Actual source code: ts.c

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

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

 13: /* Logging support */
 14: PetscClassId  TS_CLASSID, DMTS_CLASSID;
 15: PetscLogEvent TS_Step, TS_PseudoComputeTimeStep, TS_FunctionEval, TS_JacobianEval;

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

 19: static PetscErrorCode TSAdaptSetDefaultType(TSAdapt adapt, TSAdaptType default_type)
 20: {
 21:   PetscFunctionBegin;
 24:   if (!((PetscObject)adapt)->type_name) PetscCall(TSAdaptSetType(adapt, default_type));
 25:   PetscFunctionReturn(PETSC_SUCCESS);
 26: }

 28: /*@
 29:    TSSetFromOptions - Sets various `TS` parameters from the options database

 31:    Collective

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

 36:    Options Database Keys:
 37: +  -ts_type <type> - EULER, BEULER, SUNDIALS, PSEUDO, CN, RK, THETA, ALPHA, GLLE,  SSP, GLEE, BSYMP, IRK, see `TSType`
 38: .  -ts_save_trajectory - checkpoint the solution at each time-step
 39: .  -ts_max_time <time> - maximum time to compute to
 40: .  -ts_time_span <t0,...tf> - sets the time span, solutions are computed and stored for each indicated time
 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_interval <interval> - output once every interval (default=1) time steps; used with -ts_monitor_solution
 70: .  -ts_monitor_solution_vtk <filename.vts,filename.vtu> - Save each time step to a binary file, use filename-%%03" PetscInt_FMT ".vts (filename-%%03" PetscInt_FMT ".vtu)
 71: -  -ts_monitor_envelope - determine maximum and minimum value of each component of the solution over the solution time

 73:    Level: beginner

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

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

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

 85: .seealso: [](chapter_ts), `TS`, `TSGetType()`
 86: @*/
 87: PetscErrorCode TSSetFromOptions(TS ts)
 88: {
 89:   PetscBool              opt, flg, tflg;
 90:   char                   monfilename[PETSC_MAX_PATH_LEN];
 91:   PetscReal              time_step, tspan[100];
 92:   PetscInt               nt = PETSC_STATIC_ARRAY_LENGTH(tspan);
 93:   TSExactFinalTimeOption eftopt;
 94:   char                   dir[16];
 95:   TSIFunction            ifun;
 96:   const char            *defaultType;
 97:   char                   typeName[256];

 99:   PetscFunctionBegin;

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

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

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

129:   PetscCall(PetscOptionsBool("-ts_rhs_jacobian_test_mult", "Test the RHS Jacobian for consistency with RHS at each solve ", "None", ts->testjacobian, &ts->testjacobian, NULL));
130:   PetscCall(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:   PetscCall(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:     PetscCall(PetscOptionsBool("-ts_saws_block", "Block for SAWs memory snooper at end of TSSolve", "PetscObjectSAWsBlock", ((PetscObject)ts)->amspublishblock, &flg, &set));
137:     if (set) PetscCall(PetscObjectSAWsSetBlock((PetscObject)ts, flg));
138:   }
139: #endif

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

148:   PetscCall(PetscOptionsString("-ts_monitor_python", "Use Python function", "TSMonitorSet", NULL, monfilename, sizeof(monfilename), &flg));
149:   if (flg) PetscCall(PetscPythonMonitorSet((PetscObject)ts, monfilename));

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

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

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

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

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

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

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

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

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

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

226:     PetscCall(PetscOptionsInt("-ts_monitor_sp_eig", "Monitor eigenvalues of linearized operator graphically", "TSMonitorSPEig", howoften, &howoften, NULL));
227:     PetscCall(TSMonitorSPEigCtxCreate(PETSC_COMM_SELF, NULL, NULL, PETSC_DECIDE, PETSC_DECIDE, 300, 300, howoften, &ctx));
228:     PetscCall(TSMonitorSet(ts, TSMonitorSPEig, ctx, (PetscErrorCode(*)(void **))TSMonitorSPEigCtxDestroy));
229:   }
230:   PetscCall(PetscOptionsName("-ts_monitor_sp_swarm", "Display particle phase space from the DMSwarm", "TSMonitorSPSwarm", &opt));
231:   if (opt) {
232:     TSMonitorSPCtx ctx;
233:     PetscInt       howoften = 1, retain = 0;
234:     PetscBool      phase = PETSC_TRUE, create = PETSC_TRUE, multispecies = PETSC_FALSE;

236:     for (PetscInt i = 0; i < ts->numbermonitors; ++i)
237:       if (ts->monitor[i] == TSMonitorSPSwarmSolution) {
238:         create = PETSC_FALSE;
239:         break;
240:       }
241:     if (create) {
242:       PetscCall(PetscOptionsInt("-ts_monitor_sp_swarm", "Display particles phase space from the DMSwarm", "TSMonitorSPSwarm", howoften, &howoften, NULL));
243:       PetscCall(PetscOptionsInt("-ts_monitor_sp_swarm_retain", "Retain n points plotted to show trajectory, -1 for all points", "TSMonitorSPSwarm", retain, &retain, NULL));
244:       PetscCall(PetscOptionsBool("-ts_monitor_sp_swarm_phase", "Plot in phase space rather than coordinate space", "TSMonitorSPSwarm", phase, &phase, NULL));
245:       PetscCall(PetscOptionsBool("-ts_monitor_sp_swarm_multi_species", "Color particles by particle species", "TSMonitorSPSwarm", multispecies, &multispecies, NULL));
246:       PetscCall(TSMonitorSPCtxCreate(PetscObjectComm((PetscObject)ts), NULL, NULL, PETSC_DECIDE, PETSC_DECIDE, 300, 300, howoften, retain, phase, multispecies, &ctx));
247:       PetscCall(TSMonitorSet(ts, TSMonitorSPSwarmSolution, ctx, (PetscErrorCode(*)(void **))TSMonitorSPCtxDestroy));
248:     }
249:   }
250:   PetscCall(PetscOptionsName("-ts_monitor_hg_swarm", "Display particle histogram from the DMSwarm", "TSMonitorHGSwarm", &opt));
251:   if (opt) {
252:     TSMonitorHGCtx ctx;
253:     PetscInt       howoften = 1, Ns = 1;
254:     PetscBool      velocity = PETSC_FALSE, create = PETSC_TRUE;

256:     for (PetscInt i = 0; i < ts->numbermonitors; ++i)
257:       if (ts->monitor[i] == TSMonitorHGSwarmSolution) {
258:         create = PETSC_FALSE;
259:         break;
260:       }
261:     if (create) {
262:       DM       sw, dm;
263:       PetscInt Nc, Nb;

265:       PetscCall(TSGetDM(ts, &sw));
266:       PetscCall(DMSwarmGetCellDM(sw, &dm));
267:       PetscCall(DMPlexGetHeightStratum(dm, 0, NULL, &Nc));
268:       Nb = PetscMin(20, PetscMax(10, Nc));
269:       PetscCall(PetscOptionsInt("-ts_monitor_hg_swarm", "Display particles histogram from the DMSwarm", "TSMonitorHGSwarm", howoften, &howoften, NULL));
270:       PetscCall(PetscOptionsBool("-ts_monitor_hg_swarm_velocity", "Plot in velocity space rather than coordinate space", "TSMonitorHGSwarm", velocity, &velocity, NULL));
271:       PetscCall(PetscOptionsInt("-ts_monitor_hg_swarm_species", "Number of species to histogram", "TSMonitorHGSwarm", Ns, &Ns, NULL));
272:       PetscCall(PetscOptionsInt("-ts_monitor_hg_swarm_bins", "Number of histogram bins", "TSMonitorHGSwarm", Nb, &Nb, NULL));
273:       PetscCall(TSMonitorHGCtxCreate(PetscObjectComm((PetscObject)ts), NULL, NULL, PETSC_DECIDE, PETSC_DECIDE, 300, 300, howoften, Ns, Nb, velocity, &ctx));
274:       PetscCall(TSMonitorSet(ts, TSMonitorHGSwarmSolution, ctx, (PetscErrorCode(*)(void **))TSMonitorHGCtxDestroy));
275:     }
276:   }
277:   opt = PETSC_FALSE;
278:   PetscCall(PetscOptionsName("-ts_monitor_draw_solution", "Monitor solution graphically", "TSMonitorDrawSolution", &opt));
279:   if (opt) {
280:     TSMonitorDrawCtx ctx;
281:     PetscInt         howoften = 1;

283:     PetscCall(PetscOptionsInt("-ts_monitor_draw_solution", "Monitor solution graphically", "TSMonitorDrawSolution", howoften, &howoften, NULL));
284:     PetscCall(TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts), NULL, "Computed Solution", PETSC_DECIDE, PETSC_DECIDE, 300, 300, howoften, &ctx));
285:     PetscCall(TSMonitorSet(ts, TSMonitorDrawSolution, ctx, (PetscErrorCode(*)(void **))TSMonitorDrawCtxDestroy));
286:   }
287:   opt = PETSC_FALSE;
288:   PetscCall(PetscOptionsName("-ts_monitor_draw_solution_phase", "Monitor solution graphically", "TSMonitorDrawSolutionPhase", &opt));
289:   if (opt) {
290:     TSMonitorDrawCtx ctx;
291:     PetscReal        bounds[4];
292:     PetscInt         n = 4;
293:     PetscDraw        draw;
294:     PetscDrawAxis    axis;

296:     PetscCall(PetscOptionsRealArray("-ts_monitor_draw_solution_phase", "Monitor solution graphically", "TSMonitorDrawSolutionPhase", bounds, &n, NULL));
297:     PetscCheck(n == 4, PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_WRONG, "Must provide bounding box of phase field");
298:     PetscCall(TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts), NULL, NULL, PETSC_DECIDE, PETSC_DECIDE, 300, 300, 1, &ctx));
299:     PetscCall(PetscViewerDrawGetDraw(ctx->viewer, 0, &draw));
300:     PetscCall(PetscViewerDrawGetDrawAxis(ctx->viewer, 0, &axis));
301:     PetscCall(PetscDrawAxisSetLimits(axis, bounds[0], bounds[2], bounds[1], bounds[3]));
302:     PetscCall(PetscDrawAxisSetLabels(axis, "Phase Diagram", "Variable 1", "Variable 2"));
303:     PetscCall(TSMonitorSet(ts, TSMonitorDrawSolutionPhase, ctx, (PetscErrorCode(*)(void **))TSMonitorDrawCtxDestroy));
304:   }
305:   opt = PETSC_FALSE;
306:   PetscCall(PetscOptionsName("-ts_monitor_draw_error", "Monitor error graphically", "TSMonitorDrawError", &opt));
307:   if (opt) {
308:     TSMonitorDrawCtx ctx;
309:     PetscInt         howoften = 1;

311:     PetscCall(PetscOptionsInt("-ts_monitor_draw_error", "Monitor error graphically", "TSMonitorDrawError", howoften, &howoften, NULL));
312:     PetscCall(TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts), NULL, "Error", PETSC_DECIDE, PETSC_DECIDE, 300, 300, howoften, &ctx));
313:     PetscCall(TSMonitorSet(ts, TSMonitorDrawError, ctx, (PetscErrorCode(*)(void **))TSMonitorDrawCtxDestroy));
314:   }
315:   opt = PETSC_FALSE;
316:   PetscCall(PetscOptionsName("-ts_monitor_draw_solution_function", "Monitor solution provided by TSMonitorSetSolutionFunction() graphically", "TSMonitorDrawSolutionFunction", &opt));
317:   if (opt) {
318:     TSMonitorDrawCtx ctx;
319:     PetscInt         howoften = 1;

321:     PetscCall(PetscOptionsInt("-ts_monitor_draw_solution_function", "Monitor solution provided by TSMonitorSetSolutionFunction() graphically", "TSMonitorDrawSolutionFunction", howoften, &howoften, NULL));
322:     PetscCall(TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts), NULL, "Solution provided by user function", PETSC_DECIDE, PETSC_DECIDE, 300, 300, howoften, &ctx));
323:     PetscCall(TSMonitorSet(ts, TSMonitorDrawSolutionFunction, ctx, (PetscErrorCode(*)(void **))TSMonitorDrawCtxDestroy));
324:   }

326:   opt = PETSC_FALSE;
327:   PetscCall(PetscOptionsString("-ts_monitor_solution_vtk", "Save each time step to a binary file, use filename-%%03" PetscInt_FMT ".vts", "TSMonitorSolutionVTK", NULL, monfilename, sizeof(monfilename), &flg));
328:   if (flg) {
329:     const char *ptr = NULL, *ptr2 = NULL;
330:     char       *filetemplate;
331:     PetscCheck(monfilename[0], PetscObjectComm((PetscObject)ts), PETSC_ERR_USER, "-ts_monitor_solution_vtk requires a file template, e.g. filename-%%03" PetscInt_FMT ".vts");
332:     /* Do some cursory validation of the input. */
333:     PetscCall(PetscStrstr(monfilename, "%", (char **)&ptr));
334:     PetscCheck(ptr, PetscObjectComm((PetscObject)ts), PETSC_ERR_USER, "-ts_monitor_solution_vtk requires a file template, e.g. filename-%%03" PetscInt_FMT ".vts");
335:     for (ptr++; ptr && *ptr; ptr++) {
336:       PetscCall(PetscStrchr("DdiouxX", *ptr, (char **)&ptr2));
337:       PetscCheck(ptr2 || (*ptr >= '0' && *ptr <= '9'), PetscObjectComm((PetscObject)ts), PETSC_ERR_USER, "Invalid file template argument to -ts_monitor_solution_vtk, should look like filename-%%03" PetscInt_FMT ".vts");
338:       if (ptr2) break;
339:     }
340:     PetscCall(PetscStrallocpy(monfilename, &filetemplate));
341:     PetscCall(TSMonitorSet(ts, TSMonitorSolutionVTK, filetemplate, (PetscErrorCode(*)(void **))TSMonitorSolutionVTKDestroy));
342:   }

344:   PetscCall(PetscOptionsString("-ts_monitor_dmda_ray", "Display a ray of the solution", "None", "y=0", dir, sizeof(dir), &flg));
345:   if (flg) {
346:     TSMonitorDMDARayCtx *rayctx;
347:     int                  ray = 0;
348:     DMDirection          ddir;
349:     DM                   da;
350:     PetscMPIInt          rank;

352:     PetscCheck(dir[1] == '=', PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_WRONG, "Unknown ray %s", dir);
353:     if (dir[0] == 'x') ddir = DM_X;
354:     else if (dir[0] == 'y') ddir = DM_Y;
355:     else SETERRQ(PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_WRONG, "Unknown ray %s", dir);
356:     sscanf(dir + 2, "%d", &ray);

358:     PetscCall(PetscInfo(((PetscObject)ts), "Displaying DMDA ray %c = %d\n", dir[0], ray));
359:     PetscCall(PetscNew(&rayctx));
360:     PetscCall(TSGetDM(ts, &da));
361:     PetscCall(DMDAGetRay(da, ddir, ray, &rayctx->ray, &rayctx->scatter));
362:     PetscCallMPI(MPI_Comm_rank(PetscObjectComm((PetscObject)ts), &rank));
363:     if (rank == 0) PetscCall(PetscViewerDrawOpen(PETSC_COMM_SELF, NULL, NULL, 0, 0, 600, 300, &rayctx->viewer));
364:     rayctx->lgctx = NULL;
365:     PetscCall(TSMonitorSet(ts, TSMonitorDMDARay, rayctx, TSMonitorDMDARayDestroy));
366:   }
367:   PetscCall(PetscOptionsString("-ts_monitor_lg_dmda_ray", "Display a ray of the solution", "None", "x=0", dir, sizeof(dir), &flg));
368:   if (flg) {
369:     TSMonitorDMDARayCtx *rayctx;
370:     int                  ray = 0;
371:     DMDirection          ddir;
372:     DM                   da;
373:     PetscInt             howoften = 1;

375:     PetscCheck(dir[1] == '=', PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_WRONG, "Malformed ray %s", dir);
376:     if (dir[0] == 'x') ddir = DM_X;
377:     else if (dir[0] == 'y') ddir = DM_Y;
378:     else SETERRQ(PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_WRONG, "Unknown ray direction %s", dir);
379:     sscanf(dir + 2, "%d", &ray);

381:     PetscCall(PetscInfo(((PetscObject)ts), "Displaying LG DMDA ray %c = %d\n", dir[0], ray));
382:     PetscCall(PetscNew(&rayctx));
383:     PetscCall(TSGetDM(ts, &da));
384:     PetscCall(DMDAGetRay(da, ddir, ray, &rayctx->ray, &rayctx->scatter));
385:     PetscCall(TSMonitorLGCtxCreate(PETSC_COMM_SELF, NULL, NULL, PETSC_DECIDE, PETSC_DECIDE, 600, 400, howoften, &rayctx->lgctx));
386:     PetscCall(TSMonitorSet(ts, TSMonitorLGDMDARay, rayctx, TSMonitorDMDARayDestroy));
387:   }

389:   PetscCall(PetscOptionsName("-ts_monitor_envelope", "Monitor maximum and minimum value of each component of the solution", "TSMonitorEnvelope", &opt));
390:   if (opt) {
391:     TSMonitorEnvelopeCtx ctx;

393:     PetscCall(TSMonitorEnvelopeCtxCreate(ts, &ctx));
394:     PetscCall(TSMonitorSet(ts, TSMonitorEnvelope, ctx, (PetscErrorCode(*)(void **))TSMonitorEnvelopeCtxDestroy));
395:   }
396:   flg = PETSC_FALSE;
397:   PetscCall(PetscOptionsBool("-ts_monitor_cancel", "Remove all monitors", "TSMonitorCancel", flg, &flg, &opt));
398:   if (opt && flg) PetscCall(TSMonitorCancel(ts));

400:   flg = PETSC_FALSE;
401:   PetscCall(PetscOptionsBool("-ts_fd_color", "Use finite differences with coloring to compute IJacobian", "TSComputeIJacobianDefaultColor", flg, &flg, NULL));
402:   if (flg) {
403:     DM dm;

405:     PetscCall(TSGetDM(ts, &dm));
406:     PetscCall(DMTSUnsetIJacobianContext_Internal(dm));
407:     PetscCall(TSSetIJacobian(ts, NULL, NULL, TSComputeIJacobianDefaultColor, NULL));
408:     PetscCall(PetscInfo(ts, "Setting default finite difference coloring Jacobian matrix\n"));
409:   }

411:   /* Handle specific TS options */
412:   PetscTryTypeMethod(ts, setfromoptions, PetscOptionsObject);

414:   /* Handle TSAdapt options */
415:   PetscCall(TSGetAdapt(ts, &ts->adapt));
416:   PetscCall(TSAdaptSetDefaultType(ts->adapt, ts->default_adapt_type));
417:   PetscCall(TSAdaptSetFromOptions(ts->adapt, PetscOptionsObject));

419:   /* TS trajectory must be set after TS, since it may use some TS options above */
420:   tflg = ts->trajectory ? PETSC_TRUE : PETSC_FALSE;
421:   PetscCall(PetscOptionsBool("-ts_save_trajectory", "Save the solution at each timestep", "TSSetSaveTrajectory", tflg, &tflg, NULL));
422:   if (tflg) PetscCall(TSSetSaveTrajectory(ts));

424:   PetscCall(TSAdjointSetFromOptions(ts, PetscOptionsObject));

426:   /* process any options handlers added with PetscObjectAddOptionsHandler() */
427:   PetscCall(PetscObjectProcessOptionsHandlers((PetscObject)ts, PetscOptionsObject));
428:   PetscOptionsEnd();

430:   if (ts->trajectory) PetscCall(TSTrajectorySetFromOptions(ts->trajectory, ts));

432:   /* why do we have to do this here and not during TSSetUp? */
433:   PetscCall(TSGetSNES(ts, &ts->snes));
434:   if (ts->problem_type == TS_LINEAR) {
435:     PetscCall(PetscObjectTypeCompareAny((PetscObject)ts->snes, &flg, SNESKSPONLY, SNESKSPTRANSPOSEONLY, ""));
436:     if (!flg) PetscCall(SNESSetType(ts->snes, SNESKSPONLY));
437:   }
438:   PetscCall(SNESSetFromOptions(ts->snes));
439:   PetscFunctionReturn(PETSC_SUCCESS);
440: }

442: /*@
443:    TSGetTrajectory - Gets the trajectory from a `TS` if it exists

445:    Collective

447:    Input Parameters:
448: .  ts - the `TS` context obtained from `TSCreate()`

450:    Output Parameters:
451: .  tr - the `TSTrajectory` object, if it exists

453:    Level: advanced

455:    Note:
456:    This routine should be called after all `TS` options have been set

458: .seealso: [](chapter_ts), `TS`, `TSTrajectory`, `TSAdjointSolve()`, `TSTrajectory`, `TSTrajectoryCreate()`
459: @*/
460: PetscErrorCode TSGetTrajectory(TS ts, TSTrajectory *tr)
461: {
462:   PetscFunctionBegin;
464:   *tr = ts->trajectory;
465:   PetscFunctionReturn(PETSC_SUCCESS);
466: }

468: /*@
469:    TSSetSaveTrajectory - Causes the `TS` to save its solutions as it iterates forward in time in a `TSTrajectory` object

471:    Collective

473:    Input Parameter:
474: .  ts - the `TS` context obtained from `TSCreate()`

476:    Options Database Keys:
477: +  -ts_save_trajectory - saves the trajectory to a file
478: -  -ts_trajectory_type type - set trajectory type

480:    Level: intermediate

482:    Notes:
483:    This routine should be called after all `TS` options have been set

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

488: .seealso: [](chapter_ts), `TS`, `TSTrajectory`, `TSGetTrajectory()`, `TSAdjointSolve()`
489: @*/
490: PetscErrorCode TSSetSaveTrajectory(TS ts)
491: {
492:   PetscFunctionBegin;
494:   if (!ts->trajectory) PetscCall(TSTrajectoryCreate(PetscObjectComm((PetscObject)ts), &ts->trajectory));
495:   PetscFunctionReturn(PETSC_SUCCESS);
496: }

498: /*@
499:    TSResetTrajectory - Destroys and recreates the internal `TSTrajectory` object

501:    Collective

503:    Input Parameters:
504: .  ts - the `TS` context obtained from `TSCreate()`

506:    Level: intermediate

508: .seealso: [](chapter_ts), `TSTrajectory`, `TSGetTrajectory()`, `TSAdjointSolve()`, `TSRemoveTrajectory()`
509: @*/
510: PetscErrorCode TSResetTrajectory(TS ts)
511: {
512:   PetscFunctionBegin;
514:   if (ts->trajectory) {
515:     PetscCall(TSTrajectoryDestroy(&ts->trajectory));
516:     PetscCall(TSTrajectoryCreate(PetscObjectComm((PetscObject)ts), &ts->trajectory));
517:   }
518:   PetscFunctionReturn(PETSC_SUCCESS);
519: }

521: /*@
522:    TSRemoveTrajectory - Destroys and removes the internal `TSTrajectory` object from a `TS`

524:    Collective

526:    Input Parameters:
527: .  ts - the `TS` context obtained from `TSCreate()`

529:    Level: intermediate

531: .seealso: [](chapter_ts), `TSTrajectory`, `TSResetTrajectory()`, `TSAdjointSolve()`
532: @*/
533: PetscErrorCode TSRemoveTrajectory(TS ts)
534: {
535:   PetscFunctionBegin;
537:   if (ts->trajectory) PetscCall(TSTrajectoryDestroy(&ts->trajectory));
538:   PetscFunctionReturn(PETSC_SUCCESS);
539: }

541: /*@
542:    TSComputeRHSJacobian - Computes the Jacobian matrix that has been
543:       set with `TSSetRHSJacobian()`.

545:    Collective

547:    Input Parameters:
548: +  ts - the `TS` context
549: .  t - current timestep
550: -  U - input vector

552:    Output Parameters:
553: +  A - Jacobian matrix
554: -  B - optional preconditioning matrix

556:    Level: developer

558:    Note:
559:    Most users should not need to explicitly call this routine, as it
560:    is used internally within the nonlinear solvers.

562: .seealso: [](chapter_ts), `TS`, `TSSetRHSJacobian()`, `KSPSetOperators()`
563: @*/
564: PetscErrorCode TSComputeRHSJacobian(TS ts, PetscReal t, Vec U, Mat A, Mat B)
565: {
566:   PetscObjectState Ustate;
567:   PetscObjectId    Uid;
568:   DM               dm;
569:   DMTS             tsdm;
570:   TSRHSJacobian    rhsjacobianfunc;
571:   void            *ctx;
572:   TSRHSFunction    rhsfunction;

574:   PetscFunctionBegin;
577:   PetscCheckSameComm(ts, 1, U, 3);
578:   PetscCall(TSGetDM(ts, &dm));
579:   PetscCall(DMGetDMTS(dm, &tsdm));
580:   PetscCall(DMTSGetRHSFunction(dm, &rhsfunction, NULL));
581:   PetscCall(DMTSGetRHSJacobian(dm, &rhsjacobianfunc, &ctx));
582:   PetscCall(PetscObjectStateGet((PetscObject)U, &Ustate));
583:   PetscCall(PetscObjectGetId((PetscObject)U, &Uid));

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

587:   PetscCheck(ts->rhsjacobian.shift == 0.0 || !ts->rhsjacobian.reuse, PetscObjectComm((PetscObject)ts), PETSC_ERR_USER, "Should not call TSComputeRHSJacobian() on a shifted matrix (shift=%lf) when RHSJacobian is reusable.", (double)ts->rhsjacobian.shift);
588:   if (rhsjacobianfunc) {
589:     PetscCall(PetscLogEventBegin(TS_JacobianEval, ts, U, A, B));
590:     PetscCallBack("TS callback Jacobian", (*rhsjacobianfunc)(ts, t, U, A, B, ctx));
591:     ts->rhsjacs++;
592:     PetscCall(PetscLogEventEnd(TS_JacobianEval, ts, U, A, B));
593:   } else {
594:     PetscCall(MatZeroEntries(A));
595:     if (B && A != B) PetscCall(MatZeroEntries(B));
596:   }
597:   ts->rhsjacobian.time  = t;
598:   ts->rhsjacobian.shift = 0;
599:   ts->rhsjacobian.scale = 1.;
600:   PetscCall(PetscObjectGetId((PetscObject)U, &ts->rhsjacobian.Xid));
601:   PetscCall(PetscObjectStateGet((PetscObject)U, &ts->rhsjacobian.Xstate));
602:   PetscFunctionReturn(PETSC_SUCCESS);
603: }

605: /*@
606:    TSComputeRHSFunction - Evaluates the right-hand-side function for a `TS`

608:    Collective

610:    Input Parameters:
611: +  ts - the `TS` context
612: .  t - current time
613: -  U - state vector

615:    Output Parameter:
616: .  y - right hand side

618:    Level: developer

620:    Note:
621:    Most users should not need to explicitly call this routine, as it
622:    is used internally within the nonlinear solvers.

624: .seealso: [](chapter_ts), `TS`, `TSSetRHSFunction()`, `TSComputeIFunction()`
625: @*/
626: PetscErrorCode TSComputeRHSFunction(TS ts, PetscReal t, Vec U, Vec y)
627: {
628:   TSRHSFunction rhsfunction;
629:   TSIFunction   ifunction;
630:   void         *ctx;
631:   DM            dm;

633:   PetscFunctionBegin;
637:   PetscCall(TSGetDM(ts, &dm));
638:   PetscCall(DMTSGetRHSFunction(dm, &rhsfunction, &ctx));
639:   PetscCall(DMTSGetIFunction(dm, &ifunction, NULL));

641:   PetscCheck(rhsfunction || ifunction, PetscObjectComm((PetscObject)ts), PETSC_ERR_USER, "Must call TSSetRHSFunction() and / or TSSetIFunction()");

643:   if (rhsfunction) {
644:     PetscCall(PetscLogEventBegin(TS_FunctionEval, ts, U, y, 0));
645:     PetscCall(VecLockReadPush(U));
646:     PetscCallBack("TS callback right-hand-side", (*rhsfunction)(ts, t, U, y, ctx));
647:     PetscCall(VecLockReadPop(U));
648:     ts->rhsfuncs++;
649:     PetscCall(PetscLogEventEnd(TS_FunctionEval, ts, U, y, 0));
650:   } else PetscCall(VecZeroEntries(y));
651:   PetscFunctionReturn(PETSC_SUCCESS);
652: }

654: /*@
655:    TSComputeSolutionFunction - Evaluates the solution function.

657:    Collective

659:    Input Parameters:
660: +  ts - the `TS` context
661: -  t - current time

663:    Output Parameter:
664: .  U - the solution

666:    Level: developer

668: .seealso: [](chapter_ts), `TS`, `TSSetSolutionFunction()`, `TSSetRHSFunction()`, `TSComputeIFunction()`
669: @*/
670: PetscErrorCode TSComputeSolutionFunction(TS ts, PetscReal t, Vec U)
671: {
672:   TSSolutionFunction solutionfunction;
673:   void              *ctx;
674:   DM                 dm;

676:   PetscFunctionBegin;
679:   PetscCall(TSGetDM(ts, &dm));
680:   PetscCall(DMTSGetSolutionFunction(dm, &solutionfunction, &ctx));
681:   if (solutionfunction) PetscCallBack("TS callback solution", (*solutionfunction)(ts, t, U, ctx));
682:   PetscFunctionReturn(PETSC_SUCCESS);
683: }
684: /*@
685:    TSComputeForcingFunction - Evaluates the forcing function.

687:    Collective

689:    Input Parameters:
690: +  ts - the `TS` context
691: -  t - current time

693:    Output Parameter:
694: .  U - the function value

696:    Level: developer

698: .seealso: [](chapter_ts), `TS`, `TSSetSolutionFunction()`, `TSSetRHSFunction()`, `TSComputeIFunction()`
699: @*/
700: PetscErrorCode TSComputeForcingFunction(TS ts, PetscReal t, Vec U)
701: {
702:   void             *ctx;
703:   DM                dm;
704:   TSForcingFunction forcing;

706:   PetscFunctionBegin;
709:   PetscCall(TSGetDM(ts, &dm));
710:   PetscCall(DMTSGetForcingFunction(dm, &forcing, &ctx));

712:   if (forcing) PetscCallBack("TS callback forcing function", (*forcing)(ts, t, U, ctx));
713:   PetscFunctionReturn(PETSC_SUCCESS);
714: }

716: static PetscErrorCode TSGetRHSVec_Private(TS ts, Vec *Frhs)
717: {
718:   Vec F;

720:   PetscFunctionBegin;
721:   *Frhs = NULL;
722:   PetscCall(TSGetIFunction(ts, &F, NULL, NULL));
723:   if (!ts->Frhs) PetscCall(VecDuplicate(F, &ts->Frhs));
724:   *Frhs = ts->Frhs;
725:   PetscFunctionReturn(PETSC_SUCCESS);
726: }

728: PetscErrorCode TSGetRHSMats_Private(TS ts, Mat *Arhs, Mat *Brhs)
729: {
730:   Mat         A, B;
731:   TSIJacobian ijacobian;

733:   PetscFunctionBegin;
734:   if (Arhs) *Arhs = NULL;
735:   if (Brhs) *Brhs = NULL;
736:   PetscCall(TSGetIJacobian(ts, &A, &B, &ijacobian, NULL));
737:   if (Arhs) {
738:     if (!ts->Arhs) {
739:       if (ijacobian) {
740:         PetscCall(MatDuplicate(A, MAT_DO_NOT_COPY_VALUES, &ts->Arhs));
741:         PetscCall(TSSetMatStructure(ts, SAME_NONZERO_PATTERN));
742:       } else {
743:         ts->Arhs = A;
744:         PetscCall(PetscObjectReference((PetscObject)A));
745:       }
746:     } else {
747:       PetscBool flg;
748:       PetscCall(SNESGetUseMatrixFree(ts->snes, NULL, &flg));
749:       /* Handle case where user provided only RHSJacobian and used -snes_mf_operator */
750:       if (flg && !ijacobian && ts->Arhs == ts->Brhs) {
751:         PetscCall(PetscObjectDereference((PetscObject)ts->Arhs));
752:         ts->Arhs = A;
753:         PetscCall(PetscObjectReference((PetscObject)A));
754:       }
755:     }
756:     *Arhs = ts->Arhs;
757:   }
758:   if (Brhs) {
759:     if (!ts->Brhs) {
760:       if (A != B) {
761:         if (ijacobian) {
762:           PetscCall(MatDuplicate(B, MAT_DO_NOT_COPY_VALUES, &ts->Brhs));
763:         } else {
764:           ts->Brhs = B;
765:           PetscCall(PetscObjectReference((PetscObject)B));
766:         }
767:       } else {
768:         PetscCall(PetscObjectReference((PetscObject)ts->Arhs));
769:         ts->Brhs = ts->Arhs;
770:       }
771:     }
772:     *Brhs = ts->Brhs;
773:   }
774:   PetscFunctionReturn(PETSC_SUCCESS);
775: }

777: /*@
778:    TSComputeIFunction - Evaluates the DAE residual written in the implicit form F(t,U,Udot)=0

780:    Collective

782:    Input Parameters:
783: +  ts - the `TS` context
784: .  t - current time
785: .  U - state vector
786: .  Udot - time derivative of state vector
787: -  imex - flag indicates if the method is `TSIMEX` so that the RHSFunction should be kept separate

789:    Output Parameter:
790: .  Y - right hand side

792:    Level: developer

794:    Note:
795:    Most users should not need to explicitly call this routine, as it
796:    is used internally within the nonlinear solvers.

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

801: .seealso: [](chapter_ts), `TS`, `TSSetIFunction()`, `TSComputeRHSFunction()`
802: @*/
803: PetscErrorCode TSComputeIFunction(TS ts, PetscReal t, Vec U, Vec Udot, Vec Y, PetscBool imex)
804: {
805:   TSIFunction   ifunction;
806:   TSRHSFunction rhsfunction;
807:   void         *ctx;
808:   DM            dm;

810:   PetscFunctionBegin;

816:   PetscCall(TSGetDM(ts, &dm));
817:   PetscCall(DMTSGetIFunction(dm, &ifunction, &ctx));
818:   PetscCall(DMTSGetRHSFunction(dm, &rhsfunction, NULL));

820:   PetscCheck(rhsfunction || ifunction, PetscObjectComm((PetscObject)ts), PETSC_ERR_USER, "Must call TSSetRHSFunction() and / or TSSetIFunction()");

822:   PetscCall(PetscLogEventBegin(TS_FunctionEval, ts, U, Udot, Y));
823:   if (ifunction) {
824:     PetscCallBack("TS callback implicit function", (*ifunction)(ts, t, U, Udot, Y, ctx));
825:     ts->ifuncs++;
826:   }
827:   if (imex) {
828:     if (!ifunction) PetscCall(VecCopy(Udot, Y));
829:   } else if (rhsfunction) {
830:     if (ifunction) {
831:       Vec Frhs;
832:       PetscCall(TSGetRHSVec_Private(ts, &Frhs));
833:       PetscCall(TSComputeRHSFunction(ts, t, U, Frhs));
834:       PetscCall(VecAXPY(Y, -1, Frhs));
835:     } else {
836:       PetscCall(TSComputeRHSFunction(ts, t, U, Y));
837:       PetscCall(VecAYPX(Y, -1, Udot));
838:     }
839:   }
840:   PetscCall(PetscLogEventEnd(TS_FunctionEval, ts, U, Udot, Y));
841:   PetscFunctionReturn(PETSC_SUCCESS);
842: }

844: /*
845:    TSRecoverRHSJacobian - Recover the Jacobian matrix so that one can call `TSComputeRHSJacobian()` on it.

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

850: */
851: static PetscErrorCode TSRecoverRHSJacobian(TS ts, Mat A, Mat B)
852: {
853:   PetscFunctionBegin;
855:   PetscCheck(A == ts->Arhs, PetscObjectComm((PetscObject)ts), PETSC_ERR_SUP, "Invalid Amat");
856:   PetscCheck(B == ts->Brhs, PetscObjectComm((PetscObject)ts), PETSC_ERR_SUP, "Invalid Bmat");

858:   if (ts->rhsjacobian.shift) PetscCall(MatShift(A, -ts->rhsjacobian.shift));
859:   if (ts->rhsjacobian.scale == -1.) PetscCall(MatScale(A, -1));
860:   if (B && B == ts->Brhs && A != B) {
861:     if (ts->rhsjacobian.shift) PetscCall(MatShift(B, -ts->rhsjacobian.shift));
862:     if (ts->rhsjacobian.scale == -1.) PetscCall(MatScale(B, -1));
863:   }
864:   ts->rhsjacobian.shift = 0;
865:   ts->rhsjacobian.scale = 1.;
866:   PetscFunctionReturn(PETSC_SUCCESS);
867: }

869: /*@
870:    TSComputeIJacobian - Evaluates the Jacobian of the DAE

872:    Collective

874:    Input
875:       Input Parameters:
876: +  ts - the `TS` context
877: .  t - current timestep
878: .  U - state vector
879: .  Udot - time derivative of state vector
880: .  shift - shift to apply, see note below
881: -  imex - flag indicates if the method is `TSIMEX` so that the RHSJacobian should be kept separate

883:    Output Parameters:
884: +  A - Jacobian matrix
885: -  B - matrix from which the preconditioner is constructed; often the same as `A`

887:    Level: developer

889:    Notes:
890:    If F(t,U,Udot)=0 is the DAE, the required Jacobian is
891: .vb
892:    dF/dU + shift*dF/dUdot
893: .ve
894:    Most users should not need to explicitly call this routine, as it
895:    is used internally within the nonlinear solvers.

897: .seealso: [](chapter_ts), `TS`, `TSSetIJacobian()`
898: @*/
899: PetscErrorCode TSComputeIJacobian(TS ts, PetscReal t, Vec U, Vec Udot, PetscReal shift, Mat A, Mat B, PetscBool imex)
900: {
901:   TSIJacobian   ijacobian;
902:   TSRHSJacobian rhsjacobian;
903:   DM            dm;
904:   void         *ctx;

906:   PetscFunctionBegin;

915:   PetscCall(TSGetDM(ts, &dm));
916:   PetscCall(DMTSGetIJacobian(dm, &ijacobian, &ctx));
917:   PetscCall(DMTSGetRHSJacobian(dm, &rhsjacobian, NULL));

919:   PetscCheck(rhsjacobian || ijacobian, PetscObjectComm((PetscObject)ts), PETSC_ERR_USER, "Must call TSSetRHSJacobian() and / or TSSetIJacobian()");

921:   PetscCall(PetscLogEventBegin(TS_JacobianEval, ts, U, A, B));
922:   if (ijacobian) {
923:     PetscCallBack("TS callback implicit Jacobian", (*ijacobian)(ts, t, U, Udot, shift, A, B, ctx));
924:     ts->ijacs++;
925:   }
926:   if (imex) {
927:     if (!ijacobian) { /* system was written as Udot = G(t,U) */
928:       PetscBool assembled;
929:       if (rhsjacobian) {
930:         Mat Arhs = NULL;
931:         PetscCall(TSGetRHSMats_Private(ts, &Arhs, NULL));
932:         if (A == Arhs) {
933:           PetscCheck(rhsjacobian != TSComputeRHSJacobianConstant, 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 */
934:           ts->rhsjacobian.time = PETSC_MIN_REAL;
935:         }
936:       }
937:       PetscCall(MatZeroEntries(A));
938:       PetscCall(MatAssembled(A, &assembled));
939:       if (!assembled) {
940:         PetscCall(MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY));
941:         PetscCall(MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY));
942:       }
943:       PetscCall(MatShift(A, shift));
944:       if (A != B) {
945:         PetscCall(MatZeroEntries(B));
946:         PetscCall(MatAssembled(B, &assembled));
947:         if (!assembled) {
948:           PetscCall(MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY));
949:           PetscCall(MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY));
950:         }
951:         PetscCall(MatShift(B, shift));
952:       }
953:     }
954:   } else {
955:     Mat Arhs = NULL, Brhs = NULL;

957:     /* RHSJacobian needs to be converted to part of IJacobian if exists */
958:     if (rhsjacobian) PetscCall(TSGetRHSMats_Private(ts, &Arhs, &Brhs));
959:     if (Arhs == A) { /* No IJacobian matrix, so we only have the RHS matrix */
960:       PetscObjectState Ustate;
961:       PetscObjectId    Uid;
962:       TSRHSFunction    rhsfunction;

964:       PetscCall(DMTSGetRHSFunction(dm, &rhsfunction, NULL));
965:       PetscCall(PetscObjectStateGet((PetscObject)U, &Ustate));
966:       PetscCall(PetscObjectGetId((PetscObject)U, &Uid));
967:       if ((rhsjacobian == TSComputeRHSJacobianConstant || (ts->rhsjacobian.time == t && (ts->problem_type == TS_LINEAR || (ts->rhsjacobian.Xid == Uid && ts->rhsjacobian.Xstate == Ustate)) && rhsfunction != TSComputeRHSFunctionLinear)) &&
968:           ts->rhsjacobian.scale == -1.) {                      /* No need to recompute RHSJacobian */
969:         PetscCall(MatShift(A, shift - ts->rhsjacobian.shift)); /* revert the old shift and add the new shift with a single call to MatShift */
970:         if (A != B) PetscCall(MatShift(B, shift - ts->rhsjacobian.shift));
971:       } else {
972:         PetscBool flg;

974:         if (ts->rhsjacobian.reuse) { /* Undo the damage */
975:           /* MatScale has a short path for this case.
976:              However, this code path is taken the first time TSComputeRHSJacobian is called
977:              and the matrices have not been assembled yet */
978:           PetscCall(TSRecoverRHSJacobian(ts, A, B));
979:         }
980:         PetscCall(TSComputeRHSJacobian(ts, t, U, A, B));
981:         PetscCall(SNESGetUseMatrixFree(ts->snes, NULL, &flg));
982:         /* since -snes_mf_operator uses the full SNES function it does not need to be shifted or scaled here */
983:         if (!flg) {
984:           PetscCall(MatScale(A, -1));
985:           PetscCall(MatShift(A, shift));
986:         }
987:         if (A != B) {
988:           PetscCall(MatScale(B, -1));
989:           PetscCall(MatShift(B, shift));
990:         }
991:       }
992:       ts->rhsjacobian.scale = -1;
993:       ts->rhsjacobian.shift = shift;
994:     } else if (Arhs) {  /* Both IJacobian and RHSJacobian */
995:       if (!ijacobian) { /* No IJacobian provided, but we have a separate RHS matrix */
996:         PetscCall(MatZeroEntries(A));
997:         PetscCall(MatShift(A, shift));
998:         if (A != B) {
999:           PetscCall(MatZeroEntries(B));
1000:           PetscCall(MatShift(B, shift));
1001:         }
1002:       }
1003:       PetscCall(TSComputeRHSJacobian(ts, t, U, Arhs, Brhs));
1004:       PetscCall(MatAXPY(A, -1, Arhs, ts->axpy_pattern));
1005:       if (A != B) PetscCall(MatAXPY(B, -1, Brhs, ts->axpy_pattern));
1006:     }
1007:   }
1008:   PetscCall(PetscLogEventEnd(TS_JacobianEval, ts, U, A, B));
1009:   PetscFunctionReturn(PETSC_SUCCESS);
1010: }

1012: /*@C
1013:     TSSetRHSFunction - Sets the routine for evaluating the function,
1014:     where U_t = G(t,u).

1016:     Logically Collective

1018:     Input Parameters:
1019: +   ts - the `TS` context obtained from `TSCreate()`
1020: .   r - vector to put the computed right hand side (or `NULL` to have it created)
1021: .   f - routine for evaluating the right-hand-side function
1022: -   ctx - [optional] user-defined context for private data for the function evaluation routine (may be `NULL`)

1024:     Calling sequence of f:
1025: $     PetscErrorCode f(TS ts,PetscReal t,Vec u,Vec F,void *ctx);

1027: +   ts - timestep context
1028: .   t - current timestep
1029: .   u - input vector
1030: .   F - function vector
1031: -   ctx - [optional] user-defined function context

1033:     Level: beginner

1035:     Note:
1036:     You must call this function or `TSSetIFunction()` to define your ODE. You cannot use this function when solving a DAE.

1038: .seealso: [](chapter_ts), `TS`, `TSSetRHSJacobian()`, `TSSetIJacobian()`, `TSSetIFunction()`
1039: @*/
1040: PetscErrorCode TSSetRHSFunction(TS ts, Vec r, PetscErrorCode (*f)(TS, PetscReal, Vec, Vec, void *), void *ctx)
1041: {
1042:   SNES snes;
1043:   Vec  ralloc = NULL;
1044:   DM   dm;

1046:   PetscFunctionBegin;

1050:   PetscCall(TSGetDM(ts, &dm));
1051:   PetscCall(DMTSSetRHSFunction(dm, f, ctx));
1052:   PetscCall(TSGetSNES(ts, &snes));
1053:   if (!r && !ts->dm && ts->vec_sol) {
1054:     PetscCall(VecDuplicate(ts->vec_sol, &ralloc));
1055:     r = ralloc;
1056:   }
1057:   PetscCall(SNESSetFunction(snes, r, SNESTSFormFunction, ts));
1058:   PetscCall(VecDestroy(&ralloc));
1059:   PetscFunctionReturn(PETSC_SUCCESS);
1060: }

1062: /*@C
1063:     TSSetSolutionFunction - Provide a function that computes the solution of the ODE or DAE

1065:     Logically Collective

1067:     Input Parameters:
1068: +   ts - the `TS` context obtained from `TSCreate()`
1069: .   f - routine for evaluating the solution
1070: -   ctx - [optional] user-defined context for private data for the
1071:           function evaluation routine (may be `NULL`)

1073:     Calling sequence of f:
1074: $     PetscErrorCode f(TS ts,PetscReal t,Vec u,void *ctx);

1076: +   t - current timestep
1077: .   u - output vector
1078: -   ctx - [optional] user-defined function context

1080:     Options Database Keys:
1081: +  -ts_monitor_lg_error - create a graphical monitor of error history, requires user to have provided `TSSetSolutionFunction()`
1082: -  -ts_monitor_draw_error - Monitor error graphically, requires user to have provided `TSSetSolutionFunction()`

1084:     Level: intermediate

1086:     Notes:
1087:     This routine is used for testing accuracy of time integration schemes when you already know the solution.
1088:     If analytic solutions are not known for your system, consider using the Method of Manufactured Solutions to
1089:     create closed-form solutions with non-physical forcing terms.

1091:     For low-dimensional problems solved in serial, such as small discrete systems, `TSMonitorLGError()` can be used to monitor the error history.

1093: .seealso: [](chapter_ts), `TS`, `TSSetRHSJacobian()`, `TSSetIJacobian()`, `TSComputeSolutionFunction()`, `TSSetForcingFunction()`, `TSSetSolution()`, `TSGetSolution()`, `TSMonitorLGError()`, `TSMonitorDrawError()`
1094: @*/
1095: PetscErrorCode TSSetSolutionFunction(TS ts, PetscErrorCode (*f)(TS, PetscReal, Vec, void *), void *ctx)
1096: {
1097:   DM dm;

1099:   PetscFunctionBegin;
1101:   PetscCall(TSGetDM(ts, &dm));
1102:   PetscCall(DMTSSetSolutionFunction(dm, f, ctx));
1103:   PetscFunctionReturn(PETSC_SUCCESS);
1104: }

1106: /*@C
1107:     TSSetForcingFunction - Provide a function that computes a forcing term for a ODE or PDE

1109:     Logically Collective

1111:     Input Parameters:
1112: +   ts - the `TS` context obtained from `TSCreate()`
1113: .   func - routine for evaluating the forcing function
1114: -   ctx - [optional] user-defined context for private data for the
1115:           function evaluation routine (may be `NULL`)

1117:     Calling sequence of func:
1118: $     PetscErrorCode func (TS ts,PetscReal t,Vec f,void *ctx);

1120: +   t - current timestep
1121: .   f - output vector
1122: -   ctx - [optional] user-defined function context

1124:     Level: intermediate

1126:     Notes:
1127:     This routine is useful for testing accuracy of time integration schemes when using the Method of Manufactured Solutions to
1128:     create closed-form solutions with a non-physical forcing term. It allows you to use the Method of Manufactored Solution without directly editing the
1129:     definition of the problem you are solving and hence possibly introducing bugs.

1131:     This replaces the ODE F(u,u_t,t) = 0 the TS is solving with F(u,u_t,t) - func(t) = 0

1133:     This forcing function does not depend on the solution to the equations, it can only depend on spatial location, time, and possibly parameters, the
1134:     parameters can be passed in the ctx variable.

1136:     For low-dimensional problems solved in serial, such as small discrete systems, `TSMonitorLGError()` can be used to monitor the error history.

1138: .seealso: [](chapter_ts), `TS`, `TSSetRHSJacobian()`, `TSSetIJacobian()`, `TSComputeSolutionFunction()`, `TSSetSolutionFunction()`
1139: @*/
1140: PetscErrorCode TSSetForcingFunction(TS ts, TSForcingFunction func, void *ctx)
1141: {
1142:   DM dm;

1144:   PetscFunctionBegin;
1146:   PetscCall(TSGetDM(ts, &dm));
1147:   PetscCall(DMTSSetForcingFunction(dm, func, ctx));
1148:   PetscFunctionReturn(PETSC_SUCCESS);
1149: }

1151: /*@C
1152:    TSSetRHSJacobian - Sets the function to compute the Jacobian of G,
1153:    where U_t = G(U,t), as well as the location to store the matrix.

1155:    Logically Collective

1157:    Input Parameters:
1158: +  ts  - the `TS` context obtained from `TSCreate()`
1159: .  Amat - (approximate) location to store Jacobian matrix entries computed by `f`
1160: .  Pmat - matrix from which preconditioner is to be constructed (usually the same as `Amat`)
1161: .  f   - the Jacobian evaluation routine
1162: -  ctx - [optional] user-defined context for private data for the Jacobian evaluation routine (may be `NULL`)

1164:    Calling sequence of f:
1165: $     PetscErrorCode f(TS ts,PetscReal t,Vec u,Mat A,Mat B,void *ctx);

1167: +  t - current timestep
1168: .  u - input vector
1169: .  Amat - (approximate) Jacobian matrix
1170: .  Pmat - matrix from which preconditioner is to be constructed (usually the same as `Amat`)
1171: -  ctx - [optional] user-defined context for matrix evaluation routine

1173:    Level: beginner

1175:    Notes:
1176:    You must set all the diagonal entries of the matrices, if they are zero you must still set them with a zero value

1178:    The `TS` solver may modify the nonzero structure and the entries of the matrices Amat and Pmat between the calls to f()
1179:    You should not assume the values are the same in the next call to f() as you set them in the previous call.

1181: .seealso: [](chapter_ts), `TS`, `SNESComputeJacobianDefaultColor()`, `TSSetRHSFunction()`, `TSRHSJacobianSetReuse()`, `TSSetIJacobian()`
1182: @*/
1183: PetscErrorCode TSSetRHSJacobian(TS ts, Mat Amat, Mat Pmat, TSRHSJacobian f, void *ctx)
1184: {
1185:   SNES        snes;
1186:   DM          dm;
1187:   TSIJacobian ijacobian;

1189:   PetscFunctionBegin;
1193:   if (Amat) PetscCheckSameComm(ts, 1, Amat, 2);
1194:   if (Pmat) PetscCheckSameComm(ts, 1, Pmat, 3);

1196:   PetscCall(TSGetDM(ts, &dm));
1197:   PetscCall(DMTSSetRHSJacobian(dm, f, ctx));
1198:   PetscCall(DMTSGetIJacobian(dm, &ijacobian, NULL));
1199:   PetscCall(TSGetSNES(ts, &snes));
1200:   if (!ijacobian) PetscCall(SNESSetJacobian(snes, Amat, Pmat, SNESTSFormJacobian, ts));
1201:   if (Amat) {
1202:     PetscCall(PetscObjectReference((PetscObject)Amat));
1203:     PetscCall(MatDestroy(&ts->Arhs));
1204:     ts->Arhs = Amat;
1205:   }
1206:   if (Pmat) {
1207:     PetscCall(PetscObjectReference((PetscObject)Pmat));
1208:     PetscCall(MatDestroy(&ts->Brhs));
1209:     ts->Brhs = Pmat;
1210:   }
1211:   PetscFunctionReturn(PETSC_SUCCESS);
1212: }

1214: /*@C
1215:    TSSetIFunction - Set the function to compute F(t,U,U_t) where F() = 0 is the DAE to be solved.

1217:    Logically Collective

1219:    Input Parameters:
1220: +  ts  - the `TS` context obtained from `TSCreate()`
1221: .  r   - vector to hold the residual (or `NULL` to have it created internally)
1222: .  f   - the function evaluation routine
1223: -  ctx - user-defined context for private data for the function evaluation routine (may be `NULL`)

1225:    Calling sequence of f:
1226: $     PetscErrorCode f(TS ts,PetscReal t,Vec u,Vec u_t,Vec F,ctx);

1228: +  t   - time at step/stage being solved
1229: .  u   - state vector
1230: .  u_t - time derivative of state vector
1231: .  F   - function vector
1232: -  ctx - [optional] user-defined context for matrix evaluation routine

1234:    Level: beginner

1236:    Note:
1237:    The user MUST call either this routine or `TSSetRHSFunction()` to define the ODE.  When solving DAEs you must use this function.

1239: .seealso: [](chapter_ts), `TS`, `TSSetRHSJacobian()`, `TSSetRHSFunction()`, `TSSetIJacobian()`
1240: @*/
1241: PetscErrorCode TSSetIFunction(TS ts, Vec r, TSIFunction f, void *ctx)
1242: {
1243:   SNES snes;
1244:   Vec  ralloc = NULL;
1245:   DM   dm;

1247:   PetscFunctionBegin;

1251:   PetscCall(TSGetDM(ts, &dm));
1252:   PetscCall(DMTSSetIFunction(dm, f, ctx));

1254:   PetscCall(TSGetSNES(ts, &snes));
1255:   if (!r && !ts->dm && ts->vec_sol) {
1256:     PetscCall(VecDuplicate(ts->vec_sol, &ralloc));
1257:     r = ralloc;
1258:   }
1259:   PetscCall(SNESSetFunction(snes, r, SNESTSFormFunction, ts));
1260:   PetscCall(VecDestroy(&ralloc));
1261:   PetscFunctionReturn(PETSC_SUCCESS);
1262: }

1264: /*@C
1265:    TSGetIFunction - Returns the vector where the implicit residual is stored and the function/context to compute it.

1267:    Not Collective

1269:    Input Parameter:
1270: .  ts - the `TS` context

1272:    Output Parameters:
1273: +  r - vector to hold residual (or `NULL`)
1274: .  func - the function to compute residual (or `NULL`)
1275: -  ctx - the function context (or `NULL`)

1277:    Level: advanced

1279: .seealso: [](chapter_ts), `TS`, `TSSetIFunction()`, `SNESGetFunction()`
1280: @*/
1281: PetscErrorCode TSGetIFunction(TS ts, Vec *r, TSIFunction *func, void **ctx)
1282: {
1283:   SNES snes;
1284:   DM   dm;

1286:   PetscFunctionBegin;
1288:   PetscCall(TSGetSNES(ts, &snes));
1289:   PetscCall(SNESGetFunction(snes, r, NULL, NULL));
1290:   PetscCall(TSGetDM(ts, &dm));
1291:   PetscCall(DMTSGetIFunction(dm, func, ctx));
1292:   PetscFunctionReturn(PETSC_SUCCESS);
1293: }

1295: /*@C
1296:    TSGetRHSFunction - Returns the vector where the right hand side is stored and the function/context to compute it.

1298:    Not Collective

1300:    Input Parameter:
1301: .  ts - the `TS` context

1303:    Output Parameters:
1304: +  r - vector to hold computed right hand side (or `NULL`)
1305: .  func - the function to compute right hand side (or `NULL`)
1306: -  ctx - the function context (or `NULL`)

1308:    Level: advanced

1310: .seealso: [](chapter_ts), `TS`, `TSSetRHSFunction()`, `SNESGetFunction()`
1311: @*/
1312: PetscErrorCode TSGetRHSFunction(TS ts, Vec *r, TSRHSFunction *func, void **ctx)
1313: {
1314:   SNES snes;
1315:   DM   dm;

1317:   PetscFunctionBegin;
1319:   PetscCall(TSGetSNES(ts, &snes));
1320:   PetscCall(SNESGetFunction(snes, r, NULL, NULL));
1321:   PetscCall(TSGetDM(ts, &dm));
1322:   PetscCall(DMTSGetRHSFunction(dm, func, ctx));
1323:   PetscFunctionReturn(PETSC_SUCCESS);
1324: }

1326: /*@C
1327:    TSSetIJacobian - Set the function to compute the matrix dF/dU + a*dF/dU_t where F(t,U,U_t) is the function
1328:         provided with `TSSetIFunction()`.

1330:    Logically Collective

1332:    Input Parameters:
1333: +  ts  - the `TS` context obtained from `TSCreate()`
1334: .  Amat - (approximate) matrix to store Jacobian entires computed by `f`
1335: .  Pmat - matrix used to compute preconditioner (usually the same as `Amat`)
1336: .  f   - the Jacobian evaluation routine
1337: -  ctx - user-defined context for private data for the Jacobian evaluation routine (may be `NULL`)

1339:    Calling sequence of f:
1340: $    PetscErrorCode f(TS ts,PetscReal t,Vec U,Vec U_t,PetscReal a,Mat Amat,Mat Pmat,void *ctx);

1342: +  t    - time at step/stage being solved
1343: .  U    - state vector
1344: .  U_t  - time derivative of state vector
1345: .  a    - shift
1346: .  Amat - (approximate) Jacobian of F(t,U,W+a*U), equivalent to dF/dU + a*dF/dU_t
1347: .  Pmat - matrix used for constructing preconditioner, usually the same as `Amat`
1348: -  ctx  - [optional] user-defined context for matrix evaluation routine

1350:    Level: beginner

1352:    Notes:
1353:    The matrices `Amat` and `Pmat` are exactly the matrices that are used by `SNES` for the nonlinear solve.

1355:    If you know the operator Amat has a null space you can use `MatSetNullSpace()` and `MatSetTransposeNullSpace()` to supply the null
1356:    space to `Amat` and the `KSP` solvers will automatically use that null space as needed during the solution process.

1358:    The matrix dF/dU + a*dF/dU_t you provide turns out to be
1359:    the Jacobian of F(t,U,W+a*U) where F(t,U,U_t) = 0 is the DAE to be solved.
1360:    The time integrator internally approximates U_t by W+a*U where the positive "shift"
1361:    a and vector W depend on the integration method, step size, and past states. For example with
1362:    the backward Euler method a = 1/dt and W = -a*U(previous timestep) so
1363:    W + a*U = a*(U - U(previous timestep)) = (U - U(previous timestep))/dt

1365:    You must set all the diagonal entries of the matrices, if they are zero you must still set them with a zero value

1367:    The TS solver may modify the nonzero structure and the entries of the matrices `Amat` and `Pmat` between the calls to `f`
1368:    You should not assume the values are the same in the next call to `f` as you set them in the previous call.

1370: .seealso: [](chapter_ts), `TS`, `TSSetIFunction()`, `TSSetRHSJacobian()`, `SNESComputeJacobianDefaultColor()`, `SNESComputeJacobianDefault()`, `TSSetRHSFunction()`
1371: @*/
1372: PetscErrorCode TSSetIJacobian(TS ts, Mat Amat, Mat Pmat, TSIJacobian f, void *ctx)
1373: {
1374:   SNES snes;
1375:   DM   dm;

1377:   PetscFunctionBegin;
1381:   if (Amat) PetscCheckSameComm(ts, 1, Amat, 2);
1382:   if (Pmat) PetscCheckSameComm(ts, 1, Pmat, 3);

1384:   PetscCall(TSGetDM(ts, &dm));
1385:   PetscCall(DMTSSetIJacobian(dm, f, ctx));

1387:   PetscCall(TSGetSNES(ts, &snes));
1388:   PetscCall(SNESSetJacobian(snes, Amat, Pmat, SNESTSFormJacobian, ts));
1389:   PetscFunctionReturn(PETSC_SUCCESS);
1390: }

1392: /*@
1393:    TSRHSJacobianSetReuse - restore RHS Jacobian before re-evaluating.  Without this flag, `TS` will change the sign and
1394:    shift the RHS Jacobian for a finite-time-step implicit solve, in which case the user function will need to recompute
1395:    the entire Jacobian.  The reuse flag must be set if the evaluation function will assume that the matrix entries have
1396:    not been changed by the `TS`.

1398:    Logically Collective

1400:    Input Parameters:
1401: +  ts - `TS` context obtained from `TSCreate()`
1402: -  reuse - `PETSC_TRUE` if the RHS Jacobian

1404:    Level: intermediate

1406: .seealso: [](chapter_ts), `TS`, `TSSetRHSJacobian()`, `TSComputeRHSJacobianConstant()`
1407: @*/
1408: PetscErrorCode TSRHSJacobianSetReuse(TS ts, PetscBool reuse)
1409: {
1410:   PetscFunctionBegin;
1411:   ts->rhsjacobian.reuse = reuse;
1412:   PetscFunctionReturn(PETSC_SUCCESS);
1413: }

1415: /*@C
1416:    TSSetI2Function - Set the function to compute F(t,U,U_t,U_tt) where F = 0 is the DAE to be solved.

1418:    Logically Collective

1420:    Input Parameters:
1421: +  ts  - the `TS` context obtained from `TSCreate()`
1422: .  F   - vector to hold the residual (or `NULL` to have it created internally)
1423: .  fun - the function evaluation routine
1424: -  ctx - user-defined context for private data for the function evaluation routine (may be `NULL`)

1426:    Calling sequence of fun:
1427: $     PetscErrorCode fun(TS ts,PetscReal t,Vec U,Vec U_t,Vec U_tt,Vec F,ctx);

1429: +  t    - time at step/stage being solved
1430: .  U    - state vector
1431: .  U_t  - time derivative of state vector
1432: .  U_tt - second time derivative of state vector
1433: .  F    - function vector
1434: -  ctx  - [optional] user-defined context for matrix evaluation routine (may be `NULL`)

1436:    Level: beginner

1438: .seealso: [](chapter_ts), `TS`, `TSSetI2Jacobian()`, `TSSetIFunction()`, `TSCreate()`, `TSSetRHSFunction()`
1439: @*/
1440: PetscErrorCode TSSetI2Function(TS ts, Vec F, TSI2Function fun, void *ctx)
1441: {
1442:   DM dm;

1444:   PetscFunctionBegin;
1447:   PetscCall(TSSetIFunction(ts, F, NULL, NULL));
1448:   PetscCall(TSGetDM(ts, &dm));
1449:   PetscCall(DMTSSetI2Function(dm, fun, ctx));
1450:   PetscFunctionReturn(PETSC_SUCCESS);
1451: }

1453: /*@C
1454:   TSGetI2Function - Returns the vector where the implicit residual is stored and the function/context to compute it.

1456:   Not Collective

1458:   Input Parameter:
1459: . ts - the `TS` context

1461:   Output Parameters:
1462: + r - vector to hold residual (or `NULL`)
1463: . fun - the function to compute residual (or `NULL`)
1464: - ctx - the function context (or `NULL`)

1466:   Level: advanced

1468: .seealso: [](chapter_ts), `TS`, `TSSetIFunction()`, `SNESGetFunction()`, `TSCreate()`
1469: @*/
1470: PetscErrorCode TSGetI2Function(TS ts, Vec *r, TSI2Function *fun, void **ctx)
1471: {
1472:   SNES snes;
1473:   DM   dm;

1475:   PetscFunctionBegin;
1477:   PetscCall(TSGetSNES(ts, &snes));
1478:   PetscCall(SNESGetFunction(snes, r, NULL, NULL));
1479:   PetscCall(TSGetDM(ts, &dm));
1480:   PetscCall(DMTSGetI2Function(dm, fun, ctx));
1481:   PetscFunctionReturn(PETSC_SUCCESS);
1482: }

1484: /*@C
1485:    TSSetI2Jacobian - Set the function to compute the matrix dF/dU + v*dF/dU_t  + a*dF/dU_tt
1486:         where F(t,U,U_t,U_tt) is the function you provided with `TSSetI2Function()`.

1488:    Logically Collective

1490:    Input Parameters:
1491: +  ts  - the `TS` context obtained from `TSCreate()`
1492: .  J   - matrix to hold the Jacobian values
1493: .  P   - matrix for constructing the preconditioner (may be same as `J`)
1494: .  jac - the Jacobian evaluation routine
1495: -  ctx - user-defined context for private data for the Jacobian evaluation routine (may be `NULL`)

1497:    Calling sequence of jac:
1498: $    PetscErrorCode jac(TS ts,PetscReal t,Vec U,Vec U_t,Vec U_tt,PetscReal v,PetscReal a,Mat J,Mat P,void *ctx);

1500: +  t    - time at step/stage being solved
1501: .  U    - state vector
1502: .  U_t  - time derivative of state vector
1503: .  U_tt - second time derivative of state vector
1504: .  v    - shift for U_t
1505: .  a    - shift for U_tt
1506: .  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
1507: .  P    - preconditioning matrix for J, may be same as J
1508: -  ctx  - [optional] user-defined context for matrix evaluation routine

1510:    Level: beginner

1512:    Notes:
1513:    The matrices `J` and `P` are exactly the matrices that are used by `SNES` for the nonlinear solve.

1515:    The matrix dF/dU + v*dF/dU_t + a*dF/dU_tt you provide turns out to be
1516:    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.
1517:    The time integrator internally approximates U_t by W+v*U and U_tt by W'+a*U  where the positive "shift"
1518:    parameters 'v' and 'a' and vectors W, W' depend on the integration method, step size, and past states.

1520: .seealso: [](chapter_ts), `TS`, `TSSetI2Function()`, `TSGetI2Jacobian()`
1521: @*/
1522: PetscErrorCode TSSetI2Jacobian(TS ts, Mat J, Mat P, TSI2Jacobian jac, void *ctx)
1523: {
1524:   DM dm;

1526:   PetscFunctionBegin;
1530:   PetscCall(TSSetIJacobian(ts, J, P, NULL, NULL));
1531:   PetscCall(TSGetDM(ts, &dm));
1532:   PetscCall(DMTSSetI2Jacobian(dm, jac, ctx));
1533:   PetscFunctionReturn(PETSC_SUCCESS);
1534: }

1536: /*@C
1537:   TSGetI2Jacobian - Returns the implicit Jacobian at the present timestep.

1539:   Not Collective, but parallel objects are returned if `TS` is parallel

1541:   Input Parameter:
1542: . ts  - The `TS` context obtained from `TSCreate()`

1544:   Output Parameters:
1545: + J  - The (approximate) Jacobian of F(t,U,U_t,U_tt)
1546: . P - The matrix from which the preconditioner is constructed, often the same as `J`
1547: . jac - The function to compute the Jacobian matrices
1548: - ctx - User-defined context for Jacobian evaluation routine

1550:   Level: advanced

1552:   Note:
1553:     You can pass in `NULL` for any return argument you do not need.

1555: .seealso: [](chapter_ts), `TS`, `TSGetTimeStep()`, `TSGetMatrices()`, `TSGetTime()`, `TSGetStepNumber()`, `TSSetI2Jacobian()`, `TSGetI2Function()`, `TSCreate()`
1556: @*/
1557: PetscErrorCode TSGetI2Jacobian(TS ts, Mat *J, Mat *P, TSI2Jacobian *jac, void **ctx)
1558: {
1559:   SNES snes;
1560:   DM   dm;

1562:   PetscFunctionBegin;
1563:   PetscCall(TSGetSNES(ts, &snes));
1564:   PetscCall(SNESSetUpMatrices(snes));
1565:   PetscCall(SNESGetJacobian(snes, J, P, NULL, NULL));
1566:   PetscCall(TSGetDM(ts, &dm));
1567:   PetscCall(DMTSGetI2Jacobian(dm, jac, ctx));
1568:   PetscFunctionReturn(PETSC_SUCCESS);
1569: }

1571: /*@
1572:   TSComputeI2Function - Evaluates the DAE residual written in implicit form F(t,U,U_t,U_tt) = 0

1574:   Collective

1576:   Input Parameters:
1577: + ts - the `TS` context
1578: . t - current time
1579: . U - state vector
1580: . V - time derivative of state vector (U_t)
1581: - A - second time derivative of state vector (U_tt)

1583:   Output Parameter:
1584: . F - the residual vector

1586:   Level: developer

1588:   Note:
1589:   Most users should not need to explicitly call this routine, as it
1590:   is used internally within the nonlinear solvers.

1592: .seealso: [](chapter_ts), `TS`, `TSSetI2Function()`, `TSGetI2Function()`
1593: @*/
1594: PetscErrorCode TSComputeI2Function(TS ts, PetscReal t, Vec U, Vec V, Vec A, Vec F)
1595: {
1596:   DM            dm;
1597:   TSI2Function  I2Function;
1598:   void         *ctx;
1599:   TSRHSFunction rhsfunction;

1601:   PetscFunctionBegin;

1608:   PetscCall(TSGetDM(ts, &dm));
1609:   PetscCall(DMTSGetI2Function(dm, &I2Function, &ctx));
1610:   PetscCall(DMTSGetRHSFunction(dm, &rhsfunction, NULL));

1612:   if (!I2Function) {
1613:     PetscCall(TSComputeIFunction(ts, t, U, A, F, PETSC_FALSE));
1614:     PetscFunctionReturn(PETSC_SUCCESS);
1615:   }

1617:   PetscCall(PetscLogEventBegin(TS_FunctionEval, ts, U, V, F));

1619:   PetscCallBack("TS callback implicit function", I2Function(ts, t, U, V, A, F, ctx));

1621:   if (rhsfunction) {
1622:     Vec Frhs;
1623:     PetscCall(TSGetRHSVec_Private(ts, &Frhs));
1624:     PetscCall(TSComputeRHSFunction(ts, t, U, Frhs));
1625:     PetscCall(VecAXPY(F, -1, Frhs));
1626:   }

1628:   PetscCall(PetscLogEventEnd(TS_FunctionEval, ts, U, V, F));
1629:   PetscFunctionReturn(PETSC_SUCCESS);
1630: }

1632: /*@
1633:   TSComputeI2Jacobian - Evaluates the Jacobian of the DAE

1635:   Collective

1637:   Input Parameters:
1638: + ts - the `TS` context
1639: . t - current timestep
1640: . U - state vector
1641: . V - time derivative of state vector
1642: . A - second time derivative of state vector
1643: . shiftV - shift to apply, see note below
1644: - shiftA - shift to apply, see note below

1646:   Output Parameters:
1647: + J - Jacobian matrix
1648: - P - optional preconditioning matrix

1650:   Level: developer

1652:   Notes:
1653:   If F(t,U,V,A)=0 is the DAE, the required Jacobian is

1655:   dF/dU + shiftV*dF/dV + shiftA*dF/dA

1657:   Most users should not need to explicitly call this routine, as it
1658:   is used internally within the nonlinear solvers.

1660: .seealso: [](chapter_ts), `TS`, `TSSetI2Jacobian()`
1661: @*/
1662: PetscErrorCode TSComputeI2Jacobian(TS ts, PetscReal t, Vec U, Vec V, Vec A, PetscReal shiftV, PetscReal shiftA, Mat J, Mat P)
1663: {
1664:   DM            dm;
1665:   TSI2Jacobian  I2Jacobian;
1666:   void         *ctx;
1667:   TSRHSJacobian rhsjacobian;

1669:   PetscFunctionBegin;

1677:   PetscCall(TSGetDM(ts, &dm));
1678:   PetscCall(DMTSGetI2Jacobian(dm, &I2Jacobian, &ctx));
1679:   PetscCall(DMTSGetRHSJacobian(dm, &rhsjacobian, NULL));

1681:   if (!I2Jacobian) {
1682:     PetscCall(TSComputeIJacobian(ts, t, U, A, shiftA, J, P, PETSC_FALSE));
1683:     PetscFunctionReturn(PETSC_SUCCESS);
1684:   }

1686:   PetscCall(PetscLogEventBegin(TS_JacobianEval, ts, U, J, P));
1687:   PetscCallBack("TS callback implicit Jacobian", I2Jacobian(ts, t, U, V, A, shiftV, shiftA, J, P, ctx));
1688:   if (rhsjacobian) {
1689:     Mat Jrhs, Prhs;
1690:     PetscCall(TSGetRHSMats_Private(ts, &Jrhs, &Prhs));
1691:     PetscCall(TSComputeRHSJacobian(ts, t, U, Jrhs, Prhs));
1692:     PetscCall(MatAXPY(J, -1, Jrhs, ts->axpy_pattern));
1693:     if (P != J) PetscCall(MatAXPY(P, -1, Prhs, ts->axpy_pattern));
1694:   }

1696:   PetscCall(PetscLogEventEnd(TS_JacobianEval, ts, U, J, P));
1697:   PetscFunctionReturn(PETSC_SUCCESS);
1698: }

1700: /*@C
1701:    TSSetTransientVariable - sets function to transform from state to transient variables

1703:    Logically Collective

1705:    Input Parameters:
1706: +  ts - time stepping context on which to change the transient variable
1707: .  tvar - a function that transforms to transient variables
1708: -  ctx - a context for tvar

1710:     Calling sequence of tvar:
1711: $     PetscErrorCode tvar(TS ts,Vec p,Vec c,void *ctx);

1713: +   ts - timestep context
1714: .   p - input vector (primitive form)
1715: .   c - output vector, transient variables (conservative form)
1716: -   ctx - [optional] user-defined function context

1718:    Level: advanced

1720:    Notes:
1721:    This is typically used to transform from primitive to conservative variables so that a time integrator (e.g., `TSBDF`)
1722:    can be conservative.  In this context, primitive variables P are used to model the state (e.g., because they lead to
1723:    well-conditioned formulations even in limiting cases such as low-Mach or zero porosity).  The transient variable is
1724:    C(P), specified by calling this function.  An IFunction thus receives arguments (P, Cdot) and the IJacobian must be
1725:    evaluated via the chain rule, as in
1726: .vb
1727:      dF/dP + shift * dF/dCdot dC/dP.
1728: .ve

1730: .seealso: [](chapter_ts), `TS`, `TSBDF`, `DMTSSetTransientVariable()`, `DMTSGetTransientVariable()`, `TSSetIFunction()`, `TSSetIJacobian()`
1731: @*/
1732: PetscErrorCode TSSetTransientVariable(TS ts, TSTransientVariable tvar, void *ctx)
1733: {
1734:   DM dm;

1736:   PetscFunctionBegin;
1738:   PetscCall(TSGetDM(ts, &dm));
1739:   PetscCall(DMTSSetTransientVariable(dm, tvar, ctx));
1740:   PetscFunctionReturn(PETSC_SUCCESS);
1741: }

1743: /*@
1744:    TSComputeTransientVariable - transforms state (primitive) variables to transient (conservative) variables

1746:    Logically Collective

1748:    Input Parameters:
1749: +  ts - TS on which to compute
1750: -  U - state vector to be transformed to transient variables

1752:    Output Parameters:
1753: .  C - transient (conservative) variable

1755:    Level: developer

1757:    Developer Note:
1758:    If `DMTSSetTransientVariable()` has not been called, then C is not modified in this routine and C = `NULL` is allowed.
1759:    This makes it safe to call without a guard.  One can use `TSHasTransientVariable()` to check if transient variables are
1760:    being used.

1762: .seealso: [](chapter_ts), `TS`, `TSBDF`, `DMTSSetTransientVariable()`, `TSComputeIFunction()`, `TSComputeIJacobian()`
1763: @*/
1764: PetscErrorCode TSComputeTransientVariable(TS ts, Vec U, Vec C)
1765: {
1766:   DM   dm;
1767:   DMTS dmts;

1769:   PetscFunctionBegin;
1772:   PetscCall(TSGetDM(ts, &dm));
1773:   PetscCall(DMGetDMTS(dm, &dmts));
1774:   if (dmts->ops->transientvar) {
1776:     PetscCall((*dmts->ops->transientvar)(ts, U, C, dmts->transientvarctx));
1777:   }
1778:   PetscFunctionReturn(PETSC_SUCCESS);
1779: }

1781: /*@
1782:    TSHasTransientVariable - determine whether transient variables have been set

1784:    Logically Collective

1786:    Input Parameters:
1787: .  ts - `TS` on which to compute

1789:    Output Parameters:
1790: .  has - `PETSC_TRUE` if transient variables have been set

1792:    Level: developer

1794: .seealso: [](chapter_ts), `TS`, `TSBDF`, `DMTSSetTransientVariable()`, `TSComputeTransientVariable()`
1795: @*/
1796: PetscErrorCode TSHasTransientVariable(TS ts, PetscBool *has)
1797: {
1798:   DM   dm;
1799:   DMTS dmts;

1801:   PetscFunctionBegin;
1803:   PetscCall(TSGetDM(ts, &dm));
1804:   PetscCall(DMGetDMTS(dm, &dmts));
1805:   *has = dmts->ops->transientvar ? PETSC_TRUE : PETSC_FALSE;
1806:   PetscFunctionReturn(PETSC_SUCCESS);
1807: }

1809: /*@
1810:    TS2SetSolution - Sets the initial solution and time derivative vectors
1811:    for use by the `TS` routines handling second order equations.

1813:    Logically Collective

1815:    Input Parameters:
1816: +  ts - the `TS` context obtained from `TSCreate()`
1817: .  u - the solution vector
1818: -  v - the time derivative vector

1820:    Level: beginner

1822: .seealso: [](chapter_ts), `TS`
1823: @*/
1824: PetscErrorCode TS2SetSolution(TS ts, Vec u, Vec v)
1825: {
1826:   PetscFunctionBegin;
1830:   PetscCall(TSSetSolution(ts, u));
1831:   PetscCall(PetscObjectReference((PetscObject)v));
1832:   PetscCall(VecDestroy(&ts->vec_dot));
1833:   ts->vec_dot = v;
1834:   PetscFunctionReturn(PETSC_SUCCESS);
1835: }

1837: /*@
1838:    TS2GetSolution - Returns the solution and time derivative at the present timestep
1839:    for second order equations. It is valid to call this routine inside the function
1840:    that you are evaluating in order to move to the new timestep. This vector not
1841:    changed until the solution at the next timestep has been calculated.

1843:    Not Collective, but `u` returned is parallel if `TS` is parallel

1845:    Input Parameter:
1846: .  ts - the `TS` context obtained from `TSCreate()`

1848:    Output Parameters:
1849: +  u - the vector containing the solution
1850: -  v - the vector containing the time derivative

1852:    Level: intermediate

1854: .seealso: [](chapter_ts), `TS`, `TS2SetSolution()`, `TSGetTimeStep()`, `TSGetTime()`
1855: @*/
1856: PetscErrorCode TS2GetSolution(TS ts, Vec *u, Vec *v)
1857: {
1858:   PetscFunctionBegin;
1862:   if (u) *u = ts->vec_sol;
1863:   if (v) *v = ts->vec_dot;
1864:   PetscFunctionReturn(PETSC_SUCCESS);
1865: }

1867: /*@C
1868:   TSLoad - Loads a `TS` that has been stored in binary  with `TSView()`.

1870:   Collective

1872:   Input Parameters:
1873: + newdm - the newly loaded `TS`, this needs to have been created with `TSCreate()` or
1874:            some related function before a call to `TSLoad()`.
1875: - viewer - binary file viewer, obtained from `PetscViewerBinaryOpen()`

1877:    Level: intermediate

1879:   Note:
1880:  The type is determined by the data in the file, any type set into the `TS` before this call is ignored.

1882: .seealso: [](chapter_ts), `TS`, `PetscViewer`, `PetscViewerBinaryOpen()`, `TSView()`, `MatLoad()`, `VecLoad()`
1883: @*/
1884: PetscErrorCode TSLoad(TS ts, PetscViewer viewer)
1885: {
1886:   PetscBool isbinary;
1887:   PetscInt  classid;
1888:   char      type[256];
1889:   DMTS      sdm;
1890:   DM        dm;

1892:   PetscFunctionBegin;
1895:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary));
1896:   PetscCheck(isbinary, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Invalid viewer; open viewer with PetscViewerBinaryOpen()");

1898:   PetscCall(PetscViewerBinaryRead(viewer, &classid, 1, NULL, PETSC_INT));
1899:   PetscCheck(classid == TS_FILE_CLASSID, PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_WRONG, "Not TS next in file");
1900:   PetscCall(PetscViewerBinaryRead(viewer, type, 256, NULL, PETSC_CHAR));
1901:   PetscCall(TSSetType(ts, type));
1902:   PetscTryTypeMethod(ts, load, viewer);
1903:   PetscCall(DMCreate(PetscObjectComm((PetscObject)ts), &dm));
1904:   PetscCall(DMLoad(dm, viewer));
1905:   PetscCall(TSSetDM(ts, dm));
1906:   PetscCall(DMCreateGlobalVector(ts->dm, &ts->vec_sol));
1907:   PetscCall(VecLoad(ts->vec_sol, viewer));
1908:   PetscCall(DMGetDMTS(ts->dm, &sdm));
1909:   PetscCall(DMTSLoad(sdm, viewer));
1910:   PetscFunctionReturn(PETSC_SUCCESS);
1911: }

1913: #include <petscdraw.h>
1914: #if defined(PETSC_HAVE_SAWS)
1915: #include <petscviewersaws.h>
1916: #endif

1918: /*@C
1919:    TSViewFromOptions - View a `TS` based on values in the options database

1921:    Collective

1923:    Input Parameters:
1924: +  ts - the `TS` context
1925: .  obj - Optional object that provides the prefix for the options database keys
1926: -  name - command line option string to be passed by user

1928:    Level: intermediate

1930: .seealso: [](chapter_ts), `TS`, `TSView`, `PetscObjectViewFromOptions()`, `TSCreate()`
1931: @*/
1932: PetscErrorCode TSViewFromOptions(TS ts, PetscObject obj, const char name[])
1933: {
1934:   PetscFunctionBegin;
1936:   PetscCall(PetscObjectViewFromOptions((PetscObject)ts, obj, name));
1937:   PetscFunctionReturn(PETSC_SUCCESS);
1938: }

1940: /*@C
1941:     TSView - Prints the `TS` data structure.

1943:     Collective

1945:     Input Parameters:
1946: +   ts - the `TS` context obtained from `TSCreate()`
1947: -   viewer - visualization context

1949:     Options Database Key:
1950: .   -ts_view - calls `TSView()` at end of `TSStep()`

1952:     Level: beginner

1954:     Notes:
1955:     The available visualization contexts include
1956: +     `PETSC_VIEWER_STDOUT_SELF` - standard output (default)
1957: -     `PETSC_VIEWER_STDOUT_WORLD` - synchronized standard
1958:          output where only the first processor opens
1959:          the file.  All other processors send their
1960:          data to the first processor to print.

1962:     The user can open an alternative visualization context with
1963:     `PetscViewerASCIIOpen()` - output to a specified file.

1965:     In the debugger you can do call `TSView`(ts,0) to display the `TS` solver. (The same holds for any PETSc object viewer).

1967: .seealso: [](chapter_ts), `TS`, `PetscViewer`, `PetscViewerASCIIOpen()`
1968: @*/
1969: PetscErrorCode TSView(TS ts, PetscViewer viewer)
1970: {
1971:   TSType    type;
1972:   PetscBool iascii, isstring, isundials, isbinary, isdraw;
1973:   DMTS      sdm;
1974: #if defined(PETSC_HAVE_SAWS)
1975:   PetscBool issaws;
1976: #endif

1978:   PetscFunctionBegin;
1980:   if (!viewer) PetscCall(PetscViewerASCIIGetStdout(PetscObjectComm((PetscObject)ts), &viewer));
1982:   PetscCheckSameComm(ts, 1, viewer, 2);

1984:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &iascii));
1985:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERSTRING, &isstring));
1986:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary));
1987:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERDRAW, &isdraw));
1988: #if defined(PETSC_HAVE_SAWS)
1989:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERSAWS, &issaws));
1990: #endif
1991:   if (iascii) {
1992:     PetscCall(PetscObjectPrintClassNamePrefixType((PetscObject)ts, viewer));
1993:     if (ts->ops->view) {
1994:       PetscCall(PetscViewerASCIIPushTab(viewer));
1995:       PetscUseTypeMethod(ts, view, viewer);
1996:       PetscCall(PetscViewerASCIIPopTab(viewer));
1997:     }
1998:     if (ts->max_steps < PETSC_MAX_INT) PetscCall(PetscViewerASCIIPrintf(viewer, "  maximum steps=%" PetscInt_FMT "\n", ts->max_steps));
1999:     if (ts->max_time < PETSC_MAX_REAL) PetscCall(PetscViewerASCIIPrintf(viewer, "  maximum time=%g\n", (double)ts->max_time));
2000:     if (ts->ifuncs) PetscCall(PetscViewerASCIIPrintf(viewer, "  total number of I function evaluations=%" PetscInt_FMT "\n", ts->ifuncs));
2001:     if (ts->ijacs) PetscCall(PetscViewerASCIIPrintf(viewer, "  total number of I Jacobian evaluations=%" PetscInt_FMT "\n", ts->ijacs));
2002:     if (ts->rhsfuncs) PetscCall(PetscViewerASCIIPrintf(viewer, "  total number of RHS function evaluations=%" PetscInt_FMT "\n", ts->rhsfuncs));
2003:     if (ts->rhsjacs) PetscCall(PetscViewerASCIIPrintf(viewer, "  total number of RHS Jacobian evaluations=%" PetscInt_FMT "\n", ts->rhsjacs));
2004:     if (ts->usessnes) {
2005:       PetscBool lin;
2006:       if (ts->problem_type == TS_NONLINEAR) PetscCall(PetscViewerASCIIPrintf(viewer, "  total number of nonlinear solver iterations=%" PetscInt_FMT "\n", ts->snes_its));
2007:       PetscCall(PetscViewerASCIIPrintf(viewer, "  total number of linear solver iterations=%" PetscInt_FMT "\n", ts->ksp_its));
2008:       PetscCall(PetscObjectTypeCompareAny((PetscObject)ts->snes, &lin, SNESKSPONLY, SNESKSPTRANSPOSEONLY, ""));
2009:       PetscCall(PetscViewerASCIIPrintf(viewer, "  total number of %slinear solve failures=%" PetscInt_FMT "\n", lin ? "" : "non", ts->num_snes_failures));
2010:     }
2011:     PetscCall(PetscViewerASCIIPrintf(viewer, "  total number of rejected steps=%" PetscInt_FMT "\n", ts->reject));
2012:     if (ts->vrtol) PetscCall(PetscViewerASCIIPrintf(viewer, "  using vector of relative error tolerances, "));
2013:     else PetscCall(PetscViewerASCIIPrintf(viewer, "  using relative error tolerance of %g, ", (double)ts->rtol));
2014:     if (ts->vatol) PetscCall(PetscViewerASCIIPrintf(viewer, "  using vector of absolute error tolerances\n"));
2015:     else PetscCall(PetscViewerASCIIPrintf(viewer, "  using absolute error tolerance of %g\n", (double)ts->atol));
2016:     PetscCall(PetscViewerASCIIPushTab(viewer));
2017:     PetscCall(TSAdaptView(ts->adapt, viewer));
2018:     PetscCall(PetscViewerASCIIPopTab(viewer));
2019:   } else if (isstring) {
2020:     PetscCall(TSGetType(ts, &type));
2021:     PetscCall(PetscViewerStringSPrintf(viewer, " TSType: %-7.7s", type));
2022:     PetscTryTypeMethod(ts, view, viewer);
2023:   } else if (isbinary) {
2024:     PetscInt    classid = TS_FILE_CLASSID;
2025:     MPI_Comm    comm;
2026:     PetscMPIInt rank;
2027:     char        type[256];

2029:     PetscCall(PetscObjectGetComm((PetscObject)ts, &comm));
2030:     PetscCallMPI(MPI_Comm_rank(comm, &rank));
2031:     if (rank == 0) {
2032:       PetscCall(PetscViewerBinaryWrite(viewer, &classid, 1, PETSC_INT));
2033:       PetscCall(PetscStrncpy(type, ((PetscObject)ts)->type_name, 256));
2034:       PetscCall(PetscViewerBinaryWrite(viewer, type, 256, PETSC_CHAR));
2035:     }
2036:     PetscTryTypeMethod(ts, view, viewer);
2037:     if (ts->adapt) PetscCall(TSAdaptView(ts->adapt, viewer));
2038:     PetscCall(DMView(ts->dm, viewer));
2039:     PetscCall(VecView(ts->vec_sol, viewer));
2040:     PetscCall(DMGetDMTS(ts->dm, &sdm));
2041:     PetscCall(DMTSView(sdm, viewer));
2042:   } else if (isdraw) {
2043:     PetscDraw draw;
2044:     char      str[36];
2045:     PetscReal x, y, bottom, h;

2047:     PetscCall(PetscViewerDrawGetDraw(viewer, 0, &draw));
2048:     PetscCall(PetscDrawGetCurrentPoint(draw, &x, &y));
2049:     PetscCall(PetscStrcpy(str, "TS: "));
2050:     PetscCall(PetscStrcat(str, ((PetscObject)ts)->type_name));
2051:     PetscCall(PetscDrawStringBoxed(draw, x, y, PETSC_DRAW_BLACK, PETSC_DRAW_BLACK, str, NULL, &h));
2052:     bottom = y - h;
2053:     PetscCall(PetscDrawPushCurrentPoint(draw, x, bottom));
2054:     PetscTryTypeMethod(ts, view, viewer);
2055:     if (ts->adapt) PetscCall(TSAdaptView(ts->adapt, viewer));
2056:     if (ts->snes) PetscCall(SNESView(ts->snes, viewer));
2057:     PetscCall(PetscDrawPopCurrentPoint(draw));
2058: #if defined(PETSC_HAVE_SAWS)
2059:   } else if (issaws) {
2060:     PetscMPIInt rank;
2061:     const char *name;

2063:     PetscCall(PetscObjectGetName((PetscObject)ts, &name));
2064:     PetscCallMPI(MPI_Comm_rank(PETSC_COMM_WORLD, &rank));
2065:     if (!((PetscObject)ts)->amsmem && rank == 0) {
2066:       char dir[1024];

2068:       PetscCall(PetscObjectViewSAWs((PetscObject)ts, viewer));
2069:       PetscCall(PetscSNPrintf(dir, 1024, "/PETSc/Objects/%s/time_step", name));
2070:       PetscCallSAWs(SAWs_Register, (dir, &ts->steps, 1, SAWs_READ, SAWs_INT));
2071:       PetscCall(PetscSNPrintf(dir, 1024, "/PETSc/Objects/%s/time", name));
2072:       PetscCallSAWs(SAWs_Register, (dir, &ts->ptime, 1, SAWs_READ, SAWs_DOUBLE));
2073:     }
2074:     PetscTryTypeMethod(ts, view, viewer);
2075: #endif
2076:   }
2077:   if (ts->snes && ts->usessnes) {
2078:     PetscCall(PetscViewerASCIIPushTab(viewer));
2079:     PetscCall(SNESView(ts->snes, viewer));
2080:     PetscCall(PetscViewerASCIIPopTab(viewer));
2081:   }
2082:   PetscCall(DMGetDMTS(ts->dm, &sdm));
2083:   PetscCall(DMTSView(sdm, viewer));

2085:   PetscCall(PetscViewerASCIIPushTab(viewer));
2086:   PetscCall(PetscObjectTypeCompare((PetscObject)ts, TSSUNDIALS, &isundials));
2087:   PetscCall(PetscViewerASCIIPopTab(viewer));
2088:   PetscFunctionReturn(PETSC_SUCCESS);
2089: }

2091: /*@
2092:    TSSetApplicationContext - Sets an optional user-defined context for
2093:    the timesteppers.

2095:    Logically Collective

2097:    Input Parameters:
2098: +  ts - the `TS` context obtained from `TSCreate()`
2099: -  usrP -  user context

2101:    Level: intermediate

2103:    Fortran Note:
2104:     You must write a Fortran interface definition for this
2105:     function that tells Fortran the Fortran derived data type that you are passing in as the `ctx` argument.

2107: .seealso: [](chapter_ts), `TS`, `TSGetApplicationContext()`
2108: @*/
2109: PetscErrorCode TSSetApplicationContext(TS ts, void *usrP)
2110: {
2111:   PetscFunctionBegin;
2113:   ts->user = usrP;
2114:   PetscFunctionReturn(PETSC_SUCCESS);
2115: }

2117: /*@
2118:     TSGetApplicationContext - Gets the user-defined context for the
2119:     timestepper that was set with `TSSetApplicationContext()`

2121:     Not Collective

2123:     Input Parameter:
2124: .   ts - the `TS` context obtained from `TSCreate()`

2126:     Output Parameter:
2127: .   usrP - user context

2129:     Level: intermediate

2131:     Fortran Note:
2132:     You must write a Fortran interface definition for this
2133:     function that tells Fortran the Fortran derived data type that you are passing in as the `ctx` argument.

2135: .seealso: [](chapter_ts), `TS`, `TSSetApplicationContext()`
2136: @*/
2137: PetscErrorCode TSGetApplicationContext(TS ts, void *usrP)
2138: {
2139:   PetscFunctionBegin;
2141:   *(void **)usrP = ts->user;
2142:   PetscFunctionReturn(PETSC_SUCCESS);
2143: }

2145: /*@
2146:    TSGetStepNumber - Gets the number of time steps completed.

2148:    Not Collective

2150:    Input Parameter:
2151: .  ts - the `TS` context obtained from `TSCreate()`

2153:    Output Parameter:
2154: .  steps - number of steps completed so far

2156:    Level: intermediate

2158: .seealso: [](chapter_ts), `TS`, `TSGetTime()`, `TSGetTimeStep()`, `TSSetPreStep()`, `TSSetPreStage()`, `TSSetPostStage()`, `TSSetPostStep()`
2159: @*/
2160: PetscErrorCode TSGetStepNumber(TS ts, PetscInt *steps)
2161: {
2162:   PetscFunctionBegin;
2165:   *steps = ts->steps;
2166:   PetscFunctionReturn(PETSC_SUCCESS);
2167: }

2169: /*@
2170:    TSSetStepNumber - Sets the number of steps completed.

2172:    Logically Collective

2174:    Input Parameters:
2175: +  ts - the `TS` context
2176: -  steps - number of steps completed so far

2178:    Level: developer

2180:    Note:
2181:    For most uses of the `TS` solvers the user need not explicitly call
2182:    `TSSetStepNumber()`, as the step counter is appropriately updated in
2183:    `TSSolve()`/`TSStep()`/`TSRollBack()`. Power users may call this routine to
2184:    reinitialize timestepping by setting the step counter to zero (and time
2185:    to the initial time) to solve a similar problem with different initial
2186:    conditions or parameters. Other possible use case is to continue
2187:    timestepping from a previously interrupted run in such a way that `TS`
2188:    monitors will be called with a initial nonzero step counter.

2190: .seealso: [](chapter_ts), `TS`, `TSGetStepNumber()`, `TSSetTime()`, `TSSetTimeStep()`, `TSSetSolution()`
2191: @*/
2192: PetscErrorCode TSSetStepNumber(TS ts, PetscInt steps)
2193: {
2194:   PetscFunctionBegin;
2197:   PetscCheck(steps >= 0, PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_OUTOFRANGE, "Step number must be non-negative");
2198:   ts->steps = steps;
2199:   PetscFunctionReturn(PETSC_SUCCESS);
2200: }

2202: /*@
2203:    TSSetTimeStep - Allows one to reset the timestep at any time,
2204:    useful for simple pseudo-timestepping codes.

2206:    Logically Collective

2208:    Input Parameters:
2209: +  ts - the `TS` context obtained from `TSCreate()`
2210: -  time_step - the size of the timestep

2212:    Level: intermediate

2214: .seealso: [](chapter_ts), `TS`, `TSPSEUDO`, `TSGetTimeStep()`, `TSSetTime()`
2215: @*/
2216: PetscErrorCode TSSetTimeStep(TS ts, PetscReal time_step)
2217: {
2218:   PetscFunctionBegin;
2221:   ts->time_step = time_step;
2222:   PetscFunctionReturn(PETSC_SUCCESS);
2223: }

2225: /*@
2226:    TSSetExactFinalTime - Determines whether to adapt the final time step to
2227:      match the exact final time, interpolate solution to the exact final time,
2228:      or just return at the final time `TS` computed.

2230:   Logically Collective

2232:    Input Parameters:
2233: +   ts - the time-step context
2234: -   eftopt - exact final time option
2235: .vb
2236:   TS_EXACTFINALTIME_STEPOVER    - Don't do anything if final time is exceeded
2237:   TS_EXACTFINALTIME_INTERPOLATE - Interpolate back to final time
2238:   TS_EXACTFINALTIME_MATCHSTEP - Adapt final time step to match the final time
2239: .ve

2241:    Options Database Key:
2242: .   -ts_exact_final_time <stepover,interpolate,matchstep> - select the final step at runtime

2244:    Level: beginner

2246:    Note:
2247:    If you use the option `TS_EXACTFINALTIME_STEPOVER` the solution may be at a very different time
2248:    then the final time you selected.

2250: .seealso: [](chapter_ts), `TS`, `TSExactFinalTimeOption`, `TSGetExactFinalTime()`
2251: @*/
2252: PetscErrorCode TSSetExactFinalTime(TS ts, TSExactFinalTimeOption eftopt)
2253: {
2254:   PetscFunctionBegin;
2257:   ts->exact_final_time = eftopt;
2258:   PetscFunctionReturn(PETSC_SUCCESS);
2259: }

2261: /*@
2262:    TSGetExactFinalTime - Gets the exact final time option set with `TSSetExactFinalTime()`

2264:    Not Collective

2266:    Input Parameter:
2267: .  ts - the `TS` context

2269:    Output Parameter:
2270: .  eftopt - exact final time option

2272:    Level: beginner

2274: .seealso: [](chapter_ts), `TS`, `TSExactFinalTimeOption`, `TSSetExactFinalTime()`
2275: @*/
2276: PetscErrorCode TSGetExactFinalTime(TS ts, TSExactFinalTimeOption *eftopt)
2277: {
2278:   PetscFunctionBegin;
2281:   *eftopt = ts->exact_final_time;
2282:   PetscFunctionReturn(PETSC_SUCCESS);
2283: }

2285: /*@
2286:    TSGetTimeStep - Gets the current timestep size.

2288:    Not Collective

2290:    Input Parameter:
2291: .  ts - the `TS` context obtained from `TSCreate()`

2293:    Output Parameter:
2294: .  dt - the current timestep size

2296:    Level: intermediate

2298: .seealso: [](chapter_ts), `TS`, `TSSetTimeStep()`, `TSGetTime()`
2299: @*/
2300: PetscErrorCode TSGetTimeStep(TS ts, PetscReal *dt)
2301: {
2302:   PetscFunctionBegin;
2305:   *dt = ts->time_step;
2306:   PetscFunctionReturn(PETSC_SUCCESS);
2307: }

2309: /*@
2310:    TSGetSolution - Returns the solution at the present timestep. It
2311:    is valid to call this routine inside the function that you are evaluating
2312:    in order to move to the new timestep. This vector not changed until
2313:    the solution at the next timestep has been calculated.

2315:    Not Collective, but v returned is parallel if ts is parallel

2317:    Input Parameter:
2318: .  ts - the `TS` context obtained from `TSCreate()`

2320:    Output Parameter:
2321: .  v - the vector containing the solution

2323:    Level: intermediate

2325:    Note:
2326:    If you used `TSSetExactFinalTime`(ts,`TS_EXACTFINALTIME_MATCHSTEP`); this does not return the solution at the requested
2327:    final time. It returns the solution at the next timestep.

2329: .seealso: [](chapter_ts), `TS`, `TSGetTimeStep()`, `TSGetTime()`, `TSGetSolveTime()`, `TSGetSolutionComponents()`, `TSSetSolutionFunction()`
2330: @*/
2331: PetscErrorCode TSGetSolution(TS ts, Vec *v)
2332: {
2333:   PetscFunctionBegin;
2336:   *v = ts->vec_sol;
2337:   PetscFunctionReturn(PETSC_SUCCESS);
2338: }

2340: /*@
2341:    TSGetSolutionComponents - Returns any solution components at the present
2342:    timestep, if available for the time integration method being used.
2343:    Solution components are quantities that share the same size and
2344:    structure as the solution vector.

2346:    Not Collective, but v returned is parallel if ts is parallel

2348:    Parameters :
2349: +  ts - the `TS` context obtained from `TSCreate()` (input parameter).
2350: .  n - If v is `NULL`, then the number of solution components is
2351:        returned through n, else the n-th solution component is
2352:        returned in v.
2353: -  v - the vector containing the n-th solution component
2354:        (may be `NULL` to use this function to find out
2355:         the number of solutions components).

2357:    Level: advanced

2359: .seealso: [](chapter_ts), `TS`, `TSGetSolution()`
2360: @*/
2361: PetscErrorCode TSGetSolutionComponents(TS ts, PetscInt *n, Vec *v)
2362: {
2363:   PetscFunctionBegin;
2365:   if (!ts->ops->getsolutioncomponents) *n = 0;
2366:   else PetscUseTypeMethod(ts, getsolutioncomponents, n, v);
2367:   PetscFunctionReturn(PETSC_SUCCESS);
2368: }

2370: /*@
2371:    TSGetAuxSolution - Returns an auxiliary solution at the present
2372:    timestep, if available for the time integration method being used.

2374:    Not Collective, but v returned is parallel if ts is parallel

2376:    Parameters :
2377: +  ts - the `TS` context obtained from `TSCreate()` (input parameter).
2378: -  v - the vector containing the auxiliary solution

2380:    Level: intermediate

2382: .seealso: [](chapter_ts), `TS`, `TSGetSolution()`
2383: @*/
2384: PetscErrorCode TSGetAuxSolution(TS ts, Vec *v)
2385: {
2386:   PetscFunctionBegin;
2388:   if (ts->ops->getauxsolution) PetscUseTypeMethod(ts, getauxsolution, v);
2389:   else PetscCall(VecZeroEntries(*v));
2390:   PetscFunctionReturn(PETSC_SUCCESS);
2391: }

2393: /*@
2394:    TSGetTimeError - Returns the estimated error vector, if the chosen
2395:    `TSType` has an error estimation functionality and `TSSetTimeError()` was called

2397:    Not Collective, but v returned is parallel if ts is parallel

2399:    Parameters :
2400: +  ts - the `TS` context obtained from `TSCreate()` (input parameter).
2401: .  n - current estimate (n=0) or previous one (n=-1)
2402: -  v - the vector containing the error (same size as the solution).

2404:    Level: intermediate

2406:    Note:
2407:    MUST call after `TSSetUp()`

2409: .seealso: [](chapter_ts), `TSGetSolution()`, `TSSetTimeError()`
2410: @*/
2411: PetscErrorCode TSGetTimeError(TS ts, PetscInt n, Vec *v)
2412: {
2413:   PetscFunctionBegin;
2415:   if (ts->ops->gettimeerror) PetscUseTypeMethod(ts, gettimeerror, n, v);
2416:   else PetscCall(VecZeroEntries(*v));
2417:   PetscFunctionReturn(PETSC_SUCCESS);
2418: }

2420: /*@
2421:    TSSetTimeError - Sets the estimated error vector, if the chosen
2422:    `TSType` has an error estimation functionality. This can be used
2423:    to restart such a time integrator with a given error vector.

2425:    Not Collective, but v returned is parallel if ts is parallel

2427:    Parameters :
2428: +  ts - the `TS` context obtained from `TSCreate()` (input parameter).
2429: -  v - the vector containing the error (same size as the solution).

2431:    Level: intermediate

2433: .seealso: [](chapter_ts), `TS`, `TSSetSolution()`, `TSGetTimeError)`
2434: @*/
2435: PetscErrorCode TSSetTimeError(TS ts, Vec v)
2436: {
2437:   PetscFunctionBegin;
2439:   PetscCheck(ts->setupcalled, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Must call TSSetUp() first");
2440:   PetscTryTypeMethod(ts, settimeerror, v);
2441:   PetscFunctionReturn(PETSC_SUCCESS);
2442: }

2444: /* ----- Routines to initialize and destroy a timestepper ---- */
2445: /*@
2446:   TSSetProblemType - Sets the type of problem to be solved.

2448:   Not collective

2450:   Input Parameters:
2451: + ts   - The `TS`
2452: - type - One of `TS_LINEAR`, `TS_NONLINEAR` where these types refer to problems of the forms
2453: .vb
2454:          U_t - A U = 0      (linear)
2455:          U_t - A(t) U = 0   (linear)
2456:          F(t,U,U_t) = 0     (nonlinear)
2457: .ve

2459:    Level: beginner

2461: .seealso: [](chapter_ts), `TSSetUp()`, `TSProblemType`, `TS`
2462: @*/
2463: PetscErrorCode TSSetProblemType(TS ts, TSProblemType type)
2464: {
2465:   PetscFunctionBegin;
2467:   ts->problem_type = type;
2468:   if (type == TS_LINEAR) {
2469:     SNES snes;
2470:     PetscCall(TSGetSNES(ts, &snes));
2471:     PetscCall(SNESSetType(snes, SNESKSPONLY));
2472:   }
2473:   PetscFunctionReturn(PETSC_SUCCESS);
2474: }

2476: /*@C
2477:   TSGetProblemType - Gets the type of problem to be solved.

2479:   Not collective

2481:   Input Parameter:
2482: . ts   - The `TS`

2484:   Output Parameter:
2485: . type - One of `TS_LINEAR`, `TS_NONLINEAR` where these types refer to problems of the forms
2486: .vb
2487:          M U_t = A U
2488:          M(t) U_t = A(t) U
2489:          F(t,U,U_t)
2490: .ve

2492:    Level: beginner

2494: .seealso: [](chapter_ts), `TSSetUp()`, `TSProblemType`, `TS`
2495: @*/
2496: PetscErrorCode TSGetProblemType(TS ts, TSProblemType *type)
2497: {
2498:   PetscFunctionBegin;
2501:   *type = ts->problem_type;
2502:   PetscFunctionReturn(PETSC_SUCCESS);
2503: }

2505: /*
2506:     Attempt to check/preset a default value for the exact final time option. This is needed at the beginning of TSSolve() and in TSSetUp()
2507: */
2508: static PetscErrorCode TSSetExactFinalTimeDefault(TS ts)
2509: {
2510:   PetscBool isnone;

2512:   PetscFunctionBegin;
2513:   PetscCall(TSGetAdapt(ts, &ts->adapt));
2514:   PetscCall(TSAdaptSetDefaultType(ts->adapt, ts->default_adapt_type));

2516:   PetscCall(PetscObjectTypeCompare((PetscObject)ts->adapt, TSADAPTNONE, &isnone));
2517:   if (!isnone && ts->exact_final_time == TS_EXACTFINALTIME_UNSPECIFIED) ts->exact_final_time = TS_EXACTFINALTIME_MATCHSTEP;
2518:   else if (ts->exact_final_time == TS_EXACTFINALTIME_UNSPECIFIED) ts->exact_final_time = TS_EXACTFINALTIME_INTERPOLATE;
2519:   PetscFunctionReturn(PETSC_SUCCESS);
2520: }

2522: /*@
2523:    TSSetUp - Sets up the internal data structures for the later use of a timestepper.

2525:    Collective

2527:    Input Parameter:
2528: .  ts - the `TS` context obtained from `TSCreate()`

2530:    Level: advanced

2532:    Note:
2533:    For basic use of the `TS` solvers the user need not explicitly call
2534:    `TSSetUp()`, since these actions will automatically occur during
2535:    the call to `TSStep()` or `TSSolve()`.  However, if one wishes to control this
2536:    phase separately, `TSSetUp()` should be called after `TSCreate()`
2537:    and optional routines of the form TSSetXXX(), but before `TSStep()` and `TSSolve()`.

2539: .seealso: [](chapter_ts), `TSCreate()`, `TS`, `TSStep()`, `TSDestroy()`, `TSSolve()`
2540: @*/
2541: PetscErrorCode TSSetUp(TS ts)
2542: {
2543:   DM dm;
2544:   PetscErrorCode (*func)(SNES, Vec, Vec, void *);
2545:   PetscErrorCode (*jac)(SNES, Vec, Mat, Mat, void *);
2546:   TSIFunction   ifun;
2547:   TSIJacobian   ijac;
2548:   TSI2Jacobian  i2jac;
2549:   TSRHSJacobian rhsjac;

2551:   PetscFunctionBegin;
2553:   if (ts->setupcalled) PetscFunctionReturn(PETSC_SUCCESS);

2555:   if (!((PetscObject)ts)->type_name) {
2556:     PetscCall(TSGetIFunction(ts, NULL, &ifun, NULL));
2557:     PetscCall(TSSetType(ts, ifun ? TSBEULER : TSEULER));
2558:   }

2560:   if (!ts->vec_sol) {
2561:     PetscCheck(ts->dm, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Must call TSSetSolution() first");
2562:     PetscCall(DMCreateGlobalVector(ts->dm, &ts->vec_sol));
2563:   }

2565:   if (ts->tspan) {
2566:     if (!ts->tspan->vecs_sol) PetscCall(VecDuplicateVecs(ts->vec_sol, ts->tspan->num_span_times, &ts->tspan->vecs_sol));
2567:   }
2568:   if (!ts->Jacp && ts->Jacprhs) { /* IJacobianP shares the same matrix with RHSJacobianP if only RHSJacobianP is provided */
2569:     PetscCall(PetscObjectReference((PetscObject)ts->Jacprhs));
2570:     ts->Jacp = ts->Jacprhs;
2571:   }

2573:   if (ts->quadraturets) {
2574:     PetscCall(TSSetUp(ts->quadraturets));
2575:     PetscCall(VecDestroy(&ts->vec_costintegrand));
2576:     PetscCall(VecDuplicate(ts->quadraturets->vec_sol, &ts->vec_costintegrand));
2577:   }

2579:   PetscCall(TSGetRHSJacobian(ts, NULL, NULL, &rhsjac, NULL));
2580:   if (rhsjac == TSComputeRHSJacobianConstant) {
2581:     Mat  Amat, Pmat;
2582:     SNES snes;
2583:     PetscCall(TSGetSNES(ts, &snes));
2584:     PetscCall(SNESGetJacobian(snes, &Amat, &Pmat, NULL, NULL));
2585:     /* Matching matrices implies that an IJacobian is NOT set, because if it had been set, the IJacobian's matrix would
2586:      * have displaced the RHS matrix */
2587:     if (Amat && Amat == ts->Arhs) {
2588:       /* 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 */
2589:       PetscCall(MatDuplicate(ts->Arhs, MAT_COPY_VALUES, &Amat));
2590:       PetscCall(SNESSetJacobian(snes, Amat, NULL, NULL, NULL));
2591:       PetscCall(MatDestroy(&Amat));
2592:     }
2593:     if (Pmat && Pmat == ts->Brhs) {
2594:       PetscCall(MatDuplicate(ts->Brhs, MAT_COPY_VALUES, &Pmat));
2595:       PetscCall(SNESSetJacobian(snes, NULL, Pmat, NULL, NULL));
2596:       PetscCall(MatDestroy(&Pmat));
2597:     }
2598:   }

2600:   PetscCall(TSGetAdapt(ts, &ts->adapt));
2601:   PetscCall(TSAdaptSetDefaultType(ts->adapt, ts->default_adapt_type));

2603:   PetscTryTypeMethod(ts, setup);

2605:   PetscCall(TSSetExactFinalTimeDefault(ts));

2607:   /* In the case where we've set a DMTSFunction or what have you, we need the default SNESFunction
2608:      to be set right but can't do it elsewhere due to the overreliance on ctx=ts.
2609:    */
2610:   PetscCall(TSGetDM(ts, &dm));
2611:   PetscCall(DMSNESGetFunction(dm, &func, NULL));
2612:   if (!func) PetscCall(DMSNESSetFunction(dm, SNESTSFormFunction, ts));

2614:   /* If the SNES doesn't have a jacobian set and the TS has an ijacobian or rhsjacobian set, set the SNES to use it.
2615:      Otherwise, the SNES will use coloring internally to form the Jacobian.
2616:    */
2617:   PetscCall(DMSNESGetJacobian(dm, &jac, NULL));
2618:   PetscCall(DMTSGetIJacobian(dm, &ijac, NULL));
2619:   PetscCall(DMTSGetI2Jacobian(dm, &i2jac, NULL));
2620:   PetscCall(DMTSGetRHSJacobian(dm, &rhsjac, NULL));
2621:   if (!jac && (ijac || i2jac || rhsjac)) PetscCall(DMSNESSetJacobian(dm, SNESTSFormJacobian, ts));

2623:   /* if time integration scheme has a starting method, call it */
2624:   PetscTryTypeMethod(ts, startingmethod);

2626:   ts->setupcalled = PETSC_TRUE;
2627:   PetscFunctionReturn(PETSC_SUCCESS);
2628: }

2630: /*@
2631:    TSReset - Resets a `TS` context and removes any allocated `Vec`s and `Mat`s.

2633:    Collective

2635:    Input Parameter:
2636: .  ts - the `TS` context obtained from `TSCreate()`

2638:    Level: beginner

2640: .seealso: [](chapter_ts), `TS`, `TSCreate()`, `TSSetup()`, `TSDestroy()`
2641: @*/
2642: PetscErrorCode TSReset(TS ts)
2643: {
2644:   TS_RHSSplitLink ilink = ts->tsrhssplit, next;

2646:   PetscFunctionBegin;

2649:   PetscTryTypeMethod(ts, reset);
2650:   if (ts->snes) PetscCall(SNESReset(ts->snes));
2651:   if (ts->adapt) PetscCall(TSAdaptReset(ts->adapt));

2653:   PetscCall(MatDestroy(&ts->Arhs));
2654:   PetscCall(MatDestroy(&ts->Brhs));
2655:   PetscCall(VecDestroy(&ts->Frhs));
2656:   PetscCall(VecDestroy(&ts->vec_sol));
2657:   PetscCall(VecDestroy(&ts->vec_dot));
2658:   PetscCall(VecDestroy(&ts->vatol));
2659:   PetscCall(VecDestroy(&ts->vrtol));
2660:   PetscCall(VecDestroyVecs(ts->nwork, &ts->work));

2662:   PetscCall(MatDestroy(&ts->Jacprhs));
2663:   PetscCall(MatDestroy(&ts->Jacp));
2664:   if (ts->forward_solve) PetscCall(TSForwardReset(ts));
2665:   if (ts->quadraturets) {
2666:     PetscCall(TSReset(ts->quadraturets));
2667:     PetscCall(VecDestroy(&ts->vec_costintegrand));
2668:   }
2669:   while (ilink) {
2670:     next = ilink->next;
2671:     PetscCall(TSDestroy(&ilink->ts));
2672:     PetscCall(PetscFree(ilink->splitname));
2673:     PetscCall(ISDestroy(&ilink->is));
2674:     PetscCall(PetscFree(ilink));
2675:     ilink = next;
2676:   }
2677:   ts->tsrhssplit     = NULL;
2678:   ts->num_rhs_splits = 0;
2679:   if (ts->tspan) {
2680:     PetscCall(PetscFree(ts->tspan->span_times));
2681:     PetscCall(VecDestroyVecs(ts->tspan->num_span_times, &ts->tspan->vecs_sol));
2682:     PetscCall(PetscFree(ts->tspan));
2683:   }
2684:   ts->setupcalled = PETSC_FALSE;
2685:   PetscFunctionReturn(PETSC_SUCCESS);
2686: }

2688: /*@C
2689:    TSDestroy - Destroys the timestepper context that was created
2690:    with `TSCreate()`.

2692:    Collective

2694:    Input Parameter:
2695: .  ts - the `TS` context obtained from `TSCreate()`

2697:    Level: beginner

2699: .seealso: [](chapter_ts), `TS`, `TSCreate()`, `TSSetUp()`, `TSSolve()`
2700: @*/
2701: PetscErrorCode TSDestroy(TS *ts)
2702: {
2703:   PetscFunctionBegin;
2704:   if (!*ts) PetscFunctionReturn(PETSC_SUCCESS);
2706:   if (--((PetscObject)(*ts))->refct > 0) {
2707:     *ts = NULL;
2708:     PetscFunctionReturn(PETSC_SUCCESS);
2709:   }

2711:   PetscCall(TSReset(*ts));
2712:   PetscCall(TSAdjointReset(*ts));
2713:   if ((*ts)->forward_solve) PetscCall(TSForwardReset(*ts));

2715:   /* if memory was published with SAWs then destroy it */
2716:   PetscCall(PetscObjectSAWsViewOff((PetscObject)*ts));
2717:   PetscTryTypeMethod((*ts), destroy);

2719:   PetscCall(TSTrajectoryDestroy(&(*ts)->trajectory));

2721:   PetscCall(TSAdaptDestroy(&(*ts)->adapt));
2722:   PetscCall(TSEventDestroy(&(*ts)->event));

2724:   PetscCall(SNESDestroy(&(*ts)->snes));
2725:   PetscCall(DMDestroy(&(*ts)->dm));
2726:   PetscCall(TSMonitorCancel((*ts)));
2727:   PetscCall(TSAdjointMonitorCancel((*ts)));

2729:   PetscCall(TSDestroy(&(*ts)->quadraturets));
2730:   PetscCall(PetscHeaderDestroy(ts));
2731:   PetscFunctionReturn(PETSC_SUCCESS);
2732: }

2734: /*@
2735:    TSGetSNES - Returns the `SNES` (nonlinear solver) associated with
2736:    a `TS` (timestepper) context. Valid only for nonlinear problems.

2738:    Not Collective, but snes is parallel if ts is parallel

2740:    Input Parameter:
2741: .  ts - the `TS` context obtained from `TSCreate()`

2743:    Output Parameter:
2744: .  snes - the nonlinear solver context

2746:    Level: beginner

2748:    Notes:
2749:    The user can then directly manipulate the `SNES` context to set various
2750:    options, etc.  Likewise, the user can then extract and manipulate the
2751:    `KSP`, and `PC` contexts as well.

2753:    `TSGetSNES()` does not work for integrators that do not use `SNES`; in
2754:    this case `TSGetSNES()` returns `NULL` in `snes`.

2756: .seealso: [](chapter_ts), `TS`, `SNES`, `TSCreate()`, `TSSetUp()`, `TSSolve()`
2757: @*/
2758: PetscErrorCode TSGetSNES(TS ts, SNES *snes)
2759: {
2760:   PetscFunctionBegin;
2763:   if (!ts->snes) {
2764:     PetscCall(SNESCreate(PetscObjectComm((PetscObject)ts), &ts->snes));
2765:     PetscCall(PetscObjectSetOptions((PetscObject)ts->snes, ((PetscObject)ts)->options));
2766:     PetscCall(SNESSetFunction(ts->snes, NULL, SNESTSFormFunction, ts));
2767:     PetscCall(PetscObjectIncrementTabLevel((PetscObject)ts->snes, (PetscObject)ts, 1));
2768:     if (ts->dm) PetscCall(SNESSetDM(ts->snes, ts->dm));
2769:     if (ts->problem_type == TS_LINEAR) PetscCall(SNESSetType(ts->snes, SNESKSPONLY));
2770:   }
2771:   *snes = ts->snes;
2772:   PetscFunctionReturn(PETSC_SUCCESS);
2773: }

2775: /*@
2776:    TSSetSNES - Set the `SNES` (nonlinear solver) to be used by the timestepping context

2778:    Collective

2780:    Input Parameters:
2781: +  ts - the `TS` context obtained from `TSCreate()`
2782: -  snes - the nonlinear solver context

2784:    Level: developer

2786:    Note:
2787:    Most users should have the `TS` created by calling `TSGetSNES()`

2789: .seealso: [](chapter_ts), `TS`, `SNES`, `TSCreate()`, `TSSetUp()`, `TSSolve()`, `TSGetSNES()`
2790: @*/
2791: PetscErrorCode TSSetSNES(TS ts, SNES snes)
2792: {
2793:   PetscErrorCode (*func)(SNES, Vec, Mat, Mat, void *);

2795:   PetscFunctionBegin;
2798:   PetscCall(PetscObjectReference((PetscObject)snes));
2799:   PetscCall(SNESDestroy(&ts->snes));

2801:   ts->snes = snes;

2803:   PetscCall(SNESSetFunction(ts->snes, NULL, SNESTSFormFunction, ts));
2804:   PetscCall(SNESGetJacobian(ts->snes, NULL, NULL, &func, NULL));
2805:   if (func == SNESTSFormJacobian) PetscCall(SNESSetJacobian(ts->snes, NULL, NULL, SNESTSFormJacobian, ts));
2806:   PetscFunctionReturn(PETSC_SUCCESS);
2807: }

2809: /*@
2810:    TSGetKSP - Returns the `KSP` (linear solver) associated with
2811:    a `TS` (timestepper) context.

2813:    Not Collective, but `ksp` is parallel if `ts` is parallel

2815:    Input Parameter:
2816: .  ts - the `TS` context obtained from `TSCreate()`

2818:    Output Parameter:
2819: .  ksp - the nonlinear solver context

2821:    Level: beginner

2823:    Notes:
2824:    The user can then directly manipulate the `KSP` context to set various
2825:    options, etc.  Likewise, the user can then extract and manipulate the
2826:    `PC` context as well.

2828:    `TSGetKSP()` does not work for integrators that do not use `KSP`;
2829:    in this case `TSGetKSP()` returns `NULL` in `ksp`.

2831: .seealso: [](chapter_ts), `TS`, `SNES`, `KSP`, `TSCreate()`, `TSSetUp()`, `TSSolve()`, `TSGetSNES()`
2832: @*/
2833: PetscErrorCode TSGetKSP(TS ts, KSP *ksp)
2834: {
2835:   SNES snes;

2837:   PetscFunctionBegin;
2840:   PetscCheck(((PetscObject)ts)->type_name, PETSC_COMM_SELF, PETSC_ERR_ARG_NULL, "KSP is not created yet. Call TSSetType() first");
2841:   PetscCheck(ts->problem_type == TS_LINEAR, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Linear only; use TSGetSNES()");
2842:   PetscCall(TSGetSNES(ts, &snes));
2843:   PetscCall(SNESGetKSP(snes, ksp));
2844:   PetscFunctionReturn(PETSC_SUCCESS);
2845: }

2847: /* ----------- Routines to set solver parameters ---------- */

2849: /*@
2850:    TSSetMaxSteps - Sets the maximum number of steps to use.

2852:    Logically Collective

2854:    Input Parameters:
2855: +  ts - the `TS` context obtained from `TSCreate()`
2856: -  maxsteps - maximum number of steps to use

2858:    Options Database Key:
2859: .  -ts_max_steps <maxsteps> - Sets maxsteps

2861:    Level: intermediate

2863:    Note:
2864:    The default maximum number of steps is 5000

2866: .seealso: [](chapter_ts), `TS`, `TSGetMaxSteps()`, `TSSetMaxTime()`, `TSSetExactFinalTime()`
2867: @*/
2868: PetscErrorCode TSSetMaxSteps(TS ts, PetscInt maxsteps)
2869: {
2870:   PetscFunctionBegin;
2873:   PetscCheck(maxsteps >= 0, PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_OUTOFRANGE, "Maximum number of steps must be non-negative");
2874:   ts->max_steps = maxsteps;
2875:   PetscFunctionReturn(PETSC_SUCCESS);
2876: }

2878: /*@
2879:    TSGetMaxSteps - Gets the maximum number of steps to use.

2881:    Not Collective

2883:    Input Parameters:
2884: .  ts - the `TS` context obtained from `TSCreate()`

2886:    Output Parameter:
2887: .  maxsteps - maximum number of steps to use

2889:    Level: advanced

2891: .seealso: [](chapter_ts), `TS`, `TSSetMaxSteps()`, `TSGetMaxTime()`, `TSSetMaxTime()`
2892: @*/
2893: PetscErrorCode TSGetMaxSteps(TS ts, PetscInt *maxsteps)
2894: {
2895:   PetscFunctionBegin;
2898:   *maxsteps = ts->max_steps;
2899:   PetscFunctionReturn(PETSC_SUCCESS);
2900: }

2902: /*@
2903:    TSSetMaxTime - Sets the maximum (or final) time for timestepping.

2905:    Logically Collective

2907:    Input Parameters:
2908: +  ts - the `TS` context obtained from `TSCreate()`
2909: -  maxtime - final time to step to

2911:    Options Database Key:
2912: .  -ts_max_time <maxtime> - Sets maxtime

2914:    Level: intermediate

2916:    Notes:
2917:    The default maximum time is 5.0

2919: .seealso: [](chapter_ts), `TS`, `TSGetMaxTime()`, `TSSetMaxSteps()`, `TSSetExactFinalTime()`
2920: @*/
2921: PetscErrorCode TSSetMaxTime(TS ts, PetscReal maxtime)
2922: {
2923:   PetscFunctionBegin;
2926:   ts->max_time = maxtime;
2927:   PetscFunctionReturn(PETSC_SUCCESS);
2928: }

2930: /*@
2931:    TSGetMaxTime - Gets the maximum (or final) time for timestepping.

2933:    Not Collective

2935:    Input Parameters:
2936: .  ts - the `TS` context obtained from `TSCreate()`

2938:    Output Parameter:
2939: .  maxtime - final time to step to

2941:    Level: advanced

2943: .seealso: [](chapter_ts), `TS`, `TSSetMaxTime()`, `TSGetMaxSteps()`, `TSSetMaxSteps()`
2944: @*/
2945: PetscErrorCode TSGetMaxTime(TS ts, PetscReal *maxtime)
2946: {
2947:   PetscFunctionBegin;
2950:   *maxtime = ts->max_time;
2951:   PetscFunctionReturn(PETSC_SUCCESS);
2952: }

2954: /*@
2955:    TSSetInitialTimeStep - Deprecated, use `TSSetTime()` and `TSSetTimeStep()`.

2957:    Level: deprecated

2959: @*/
2960: PetscErrorCode TSSetInitialTimeStep(TS ts, PetscReal initial_time, PetscReal time_step)
2961: {
2962:   PetscFunctionBegin;
2964:   PetscCall(TSSetTime(ts, initial_time));
2965:   PetscCall(TSSetTimeStep(ts, time_step));
2966:   PetscFunctionReturn(PETSC_SUCCESS);
2967: }

2969: /*@
2970:    TSGetDuration - Deprecated, use `TSGetMaxSteps()` and `TSGetMaxTime()`.

2972:    Level: deprecated

2974: @*/
2975: PetscErrorCode TSGetDuration(TS ts, PetscInt *maxsteps, PetscReal *maxtime)
2976: {
2977:   PetscFunctionBegin;
2979:   if (maxsteps) {
2981:     *maxsteps = ts->max_steps;
2982:   }
2983:   if (maxtime) {
2985:     *maxtime = ts->max_time;
2986:   }
2987:   PetscFunctionReturn(PETSC_SUCCESS);
2988: }

2990: /*@
2991:    TSSetDuration - Deprecated, use `TSSetMaxSteps()` and `TSSetMaxTime()`.

2993:    Level: deprecated

2995: @*/
2996: PetscErrorCode TSSetDuration(TS ts, PetscInt maxsteps, PetscReal maxtime)
2997: {
2998:   PetscFunctionBegin;
3002:   if (maxsteps >= 0) ts->max_steps = maxsteps;
3003:   if (maxtime != PETSC_DEFAULT) ts->max_time = maxtime;
3004:   PetscFunctionReturn(PETSC_SUCCESS);
3005: }

3007: /*@
3008:    TSGetTimeStepNumber - Deprecated, use `TSGetStepNumber()`.

3010:    Level: deprecated

3012: @*/
3013: PetscErrorCode TSGetTimeStepNumber(TS ts, PetscInt *steps)
3014: {
3015:   return TSGetStepNumber(ts, steps);
3016: }

3018: /*@
3019:    TSGetTotalSteps - Deprecated, use `TSGetStepNumber()`.

3021:    Level: deprecated

3023: @*/
3024: PetscErrorCode TSGetTotalSteps(TS ts, PetscInt *steps)
3025: {
3026:   return TSGetStepNumber(ts, steps);
3027: }

3029: /*@
3030:    TSSetSolution - Sets the initial solution vector
3031:    for use by the `TS` routines.

3033:    Logically Collective

3035:    Input Parameters:
3036: +  ts - the `TS` context obtained from `TSCreate()`
3037: -  u - the solution vector

3039:    Level: beginner

3041: .seealso: [](chapter_ts), `TS`, `TSSetSolutionFunction()`, `TSGetSolution()`, `TSCreate()`
3042: @*/
3043: PetscErrorCode TSSetSolution(TS ts, Vec u)
3044: {
3045:   DM dm;

3047:   PetscFunctionBegin;
3050:   PetscCall(PetscObjectReference((PetscObject)u));
3051:   PetscCall(VecDestroy(&ts->vec_sol));
3052:   ts->vec_sol = u;

3054:   PetscCall(TSGetDM(ts, &dm));
3055:   PetscCall(DMShellSetGlobalVector(dm, u));
3056:   PetscFunctionReturn(PETSC_SUCCESS);
3057: }

3059: /*@C
3060:   TSSetPreStep - Sets the general-purpose function
3061:   called once at the beginning of each time step.

3063:   Logically Collective

3065:   Input Parameters:
3066: + ts   - The `TS` context obtained from `TSCreate()`
3067: - func - The function

3069:   Calling sequence of func:
3070: .vb
3071:   PetscErrorCode func (TS ts);
3072: .ve

3074:   Level: intermediate

3076: .seealso: [](chapter_ts), `TS`, `TSSetPreStage()`, `TSSetPostStage()`, `TSSetPostStep()`, `TSStep()`, `TSRestartStep()`
3077: @*/
3078: PetscErrorCode TSSetPreStep(TS ts, PetscErrorCode (*func)(TS))
3079: {
3080:   PetscFunctionBegin;
3082:   ts->prestep = func;
3083:   PetscFunctionReturn(PETSC_SUCCESS);
3084: }

3086: /*@
3087:   TSPreStep - Runs the user-defined pre-step function provided with `TSSetPreStep()`

3089:   Collective

3091:   Input Parameters:
3092: . ts   - The `TS` context obtained from `TSCreate()`

3094:   Level: developer

3096:   Note:
3097:   `TSPreStep()` is typically used within time stepping implementations,
3098:   so most users would not generally call this routine themselves.

3100: .seealso: [](chapter_ts), `TS`, `TSSetPreStep()`, `TSPreStage()`, `TSPostStage()`, `TSPostStep()`
3101: @*/
3102: PetscErrorCode TSPreStep(TS ts)
3103: {
3104:   PetscFunctionBegin;
3106:   if (ts->prestep) {
3107:     Vec              U;
3108:     PetscObjectId    idprev;
3109:     PetscBool        sameObject;
3110:     PetscObjectState sprev, spost;

3112:     PetscCall(TSGetSolution(ts, &U));
3113:     PetscCall(PetscObjectGetId((PetscObject)U, &idprev));
3114:     PetscCall(PetscObjectStateGet((PetscObject)U, &sprev));
3115:     PetscCallBack("TS callback preset", (*ts->prestep)(ts));
3116:     PetscCall(TSGetSolution(ts, &U));
3117:     PetscCall(PetscObjectCompareId((PetscObject)U, idprev, &sameObject));
3118:     PetscCall(PetscObjectStateGet((PetscObject)U, &spost));
3119:     if (!sameObject || sprev != spost) PetscCall(TSRestartStep(ts));
3120:   }
3121:   PetscFunctionReturn(PETSC_SUCCESS);
3122: }

3124: /*@C
3125:   TSSetPreStage - Sets the general-purpose function
3126:   called once at the beginning of each stage.

3128:   Logically Collective

3130:   Input Parameters:
3131: + ts   - The `TS` context obtained from `TSCreate()`
3132: - func - The function

3134:   Calling sequence of func:
3135: .vb
3136:   PetscErrorCode func(TS ts, PetscReal stagetime);
3137: .ve

3139:   Level: intermediate

3141:   Note:
3142:   There may be several stages per time step. If the solve for a given stage fails, the step may be rejected and retried.
3143:   The time step number being computed can be queried using `TSGetStepNumber()` and the total size of the step being
3144:   attempted can be obtained using `TSGetTimeStep()`. The time at the start of the step is available via `TSGetTime()`.

3146: .seealso: [](chapter_ts), `TS`, `TSSetPostStage()`, `TSSetPreStep()`, `TSSetPostStep()`, `TSGetApplicationContext()`
3147: @*/
3148: PetscErrorCode TSSetPreStage(TS ts, PetscErrorCode (*func)(TS, PetscReal))
3149: {
3150:   PetscFunctionBegin;
3152:   ts->prestage = func;
3153:   PetscFunctionReturn(PETSC_SUCCESS);
3154: }

3156: /*@C
3157:   TSSetPostStage - Sets the general-purpose function, provided with `TSSetPostStep()`,
3158:   called once at the end of each stage.

3160:   Logically Collective

3162:   Input Parameters:
3163: + ts   - The `TS` context obtained from `TSCreate()`
3164: - func - The function

3166:   Calling sequence of func:
3167: .vb
3168:   PetscErrorCode func(TS ts, PetscReal stagetime, PetscInt stageindex, Vec* Y);
3169: .ve

3171:   Level: intermediate

3173:   Note:
3174:   There may be several stages per time step. If the solve for a given stage fails, the step may be rejected and retried.
3175:   The time step number being computed can be queried using `TSGetStepNumber()` and the total size of the step being
3176:   attempted can be obtained using `TSGetTimeStep()`. The time at the start of the step is available via `TSGetTime()`.

3178: .seealso: [](chapter_ts), `TS`, `TSSetPreStage()`, `TSSetPreStep()`, `TSSetPostStep()`, `TSGetApplicationContext()`
3179: @*/
3180: PetscErrorCode TSSetPostStage(TS ts, PetscErrorCode (*func)(TS, PetscReal, PetscInt, Vec *))
3181: {
3182:   PetscFunctionBegin;
3184:   ts->poststage = func;
3185:   PetscFunctionReturn(PETSC_SUCCESS);
3186: }

3188: /*@C
3189:   TSSetPostEvaluate - Sets the general-purpose function
3190:   called once at the end of each step evaluation.

3192:   Logically Collective

3194:   Input Parameters:
3195: + ts   - The `TS` context obtained from `TSCreate()`
3196: - func - The function

3198:   Calling sequence of func:
3199: .vb
3200:   PetscErrorCode func(TS ts);
3201: .ve

3203:   Level: intermediate

3205:   Note:
3206:   Semantically, `TSSetPostEvaluate()` differs from `TSSetPostStep()` since the function it sets is called before event-handling
3207:   thus guaranteeing the same solution (computed by the time-stepper) will be passed to it. On the other hand, `TSPostStep()`
3208:   may be passed a different solution, possibly changed by the event handler. `TSPostEvaluate()` is called after the next step
3209:   solution is evaluated allowing to modify it, if need be. The solution can be obtained with `TSGetSolution()`, the time step
3210:   with `TSGetTimeStep()`, and the time at the start of the step is available via `TSGetTime()`

3212: .seealso: [](chapter_ts), `TS`, `TSSetPreStage()`, `TSSetPreStep()`, `TSSetPostStep()`, `TSGetApplicationContext()`
3213: @*/
3214: PetscErrorCode TSSetPostEvaluate(TS ts, PetscErrorCode (*func)(TS))
3215: {
3216:   PetscFunctionBegin;
3218:   ts->postevaluate = func;
3219:   PetscFunctionReturn(PETSC_SUCCESS);
3220: }

3222: /*@
3223:   TSPreStage - Runs the user-defined pre-stage function set using `TSSetPreStage()`

3225:   Collective

3227:   Input Parameters:
3228: . ts          - The `TS` context obtained from `TSCreate()`
3229:   stagetime   - The absolute time of the current stage

3231:   Level: developer

3233:   Note:
3234:   `TSPreStage()` is typically used within time stepping implementations,
3235:   most users would not generally call this routine themselves.

3237: .seealso: [](chapter_ts), `TS`, `TSPostStage()`, `TSSetPreStep()`, `TSPreStep()`, `TSPostStep()`
3238: @*/
3239: PetscErrorCode TSPreStage(TS ts, PetscReal stagetime)
3240: {
3241:   PetscFunctionBegin;
3243:   if (ts->prestage) PetscCallBack("TS callback prestage", (*ts->prestage)(ts, stagetime));
3244:   PetscFunctionReturn(PETSC_SUCCESS);
3245: }

3247: /*@
3248:   TSPostStage - Runs the user-defined post-stage function set using `TSSetPostStage()`

3250:   Collective

3252:   Input Parameters:
3253: . ts          - The `TS` context obtained from `TSCreate()`
3254:   stagetime   - The absolute time of the current stage
3255:   stageindex  - Stage number
3256:   Y           - Array of vectors (of size = total number
3257:                 of stages) with the stage solutions

3259:   Level: developer

3261:   Note:
3262:   `TSPostStage()` is typically used within time stepping implementations,
3263:   most users would not generally call this routine themselves.

3265: .seealso: [](chapter_ts), `TS`, `TSPreStage()`, `TSSetPreStep()`, `TSPreStep()`, `TSPostStep()`
3266: @*/
3267: PetscErrorCode TSPostStage(TS ts, PetscReal stagetime, PetscInt stageindex, Vec *Y)
3268: {
3269:   PetscFunctionBegin;
3271:   if (ts->poststage) PetscCallBack("TS callback poststage", (*ts->poststage)(ts, stagetime, stageindex, Y));
3272:   PetscFunctionReturn(PETSC_SUCCESS);
3273: }

3275: /*@
3276:   TSPostEvaluate - Runs the user-defined post-evaluate function set using `TSSetPostEvaluate()`

3278:   Collective

3280:   Input Parameters:
3281: . ts - The `TS` context obtained from `TSCreate()`

3283:   Level: developer

3285:   Note:
3286:   `TSPostEvaluate()` is typically used within time stepping implementations,
3287:   most users would not generally call this routine themselves.

3289: .seealso: [](chapter_ts), `TS`, `TSSetPostEvaluate()`, `TSSetPreStep()`, `TSPreStep()`, `TSPostStep()`
3290: @*/
3291: PetscErrorCode TSPostEvaluate(TS ts)
3292: {
3293:   PetscFunctionBegin;
3295:   if (ts->postevaluate) {
3296:     Vec              U;
3297:     PetscObjectState sprev, spost;

3299:     PetscCall(TSGetSolution(ts, &U));
3300:     PetscCall(PetscObjectStateGet((PetscObject)U, &sprev));
3301:     PetscCallBack("TS callback postevaluate", (*ts->postevaluate)(ts));
3302:     PetscCall(PetscObjectStateGet((PetscObject)U, &spost));
3303:     if (sprev != spost) PetscCall(TSRestartStep(ts));
3304:   }
3305:   PetscFunctionReturn(PETSC_SUCCESS);
3306: }

3308: /*@C
3309:   TSSetPostStep - Sets the general-purpose function
3310:   called once at the end of each time step.

3312:   Logically Collective

3314:   Input Parameters:
3315: + ts   - The `TS` context obtained from `TSCreate()`
3316: - func - The function

3318:   Calling sequence of func:
3319: $ func (TS ts);

3321:   Level: intermediate

3323:   Note:
3324:   The function set by `TSSetPostStep()` is called after each successful step. The solution vector
3325:   obtained by `TSGetSolution()` may be different than that computed at the step end if the event handler
3326:   locates an event and `TSPostEvent()` modifies it. Use `TSSetPostEvaluate()` if an unmodified solution is needed instead.

3328: .seealso: [](chapter_ts), `TS`, `TSSetPreStep()`, `TSSetPreStage()`, `TSSetPostEvaluate()`, `TSGetTimeStep()`, `TSGetStepNumber()`, `TSGetTime()`, `TSRestartStep()`
3329: @*/
3330: PetscErrorCode TSSetPostStep(TS ts, PetscErrorCode (*func)(TS))
3331: {
3332:   PetscFunctionBegin;
3334:   ts->poststep = func;
3335:   PetscFunctionReturn(PETSC_SUCCESS);
3336: }

3338: /*@
3339:   TSPostStep - Runs the user-defined post-step function that was set with `TSSetPostStep()`

3341:   Collective

3343:   Input Parameters:
3344: . ts   - The `TS` context obtained from `TSCreate()`

3346:   Note:
3347:   `TSPostStep()` is typically used within time stepping implementations,
3348:   so most users would not generally call this routine themselves.

3350:   Level: developer

3352: .seealso: [](chapter_ts), `TS`, `TSSetPreStep()`, `TSSetPreStage()`, `TSSetPostEvaluate()`, `TSGetTimeStep()`, `TSGetStepNumber()`, `TSGetTime()`, `TSSetPotsStep()`
3353: @*/
3354: PetscErrorCode TSPostStep(TS ts)
3355: {
3356:   PetscFunctionBegin;
3358:   if (ts->poststep) {
3359:     Vec              U;
3360:     PetscObjectId    idprev;
3361:     PetscBool        sameObject;
3362:     PetscObjectState sprev, spost;

3364:     PetscCall(TSGetSolution(ts, &U));
3365:     PetscCall(PetscObjectGetId((PetscObject)U, &idprev));
3366:     PetscCall(PetscObjectStateGet((PetscObject)U, &sprev));
3367:     PetscCallBack("TS callback poststep", (*ts->poststep)(ts));
3368:     PetscCall(TSGetSolution(ts, &U));
3369:     PetscCall(PetscObjectCompareId((PetscObject)U, idprev, &sameObject));
3370:     PetscCall(PetscObjectStateGet((PetscObject)U, &spost));
3371:     if (!sameObject || sprev != spost) PetscCall(TSRestartStep(ts));
3372:   }
3373:   PetscFunctionReturn(PETSC_SUCCESS);
3374: }

3376: /*@
3377:    TSInterpolate - Interpolate the solution computed during the previous step to an arbitrary location in the interval

3379:    Collective

3381:    Input Parameters:
3382: +  ts - time stepping context
3383: -  t - time to interpolate to

3385:    Output Parameter:
3386: .  U - state at given time

3388:    Level: intermediate

3390:    Developer Note:
3391:    `TSInterpolate()` and the storing of previous steps/stages should be generalized to support delay differential equations and continuous adjoints.

3393: .seealso: [](chapter_ts), `TS`, `TSSetExactFinalTime()`, `TSSolve()`
3394: @*/
3395: PetscErrorCode TSInterpolate(TS ts, PetscReal t, Vec U)
3396: {
3397:   PetscFunctionBegin;
3400:   PetscCheck(t >= ts->ptime_prev && t <= ts->ptime, PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_OUTOFRANGE, "Requested time %g not in last time steps [%g,%g]", (double)t, (double)ts->ptime_prev, (double)ts->ptime);
3401:   PetscUseTypeMethod(ts, interpolate, t, U);
3402:   PetscFunctionReturn(PETSC_SUCCESS);
3403: }

3405: /*@
3406:    TSStep - Steps one time step

3408:    Collective

3410:    Input Parameter:
3411: .  ts - the `TS` context obtained from `TSCreate()`

3413:    Level: developer

3415:    Notes:
3416:    The public interface for the ODE/DAE solvers is `TSSolve()`, you should almost for sure be using that routine and not this routine.

3418:    The hook set using `TSSetPreStep()` is called before each attempt to take the step. In general, the time step size may
3419:    be changed due to adaptive error controller or solve failures. Note that steps may contain multiple stages.

3421:    This may over-step the final time provided in `TSSetMaxTime()` depending on the time-step used. `TSSolve()` interpolates to exactly the
3422:    time provided in `TSSetMaxTime()`. One can use `TSInterpolate()` to determine an interpolated solution within the final timestep.

3424: .seealso: [](chapter_ts), `TS`, `TSCreate()`, `TSSetUp()`, `TSDestroy()`, `TSSolve()`, `TSSetPreStep()`, `TSSetPreStage()`, `TSSetPostStage()`, `TSInterpolate()`
3425: @*/
3426: PetscErrorCode TSStep(TS ts)
3427: {
3428:   static PetscBool cite = PETSC_FALSE;
3429:   PetscReal        ptime;

3431:   PetscFunctionBegin;
3433:   PetscCall(PetscCitationsRegister("@article{tspaper,\n"
3434:                                    "  title         = {{PETSc/TS}: A Modern Scalable {DAE/ODE} Solver Library},\n"
3435:                                    "  author        = {Abhyankar, Shrirang and Brown, Jed and Constantinescu, Emil and Ghosh, Debojyoti and Smith, Barry F. and Zhang, Hong},\n"
3436:                                    "  journal       = {arXiv e-preprints},\n"
3437:                                    "  eprint        = {1806.01437},\n"
3438:                                    "  archivePrefix = {arXiv},\n"
3439:                                    "  year          = {2018}\n}\n",
3440:                                    &cite));
3441:   PetscCall(TSSetUp(ts));
3442:   PetscCall(TSTrajectorySetUp(ts->trajectory, ts));

3444:   PetscCheck(ts->max_time < PETSC_MAX_REAL || ts->max_steps != PETSC_MAX_INT, PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_WRONGSTATE, "You must call TSSetMaxTime() or TSSetMaxSteps(), or use -ts_max_time <time> or -ts_max_steps <steps>");
3445:   PetscCheck(ts->exact_final_time != TS_EXACTFINALTIME_UNSPECIFIED, PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_WRONGSTATE, "You must call TSSetExactFinalTime() or use -ts_exact_final_time <stepover,interpolate,matchstep> before calling TSStep()");
3446:   PetscCheck(ts->exact_final_time != TS_EXACTFINALTIME_MATCHSTEP || ts->adapt, PetscObjectComm((PetscObject)ts), PETSC_ERR_SUP, "Since TS is not adaptive you cannot use TS_EXACTFINALTIME_MATCHSTEP, suggest TS_EXACTFINALTIME_INTERPOLATE");

3448:   if (!ts->steps) ts->ptime_prev = ts->ptime;
3449:   ptime                   = ts->ptime;
3450:   ts->ptime_prev_rollback = ts->ptime_prev;
3451:   ts->reason              = TS_CONVERGED_ITERATING;

3453:   PetscCall(PetscLogEventBegin(TS_Step, ts, 0, 0, 0));
3454:   PetscUseTypeMethod(ts, step);
3455:   PetscCall(PetscLogEventEnd(TS_Step, ts, 0, 0, 0));

3457:   if (ts->tspan && PetscIsCloseAtTol(ts->ptime, ts->tspan->span_times[ts->tspan->spanctr], ts->tspan->reltol * ts->time_step + ts->tspan->abstol, 0) && ts->tspan->spanctr < ts->tspan->num_span_times)
3458:     PetscCall(VecCopy(ts->vec_sol, ts->tspan->vecs_sol[ts->tspan->spanctr++]));
3459:   if (ts->reason >= 0) {
3460:     ts->ptime_prev = ptime;
3461:     ts->steps++;
3462:     ts->steprollback = PETSC_FALSE;
3463:     ts->steprestart  = PETSC_FALSE;
3464:   }
3465:   if (!ts->reason) {
3466:     if (ts->steps >= ts->max_steps) ts->reason = TS_CONVERGED_ITS;
3467:     else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME;
3468:   }

3470:   if (ts->reason < 0 && ts->errorifstepfailed) {
3471:     PetscCall(TSMonitorCancel(ts));
3472:     PetscCheck(ts->reason != TS_DIVERGED_NONLINEAR_SOLVE, 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]);
3473:     SETERRQ(PetscObjectComm((PetscObject)ts), PETSC_ERR_NOT_CONVERGED, "TSStep has failed due to %s", TSConvergedReasons[ts->reason]);
3474:   }
3475:   PetscFunctionReturn(PETSC_SUCCESS);
3476: }

3478: /*@
3479:    TSEvaluateWLTE - Evaluate the weighted local truncation error norm
3480:    at the end of a time step with a given order of accuracy.

3482:    Collective

3484:    Input Parameters:
3485: +  ts - time stepping context
3486: -  wnormtype - norm type, either `NORM_2` or `NORM_INFINITY`

3488:    Input/Output Parameter:
3489: .  order - optional, desired order for the error evaluation or `PETSC_DECIDE`;
3490:            on output, the actual order of the error evaluation

3492:    Output Parameter:
3493: .  wlte - the weighted local truncation error norm

3495:    Level: advanced

3497:    Note:
3498:    If the timestepper cannot evaluate the error in a particular step
3499:    (eg. in the first step or restart steps after event handling),
3500:    this routine returns wlte=-1.0 .

3502: .seealso: [](chapter_ts), `TS`, `TSStep()`, `TSAdapt`, `TSErrorWeightedNorm()`
3503: @*/
3504: PetscErrorCode TSEvaluateWLTE(TS ts, NormType wnormtype, PetscInt *order, PetscReal *wlte)
3505: {
3506:   PetscFunctionBegin;
3513:   PetscCheck(wnormtype == NORM_2 || wnormtype == NORM_INFINITY, PetscObjectComm((PetscObject)ts), PETSC_ERR_SUP, "No support for norm type %s", NormTypes[wnormtype]);
3514:   PetscUseTypeMethod(ts, evaluatewlte, wnormtype, order, wlte);
3515:   PetscFunctionReturn(PETSC_SUCCESS);
3516: }

3518: /*@
3519:    TSEvaluateStep - Evaluate the solution at the end of a time step with a given order of accuracy.

3521:    Collective

3523:    Input Parameters:
3524: +  ts - time stepping context
3525: .  order - desired order of accuracy
3526: -  done - whether the step was evaluated at this order (pass `NULL` to generate an error if not available)

3528:    Output Parameter:
3529: .  U - state at the end of the current step

3531:    Level: advanced

3533:    Notes:
3534:    This function cannot be called until all stages have been evaluated.

3536:    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.

3538: .seealso: [](chapter_ts), `TS`, `TSStep()`, `TSAdapt`
3539: @*/
3540: PetscErrorCode TSEvaluateStep(TS ts, PetscInt order, Vec U, PetscBool *done)
3541: {
3542:   PetscFunctionBegin;
3546:   PetscUseTypeMethod(ts, evaluatestep, order, U, done);
3547:   PetscFunctionReturn(PETSC_SUCCESS);
3548: }

3550: /*@C
3551:   TSGetComputeInitialCondition - Get the function used to automatically compute an initial condition for the timestepping.

3553:   Not collective

3555:   Input Parameter:
3556: . ts - time stepping context

3558:   Output Parameter:
3559: . initConditions - The function which computes an initial condition

3561:   The calling sequence for the function is
3562: .vb
3563:  initCondition(TS ts, Vec u)
3564:  ts - The timestepping context
3565:  u  - The input vector in which the initial condition is stored
3566: .ve

3568:    Level: advanced

3570: .seealso: [](chapter_ts), `TS`, `TSSetComputeInitialCondition()`, `TSComputeInitialCondition()`
3571: @*/
3572: PetscErrorCode TSGetComputeInitialCondition(TS ts, PetscErrorCode (**initCondition)(TS, Vec))
3573: {
3574:   PetscFunctionBegin;
3577:   *initCondition = ts->ops->initcondition;
3578:   PetscFunctionReturn(PETSC_SUCCESS);
3579: }

3581: /*@C
3582:   TSSetComputeInitialCondition - Set the function used to automatically compute an initial condition for the timestepping.

3584:   Logically collective

3586:   Input Parameters:
3587: + ts  - time stepping context
3588: - initCondition - The function which computes an initial condition

3590:   Calling sequence for initCondition:
3591: $ PetscErrorCode initCondition(TS ts, Vec u)
3592: + ts - The timestepping context
3593: - u  - The input vector in which the initial condition is to be stored

3595:   Level: advanced

3597: .seealso: [](chapter_ts), `TS`, `TSGetComputeInitialCondition()`, `TSComputeInitialCondition()`
3598: @*/
3599: PetscErrorCode TSSetComputeInitialCondition(TS ts, PetscErrorCode (*initCondition)(TS, Vec))
3600: {
3601:   PetscFunctionBegin;
3604:   ts->ops->initcondition = initCondition;
3605:   PetscFunctionReturn(PETSC_SUCCESS);
3606: }

3608: /*@
3609:   TSComputeInitialCondition - Compute an initial condition for the timestepping using the function previously set with `TSSetComputeInitialCondition()`

3611:   Collective

3613:   Input Parameters:
3614: + ts - time stepping context
3615: - u  - The `Vec` to store the condition in which will be used in `TSSolve()`

3617:   Level: advanced

3619: .seealso: [](chapter_ts), `TS`, `TSGetComputeInitialCondition()`, `TSSetComputeInitialCondition()`, `TSSolve()`
3620: @*/
3621: PetscErrorCode TSComputeInitialCondition(TS ts, Vec u)
3622: {
3623:   PetscFunctionBegin;
3626:   PetscTryTypeMethod(ts, initcondition, u);
3627:   PetscFunctionReturn(PETSC_SUCCESS);
3628: }

3630: /*@C
3631:   TSGetComputeExactError - Get the function used to automatically compute the exact error for the timestepping.

3633:   Not collective

3635:   Input Parameter:
3636: . ts - time stepping context

3638:   Output Parameter:
3639: . exactError - The function which computes the solution error

3641:   Calling sequence for exactError:
3642: $ PetscErrorCode exactError(TS ts, Vec u)
3643: + ts - The timestepping context
3644: . u  - The approximate solution vector
3645: - e  - The input vector in which the error is stored

3647:   Level: advanced

3649: .seealso: [](chapter_ts), `TS`, `TSGetComputeExactError()`, `TSComputeExactError()`
3650: @*/
3651: PetscErrorCode TSGetComputeExactError(TS ts, PetscErrorCode (**exactError)(TS, Vec, Vec))
3652: {
3653:   PetscFunctionBegin;
3656:   *exactError = ts->ops->exacterror;
3657:   PetscFunctionReturn(PETSC_SUCCESS);
3658: }

3660: /*@C
3661:   TSSetComputeExactError - Set the function used to automatically compute the exact error for the timestepping.

3663:   Logically collective

3665:   Input Parameters:
3666: + ts - time stepping context
3667: - exactError - The function which computes the solution error

3669:   Calling sequence for exactError:
3670: $ PetscErrorCode exactError(TS ts, Vec u)
3671: + ts - The timestepping context
3672: . u  - The approximate solution vector
3673: - e  - The input vector in which the error is stored

3675:   Level: advanced

3677: .seealso: [](chapter_ts), `TS`, `TSGetComputeExactError()`, `TSComputeExactError()`
3678: @*/
3679: PetscErrorCode TSSetComputeExactError(TS ts, PetscErrorCode (*exactError)(TS, Vec, Vec))
3680: {
3681:   PetscFunctionBegin;
3684:   ts->ops->exacterror = exactError;
3685:   PetscFunctionReturn(PETSC_SUCCESS);
3686: }

3688: /*@
3689:   TSComputeExactError - Compute the solution error for the timestepping using the function previously set with `TSSetComputeExactError()`

3691:   Collective

3693:   Input Parameters:
3694: + ts - time stepping context
3695: . u  - The approximate solution
3696: - e  - The `Vec` used to store the error

3698:   Level: advanced

3700: .seealso: [](chapter_ts), `TS`, `TSGetComputeInitialCondition()`, `TSSetComputeInitialCondition()`, `TSSolve()`
3701: @*/
3702: PetscErrorCode TSComputeExactError(TS ts, Vec u, Vec e)
3703: {
3704:   PetscFunctionBegin;
3708:   PetscTryTypeMethod(ts, exacterror, u, e);
3709:   PetscFunctionReturn(PETSC_SUCCESS);
3710: }

3712: /*@
3713:    TSSolve - Steps the requested number of timesteps.

3715:    Collective

3717:    Input Parameters:
3718: +  ts - the `TS` context obtained from `TSCreate()`
3719: -  u - the solution vector  (can be null if `TSSetSolution()` was used and `TSSetExactFinalTime`(ts,`TS_EXACTFINALTIME_MATCHSTEP`) was not used,
3720:                              otherwise must contain the initial conditions and will contain the solution at the final requested time

3722:    Level: beginner

3724:    Notes:
3725:    The final time returned by this function may be different from the time of the internally
3726:    held state accessible by `TSGetSolution()` and `TSGetTime()` because the method may have
3727:    stepped over the final time.

3729: .seealso: [](chapter_ts), `TS`, `TSCreate()`, `TSSetSolution()`, `TSStep()`, `TSGetTime()`, `TSGetSolveTime()`
3730: @*/
3731: PetscErrorCode TSSolve(TS ts, Vec u)
3732: {
3733:   Vec solution;

3735:   PetscFunctionBegin;

3739:   PetscCall(TSSetExactFinalTimeDefault(ts));
3740:   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 */
3741:     if (!ts->vec_sol || u == ts->vec_sol) {
3742:       PetscCall(VecDuplicate(u, &solution));
3743:       PetscCall(TSSetSolution(ts, solution));
3744:       PetscCall(VecDestroy(&solution)); /* grant ownership */
3745:     }
3746:     PetscCall(VecCopy(u, ts->vec_sol));
3747:     PetscCheck(!ts->forward_solve, PetscObjectComm((PetscObject)ts), PETSC_ERR_SUP, "Sensitivity analysis does not support the mode TS_EXACTFINALTIME_INTERPOLATE");
3748:   } else if (u) PetscCall(TSSetSolution(ts, u));
3749:   PetscCall(TSSetUp(ts));
3750:   PetscCall(TSTrajectorySetUp(ts->trajectory, ts));

3752:   PetscCheck(ts->max_time < PETSC_MAX_REAL || ts->max_steps != PETSC_MAX_INT, PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_WRONGSTATE, "You must call TSSetMaxTime() or TSSetMaxSteps(), or use -ts_max_time <time> or -ts_max_steps <steps>");
3753:   PetscCheck(ts->exact_final_time != TS_EXACTFINALTIME_UNSPECIFIED, PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_WRONGSTATE, "You must call TSSetExactFinalTime() or use -ts_exact_final_time <stepover,interpolate,matchstep> before calling TSSolve()");
3754:   PetscCheck(ts->exact_final_time != TS_EXACTFINALTIME_MATCHSTEP || ts->adapt, PetscObjectComm((PetscObject)ts), PETSC_ERR_SUP, "Since TS is not adaptive you cannot use TS_EXACTFINALTIME_MATCHSTEP, suggest TS_EXACTFINALTIME_INTERPOLATE");
3755:   PetscCheck(!(ts->tspan && ts->exact_final_time != TS_EXACTFINALTIME_MATCHSTEP), PetscObjectComm((PetscObject)ts), PETSC_ERR_SUP, "You must use TS_EXACTFINALTIME_MATCHSTEP when using time span");

3757:   if (ts->tspan && PetscIsCloseAtTol(ts->ptime, ts->tspan->span_times[0], ts->tspan->reltol * ts->time_step + ts->tspan->abstol, 0)) { /* starting point in time span */
3758:     PetscCall(VecCopy(ts->vec_sol, ts->tspan->vecs_sol[0]));
3759:     ts->tspan->spanctr = 1;
3760:   }

3762:   if (ts->forward_solve) PetscCall(TSForwardSetUp(ts));

3764:   /* reset number of steps only when the step is not restarted. ARKIMEX
3765:      restarts the step after an event. Resetting these counters in such case causes
3766:      TSTrajectory to incorrectly save the output files
3767:   */
3768:   /* reset time step and iteration counters */
3769:   if (!ts->steps) {
3770:     ts->ksp_its           = 0;
3771:     ts->snes_its          = 0;
3772:     ts->num_snes_failures = 0;
3773:     ts->reject            = 0;
3774:     ts->steprestart       = PETSC_TRUE;
3775:     ts->steprollback      = PETSC_FALSE;
3776:     ts->rhsjacobian.time  = PETSC_MIN_REAL;
3777:   }

3779:   /* make sure initial time step does not overshoot final time or the next point in tspan */
3780:   if (ts->exact_final_time == TS_EXACTFINALTIME_MATCHSTEP) {
3781:     PetscReal maxdt;
3782:     PetscReal dt = ts->time_step;

3784:     if (ts->tspan) maxdt = ts->tspan->span_times[ts->tspan->spanctr] - ts->ptime;
3785:     else maxdt = ts->max_time - ts->ptime;
3786:     ts->time_step = dt >= maxdt ? maxdt : (PetscIsCloseAtTol(dt, maxdt, 10 * PETSC_MACHINE_EPSILON, 0) ? maxdt : dt);
3787:   }
3788:   ts->reason = TS_CONVERGED_ITERATING;

3790:   {
3791:     PetscViewer       viewer;
3792:     PetscViewerFormat format;
3793:     PetscBool         flg;
3794:     static PetscBool  incall = PETSC_FALSE;

3796:     if (!incall) {
3797:       /* Estimate the convergence rate of the time discretization */
3798:       PetscCall(PetscOptionsGetViewer(PetscObjectComm((PetscObject)ts), ((PetscObject)ts)->options, ((PetscObject)ts)->prefix, "-ts_convergence_estimate", &viewer, &format, &flg));
3799:       if (flg) {
3800:         PetscConvEst conv;
3801:         DM           dm;
3802:         PetscReal   *alpha; /* Convergence rate of the solution error for each field in the L_2 norm */
3803:         PetscInt     Nf;
3804:         PetscBool    checkTemporal = PETSC_TRUE;

3806:         incall = PETSC_TRUE;
3807:         PetscCall(PetscOptionsGetBool(((PetscObject)ts)->options, ((PetscObject)ts)->prefix, "-ts_convergence_temporal", &checkTemporal, &flg));
3808:         PetscCall(TSGetDM(ts, &dm));
3809:         PetscCall(DMGetNumFields(dm, &Nf));
3810:         PetscCall(PetscCalloc1(PetscMax(Nf, 1), &alpha));
3811:         PetscCall(PetscConvEstCreate(PetscObjectComm((PetscObject)ts), &conv));
3812:         PetscCall(PetscConvEstUseTS(conv, checkTemporal));
3813:         PetscCall(PetscConvEstSetSolver(conv, (PetscObject)ts));
3814:         PetscCall(PetscConvEstSetFromOptions(conv));
3815:         PetscCall(PetscConvEstSetUp(conv));
3816:         PetscCall(PetscConvEstGetConvRate(conv, alpha));
3817:         PetscCall(PetscViewerPushFormat(viewer, format));
3818:         PetscCall(PetscConvEstRateView(conv, alpha, viewer));
3819:         PetscCall(PetscViewerPopFormat(viewer));
3820:         PetscCall(PetscViewerDestroy(&viewer));
3821:         PetscCall(PetscConvEstDestroy(&conv));
3822:         PetscCall(PetscFree(alpha));
3823:         incall = PETSC_FALSE;
3824:       }
3825:     }
3826:   }

3828:   PetscCall(TSViewFromOptions(ts, NULL, "-ts_view_pre"));

3830:   if (ts->ops->solve) { /* This private interface is transitional and should be removed when all implementations are updated. */
3831:     PetscUseTypeMethod(ts, solve);
3832:     if (u) PetscCall(VecCopy(ts->vec_sol, u));
3833:     ts->solvetime = ts->ptime;
3834:     solution      = ts->vec_sol;
3835:   } else { /* Step the requested number of timesteps. */
3836:     if (ts->steps >= ts->max_steps) ts->reason = TS_CONVERGED_ITS;
3837:     else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME;

3839:     if (!ts->steps) {
3840:       PetscCall(TSTrajectorySet(ts->trajectory, ts, ts->steps, ts->ptime, ts->vec_sol));
3841:       PetscCall(TSEventInitialize(ts->event, ts, ts->ptime, ts->vec_sol));
3842:     }

3844:     while (!ts->reason) {
3845:       PetscCall(TSMonitor(ts, ts->steps, ts->ptime, ts->vec_sol));
3846:       if (!ts->steprollback) PetscCall(TSPreStep(ts));
3847:       PetscCall(TSStep(ts));
3848:       if (ts->testjacobian) PetscCall(TSRHSJacobianTest(ts, NULL));
3849:       if (ts->testjacobiantranspose) PetscCall(TSRHSJacobianTestTranspose(ts, NULL));
3850:       if (ts->quadraturets && ts->costintegralfwd) { /* Must evaluate the cost integral before event is handled. The cost integral value can also be rolled back. */
3851:         if (ts->reason >= 0) ts->steps--;            /* Revert the step number changed by TSStep() */
3852:         PetscCall(TSForwardCostIntegral(ts));
3853:         if (ts->reason >= 0) ts->steps++;
3854:       }
3855:       if (ts->forward_solve) {            /* compute forward sensitivities before event handling because postevent() may change RHS and jump conditions may have to be applied */
3856:         if (ts->reason >= 0) ts->steps--; /* Revert the step number changed by TSStep() */
3857:         PetscCall(TSForwardStep(ts));
3858:         if (ts->reason >= 0) ts->steps++;
3859:       }
3860:       PetscCall(TSPostEvaluate(ts));
3861:       PetscCall(TSEventHandler(ts)); /* The right-hand side may be changed due to event. Be careful with Any computation using the RHS information after this point. */
3862:       if (ts->steprollback) PetscCall(TSPostEvaluate(ts));
3863:       if (!ts->steprollback) {
3864:         PetscCall(TSTrajectorySet(ts->trajectory, ts, ts->steps, ts->ptime, ts->vec_sol));
3865:         PetscCall(TSPostStep(ts));
3866:       }
3867:     }
3868:     PetscCall(TSMonitor(ts, ts->steps, ts->ptime, ts->vec_sol));

3870:     if (ts->exact_final_time == TS_EXACTFINALTIME_INTERPOLATE && ts->ptime > ts->max_time) {
3871:       PetscCall(TSInterpolate(ts, ts->max_time, u));
3872:       ts->solvetime = ts->max_time;
3873:       solution      = u;
3874:       PetscCall(TSMonitor(ts, -1, ts->solvetime, solution));
3875:     } else {
3876:       if (u) PetscCall(VecCopy(ts->vec_sol, u));
3877:       ts->solvetime = ts->ptime;
3878:       solution      = ts->vec_sol;
3879:     }
3880:   }

3882:   PetscCall(TSViewFromOptions(ts, NULL, "-ts_view"));
3883:   PetscCall(VecViewFromOptions(solution, (PetscObject)ts, "-ts_view_solution"));
3884:   PetscCall(PetscObjectSAWsBlock((PetscObject)ts));
3885:   if (ts->adjoint_solve) PetscCall(TSAdjointSolve(ts));
3886:   PetscFunctionReturn(PETSC_SUCCESS);
3887: }

3889: /*@
3890:    TSGetTime - Gets the time of the most recently completed step.

3892:    Not Collective

3894:    Input Parameter:
3895: .  ts - the `TS` context obtained from `TSCreate()`

3897:    Output Parameter:
3898: .  t  - the current time. This time may not corresponds to the final time set with `TSSetMaxTime()`, use `TSGetSolveTime()`.

3900:    Level: beginner

3902:    Note:
3903:    When called during time step evaluation (e.g. during residual evaluation or via hooks set using `TSSetPreStep()`,
3904:    `TSSetPreStage()`, `TSSetPostStage()`, or `TSSetPostStep()`), the time is the time at the start of the step being evaluated.

3906: .seealso: [](chapter_ts), TS`, ``TSGetSolveTime()`, `TSSetTime()`, `TSGetTimeStep()`, `TSGetStepNumber()`
3907: @*/
3908: PetscErrorCode TSGetTime(TS ts, PetscReal *t)
3909: {
3910:   PetscFunctionBegin;
3913:   *t = ts->ptime;
3914:   PetscFunctionReturn(PETSC_SUCCESS);
3915: }

3917: /*@
3918:    TSGetPrevTime - Gets the starting time of the previously completed step.

3920:    Not Collective

3922:    Input Parameter:
3923: .  ts - the `TS` context obtained from `TSCreate()`

3925:    Output Parameter:
3926: .  t  - the previous time

3928:    Level: beginner

3930: .seealso: [](chapter_ts), TS`, ``TSGetTime()`, `TSGetSolveTime()`, `TSGetTimeStep()`
3931: @*/
3932: PetscErrorCode TSGetPrevTime(TS ts, PetscReal *t)
3933: {
3934:   PetscFunctionBegin;
3937:   *t = ts->ptime_prev;
3938:   PetscFunctionReturn(PETSC_SUCCESS);
3939: }

3941: /*@
3942:    TSSetTime - Allows one to reset the time.

3944:    Logically Collective

3946:    Input Parameters:
3947: +  ts - the `TS` context obtained from `TSCreate()`
3948: -  time - the time

3950:    Level: intermediate

3952: .seealso: [](chapter_ts), `TS`, `TSGetTime()`, `TSSetMaxSteps()`
3953: @*/
3954: PetscErrorCode TSSetTime(TS ts, PetscReal t)
3955: {
3956:   PetscFunctionBegin;
3959:   ts->ptime = t;
3960:   PetscFunctionReturn(PETSC_SUCCESS);
3961: }

3963: /*@C
3964:    TSSetOptionsPrefix - Sets the prefix used for searching for all
3965:    TS options in the database.

3967:    Logically Collective

3969:    Input Parameters:
3970: +  ts     - The `TS` context
3971: -  prefix - The prefix to prepend to all option names

3973:    Level: advanced

3975:    Note:
3976:    A hyphen (-) must NOT be given at the beginning of the prefix name.
3977:    The first character of all runtime options is AUTOMATICALLY the
3978:    hyphen.

3980: .seealso: [](chapter_ts), `TS`, `TSSetFromOptions()`, `TSAppendOptionsPrefix()`
3981: @*/
3982: PetscErrorCode TSSetOptionsPrefix(TS ts, const char prefix[])
3983: {
3984:   SNES snes;

3986:   PetscFunctionBegin;
3988:   PetscCall(PetscObjectSetOptionsPrefix((PetscObject)ts, prefix));
3989:   PetscCall(TSGetSNES(ts, &snes));
3990:   PetscCall(SNESSetOptionsPrefix(snes, prefix));
3991:   PetscFunctionReturn(PETSC_SUCCESS);
3992: }

3994: /*@C
3995:    TSAppendOptionsPrefix - Appends to the prefix used for searching for all
3996:    TS options in the database.

3998:    Logically Collective

4000:    Input Parameters:
4001: +  ts     - The `TS` context
4002: -  prefix - The prefix to prepend to all option names

4004:    Level: advanced

4006:    Note:
4007:    A hyphen (-) must NOT be given at the beginning of the prefix name.
4008:    The first character of all runtime options is AUTOMATICALLY the
4009:    hyphen.

4011: .seealso: [](chapter_ts), `TS`, `TSGetOptionsPrefix()`, `TSSetOptionsPrefix()`, `TSSetFromOptions()`
4012: @*/
4013: PetscErrorCode TSAppendOptionsPrefix(TS ts, const char prefix[])
4014: {
4015:   SNES snes;

4017:   PetscFunctionBegin;
4019:   PetscCall(PetscObjectAppendOptionsPrefix((PetscObject)ts, prefix));
4020:   PetscCall(TSGetSNES(ts, &snes));
4021:   PetscCall(SNESAppendOptionsPrefix(snes, prefix));
4022:   PetscFunctionReturn(PETSC_SUCCESS);
4023: }

4025: /*@C
4026:    TSGetOptionsPrefix - Sets the prefix used for searching for all
4027:    `TS` options in the database.

4029:    Not Collective

4031:    Input Parameter:
4032: .  ts - The `TS` context

4034:    Output Parameter:
4035: .  prefix - A pointer to the prefix string used

4037:    Level: intermediate

4039:    Fortran Note:
4040:    The user should pass in a string 'prefix' of
4041:    sufficient length to hold the prefix.

4043: .seealso: [](chapter_ts), `TS`, `TSAppendOptionsPrefix()`, `TSSetFromOptions()`
4044: @*/
4045: PetscErrorCode TSGetOptionsPrefix(TS ts, const char *prefix[])
4046: {
4047:   PetscFunctionBegin;
4050:   PetscCall(PetscObjectGetOptionsPrefix((PetscObject)ts, prefix));
4051:   PetscFunctionReturn(PETSC_SUCCESS);
4052: }

4054: /*@C
4055:    TSGetRHSJacobian - Returns the Jacobian J at the present timestep.

4057:    Not Collective, but parallel objects are returned if ts is parallel

4059:    Input Parameter:
4060: .  ts  - The `TS` context obtained from `TSCreate()`

4062:    Output Parameters:
4063: +  Amat - The (approximate) Jacobian J of G, where U_t = G(U,t)  (or `NULL`)
4064: .  Pmat - The matrix from which the preconditioner is constructed, usually the same as `Amat`  (or `NULL`)
4065: .  func - Function to compute the Jacobian of the RHS  (or `NULL`)
4066: -  ctx - User-defined context for Jacobian evaluation routine  (or `NULL`)

4068:    Level: intermediate

4070:    Note:
4071:     You can pass in `NULL` for any return argument you do not need.

4073: .seealso: [](chapter_ts), `TS`, `TSGetTimeStep()`, `TSGetMatrices()`, `TSGetTime()`, `TSGetStepNumber()`

4075: @*/
4076: PetscErrorCode TSGetRHSJacobian(TS ts, Mat *Amat, Mat *Pmat, TSRHSJacobian *func, void **ctx)
4077: {
4078:   DM dm;

4080:   PetscFunctionBegin;
4081:   if (Amat || Pmat) {
4082:     SNES snes;
4083:     PetscCall(TSGetSNES(ts, &snes));
4084:     PetscCall(SNESSetUpMatrices(snes));
4085:     PetscCall(SNESGetJacobian(snes, Amat, Pmat, NULL, NULL));
4086:   }
4087:   PetscCall(TSGetDM(ts, &dm));
4088:   PetscCall(DMTSGetRHSJacobian(dm, func, ctx));
4089:   PetscFunctionReturn(PETSC_SUCCESS);
4090: }

4092: /*@C
4093:    TSGetIJacobian - Returns the implicit Jacobian at the present timestep.

4095:    Not Collective, but parallel objects are returned if ts is parallel

4097:    Input Parameter:
4098: .  ts  - The `TS` context obtained from `TSCreate()`

4100:    Output Parameters:
4101: +  Amat  - The (approximate) Jacobian of F(t,U,U_t)
4102: .  Pmat - The matrix from which the preconditioner is constructed, often the same as `Amat`
4103: .  f   - The function to compute the matrices
4104: - ctx - User-defined context for Jacobian evaluation routine

4106:    Level: advanced

4108:    Note:
4109:     You can pass in `NULL` for any return argument you do not need.

4111: .seealso: [](chapter_ts), `TS`, `TSGetTimeStep()`, `TSGetRHSJacobian()`, `TSGetMatrices()`, `TSGetTime()`, `TSGetStepNumber()`
4112: @*/
4113: PetscErrorCode TSGetIJacobian(TS ts, Mat *Amat, Mat *Pmat, TSIJacobian *f, void **ctx)
4114: {
4115:   DM dm;

4117:   PetscFunctionBegin;
4118:   if (Amat || Pmat) {
4119:     SNES snes;
4120:     PetscCall(TSGetSNES(ts, &snes));
4121:     PetscCall(SNESSetUpMatrices(snes));
4122:     PetscCall(SNESGetJacobian(snes, Amat, Pmat, NULL, NULL));
4123:   }
4124:   PetscCall(TSGetDM(ts, &dm));
4125:   PetscCall(DMTSGetIJacobian(dm, f, ctx));
4126:   PetscFunctionReturn(PETSC_SUCCESS);
4127: }

4129: #include <petsc/private/dmimpl.h>
4130: /*@
4131:    TSSetDM - Sets the `DM` that may be used by some nonlinear solvers or preconditioners under the `TS`

4133:    Logically Collective

4135:    Input Parameters:
4136: +  ts - the `TS` integrator object
4137: -  dm - the dm, cannot be `NULL`

4139:    Level: intermediate

4141:    Notes:
4142:    A `DM` can only be used for solving one problem at a time because information about the problem is stored on the `DM`,
4143:    even when not using interfaces like `DMTSSetIFunction()`.  Use `DMClone()` to get a distinct `DM` when solving
4144:    different problems using the same function space.

4146: .seealso: [](chapter_ts), `TS`, `DM`, `TSGetDM()`, `SNESSetDM()`, `SNESGetDM()`
4147: @*/
4148: PetscErrorCode TSSetDM(TS ts, DM dm)
4149: {
4150:   SNES snes;
4151:   DMTS tsdm;

4153:   PetscFunctionBegin;
4156:   PetscCall(PetscObjectReference((PetscObject)dm));
4157:   if (ts->dm) { /* Move the DMTS context over to the new DM unless the new DM already has one */
4158:     if (ts->dm->dmts && !dm->dmts) {
4159:       PetscCall(DMCopyDMTS(ts->dm, dm));
4160:       PetscCall(DMGetDMTS(ts->dm, &tsdm));
4161:       /* Grant write privileges to the replacement DM */
4162:       if (tsdm->originaldm == ts->dm) tsdm->originaldm = dm;
4163:     }
4164:     PetscCall(DMDestroy(&ts->dm));
4165:   }
4166:   ts->dm = dm;

4168:   PetscCall(TSGetSNES(ts, &snes));
4169:   PetscCall(SNESSetDM(snes, dm));
4170:   PetscFunctionReturn(PETSC_SUCCESS);
4171: }

4173: /*@
4174:    TSGetDM - Gets the `DM` that may be used by some preconditioners

4176:    Not Collective

4178:    Input Parameter:
4179: . ts - the `TS`

4181:    Output Parameter:
4182: .  dm - the `DM`

4184:    Level: intermediate

4186: .seealso: [](chapter_ts), `TS`, `DM`, `TSSetDM()`, `SNESSetDM()`, `SNESGetDM()`
4187: @*/
4188: PetscErrorCode TSGetDM(TS ts, DM *dm)
4189: {
4190:   PetscFunctionBegin;
4192:   if (!ts->dm) {
4193:     PetscCall(DMShellCreate(PetscObjectComm((PetscObject)ts), &ts->dm));
4194:     if (ts->snes) PetscCall(SNESSetDM(ts->snes, ts->dm));
4195:   }
4196:   *dm = ts->dm;
4197:   PetscFunctionReturn(PETSC_SUCCESS);
4198: }

4200: /*@
4201:    SNESTSFormFunction - Function to evaluate nonlinear residual

4203:    Logically Collective

4205:    Input Parameters:
4206: + snes - nonlinear solver
4207: . U - the current state at which to evaluate the residual
4208: - ctx - user context, must be a TS

4210:    Output Parameter:
4211: . F - the nonlinear residual

4213:    Level: advanced

4215:    Note:
4216:    This function is not normally called by users and is automatically registered with the `SNES` used by `TS`.
4217:    It is most frequently passed to `MatFDColoringSetFunction()`.

4219: .seealso: [](chapter_ts), `SNESSetFunction()`, `MatFDColoringSetFunction()`
4220: @*/
4221: PetscErrorCode SNESTSFormFunction(SNES snes, Vec U, Vec F, void *ctx)
4222: {
4223:   TS ts = (TS)ctx;

4225:   PetscFunctionBegin;
4230:   PetscCall((ts->ops->snesfunction)(snes, U, F, ts));
4231:   PetscFunctionReturn(PETSC_SUCCESS);
4232: }

4234: /*@
4235:    SNESTSFormJacobian - Function to evaluate the Jacobian

4237:    Collective

4239:    Input Parameters:
4240: + snes - nonlinear solver
4241: . U - the current state at which to evaluate the residual
4242: - ctx - user context, must be a `TS`

4244:    Output Parameters:
4245: + A - the Jacobian
4246: - B - the preconditioning matrix (may be the same as A)

4248:    Level: developer

4250:    Note:
4251:    This function is not normally called by users and is automatically registered with the `SNES` used by `TS`.

4253: .seealso: [](chapter_ts), `SNESSetJacobian()`
4254: @*/
4255: PetscErrorCode SNESTSFormJacobian(SNES snes, Vec U, Mat A, Mat B, void *ctx)
4256: {
4257:   TS ts = (TS)ctx;

4259:   PetscFunctionBegin;
4267:   PetscCall((ts->ops->snesjacobian)(snes, U, A, B, ts));
4268:   PetscFunctionReturn(PETSC_SUCCESS);
4269: }

4271: /*@C
4272:    TSComputeRHSFunctionLinear - Evaluate the right hand side via the user-provided Jacobian, for linear problems Udot = A U only

4274:    Collective

4276:    Input Parameters:
4277: +  ts - time stepping context
4278: .  t - time at which to evaluate
4279: .  U - state at which to evaluate
4280: -  ctx - context

4282:    Output Parameter:
4283: .  F - right hand side

4285:    Level: intermediate

4287:    Note:
4288:    This function is intended to be passed to `TSSetRHSFunction()` to evaluate the right hand side for linear problems.
4289:    The matrix (and optionally the evaluation context) should be passed to `TSSetRHSJacobian()`.

4291: .seealso: [](chapter_ts), `TS`, `TSSetRHSFunction()`, `TSSetRHSJacobian()`, `TSComputeRHSJacobianConstant()`
4292: @*/
4293: PetscErrorCode TSComputeRHSFunctionLinear(TS ts, PetscReal t, Vec U, Vec F, void *ctx)
4294: {
4295:   Mat Arhs, Brhs;

4297:   PetscFunctionBegin;
4298:   PetscCall(TSGetRHSMats_Private(ts, &Arhs, &Brhs));
4299:   /* undo the damage caused by shifting */
4300:   PetscCall(TSRecoverRHSJacobian(ts, Arhs, Brhs));
4301:   PetscCall(TSComputeRHSJacobian(ts, t, U, Arhs, Brhs));
4302:   PetscCall(MatMult(Arhs, U, F));
4303:   PetscFunctionReturn(PETSC_SUCCESS);
4304: }

4306: /*@C
4307:    TSComputeRHSJacobianConstant - Reuses a Jacobian that is time-independent.

4309:    Collective

4311:    Input Parameters:
4312: +  ts - time stepping context
4313: .  t - time at which to evaluate
4314: .  U - state at which to evaluate
4315: -  ctx - context

4317:    Output Parameters:
4318: +  A - pointer to operator
4319: -  B - pointer to preconditioning matrix

4321:    Level: intermediate

4323:    Note:
4324:    This function is intended to be passed to `TSSetRHSJacobian()` to evaluate the Jacobian for linear time-independent problems.

4326: .seealso: [](chapter_ts), `TS`, `TSSetRHSFunction()`, `TSSetRHSJacobian()`, `TSComputeRHSFunctionLinear()`
4327: @*/
4328: PetscErrorCode TSComputeRHSJacobianConstant(TS ts, PetscReal t, Vec U, Mat A, Mat B, void *ctx)
4329: {
4330:   PetscFunctionBegin;
4331:   PetscFunctionReturn(PETSC_SUCCESS);
4332: }

4334: /*@C
4335:    TSComputeIFunctionLinear - Evaluate the left hand side via the user-provided Jacobian, for linear problems only

4337:    Collective

4339:    Input Parameters:
4340: +  ts - time stepping context
4341: .  t - time at which to evaluate
4342: .  U - state at which to evaluate
4343: .  Udot - time derivative of state vector
4344: -  ctx - context

4346:    Output Parameter:
4347: .  F - left hand side

4349:    Level: intermediate

4351:    Notes:
4352:    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
4353:    user is required to write their own `TSComputeIFunction()`.
4354:    This function is intended to be passed to `TSSetIFunction()` to evaluate the left hand side for linear problems.
4355:    The matrix (and optionally the evaluation context) should be passed to `TSSetIJacobian()`.

4357:    Note that using this function is NOT equivalent to using `TSComputeRHSFunctionLinear()` since that solves Udot = A U

4359: .seealso: [](chapter_ts), `TS`, `TSSetIFunction()`, `TSSetIJacobian()`, `TSComputeIJacobianConstant()`, `TSComputeRHSFunctionLinear()`
4360: @*/
4361: PetscErrorCode TSComputeIFunctionLinear(TS ts, PetscReal t, Vec U, Vec Udot, Vec F, void *ctx)
4362: {
4363:   Mat A, B;

4365:   PetscFunctionBegin;
4366:   PetscCall(TSGetIJacobian(ts, &A, &B, NULL, NULL));
4367:   PetscCall(TSComputeIJacobian(ts, t, U, Udot, 1.0, A, B, PETSC_TRUE));
4368:   PetscCall(MatMult(A, Udot, F));
4369:   PetscFunctionReturn(PETSC_SUCCESS);
4370: }

4372: /*@C
4373:    TSComputeIJacobianConstant - Reuses a time-independent for a semi-implicit DAE or ODE

4375:    Collective

4377:    Input Parameters:
4378: +  ts - time stepping context
4379: .  t - time at which to evaluate
4380: .  U - state at which to evaluate
4381: .  Udot - time derivative of state vector
4382: .  shift - shift to apply
4383: -  ctx - context

4385:    Output Parameters:
4386: +  A - pointer to operator
4387: -  B - pointer to preconditioning matrix

4389:    Level: advanced

4391:    Notes:
4392:    This function is intended to be passed to `TSSetIJacobian()` to evaluate the Jacobian for linear time-independent problems.

4394:    It is only appropriate for problems of the form

4396: $     M Udot = F(U,t)

4398:   where M is constant and F is non-stiff.  The user must pass M to `TSSetIJacobian()`.  The current implementation only
4399:   works with IMEX time integration methods such as `TSROSW` and `TSARKIMEX`, since there is no support for de-constructing
4400:   an implicit operator of the form

4402: $    shift*M + J

4404:   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
4405:   a copy of M or reassemble it when requested.

4407: .seealso: [](chapter_ts), `TS`, `TSROSW`, `TSARKIMEX`, `TSSetIFunction()`, `TSSetIJacobian()`, `TSComputeIFunctionLinear()`
4408: @*/
4409: PetscErrorCode TSComputeIJacobianConstant(TS ts, PetscReal t, Vec U, Vec Udot, PetscReal shift, Mat A, Mat B, void *ctx)
4410: {
4411:   PetscFunctionBegin;
4412:   PetscCall(MatScale(A, shift / ts->ijacobian.shift));
4413:   ts->ijacobian.shift = shift;
4414:   PetscFunctionReturn(PETSC_SUCCESS);
4415: }

4417: /*@
4418:    TSGetEquationType - Gets the type of the equation that `TS` is solving.

4420:    Not Collective

4422:    Input Parameter:
4423: .  ts - the `TS` context

4425:    Output Parameter:
4426: .  equation_type - see `TSEquationType`

4428:    Level: beginner

4430: .seealso: [](chapter_ts), `TS`, `TSSetEquationType()`, `TSEquationType`
4431: @*/
4432: PetscErrorCode TSGetEquationType(TS ts, TSEquationType *equation_type)
4433: {
4434:   PetscFunctionBegin;
4437:   *equation_type = ts->equation_type;
4438:   PetscFunctionReturn(PETSC_SUCCESS);
4439: }

4441: /*@
4442:    TSSetEquationType - Sets the type of the equation that `TS` is solving.

4444:    Not Collective

4446:    Input Parameters:
4447: +  ts - the `TS` context
4448: -  equation_type - see `TSEquationType`

4450:    Level: advanced

4452: .seealso: [](chapter_ts), `TS`, `TSGetEquationType()`, `TSEquationType`
4453: @*/
4454: PetscErrorCode TSSetEquationType(TS ts, TSEquationType equation_type)
4455: {
4456:   PetscFunctionBegin;
4458:   ts->equation_type = equation_type;
4459:   PetscFunctionReturn(PETSC_SUCCESS);
4460: }

4462: /*@
4463:    TSGetConvergedReason - Gets the reason the `TS` iteration was stopped.

4465:    Not Collective

4467:    Input Parameter:
4468: .  ts - the `TS` context

4470:    Output Parameter:
4471: .  reason - negative value indicates diverged, positive value converged, see `TSConvergedReason` or the
4472:             manual pages for the individual convergence tests for complete lists

4474:    Level: beginner

4476:    Note:
4477:    Can only be called after the call to `TSSolve()` is complete.

4479: .seealso: [](chapter_ts), `TS`, `TSSolve()`, `TSSetConvergenceTest()`, `TSConvergedReason`
4480: @*/
4481: PetscErrorCode TSGetConvergedReason(TS ts, TSConvergedReason *reason)
4482: {
4483:   PetscFunctionBegin;
4486:   *reason = ts->reason;
4487:   PetscFunctionReturn(PETSC_SUCCESS);
4488: }

4490: /*@
4491:    TSSetConvergedReason - Sets the reason for handling the convergence of `TSSolve()`.

4493:    Logically Collective; reason must contain common value

4495:    Input Parameters:
4496: +  ts - the `TS` context
4497: -  reason - negative value indicates diverged, positive value converged, see `TSConvergedReason` or the
4498:             manual pages for the individual convergence tests for complete lists

4500:    Level: advanced

4502:    Note:
4503:    Can only be called while `TSSolve()` is active.

4505: .seealso: [](chapter_ts), `TS`, `TSSolve()`, `TSConvergedReason`
4506: @*/
4507: PetscErrorCode TSSetConvergedReason(TS ts, TSConvergedReason reason)
4508: {
4509:   PetscFunctionBegin;
4511:   ts->reason = reason;
4512:   PetscFunctionReturn(PETSC_SUCCESS);
4513: }

4515: /*@
4516:    TSGetSolveTime - Gets the time after a call to `TSSolve()`

4518:    Not Collective

4520:    Input Parameter:
4521: .  ts - the `TS` context

4523:    Output Parameter:
4524: .  ftime - the final time. This time corresponds to the final time set with `TSSetMaxTime()`

4526:    Level: beginner

4528:    Note:
4529:    Can only be called after the call to `TSSolve()` is complete.

4531: .seealso: [](chapter_ts), `TS`, `TSSolve()`, `TSSetConvergenceTest()`, `TSConvergedReason`
4532: @*/
4533: PetscErrorCode TSGetSolveTime(TS ts, PetscReal *ftime)
4534: {
4535:   PetscFunctionBegin;
4538:   *ftime = ts->solvetime;
4539:   PetscFunctionReturn(PETSC_SUCCESS);
4540: }

4542: /*@
4543:    TSGetSNESIterations - Gets the total number of nonlinear iterations
4544:    used by the time integrator.

4546:    Not Collective

4548:    Input Parameter:
4549: .  ts - `TS` context

4551:    Output Parameter:
4552: .  nits - number of nonlinear iterations

4554:    Level: intermediate

4556:    Note:
4557:    This counter is reset to zero for each successive call to `TSSolve()`.

4559: .seealso: [](chapter_ts), `TS`, `TSSolve()`, `TSGetKSPIterations()`
4560: @*/
4561: PetscErrorCode TSGetSNESIterations(TS ts, PetscInt *nits)
4562: {
4563:   PetscFunctionBegin;
4566:   *nits = ts->snes_its;
4567:   PetscFunctionReturn(PETSC_SUCCESS);
4568: }

4570: /*@
4571:    TSGetKSPIterations - Gets the total number of linear iterations
4572:    used by the time integrator.

4574:    Not Collective

4576:    Input Parameter:
4577: .  ts - `TS` context

4579:    Output Parameter:
4580: .  lits - number of linear iterations

4582:    Level: intermediate

4584:    Note:
4585:    This counter is reset to zero for each successive call to `TSSolve()`.

4587: .seealso: [](chapter_ts), `TS`, `TSSolve()`, `TSGetSNESIterations()`, `SNESGetKSPIterations()`
4588: @*/
4589: PetscErrorCode TSGetKSPIterations(TS ts, PetscInt *lits)
4590: {
4591:   PetscFunctionBegin;
4594:   *lits = ts->ksp_its;
4595:   PetscFunctionReturn(PETSC_SUCCESS);
4596: }

4598: /*@
4599:    TSGetStepRejections - Gets the total number of rejected steps.

4601:    Not Collective

4603:    Input Parameter:
4604: .  ts - `TS` context

4606:    Output Parameter:
4607: .  rejects - number of steps rejected

4609:    Level: intermediate

4611:    Note:
4612:    This counter is reset to zero for each successive call to `TSSolve()`.

4614: .seealso: [](chapter_ts), `TS`, `TSSolve()`, `TSGetSNESIterations()`, `TSGetKSPIterations()`, `TSSetMaxStepRejections()`, `TSGetSNESFailures()`, `TSSetMaxSNESFailures()`, `TSSetErrorIfStepFails()`
4615: @*/
4616: PetscErrorCode TSGetStepRejections(TS ts, PetscInt *rejects)
4617: {
4618:   PetscFunctionBegin;
4621:   *rejects = ts->reject;
4622:   PetscFunctionReturn(PETSC_SUCCESS);
4623: }

4625: /*@
4626:    TSGetSNESFailures - Gets the total number of failed `SNES` solves in a `TS`

4628:    Not Collective

4630:    Input Parameter:
4631: .  ts - `TS` context

4633:    Output Parameter:
4634: .  fails - number of failed nonlinear solves

4636:    Level: intermediate

4638:    Note:
4639:    This counter is reset to zero for each successive call to `TSSolve()`.

4641: .seealso: [](chapter_ts), `TS`, `TSSolve()`, `TSGetSNESIterations()`, `TSGetKSPIterations()`, `TSSetMaxStepRejections()`, `TSGetStepRejections()`, `TSSetMaxSNESFailures()`
4642: @*/
4643: PetscErrorCode TSGetSNESFailures(TS ts, PetscInt *fails)
4644: {
4645:   PetscFunctionBegin;
4648:   *fails = ts->num_snes_failures;
4649:   PetscFunctionReturn(PETSC_SUCCESS);
4650: }

4652: /*@
4653:    TSSetMaxStepRejections - Sets the maximum number of step rejections before a time step fails

4655:    Not Collective

4657:    Input Parameters:
4658: +  ts - `TS` context
4659: -  rejects - maximum number of rejected steps, pass -1 for unlimited

4661:    Options Database Key:
4662: .  -ts_max_reject - Maximum number of step rejections before a step fails

4664:    Level: intermediate

4666: .seealso: [](chapter_ts), `TS`, `SNES`, `TSGetSNESIterations()`, `TSGetKSPIterations()`, `TSSetMaxSNESFailures()`, `TSGetStepRejections()`, `TSGetSNESFailures()`, `TSSetErrorIfStepFails()`, `TSGetConvergedReason()`
4667: @*/
4668: PetscErrorCode TSSetMaxStepRejections(TS ts, PetscInt rejects)
4669: {
4670:   PetscFunctionBegin;
4672:   ts->max_reject = rejects;
4673:   PetscFunctionReturn(PETSC_SUCCESS);
4674: }

4676: /*@
4677:    TSSetMaxSNESFailures - Sets the maximum number of failed `SNES` solves

4679:    Not Collective

4681:    Input Parameters:
4682: +  ts - `TS` context
4683: -  fails - maximum number of failed nonlinear solves, pass -1 for unlimited

4685:    Options Database Key:
4686: .  -ts_max_snes_failures - Maximum number of nonlinear solve failures

4688:    Level: intermediate

4690: .seealso: [](chapter_ts), `TS`, `SNES`, `TSGetSNESIterations()`, `TSGetKSPIterations()`, `TSSetMaxStepRejections()`, `TSGetStepRejections()`, `TSGetSNESFailures()`, `SNESGetConvergedReason()`, `TSGetConvergedReason()`
4691: @*/
4692: PetscErrorCode TSSetMaxSNESFailures(TS ts, PetscInt fails)
4693: {
4694:   PetscFunctionBegin;
4696:   ts->max_snes_failures = fails;
4697:   PetscFunctionReturn(PETSC_SUCCESS);
4698: }

4700: /*@
4701:    TSSetErrorIfStepFails - Immediately error if no step succeeds during `TSSolve()`

4703:    Not Collective

4705:    Input Parameters:
4706: +  ts - `TS` context
4707: -  err - `PETSC_TRUE` to error if no step succeeds, `PETSC_FALSE` to return without failure

4709:    Options Database Key:
4710: .  -ts_error_if_step_fails - Error if no step succeeds

4712:    Level: intermediate

4714: .seealso: [](chapter_ts), `TS`, `TSGetSNESIterations()`, `TSGetKSPIterations()`, `TSSetMaxStepRejections()`, `TSGetStepRejections()`, `TSGetSNESFailures()`, `TSSetErrorIfStepFails()`, `TSGetConvergedReason()`
4715: @*/
4716: PetscErrorCode TSSetErrorIfStepFails(TS ts, PetscBool err)
4717: {
4718:   PetscFunctionBegin;
4720:   ts->errorifstepfailed = err;
4721:   PetscFunctionReturn(PETSC_SUCCESS);
4722: }

4724: /*@
4725:    TSGetAdapt - Get the adaptive controller context for the current method

4727:    Collective on `ts` if controller has not been created yet

4729:    Input Parameter:
4730: .  ts - time stepping context

4732:    Output Parameter:
4733: .  adapt - adaptive controller

4735:    Level: intermediate

4737: .seealso: [](chapter_ts), `TS`, `TSAdapt`, `TSAdaptSetType()`, `TSAdaptChoose()`
4738: @*/
4739: PetscErrorCode TSGetAdapt(TS ts, TSAdapt *adapt)
4740: {
4741:   PetscFunctionBegin;
4744:   if (!ts->adapt) {
4745:     PetscCall(TSAdaptCreate(PetscObjectComm((PetscObject)ts), &ts->adapt));
4746:     PetscCall(PetscObjectIncrementTabLevel((PetscObject)ts->adapt, (PetscObject)ts, 1));
4747:   }
4748:   *adapt = ts->adapt;
4749:   PetscFunctionReturn(PETSC_SUCCESS);
4750: }

4752: /*@
4753:    TSSetTolerances - Set tolerances for local truncation error when using an adaptive controller

4755:    Logically Collective

4757:    Input Parameters:
4758: +  ts - time integration context
4759: .  atol - scalar absolute tolerances, `PETSC_DECIDE` to leave current value
4760: .  vatol - vector of absolute tolerances or `NULL`, used in preference to atol if present
4761: .  rtol - scalar relative tolerances, `PETSC_DECIDE` to leave current value
4762: -  vrtol - vector of relative tolerances or `NULL`, used in preference to atol if present

4764:    Options Database Keys:
4765: +  -ts_rtol <rtol> - relative tolerance for local truncation error
4766: -  -ts_atol <atol> - Absolute tolerance for local truncation error

4768:    Level: beginner

4770:    Notes:
4771:    With PETSc's implicit schemes for DAE problems, the calculation of the local truncation error
4772:    (LTE) includes both the differential and the algebraic variables. If one wants the LTE to be
4773:    computed only for the differential or the algebraic part then this can be done using the vector of
4774:    tolerances vatol. For example, by setting the tolerance vector with the desired tolerance for the
4775:    differential part and infinity for the algebraic part, the LTE calculation will include only the
4776:    differential variables.

4778: .seealso: [](chapter_ts), `TS`, `TSAdapt`, `TSErrorWeightedNorm()`, `TSGetTolerances()`
4779: @*/
4780: PetscErrorCode TSSetTolerances(TS ts, PetscReal atol, Vec vatol, PetscReal rtol, Vec vrtol)
4781: {
4782:   PetscFunctionBegin;
4783:   if (atol != PETSC_DECIDE && atol != PETSC_DEFAULT) ts->atol = atol;
4784:   if (vatol) {
4785:     PetscCall(PetscObjectReference((PetscObject)vatol));
4786:     PetscCall(VecDestroy(&ts->vatol));
4787:     ts->vatol = vatol;
4788:   }
4789:   if (rtol != PETSC_DECIDE && rtol != PETSC_DEFAULT) ts->rtol = rtol;
4790:   if (vrtol) {
4791:     PetscCall(PetscObjectReference((PetscObject)vrtol));
4792:     PetscCall(VecDestroy(&ts->vrtol));
4793:     ts->vrtol = vrtol;
4794:   }
4795:   PetscFunctionReturn(PETSC_SUCCESS);
4796: }

4798: /*@
4799:    TSGetTolerances - Get tolerances for local truncation error when using adaptive controller

4801:    Logically Collective

4803:    Input Parameter:
4804: .  ts - time integration context

4806:    Output Parameters:
4807: +  atol - scalar absolute tolerances, `NULL` to ignore
4808: .  vatol - vector of absolute tolerances, `NULL` to ignore
4809: .  rtol - scalar relative tolerances, `NULL` to ignore
4810: -  vrtol - vector of relative tolerances, `NULL` to ignore

4812:    Level: beginner

4814: .seealso: [](chapter_ts), `TS`, `TSAdapt`, `TSErrorWeightedNorm()`, `TSSetTolerances()`
4815: @*/
4816: PetscErrorCode TSGetTolerances(TS ts, PetscReal *atol, Vec *vatol, PetscReal *rtol, Vec *vrtol)
4817: {
4818:   PetscFunctionBegin;
4819:   if (atol) *atol = ts->atol;
4820:   if (vatol) *vatol = ts->vatol;
4821:   if (rtol) *rtol = ts->rtol;
4822:   if (vrtol) *vrtol = ts->vrtol;
4823:   PetscFunctionReturn(PETSC_SUCCESS);
4824: }

4826: /*@
4827:    TSErrorWeightedNorm2 - compute a weighted 2-norm of the difference between two state vectors

4829:    Collective

4831:    Input Parameters:
4832: +  ts - time stepping context
4833: .  U - state vector, usually ts->vec_sol
4834: -  Y - state vector to be compared to U

4836:    Output Parameters:
4837: +  norm - weighted norm, a value of 1.0 means that the error matches the tolerances
4838: .  norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances
4839: -  normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances

4841:    Level: developer

4843: .seealso: [](chapter_ts), `TS`, `TSErrorWeightedNorm()`, `TSErrorWeightedNormInfinity()`
4844: @*/
4845: PetscErrorCode TSErrorWeightedNorm2(TS ts, Vec U, Vec Y, PetscReal *norm, PetscReal *norma, PetscReal *normr)
4846: {
4847:   PetscInt           i, n, N, rstart;
4848:   PetscInt           n_loc, na_loc, nr_loc;
4849:   PetscReal          n_glb, na_glb, nr_glb;
4850:   const PetscScalar *u, *y;
4851:   PetscReal          sum, suma, sumr, gsum, gsuma, gsumr, diff;
4852:   PetscReal          tol, tola, tolr;
4853:   PetscReal          err_loc[6], err_glb[6];

4855:   PetscFunctionBegin;
4861:   PetscCheckSameComm(U, 2, Y, 3);
4865:   PetscCheck(U != Y, PetscObjectComm((PetscObject)U), PETSC_ERR_ARG_IDN, "U and Y cannot be the same vector");

4867:   PetscCall(VecGetSize(U, &N));
4868:   PetscCall(VecGetLocalSize(U, &n));
4869:   PetscCall(VecGetOwnershipRange(U, &rstart, NULL));
4870:   PetscCall(VecGetArrayRead(U, &u));
4871:   PetscCall(VecGetArrayRead(Y, &y));
4872:   sum    = 0.;
4873:   n_loc  = 0;
4874:   suma   = 0.;
4875:   na_loc = 0;
4876:   sumr   = 0.;
4877:   nr_loc = 0;
4878:   if (ts->vatol && ts->vrtol) {
4879:     const PetscScalar *atol, *rtol;
4880:     PetscCall(VecGetArrayRead(ts->vatol, &atol));
4881:     PetscCall(VecGetArrayRead(ts->vrtol, &rtol));
4882:     for (i = 0; i < n; i++) {
4883:       SkipSmallValue(y[i], u[i], ts->adapt->ignore_max);
4884:       diff = PetscAbsScalar(y[i] - u[i]);
4885:       tola = PetscRealPart(atol[i]);
4886:       if (tola > 0.) {
4887:         suma += PetscSqr(diff / tola);
4888:         na_loc++;
4889:       }
4890:       tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]), PetscAbsScalar(y[i]));
4891:       if (tolr > 0.) {
4892:         sumr += PetscSqr(diff / tolr);
4893:         nr_loc++;
4894:       }
4895:       tol = tola + tolr;
4896:       if (tol > 0.) {
4897:         sum += PetscSqr(diff / tol);
4898:         n_loc++;
4899:       }
4900:     }
4901:     PetscCall(VecRestoreArrayRead(ts->vatol, &atol));
4902:     PetscCall(VecRestoreArrayRead(ts->vrtol, &rtol));
4903:   } else if (ts->vatol) { /* vector atol, scalar rtol */
4904:     const PetscScalar *atol;
4905:     PetscCall(VecGetArrayRead(ts->vatol, &atol));
4906:     for (i = 0; i < n; i++) {
4907:       SkipSmallValue(y[i], u[i], ts->adapt->ignore_max);
4908:       diff = PetscAbsScalar(y[i] - u[i]);
4909:       tola = PetscRealPart(atol[i]);
4910:       if (tola > 0.) {
4911:         suma += PetscSqr(diff / tola);
4912:         na_loc++;
4913:       }
4914:       tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]), PetscAbsScalar(y[i]));
4915:       if (tolr > 0.) {
4916:         sumr += PetscSqr(diff / tolr);
4917:         nr_loc++;
4918:       }
4919:       tol = tola + tolr;
4920:       if (tol > 0.) {
4921:         sum += PetscSqr(diff / tol);
4922:         n_loc++;
4923:       }
4924:     }
4925:     PetscCall(VecRestoreArrayRead(ts->vatol, &atol));
4926:   } else if (ts->vrtol) { /* scalar atol, vector rtol */
4927:     const PetscScalar *rtol;
4928:     PetscCall(VecGetArrayRead(ts->vrtol, &rtol));
4929:     for (i = 0; i < n; i++) {
4930:       SkipSmallValue(y[i], u[i], ts->adapt->ignore_max);
4931:       diff = PetscAbsScalar(y[i] - u[i]);
4932:       tola = ts->atol;
4933:       if (tola > 0.) {
4934:         suma += PetscSqr(diff / tola);
4935:         na_loc++;
4936:       }
4937:       tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]), PetscAbsScalar(y[i]));
4938:       if (tolr > 0.) {
4939:         sumr += PetscSqr(diff / tolr);
4940:         nr_loc++;
4941:       }
4942:       tol = tola + tolr;
4943:       if (tol > 0.) {
4944:         sum += PetscSqr(diff / tol);
4945:         n_loc++;
4946:       }
4947:     }
4948:     PetscCall(VecRestoreArrayRead(ts->vrtol, &rtol));
4949:   } else { /* scalar atol, scalar rtol */
4950:     for (i = 0; i < n; i++) {
4951:       SkipSmallValue(y[i], u[i], ts->adapt->ignore_max);
4952:       diff = PetscAbsScalar(y[i] - u[i]);
4953:       tola = ts->atol;
4954:       if (tola > 0.) {
4955:         suma += PetscSqr(diff / tola);
4956:         na_loc++;
4957:       }
4958:       tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]), PetscAbsScalar(y[i]));
4959:       if (tolr > 0.) {
4960:         sumr += PetscSqr(diff / tolr);
4961:         nr_loc++;
4962:       }
4963:       tol = tola + tolr;
4964:       if (tol > 0.) {
4965:         sum += PetscSqr(diff / tol);
4966:         n_loc++;
4967:       }
4968:     }
4969:   }
4970:   PetscCall(VecRestoreArrayRead(U, &u));
4971:   PetscCall(VecRestoreArrayRead(Y, &y));

4973:   err_loc[0] = sum;
4974:   err_loc[1] = suma;
4975:   err_loc[2] = sumr;
4976:   err_loc[3] = (PetscReal)n_loc;
4977:   err_loc[4] = (PetscReal)na_loc;
4978:   err_loc[5] = (PetscReal)nr_loc;

4980:   PetscCall(MPIU_Allreduce(err_loc, err_glb, 6, MPIU_REAL, MPIU_SUM, PetscObjectComm((PetscObject)ts)));

4982:   gsum   = err_glb[0];
4983:   gsuma  = err_glb[1];
4984:   gsumr  = err_glb[2];
4985:   n_glb  = err_glb[3];
4986:   na_glb = err_glb[4];
4987:   nr_glb = err_glb[5];

4989:   *norm = 0.;
4990:   if (n_glb > 0.) *norm = PetscSqrtReal(gsum / n_glb);
4991:   *norma = 0.;
4992:   if (na_glb > 0.) *norma = PetscSqrtReal(gsuma / na_glb);
4993:   *normr = 0.;
4994:   if (nr_glb > 0.) *normr = PetscSqrtReal(gsumr / nr_glb);

4996:   PetscCheck(!PetscIsInfOrNanScalar(*norm), PetscObjectComm((PetscObject)ts), PETSC_ERR_FP, "Infinite or not-a-number generated in norm");
4997:   PetscCheck(!PetscIsInfOrNanScalar(*norma), PetscObjectComm((PetscObject)ts), PETSC_ERR_FP, "Infinite or not-a-number generated in norma");
4998:   PetscCheck(!PetscIsInfOrNanScalar(*normr), PetscObjectComm((PetscObject)ts), PETSC_ERR_FP, "Infinite or not-a-number generated in normr");
4999:   PetscFunctionReturn(PETSC_SUCCESS);
5000: }

5002: /*@
5003:    TSErrorWeightedNormInfinity - compute a weighted infinity-norm of the difference between two state vectors

5005:    Collective

5007:    Input Parameters:
5008: +  ts - time stepping context
5009: .  U - state vector, usually ts->vec_sol
5010: -  Y - state vector to be compared to U

5012:    Output Parameters:
5013: +  norm - weighted norm, a value of 1.0 means that the error matches the tolerances
5014: .  norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances
5015: -  normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances

5017:    Level: developer

5019: .seealso: [](chapter_ts), `TS`, `TSErrorWeightedNorm()`, `TSErrorWeightedNorm2()`
5020: @*/
5021: PetscErrorCode TSErrorWeightedNormInfinity(TS ts, Vec U, Vec Y, PetscReal *norm, PetscReal *norma, PetscReal *normr)
5022: {
5023:   PetscInt           i, n, N, rstart;
5024:   const PetscScalar *u, *y;
5025:   PetscReal          max, gmax, maxa, gmaxa, maxr, gmaxr;
5026:   PetscReal          tol, tola, tolr, diff;
5027:   PetscReal          err_loc[3], err_glb[3];

5029:   PetscFunctionBegin;
5035:   PetscCheckSameComm(U, 2, Y, 3);
5039:   PetscCheck(U != Y, PetscObjectComm((PetscObject)U), PETSC_ERR_ARG_IDN, "U and Y cannot be the same vector");

5041:   PetscCall(VecGetSize(U, &N));
5042:   PetscCall(VecGetLocalSize(U, &n));
5043:   PetscCall(VecGetOwnershipRange(U, &rstart, NULL));
5044:   PetscCall(VecGetArrayRead(U, &u));
5045:   PetscCall(VecGetArrayRead(Y, &y));

5047:   max  = 0.;
5048:   maxa = 0.;
5049:   maxr = 0.;

5051:   if (ts->vatol && ts->vrtol) { /* vector atol, vector rtol */
5052:     const PetscScalar *atol, *rtol;
5053:     PetscCall(VecGetArrayRead(ts->vatol, &atol));
5054:     PetscCall(VecGetArrayRead(ts->vrtol, &rtol));

5056:     for (i = 0; i < n; i++) {
5057:       SkipSmallValue(y[i], u[i], ts->adapt->ignore_max);
5058:       diff = PetscAbsScalar(y[i] - u[i]);
5059:       tola = PetscRealPart(atol[i]);
5060:       tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]), PetscAbsScalar(y[i]));
5061:       tol  = tola + tolr;
5062:       if (tola > 0.) maxa = PetscMax(maxa, diff / tola);
5063:       if (tolr > 0.) maxr = PetscMax(maxr, diff / tolr);
5064:       if (tol > 0.) max = PetscMax(max, diff / tol);
5065:     }
5066:     PetscCall(VecRestoreArrayRead(ts->vatol, &atol));
5067:     PetscCall(VecRestoreArrayRead(ts->vrtol, &rtol));
5068:   } else if (ts->vatol) { /* vector atol, scalar rtol */
5069:     const PetscScalar *atol;
5070:     PetscCall(VecGetArrayRead(ts->vatol, &atol));
5071:     for (i = 0; i < n; i++) {
5072:       SkipSmallValue(y[i], u[i], ts->adapt->ignore_max);
5073:       diff = PetscAbsScalar(y[i] - u[i]);
5074:       tola = PetscRealPart(atol[i]);
5075:       tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]), PetscAbsScalar(y[i]));
5076:       tol  = tola + tolr;
5077:       if (tola > 0.) maxa = PetscMax(maxa, diff / tola);
5078:       if (tolr > 0.) maxr = PetscMax(maxr, diff / tolr);
5079:       if (tol > 0.) max = PetscMax(max, diff / tol);
5080:     }
5081:     PetscCall(VecRestoreArrayRead(ts->vatol, &atol));
5082:   } else if (ts->vrtol) { /* scalar atol, vector rtol */
5083:     const PetscScalar *rtol;
5084:     PetscCall(VecGetArrayRead(ts->vrtol, &rtol));

5086:     for (i = 0; i < n; i++) {
5087:       SkipSmallValue(y[i], u[i], ts->adapt->ignore_max);
5088:       diff = PetscAbsScalar(y[i] - u[i]);
5089:       tola = ts->atol;
5090:       tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]), PetscAbsScalar(y[i]));
5091:       tol  = tola + tolr;
5092:       if (tola > 0.) maxa = PetscMax(maxa, diff / tola);
5093:       if (tolr > 0.) maxr = PetscMax(maxr, diff / tolr);
5094:       if (tol > 0.) max = PetscMax(max, diff / tol);
5095:     }
5096:     PetscCall(VecRestoreArrayRead(ts->vrtol, &rtol));
5097:   } else { /* scalar atol, scalar rtol */

5099:     for (i = 0; i < n; i++) {
5100:       SkipSmallValue(y[i], u[i], ts->adapt->ignore_max);
5101:       diff = PetscAbsScalar(y[i] - u[i]);
5102:       tola = ts->atol;
5103:       tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]), PetscAbsScalar(y[i]));
5104:       tol  = tola + tolr;
5105:       if (tola > 0.) maxa = PetscMax(maxa, diff / tola);
5106:       if (tolr > 0.) maxr = PetscMax(maxr, diff / tolr);
5107:       if (tol > 0.) max = PetscMax(max, diff / tol);
5108:     }
5109:   }
5110:   PetscCall(VecRestoreArrayRead(U, &u));
5111:   PetscCall(VecRestoreArrayRead(Y, &y));
5112:   err_loc[0] = max;
5113:   err_loc[1] = maxa;
5114:   err_loc[2] = maxr;
5115:   PetscCall(MPIU_Allreduce(err_loc, err_glb, 3, MPIU_REAL, MPIU_MAX, PetscObjectComm((PetscObject)ts)));
5116:   gmax  = err_glb[0];
5117:   gmaxa = err_glb[1];
5118:   gmaxr = err_glb[2];

5120:   *norm  = gmax;
5121:   *norma = gmaxa;
5122:   *normr = gmaxr;
5123:   PetscCheck(!PetscIsInfOrNanScalar(*norm), PetscObjectComm((PetscObject)ts), PETSC_ERR_FP, "Infinite or not-a-number generated in norm");
5124:   PetscCheck(!PetscIsInfOrNanScalar(*norma), PetscObjectComm((PetscObject)ts), PETSC_ERR_FP, "Infinite or not-a-number generated in norma");
5125:   PetscCheck(!PetscIsInfOrNanScalar(*normr), PetscObjectComm((PetscObject)ts), PETSC_ERR_FP, "Infinite or not-a-number generated in normr");
5126:   PetscFunctionReturn(PETSC_SUCCESS);
5127: }

5129: /*@
5130:    TSErrorWeightedNorm - compute a weighted norm of the difference between two state vectors based on supplied absolute and relative tolerances

5132:    Collective

5134:    Input Parameters:
5135: +  ts - time stepping context
5136: .  U - state vector, usually ts->vec_sol
5137: .  Y - state vector to be compared to U
5138: -  wnormtype - norm type, either `NORM_2` or `NORM_INFINITY`

5140:    Output Parameters:
5141: +  norm  - weighted norm, a value of 1.0 achieves a balance between absolute and relative tolerances
5142: .  norma - weighted norm, a value of 1.0 means that the error meets the absolute tolerance set by the user
5143: -  normr - weighted norm, a value of 1.0 means that the error meets the relative tolerance set by the user

5145:    Options Database Key:
5146: .  -ts_adapt_wnormtype <wnormtype> - 2, INFINITY

5148:    Level: developer

5150: .seealso: [](chapter_ts), `TS`, `TSErrorWeightedNormInfinity()`, `TSErrorWeightedNorm2()`, `TSErrorWeightedENorm`
5151: @*/
5152: PetscErrorCode TSErrorWeightedNorm(TS ts, Vec U, Vec Y, NormType wnormtype, PetscReal *norm, PetscReal *norma, PetscReal *normr)
5153: {
5154:   PetscFunctionBegin;
5155:   if (wnormtype == NORM_2) PetscCall(TSErrorWeightedNorm2(ts, U, Y, norm, norma, normr));
5156:   else if (wnormtype == NORM_INFINITY) PetscCall(TSErrorWeightedNormInfinity(ts, U, Y, norm, norma, normr));
5157:   else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "No support for norm type %s", NormTypes[wnormtype]);
5158:   PetscFunctionReturn(PETSC_SUCCESS);
5159: }

5161: /*@
5162:    TSErrorWeightedENorm2 - compute a weighted 2 error norm based on supplied absolute and relative tolerances

5164:    Collective

5166:    Input Parameters:
5167: +  ts - time stepping context
5168: .  E - error vector
5169: .  U - state vector, usually ts->vec_sol
5170: -  Y - state vector, previous time step

5172:    Output Parameters:
5173: +  norm - weighted norm, a value of 1.0 means that the error matches the tolerances
5174: .  norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances
5175: -  normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances

5177:    Level: developer

5179: .seealso: [](chapter_ts), `TS`, `TSErrorWeightedENorm()`, `TSErrorWeightedENormInfinity()`
5180: @*/
5181: PetscErrorCode TSErrorWeightedENorm2(TS ts, Vec E, Vec U, Vec Y, PetscReal *norm, PetscReal *norma, PetscReal *normr)
5182: {
5183:   PetscInt           i, n, N, rstart;
5184:   PetscInt           n_loc, na_loc, nr_loc;
5185:   PetscReal          n_glb, na_glb, nr_glb;
5186:   const PetscScalar *e, *u, *y;
5187:   PetscReal          err, sum, suma, sumr, gsum, gsuma, gsumr;
5188:   PetscReal          tol, tola, tolr;
5189:   PetscReal          err_loc[6], err_glb[6];

5191:   PetscFunctionBegin;
5199:   PetscCheckSameComm(E, 2, U, 3);
5200:   PetscCheckSameComm(U, 3, Y, 4);

5205:   PetscCall(VecGetSize(E, &N));
5206:   PetscCall(VecGetLocalSize(E, &n));
5207:   PetscCall(VecGetOwnershipRange(E, &rstart, NULL));
5208:   PetscCall(VecGetArrayRead(E, &e));
5209:   PetscCall(VecGetArrayRead(U, &u));
5210:   PetscCall(VecGetArrayRead(Y, &y));
5211:   sum    = 0.;
5212:   n_loc  = 0;
5213:   suma   = 0.;
5214:   na_loc = 0;
5215:   sumr   = 0.;
5216:   nr_loc = 0;
5217:   if (ts->vatol && ts->vrtol) {
5218:     const PetscScalar *atol, *rtol;
5219:     PetscCall(VecGetArrayRead(ts->vatol, &atol));
5220:     PetscCall(VecGetArrayRead(ts->vrtol, &rtol));
5221:     for (i = 0; i < n; i++) {
5222:       SkipSmallValue(y[i], u[i], ts->adapt->ignore_max);
5223:       err  = PetscAbsScalar(e[i]);
5224:       tola = PetscRealPart(atol[i]);
5225:       if (tola > 0.) {
5226:         suma += PetscSqr(err / tola);
5227:         na_loc++;
5228:       }
5229:       tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]), PetscAbsScalar(y[i]));
5230:       if (tolr > 0.) {
5231:         sumr += PetscSqr(err / tolr);
5232:         nr_loc++;
5233:       }
5234:       tol = tola + tolr;
5235:       if (tol > 0.) {
5236:         sum += PetscSqr(err / tol);
5237:         n_loc++;
5238:       }
5239:     }
5240:     PetscCall(VecRestoreArrayRead(ts->vatol, &atol));
5241:     PetscCall(VecRestoreArrayRead(ts->vrtol, &rtol));
5242:   } else if (ts->vatol) { /* vector atol, scalar rtol */
5243:     const PetscScalar *atol;
5244:     PetscCall(VecGetArrayRead(ts->vatol, &atol));
5245:     for (i = 0; i < n; i++) {
5246:       SkipSmallValue(y[i], u[i], ts->adapt->ignore_max);
5247:       err  = PetscAbsScalar(e[i]);
5248:       tola = PetscRealPart(atol[i]);
5249:       if (tola > 0.) {
5250:         suma += PetscSqr(err / tola);
5251:         na_loc++;
5252:       }
5253:       tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]), PetscAbsScalar(y[i]));
5254:       if (tolr > 0.) {
5255:         sumr += PetscSqr(err / tolr);
5256:         nr_loc++;
5257:       }
5258:       tol = tola + tolr;
5259:       if (tol > 0.) {
5260:         sum += PetscSqr(err / tol);
5261:         n_loc++;
5262:       }
5263:     }
5264:     PetscCall(VecRestoreArrayRead(ts->vatol, &atol));
5265:   } else if (ts->vrtol) { /* scalar atol, vector rtol */
5266:     const PetscScalar *rtol;
5267:     PetscCall(VecGetArrayRead(ts->vrtol, &rtol));
5268:     for (i = 0; i < n; i++) {
5269:       SkipSmallValue(y[i], u[i], ts->adapt->ignore_max);
5270:       err  = PetscAbsScalar(e[i]);
5271:       tola = ts->atol;
5272:       if (tola > 0.) {
5273:         suma += PetscSqr(err / tola);
5274:         na_loc++;
5275:       }
5276:       tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]), PetscAbsScalar(y[i]));
5277:       if (tolr > 0.) {
5278:         sumr += PetscSqr(err / tolr);
5279:         nr_loc++;
5280:       }
5281:       tol = tola + tolr;
5282:       if (tol > 0.) {
5283:         sum += PetscSqr(err / tol);
5284:         n_loc++;
5285:       }
5286:     }
5287:     PetscCall(VecRestoreArrayRead(ts->vrtol, &rtol));
5288:   } else { /* scalar atol, scalar rtol */
5289:     for (i = 0; i < n; i++) {
5290:       SkipSmallValue(y[i], u[i], ts->adapt->ignore_max);
5291:       err  = PetscAbsScalar(e[i]);
5292:       tola = ts->atol;
5293:       if (tola > 0.) {
5294:         suma += PetscSqr(err / tola);
5295:         na_loc++;
5296:       }
5297:       tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]), PetscAbsScalar(y[i]));
5298:       if (tolr > 0.) {
5299:         sumr += PetscSqr(err / tolr);
5300:         nr_loc++;
5301:       }
5302:       tol = tola + tolr;
5303:       if (tol > 0.) {
5304:         sum += PetscSqr(err / tol);
5305:         n_loc++;
5306:       }
5307:     }
5308:   }
5309:   PetscCall(VecRestoreArrayRead(E, &e));
5310:   PetscCall(VecRestoreArrayRead(U, &u));
5311:   PetscCall(VecRestoreArrayRead(Y, &y));

5313:   err_loc[0] = sum;
5314:   err_loc[1] = suma;
5315:   err_loc[2] = sumr;
5316:   err_loc[3] = (PetscReal)n_loc;
5317:   err_loc[4] = (PetscReal)na_loc;
5318:   err_loc[5] = (PetscReal)nr_loc;

5320:   PetscCall(MPIU_Allreduce(err_loc, err_glb, 6, MPIU_REAL, MPIU_SUM, PetscObjectComm((PetscObject)ts)));

5322:   gsum   = err_glb[0];
5323:   gsuma  = err_glb[1];
5324:   gsumr  = err_glb[2];
5325:   n_glb  = err_glb[3];
5326:   na_glb = err_glb[4];
5327:   nr_glb = err_glb[5];

5329:   *norm = 0.;
5330:   if (n_glb > 0.) *norm = PetscSqrtReal(gsum / n_glb);
5331:   *norma = 0.;
5332:   if (na_glb > 0.) *norma = PetscSqrtReal(gsuma / na_glb);
5333:   *normr = 0.;
5334:   if (nr_glb > 0.) *normr = PetscSqrtReal(gsumr / nr_glb);

5336:   PetscCheck(!PetscIsInfOrNanScalar(*norm), PetscObjectComm((PetscObject)ts), PETSC_ERR_FP, "Infinite or not-a-number generated in norm");
5337:   PetscCheck(!PetscIsInfOrNanScalar(*norma), PetscObjectComm((PetscObject)ts), PETSC_ERR_FP, "Infinite or not-a-number generated in norma");
5338:   PetscCheck(!PetscIsInfOrNanScalar(*normr), PetscObjectComm((PetscObject)ts), PETSC_ERR_FP, "Infinite or not-a-number generated in normr");
5339:   PetscFunctionReturn(PETSC_SUCCESS);
5340: }

5342: /*@
5343:    TSErrorWeightedENormInfinity - compute a weighted infinity error norm based on supplied absolute and relative tolerances

5345:    Collective

5347:    Input Parameters:
5348: +  ts - time stepping context
5349: .  E - error vector
5350: .  U - state vector, usually ts->vec_sol
5351: -  Y - state vector, previous time step

5353:    Output Parameters:
5354: +  norm - weighted norm, a value of 1.0 means that the error matches the tolerances
5355: .  norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances
5356: -  normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances

5358:    Level: developer

5360: .seealso: [](chapter_ts), `TS`, `TSErrorWeightedENorm()`, `TSErrorWeightedENorm2()`
5361: @*/
5362: PetscErrorCode TSErrorWeightedENormInfinity(TS ts, Vec E, Vec U, Vec Y, PetscReal *norm, PetscReal *norma, PetscReal *normr)
5363: {
5364:   PetscInt           i, n, N, rstart;
5365:   const PetscScalar *e, *u, *y;
5366:   PetscReal          err, max, gmax, maxa, gmaxa, maxr, gmaxr;
5367:   PetscReal          tol, tola, tolr;
5368:   PetscReal          err_loc[3], err_glb[3];

5370:   PetscFunctionBegin;
5378:   PetscCheckSameComm(E, 2, U, 3);
5379:   PetscCheckSameComm(U, 3, Y, 4);

5384:   PetscCall(VecGetSize(E, &N));
5385:   PetscCall(VecGetLocalSize(E, &n));
5386:   PetscCall(VecGetOwnershipRange(E, &rstart, NULL));
5387:   PetscCall(VecGetArrayRead(E, &e));
5388:   PetscCall(VecGetArrayRead(U, &u));
5389:   PetscCall(VecGetArrayRead(Y, &y));

5391:   max  = 0.;
5392:   maxa = 0.;
5393:   maxr = 0.;

5395:   if (ts->vatol && ts->vrtol) { /* vector atol, vector rtol */
5396:     const PetscScalar *atol, *rtol;
5397:     PetscCall(VecGetArrayRead(ts->vatol, &atol));
5398:     PetscCall(VecGetArrayRead(ts->vrtol, &rtol));

5400:     for (i = 0; i < n; i++) {
5401:       SkipSmallValue(y[i], u[i], ts->adapt->ignore_max);
5402:       err  = PetscAbsScalar(e[i]);
5403:       tola = PetscRealPart(atol[i]);
5404:       tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]), PetscAbsScalar(y[i]));
5405:       tol  = tola + tolr;
5406:       if (tola > 0.) maxa = PetscMax(maxa, err / tola);
5407:       if (tolr > 0.) maxr = PetscMax(maxr, err / tolr);
5408:       if (tol > 0.) max = PetscMax(max, err / tol);
5409:     }
5410:     PetscCall(VecRestoreArrayRead(ts->vatol, &atol));
5411:     PetscCall(VecRestoreArrayRead(ts->vrtol, &rtol));
5412:   } else if (ts->vatol) { /* vector atol, scalar rtol */
5413:     const PetscScalar *atol;
5414:     PetscCall(VecGetArrayRead(ts->vatol, &atol));
5415:     for (i = 0; i < n; i++) {
5416:       SkipSmallValue(y[i], u[i], ts->adapt->ignore_max);
5417:       err  = PetscAbsScalar(e[i]);
5418:       tola = PetscRealPart(atol[i]);
5419:       tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]), PetscAbsScalar(y[i]));
5420:       tol  = tola + tolr;
5421:       if (tola > 0.) maxa = PetscMax(maxa, err / tola);
5422:       if (tolr > 0.) maxr = PetscMax(maxr, err / tolr);
5423:       if (tol > 0.) max = PetscMax(max, err / tol);
5424:     }
5425:     PetscCall(VecRestoreArrayRead(ts->vatol, &atol));
5426:   } else if (ts->vrtol) { /* scalar atol, vector rtol */
5427:     const PetscScalar *rtol;
5428:     PetscCall(VecGetArrayRead(ts->vrtol, &rtol));

5430:     for (i = 0; i < n; i++) {
5431:       SkipSmallValue(y[i], u[i], ts->adapt->ignore_max);
5432:       err  = PetscAbsScalar(e[i]);
5433:       tola = ts->atol;
5434:       tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]), PetscAbsScalar(y[i]));
5435:       tol  = tola + tolr;
5436:       if (tola > 0.) maxa = PetscMax(maxa, err / tola);
5437:       if (tolr > 0.) maxr = PetscMax(maxr, err / tolr);
5438:       if (tol > 0.) max = PetscMax(max, err / tol);
5439:     }
5440:     PetscCall(VecRestoreArrayRead(ts->vrtol, &rtol));
5441:   } else { /* scalar atol, scalar rtol */

5443:     for (i = 0; i < n; i++) {
5444:       SkipSmallValue(y[i], u[i], ts->adapt->ignore_max);
5445:       err  = PetscAbsScalar(e[i]);
5446:       tola = ts->atol;
5447:       tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]), PetscAbsScalar(y[i]));
5448:       tol  = tola + tolr;
5449:       if (tola > 0.) maxa = PetscMax(maxa, err / tola);
5450:       if (tolr > 0.) maxr = PetscMax(maxr, err / tolr);
5451:       if (tol > 0.) max = PetscMax(max, err / tol);
5452:     }
5453:   }
5454:   PetscCall(VecRestoreArrayRead(E, &e));
5455:   PetscCall(VecRestoreArrayRead(U, &u));
5456:   PetscCall(VecRestoreArrayRead(Y, &y));
5457:   err_loc[0] = max;
5458:   err_loc[1] = maxa;
5459:   err_loc[2] = maxr;
5460:   PetscCall(MPIU_Allreduce(err_loc, err_glb, 3, MPIU_REAL, MPIU_MAX, PetscObjectComm((PetscObject)ts)));
5461:   gmax  = err_glb[0];
5462:   gmaxa = err_glb[1];
5463:   gmaxr = err_glb[2];

5465:   *norm  = gmax;
5466:   *norma = gmaxa;
5467:   *normr = gmaxr;
5468:   PetscCheck(!PetscIsInfOrNanScalar(*norm), PetscObjectComm((PetscObject)ts), PETSC_ERR_FP, "Infinite or not-a-number generated in norm");
5469:   PetscCheck(!PetscIsInfOrNanScalar(*norma), PetscObjectComm((PetscObject)ts), PETSC_ERR_FP, "Infinite or not-a-number generated in norma");
5470:   PetscCheck(!PetscIsInfOrNanScalar(*normr), PetscObjectComm((PetscObject)ts), PETSC_ERR_FP, "Infinite or not-a-number generated in normr");
5471:   PetscFunctionReturn(PETSC_SUCCESS);
5472: }

5474: /*@
5475:    TSErrorWeightedENorm - compute a weighted error norm based on supplied absolute and relative tolerances

5477:    Collective

5479:    Input Parameters:
5480: +  ts - time stepping context
5481: .  E - error vector
5482: .  U - state vector, usually ts->vec_sol
5483: .  Y - state vector, previous time step
5484: -  wnormtype - norm type, either `NORM_2` or `NORM_INFINITY`

5486:    Output Parameters:
5487: +  norm  - weighted norm, a value of 1.0 achieves a balance between absolute and relative tolerances
5488: .  norma - weighted norm, a value of 1.0 means that the error meets the absolute tolerance set by the user
5489: -  normr - weighted norm, a value of 1.0 means that the error meets the relative tolerance set by the user

5491:    Options Database Key:
5492: .  -ts_adapt_wnormtype <wnormtype> - 2, INFINITY

5494:    Level: developer

5496: .seealso: [](chapter_ts), `TS`, `TSErrorWeightedENormInfinity()`, `TSErrorWeightedENorm2()`, `TSErrorWeightedNormInfinity()`, `TSErrorWeightedNorm2()`
5497: @*/
5498: PetscErrorCode TSErrorWeightedENorm(TS ts, Vec E, Vec U, Vec Y, NormType wnormtype, PetscReal *norm, PetscReal *norma, PetscReal *normr)
5499: {
5500:   PetscFunctionBegin;
5501:   if (wnormtype == NORM_2) PetscCall(TSErrorWeightedENorm2(ts, E, U, Y, norm, norma, normr));
5502:   else if (wnormtype == NORM_INFINITY) PetscCall(TSErrorWeightedENormInfinity(ts, E, U, Y, norm, norma, normr));
5503:   else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "No support for norm type %s", NormTypes[wnormtype]);
5504:   PetscFunctionReturn(PETSC_SUCCESS);
5505: }

5507: /*@
5508:    TSSetCFLTimeLocal - Set the local CFL constraint relative to forward Euler

5510:    Logically Collective

5512:    Input Parameters:
5513: +  ts - time stepping context
5514: -  cfltime - maximum stable time step if using forward Euler (value can be different on each process)

5516:    Note:
5517:    After calling this function, the global CFL time can be obtained by calling TSGetCFLTime()

5519:    Level: intermediate

5521: .seealso: [](chapter_ts), `TSGetCFLTime()`, `TSADAPTCFL`
5522: @*/
5523: PetscErrorCode TSSetCFLTimeLocal(TS ts, PetscReal cfltime)
5524: {
5525:   PetscFunctionBegin;
5527:   ts->cfltime_local = cfltime;
5528:   ts->cfltime       = -1.;
5529:   PetscFunctionReturn(PETSC_SUCCESS);
5530: }

5532: /*@
5533:    TSGetCFLTime - Get the maximum stable time step according to CFL criteria applied to forward Euler

5535:    Collective

5537:    Input Parameter:
5538: .  ts - time stepping context

5540:    Output Parameter:
5541: .  cfltime - maximum stable time step for forward Euler

5543:    Level: advanced

5545: .seealso: [](chapter_ts), `TSSetCFLTimeLocal()`
5546: @*/
5547: PetscErrorCode TSGetCFLTime(TS ts, PetscReal *cfltime)
5548: {
5549:   PetscFunctionBegin;
5550:   if (ts->cfltime < 0) PetscCall(MPIU_Allreduce(&ts->cfltime_local, &ts->cfltime, 1, MPIU_REAL, MPIU_MIN, PetscObjectComm((PetscObject)ts)));
5551:   *cfltime = ts->cfltime;
5552:   PetscFunctionReturn(PETSC_SUCCESS);
5553: }

5555: /*@
5556:    TSVISetVariableBounds - Sets the lower and upper bounds for the solution vector. xl <= x <= xu

5558:    Input Parameters:
5559: +  ts   - the `TS` context.
5560: .  xl   - lower bound.
5561: -  xu   - upper bound.

5563:    Level: advanced

5565:    Note:
5566:    If this routine is not called then the lower and upper bounds are set to
5567:    `PETSC_NINFINITY` and `PETSC_INFINITY` respectively during `SNESSetUp()`.

5569: .seealso: [](chapter_ts), `TS`
5570: @*/
5571: PetscErrorCode TSVISetVariableBounds(TS ts, Vec xl, Vec xu)
5572: {
5573:   SNES snes;

5575:   PetscFunctionBegin;
5576:   PetscCall(TSGetSNES(ts, &snes));
5577:   PetscCall(SNESVISetVariableBounds(snes, xl, xu));
5578:   PetscFunctionReturn(PETSC_SUCCESS);
5579: }

5581: /*@
5582:    TSComputeLinearStability - computes the linear stability function at a point

5584:    Collective

5586:    Input Parameters:
5587: +  ts - the `TS` context
5588: -  xr,xi - real and imaginary part of input arguments

5590:    Output Parameters:
5591: .  yr,yi - real and imaginary part of function value

5593:    Level: developer

5595: .seealso: [](chapter_ts), `TS`, `TSSetRHSFunction()`, `TSComputeIFunction()`
5596: @*/
5597: PetscErrorCode TSComputeLinearStability(TS ts, PetscReal xr, PetscReal xi, PetscReal *yr, PetscReal *yi)
5598: {
5599:   PetscFunctionBegin;
5601:   PetscUseTypeMethod(ts, linearstability, xr, xi, yr, yi);
5602:   PetscFunctionReturn(PETSC_SUCCESS);
5603: }

5605: /*@
5606:    TSRestartStep - Flags the solver to restart the next step

5608:    Collective

5610:    Input Parameter:
5611: .  ts - the `TS` context obtained from `TSCreate()`

5613:    Level: advanced

5615:    Notes:
5616:    Multistep methods like `TSBDF` or Runge-Kutta methods with FSAL property require restarting the solver in the event of
5617:    discontinuities. These discontinuities may be introduced as a consequence of explicitly modifications to the solution
5618:    vector (which PETSc attempts to detect and handle) or problem coefficients (which PETSc is not able to detect). For
5619:    the sake of correctness and maximum safety, users are expected to call `TSRestart()` whenever they introduce
5620:    discontinuities in callback routines (e.g. prestep and poststep routines, or implicit/rhs function routines with
5621:    discontinuous source terms).

5623: .seealso: [](chapter_ts), `TS`, `TSBDF`, `TSSolve()`, `TSSetPreStep()`, `TSSetPostStep()`
5624: @*/
5625: PetscErrorCode TSRestartStep(TS ts)
5626: {
5627:   PetscFunctionBegin;
5629:   ts->steprestart = PETSC_TRUE;
5630:   PetscFunctionReturn(PETSC_SUCCESS);
5631: }

5633: /*@
5634:    TSRollBack - Rolls back one time step

5636:    Collective

5638:    Input Parameter:
5639: .  ts - the `TS` context obtained from `TSCreate()`

5641:    Level: advanced

5643: .seealso: [](chapter_ts), `TS`, `TSCreate()`, `TSSetUp()`, `TSDestroy()`, `TSSolve()`, `TSSetPreStep()`, `TSSetPreStage()`, `TSInterpolate()`
5644: @*/
5645: PetscErrorCode TSRollBack(TS ts)
5646: {
5647:   PetscFunctionBegin;
5649:   PetscCheck(!ts->steprollback, PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_WRONGSTATE, "TSRollBack already called");
5650:   PetscUseTypeMethod(ts, rollback);
5651:   ts->time_step  = ts->ptime - ts->ptime_prev;
5652:   ts->ptime      = ts->ptime_prev;
5653:   ts->ptime_prev = ts->ptime_prev_rollback;
5654:   ts->steps--;
5655:   ts->steprollback = PETSC_TRUE;
5656:   PetscFunctionReturn(PETSC_SUCCESS);
5657: }

5659: /*@
5660:    TSGetStages - Get the number of stages and stage values

5662:    Input Parameter:
5663: .  ts - the `TS` context obtained from `TSCreate()`

5665:    Output Parameters:
5666: +  ns - the number of stages
5667: -  Y - the current stage vectors

5669:    Level: advanced

5671:    Note:
5672:    Both `ns` and `Y` can be `NULL`.

5674: .seealso: [](chapter_ts), `TS`, `TSCreate()`
5675: @*/
5676: PetscErrorCode TSGetStages(TS ts, PetscInt *ns, Vec **Y)
5677: {
5678:   PetscFunctionBegin;
5682:   if (!ts->ops->getstages) {
5683:     if (ns) *ns = 0;
5684:     if (Y) *Y = NULL;
5685:   } else PetscUseTypeMethod(ts, getstages, ns, Y);
5686:   PetscFunctionReturn(PETSC_SUCCESS);
5687: }

5689: /*@C
5690:   TSComputeIJacobianDefaultColor - Computes the Jacobian using finite differences and coloring to exploit matrix sparsity.

5692:   Collective

5694:   Input Parameters:
5695: + ts - the `TS` context
5696: . t - current timestep
5697: . U - state vector
5698: . Udot - time derivative of state vector
5699: . shift - shift to apply, see note below
5700: - ctx - an optional user context

5702:   Output Parameters:
5703: + J - Jacobian matrix (not altered in this routine)
5704: - B - newly computed Jacobian matrix to use with preconditioner (generally the same as `J`)

5706:   Level: intermediate

5708:   Notes:
5709:   If F(t,U,Udot)=0 is the DAE, the required Jacobian is

5711:   dF/dU + shift*dF/dUdot

5713:   Most users should not need to explicitly call this routine, as it
5714:   is used internally within the nonlinear solvers.

5716:   This will first try to get the coloring from the `DM`.  If the `DM` type has no coloring
5717:   routine, then it will try to get the coloring from the matrix.  This requires that the
5718:   matrix have nonzero entries precomputed.

5720: .seealso: [](chapter_ts), `TS`, `TSSetIJacobian()`, `MatFDColoringCreate()`, `MatFDColoringSetFunction()`
5721: @*/
5722: PetscErrorCode TSComputeIJacobianDefaultColor(TS ts, PetscReal t, Vec U, Vec Udot, PetscReal shift, Mat J, Mat B, void *ctx)
5723: {
5724:   SNES          snes;
5725:   MatFDColoring color;
5726:   PetscBool     hascolor, matcolor = PETSC_FALSE;

5728:   PetscFunctionBegin;
5729:   PetscCall(PetscOptionsGetBool(((PetscObject)ts)->options, ((PetscObject)ts)->prefix, "-ts_fd_color_use_mat", &matcolor, NULL));
5730:   PetscCall(PetscObjectQuery((PetscObject)B, "TSMatFDColoring", (PetscObject *)&color));
5731:   if (!color) {
5732:     DM         dm;
5733:     ISColoring iscoloring;

5735:     PetscCall(TSGetDM(ts, &dm));
5736:     PetscCall(DMHasColoring(dm, &hascolor));
5737:     if (hascolor && !matcolor) {
5738:       PetscCall(DMCreateColoring(dm, IS_COLORING_GLOBAL, &iscoloring));
5739:       PetscCall(MatFDColoringCreate(B, iscoloring, &color));
5740:       PetscCall(MatFDColoringSetFunction(color, (PetscErrorCode(*)(void))SNESTSFormFunction, (void *)ts));
5741:       PetscCall(MatFDColoringSetFromOptions(color));
5742:       PetscCall(MatFDColoringSetUp(B, iscoloring, color));
5743:       PetscCall(ISColoringDestroy(&iscoloring));
5744:     } else {
5745:       MatColoring mc;

5747:       PetscCall(MatColoringCreate(B, &mc));
5748:       PetscCall(MatColoringSetDistance(mc, 2));
5749:       PetscCall(MatColoringSetType(mc, MATCOLORINGSL));
5750:       PetscCall(MatColoringSetFromOptions(mc));
5751:       PetscCall(MatColoringApply(mc, &iscoloring));
5752:       PetscCall(MatColoringDestroy(&mc));
5753:       PetscCall(MatFDColoringCreate(B, iscoloring, &color));
5754:       PetscCall(MatFDColoringSetFunction(color, (PetscErrorCode(*)(void))SNESTSFormFunction, (void *)ts));
5755:       PetscCall(MatFDColoringSetFromOptions(color));
5756:       PetscCall(MatFDColoringSetUp(B, iscoloring, color));
5757:       PetscCall(ISColoringDestroy(&iscoloring));
5758:     }
5759:     PetscCall(PetscObjectCompose((PetscObject)B, "TSMatFDColoring", (PetscObject)color));
5760:     PetscCall(PetscObjectDereference((PetscObject)color));
5761:   }
5762:   PetscCall(TSGetSNES(ts, &snes));
5763:   PetscCall(MatFDColoringApply(B, color, U, snes));
5764:   if (J != B) {
5765:     PetscCall(MatAssemblyBegin(J, MAT_FINAL_ASSEMBLY));
5766:     PetscCall(MatAssemblyEnd(J, MAT_FINAL_ASSEMBLY));
5767:   }
5768:   PetscFunctionReturn(PETSC_SUCCESS);
5769: }

5771: /*@
5772:     TSSetFunctionDomainError - Set a function that tests if the current state vector is valid

5774:     Input Parameters:
5775: +    ts - the `TS` context
5776: -    func - function called within `TSFunctionDomainError()`

5778:     Calling sequence of func:
5779: $     PetscErrorCode func(TS ts,PetscReal time,Vec state,PetscBool reject)

5781: +   ts - the TS context
5782: .   time - the current time (of the stage)
5783: .   state - the state to check if it is valid
5784: -   reject - (output parameter) PETSC_FALSE if the state is acceptable, PETSC_TRUE if not acceptable

5786:     Level: intermediate

5788:     Notes:
5789:       If an implicit ODE solver is being used then, in addition to providing this routine, the
5790:       user's code should call `SNESSetFunctionDomainError()` when domain errors occur during
5791:       function evaluations where the functions are provided by `TSSetIFunction()` or `TSSetRHSFunction()`.
5792:       Use `TSGetSNES()` to obtain the `SNES` object

5794:     Developer Note:
5795:       The naming of this function is inconsistent with the `SNESSetFunctionDomainError()`
5796:       since one takes a function pointer and the other does not.

5798: .seealso: [](chapter_ts), `TSAdaptCheckStage()`, `TSFunctionDomainError()`, `SNESSetFunctionDomainError()`, `TSGetSNES()`
5799: @*/

5801: PetscErrorCode TSSetFunctionDomainError(TS ts, PetscErrorCode (*func)(TS, PetscReal, Vec, PetscBool *))
5802: {
5803:   PetscFunctionBegin;
5805:   ts->functiondomainerror = func;
5806:   PetscFunctionReturn(PETSC_SUCCESS);
5807: }

5809: /*@
5810:     TSFunctionDomainError - Checks if the current state is valid

5812:     Input Parameters:
5813: +    ts - the `TS` context
5814: .    stagetime - time of the simulation
5815: -    Y - state vector to check.

5817:     Output Parameter:
5818: .    accept - Set to `PETSC_FALSE` if the current state vector is valid.

5820:     Level: developer

5822:     Note:
5823:     This function is called by the `TS` integration routines and calls the user provided function (set with `TSSetFunctionDomainError()`)
5824:     to check if the current state is valid.

5826: .seealso: [](chapter_ts), `TS`, `TSSetFunctionDomainError()`
5827: @*/
5828: PetscErrorCode TSFunctionDomainError(TS ts, PetscReal stagetime, Vec Y, PetscBool *accept)
5829: {
5830:   PetscFunctionBegin;
5832:   *accept = PETSC_TRUE;
5833:   if (ts->functiondomainerror) PetscCall((*ts->functiondomainerror)(ts, stagetime, Y, accept));
5834:   PetscFunctionReturn(PETSC_SUCCESS);
5835: }

5837: /*@C
5838:   TSClone - This function clones a time step `TS` object.

5840:   Collective

5842:   Input Parameter:
5843: . tsin    - The input `TS`

5845:   Output Parameter:
5846: . tsout   - The output `TS` (cloned)

5848:   Level: developer

5850:   Notes:
5851:   This function is used to create a clone of a `TS` object. It is used in `TSARKIMEX` for initializing the slope for first stage explicit methods.
5852:   It will likely be replaced in the future with a mechanism of switching methods on the fly.

5854:   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
5855: .vb
5856:  SNES snes_dup = NULL;
5857:  TSGetSNES(ts,&snes_dup);
5858:  TSSetSNES(ts,snes_dup);
5859: .ve

5861: .seealso: [](chapter_ts), `TS`, `SNES`, `TSCreate()`, `TSSetType()`, `TSSetUp()`, `TSDestroy()`, `TSSetProblemType()`
5862: @*/
5863: PetscErrorCode TSClone(TS tsin, TS *tsout)
5864: {
5865:   TS     t;
5866:   SNES   snes_start;
5867:   DM     dm;
5868:   TSType type;

5870:   PetscFunctionBegin;
5872:   *tsout = NULL;

5874:   PetscCall(PetscHeaderCreate(t, TS_CLASSID, "TS", "Time stepping", "TS", PetscObjectComm((PetscObject)tsin), TSDestroy, TSView));

5876:   /* General TS description */
5877:   t->numbermonitors    = 0;
5878:   t->monitorFrequency  = 1;
5879:   t->setupcalled       = 0;
5880:   t->ksp_its           = 0;
5881:   t->snes_its          = 0;
5882:   t->nwork             = 0;
5883:   t->rhsjacobian.time  = PETSC_MIN_REAL;
5884:   t->rhsjacobian.scale = 1.;
5885:   t->ijacobian.shift   = 1.;

5887:   PetscCall(TSGetSNES(tsin, &snes_start));
5888:   PetscCall(TSSetSNES(t, snes_start));

5890:   PetscCall(TSGetDM(tsin, &dm));
5891:   PetscCall(TSSetDM(t, dm));

5893:   t->adapt = tsin->adapt;
5894:   PetscCall(PetscObjectReference((PetscObject)t->adapt));

5896:   t->trajectory = tsin->trajectory;
5897:   PetscCall(PetscObjectReference((PetscObject)t->trajectory));

5899:   t->event = tsin->event;
5900:   if (t->event) t->event->refct++;

5902:   t->problem_type      = tsin->problem_type;
5903:   t->ptime             = tsin->ptime;
5904:   t->ptime_prev        = tsin->ptime_prev;
5905:   t->time_step         = tsin->time_step;
5906:   t->max_time          = tsin->max_time;
5907:   t->steps             = tsin->steps;
5908:   t->max_steps         = tsin->max_steps;
5909:   t->equation_type     = tsin->equation_type;
5910:   t->atol              = tsin->atol;
5911:   t->rtol              = tsin->rtol;
5912:   t->max_snes_failures = tsin->max_snes_failures;
5913:   t->max_reject        = tsin->max_reject;
5914:   t->errorifstepfailed = tsin->errorifstepfailed;

5916:   PetscCall(TSGetType(tsin, &type));
5917:   PetscCall(TSSetType(t, type));

5919:   t->vec_sol = NULL;

5921:   t->cfltime          = tsin->cfltime;
5922:   t->cfltime_local    = tsin->cfltime_local;
5923:   t->exact_final_time = tsin->exact_final_time;

5925:   PetscCall(PetscMemcpy(t->ops, tsin->ops, sizeof(struct _TSOps)));

5927:   if (((PetscObject)tsin)->fortran_func_pointers) {
5928:     PetscInt i;
5929:     PetscCall(PetscMalloc((10) * sizeof(void (*)(void)), &((PetscObject)t)->fortran_func_pointers));
5930:     for (i = 0; i < 10; i++) ((PetscObject)t)->fortran_func_pointers[i] = ((PetscObject)tsin)->fortran_func_pointers[i];
5931:   }
5932:   *tsout = t;
5933:   PetscFunctionReturn(PETSC_SUCCESS);
5934: }

5936: static PetscErrorCode RHSWrapperFunction_TSRHSJacobianTest(void *ctx, Vec x, Vec y)
5937: {
5938:   TS ts = (TS)ctx;

5940:   PetscFunctionBegin;
5941:   PetscCall(TSComputeRHSFunction(ts, 0, x, y));
5942:   PetscFunctionReturn(PETSC_SUCCESS);
5943: }

5945: /*@
5946:     TSRHSJacobianTest - Compares the multiply routine provided to the `MATSHELL` with differencing on the `TS` given RHS function.

5948:    Logically Collective

5950:     Input Parameters:
5951:     TS - the time stepping routine

5953:    Output Parameter:
5954: .   flg - `PETSC_TRUE` if the multiply is likely correct

5956:    Options Database Key:
5957:  .   -ts_rhs_jacobian_test_mult -mat_shell_test_mult_view - run the test at each timestep of the integrator

5959:    Level: advanced

5961:    Note:
5962:     This only works for problems defined using `TSSetRHSFunction()` and Jacobian NOT `TSSetIFunction()` and Jacobian

5964: .seealso: [](chapter_ts), `TS`, `Mat`, `MATSHELL`, `MatCreateShell()`, `MatShellGetContext()`, `MatShellGetOperation()`, `MatShellTestMultTranspose()`, `TSRHSJacobianTestTranspose()`
5965: @*/
5966: PetscErrorCode TSRHSJacobianTest(TS ts, PetscBool *flg)
5967: {
5968:   Mat           J, B;
5969:   TSRHSJacobian func;
5970:   void         *ctx;

5972:   PetscFunctionBegin;
5973:   PetscCall(TSGetRHSJacobian(ts, &J, &B, &func, &ctx));
5974:   PetscCall((*func)(ts, 0.0, ts->vec_sol, J, B, ctx));
5975:   PetscCall(MatShellTestMult(J, RHSWrapperFunction_TSRHSJacobianTest, ts->vec_sol, ts, flg));
5976:   PetscFunctionReturn(PETSC_SUCCESS);
5977: }

5979: /*@C
5980:     TSRHSJacobianTestTranspose - Compares the multiply transpose routine provided to the `MATSHELL` with differencing on the `TS` given RHS function.

5982:    Logically Collective

5984:     Input Parameters:
5985:     TS - the time stepping routine

5987:    Output Parameter:
5988: .   flg - `PETSC_TRUE` if the multiply is likely correct

5990:    Options Database Key:
5991: .   -ts_rhs_jacobian_test_mult_transpose -mat_shell_test_mult_transpose_view - run the test at each timestep of the integrator

5993:    Level: advanced

5995:    Notes:
5996:     This only works for problems defined using `TSSetRHSFunction()` and Jacobian NOT `TSSetIFunction()` and Jacobian

5998: .seealso: [](chapter_ts), `TS`, `Mat`, `MatCreateShell()`, `MatShellGetContext()`, `MatShellGetOperation()`, `MatShellTestMultTranspose()`, `TSRHSJacobianTest()`
5999: @*/
6000: PetscErrorCode TSRHSJacobianTestTranspose(TS ts, PetscBool *flg)
6001: {
6002:   Mat           J, B;
6003:   void         *ctx;
6004:   TSRHSJacobian func;

6006:   PetscFunctionBegin;
6007:   PetscCall(TSGetRHSJacobian(ts, &J, &B, &func, &ctx));
6008:   PetscCall((*func)(ts, 0.0, ts->vec_sol, J, B, ctx));
6009:   PetscCall(MatShellTestMultTranspose(J, RHSWrapperFunction_TSRHSJacobianTest, ts->vec_sol, ts, flg));
6010:   PetscFunctionReturn(PETSC_SUCCESS);
6011: }

6013: /*@
6014:   TSSetUseSplitRHSFunction - Use the split RHSFunction when a multirate method is used.

6016:   Logically collective

6018:   Input Parameters:
6019: +  ts - timestepping context
6020: -  use_splitrhsfunction - `PETSC_TRUE` indicates that the split RHSFunction will be used

6022:   Options Database Key:
6023: .   -ts_use_splitrhsfunction - <true,false>

6025:   Level: intermediate

6027:   Note:
6028:   This is only for multirate methods

6030: .seealso: [](chapter_ts), `TS`, `TSGetUseSplitRHSFunction()`
6031: @*/
6032: PetscErrorCode TSSetUseSplitRHSFunction(TS ts, PetscBool use_splitrhsfunction)
6033: {
6034:   PetscFunctionBegin;
6036:   ts->use_splitrhsfunction = use_splitrhsfunction;
6037:   PetscFunctionReturn(PETSC_SUCCESS);
6038: }

6040: /*@
6041:   TSGetUseSplitRHSFunction - Gets whether to use the split RHSFunction when a multirate method is used.

6043:   Not collective

6045:   Input Parameter:
6046: .  ts - timestepping context

6048:   Output Parameter:
6049: .  use_splitrhsfunction - `PETSC_TRUE` indicates that the split RHSFunction will be used

6051:   Level: intermediate

6053: .seealso: [](chapter_ts), `TS`, `TSSetUseSplitRHSFunction()`
6054: @*/
6055: PetscErrorCode TSGetUseSplitRHSFunction(TS ts, PetscBool *use_splitrhsfunction)
6056: {
6057:   PetscFunctionBegin;
6059:   *use_splitrhsfunction = ts->use_splitrhsfunction;
6060:   PetscFunctionReturn(PETSC_SUCCESS);
6061: }

6063: /*@
6064:     TSSetMatStructure - sets the relationship between the nonzero structure of the RHS Jacobian matrix to the IJacobian matrix.

6066:    Logically  Collective

6068:    Input Parameters:
6069: +  ts - the time-stepper
6070: -  str - the structure (the default is `UNKNOWN_NONZERO_PATTERN`)

6072:    Level: intermediate

6074:    Note:
6075:      When the relationship between the nonzero structures is known and supplied the solution process can be much faster

6077: .seealso: [](chapter_ts), `TS`, `MatAXPY()`, `MatStructure`
6078:  @*/
6079: PetscErrorCode TSSetMatStructure(TS ts, MatStructure str)
6080: {
6081:   PetscFunctionBegin;
6083:   ts->axpy_pattern = str;
6084:   PetscFunctionReturn(PETSC_SUCCESS);
6085: }

6087: /*@
6088:   TSSetTimeSpan - sets the time span. The solution will be computed and stored for each time requested in the span

6090:   Collective

6092:   Input Parameters:
6093: + ts - the time-stepper
6094: . n - number of the time points (>=2)
6095: - span_times - array of the time points. The first element and the last element are the initial time and the final time respectively.

6097:   Options Database Key:
6098: . -ts_time_span <t0,...tf> - Sets the time span

6100:   Level: intermediate

6102:   Notes:
6103:   The elements in tspan must be all increasing. They correspond to the intermediate points for time integration.
6104:   `TS_EXACTFINALTIME_MATCHSTEP` must be used to make the last time step in each sub-interval match the intermediate points specified.
6105:   The intermediate solutions are saved in a vector array that can be accessed with `TSGetTimeSpanSolutions()`. Thus using time span may
6106:   pressure the memory system when using a large number of span points.

6108: .seealso: [](chapter_ts), `TS`, `TSGetTimeSpan()`, `TSGetTimeSpanSolutions()`
6109:  @*/
6110: PetscErrorCode TSSetTimeSpan(TS ts, PetscInt n, PetscReal *span_times)
6111: {
6112:   PetscFunctionBegin;
6114:   PetscCheck(n >= 2, PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_WRONG, "Minimum time span size is 2 but %" PetscInt_FMT " is provided", n);
6115:   if (ts->tspan && n != ts->tspan->num_span_times) {
6116:     PetscCall(PetscFree(ts->tspan->span_times));
6117:     PetscCall(VecDestroyVecs(ts->tspan->num_span_times, &ts->tspan->vecs_sol));
6118:     PetscCall(PetscMalloc1(n, &ts->tspan->span_times));
6119:   }
6120:   if (!ts->tspan) {
6121:     TSTimeSpan tspan;
6122:     PetscCall(PetscNew(&tspan));
6123:     PetscCall(PetscMalloc1(n, &tspan->span_times));
6124:     tspan->reltol = 1e-6;
6125:     tspan->abstol = 10 * PETSC_MACHINE_EPSILON;
6126:     ts->tspan     = tspan;
6127:   }
6128:   ts->tspan->num_span_times = n;
6129:   PetscCall(PetscArraycpy(ts->tspan->span_times, span_times, n));
6130:   PetscCall(TSSetTime(ts, ts->tspan->span_times[0]));
6131:   PetscCall(TSSetMaxTime(ts, ts->tspan->span_times[n - 1]));
6132:   PetscFunctionReturn(PETSC_SUCCESS);
6133: }

6135: /*@C
6136:   TSGetTimeSpan - gets the time span set with `TSSetTimeSpan()`

6138:   Not Collective

6140:   Input Parameter:
6141: . ts - the time-stepper

6143:   Output Parameters:
6144: + n - number of the time points (>=2)
6145: - span_times - array of the time points. The first element and the last element are the initial time and the final time respectively.

6147:   Level: beginner

6149:   Note:
6150:   The values obtained are valid until the `TS` object is destroyed.

6152:   Both `n` and `span_times` can be `NULL`.

6154: .seealso: [](chapter_ts), `TS`, `TSSetTimeSpan()`, `TSGetTimeSpanSolutions()`
6155:  @*/
6156: PetscErrorCode TSGetTimeSpan(TS ts, PetscInt *n, const PetscReal **span_times)
6157: {
6158:   PetscFunctionBegin;
6162:   if (!ts->tspan) {
6163:     if (n) *n = 0;
6164:     if (span_times) *span_times = NULL;
6165:   } else {
6166:     if (n) *n = ts->tspan->num_span_times;
6167:     if (span_times) *span_times = ts->tspan->span_times;
6168:   }
6169:   PetscFunctionReturn(PETSC_SUCCESS);
6170: }

6172: /*@
6173:    TSGetTimeSpanSolutions - Get the number of solutions and the solutions at the time points specified by the time span.

6175:    Input Parameter:
6176: .  ts - the `TS` context obtained from `TSCreate()`

6178:    Output Parameters:
6179: +  nsol - the number of solutions
6180: -  Sols - the solution vectors

6182:    Level: intermediate

6184:    Notes:
6185:     Both `nsol` and `Sols` can be `NULL`.

6187:     Some time points in the time span may be skipped by `TS` so that `nsol` is less than the number of points specified by `TSSetTimeSpan()`.
6188:     For example, manipulating the step size, especially with a reduced precision, may cause `TS` to step over certain points in the span.

6190: .seealso: [](chapter_ts), `TS`, `TSSetTimeSpan()`
6191: @*/
6192: PetscErrorCode TSGetTimeSpanSolutions(TS ts, PetscInt *nsol, Vec **Sols)
6193: {
6194:   PetscFunctionBegin;
6198:   if (!ts->tspan) {
6199:     if (nsol) *nsol = 0;
6200:     if (Sols) *Sols = NULL;
6201:   } else {
6202:     if (nsol) *nsol = ts->tspan->spanctr;
6203:     if (Sols) *Sols = ts->tspan->vecs_sol;
6204:   }
6205:   PetscFunctionReturn(PETSC_SUCCESS);
6206: }

6208: /*@C
6209:   TSPruneIJacobianColor - Remove nondiagonal zeros in the Jacobian matrix and update the `MatMFFD` coloring information.

6211:   Collective

6213:   Input Parameters:
6214: + ts - the `TS` context
6215: . J - Jacobian matrix (not altered in this routine)
6216: - B - newly computed Jacobian matrix to use with preconditioner

6218:   Level: intermediate

6220:   Notes:
6221:   This function improves the `MatFDColoring` performance when the Jacobian matrix was over-allocated or contains
6222:   many constant zeros entries, which is typically the case when the matrix is generated by a `DM`
6223:   and multiple fields are involved.

6225:   Users need to make sure that the Jacobian matrix is properly filled to reflect the sparsity
6226:   structure. For `MatFDColoring`, the values of nonzero entries are not important. So one can
6227:   usually call `TSComputeIJacobian()` with randomized input vectors to generate a dummy Jacobian.
6228:   `TSComputeIJacobian()` should be called before `TSSolve()` but after `TSSetUp()`.

6230: .seealso: [](chapter_ts), `TS`, `MatFDColoring`, `TSComputeIJacobianDefaultColor()`, `MatEliminateZeros()`, `MatFDColoringCreate()`, `MatFDColoringSetFunction()`
6231: @*/
6232: PetscErrorCode TSPruneIJacobianColor(TS ts, Mat J, Mat B)
6233: {
6234:   MatColoring   mc            = NULL;
6235:   ISColoring    iscoloring    = NULL;
6236:   MatFDColoring matfdcoloring = NULL;

6238:   PetscFunctionBegin;
6239:   /* Generate new coloring after eliminating zeros in the matrix */
6240:   PetscCall(MatEliminateZeros(B));
6241:   PetscCall(MatColoringCreate(B, &mc));
6242:   PetscCall(MatColoringSetDistance(mc, 2));
6243:   PetscCall(MatColoringSetType(mc, MATCOLORINGSL));
6244:   PetscCall(MatColoringSetFromOptions(mc));
6245:   PetscCall(MatColoringApply(mc, &iscoloring));
6246:   PetscCall(MatColoringDestroy(&mc));
6247:   /* Replace the old coloring with the new one */
6248:   PetscCall(MatFDColoringCreate(B, iscoloring, &matfdcoloring));
6249:   PetscCall(MatFDColoringSetFunction(matfdcoloring, (PetscErrorCode(*)(void))SNESTSFormFunction, (void *)ts));
6250:   PetscCall(MatFDColoringSetFromOptions(matfdcoloring));
6251:   PetscCall(MatFDColoringSetUp(B, iscoloring, matfdcoloring));
6252:   PetscCall(PetscObjectCompose((PetscObject)B, "TSMatFDColoring", (PetscObject)matfdcoloring));
6253:   PetscCall(PetscObjectDereference((PetscObject)matfdcoloring));
6254:   PetscCall(ISColoringDestroy(&iscoloring));
6255:   PetscFunctionReturn(PETSC_SUCCESS);
6256: }