:
    4393:    This function is not normally called by users and is automatically registered with the SNES used by TS.

    4395:    Level: developer

    4397: .seealso: SNESSetJacobian()
    4398: @*/
    4399: PetscErrorCode  SNESTSFormJacobian(SNES snes,Vec U,Mat A,Mat B,void *ctx)
    4400: {
    4401:   TS             ts = (TS)ctx;

    4412:   (ts->ops->snesjacobian)(snes,U,A,B,ts);
    4413:   return(0);
    4414: }

    4416: /*@C
    4417:    TSComputeRHSFunctionLinear - Evaluate the right hand side via the user-provided Jacobian, for linear problems Udot = A U only

    4419:    Collective on TS

    4421:    Input Parameters:
    4422: +  ts - time stepping context
    4423: .  t - time at which to evaluate
    4424: .  U - state at which to evaluate
    4425: -  ctx - context

    4427:    Output Parameter:
    4428: .  F - right hand side

    4430:    Level: intermediate

    4432:    Notes:
    4433:    This function is intended to be passed to TSSetRHSFunction() to evaluate the right hand side for linear problems.
    4434:    The matrix (and optionally the evaluation context) should be passed to TSSetRHSJacobian().

    4436: .seealso: TSSetRHSFunction(), TSSetRHSJacobian(), TSComputeRHSJacobianConstant()
    4437: @*/
    4438: PetscErrorCode TSComputeRHSFunctionLinear(TS ts,PetscReal t,Vec U,Vec F,void *ctx)
    4439: {
    4441:   Mat            Arhs,Brhs;

    4444:   TSGetRHSMats_Private(ts,&Arhs,&Brhs);
    4445:   /* undo the damage caused by shifting */
    4446:   TSRecoverRHSJacobian(ts,Arhs,Brhs);
    4447:   TSComputeRHSJacobian(ts,t,U,Arhs,Brhs);
    4448:   MatMult(Arhs,U,F);
    4449:   return(0);
    4450: }

    4452: /*@C
    4453:    TSComputeRHSJacobianConstant - Reuses a Jacobian that is time-independent.

    4455:    Collective on TS

    4457:    Input Parameters:
    4458: +  ts - time stepping context
    4459: .  t - time at which to evaluate
    4460: .  U - state at which to evaluate
    4461: -  ctx - context

    4463:    Output Parameters:
    4464: +  A - pointer to operator
    4465: -  B - pointer to preconditioning matrix

    4467:    Level: intermediate

    4469:    Notes:
    4470:    This function is intended to be passed to TSSetRHSJacobian() to evaluate the Jacobian for linear time-independent problems.

    4472: .seealso: TSSetRHSFunction(), TSSetRHSJacobian(), TSComputeRHSFunctionLinear()
    4473: @*/
    4474: PetscErrorCode TSComputeRHSJacobianConstant(TS ts,PetscReal t,Vec U,Mat A,Mat B,void *ctx)
    4475: {
    4477:   return(0);
    4478: }

    4480: /*@C
    4481:    TSComputeIFunctionLinear - Evaluate the left hand side via the user-provided Jacobian, for linear problems only

    4483:    Collective on TS

    4485:    Input Parameters:
    4486: +  ts - time stepping context
    4487: .  t - time at which to evaluate
    4488: .  U - state at which to evaluate
    4489: .  Udot - time derivative of state vector
    4490: -  ctx - context

    4492:    Output Parameter:
    4493: .  F - left hand side

    4495:    Level: intermediate

    4497:    Notes:
    4498:    The assumption here is that the left hand side is of the form A*Udot (and not A*Udot + B*U). For other cases, the
    4499:    user is required to write their own TSComputeIFunction.
    4500:    This function is intended to be passed to TSSetIFunction() to evaluate the left hand side for linear problems.
    4501:    The matrix (and optionally the evaluation context) should be passed to TSSetIJacobian().

    4503:    Note that using this function is NOT equivalent to using TSComputeRHSFunctionLinear() since that solves Udot = A U

    4505: .seealso: TSSetIFunction(), TSSetIJacobian(), TSComputeIJacobianConstant(), TSComputeRHSFunctionLinear()
    4506: @*/
    4507: PetscErrorCode TSComputeIFunctionLinear(TS ts,PetscReal t,Vec U,Vec Udot,Vec F,void *ctx)
    4508: {
    4510:   Mat            A,B;

    4513:   TSGetIJacobian(ts,&A,&B,NULL,NULL);
    4514:   TSComputeIJacobian(ts,t,U,Udot,1.0,A,B,PETSC_TRUE);
    4515:   MatMult(A,Udot,F);
    4516:   return(0);
    4517: }

    4519: /*@C
    4520:    TSComputeIJacobianConstant - Reuses a time-independent for a semi-implicit DAE or ODE

    4522:    Collective on TS

    4524:    Input Parameters:
    4525: +  ts - time stepping context
    4526: .  t - time at which to evaluate
    4527: .  U - state at which to evaluate
    4528: .  Udot - time derivative of state vector
    4529: .  shift - shift to apply
    4530: -  ctx - context

    4532:    Output Parameters:
    4533: +  A - pointer to operator
    4534: -  B - pointer to preconditioning matrix

    4536:    Level: advanced

    4538:    Notes:
    4539:    This function is intended to be passed to TSSetIJacobian() to evaluate the Jacobian for linear time-independent problems.

    4541:    It is only appropriate for problems of the form

    4543: $     M Udot = F(U,t)

    4545:   where M is constant and F is non-stiff.  The user must pass M to TSSetIJacobian().  The current implementation only
    4546:   works with IMEX time integration methods such as TSROSW and TSARKIMEX, since there is no support for de-constructing
    4547:   an implicit operator of the form

    4549: $    shift*M + J

    4551:   where J is the Jacobian of -F(U).  Support may be added in a future version of PETSc, but for now, the user must store
    4552:   a copy of M or reassemble it when requested.

    4554: .seealso: TSSetIFunction(), TSSetIJacobian(), TSComputeIFunctionLinear()
    4555: @*/
    4556: PetscErrorCode TSComputeIJacobianConstant(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat A,Mat B,void *ctx)
    4557: {

    4561:   MatScale(A, shift / ts->ijacobian.shift);
    4562:   ts->ijacobian.shift = shift;
    4563:   return(0);
    4564: }

    4566: /*@
    4567:    TSGetEquationType - Gets the type of the equation that TS is solving.

    4569:    Not Collective

    4571:    Input Parameter:
    4572: .  ts - the TS context

    4574:    Output Parameter:
    4575: .  equation_type - see TSEquationType

    4577:    Level: beginner

    4579: .seealso: TSSetEquationType(), TSEquationType
    4580: @*/
    4581: PetscErrorCode  TSGetEquationType(TS ts,TSEquationType *equation_type)
    4582: {
    4586:   *equation_type = ts->equation_type;
    4587:   return(0);
    4588: }

    4590: /*@
    4591:    TSSetEquationType - Sets the type of the equation that TS is solving.

    4593:    Not Collective

    4595:    Input Parameters:
    4596: +  ts - the TS context
    4597: -  equation_type - see TSEquationType

    4599:    Level: advanced

    4601: .seealso: TSGetEquationType(), TSEquationType
    4602: @*/
    4603: PetscErrorCode  TSSetEquationType(TS ts,TSEquationType equation_type)
    4604: {
    4607:   ts->equation_type = equation_type;
    4608:   return(0);
    4609: }

    4611: /*@
    4612:    TSGetConvergedReason - Gets the reason the TS iteration was stopped.

    4614:    Not Collective

    4616:    Input Parameter:
    4617: .  ts - the TS context

    4619:    Output Parameter:
    4620: .  reason - negative value indicates diverged, positive value converged, see TSConvergedReason or the
    4621:             manual pages for the individual convergence tests for complete lists

    4623:    Level: beginner

    4625:    Notes:
    4626:    Can only be called after the call to TSSolve() is complete.

    4628: .seealso: TSSetConvergenceTest(), TSConvergedReason
    4629: @*/
    4630: PetscErrorCode  TSGetConvergedReason(TS ts,TSConvergedReason *reason)
    4631: {
    4635:   *reason = ts->reason;
    4636:   return(0);
    4637: }

    4639: /*@
    4640:    TSSetConvergedReason - Sets the reason for handling the convergence of TSSolve.

    4642:    Logically Collective; reason must contain common value

    4644:    Input Parameters:
    4645: +  ts - the TS context
    4646: -  reason - negative value indicates diverged, positive value converged, see TSConvergedReason or the
    4647:             manual pages for the individual convergence tests for complete lists

    4649:    Level: advanced

    4651:    Notes:
    4652:    Can only be called while TSSolve() is active.

    4654: .seealso: TSConvergedReason
    4655: @*/
    4656: PetscErrorCode  TSSetConvergedReason(TS ts,TSConvergedReason reason)
    4657: {
    4660:   ts->reason = reason;
    4661:   return(0);
    4662: }

    4664: /*@
    4665:    TSGetSolveTime - Gets the time after a call to TSSolve()

    4667:    Not Collective

    4669:    Input Parameter:
    4670: .  ts - the TS context

    4672:    Output Parameter:
    4673: .  ftime - the final time. This time corresponds to the final time set with TSSetMaxTime()

    4675:    Level: beginner

    4677:    Notes:
    4678:    Can only be called after the call to TSSolve() is complete.

    4680: .seealso: TSSetConvergenceTest(), TSConvergedReason
    4681: @*/
    4682: PetscErrorCode  TSGetSolveTime(TS ts,PetscReal *ftime)
    4683: {
    4687:   *ftime = ts->solvetime;
    4688:   return(0);
    4689: }

    4691: /*@
    4692:    TSGetSNESIterations - Gets the total number of nonlinear iterations
    4693:    used by the time integrator.

    4695:    Not Collective

    4697:    Input Parameter:
    4698: .  ts - TS context

    4700:    Output Parameter:
    4701: .  nits - number of nonlinear iterations

    4703:    Notes:
    4704:    This counter is reset to zero for each successive call to TSSolve().

    4706:    Level: intermediate

    4708: .seealso:  TSGetKSPIterations()
    4709: @*/
    4710: PetscErrorCode TSGetSNESIterations(TS ts,PetscInt *nits)
    4711: {
    4715:   *nits = ts->snes_its;
    4716:   return(0);
    4717: }

    4719: /*@
    4720:    TSGetKSPIterations - Gets the total number of linear iterations
    4721:    used by the time integrator.

    4723:    Not Collective

    4725:    Input Parameter:
    4726: .  ts - TS context

    4728:    Output Parameter:
    4729: .  lits - number of linear iterations

    4731:    Notes:
    4732:    This counter is reset to zero for each successive call to TSSolve().

    4734:    Level: intermediate

    4736: .seealso:  TSGetSNESIterations(), SNESGetKSPIterations()
    4737: @*/
    4738: PetscErrorCode TSGetKSPIterations(TS ts,PetscInt *lits)
    4739: {
    4743:   *lits = ts->ksp_its;
    4744:   return(0);
    4745: }

    4747: /*@
    4748:    TSGetStepRejections - Gets the total number of rejected steps.

    4750:    Not Collective

    4752:    Input Parameter:
    4753: .  ts - TS context

    4755:    Output Parameter:
    4756: .  rejects - number of steps rejected

    4758:    Notes:
    4759:    This counter is reset to zero for each successive call to TSSolve().

    4761:    Level: intermediate

    4763: .seealso:  TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetSNESFailures(), TSSetMaxSNESFailures(), TSSetErrorIfStepFails()
    4764: @*/
    4765: PetscErrorCode TSGetStepRejections(TS ts,PetscInt *rejects)
    4766: {
    4770:   *rejects = ts->reject;
    4771:   return(0);
    4772: }

    4774: /*@
    4775:    TSGetSNESFailures - Gets the total number of failed SNES solves

    4777:    Not Collective

    4779:    Input Parameter:
    4780: .  ts - TS context

    4782:    Output Parameter:
    4783: .  fails - number of failed nonlinear solves

    4785:    Notes:
    4786:    This counter is reset to zero for each successive call to TSSolve().

    4788:    Level: intermediate

    4790: .seealso:  TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSSetMaxSNESFailures()
    4791: @*/
    4792: PetscErrorCode TSGetSNESFailures(TS ts,PetscInt *fails)
    4793: {
    4797:   *fails = ts->num_snes_failures;
    4798:   return(0);
    4799: }

    4801: /*@
    4802:    TSSetMaxStepRejections - Sets the maximum number of step rejections before a step fails

    4804:    Not Collective

    4806:    Input Parameters:
    4807: +  ts - TS context
    4808: -  rejects - maximum number of rejected steps, pass -1 for unlimited

    4810:    Notes:
    4811:    The counter is reset to zero for each step

    4813:    Options Database Key:
    4814:  .  -ts_max_reject - Maximum number of step rejections before a step fails

    4816:    Level: intermediate

    4818: .seealso:  TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxSNESFailures(), TSGetStepRejections(), TSGetSNESFailures(), TSSetErrorIfStepFails(), TSGetConvergedReason()
    4819: @*/
    4820: PetscErrorCode TSSetMaxStepRejections(TS ts,PetscInt rejects)
    4821: {
    4824:   ts->max_reject = rejects;
    4825:   return(0);
    4826: }

    4828: /*@
    4829:    TSSetMaxSNESFailures - Sets the maximum number of failed SNES solves

    4831:    Not Collective

    4833:    Input Parameters:
    4834: +  ts - TS context
    4835: -  fails - maximum number of failed nonlinear solves, pass -1 for unlimited

    4837:    Notes:
    4838:    The counter is reset to zero for each successive call to TSSolve().

    4840:    Options Database Key:
    4841:  .  -ts_max_snes_failures - Maximum number of nonlinear solve failures

    4843:    Level: intermediate

    4845: .seealso:  TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSGetSNESFailures(), SNESGetConvergedReason(), TSGetConvergedReason()
    4846: @*/
    4847: PetscErrorCode TSSetMaxSNESFailures(TS ts,PetscInt fails)
    4848: {
    4851:   ts->max_snes_failures = fails;
    4852:   return(0);
    4853: }

    4855: /*@
    4856:    TSSetErrorIfStepFails - Error if no step succeeds

    4858:    Not Collective

    4860:    Input Parameters:
    4861: +  ts - TS context
    4862: -  err - PETSC_TRUE to error if no step succeeds, PETSC_FALSE to return without failure

    4864:    Options Database Key:
    4865:  .  -ts_error_if_step_fails - Error if no step succeeds

    4867:    Level: intermediate

    4869: .seealso:  TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSGetSNESFailures(), TSSetErrorIfStepFails(), TSGetConvergedReason()
    4870: @*/
    4871: PetscErrorCode TSSetErrorIfStepFails(TS ts,PetscBool err)
    4872: {
    4875:   ts->errorifstepfailed = err;
    4876:   return(0);
    4877: }

    4879: /*@
    4880:    TSGetAdapt - Get the adaptive controller context for the current method

    4882:    Collective on TS if controller has not been created yet

    4884:    Input Parameter:
    4885: .  ts - time stepping context

    4887:    Output Parameter:
    4888: .  adapt - adaptive controller

    4890:    Level: intermediate

    4892: .seealso: TSAdapt, TSAdaptSetType(), TSAdaptChoose()
    4893: @*/
    4894: PetscErrorCode TSGetAdapt(TS ts,TSAdapt *adapt)
    4895: {

    4901:   if (!ts->adapt) {
    4902:     TSAdaptCreate(PetscObjectComm((PetscObject)ts),&ts->adapt);
    4903:     PetscLogObjectParent((PetscObject)ts,(PetscObject)ts->adapt);
    4904:     PetscObjectIncrementTabLevel((PetscObject)ts->adapt,(PetscObject)ts,1);
    4905:   }
    4906:   *adapt = ts->adapt;
    4907:   return(0);
    4908: }

    4910: /*@
    4911:    TSSetTolerances - Set tolerances for local truncation error when using adaptive controller

    4913:    Logically Collective

    4915:    Input Parameters:
    4916: +  ts - time integration context
    4917: .  atol - scalar absolute tolerances, PETSC_DECIDE to leave current value
    4918: .  vatol - vector of absolute tolerances or NULL, used in preference to atol if present
    4919: .  rtol - scalar relative tolerances, PETSC_DECIDE to leave current value
    4920: -  vrtol - vector of relative tolerances or NULL, used in preference to atol if present

    4922:    Options Database keys:
    4923: +  -ts_rtol <rtol> - relative tolerance for local truncation error
    4924: -  -ts_atol <atol> Absolute tolerance for local truncation error

    4926:    Notes:
    4927:    With PETSc's implicit schemes for DAE problems, the calculation of the local truncation error
    4928:    (LTE) includes both the differential and the algebraic variables. If one wants the LTE to be
    4929:    computed only for the differential or the algebraic part then this can be done using the vector of
    4930:    tolerances vatol. For example, by setting the tolerance vector with the desired tolerance for the
    4931:    differential part and infinity for the algebraic part, the LTE calculation will include only the
    4932:    differential variables.

    4934:    Level: beginner

    4936: .seealso: TS, TSAdapt, TSErrorWeightedNorm(), TSGetTolerances()
    4937: @*/
    4938: PetscErrorCode TSSetTolerances(TS ts,PetscReal atol,Vec vatol,PetscReal rtol,Vec vrtol)
    4939: {

    4943:   if (atol != PETSC_DECIDE && atol != PETSC_DEFAULT) ts->atol = atol;
    4944:   if (vatol) {
    4945:     PetscObjectReference((PetscObject)vatol);
    4946:     VecDestroy(&ts->vatol);
    4947:     ts->vatol = vatol;
    4948:   }
    4949:   if (rtol != PETSC_DECIDE && rtol != PETSC_DEFAULT) ts->rtol = rtol;
    4950:   if (vrtol) {
    4951:     PetscObjectReference((PetscObject)vrtol);
    4952:     VecDestroy(&ts->vrtol);
    4953:     ts->vrtol = vrtol;
    4954:   }
    4955:   return(0);
    4956: }

    4958: /*@
    4959:    TSGetTolerances - Get tolerances for local truncation error when using adaptive controller

    4961:    Logically Collective

    4963:    Input Parameter:
    4964: .  ts - time integration context

    4966:    Output Parameters:
    4967: +  atol - scalar absolute tolerances, NULL to ignore
    4968: .  vatol - vector of absolute tolerances, NULL to ignore
    4969: .  rtol - scalar relative tolerances, NULL to ignore
    4970: -  vrtol - vector of relative tolerances, NULL to ignore

    4972:    Level: beginner

    4974: .seealso: TS, TSAdapt, TSErrorWeightedNorm(), TSSetTolerances()
    4975: @*/
    4976: PetscErrorCode TSGetTolerances(TS ts,PetscReal *atol,Vec *vatol,PetscReal *rtol,Vec *vrtol)
    4977: {
    4979:   if (atol)  *atol  = ts->atol;
    4980:   if (vatol) *vatol = ts->vatol;
    4981:   if (rtol)  *rtol  = ts->rtol;
    4982:   if (vrtol) *vrtol = ts->vrtol;
    4983:   return(0);
    4984: }

    4986: /*@
    4987:    TSErrorWeightedNorm2 - compute a weighted 2-norm of the difference between two state vectors

    4989:    Collective on TS

    4991:    Input Parameters:
    4992: +  ts - time stepping context
    4993: .  U - state vector, usually ts->vec_sol
    4994: -  Y - state vector to be compared to U

    4996:    Output Parameters:
    4997: +  norm - weighted norm, a value of 1.0 means that the error matches the tolerances
    4998: .  norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances
    4999: -  normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances

    5001:    Level: developer

    5003: .seealso: TSErrorWeightedNorm(), TSErrorWeightedNormInfinity()
    5004: @*/
    5005: PetscErrorCode TSErrorWeightedNorm2(TS ts,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr)
    5006: {
    5007:   PetscErrorCode    ierr;
    5008:   PetscInt          i,n,N,rstart;
    5009:   PetscInt          n_loc,na_loc,nr_loc;
    5010:   PetscReal         n_glb,na_glb,nr_glb;
    5011:   const PetscScalar *u,*y;
    5012:   PetscReal         sum,suma,sumr,gsum,gsuma,gsumr,diff;
    5013:   PetscReal         tol,tola,tolr;
    5014:   PetscReal         err_loc[6],err_glb[6];

    5026:   if (U == Y) SETERRQ(PetscObjectComm((PetscObject)U),PETSC_ERR_ARG_IDN,"U and Y cannot be the same vector");

    5028:   VecGetSize(U,&N);
    5029:   VecGetLocalSize(U,&n);
    5030:   VecGetOwnershipRange(U,&rstart,NULL);
    5031:   VecGetArrayRead(U,&u);
    5032:   VecGetArrayRead(Y,&y);
    5033:   sum  = 0.; n_loc  = 0;
    5034:   suma = 0.; na_loc = 0;
    5035:   sumr = 0.; nr_loc = 0;
    5036:   if (ts->vatol && ts->vrtol) {
    5037:     const PetscScalar *atol,*rtol;
    5038:     VecGetArrayRead(ts->vatol,&atol);
    5039:     VecGetArrayRead(ts->vrtol,&rtol);
    5040:     for (i=0; i<n; i++) {
    5041:       SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
    5042:       diff = PetscAbsScalar(y[i] - u[i]);
    5043:       tola = PetscRealPart(atol[i]);
    5044:       if (tola>0.) {
    5045:         suma  += PetscSqr(diff/tola);
    5046:         na_loc++;
    5047:       }
    5048:       tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
    5049:       if (tolr>0.) {
    5050:         sumr  += PetscSqr(diff/tolr);
    5051:         nr_loc++;
    5052:       }
    5053:       tol=tola+tolr;
    5054:       if (tol>0.) {
    5055:         sum  += PetscSqr(diff/tol);
    5056:         n_loc++;
    5057:       }
    5058:     }
    5059:     VecRestoreArrayRead(ts->vatol,&atol);
    5060:     VecRestoreArrayRead(ts->vrtol,&rtol);
    5061:   } else if (ts->vatol) {       /* vector atol, scalar rtol */
    5062:     const PetscScalar *atol;
    5063:     VecGetArrayRead(ts->vatol,&atol);
    5064:     for (i=0; i<n; i++) {
    5065:       SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
    5066:       diff = PetscAbsScalar(y[i] - u[i]);
    5067:       tola = PetscRealPart(atol[i]);
    5068:       if (tola>0.) {
    5069:         suma  += PetscSqr(diff/tola);
    5070:         na_loc++;
    5071:       }
    5072:       tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
    5073:       if (tolr>0.) {
    5074:         sumr  += PetscSqr(diff/tolr);
    5075:         nr_loc++;
    5076:       }
    5077:       tol=tola+tolr;
    5078:       if (tol>0.) {
    5079:         sum  += PetscSqr(diff/tol);
    5080:         n_loc++;
    5081:       }
    5082:     }
    5083:     VecRestoreArrayRead(ts->vatol,&atol);
    5084:   } else if (ts->vrtol) {       /* scalar atol, vector rtol */
    5085:     const PetscScalar *rtol;
    5086:     VecGetArrayRead(ts->vrtol,&rtol);
    5087:     for (i=0; i<n; i++) {
    5088:       SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
    5089:       diff = PetscAbsScalar(y[i] - u[i]);
    5090:       tola = ts->atol;
    5091:       if (tola>0.) {
    5092:         suma  += PetscSqr(diff/tola);
    5093:         na_loc++;
    5094:       }
    5095:       tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
    5096:       if (tolr>0.) {
    5097:         sumr  += PetscSqr(diff/tolr);
    5098:         nr_loc++;
    5099:       }
    5100:       tol=tola+tolr;
    5101:       if (tol>0.) {
    5102:         sum  += PetscSqr(diff/tol);
    5103:         n_loc++;
    5104:       }
    5105:     }
    5106:     VecRestoreArrayRead(ts->vrtol,&rtol);
    5107:   } else {                      /* scalar atol, scalar rtol */
    5108:     for (i=0; i<n; i++) {
    5109:       SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
    5110:       diff = PetscAbsScalar(y[i] - u[i]);
    5111:       tola = ts->atol;
    5112:       if (tola>0.) {
    5113:         suma  += PetscSqr(diff/tola);
    5114:         na_loc++;
    5115:       }
    5116:       tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
    5117:       if (tolr>0.) {
    5118:         sumr  += PetscSqr(diff/tolr);
    5119:         nr_loc++;
    5120:       }
    5121:       tol=tola+tolr;
    5122:       if (tol>0.) {
    5123:         sum  += PetscSqr(diff/tol);
    5124:         n_loc++;
    5125:       }
    5126:     }
    5127:   }
    5128:   VecRestoreArrayRead(U,&u);
    5129:   VecRestoreArrayRead(Y,&y);

    5131:   err_loc[0] = sum;
    5132:   err_loc[1] = suma;
    5133:   err_loc[2] = sumr;
    5134:   err_loc[3] = (PetscReal)n_loc;
    5135:   err_loc[4] = (PetscReal)na_loc;
    5136:   err_loc[5] = (PetscReal)nr_loc;

    5138:   MPIU_Allreduce(err_loc,err_glb,6,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)ts));

    5140:   gsum   = err_glb[0];
    5141:   gsuma  = err_glb[1];
    5142:   gsumr  = err_glb[2];
    5143:   n_glb  = err_glb[3];
    5144:   na_glb = err_glb[4];
    5145:   nr_glb = err_glb[5];

    5147:   *norm  = 0.;
    5148:   if (n_glb>0.) {*norm  = PetscSqrtReal(gsum  / n_glb);}
    5149:   *norma = 0.;
    5150:   if (na_glb>0.) {*norma = PetscSqrtReal(gsuma / na_glb);}
    5151:   *normr = 0.;
    5152:   if (nr_glb>0.) {*normr = PetscSqrtReal(gsumr / nr_glb);}

    5154:   if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm");
    5155:   if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma");
    5156:   if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr");
    5157:   return(0);
    5158: }

    5160: /*@
    5161:    TSErrorWeightedNormInfinity - compute a weighted infinity-norm of the difference between two state vectors

    5163:    Collective on TS

    5165:    Input Parameters:
    5166: +  ts - time stepping context
    5167: .  U - state vector, usually ts->vec_sol
    5168: -  Y - state vector to be compared to U

    5170:    Output Parameters:
    5171: +  norm - weighted norm, a value of 1.0 means that the error matches the tolerances
    5172: .  norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances
    5173: -  normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances

    5175:    Level: developer

    5177: .seealso: TSErrorWeightedNorm(), TSErrorWeightedNorm2()
    5178: @*/
    5179: PetscErrorCode TSErrorWeightedNormInfinity(TS ts,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr)
    5180: {
    5181:   PetscErrorCode    ierr;
    5182:   PetscInt          i,n,N,rstart;
    5183:   const PetscScalar *u,*y;
    5184:   PetscReal         max,gmax,maxa,gmaxa,maxr,gmaxr;
    5185:   PetscReal         tol,tola,tolr,diff;
    5186:   PetscReal         err_loc[3],err_glb[3];

    5198:   if (U == Y) SETERRQ(PetscObjectComm((PetscObject)U),PETSC_ERR_ARG_IDN,"U and Y cannot be the same vector");

    5200:   VecGetSize(U,&N);
    5201:   VecGetLocalSize(U,&n);
    5202:   VecGetOwnershipRange(U,&rstart,NULL);
    5203:   VecGetArrayRead(U,&u);
    5204:   VecGetArrayRead(Y,&y);

    5206:   max=0.;
    5207:   maxa=0.;
    5208:   maxr=0.;

    5210:   if (ts->vatol && ts->vrtol) {     /* vector atol, vector rtol */
    5211:     const PetscScalar *atol,*rtol;
    5212:     VecGetArrayRead(ts->vatol,&atol);
    5213:     VecGetArrayRead(ts->vrtol,&rtol);

    5215:     for (i=0; i<n; i++) {
    5216:       SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
    5217:       diff = PetscAbsScalar(y[i] - u[i]);
    5218:       tola = PetscRealPart(atol[i]);
    5219:       tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
    5220:       tol  = tola+tolr;
    5221:       if (tola>0.) {
    5222:         maxa = PetscMax(maxa,diff / tola);
    5223:       }
    5224:       if (tolr>0.) {
    5225:         maxr = PetscMax(maxr,diff / tolr);
    5226:       }
    5227:       if (tol>0.) {
    5228:         max = PetscMax(max,diff / tol);
    5229:       }
    5230:     }
    5231:     VecRestoreArrayRead(ts->vatol,&atol);
    5232:     VecRestoreArrayRead(ts->vrtol,&rtol);
    5233:   } else if (ts->vatol) {       /* vector atol, scalar rtol */
    5234:     const PetscScalar *atol;
    5235:     VecGetArrayRead(ts->vatol,&atol);
    5236:     for (i=0; i<n; i++) {
    5237:       SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
    5238:       diff = PetscAbsScalar(y[i] - u[i]);
    5239:       tola = PetscRealPart(atol[i]);
    5240:       tolr = ts->rtol  * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
    5241:       tol  = tola+tolr;
    5242:       if (tola>0.) {
    5243:         maxa = PetscMax(maxa,diff / tola);
    5244:       }
    5245:       if (tolr>0.) {
    5246:         maxr = PetscMax(maxr,diff / tolr);
    5247:       }
    5248:       if (tol>0.) {
    5249:         max = PetscMax(max,diff / tol);
    5250:       }
    5251:     }
    5252:     VecRestoreArrayRead(ts->vatol,&atol);
    5253:   } else if (ts->vrtol) {       /* scalar atol, vector rtol */
    5254:     const PetscScalar *rtol;
    5255:     VecGetArrayRead(ts->vrtol,&rtol);

    5257:     for (i=0; i<n; i++) {
    5258:       SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
    5259:       diff = PetscAbsScalar(y[i] - u[i]);
    5260:       tola = ts->atol;
    5261:       tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
    5262:       tol  = tola+tolr;
    5263:       if (tola>0.) {
    5264:         maxa = PetscMax(maxa,diff / tola);
    5265:       }
    5266:       if (tolr>0.) {
    5267:         maxr = PetscMax(maxr,diff / tolr);
    5268:       }
    5269:       if (tol>0.) {
    5270:         max = PetscMax(max,diff / tol);
    5271:       }
    5272:     }
    5273:     VecRestoreArrayRead(ts->vrtol,&rtol);
    5274:   } else {                      /* scalar atol, scalar rtol */

    5276:     for (i=0; i<n; i++) {
    5277:       SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
    5278:       diff = PetscAbsScalar(y[i] - u[i]);
    5279:       tola = ts->atol;
    5280:       tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
    5281:       tol  = tola+tolr;
    5282:       if (tola>0.) {
    5283:         maxa = PetscMax(maxa,diff / tola);
    5284:       }
    5285:       if (tolr>0.) {
    5286:         maxr = PetscMax(maxr,diff / tolr);
    5287:       }
    5288:       if (tol>0.) {
    5289:         max = PetscMax(max,diff / tol);
    5290:       }
    5291:     }
    5292:   }
    5293:   VecRestoreArrayRead(U,&u);
    5294:   VecRestoreArrayRead(Y,&y);
    5295:   err_loc[0] = max;
    5296:   err_loc[1] = maxa;
    5297:   err_loc[2] = maxr;
    5298:   MPIU_Allreduce(err_loc,err_glb,3,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)ts));
    5299:   gmax   = err_glb[0];
    5300:   gmaxa  = err_glb[1];
    5301:   gmaxr  = err_glb[2];

    5303:   *norm = gmax;
    5304:   *norma = gmaxa;
    5305:   *normr = gmaxr;
    5306:   if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm");
    5307:     if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma");
    5308:     if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr");
    5309:   return(0);
    5310: }

    5312: /*@
    5313:    TSErrorWeightedNorm - compute a weighted norm of the difference between two state vectors based on supplied absolute and relative tolerances

    5315:    Collective on TS

    5317:    Input Parameters:
    5318: +  ts - time stepping context
    5319: .  U - state vector, usually ts->vec_sol
    5320: .  Y - state vector to be compared to U
    5321: -  wnormtype - norm type, either NORM_2 or NORM_INFINITY

    5323:    Output Parameters:
    5324: +  norm  - weighted norm, a value of 1.0 achieves a balance between absolute and relative tolerances
    5325: .  norma - weighted norm, a value of 1.0 means that the error meets the absolute tolerance set by the user
    5326: -  normr - weighted norm, a value of 1.0 means that the error meets the relative tolerance set by the user

    5328:    Options Database Keys:
    5329: .  -ts_adapt_wnormtype <wnormtype> - 2, INFINITY

    5331:    Level: developer

    5333: .seealso: TSErrorWeightedNormInfinity(), TSErrorWeightedNorm2(), TSErrorWeightedENorm
    5334: @*/
    5335: PetscErrorCode TSErrorWeightedNorm(TS ts,Vec U,Vec Y,NormType wnormtype,PetscReal *norm,PetscReal *norma,PetscReal *normr)
    5336: {

    5340:   if (wnormtype == NORM_2) {
    5341:     TSErrorWeightedNorm2(ts,U,Y,norm,norma,normr);
    5342:   } else if (wnormtype == NORM_INFINITY) {
    5343:     TSErrorWeightedNormInfinity(ts,U,Y,norm,norma,normr);
    5344:   } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]);
    5345:   return(0);
    5346: }

    5348: /*@
    5349:    TSErrorWeightedENorm2 - compute a weighted 2 error norm based on supplied absolute and relative tolerances

    5351:    Collective on TS

    5353:    Input Parameters:
    5354: +  ts - time stepping context
    5355: .  E - error vector
    5356: .  U - state vector, usually ts->vec_sol
    5357: -  Y - state vector, previous time step

    5359:    Output Parameters:
    5360: +  norm - weighted norm, a value of 1.0 means that the error matches the tolerances
    5361: .  norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances
    5362: -  normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances

    5364:    Level: developer

    5366: .seealso: TSErrorWeightedENorm(), TSErrorWeightedENormInfinity()
    5367: @*/
    5368: PetscErrorCode TSErrorWeightedENorm2(TS ts,Vec E,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr)
    5369: {
    5370:   PetscErrorCode    ierr;
    5371:   PetscInt          i,n,N,rstart;
    5372:   PetscInt          n_loc,na_loc,nr_loc;
    5373:   PetscReal         n_glb,na_glb,nr_glb;
    5374:   const PetscScalar *e,*u,*y;
    5375:   PetscReal         err,sum,suma,sumr,gsum,gsuma,gsumr;
    5376:   PetscReal         tol,tola,tolr;
    5377:   PetscReal         err_loc[6],err_glb[6];

    5393:   VecGetSize(E,&N);
    5394:   VecGetLocalSize(E,&n);
    5395:   VecGetOwnershipRange(E,&rstart,NULL);
    5396:   VecGetArrayRead(E,&e);
    5397:   VecGetArrayRead(U,&u);
    5398:   VecGetArrayRead(Y,&y);
    5399:   sum  = 0.; n_loc  = 0;
    5400:   suma = 0.; na_loc = 0;
    5401:   sumr = 0.; nr_loc = 0;
    5402:   if (ts->vatol && ts->vrtol) {
    5403:     const PetscScalar *atol,*rtol;
    5404:     VecGetArrayRead(ts->vatol,&atol);
    5405:     VecGetArrayRead(ts->vrtol,&rtol);
    5406:     for (i=0; i<n; i++) {
    5407:       SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
    5408:       err = PetscAbsScalar(e[i]);
    5409:       tola = PetscRealPart(atol[i]);
    5410:       if (tola>0.) {
    5411:         suma  += PetscSqr(err/tola);
    5412:         na_loc++;
    5413:       }
    5414:       tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
    5415:       if (tolr>0.) {
    5416:         sumr  += PetscSqr(err/tolr);
    5417:         nr_loc++;
    5418:       }
    5419:       tol=tola+tolr;
    5420:       if (tol>0.) {
    5421:         sum  += PetscSqr(err/tol);
    5422:         n_loc++;
    5423:       }
    5424:     }
    5425:     VecRestoreArrayRead(ts->vatol,&atol);
    5426:     VecRestoreArrayRead(ts->vrtol,&rtol);
    5427:   } else if (ts->vatol) {       /* vector atol, scalar rtol */
    5428:     const PetscScalar *atol;
    5429:     VecGetArrayRead(ts->vatol,&atol);
    5430:     for (i=0; i<n; i++) {
    5431:       SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
    5432:       err = PetscAbsScalar(e[i]);
    5433:       tola = PetscRealPart(atol[i]);
    5434:       if (tola>0.) {
    5435:         suma  += PetscSqr(err/tola);
    5436:         na_loc++;
    5437:       }
    5438:       tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
    5439:       if (tolr>0.) {
    5440:         sumr  += PetscSqr(err/tolr);
    5441:         nr_loc++;
    5442:       }
    5443:       tol=tola+tolr;
    5444:       if (tol>0.) {
    5445:         sum  += PetscSqr(err/tol);
    5446:         n_loc++;
    5447:       }
    5448:     }
    5449:     VecRestoreArrayRead(ts->vatol,&atol);
    5450:   } else if (ts->vrtol) {       /* scalar atol, vector rtol */
    5451:     const PetscScalar *rtol;
    5452:     VecGetArrayRead(ts->vrtol,&rtol);
    5453:     for (i=0; i<n; i++) {
    5454:       SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
    5455:       err = PetscAbsScalar(e[i]);
    5456:       tola = ts->atol;
    5457:       if (tola>0.) {
    5458:         suma  += PetscSqr(err/tola);
    5459:         na_loc++;
    5460:       }
    5461:       tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
    5462:       if (tolr>0.) {
    5463:         sumr  += PetscSqr(err/tolr);
    5464:         nr_loc++;
    5465:       }
    5466:       tol=tola+tolr;
    5467:       if (tol>0.) {
    5468:         sum  += PetscSqr(err/tol);
    5469:         n_loc++;
    5470:       }
    5471:     }
    5472:     VecRestoreArrayRead(ts->vrtol,&rtol);
    5473:   } else {                      /* scalar atol, scalar rtol */
    5474:     for (i=0; i<n; i++) {
    5475:       SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
    5476:       err = PetscAbsScalar(e[i]);
    5477:       tola = ts->atol;
    5478:       if (tola>0.) {
    5479:         suma  += PetscSqr(err/tola);
    5480:         na_loc++;
    5481:       }
    5482:       tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
    5483:       if (tolr>0.) {
    5484:         sumr  += PetscSqr(err/tolr);
    5485:         nr_loc++;
    5486:       }
    5487:       tol=tola+tolr;
    5488:       if (tol>0.) {
    5489:         sum  += PetscSqr(err/tol);
    5490:         n_loc++;
    5491:       }
    5492:     }
    5493:   }
    5494:   VecRestoreArrayRead(E,&e);
    5495:   VecRestoreArrayRead(U,&u);
    5496:   VecRestoreArrayRead(Y,&y);

    5498:   err_loc[0] = sum;
    5499:   err_loc[1] = suma;
    5500:   err_loc[2] = sumr;
    5501:   err_loc[3] = (PetscReal)n_loc;
    5502:   err_loc[4] = (PetscReal)na_loc;
    5503:   err_loc[5] = (PetscReal)nr_loc;

    5505:   MPIU_Allreduce(err_loc,err_glb,6,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)ts));

    5507:   gsum   = err_glb[0];
    5508:   gsuma  = err_glb[1];
    5509:   gsumr  = err_glb[2];
    5510:   n_glb  = err_glb[3];
    5511:   na_glb = err_glb[4];
    5512:   nr_glb = err_glb[5];

    5514:   *norm  = 0.;
    5515:   if (n_glb>0.) {*norm  = PetscSqrtReal(gsum  / n_glb);}
    5516:   *norma = 0.;
    5517:   if (na_glb>0.) {*norma = PetscSqrtReal(gsuma / na_glb);}
    5518:   *normr = 0.;
    5519:   if (nr_glb>0.) {*normr = PetscSqrtReal(gsumr / nr_glb);}

    5521:   if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm");
    5522:   if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma");
    5523:   if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr");
    5524:   return(0);
    5525: }

    5527: /*@
    5528:    TSErrorWeightedENormInfinity - compute a weighted infinity error norm based on supplied absolute and relative tolerances
    5529:    Collective on TS

    5531:    Input Parameters:
    5532: +  ts - time stepping context
    5533: .  E - error vector
    5534: .  U - state vector, usually ts->vec_sol
    5535: -  Y - state vector, previous time step

    5537:    Output Parameters:
    5538: +  norm - weighted norm, a value of 1.0 means that the error matches the tolerances
    5539: .  norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances
    5540: -  normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances

    5542:    Level: developer

    5544: .seealso: TSErrorWeightedENorm(), TSErrorWeightedENorm2()
    5545: @*/
    5546: PetscErrorCode TSErrorWeightedENormInfinity(TS ts,Vec E,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr)
    5547: {
    5548:   PetscErrorCode    ierr;
    5549:   PetscInt          i,n,N,rstart;
    5550:   const PetscScalar *e,*u,*y;
    5551:   PetscReal         err,max,gmax,maxa,gmaxa,maxr,gmaxr;
    5552:   PetscReal         tol,tola,tolr;
    5553:   PetscReal         err_loc[3],err_glb[3];

    5569:   VecGetSize(E,&N);
    5570:   VecGetLocalSize(E,&n);
    5571:   VecGetOwnershipRange(E,&rstart,NULL);
    5572:   VecGetArrayRead(E,&e);
    5573:   VecGetArrayRead(U,&u);
    5574:   VecGetArrayRead(Y,&y);

    5576:   max=0.;
    5577:   maxa=0.;
    5578:   maxr=0.;

    5580:   if (ts->vatol && ts->vrtol) {     /* vector atol, vector rtol */
    5581:     const PetscScalar *atol,*rtol;
    5582:     VecGetArrayRead(ts->vatol,&atol);
    5583:     VecGetArrayRead(ts->vrtol,&rtol);

    5585:     for (i=0; i<n; i++) {
    5586:       SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
    5587:       err = PetscAbsScalar(e[i]);
    5588:       tola = PetscRealPart(atol[i]);
    5589:       tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
    5590:       tol  = tola+tolr;
    5591:       if (tola>0.) {
    5592:         maxa = PetscMax(maxa,err / tola);
    5593:       }
    5594:       if (tolr>0.) {
    5595:         maxr = PetscMax(maxr,err / tolr);
    5596:       }
    5597:       if (tol>0.) {
    5598:         max = PetscMax(max,err / tol);
    5599:       }
    5600:     }
    5601:     VecRestoreArrayRead(ts->vatol,&atol);
    5602:     VecRestoreArrayRead(ts->vrtol,&rtol);
    5603:   } else if (ts->vatol) {       /* vector atol, scalar rtol */
    5604:     const PetscScalar *atol;
    5605:     VecGetArrayRead(ts->vatol,&atol);
    5606:     for (i=0; i<n; i++) {
    5607:       SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
    5608:       err = PetscAbsScalar(e[i]);
    5609:       tola = PetscRealPart(atol[i]);
    5610:       tolr = ts->rtol  * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
    5611:       tol  = tola+tolr;
    5612:       if (tola>0.) {
    5613:         maxa = PetscMax(maxa,err / tola);
    5614:       }
    5615:       if (tolr>0.) {
    5616:         maxr = PetscMax(maxr,err / tolr);
    5617:       }
    5618:       if (tol>0.) {
    5619:         max = PetscMax(max,err / tol);
    5620:       }
    5621:     }
    5622:     VecRestoreArrayRead(ts->vatol,&atol);
    5623:   } else if (ts->vrtol) {       /* scalar atol, vector rtol */
    5624:     const PetscScalar *rtol;
    5625:     VecGetArrayRead(ts->vrtol,&rtol);

    5627:     for (i=0; i<n; i++) {
    5628:       SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
    5629:       err = PetscAbsScalar(e[i]);
    5630:       tola = ts->atol;
    5631:       tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
    5632:       tol  = tola+tolr;
    5633:       if (tola>0.) {
    5634:         maxa = PetscMax(maxa,err / tola);
    5635:       }
    5636:       if (tolr>0.) {
    5637:         maxr = PetscMax(maxr,err / tolr);
    5638:       }
    5639:       if (tol>0.) {
    5640:         max = PetscMax(max,err / tol);
    5641:       }
    5642:     }
    5643:     VecRestoreArrayRead(ts->vrtol,&rtol);
    5644:   } else {                      /* scalar atol, scalar rtol */

    5646:     for (i=0; i<n; i++) {
    5647:       SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
    5648:       err = PetscAbsScalar(e[i]);
    5649:       tola = ts->atol;
    5650:       tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
    5651:       tol  = tola+tolr;
    5652:       if (tola>0.) {
    5653:         maxa = PetscMax(maxa,err / tola);
    5654:       }
    5655:       if (tolr>0.) {
    5656:         maxr = PetscMax(maxr,err / tolr);
    5657:       }
    5658:       if (tol>0.) {
    5659:         max = PetscMax(max,err / tol);
    5660:       }
    5661:     }
    5662:   }
    5663:   VecRestoreArrayRead(E,&e);
    5664:   VecRestoreArrayRead(U,&u);
    5665:   VecRestoreArrayRead(Y,&y);
    5666:   err_loc[0] = max;
    5667:   err_loc[1] = maxa;
    5668:   err_loc[2] = maxr;
    5669:   MPIU_Allreduce(err_loc,err_glb,3,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)ts));
    5670:   gmax   = err_glb[0];
    5671:   gmaxa  = err_glb[1];
    5672:   gmaxr  = err_glb[2];

    5674:   *norm = gmax;
    5675:   *norma = gmaxa;
    5676:   *normr = gmaxr;
    5677:   if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm");
    5678:     if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma");
    5679:     if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr");
    5680:   return(0);
    5681: }

    5683: /*@
    5684:    TSErrorWeightedENorm - compute a weighted error norm based on supplied absolute and relative tolerances

    5686:    Collective on TS

    5688:    Input Parameters:
    5689: +  ts - time stepping context
    5690: .  E - error vector
    5691: .  U - state vector, usually ts->vec_sol
    5692: .  Y - state vector, previous time step
    5693: -  wnormtype - norm type, either NORM_2 or NORM_INFINITY

    5695:    Output Parameters:
    5696: +  norm  - weighted norm, a value of 1.0 achieves a balance between absolute and relative tolerances
    5697: .  norma - weighted norm, a value of 1.0 means that the error meets the absolute tolerance set by the user
    5698: -  normr - weighted norm, a value of 1.0 means that the error meets the relative tolerance set by the user

    5700:    Options Database Keys:
    5701: .  -ts_adapt_wnormtype <wnormtype> - 2, INFINITY

    5703:    Level: developer

    5705: .seealso: TSErrorWeightedENormInfinity(), TSErrorWeightedENorm2(), TSErrorWeightedNormInfinity(), TSErrorWeightedNorm2()
    5706: @*/
    5707: PetscErrorCode TSErrorWeightedENorm(TS ts,Vec E,Vec U,Vec Y,NormType wnormtype,PetscReal *norm,PetscReal *norma,PetscReal *normr)
    5708: {

    5712:   if (wnormtype == NORM_2) {
    5713:     TSErrorWeightedENorm2(ts,E,U,Y,norm,norma,normr);
    5714:   } else if (wnormtype == NORM_INFINITY) {
    5715:     TSErrorWeightedENormInfinity(ts,E,U,Y,norm,norma,normr);
    5716:   } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]);
    5717:   return(0);
    5718: }

    5720: /*@
    5721:    TSSetCFLTimeLocal - Set the local CFL constraint relative to forward Euler

    5723:    Logically Collective on TS

    5725:    Input Parameters:
    5726: +  ts - time stepping context
    5727: -  cfltime - maximum stable time step if using forward Euler (value can be different on each process)

    5729:    Note:
    5730:    After calling this function, the global CFL time can be obtained by calling TSGetCFLTime()

    5732:    Level: intermediate

    5734: .seealso: TSGetCFLTime(), TSADAPTCFL
    5735: @*/
    5736: PetscErrorCode TSSetCFLTimeLocal(TS ts,PetscReal cfltime)
    5737: {
    5740:   ts->cfltime_local = cfltime;
    5741:   ts->cfltime       = -1.;
    5742:   return(0);
    5743: }

    5745: /*@
    5746:    TSGetCFLTime - Get the maximum stable time step according to CFL criteria applied to forward Euler

    5748:    Collective on TS

    5750:    Input Parameter:
    5751: .  ts - time stepping context

    5753:    Output Parameter:
    5754: .  cfltime - maximum stable time step for forward Euler

    5756:    Level: advanced

    5758: .seealso: TSSetCFLTimeLocal()
    5759: @*/
    5760: PetscErrorCode TSGetCFLTime(TS ts,PetscReal *cfltime)
    5761: {

    5765:   if (ts->cfltime < 0) {
    5766:     MPIU_Allreduce(&ts->cfltime_local,&ts->cfltime,1,MPIU_REAL,MPIU_MIN,PetscObjectComm((PetscObject)ts));
    5767:   }
    5768:   *cfltime = ts->cfltime;
    5769:   return(0);
    5770: }

    5772: /*@
    5773:    TSVISetVariableBounds - Sets the lower and upper bounds for the solution vector. xl <= x <= xu

    5775:    Input Parameters:
    5776: +  ts   - the TS context.
    5777: .  xl   - lower bound.
    5778: -  xu   - upper bound.

    5780:    Notes:
    5781:    If this routine is not called then the lower and upper bounds are set to
    5782:    PETSC_NINFINITY and PETSC_INFINITY respectively during SNESSetUp().

    5784:    Level: advanced

    5786: @*/
    5787: PetscErrorCode TSVISetVariableBounds(TS ts, Vec xl, Vec xu)
    5788: {
    5790:   SNES           snes;

    5793:   TSGetSNES(ts,&snes);
    5794:   SNESVISetVariableBounds(snes,xl,xu);
    5795:   return(0);
    5796: }

    5798: /*@
    5799:    TSComputeLinearStability - computes the linear stability function at a point

    5801:    Collective on TS

    5803:    Input Parameters:
    5804: +  ts - the TS context
    5805: -  xr,xi - real and imaginary part of input arguments

    5807:    Output Parameters:
    5808: .  yr,yi - real and imaginary part of function value

    5810:    Level: developer

    5812: .seealso: TSSetRHSFunction(), TSComputeIFunction()
    5813: @*/
    5814: PetscErrorCode TSComputeLinearStability(TS ts,PetscReal xr,PetscReal xi,PetscReal *yr,PetscReal *yi)
    5815: {

    5820:   if (!ts->ops->linearstability) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Linearized stability function not provided for this method");
    5821:   (*ts->ops->linearstability)(ts,xr,xi,yr,yi);
    5822:   return(0);
    5823: }

    5825: /*@
    5826:    TSRestartStep - Flags the solver to restart the next step

    5828:    Collective on TS

    5830:    Input Parameter:
    5831: .  ts - the TS context obtained from TSCreate()

    5833:    Level: advanced

    5835:    Notes:
    5836:    Multistep methods like BDF or Runge-Kutta methods with FSAL property require restarting the solver in the event of
    5837:    discontinuities. These discontinuities may be introduced as a consequence of explicitly modifications to the solution
    5838:    vector (which PETSc attempts to detect and handle) or problem coefficients (which PETSc is not able to detect). For
    5839:    the sake of correctness and maximum safety, users are expected to call TSRestart() whenever they introduce
    5840:    discontinuities in callback routines (e.g. prestep and poststep routines, or implicit/rhs function routines with
    5841:    discontinuous source terms).

    5843: .seealso: TSSolve(), TSSetPreStep(), TSSetPostStep()
    5844: @*/
    5845: PetscErrorCode TSRestartStep(TS ts)
    5846: {
    5849:   ts->steprestart = PETSC_TRUE;
    5850:   return(0);
    5851: }

    5853: /*@
    5854:    TSRollBack - Rolls back one time step

    5856:    Collective on TS

    5858:    Input Parameter:
    5859: .  ts - the TS context obtained from TSCreate()

    5861:    Level: advanced

    5863: .seealso: TSCreate(), TSSetUp(), TSDestroy(), TSSolve(), TSSetPreStep(), TSSetPreStage(), TSInterpolate()
    5864: @*/
    5865: PetscErrorCode  TSRollBack(TS ts)
    5866: {

    5871:   if (ts->steprollback) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"TSRollBack already called");
    5872:   if (!ts->ops->rollback) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSRollBack not implemented for type '%s'",((PetscObject)ts)->type_name);
    5873:   (*ts->ops->rollback)(ts);
    5874:   ts->time_step = ts->ptime - ts->ptime_prev;
    5875:   ts->ptime = ts->ptime_prev;
    5876:   ts->ptime_prev = ts->ptime_prev_rollback;
    5877:   ts->steps--;
    5878:   ts->steprollback = PETSC_TRUE;
    5879:   return(0);
    5880: }

    5882: /*@
    5883:    TSGetStages - Get the number of stages and stage values

    5885:    Input Parameter:
    5886: .  ts - the TS context obtained from TSCreate()

    5888:    Output Parameters:
    5889: +  ns - the number of stages
    5890: -  Y - the current stage vectors

    5892:    Level: advanced

    5894:    Notes: Both ns and Y can be NULL.

    5896: .seealso: TSCreate()
    5897: @*/
    5898: PetscErrorCode  TSGetStages(TS ts,PetscInt *ns,Vec **Y)
    5899: {

    5906:   if (!ts->ops->getstages) {
    5907:     if (ns) *ns = 0;
    5908:     if (Y) *Y = NULL;
    5909:   } else {
    5910:     (*ts->ops->getstages)(ts,ns,Y);
    5911:   }
    5912:   return(0);
    5913: }

    5915: /*@C
    5916:   TSComputeIJacobianDefaultColor - Computes the Jacobian using finite differences and coloring to exploit matrix sparsity.

    5918:   Collective on SNES

    5920:   Input Parameters:
    5921: + ts - the TS context
    5922: . t - current timestep
    5923: . U - state vector
    5924: . Udot - time derivative of state vector
    5925: . shift - shift to apply, see note below
    5926: - ctx - an optional user context

    5928:   Output Parameters:
    5929: + J - Jacobian matrix (not altered in this routine)
    5930: - B - newly computed Jacobian matrix to use with preconditioner (generally the same as J)

    5932:   Level: intermediate

    5934:   Notes:
    5935:   If F(t,U,Udot)=0 is the DAE, the required Jacobian is

    5937:   dF/dU + shift*dF/dUdot

    5939:   Most users should not need to explicitly call this routine, as it
    5940:   is used internally within the nonlinear solvers.

    5942:   This will first try to get the coloring from the DM.  If the DM type has no coloring
    5943:   routine, then it will try to get the coloring from the matrix.  This requires that the
    5944:   matrix have nonzero entries precomputed.

    5946: .seealso: TSSetIJacobian(), MatFDColoringCreate(), MatFDColoringSetFunction()
    5947: @*/
    5948: PetscErrorCode TSComputeIJacobianDefaultColor(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat J,Mat B,void *ctx)
    5949: {
    5950:   SNES           snes;
    5951:   MatFDColoring  color;
    5952:   PetscBool      hascolor, matcolor = PETSC_FALSE;

    5956:   PetscOptionsGetBool(((PetscObject)ts)->options,((PetscObject) ts)->prefix, "-ts_fd_color_use_mat", &matcolor, NULL);
    5957:   PetscObjectQuery((PetscObject) B, "TSMatFDColoring", (PetscObject *) &color);
    5958:   if (!color) {
    5959:     DM         dm;
    5960:     ISColoring iscoloring;

    5962:     TSGetDM(ts, &dm);
    5963:     DMHasColoring(dm, &hascolor);
    5964:     if (hascolor && !matcolor) {
    5965:       DMCreateColoring(dm, IS_COLORING_GLOBAL, &iscoloring);
    5966:       MatFDColoringCreate(B, iscoloring, &color);
    5967:       MatFDColoringSetFunction(color, (PetscErrorCode (*)(void)) SNESTSFormFunction, (void *) ts);
    5968:       MatFDColoringSetFromOptions(color);
    5969:       MatFDColoringSetUp(B, iscoloring, color);
    5970:       ISColoringDestroy(&iscoloring);
    5971:     } else {
    5972:       MatColoring mc;

    5974:       MatColoringCreate(B, &mc);
    5975:       MatColoringSetDistance(mc, 2);
    5976:       MatColoringSetType(mc, MATCOLORINGSL);
    5977:       MatColoringSetFromOptions(mc);
    5978:       MatColoringApply(mc, &iscoloring);
    5979:       MatColoringDestroy(&mc);
    5980:       MatFDColoringCreate(B, iscoloring, &color);
    5981:       MatFDColoringSetFunction(color, (PetscErrorCode (*)(void)) SNESTSFormFunction, (void *) ts);
    5982:       MatFDColoringSetFromOptions(color);
    5983:       MatFDColoringSetUp(B, iscoloring, color);
    5984:       ISColoringDestroy(&iscoloring);
    5985:     }
    5986:     PetscObjectCompose((PetscObject) B, "TSMatFDColoring", (PetscObject) color);
    5987:     PetscObjectDereference((PetscObject) color);
    5988:   }
    5989:   TSGetSNES(ts, &snes);
    5990:   MatFDColoringApply(B, color, U, snes);
    5991:   if (J != B) {
    5992:     MatAssemblyBegin(J, MAT_FINAL_ASSEMBLY);
    5993:     MatAssemblyEnd(J, MAT_FINAL_ASSEMBLY);
    5994:   }
    5995:   return(0);
    5996: }

    5998: /*@
    5999:     TSSetFunctionDomainError - Set a function that tests if the current state vector is valid

    6001:     Input Parameters:
    6002: +    ts - the TS context
    6003: -    func - function called within TSFunctionDomainError

    6005:     Calling sequence of func:
    6006: $     PetscErrorCode func(TS ts,PetscReal time,Vec state,PetscBool reject)

    6008: +   ts - the TS context
    6009: .   time - the current time (of the stage)
    6010: .   state - the state to check if it is valid
    6011: -   reject - (output parameter) PETSC_FALSE if the state is acceptable, PETSC_TRUE if not acceptable

    6013:     Level: intermediate

    6015:     Notes:
    6016:       If an implicit ODE solver is being used then, in addition to providing this routine, the
    6017:       user's code should call SNESSetFunctionDomainError() when domain errors occur during
    6018:       function evaluations where the functions are provided by TSSetIFunction() or TSSetRHSFunction().
    6019:       Use TSGetSNES() to obtain the SNES object

    6021:     Developer Notes:
    6022:       The naming of this function is inconsistent with the SNESSetFunctionDomainError()
    6023:       since one takes a function pointer and the other does not.

    6025: .seealso: TSAdaptCheckStage(), TSFunctionDomainError(), SNESSetFunctionDomainError(), TSGetSNES()
    6026: @*/

    6028: PetscErrorCode TSSetFunctionDomainError(TS ts, PetscErrorCode (*func)(TS,PetscReal,Vec,PetscBool*))
    6029: {
    6032:   ts->functiondomainerror = func;
    6033:   return(0);
    6034: }

    6036: /*@
    6037:     TSFunctionDomainError - Checks if the current state is valid

    6039:     Input Parameters:
    6040: +    ts - the TS context
    6041: .    stagetime - time of the simulation
    6042: -    Y - state vector to check.

    6044:     Output Parameter:
    6045: .    accept - Set to PETSC_FALSE if the current state vector is valid.

    6047:     Note:
    6048:     This function is called by the TS integration routines and calls the user provided function (set with TSSetFunctionDomainError())
    6049:     to check if the current state is valid.

    6051:     Level: developer

    6053: .seealso: TSSetFunctionDomainError()
    6054: @*/
    6055: PetscErrorCode TSFunctionDomainError(TS ts,PetscReal stagetime,Vec Y,PetscBool* accept)
    6056: {
    6059:   *accept = PETSC_TRUE;
    6060:   if (ts->functiondomainerror) {
    6061:     PetscStackCallStandard((*ts->functiondomainerror),(ts,stagetime,Y,accept));
    6062:   }
    6063:   return(0);
    6064: }

    6066: /*@C
    6067:   TSClone - This function clones a time step object.

    6069:   Collective

    6071:   Input Parameter:
    6072: . tsin    - The input TS

    6074:   Output Parameter:
    6075: . tsout   - The output TS (cloned)

    6077:   Notes:
    6078:   This function is used to create a clone of a TS object. It is used in ARKIMEX for initializing the slope for first stage explicit methods. It will likely be replaced in the future with a mechanism of switching methods on the fly.

    6080:   When using TSDestroy() on a clone the user has to first reset the correct TS reference in the embedded SNES object: e.g.: by running SNES snes_dup=NULL; TSGetSNES(ts,&snes_dup); TSSetSNES(ts,snes_dup);

    6082:   Level: developer

    6084: .seealso: TSCreate(), TSSetType(), TSSetUp(), TSDestroy(), TSSetProblemType()
    6085: @*/
    6086: PetscErrorCode  TSClone(TS tsin, TS *tsout)
    6087: {
    6088:   TS             t;
    6090:   SNES           snes_start;
    6091:   DM             dm;
    6092:   TSType         type;

    6096:   *tsout = NULL;

    6098:   PetscHeaderCreate(t, TS_CLASSID, "TS", "Time stepping", "TS", PetscObjectComm((PetscObject)tsin), TSDestroy, TSView);

    6100:   /* General TS description */
    6101:   t->numbermonitors    = 0;
    6102:   t->monitorFrequency  = 1;
    6103:   t->setupcalled       = 0;
    6104:   t->ksp_its           = 0;
    6105:   t->snes_its          = 0;
    6106:   t->nwork             = 0;
    6107:   t->rhsjacobian.time  = PETSC_MIN_REAL;
    6108:   t->rhsjacobian.scale = 1.;
    6109:   t->ijacobian.shift   = 1.;

    6111:   TSGetSNES(tsin,&snes_start);
    6112:   TSSetSNES(t,snes_start);

    6114:   TSGetDM(tsin,&dm);
    6115:   TSSetDM(t,dm);

    6117:   t->adapt = tsin->adapt;
    6118:   PetscObjectReference((PetscObject)t->adapt);

    6120:   t->trajectory = tsin->trajectory;
    6121:   PetscObjectReference((PetscObject)t->trajectory);

    6123:   t->event = tsin->event;
    6124:   if (t->event) t->event->refct++;

    6126:   t->problem_type      = tsin->problem_type;
    6127:   t->ptime             = tsin->ptime;
    6128:   t->ptime_prev        = tsin->ptime_prev;
    6129:   t->time_step         = tsin->time_step;
    6130:   t->max_time          = tsin->max_time;
    6131:   t->steps             = tsin->steps;
    6132:   t->max_steps         = tsin->max_steps;
    6133:   t->equation_type     = tsin->equation_type;
    6134:   t->atol              = tsin->atol;
    6135:   t->rtol              = tsin->rtol;
    6136:   t->max_snes_failures = tsin->max_snes_failures;
    6137:   t->max_reject        = tsin->max_reject;
    6138:   t->errorifstepfailed = tsin->errorifstepfailed;

    6140:   TSGetType(tsin,&type);
    6141:   TSSetType(t,type);

    6143:   t->vec_sol           = NULL;

    6145:   t->cfltime          = tsin->cfltime;
    6146:   t->cfltime_local    = tsin->cfltime_local;
    6147:   t->exact_final_time = tsin->exact_final_time;

    6149:   PetscMemcpy(t->ops,tsin->ops,sizeof(struct _TSOps));

    6151:   if (((PetscObject)tsin)->fortran_func_pointers) {
    6152:     PetscInt i;
    6153:     PetscMalloc((10)*sizeof(void(*)(void)),&((PetscObject)t)->fortran_func_pointers);
    6154:     for (i=0; i<10; i++) {
    6155:       ((PetscObject)t)->fortran_func_pointers[i] = ((PetscObject)tsin)->fortran_func_pointers[i];
    6156:     }
    6157:   }
    6158:   *tsout = t;
    6159:   return(0);
    6160: }

    6162: static PetscErrorCode RHSWrapperFunction_TSRHSJacobianTest(void* ctx,Vec x,Vec y)
    6163: {
    6165:   TS             ts = (TS) ctx;

    6168:   TSComputeRHSFunction(ts,0,x,y);
    6169:   return(0);
    6170: }

    6172: /*@
    6173:     TSRHSJacobianTest - Compares the multiply routine provided to the MATSHELL with differencing on the TS given RHS function.

    6175:    Logically Collective on TS

    6177:     Input Parameters:
    6178:     TS - the time stepping routine

    6180:    Output Parameter:
    6181: .   flg - PETSC_TRUE if the multiply is likely correct

    6183:    Options Database:
    6184:  .   -ts_rhs_jacobian_test_mult -mat_shell_test_mult_view - run the test at each timestep of the integrator

    6186:    Level: advanced

    6188:    Notes:
    6189:     This only works for problems defined only the RHS function and Jacobian NOT IFunction and IJacobian

    6191: .seealso: MatCreateShell(), MatShellGetContext(), MatShellGetOperation(), MatShellTestMultTranspose(), TSRHSJacobianTestTranspose()
    6192: @*/
    6193: PetscErrorCode  TSRHSJacobianTest(TS ts,PetscBool *flg)
    6194: {
    6195:   Mat            J,B;
    6197:   TSRHSJacobian  func;
    6198:   void*          ctx;

    6201:   TSGetRHSJacobian(ts,&J,&B,&func,&ctx);
    6202:   (*func)(ts,0.0,ts->vec_sol,J,B,ctx);
    6203:   MatShellTestMult(J,RHSWrapperFunction_TSRHSJacobianTest,ts->vec_sol,ts,flg);
    6204:   return(0);
    6205: }

    6207: /*@C
    6208:     TSRHSJacobianTestTranspose - Compares the multiply transpose routine provided to the MATSHELL with differencing on the TS given RHS function.

    6210:    Logically Collective on TS

    6212:     Input Parameters:
    6213:     TS - the time stepping routine

    6215:    Output Parameter:
    6216: .   flg - PETSC_TRUE if the multiply is likely correct

    6218:    Options Database:
    6219: .   -ts_rhs_jacobian_test_mult_transpose -mat_shell_test_mult_transpose_view - run the test at each timestep of the integrator

    6221:    Notes:
    6222:     This only works for problems defined only the RHS function and Jacobian NOT IFunction and IJacobian

    6224:    Level: advanced

    6226: .seealso: MatCreateShell(), MatShellGetContext(), MatShellGetOperation(), MatShellTestMultTranspose(), TSRHSJacobianTest()
    6227: @*/
    6228: PetscErrorCode  TSRHSJacobianTestTranspose(TS ts,PetscBool *flg)
    6229: {
    6230:   Mat            J,B;
    6232:   void           *ctx;
    6233:   TSRHSJacobian  func;

    6236:   TSGetRHSJacobian(ts,&J,&B,&func,&ctx);
    6237:   (*func)(ts,0.0,ts->vec_sol,J,B,ctx);
    6238:   MatShellTestMultTranspose(J,RHSWrapperFunction_TSRHSJacobianTest,ts->vec_sol,ts,flg);
    6239:   return(0);
    6240: }

    6242: /*@
    6243:   TSSetUseSplitRHSFunction - Use the split RHSFunction when a multirate method is used.

    6245:   Logically collective

    6247:   Input Parameters:
    6248: +  ts - timestepping context
    6249: -  use_splitrhsfunction - PETSC_TRUE indicates that the split RHSFunction will be used

    6251:   Options Database:
    6252: .   -ts_use_splitrhsfunction - <true,false>

    6254:   Notes:
    6255:     This is only useful for multirate methods

    6257:   Level: intermediate

    6259: .seealso: TSGetUseSplitRHSFunction()
    6260: @*/
    6261: PetscErrorCode TSSetUseSplitRHSFunction(TS ts, PetscBool use_splitrhsfunction)
    6262: {
    6265:   ts->use_splitrhsfunction = use_splitrhsfunction;
    6266:   return(0);
    6267: }

    6269: /*@
    6270:   TSGetUseSplitRHSFunction - Gets whether to use the split RHSFunction when a multirate method is used.

    6272:   Not collective

    6274:   Input Parameter:
    6275: .  ts - timestepping context

    6277:   Output Parameter:
    6278: .  use_splitrhsfunction - PETSC_TRUE indicates that the split RHSFunction will be used

    6280:   Level: intermediate

    6282: .seealso: TSSetUseSplitRHSFunction()
    6283: @*/
    6284: PetscErrorCode TSGetUseSplitRHSFunction(TS ts, PetscBool *use_splitrhsfunction)
    6285: {
    6288:   *use_splitrhsfunction = ts->use_splitrhsfunction;
    6289:   return(0);
    6290: }

    6292: /*@
    6293:     TSSetMatStructure - sets the relationship between the nonzero structure of the RHS Jacobian matrix to the IJacobian matrix.

    6295:    Logically  Collective on ts

    6297:    Input Parameters:
    6298: +  ts - the time-stepper
    6299: -  str - the structure (the default is UNKNOWN_NONZERO_PATTERN)

    6301:    Level: intermediate

    6303:    Notes:
    6304:      When the relationship between the nonzero structures is known and supplied the solution process can be much faster

    6306: .seealso: MatAXPY(), MatStructure
    6307:  @*/
    6308: PetscErrorCode TSSetMatStructure(TS ts,MatStructure str)
    6309: {
    6312:   ts->axpy_pattern = str;
    6313:   return(0);
    6314: }