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: /* Logging support */
11: PetscClassId TS_CLASSID, DMTS_CLASSID;
12: PetscLogEvent TS_Step, TS_PseudoComputeTimeStep, TS_FunctionEval, TS_JacobianEval;
14: const char *const TSExactFinalTimeOptions[] = {"UNSPECIFIED", "STEPOVER", "INTERPOLATE", "MATCHSTEP", "TSExactFinalTimeOption", "TS_EXACTFINALTIME_", NULL};
16: static PetscErrorCode TSAdaptSetDefaultType(TSAdapt adapt, TSAdaptType default_type)
17: {
18: PetscFunctionBegin;
20: PetscAssertPointer(default_type, 2);
21: if (!((PetscObject)adapt)->type_name) PetscCall(TSAdaptSetType(adapt, default_type));
22: PetscFunctionReturn(PETSC_SUCCESS);
23: }
25: /*@
26: TSSetFromOptions - Sets various `TS` parameters from the options database
28: Collective
30: Input Parameter:
31: . ts - the `TS` context obtained from `TSCreate()`
33: Options Database Keys:
34: + -ts_type type - EULER, BEULER, SUNDIALS, PSEUDO, CN, RK, THETA, ALPHA, GLLE, SSP, GLEE, BSYMP, IRK, see `TSType`
35: . -ts_save_trajectory - checkpoint the solution at each time-step
36: . -ts_max_time time - maximum time to compute to
37: . -ts_time_span t0,...,tf - sets the time span, solutions are computed and stored for each indicated time, init_time and max_time are set
38: . -ts_eval_times t0,...,tn - time points where solutions are computed and stored for each indicated time
39: . -ts_max_steps steps - maximum time-step number to execute until (possibly with nonzero starting value)
40: . -ts_run_steps steps - maximum number of time steps for `TSSolve()` to take on each call
41: . -ts_init_time time - initial time to start computation
42: . -ts_final_time time - final time to compute to (deprecated: use `-ts_max_time`)
43: . -ts_time_step dt - initial time step (only a suggestion, the actual initial time step used differ)
44: . -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
45: . -ts_max_snes_failures maxfailures - Maximum number of nonlinear solve failures allowed
46: . -ts_max_step_rejections maxrejects - Maximum number of step rejections before step fails
47: . -ts_error_if_step_fails (true|false) - Error if no step succeeds
48: . -ts_rtol rtol - relative tolerance for local truncation error
49: . -ts_atol atol - Absolute tolerance for local truncation error
50: . -ts_rhs_jacobian_test_mult -mat_shell_test_mult_view - test the Jacobian at each iteration against finite difference with RHS function
51: . -ts_rhs_jacobian_test_mult_transpose - test the Jacobian at each iteration against finite difference with RHS function
52: . -ts_adjoint_solve (true|false) - After solving the ODE/DAE solve the adjoint problem (requires `-ts_save_trajectory`)
53: . -ts_fd_color - Use finite differences with coloring to compute IJacobian
54: . -ts_monitor - print information at each timestep
55: . -ts_monitor_cancel - Cancel all monitors
56: . -ts_monitor_wall_clock_time - Monitor wall-clock time, KSP iterations, and SNES iterations per step
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. Use -1 to only output at the end of the simulation
70: . -ts_monitor_solution_skip_initial - skip writing of initial condition
71: . -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)
72: . -ts_monitor_solution_vtk_interval interval - output once every interval (default=1) time steps. Use -1 to only output at the end of the simulation
73: - -ts_monitor_envelope - determine maximum and minimum value of each component of the solution over the solution time
75: Level: beginner
77: Notes:
78: See `SNESSetFromOptions()` and `KSPSetFromOptions()` for how to control the nonlinear and linear solves used by the time-stepper.
80: Certain `SNES` options get reset for each new nonlinear solver, for example `-snes_lag_jacobian its` and `-snes_lag_preconditioner its`, in order
81: to retain them over the multiple nonlinear solves that `TS` uses you must also provide `-snes_lag_jacobian_persists true` and
82: `-snes_lag_preconditioner_persists true`
84: Developer Notes:
85: We should unify all the -ts_monitor options in the way that -xxx_view has been unified
87: .seealso: [](ch_ts), `TS`, `TSGetType()`
88: @*/
89: PetscErrorCode TSSetFromOptions(TS ts)
90: {
91: PetscBool opt, flg, tflg;
92: char monfilename[PETSC_MAX_PATH_LEN];
93: PetscReal time_step, eval_times[100] = {0};
94: PetscInt num_eval_times = PETSC_STATIC_ARRAY_LENGTH(eval_times);
95: TSExactFinalTimeOption eftopt;
96: char dir[16];
97: TSIFunctionFn *ifun;
98: const char *defaultType;
99: char typeName[256];
101: PetscFunctionBegin;
104: PetscCall(TSRegisterAll());
105: PetscCall(TSGetIFunction(ts, NULL, &ifun, NULL));
107: PetscObjectOptionsBegin((PetscObject)ts);
108: if (((PetscObject)ts)->type_name) defaultType = ((PetscObject)ts)->type_name;
109: else defaultType = ifun ? TSBEULER : TSEULER;
110: PetscCall(PetscOptionsFList("-ts_type", "TS method", "TSSetType", TSList, defaultType, typeName, 256, &opt));
111: if (opt) PetscCall(TSSetType(ts, typeName));
112: else PetscCall(TSSetType(ts, defaultType));
114: /* Handle generic TS options */
115: PetscCall(PetscOptionsDeprecated("-ts_final_time", "-ts_max_time", "3.10", NULL));
116: PetscCall(PetscOptionsReal("-ts_max_time", "Maximum time to run to", "TSSetMaxTime", ts->max_time, &ts->max_time, NULL));
117: PetscCall(PetscOptionsRealArray("-ts_time_span", "Time span", "TSSetTimeSpan", eval_times, &num_eval_times, &flg));
118: if (flg) PetscCall(TSSetTimeSpan(ts, num_eval_times, eval_times));
119: num_eval_times = PETSC_STATIC_ARRAY_LENGTH(eval_times);
120: PetscCall(PetscOptionsRealArray("-ts_eval_times", "Evaluation time points", "TSSetEvaluationTimes", eval_times, &num_eval_times, &opt));
121: PetscCheck(flg != opt || (!flg && !opt), PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_WRONG, "May not provide -ts_time_span and -ts_eval_times simultaneously");
122: if (opt) PetscCall(TSSetEvaluationTimes(ts, num_eval_times, eval_times));
123: PetscCall(PetscOptionsInt("-ts_max_steps", "Maximum time step number to execute to (possibly with non-zero starting value)", "TSSetMaxSteps", ts->max_steps, &ts->max_steps, NULL));
124: PetscCall(PetscOptionsInt("-ts_run_steps", "Maximum number of time steps to take on each call to TSSolve()", "TSSetRunSteps", ts->run_steps, &ts->run_steps, NULL));
125: PetscCall(PetscOptionsReal("-ts_init_time", "Initial time", "TSSetTime", ts->ptime, &ts->ptime, NULL));
126: PetscCall(PetscOptionsDeprecated("-ts_dt", "-ts_time_step", "3.25", NULL));
127: PetscCall(PetscOptionsReal("-ts_time_step", "Initial time step", "TSSetTimeStep", ts->time_step, &time_step, &flg));
128: if (flg) PetscCall(TSSetTimeStep(ts, time_step));
129: PetscCall(PetscOptionsEnum("-ts_exact_final_time", "Option for handling of final time step", "TSSetExactFinalTime", TSExactFinalTimeOptions, (PetscEnum)ts->exact_final_time, (PetscEnum *)&eftopt, &flg));
130: if (flg) PetscCall(TSSetExactFinalTime(ts, eftopt));
131: PetscCall(PetscOptionsInt("-ts_max_snes_failures", "Maximum number of nonlinear solve failures", "TSSetMaxSNESFailures", ts->max_snes_failures, &ts->max_snes_failures, &flg));
132: if (flg) PetscCall(TSSetMaxSNESFailures(ts, ts->max_snes_failures));
133: PetscCall(PetscOptionsDeprecated("-ts_max_reject", "-ts_max_step_rejections", "3.25", NULL));
134: PetscCall(PetscOptionsInt("-ts_max_step_rejections", "Maximum number of step rejections before step fails", "TSSetMaxStepRejections", ts->max_reject, &ts->max_reject, &flg));
135: if (flg) PetscCall(TSSetMaxStepRejections(ts, ts->max_reject));
136: PetscCall(PetscOptionsBool("-ts_error_if_step_fails", "Error if no step succeeds", "TSSetErrorIfStepFails", ts->errorifstepfailed, &ts->errorifstepfailed, NULL));
137: PetscCall(PetscOptionsBoundedReal("-ts_rtol", "Relative tolerance for local truncation error", "TSSetTolerances", ts->rtol, &ts->rtol, NULL, 0));
138: PetscCall(PetscOptionsBoundedReal("-ts_atol", "Absolute tolerance for local truncation error", "TSSetTolerances", ts->atol, &ts->atol, NULL, 0));
140: PetscCall(PetscOptionsBool("-ts_rhs_jacobian_test_mult", "Test the RHS Jacobian for consistency with RHS at each solve ", "None", ts->testjacobian, &ts->testjacobian, NULL));
141: 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));
142: PetscCall(PetscOptionsBool("-ts_use_splitrhsfunction", "Use the split RHS function for multirate solvers ", "TSSetUseSplitRHSFunction", ts->use_splitrhsfunction, &ts->use_splitrhsfunction, NULL));
143: #if defined(PETSC_HAVE_SAWS)
144: {
145: PetscBool set;
146: flg = PETSC_FALSE;
147: PetscCall(PetscOptionsBool("-ts_saws_block", "Block for SAWs memory snooper at end of TSSolve", "PetscObjectSAWsBlock", ((PetscObject)ts)->amspublishblock, &flg, &set));
148: if (set) PetscCall(PetscObjectSAWsSetBlock((PetscObject)ts, flg));
149: }
150: #endif
152: /* Monitor options */
153: PetscCall(PetscOptionsDeprecated("-ts_monitor_frequency", "-ts_dmswarm_monitor_moments_interval", "3.24", "Retired in favor of monitor-specific intervals (ts_dmswarm_monitor_moments was the only monitor to use ts_monitor_frequency)"));
154: PetscCall(TSMonitorSetFromOptions(ts, "-ts_monitor", "Monitor time and timestep size", "TSMonitorDefault", TSMonitorDefault, NULL));
155: PetscCall(TSMonitorSetFromOptions(ts, "-ts_monitor_wall_clock_time", "Monitor wall-clock time, KSP iterations, and SNES iterations per step", "TSMonitorWallClockTime", TSMonitorWallClockTime, TSMonitorWallClockTimeSetUp));
156: PetscCall(TSMonitorSetFromOptions(ts, "-ts_monitor_extreme", "Monitor extreme values of the solution", "TSMonitorExtreme", TSMonitorExtreme, NULL));
157: PetscCall(TSMonitorSetFromOptions(ts, "-ts_monitor_solution", "View the solution at each timestep", "TSMonitorSolution", TSMonitorSolution, TSMonitorSolutionSetup));
158: PetscCall(TSMonitorSetFromOptions(ts, "-ts_dmswarm_monitor_moments", "Monitor moments of particle distribution", "TSDMSwarmMonitorMoments", TSDMSwarmMonitorMoments, NULL));
159: PetscCall(PetscOptionsString("-ts_monitor_python", "Use Python function", "TSMonitorSet", NULL, monfilename, sizeof(monfilename), &flg));
160: if (flg) PetscCall(PetscPythonMonitorSet((PetscObject)ts, monfilename));
162: PetscCall(PetscOptionsName("-ts_monitor_lg_solution", "Monitor solution graphically", "TSMonitorLGSolution", &opt));
163: if (opt) {
164: PetscInt howoften = 1;
165: DM dm;
166: PetscBool net;
168: PetscCall(PetscOptionsInt("-ts_monitor_lg_solution", "Monitor solution graphically", "TSMonitorLGSolution", howoften, &howoften, NULL));
169: PetscCall(TSGetDM(ts, &dm));
170: PetscCall(PetscObjectTypeCompare((PetscObject)dm, DMNETWORK, &net));
171: if (net) {
172: TSMonitorLGCtxNetwork ctx;
173: PetscCall(TSMonitorLGCtxNetworkCreate(ts, NULL, NULL, PETSC_DECIDE, PETSC_DECIDE, 600, 400, howoften, &ctx));
174: PetscCall(TSMonitorSet(ts, TSMonitorLGCtxNetworkSolution, ctx, (PetscCtxDestroyFn *)TSMonitorLGCtxNetworkDestroy));
175: PetscCall(PetscOptionsBool("-ts_monitor_lg_solution_semilogy", "Plot the solution with a semi-log axis", "", ctx->semilogy, &ctx->semilogy, NULL));
176: } else {
177: TSMonitorLGCtx ctx;
178: PetscCall(TSMonitorLGCtxCreate(PETSC_COMM_SELF, NULL, NULL, PETSC_DECIDE, PETSC_DECIDE, 400, 300, howoften, &ctx));
179: PetscCall(TSMonitorSet(ts, TSMonitorLGSolution, ctx, (PetscCtxDestroyFn *)TSMonitorLGCtxDestroy));
180: }
181: }
183: PetscCall(PetscOptionsName("-ts_monitor_lg_error", "Monitor error graphically", "TSMonitorLGError", &opt));
184: if (opt) {
185: TSMonitorLGCtx ctx;
186: PetscInt howoften = 1;
188: PetscCall(PetscOptionsInt("-ts_monitor_lg_error", "Monitor error graphically", "TSMonitorLGError", howoften, &howoften, NULL));
189: PetscCall(TSMonitorLGCtxCreate(PETSC_COMM_SELF, NULL, NULL, PETSC_DECIDE, PETSC_DECIDE, 400, 300, howoften, &ctx));
190: PetscCall(TSMonitorSet(ts, TSMonitorLGError, ctx, (PetscCtxDestroyFn *)TSMonitorLGCtxDestroy));
191: }
192: PetscCall(TSMonitorSetFromOptions(ts, "-ts_monitor_error", "View the error at each timestep", "TSMonitorError", TSMonitorError, NULL));
194: PetscCall(PetscOptionsName("-ts_monitor_lg_timestep", "Monitor timestep size graphically", "TSMonitorLGTimeStep", &opt));
195: if (opt) {
196: TSMonitorLGCtx ctx;
197: PetscInt howoften = 1;
199: PetscCall(PetscOptionsInt("-ts_monitor_lg_timestep", "Monitor timestep size graphically", "TSMonitorLGTimeStep", howoften, &howoften, NULL));
200: PetscCall(TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts), NULL, NULL, PETSC_DECIDE, PETSC_DECIDE, 400, 300, howoften, &ctx));
201: PetscCall(TSMonitorSet(ts, TSMonitorLGTimeStep, ctx, (PetscCtxDestroyFn *)TSMonitorLGCtxDestroy));
202: }
203: PetscCall(PetscOptionsName("-ts_monitor_lg_timestep_log", "Monitor log timestep size graphically", "TSMonitorLGTimeStep", &opt));
204: if (opt) {
205: TSMonitorLGCtx ctx;
206: PetscInt howoften = 1;
208: PetscCall(PetscOptionsInt("-ts_monitor_lg_timestep_log", "Monitor log timestep size graphically", "TSMonitorLGTimeStep", howoften, &howoften, NULL));
209: PetscCall(TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts), NULL, NULL, PETSC_DECIDE, PETSC_DECIDE, 400, 300, howoften, &ctx));
210: PetscCall(TSMonitorSet(ts, TSMonitorLGTimeStep, ctx, (PetscCtxDestroyFn *)TSMonitorLGCtxDestroy));
211: ctx->semilogy = PETSC_TRUE;
212: }
214: PetscCall(PetscOptionsName("-ts_monitor_lg_snes_iterations", "Monitor number nonlinear iterations for each timestep graphically", "TSMonitorLGSNESIterations", &opt));
215: if (opt) {
216: TSMonitorLGCtx ctx;
217: PetscInt howoften = 1;
219: PetscCall(PetscOptionsInt("-ts_monitor_lg_snes_iterations", "Monitor number nonlinear iterations for each timestep graphically", "TSMonitorLGSNESIterations", howoften, &howoften, NULL));
220: PetscCall(TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts), NULL, NULL, PETSC_DECIDE, PETSC_DECIDE, 400, 300, howoften, &ctx));
221: PetscCall(TSMonitorSet(ts, TSMonitorLGSNESIterations, ctx, (PetscCtxDestroyFn *)TSMonitorLGCtxDestroy));
222: }
223: PetscCall(PetscOptionsName("-ts_monitor_lg_ksp_iterations", "Monitor number nonlinear iterations for each timestep graphically", "TSMonitorLGKSPIterations", &opt));
224: if (opt) {
225: TSMonitorLGCtx ctx;
226: PetscInt howoften = 1;
228: PetscCall(PetscOptionsInt("-ts_monitor_lg_ksp_iterations", "Monitor number nonlinear iterations for each timestep graphically", "TSMonitorLGKSPIterations", howoften, &howoften, NULL));
229: PetscCall(TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts), NULL, NULL, PETSC_DECIDE, PETSC_DECIDE, 400, 300, howoften, &ctx));
230: PetscCall(TSMonitorSet(ts, TSMonitorLGKSPIterations, ctx, (PetscCtxDestroyFn *)TSMonitorLGCtxDestroy));
231: }
232: PetscCall(PetscOptionsName("-ts_monitor_sp_eig", "Monitor eigenvalues of linearized operator graphically", "TSMonitorSPEig", &opt));
233: if (opt) {
234: TSMonitorSPEigCtx ctx;
235: PetscInt howoften = 1;
237: PetscCall(PetscOptionsInt("-ts_monitor_sp_eig", "Monitor eigenvalues of linearized operator graphically", "TSMonitorSPEig", howoften, &howoften, NULL));
238: PetscCall(TSMonitorSPEigCtxCreate(PETSC_COMM_SELF, NULL, NULL, PETSC_DECIDE, PETSC_DECIDE, 300, 300, howoften, &ctx));
239: PetscCall(TSMonitorSet(ts, TSMonitorSPEig, ctx, (PetscCtxDestroyFn *)TSMonitorSPEigCtxDestroy));
240: }
241: PetscCall(PetscOptionsName("-ts_monitor_sp_swarm", "Display particle phase space from the DMSwarm", "TSMonitorSPSwarm", &opt));
242: if (opt) {
243: TSMonitorSPCtx ctx;
244: PetscInt howoften = 1, retain = 0;
245: PetscBool phase = PETSC_TRUE, create = PETSC_TRUE, multispecies = PETSC_FALSE;
247: for (PetscInt i = 0; i < ts->numbermonitors; ++i)
248: if (ts->monitor[i] == TSMonitorSPSwarmSolution) {
249: create = PETSC_FALSE;
250: break;
251: }
252: if (create) {
253: PetscCall(PetscOptionsInt("-ts_monitor_sp_swarm", "Display particles phase space from the DMSwarm", "TSMonitorSPSwarm", howoften, &howoften, NULL));
254: PetscCall(PetscOptionsInt("-ts_monitor_sp_swarm_retain", "Retain n points plotted to show trajectory, -1 for all points", "TSMonitorSPSwarm", retain, &retain, NULL));
255: PetscCall(PetscOptionsBool("-ts_monitor_sp_swarm_phase", "Plot in phase space rather than coordinate space", "TSMonitorSPSwarm", phase, &phase, NULL));
256: PetscCall(PetscOptionsBool("-ts_monitor_sp_swarm_multi_species", "Color particles by particle species", "TSMonitorSPSwarm", multispecies, &multispecies, NULL));
257: PetscCall(TSMonitorSPCtxCreate(PetscObjectComm((PetscObject)ts), NULL, NULL, PETSC_DECIDE, PETSC_DECIDE, 300, 300, howoften, retain, phase, multispecies, &ctx));
258: PetscCall(TSMonitorSet(ts, TSMonitorSPSwarmSolution, ctx, (PetscCtxDestroyFn *)TSMonitorSPCtxDestroy));
259: }
260: }
261: PetscCall(PetscOptionsName("-ts_monitor_hg_swarm", "Display particle histogram from the DMSwarm", "TSMonitorHGSwarm", &opt));
262: if (opt) {
263: TSMonitorHGCtx ctx;
264: PetscInt howoften = 1, Ns = 1;
265: PetscBool velocity = PETSC_FALSE, create = PETSC_TRUE;
267: for (PetscInt i = 0; i < ts->numbermonitors; ++i)
268: if (ts->monitor[i] == TSMonitorHGSwarmSolution) {
269: create = PETSC_FALSE;
270: break;
271: }
272: if (create) {
273: DM sw, dm;
274: PetscInt Nc, Nb;
276: PetscCall(TSGetDM(ts, &sw));
277: PetscCall(DMSwarmGetCellDM(sw, &dm));
278: PetscCall(DMPlexGetHeightStratum(dm, 0, NULL, &Nc));
279: Nb = PetscMin(20, PetscMax(10, Nc));
280: PetscCall(PetscOptionsInt("-ts_monitor_hg_swarm", "Display particles histogram from the DMSwarm", "TSMonitorHGSwarm", howoften, &howoften, NULL));
281: PetscCall(PetscOptionsBool("-ts_monitor_hg_swarm_velocity", "Plot in velocity space rather than coordinate space", "TSMonitorHGSwarm", velocity, &velocity, NULL));
282: PetscCall(PetscOptionsInt("-ts_monitor_hg_swarm_species", "Number of species to histogram", "TSMonitorHGSwarm", Ns, &Ns, NULL));
283: PetscCall(PetscOptionsInt("-ts_monitor_hg_swarm_bins", "Number of histogram bins", "TSMonitorHGSwarm", Nb, &Nb, NULL));
284: PetscCall(TSMonitorHGCtxCreate(PetscObjectComm((PetscObject)ts), NULL, NULL, PETSC_DECIDE, PETSC_DECIDE, 300, 300, howoften, Ns, Nb, velocity, &ctx));
285: PetscCall(TSMonitorSet(ts, TSMonitorHGSwarmSolution, ctx, (PetscCtxDestroyFn *)TSMonitorHGCtxDestroy));
286: }
287: }
288: opt = PETSC_FALSE;
289: PetscCall(PetscOptionsName("-ts_monitor_draw_solution", "Monitor solution graphically", "TSMonitorDrawSolution", &opt));
290: if (opt) {
291: TSMonitorDrawCtx ctx;
292: PetscInt howoften = 1;
294: PetscCall(PetscOptionsInt("-ts_monitor_draw_solution", "Monitor solution graphically", "TSMonitorDrawSolution", howoften, &howoften, NULL));
295: PetscCall(TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts), NULL, "Computed Solution", PETSC_DECIDE, PETSC_DECIDE, 300, 300, howoften, &ctx));
296: PetscCall(TSMonitorSet(ts, TSMonitorDrawSolution, ctx, (PetscCtxDestroyFn *)TSMonitorDrawCtxDestroy));
297: }
298: opt = PETSC_FALSE;
299: PetscCall(PetscOptionsName("-ts_monitor_draw_solution_phase", "Monitor solution graphically", "TSMonitorDrawSolutionPhase", &opt));
300: if (opt) {
301: TSMonitorDrawCtx ctx;
302: PetscReal bounds[4];
303: PetscInt n = 4;
304: PetscDraw draw;
305: PetscDrawAxis axis;
307: PetscCall(PetscOptionsRealArray("-ts_monitor_draw_solution_phase", "Monitor solution graphically", "TSMonitorDrawSolutionPhase", bounds, &n, NULL));
308: PetscCheck(n == 4, PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_WRONG, "Must provide bounding box of phase field");
309: PetscCall(TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts), NULL, NULL, PETSC_DECIDE, PETSC_DECIDE, 300, 300, 1, &ctx));
310: PetscCall(PetscViewerDrawGetDraw(ctx->viewer, 0, &draw));
311: PetscCall(PetscViewerDrawGetDrawAxis(ctx->viewer, 0, &axis));
312: PetscCall(PetscDrawAxisSetLimits(axis, bounds[0], bounds[2], bounds[1], bounds[3]));
313: PetscCall(PetscDrawAxisSetLabels(axis, "Phase Diagram", "Variable 1", "Variable 2"));
314: PetscCall(TSMonitorSet(ts, TSMonitorDrawSolutionPhase, ctx, (PetscCtxDestroyFn *)TSMonitorDrawCtxDestroy));
315: }
316: opt = PETSC_FALSE;
317: PetscCall(PetscOptionsName("-ts_monitor_draw_error", "Monitor error graphically", "TSMonitorDrawError", &opt));
318: if (opt) {
319: TSMonitorDrawCtx ctx;
320: PetscInt howoften = 1;
322: PetscCall(PetscOptionsInt("-ts_monitor_draw_error", "Monitor error graphically", "TSMonitorDrawError", howoften, &howoften, NULL));
323: PetscCall(TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts), NULL, "Error", PETSC_DECIDE, PETSC_DECIDE, 300, 300, howoften, &ctx));
324: PetscCall(TSMonitorSet(ts, TSMonitorDrawError, ctx, (PetscCtxDestroyFn *)TSMonitorDrawCtxDestroy));
325: }
326: opt = PETSC_FALSE;
327: PetscCall(PetscOptionsName("-ts_monitor_draw_solution_function", "Monitor solution provided by TSMonitorSetSolutionFunction() graphically", "TSMonitorDrawSolutionFunction", &opt));
328: if (opt) {
329: TSMonitorDrawCtx ctx;
330: PetscInt howoften = 1;
332: PetscCall(PetscOptionsInt("-ts_monitor_draw_solution_function", "Monitor solution provided by TSMonitorSetSolutionFunction() graphically", "TSMonitorDrawSolutionFunction", howoften, &howoften, NULL));
333: PetscCall(TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts), NULL, "Solution provided by user function", PETSC_DECIDE, PETSC_DECIDE, 300, 300, howoften, &ctx));
334: PetscCall(TSMonitorSet(ts, TSMonitorDrawSolutionFunction, ctx, (PetscCtxDestroyFn *)TSMonitorDrawCtxDestroy));
335: }
337: opt = PETSC_FALSE;
338: 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));
339: if (flg) {
340: TSMonitorVTKCtx ctx;
342: PetscCall(TSMonitorSolutionVTKCtxCreate(monfilename, &ctx));
343: PetscCall(PetscOptionsInt("-ts_monitor_solution_vtk_interval", "Save every interval time step (-1 for last step only)", NULL, ctx->interval, &ctx->interval, NULL));
344: PetscCall(TSMonitorSet(ts, (PetscErrorCode (*)(TS, PetscInt, PetscReal, Vec, PetscCtx))TSMonitorSolutionVTK, ctx, (PetscCtxDestroyFn *)TSMonitorSolutionVTKDestroy));
345: }
347: PetscCall(PetscOptionsString("-ts_monitor_dmda_ray", "Display a ray of the solution", "None", "y=0", dir, sizeof(dir), &flg));
348: if (flg) {
349: TSMonitorDMDARayCtx *rayctx;
350: int ray = 0;
351: DMDirection ddir;
352: DM da;
353: PetscMPIInt rank;
355: PetscCheck(dir[1] == '=', PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_WRONG, "Unknown ray %s", dir);
356: if (dir[0] == 'x') ddir = DM_X;
357: else if (dir[0] == 'y') ddir = DM_Y;
358: else SETERRQ(PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_WRONG, "Unknown ray %s", dir);
359: sscanf(dir + 2, "%d", &ray);
361: PetscCall(PetscInfo(ts, "Displaying DMDA ray %c = %d\n", dir[0], ray));
362: PetscCall(PetscNew(&rayctx));
363: PetscCall(TSGetDM(ts, &da));
364: PetscCall(DMDAGetRay(da, ddir, ray, &rayctx->ray, &rayctx->scatter));
365: PetscCallMPI(MPI_Comm_rank(PetscObjectComm((PetscObject)ts), &rank));
366: if (rank == 0) PetscCall(PetscViewerDrawOpen(PETSC_COMM_SELF, NULL, NULL, 0, 0, 600, 300, &rayctx->viewer));
367: rayctx->lgctx = NULL;
368: PetscCall(TSMonitorSet(ts, TSMonitorDMDARay, rayctx, TSMonitorDMDARayDestroy));
369: }
370: PetscCall(PetscOptionsString("-ts_monitor_lg_dmda_ray", "Display a ray of the solution", "None", "x=0", dir, sizeof(dir), &flg));
371: if (flg) {
372: TSMonitorDMDARayCtx *rayctx;
373: int ray = 0;
374: DMDirection ddir;
375: DM da;
376: PetscInt howoften = 1;
378: PetscCheck(dir[1] == '=', PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_WRONG, "Malformed ray %s", dir);
379: if (dir[0] == 'x') ddir = DM_X;
380: else if (dir[0] == 'y') ddir = DM_Y;
381: else SETERRQ(PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_WRONG, "Unknown ray direction %s", dir);
382: sscanf(dir + 2, "%d", &ray);
384: PetscCall(PetscInfo(ts, "Displaying LG DMDA ray %c = %d\n", dir[0], ray));
385: PetscCall(PetscNew(&rayctx));
386: PetscCall(TSGetDM(ts, &da));
387: PetscCall(DMDAGetRay(da, ddir, ray, &rayctx->ray, &rayctx->scatter));
388: PetscCall(TSMonitorLGCtxCreate(PETSC_COMM_SELF, NULL, NULL, PETSC_DECIDE, PETSC_DECIDE, 600, 400, howoften, &rayctx->lgctx));
389: PetscCall(TSMonitorSet(ts, TSMonitorLGDMDARay, rayctx, TSMonitorDMDARayDestroy));
390: }
392: PetscCall(PetscOptionsName("-ts_monitor_envelope", "Monitor maximum and minimum value of each component of the solution", "TSMonitorEnvelope", &opt));
393: if (opt) {
394: TSMonitorEnvelopeCtx ctx;
396: PetscCall(TSMonitorEnvelopeCtxCreate(ts, &ctx));
397: PetscCall(TSMonitorSet(ts, TSMonitorEnvelope, ctx, (PetscCtxDestroyFn *)TSMonitorEnvelopeCtxDestroy));
398: }
399: flg = PETSC_FALSE;
400: PetscCall(PetscOptionsBool("-ts_monitor_cancel", "Remove all monitors", "TSMonitorCancel", flg, &flg, &opt));
401: if (opt && flg) PetscCall(TSMonitorCancel(ts));
403: flg = PETSC_FALSE;
404: PetscCall(PetscOptionsBool("-ts_fd_color", "Use finite differences with coloring to compute IJacobian", "TSComputeIJacobianDefaultColor", flg, &flg, NULL));
405: if (flg) {
406: DM dm;
408: PetscCall(TSGetDM(ts, &dm));
409: PetscCall(DMTSUnsetIJacobianContext_Internal(dm));
410: PetscCall(TSSetIJacobian(ts, NULL, NULL, TSComputeIJacobianDefaultColor, NULL));
411: PetscCall(PetscInfo(ts, "Setting default finite difference coloring Jacobian matrix\n"));
412: }
414: /* Handle specific TS options */
415: PetscTryTypeMethod(ts, setfromoptions, PetscOptionsObject);
417: /* Handle TSAdapt options */
418: PetscCall(TSGetAdapt(ts, &ts->adapt));
419: PetscCall(TSAdaptSetDefaultType(ts->adapt, ts->default_adapt_type));
420: PetscCall(TSAdaptSetFromOptions(ts->adapt, PetscOptionsObject));
422: /* TS trajectory must be set after TS, since it may use some TS options above */
423: tflg = ts->trajectory ? PETSC_TRUE : PETSC_FALSE;
424: PetscCall(PetscOptionsBool("-ts_save_trajectory", "Save the solution at each timestep", "TSSetSaveTrajectory", tflg, &tflg, NULL));
425: if (tflg) PetscCall(TSSetSaveTrajectory(ts));
427: PetscCall(TSAdjointSetFromOptions(ts, PetscOptionsObject));
429: /* process any options handlers added with PetscObjectAddOptionsHandler() */
430: PetscCall(PetscObjectProcessOptionsHandlers((PetscObject)ts, PetscOptionsObject));
431: PetscOptionsEnd();
433: if (ts->trajectory) PetscCall(TSTrajectorySetFromOptions(ts->trajectory, ts));
435: /* why do we have to do this here and not during TSSetUp? */
436: PetscCall(TSGetSNES(ts, &ts->snes));
437: if (ts->problem_type == TS_LINEAR) {
438: PetscCall(PetscObjectTypeCompareAny((PetscObject)ts->snes, &flg, SNESKSPONLY, SNESKSPTRANSPOSEONLY, ""));
439: if (!flg) PetscCall(SNESSetType(ts->snes, SNESKSPONLY));
440: }
441: PetscCall(SNESSetFromOptions(ts->snes));
442: PetscFunctionReturn(PETSC_SUCCESS);
443: }
445: /*@
446: TSGetTrajectory - Gets the trajectory from a `TS` if it exists
448: Collective
450: Input Parameter:
451: . ts - the `TS` context obtained from `TSCreate()`
453: Output Parameter:
454: . tr - the `TSTrajectory` object, if it exists
456: Level: advanced
458: Note:
459: This routine should be called after all `TS` options have been set
461: .seealso: [](ch_ts), `TS`, `TSTrajectory`, `TSAdjointSolve()`, `TSTrajectoryCreate()`
462: @*/
463: PetscErrorCode TSGetTrajectory(TS ts, TSTrajectory *tr)
464: {
465: PetscFunctionBegin;
467: *tr = ts->trajectory;
468: PetscFunctionReturn(PETSC_SUCCESS);
469: }
471: /*@
472: TSSetSaveTrajectory - Causes the `TS` to save its solutions as it iterates forward in time in a `TSTrajectory` object
474: Collective
476: Input Parameter:
477: . ts - the `TS` context obtained from `TSCreate()`
479: Options Database Keys:
480: + -ts_save_trajectory - saves the trajectory to a file
481: - -ts_trajectory_type type - set trajectory type
483: Level: intermediate
485: Notes:
486: This routine should be called after all `TS` options have been set
488: The `TSTRAJECTORYVISUALIZATION` files can be loaded into Python with $PETSC_DIR/lib/petsc/bin/PetscBinaryIOTrajectory.py and
489: MATLAB with $PETSC_DIR/share/petsc/matlab/PetscReadBinaryTrajectory.m
491: .seealso: [](ch_ts), `TS`, `TSTrajectory`, `TSGetTrajectory()`, `TSAdjointSolve()`
492: @*/
493: PetscErrorCode TSSetSaveTrajectory(TS ts)
494: {
495: PetscFunctionBegin;
497: if (!ts->trajectory) PetscCall(TSTrajectoryCreate(PetscObjectComm((PetscObject)ts), &ts->trajectory));
498: PetscFunctionReturn(PETSC_SUCCESS);
499: }
501: /*@
502: TSResetTrajectory - Destroys and recreates the internal `TSTrajectory` object
504: Collective
506: Input Parameter:
507: . ts - the `TS` context obtained from `TSCreate()`
509: Level: intermediate
511: .seealso: [](ch_ts), `TSTrajectory`, `TSGetTrajectory()`, `TSAdjointSolve()`, `TSRemoveTrajectory()`
512: @*/
513: PetscErrorCode TSResetTrajectory(TS ts)
514: {
515: PetscFunctionBegin;
517: if (ts->trajectory) {
518: PetscCall(TSTrajectoryDestroy(&ts->trajectory));
519: PetscCall(TSTrajectoryCreate(PetscObjectComm((PetscObject)ts), &ts->trajectory));
520: }
521: PetscFunctionReturn(PETSC_SUCCESS);
522: }
524: /*@
525: TSRemoveTrajectory - Destroys and removes the internal `TSTrajectory` object from a `TS`
527: Collective
529: Input Parameter:
530: . ts - the `TS` context obtained from `TSCreate()`
532: Level: intermediate
534: .seealso: [](ch_ts), `TSTrajectory`, `TSResetTrajectory()`, `TSAdjointSolve()`
535: @*/
536: PetscErrorCode TSRemoveTrajectory(TS ts)
537: {
538: PetscFunctionBegin;
540: PetscCall(TSTrajectoryDestroy(&ts->trajectory));
541: PetscFunctionReturn(PETSC_SUCCESS);
542: }
544: /*@
545: TSComputeRHSJacobian - Computes the Jacobian matrix that has been
546: set with `TSSetRHSJacobian()`.
548: Collective
550: Input Parameters:
551: + ts - the `TS` context
552: . t - current timestep
553: - U - input vector
555: Output Parameters:
556: + A - Jacobian matrix
557: - B - optional matrix used to compute the preconditioner, often the same as `A`
559: Level: developer
561: Note:
562: Most users should not need to explicitly call this routine, as it
563: is used internally within the ODE integrators.
565: .seealso: [](ch_ts), `TS`, `TSSetRHSJacobian()`, `KSPSetOperators()`
566: @*/
567: PetscErrorCode TSComputeRHSJacobian(TS ts, PetscReal t, Vec U, Mat A, Mat B)
568: {
569: PetscObjectState Ustate;
570: PetscObjectId Uid;
571: DM dm;
572: DMTS tsdm;
573: TSRHSJacobianFn *rhsjacobianfunc;
574: void *ctx;
575: TSRHSFunctionFn *rhsfunction;
577: PetscFunctionBegin;
580: PetscCheckSameComm(ts, 1, U, 3);
581: PetscCall(TSGetDM(ts, &dm));
582: PetscCall(DMGetDMTS(dm, &tsdm));
583: PetscCall(DMTSGetRHSFunction(dm, &rhsfunction, NULL));
584: PetscCall(DMTSGetRHSJacobian(dm, &rhsjacobianfunc, &ctx));
585: PetscCall(PetscObjectStateGet((PetscObject)U, &Ustate));
586: PetscCall(PetscObjectGetId((PetscObject)U, &Uid));
588: if (ts->rhsjacobian.time == t && (ts->problem_type == TS_LINEAR || (ts->rhsjacobian.Xid == Uid && ts->rhsjacobian.Xstate == Ustate)) && (rhsfunction != TSComputeRHSFunctionLinear)) PetscFunctionReturn(PETSC_SUCCESS);
590: 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);
591: if (rhsjacobianfunc) {
592: PetscCall(PetscLogEventBegin(TS_JacobianEval, U, ts, A, B));
593: PetscCallBack("TS callback Jacobian", (*rhsjacobianfunc)(ts, t, U, A, B, ctx));
594: ts->rhsjacs++;
595: PetscCall(PetscLogEventEnd(TS_JacobianEval, U, ts, A, B));
596: } else {
597: PetscCall(MatZeroEntries(A));
598: if (B && A != B) PetscCall(MatZeroEntries(B));
599: }
600: ts->rhsjacobian.time = t;
601: ts->rhsjacobian.shift = 0;
602: ts->rhsjacobian.scale = 1.;
603: PetscCall(PetscObjectGetId((PetscObject)U, &ts->rhsjacobian.Xid));
604: PetscCall(PetscObjectStateGet((PetscObject)U, &ts->rhsjacobian.Xstate));
605: PetscFunctionReturn(PETSC_SUCCESS);
606: }
608: /*@
609: TSComputeRHSFunction - Evaluates the right-hand-side function for a `TS`
611: Collective
613: Input Parameters:
614: + ts - the `TS` context
615: . t - current time
616: - U - state vector
618: Output Parameter:
619: . y - right-hand side
621: Level: developer
623: Note:
624: Most users should not need to explicitly call this routine, as it
625: is used internally within the nonlinear solvers.
627: .seealso: [](ch_ts), `TS`, `TSSetRHSFunction()`, `TSComputeIFunction()`
628: @*/
629: PetscErrorCode TSComputeRHSFunction(TS ts, PetscReal t, Vec U, Vec y)
630: {
631: TSRHSFunctionFn *rhsfunction;
632: TSIFunctionFn *ifunction;
633: void *ctx;
634: DM dm;
636: PetscFunctionBegin;
640: PetscCall(TSGetDM(ts, &dm));
641: PetscCall(DMTSGetRHSFunction(dm, &rhsfunction, &ctx));
642: PetscCall(DMTSGetIFunction(dm, &ifunction, NULL));
644: PetscCheck(rhsfunction || ifunction, PetscObjectComm((PetscObject)ts), PETSC_ERR_USER, "Must call TSSetRHSFunction() and / or TSSetIFunction()");
646: if (rhsfunction) {
647: PetscCall(PetscLogEventBegin(TS_FunctionEval, U, ts, y, 0));
648: PetscCall(VecLockReadPush(U));
649: PetscCallBack("TS callback right-hand-side", (*rhsfunction)(ts, t, U, y, ctx));
650: PetscCall(VecLockReadPop(U));
651: ts->rhsfuncs++;
652: PetscCall(PetscLogEventEnd(TS_FunctionEval, U, ts, y, 0));
653: } else PetscCall(VecZeroEntries(y));
654: PetscFunctionReturn(PETSC_SUCCESS);
655: }
657: /*@
658: TSComputeSolutionFunction - Evaluates the solution function.
660: Collective
662: Input Parameters:
663: + ts - the `TS` context
664: - t - current time
666: Output Parameter:
667: . U - the solution
669: Level: developer
671: .seealso: [](ch_ts), `TS`, `TSSetSolutionFunction()`, `TSSetRHSFunction()`, `TSComputeIFunction()`
672: @*/
673: PetscErrorCode TSComputeSolutionFunction(TS ts, PetscReal t, Vec U)
674: {
675: TSSolutionFn *solutionfunction;
676: void *ctx;
677: DM dm;
679: PetscFunctionBegin;
682: PetscCall(TSGetDM(ts, &dm));
683: PetscCall(DMTSGetSolutionFunction(dm, &solutionfunction, &ctx));
684: if (solutionfunction) PetscCallBack("TS callback solution", (*solutionfunction)(ts, t, U, ctx));
685: PetscFunctionReturn(PETSC_SUCCESS);
686: }
687: /*@
688: TSComputeForcingFunction - Evaluates the forcing function.
690: Collective
692: Input Parameters:
693: + ts - the `TS` context
694: - t - current time
696: Output Parameter:
697: . U - the function value
699: Level: developer
701: .seealso: [](ch_ts), `TS`, `TSSetSolutionFunction()`, `TSSetRHSFunction()`, `TSComputeIFunction()`
702: @*/
703: PetscErrorCode TSComputeForcingFunction(TS ts, PetscReal t, Vec U)
704: {
705: void *ctx;
706: DM dm;
707: TSForcingFn *forcing;
709: PetscFunctionBegin;
712: PetscCall(TSGetDM(ts, &dm));
713: PetscCall(DMTSGetForcingFunction(dm, &forcing, &ctx));
715: if (forcing) PetscCallBack("TS callback forcing function", (*forcing)(ts, t, U, ctx));
716: PetscFunctionReturn(PETSC_SUCCESS);
717: }
719: PetscErrorCode TSGetRHSMats_Private(TS ts, Mat *Arhs, Mat *Brhs)
720: {
721: Mat A, B;
722: TSIJacobianFn *ijacobian;
724: PetscFunctionBegin;
725: if (Arhs) *Arhs = NULL;
726: if (Brhs) *Brhs = NULL;
727: PetscCall(TSGetIJacobian(ts, &A, &B, &ijacobian, NULL));
728: if (Arhs) {
729: if (!ts->Arhs) {
730: if (ijacobian) {
731: PetscCall(MatDuplicate(A, MAT_DO_NOT_COPY_VALUES, &ts->Arhs));
732: PetscCall(TSSetMatStructure(ts, SAME_NONZERO_PATTERN));
733: } else {
734: ts->Arhs = A;
735: PetscCall(PetscObjectReference((PetscObject)A));
736: }
737: } else {
738: PetscBool flg;
739: PetscCall(SNESGetUseMatrixFree(ts->snes, NULL, &flg));
740: /* Handle case where user provided only RHSJacobian and used -snes_mf_operator */
741: if (flg && !ijacobian && ts->Arhs == ts->Brhs) {
742: PetscCall(PetscObjectDereference((PetscObject)ts->Arhs));
743: ts->Arhs = A;
744: PetscCall(PetscObjectReference((PetscObject)A));
745: }
746: }
747: *Arhs = ts->Arhs;
748: }
749: if (Brhs) {
750: if (!ts->Brhs) {
751: if (A != B) {
752: if (ijacobian) {
753: PetscCall(MatDuplicate(B, MAT_DO_NOT_COPY_VALUES, &ts->Brhs));
754: } else {
755: ts->Brhs = B;
756: PetscCall(PetscObjectReference((PetscObject)B));
757: }
758: } else {
759: PetscCall(PetscObjectReference((PetscObject)ts->Arhs));
760: ts->Brhs = ts->Arhs;
761: }
762: }
763: *Brhs = ts->Brhs;
764: }
765: PetscFunctionReturn(PETSC_SUCCESS);
766: }
768: /*@
769: TSComputeIFunction - Evaluates the DAE residual written in the implicit form F(t,U,Udot)=0
771: Collective
773: Input Parameters:
774: + ts - the `TS` context
775: . t - current time
776: . U - state vector
777: . Udot - time derivative of state vector
778: - imex - flag indicates if the method is `TSARKIMEX` so that the RHSFunction should be kept separate
780: Output Parameter:
781: . Y - right-hand side
783: Level: developer
785: Note:
786: Most users should not need to explicitly call this routine, as it
787: is used internally within the nonlinear solvers.
789: If the user did not write their equations in implicit form, this
790: function recasts them in implicit form.
792: .seealso: [](ch_ts), `TS`, `TSSetIFunction()`, `TSComputeRHSFunction()`
793: @*/
794: PetscErrorCode TSComputeIFunction(TS ts, PetscReal t, Vec U, Vec Udot, Vec Y, PetscBool imex)
795: {
796: TSIFunctionFn *ifunction;
797: TSRHSFunctionFn *rhsfunction;
798: void *ctx;
799: DM dm;
801: PetscFunctionBegin;
807: PetscCall(TSGetDM(ts, &dm));
808: PetscCall(DMTSGetIFunction(dm, &ifunction, &ctx));
809: PetscCall(DMTSGetRHSFunction(dm, &rhsfunction, NULL));
811: PetscCheck(rhsfunction || ifunction, PetscObjectComm((PetscObject)ts), PETSC_ERR_USER, "Must call TSSetRHSFunction() and / or TSSetIFunction()");
813: PetscCall(PetscLogEventBegin(TS_FunctionEval, U, ts, Udot, Y));
814: if (ifunction) {
815: PetscCallBack("TS callback implicit function", (*ifunction)(ts, t, U, Udot, Y, ctx));
816: ts->ifuncs++;
817: }
818: if (imex) {
819: if (!ifunction) PetscCall(VecCopy(Udot, Y));
820: } else if (rhsfunction) {
821: if (ifunction) {
822: Vec Frhs;
824: PetscCall(DMGetGlobalVector(dm, &Frhs));
825: PetscCall(TSComputeRHSFunction(ts, t, U, Frhs));
826: PetscCall(VecAXPY(Y, -1, Frhs));
827: PetscCall(DMRestoreGlobalVector(dm, &Frhs));
828: } else {
829: PetscCall(TSComputeRHSFunction(ts, t, U, Y));
830: PetscCall(VecAYPX(Y, -1, Udot));
831: }
832: }
833: PetscCall(PetscLogEventEnd(TS_FunctionEval, U, ts, Udot, Y));
834: PetscFunctionReturn(PETSC_SUCCESS);
835: }
837: /*
838: TSRecoverRHSJacobian - Recover the Jacobian matrix so that one can call `TSComputeRHSJacobian()` on it.
840: Note:
841: This routine is needed when one switches from `TSComputeIJacobian()` to `TSComputeRHSJacobian()` because the Jacobian matrix may be shifted or scaled in `TSComputeIJacobian()`.
843: */
844: static PetscErrorCode TSRecoverRHSJacobian(TS ts, Mat A, Mat B)
845: {
846: PetscFunctionBegin;
848: PetscCheck(A == ts->Arhs, PetscObjectComm((PetscObject)ts), PETSC_ERR_SUP, "Invalid Amat");
849: PetscCheck(B == ts->Brhs, PetscObjectComm((PetscObject)ts), PETSC_ERR_SUP, "Invalid Bmat");
851: if (ts->rhsjacobian.shift) PetscCall(MatShift(A, -ts->rhsjacobian.shift));
852: if (ts->rhsjacobian.scale == -1.) PetscCall(MatScale(A, -1));
853: if (B && B == ts->Brhs && A != B) {
854: if (ts->rhsjacobian.shift) PetscCall(MatShift(B, -ts->rhsjacobian.shift));
855: if (ts->rhsjacobian.scale == -1.) PetscCall(MatScale(B, -1));
856: }
857: ts->rhsjacobian.shift = 0;
858: ts->rhsjacobian.scale = 1.;
859: PetscFunctionReturn(PETSC_SUCCESS);
860: }
862: /*@
863: TSComputeIJacobian - Evaluates the Jacobian of the DAE
865: Collective
867: Input Parameters:
868: + ts - the `TS` context
869: . t - current timestep
870: . U - state vector
871: . Udot - time derivative of state vector
872: . shift - shift to apply, see note below
873: - imex - flag indicates if the method is `TSARKIMEX` so that the RHSJacobian should be kept separate
875: Output Parameters:
876: + A - Jacobian matrix
877: - B - matrix from which the preconditioner is constructed; often the same as `A`
879: Level: developer
881: Notes:
882: If $ F(t,U,\dot{U})=0 $ is the DAE, the required Jacobian is
883: .vb
884: dF/dU + shift*dF/dUdot
885: .ve
886: Most users should not need to explicitly call this routine, as it
887: is used internally within the nonlinear solvers.
889: .seealso: [](ch_ts), `TS`, `TSSetIJacobian()`
890: @*/
891: PetscErrorCode TSComputeIJacobian(TS ts, PetscReal t, Vec U, Vec Udot, PetscReal shift, Mat A, Mat B, PetscBool imex)
892: {
893: TSIJacobianFn *ijacobian;
894: TSRHSJacobianFn *rhsjacobian;
895: DM dm;
896: void *ctx;
898: PetscFunctionBegin;
905: PetscCall(TSGetDM(ts, &dm));
906: PetscCall(DMTSGetIJacobian(dm, &ijacobian, &ctx));
907: PetscCall(DMTSGetRHSJacobian(dm, &rhsjacobian, NULL));
909: PetscCheck(rhsjacobian || ijacobian, PetscObjectComm((PetscObject)ts), PETSC_ERR_USER, "Must call TSSetRHSJacobian() and / or TSSetIJacobian()");
911: PetscCall(PetscLogEventBegin(TS_JacobianEval, U, ts, A, B));
912: if (ijacobian) {
913: PetscCallBack("TS callback implicit Jacobian", (*ijacobian)(ts, t, U, Udot, shift, A, B, ctx));
914: ts->ijacs++;
915: }
916: if (imex) {
917: if (!ijacobian) { /* system was written as Udot = G(t,U) */
918: PetscBool assembled;
919: if (rhsjacobian) {
920: Mat Arhs = NULL;
921: PetscCall(TSGetRHSMats_Private(ts, &Arhs, NULL));
922: if (A == Arhs) {
923: 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 */
924: ts->rhsjacobian.time = PETSC_MIN_REAL;
925: }
926: }
927: PetscCall(MatZeroEntries(A));
928: PetscCall(MatAssembled(A, &assembled));
929: if (!assembled) {
930: PetscCall(MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY));
931: PetscCall(MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY));
932: }
933: PetscCall(MatShift(A, shift));
934: if (A != B) {
935: PetscCall(MatZeroEntries(B));
936: PetscCall(MatAssembled(B, &assembled));
937: if (!assembled) {
938: PetscCall(MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY));
939: PetscCall(MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY));
940: }
941: PetscCall(MatShift(B, shift));
942: }
943: }
944: } else {
945: Mat Arhs = NULL, Brhs = NULL;
947: /* RHSJacobian needs to be converted to part of IJacobian if exists */
948: if (rhsjacobian) PetscCall(TSGetRHSMats_Private(ts, &Arhs, &Brhs));
949: if (Arhs == A) { /* No IJacobian matrix, so we only have the RHS matrix */
950: PetscObjectState Ustate;
951: PetscObjectId Uid;
952: TSRHSFunctionFn *rhsfunction;
954: PetscCall(DMTSGetRHSFunction(dm, &rhsfunction, NULL));
955: PetscCall(PetscObjectStateGet((PetscObject)U, &Ustate));
956: PetscCall(PetscObjectGetId((PetscObject)U, &Uid));
957: if ((rhsjacobian == TSComputeRHSJacobianConstant || (ts->rhsjacobian.time == t && (ts->problem_type == TS_LINEAR || (ts->rhsjacobian.Xid == Uid && ts->rhsjacobian.Xstate == Ustate)) && rhsfunction != TSComputeRHSFunctionLinear)) &&
958: ts->rhsjacobian.scale == -1.) { /* No need to recompute RHSJacobian */
959: PetscCall(MatShift(A, shift - ts->rhsjacobian.shift)); /* revert the old shift and add the new shift with a single call to MatShift */
960: if (A != B) PetscCall(MatShift(B, shift - ts->rhsjacobian.shift));
961: } else {
962: PetscBool flg;
964: if (ts->rhsjacobian.reuse) { /* Undo the damage */
965: /* MatScale has a short path for this case.
966: However, this code path is taken the first time TSComputeRHSJacobian is called
967: and the matrices have not been assembled yet */
968: PetscCall(TSRecoverRHSJacobian(ts, A, B));
969: }
970: PetscCall(TSComputeRHSJacobian(ts, t, U, A, B));
971: PetscCall(SNESGetUseMatrixFree(ts->snes, NULL, &flg));
972: /* since -snes_mf_operator uses the full SNES function it does not need to be shifted or scaled here */
973: if (!flg) {
974: PetscCall(MatScale(A, -1));
975: PetscCall(MatShift(A, shift));
976: }
977: if (A != B) {
978: PetscCall(MatScale(B, -1));
979: PetscCall(MatShift(B, shift));
980: }
981: }
982: ts->rhsjacobian.scale = -1;
983: ts->rhsjacobian.shift = shift;
984: } else if (Arhs) { /* Both IJacobian and RHSJacobian */
985: if (!ijacobian) { /* No IJacobian provided, but we have a separate RHS matrix */
986: PetscCall(MatZeroEntries(A));
987: PetscCall(MatShift(A, shift));
988: if (A != B) {
989: PetscCall(MatZeroEntries(B));
990: PetscCall(MatShift(B, shift));
991: }
992: }
993: PetscCall(TSComputeRHSJacobian(ts, t, U, Arhs, Brhs));
994: PetscCall(MatAXPY(A, -1, Arhs, ts->axpy_pattern));
995: if (A != B) PetscCall(MatAXPY(B, -1, Brhs, ts->axpy_pattern));
996: }
997: }
998: PetscCall(PetscLogEventEnd(TS_JacobianEval, U, ts, A, B));
999: PetscFunctionReturn(PETSC_SUCCESS);
1000: }
1002: /*@C
1003: TSSetRHSFunction - Sets the routine for evaluating the function,
1004: where U_t = G(t,u).
1006: Logically Collective
1008: Input Parameters:
1009: + ts - the `TS` context obtained from `TSCreate()`
1010: . r - vector to put the computed right-hand side (or `NULL` to have it created)
1011: . f - routine for evaluating the right-hand-side function
1012: - ctx - [optional] user-defined context for private data for the function evaluation routine (may be `NULL`)
1014: Level: beginner
1016: Note:
1017: You must call this function or `TSSetIFunction()` to define your ODE. You cannot use this function when solving a DAE.
1019: .seealso: [](ch_ts), `TS`, `TSRHSFunctionFn`, `TSSetRHSJacobian()`, `TSSetIJacobian()`, `TSSetIFunction()`
1020: @*/
1021: PetscErrorCode TSSetRHSFunction(TS ts, Vec r, TSRHSFunctionFn *f, PetscCtx ctx)
1022: {
1023: SNES snes;
1024: Vec ralloc = NULL;
1025: DM dm;
1027: PetscFunctionBegin;
1031: PetscCall(TSGetDM(ts, &dm));
1032: PetscCall(DMTSSetRHSFunction(dm, f, ctx));
1033: PetscCall(TSGetSNES(ts, &snes));
1034: if (!r && !ts->dm && ts->vec_sol) {
1035: PetscCall(VecDuplicate(ts->vec_sol, &ralloc));
1036: r = ralloc;
1037: }
1038: PetscCall(SNESSetFunction(snes, r, SNESTSFormFunction, ts));
1039: PetscCall(VecDestroy(&ralloc));
1040: PetscFunctionReturn(PETSC_SUCCESS);
1041: }
1043: /*@C
1044: TSSetSolutionFunction - Provide a function that computes the solution of the ODE or DAE
1046: Logically Collective
1048: Input Parameters:
1049: + ts - the `TS` context obtained from `TSCreate()`
1050: . f - routine for evaluating the solution
1051: - ctx - [optional] user-defined context for private data for the
1052: function evaluation routine (may be `NULL`)
1054: Options Database Keys:
1055: + -ts_monitor_lg_error - create a graphical monitor of error history, requires user to have provided `TSSetSolutionFunction()`
1056: - -ts_monitor_draw_error - Monitor error graphically, requires user to have provided `TSSetSolutionFunction()`
1058: Level: intermediate
1060: Notes:
1061: This routine is used for testing accuracy of time integration schemes when you already know the solution.
1062: If analytic solutions are not known for your system, consider using the Method of Manufactured Solutions to
1063: create closed-form solutions with non-physical forcing terms.
1065: For low-dimensional problems solved in serial, such as small discrete systems, `TSMonitorLGError()` can be used to monitor the error history.
1067: .seealso: [](ch_ts), `TS`, `TSSolutionFn`, `TSSetRHSJacobian()`, `TSSetIJacobian()`, `TSComputeSolutionFunction()`, `TSSetForcingFunction()`, `TSSetSolution()`, `TSGetSolution()`, `TSMonitorLGError()`, `TSMonitorDrawError()`
1068: @*/
1069: PetscErrorCode TSSetSolutionFunction(TS ts, TSSolutionFn *f, PetscCtx ctx)
1070: {
1071: DM dm;
1073: PetscFunctionBegin;
1075: PetscCall(TSGetDM(ts, &dm));
1076: PetscCall(DMTSSetSolutionFunction(dm, f, ctx));
1077: PetscFunctionReturn(PETSC_SUCCESS);
1078: }
1080: /*@C
1081: TSSetForcingFunction - Provide a function that computes a forcing term for a ODE or PDE
1083: Logically Collective
1085: Input Parameters:
1086: + ts - the `TS` context obtained from `TSCreate()`
1087: . func - routine for evaluating the forcing function
1088: - ctx - [optional] user-defined context for private data for the function evaluation routine
1089: (may be `NULL`)
1091: Level: intermediate
1093: Notes:
1094: This routine is useful for testing accuracy of time integration schemes when using the Method of Manufactured Solutions to
1095: create closed-form solutions with a non-physical forcing term. It allows you to use the Method of Manufactored Solution without directly editing the
1096: definition of the problem you are solving and hence possibly introducing bugs.
1098: This replaces the ODE F(u,u_t,t) = 0 the `TS` is solving with F(u,u_t,t) - func(t) = 0
1100: This forcing function does not depend on the solution to the equations, it can only depend on spatial location, time, and possibly parameters, the
1101: parameters can be passed in the ctx variable.
1103: For low-dimensional problems solved in serial, such as small discrete systems, `TSMonitorLGError()` can be used to monitor the error history.
1105: .seealso: [](ch_ts), `TS`, `TSForcingFn`, `TSSetRHSJacobian()`, `TSSetIJacobian()`,
1106: `TSComputeSolutionFunction()`, `TSSetSolutionFunction()`
1107: @*/
1108: PetscErrorCode TSSetForcingFunction(TS ts, TSForcingFn *func, PetscCtx ctx)
1109: {
1110: DM dm;
1112: PetscFunctionBegin;
1114: PetscCall(TSGetDM(ts, &dm));
1115: PetscCall(DMTSSetForcingFunction(dm, func, ctx));
1116: PetscFunctionReturn(PETSC_SUCCESS);
1117: }
1119: /*@C
1120: TSSetRHSJacobian - Sets the function to compute the Jacobian of G,
1121: where U_t = G(U,t), as well as the location to store the matrix.
1123: Logically Collective
1125: Input Parameters:
1126: + ts - the `TS` context obtained from `TSCreate()`
1127: . Amat - (approximate) location to store Jacobian matrix entries computed by `f`
1128: . Pmat - matrix from which preconditioner is to be constructed (usually the same as `Amat`)
1129: . f - the Jacobian evaluation routine
1130: - ctx - [optional] user-defined context for private data for the Jacobian evaluation routine (may be `NULL`)
1132: Level: beginner
1134: Notes:
1135: You must set all the diagonal entries of the matrices, if they are zero you must still set them with a zero value
1137: The `TS` solver may modify the nonzero structure and the entries of the matrices `Amat` and `Pmat` between the calls to `f()`
1138: You should not assume the values are the same in the next call to f() as you set them in the previous call.
1140: .seealso: [](ch_ts), `TS`, `TSRHSJacobianFn`, `SNESComputeJacobianDefaultColor()`,
1141: `TSSetRHSFunction()`, `TSRHSJacobianSetReuse()`, `TSSetIJacobian()`, `TSRHSFunctionFn`, `TSIFunctionFn`
1142: @*/
1143: PetscErrorCode TSSetRHSJacobian(TS ts, Mat Amat, Mat Pmat, TSRHSJacobianFn *f, PetscCtx ctx)
1144: {
1145: SNES snes;
1146: DM dm;
1147: TSIJacobianFn *ijacobian;
1149: PetscFunctionBegin;
1153: if (Amat) PetscCheckSameComm(ts, 1, Amat, 2);
1154: if (Pmat) PetscCheckSameComm(ts, 1, Pmat, 3);
1156: PetscCall(TSGetDM(ts, &dm));
1157: PetscCall(DMTSSetRHSJacobian(dm, f, ctx));
1158: PetscCall(DMTSGetIJacobian(dm, &ijacobian, NULL));
1159: PetscCall(TSGetSNES(ts, &snes));
1160: if (!ijacobian) PetscCall(SNESSetJacobian(snes, Amat, Pmat, SNESTSFormJacobian, ts));
1161: if (Amat) {
1162: PetscCall(PetscObjectReference((PetscObject)Amat));
1163: PetscCall(MatDestroy(&ts->Arhs));
1164: ts->Arhs = Amat;
1165: }
1166: if (Pmat) {
1167: PetscCall(PetscObjectReference((PetscObject)Pmat));
1168: PetscCall(MatDestroy(&ts->Brhs));
1169: ts->Brhs = Pmat;
1170: }
1171: PetscFunctionReturn(PETSC_SUCCESS);
1172: }
1174: /*@C
1175: TSSetIFunction - Set the function to compute F(t,U,U_t) where F() = 0 is the DAE to be solved.
1177: Logically Collective
1179: Input Parameters:
1180: + ts - the `TS` context obtained from `TSCreate()`
1181: . r - vector to hold the residual (or `NULL` to have it created internally)
1182: . f - the function evaluation routine
1183: - ctx - user-defined context for private data for the function evaluation routine (may be `NULL`)
1185: Level: beginner
1187: Note:
1188: The user MUST call either this routine or `TSSetRHSFunction()` to define the ODE. When solving DAEs you must use this function.
1190: .seealso: [](ch_ts), `TS`, `TSIFunctionFn`, `TSSetRHSJacobian()`, `TSSetRHSFunction()`,
1191: `TSSetIJacobian()`
1192: @*/
1193: PetscErrorCode TSSetIFunction(TS ts, Vec r, TSIFunctionFn *f, PetscCtx ctx)
1194: {
1195: SNES snes;
1196: Vec ralloc = NULL;
1197: DM dm;
1199: PetscFunctionBegin;
1203: PetscCall(TSGetDM(ts, &dm));
1204: PetscCall(DMTSSetIFunction(dm, f, ctx));
1206: PetscCall(TSGetSNES(ts, &snes));
1207: if (!r && !ts->dm && ts->vec_sol) {
1208: PetscCall(VecDuplicate(ts->vec_sol, &ralloc));
1209: r = ralloc;
1210: }
1211: PetscCall(SNESSetFunction(snes, r, SNESTSFormFunction, ts));
1212: PetscCall(VecDestroy(&ralloc));
1213: PetscFunctionReturn(PETSC_SUCCESS);
1214: }
1216: /*@C
1217: TSGetIFunction - Returns the vector where the implicit residual is stored and the function/context to compute it.
1219: Not Collective
1221: Input Parameter:
1222: . ts - the `TS` context
1224: Output Parameters:
1225: + r - vector to hold residual (or `NULL`)
1226: . func - the function to compute residual (or `NULL`)
1227: - ctx - the function context (or `NULL`)
1229: Level: advanced
1231: .seealso: [](ch_ts), `TS`, `TSSetIFunction()`, `SNESGetFunction()`
1232: @*/
1233: PetscErrorCode TSGetIFunction(TS ts, Vec *r, TSIFunctionFn **func, PetscCtxRt ctx)
1234: {
1235: SNES snes;
1236: DM dm;
1238: PetscFunctionBegin;
1240: PetscCall(TSGetSNES(ts, &snes));
1241: PetscCall(SNESGetFunction(snes, r, NULL, NULL));
1242: PetscCall(TSGetDM(ts, &dm));
1243: PetscCall(DMTSGetIFunction(dm, func, ctx));
1244: PetscFunctionReturn(PETSC_SUCCESS);
1245: }
1247: /*@C
1248: TSGetRHSFunction - Returns the vector where the right-hand side is stored and the function/context to compute it.
1250: Not Collective
1252: Input Parameter:
1253: . ts - the `TS` context
1255: Output Parameters:
1256: + r - vector to hold computed right-hand side (or `NULL`)
1257: . func - the function to compute right-hand side (or `NULL`)
1258: - ctx - the function context (or `NULL`)
1260: Level: advanced
1262: .seealso: [](ch_ts), `TS`, `TSSetRHSFunction()`, `SNESGetFunction()`
1263: @*/
1264: PetscErrorCode TSGetRHSFunction(TS ts, Vec *r, TSRHSFunctionFn **func, PetscCtxRt ctx)
1265: {
1266: SNES snes;
1267: DM dm;
1269: PetscFunctionBegin;
1271: PetscCall(TSGetSNES(ts, &snes));
1272: PetscCall(SNESGetFunction(snes, r, NULL, NULL));
1273: PetscCall(TSGetDM(ts, &dm));
1274: PetscCall(DMTSGetRHSFunction(dm, func, ctx));
1275: PetscFunctionReturn(PETSC_SUCCESS);
1276: }
1278: /*@C
1279: TSSetIJacobian - Set the function to compute the matrix dF/dU + a*dF/dU_t where F(t,U,U_t) is the function
1280: provided with `TSSetIFunction()`.
1282: Logically Collective
1284: Input Parameters:
1285: + ts - the `TS` context obtained from `TSCreate()`
1286: . Amat - (approximate) matrix to store Jacobian entries computed by `f`
1287: . Pmat - matrix used to compute preconditioner (usually the same as `Amat`)
1288: . f - the Jacobian evaluation routine
1289: - ctx - user-defined context for private data for the Jacobian evaluation routine (may be `NULL`)
1291: Level: beginner
1293: Notes:
1294: The matrices `Amat` and `Pmat` are exactly the matrices that are used by `SNES` for the nonlinear solve.
1296: If you know the operator Amat has a null space you can use `MatSetNullSpace()` and `MatSetTransposeNullSpace()` to supply the null
1297: space to `Amat` and the `KSP` solvers will automatically use that null space as needed during the solution process.
1299: The matrix dF/dU + a*dF/dU_t you provide turns out to be
1300: the Jacobian of F(t,U,W+a*U) where F(t,U,U_t) = 0 is the DAE to be solved.
1301: The time integrator internally approximates U_t by W+a*U where the positive "shift"
1302: a and vector W depend on the integration method, step size, and past states. For example with
1303: the backward Euler method a = 1/dt and W = -a*U(previous timestep) so
1304: W + a*U = a*(U - U(previous timestep)) = (U - U(previous timestep))/dt
1306: You must set all the diagonal entries of the matrices, if they are zero you must still set them with a zero value
1308: The TS solver may modify the nonzero structure and the entries of the matrices `Amat` and `Pmat` between the calls to `f`
1309: You should not assume the values are the same in the next call to `f` as you set them in the previous call.
1311: In case `TSSetRHSJacobian()` is also used in conjunction with a fully-implicit solver,
1312: multilevel linear solvers, e.g. `PCMG`, will likely not work due to the way `TS` handles rhs matrices.
1314: .seealso: [](ch_ts), `TS`, `TSIJacobianFn`, `TSSetIFunction()`, `TSSetRHSJacobian()`,
1315: `SNESComputeJacobianDefaultColor()`, `SNESComputeJacobianDefault()`, `TSSetRHSFunction()`
1316: @*/
1317: PetscErrorCode TSSetIJacobian(TS ts, Mat Amat, Mat Pmat, TSIJacobianFn *f, PetscCtx ctx)
1318: {
1319: SNES snes;
1320: DM dm;
1322: PetscFunctionBegin;
1326: if (Amat) PetscCheckSameComm(ts, 1, Amat, 2);
1327: if (Pmat) PetscCheckSameComm(ts, 1, Pmat, 3);
1329: PetscCall(TSGetDM(ts, &dm));
1330: PetscCall(DMTSSetIJacobian(dm, f, ctx));
1332: PetscCall(TSGetSNES(ts, &snes));
1333: PetscCall(SNESSetJacobian(snes, Amat, Pmat, SNESTSFormJacobian, ts));
1334: PetscFunctionReturn(PETSC_SUCCESS);
1335: }
1337: /*@
1338: TSRHSJacobianSetReuse - restore the RHS Jacobian before calling the user-provided `TSRHSJacobianFn` function again
1340: Logically Collective
1342: Input Parameters:
1343: + ts - `TS` context obtained from `TSCreate()`
1344: - reuse - `PETSC_TRUE` if the RHS Jacobian
1346: Level: intermediate
1348: Notes:
1349: Without this flag, `TS` will change the sign and shift the RHS Jacobian for a
1350: finite-time-step implicit solve, in which case the user function will need to recompute the
1351: entire Jacobian. The `reuse `flag must be set if the evaluation function assumes that the
1352: matrix entries have not been changed by the `TS`.
1354: .seealso: [](ch_ts), `TS`, `TSSetRHSJacobian()`, `TSComputeRHSJacobianConstant()`
1355: @*/
1356: PetscErrorCode TSRHSJacobianSetReuse(TS ts, PetscBool reuse)
1357: {
1358: PetscFunctionBegin;
1359: ts->rhsjacobian.reuse = reuse;
1360: PetscFunctionReturn(PETSC_SUCCESS);
1361: }
1363: /*@C
1364: TSSetI2Function - Set the function to compute F(t,U,U_t,U_tt) where F = 0 is the DAE to be solved.
1366: Logically Collective
1368: Input Parameters:
1369: + ts - the `TS` context obtained from `TSCreate()`
1370: . F - vector to hold the residual (or `NULL` to have it created internally)
1371: . fun - the function evaluation routine
1372: - ctx - user-defined context for private data for the function evaluation routine (may be `NULL`)
1374: Level: beginner
1376: .seealso: [](ch_ts), `TS`, `TSI2FunctionFn`, `TSSetI2Jacobian()`, `TSSetIFunction()`,
1377: `TSCreate()`, `TSSetRHSFunction()`
1378: @*/
1379: PetscErrorCode TSSetI2Function(TS ts, Vec F, TSI2FunctionFn *fun, PetscCtx ctx)
1380: {
1381: DM dm;
1383: PetscFunctionBegin;
1386: PetscCall(TSSetIFunction(ts, F, NULL, NULL));
1387: PetscCall(TSGetDM(ts, &dm));
1388: PetscCall(DMTSSetI2Function(dm, fun, ctx));
1389: PetscFunctionReturn(PETSC_SUCCESS);
1390: }
1392: /*@C
1393: TSGetI2Function - Returns the vector where the implicit residual is stored and the function/context to compute it.
1395: Not Collective
1397: Input Parameter:
1398: . ts - the `TS` context
1400: Output Parameters:
1401: + r - vector to hold residual (or `NULL`)
1402: . fun - the function to compute residual (or `NULL`)
1403: - ctx - the function context (or `NULL`)
1405: Level: advanced
1407: .seealso: [](ch_ts), `TS`, `TSSetIFunction()`, `SNESGetFunction()`, `TSCreate()`
1408: @*/
1409: PetscErrorCode TSGetI2Function(TS ts, Vec *r, TSI2FunctionFn **fun, PetscCtxRt ctx)
1410: {
1411: SNES snes;
1412: DM dm;
1414: PetscFunctionBegin;
1416: PetscCall(TSGetSNES(ts, &snes));
1417: PetscCall(SNESGetFunction(snes, r, NULL, NULL));
1418: PetscCall(TSGetDM(ts, &dm));
1419: PetscCall(DMTSGetI2Function(dm, fun, ctx));
1420: PetscFunctionReturn(PETSC_SUCCESS);
1421: }
1423: /*@C
1424: TSSetI2Jacobian - Set the function to compute the matrix dF/dU + v*dF/dU_t + a*dF/dU_tt
1425: where F(t,U,U_t,U_tt) is the function you provided with `TSSetI2Function()`.
1427: Logically Collective
1429: Input Parameters:
1430: + ts - the `TS` context obtained from `TSCreate()`
1431: . J - matrix to hold the Jacobian values
1432: . P - matrix for constructing the preconditioner (may be same as `J`)
1433: . jac - the Jacobian evaluation routine, see `TSI2JacobianFn` for the calling sequence
1434: - ctx - user-defined context for private data for the Jacobian evaluation routine (may be `NULL`)
1436: Level: beginner
1438: Notes:
1439: The matrices `J` and `P` are exactly the matrices that are used by `SNES` for the nonlinear solve.
1441: The matrix dF/dU + v*dF/dU_t + a*dF/dU_tt you provide turns out to be
1442: 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.
1443: The time integrator internally approximates U_t by W+v*U and U_tt by W'+a*U where the positive "shift"
1444: parameters 'v' and 'a' and vectors W, W' depend on the integration method, step size, and past states.
1446: .seealso: [](ch_ts), `TS`, `TSI2JacobianFn`, `TSSetI2Function()`, `TSGetI2Jacobian()`
1447: @*/
1448: PetscErrorCode TSSetI2Jacobian(TS ts, Mat J, Mat P, TSI2JacobianFn *jac, PetscCtx ctx)
1449: {
1450: DM dm;
1452: PetscFunctionBegin;
1456: PetscCall(TSSetIJacobian(ts, J, P, NULL, NULL));
1457: PetscCall(TSGetDM(ts, &dm));
1458: PetscCall(DMTSSetI2Jacobian(dm, jac, ctx));
1459: PetscFunctionReturn(PETSC_SUCCESS);
1460: }
1462: /*@C
1463: TSGetI2Jacobian - Returns the implicit Jacobian at the present timestep.
1465: Not Collective, but parallel objects are returned if `TS` is parallel
1467: Input Parameter:
1468: . ts - The `TS` context obtained from `TSCreate()`
1470: Output Parameters:
1471: + J - The (approximate) Jacobian of F(t,U,U_t,U_tt)
1472: . P - The matrix from which the preconditioner is constructed, often the same as `J`
1473: . jac - The function to compute the Jacobian matrices
1474: - ctx - User-defined context for Jacobian evaluation routine
1476: Level: advanced
1478: Note:
1479: You can pass in `NULL` for any return argument you do not need.
1481: .seealso: [](ch_ts), `TS`, `TSGetTimeStep()`, `TSGetMatrices()`, `TSGetTime()`, `TSGetStepNumber()`, `TSSetI2Jacobian()`, `TSGetI2Function()`, `TSCreate()`
1482: @*/
1483: PetscErrorCode TSGetI2Jacobian(TS ts, Mat *J, Mat *P, TSI2JacobianFn **jac, PetscCtxRt ctx)
1484: {
1485: SNES snes;
1486: DM dm;
1488: PetscFunctionBegin;
1489: PetscCall(TSGetSNES(ts, &snes));
1490: PetscCall(SNESSetUpMatrices(snes));
1491: PetscCall(SNESGetJacobian(snes, J, P, NULL, NULL));
1492: PetscCall(TSGetDM(ts, &dm));
1493: PetscCall(DMTSGetI2Jacobian(dm, jac, ctx));
1494: PetscFunctionReturn(PETSC_SUCCESS);
1495: }
1497: /*@
1498: TSComputeI2Function - Evaluates the DAE residual written in implicit form F(t,U,U_t,U_tt) = 0
1500: Collective
1502: Input Parameters:
1503: + ts - the `TS` context
1504: . t - current time
1505: . U - state vector
1506: . V - time derivative of state vector (U_t)
1507: - A - second time derivative of state vector (U_tt)
1509: Output Parameter:
1510: . F - the residual vector
1512: Level: developer
1514: Note:
1515: Most users should not need to explicitly call this routine, as it
1516: is used internally within the nonlinear solvers.
1518: .seealso: [](ch_ts), `TS`, `TSSetI2Function()`, `TSGetI2Function()`
1519: @*/
1520: PetscErrorCode TSComputeI2Function(TS ts, PetscReal t, Vec U, Vec V, Vec A, Vec F)
1521: {
1522: DM dm;
1523: TSI2FunctionFn *I2Function;
1524: void *ctx;
1525: TSRHSFunctionFn *rhsfunction;
1527: PetscFunctionBegin;
1534: PetscCall(TSGetDM(ts, &dm));
1535: PetscCall(DMTSGetI2Function(dm, &I2Function, &ctx));
1536: PetscCall(DMTSGetRHSFunction(dm, &rhsfunction, NULL));
1538: if (!I2Function) {
1539: PetscCall(TSComputeIFunction(ts, t, U, A, F, PETSC_FALSE));
1540: PetscFunctionReturn(PETSC_SUCCESS);
1541: }
1543: PetscCall(PetscLogEventBegin(TS_FunctionEval, U, ts, V, F));
1545: PetscCallBack("TS callback implicit function", I2Function(ts, t, U, V, A, F, ctx));
1547: if (rhsfunction) {
1548: Vec Frhs;
1550: PetscCall(DMGetGlobalVector(dm, &Frhs));
1551: PetscCall(TSComputeRHSFunction(ts, t, U, Frhs));
1552: PetscCall(VecAXPY(F, -1, Frhs));
1553: PetscCall(DMRestoreGlobalVector(dm, &Frhs));
1554: }
1556: PetscCall(PetscLogEventEnd(TS_FunctionEval, U, ts, V, F));
1557: PetscFunctionReturn(PETSC_SUCCESS);
1558: }
1560: /*@
1561: TSComputeI2Jacobian - Evaluates the Jacobian of the DAE
1563: Collective
1565: Input Parameters:
1566: + ts - the `TS` context
1567: . t - current timestep
1568: . U - state vector
1569: . V - time derivative of state vector
1570: . A - second time derivative of state vector
1571: . shiftV - shift to apply, see note below
1572: - shiftA - shift to apply, see note below
1574: Output Parameters:
1575: + J - Jacobian matrix
1576: - P - optional matrix used to construct the preconditioner
1578: Level: developer
1580: Notes:
1581: If $F(t,U,V,A) = 0$ is the DAE, the required Jacobian is
1583: $$
1584: dF/dU + shiftV*dF/dV + shiftA*dF/dA
1585: $$
1587: Most users should not need to explicitly call this routine, as it
1588: is used internally within the ODE integrators.
1590: .seealso: [](ch_ts), `TS`, `TSSetI2Jacobian()`
1591: @*/
1592: PetscErrorCode TSComputeI2Jacobian(TS ts, PetscReal t, Vec U, Vec V, Vec A, PetscReal shiftV, PetscReal shiftA, Mat J, Mat P)
1593: {
1594: DM dm;
1595: TSI2JacobianFn *I2Jacobian;
1596: void *ctx;
1597: TSRHSJacobianFn *rhsjacobian;
1599: PetscFunctionBegin;
1607: PetscCall(TSGetDM(ts, &dm));
1608: PetscCall(DMTSGetI2Jacobian(dm, &I2Jacobian, &ctx));
1609: PetscCall(DMTSGetRHSJacobian(dm, &rhsjacobian, NULL));
1611: if (!I2Jacobian) {
1612: PetscCall(TSComputeIJacobian(ts, t, U, A, shiftA, J, P, PETSC_FALSE));
1613: PetscFunctionReturn(PETSC_SUCCESS);
1614: }
1616: PetscCall(PetscLogEventBegin(TS_JacobianEval, U, ts, J, P));
1617: PetscCallBack("TS callback implicit Jacobian", I2Jacobian(ts, t, U, V, A, shiftV, shiftA, J, P, ctx));
1618: if (rhsjacobian) {
1619: Mat Jrhs, Prhs;
1620: PetscCall(TSGetRHSMats_Private(ts, &Jrhs, &Prhs));
1621: PetscCall(TSComputeRHSJacobian(ts, t, U, Jrhs, Prhs));
1622: PetscCall(MatAXPY(J, -1, Jrhs, ts->axpy_pattern));
1623: if (P != J) PetscCall(MatAXPY(P, -1, Prhs, ts->axpy_pattern));
1624: }
1626: PetscCall(PetscLogEventEnd(TS_JacobianEval, U, ts, J, P));
1627: PetscFunctionReturn(PETSC_SUCCESS);
1628: }
1630: /*@C
1631: TSSetTransientVariable - sets function to transform from state to transient variables
1633: Logically Collective
1635: Input Parameters:
1636: + ts - time stepping context on which to change the transient variable
1637: . tvar - a function that transforms to transient variables, see `TSTransientVariableFn` for the calling sequence
1638: - ctx - a context for tvar
1640: Level: advanced
1642: Notes:
1643: This is typically used to transform from primitive to conservative variables so that a time integrator (e.g., `TSBDF`)
1644: can be conservative. In this context, primitive variables P are used to model the state (e.g., because they lead to
1645: well-conditioned formulations even in limiting cases such as low-Mach or zero porosity). The transient variable is
1646: C(P), specified by calling this function. An IFunction thus receives arguments (P, Cdot) and the IJacobian must be
1647: evaluated via the chain rule, as in
1648: .vb
1649: dF/dP + shift * dF/dCdot dC/dP.
1650: .ve
1652: .seealso: [](ch_ts), `TS`, `TSBDF`, `TSTransientVariableFn`, `DMTSSetTransientVariable()`, `DMTSGetTransientVariable()`, `TSSetIFunction()`, `TSSetIJacobian()`
1653: @*/
1654: PetscErrorCode TSSetTransientVariable(TS ts, TSTransientVariableFn *tvar, PetscCtx ctx)
1655: {
1656: DM dm;
1658: PetscFunctionBegin;
1660: PetscCall(TSGetDM(ts, &dm));
1661: PetscCall(DMTSSetTransientVariable(dm, tvar, ctx));
1662: PetscFunctionReturn(PETSC_SUCCESS);
1663: }
1665: /*@
1666: TSComputeTransientVariable - transforms state (primitive) variables to transient (conservative) variables
1668: Logically Collective
1670: Input Parameters:
1671: + ts - TS on which to compute
1672: - U - state vector to be transformed to transient variables
1674: Output Parameter:
1675: . C - transient (conservative) variable
1677: Level: developer
1679: Developer Notes:
1680: If `DMTSSetTransientVariable()` has not been called, then C is not modified in this routine and C = `NULL` is allowed.
1681: This makes it safe to call without a guard. One can use `TSHasTransientVariable()` to check if transient variables are
1682: being used.
1684: .seealso: [](ch_ts), `TS`, `TSBDF`, `DMTSSetTransientVariable()`, `TSComputeIFunction()`, `TSComputeIJacobian()`
1685: @*/
1686: PetscErrorCode TSComputeTransientVariable(TS ts, Vec U, Vec C)
1687: {
1688: DM dm;
1689: DMTS dmts;
1691: PetscFunctionBegin;
1694: PetscCall(TSGetDM(ts, &dm));
1695: PetscCall(DMGetDMTS(dm, &dmts));
1696: if (dmts->ops->transientvar) {
1698: PetscCall((*dmts->ops->transientvar)(ts, U, C, dmts->transientvarctx));
1699: }
1700: PetscFunctionReturn(PETSC_SUCCESS);
1701: }
1703: /*@
1704: TSHasTransientVariable - determine whether transient variables have been set
1706: Logically Collective
1708: Input Parameter:
1709: . ts - `TS` on which to compute
1711: Output Parameter:
1712: . has - `PETSC_TRUE` if transient variables have been set
1714: Level: developer
1716: .seealso: [](ch_ts), `TS`, `TSBDF`, `DMTSSetTransientVariable()`, `TSComputeTransientVariable()`
1717: @*/
1718: PetscErrorCode TSHasTransientVariable(TS ts, PetscBool *has)
1719: {
1720: DM dm;
1721: DMTS dmts;
1723: PetscFunctionBegin;
1725: PetscCall(TSGetDM(ts, &dm));
1726: PetscCall(DMGetDMTS(dm, &dmts));
1727: *has = dmts->ops->transientvar ? PETSC_TRUE : PETSC_FALSE;
1728: PetscFunctionReturn(PETSC_SUCCESS);
1729: }
1731: /*@
1732: TS2SetSolution - Sets the initial solution and time derivative vectors
1733: for use by the `TS` routines handling second order equations.
1735: Logically Collective
1737: Input Parameters:
1738: + ts - the `TS` context obtained from `TSCreate()`
1739: . u - the solution vector
1740: - v - the time derivative vector
1742: Level: beginner
1744: .seealso: [](ch_ts), `TS`
1745: @*/
1746: PetscErrorCode TS2SetSolution(TS ts, Vec u, Vec v)
1747: {
1748: PetscFunctionBegin;
1752: PetscCall(TSSetSolution(ts, u));
1753: PetscCall(PetscObjectReference((PetscObject)v));
1754: PetscCall(VecDestroy(&ts->vec_dot));
1755: ts->vec_dot = v;
1756: PetscFunctionReturn(PETSC_SUCCESS);
1757: }
1759: /*@
1760: TS2GetSolution - Returns the solution and time derivative at the present timestep
1761: for second order equations.
1763: Not Collective
1765: Input Parameter:
1766: . ts - the `TS` context obtained from `TSCreate()`
1768: Output Parameters:
1769: + u - the vector containing the solution
1770: - v - the vector containing the time derivative
1772: Level: intermediate
1774: Notes:
1775: It is valid to call this routine inside the function
1776: that you are evaluating in order to move to the new timestep. This vector not
1777: changed until the solution at the next timestep has been calculated.
1779: .seealso: [](ch_ts), `TS`, `TS2SetSolution()`, `TSGetTimeStep()`, `TSGetTime()`
1780: @*/
1781: PetscErrorCode TS2GetSolution(TS ts, Vec *u, Vec *v)
1782: {
1783: PetscFunctionBegin;
1785: if (u) PetscAssertPointer(u, 2);
1786: if (v) PetscAssertPointer(v, 3);
1787: if (u) *u = ts->vec_sol;
1788: if (v) *v = ts->vec_dot;
1789: PetscFunctionReturn(PETSC_SUCCESS);
1790: }
1792: /*@
1793: TSLoad - Loads a `TS` that has been stored in binary with `TSView()`.
1795: Collective
1797: Input Parameters:
1798: + ts - the newly loaded `TS`, this needs to have been created with `TSCreate()` or
1799: some related function before a call to `TSLoad()`.
1800: - viewer - binary file viewer, obtained from `PetscViewerBinaryOpen()`
1802: Level: intermediate
1804: Note:
1805: The type is determined by the data in the file, any type set into the `TS` before this call is ignored.
1807: .seealso: [](ch_ts), `TS`, `PetscViewer`, `PetscViewerBinaryOpen()`, `TSView()`, `MatLoad()`, `VecLoad()`
1808: @*/
1809: PetscErrorCode TSLoad(TS ts, PetscViewer viewer)
1810: {
1811: PetscBool isbinary;
1812: PetscInt classid;
1813: char type[256];
1814: DMTS sdm;
1815: DM dm;
1817: PetscFunctionBegin;
1820: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary));
1821: PetscCheck(isbinary, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Invalid viewer; open viewer with PetscViewerBinaryOpen()");
1823: PetscCall(PetscViewerBinaryRead(viewer, &classid, 1, NULL, PETSC_INT));
1824: PetscCheck(classid == TS_FILE_CLASSID, PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_WRONG, "Not TS next in file");
1825: PetscCall(PetscViewerBinaryRead(viewer, type, 256, NULL, PETSC_CHAR));
1826: PetscCall(TSSetType(ts, type));
1827: PetscTryTypeMethod(ts, load, viewer);
1828: PetscCall(DMCreate(PetscObjectComm((PetscObject)ts), &dm));
1829: PetscCall(DMLoad(dm, viewer));
1830: PetscCall(TSSetDM(ts, dm));
1831: PetscCall(DMCreateGlobalVector(ts->dm, &ts->vec_sol));
1832: PetscCall(VecLoad(ts->vec_sol, viewer));
1833: PetscCall(DMGetDMTS(ts->dm, &sdm));
1834: PetscCall(DMTSLoad(sdm, viewer));
1835: PetscFunctionReturn(PETSC_SUCCESS);
1836: }
1838: #include <petscdraw.h>
1839: #if defined(PETSC_HAVE_SAWS)
1840: #include <petscviewersaws.h>
1841: #endif
1843: /*@
1844: TSViewFromOptions - View a `TS` based on values in the options database
1846: Collective
1848: Input Parameters:
1849: + ts - the `TS` context
1850: . obj - Optional object that provides the prefix for the options database keys
1851: - name - command line option string to be passed by user
1853: Options Database Key:
1854: . -name [viewertype][:...] - option name and values. See `PetscObjectViewFromOptions()` for the possible arguments
1856: Level: intermediate
1858: .seealso: [](ch_ts), `TS`, `TSView`, `PetscObjectViewFromOptions()`, `TSCreate()`
1859: @*/
1860: PetscErrorCode TSViewFromOptions(TS ts, PetscObject obj, const char name[])
1861: {
1862: PetscFunctionBegin;
1864: PetscCall(PetscObjectViewFromOptions((PetscObject)ts, obj, name));
1865: PetscFunctionReturn(PETSC_SUCCESS);
1866: }
1868: /*@
1869: TSView - Prints the `TS` data structure.
1871: Collective
1873: Input Parameters:
1874: + ts - the `TS` context obtained from `TSCreate()`
1875: - viewer - visualization context
1877: Options Database Key:
1878: . -ts_view - calls `TSView()` at end of `TSStep()`
1880: Level: beginner
1882: Notes:
1883: The available visualization contexts include
1884: + `PETSC_VIEWER_STDOUT_SELF` - standard output (default)
1885: - `PETSC_VIEWER_STDOUT_WORLD` - synchronized standard
1886: output where only the first processor opens
1887: the file. All other processors send their
1888: data to the first processor to print.
1890: The user can open an alternative visualization context with
1891: `PetscViewerASCIIOpen()` - output to a specified file.
1893: In the debugger you can do call `TSView`(ts,0) to display the `TS` solver. (The same holds for any PETSc object viewer).
1895: The "initial time step" displayed is the default time step from `TSCreate()` or that set with `TSSetTimeStep()` or `-ts_time_step`
1897: .seealso: [](ch_ts), `TS`, `PetscViewer`, `PetscViewerASCIIOpen()`
1898: @*/
1899: PetscErrorCode TSView(TS ts, PetscViewer viewer)
1900: {
1901: TSType type;
1902: PetscBool isascii, isstring, issundials, isbinary, isdraw;
1903: DMTS sdm;
1904: #if defined(PETSC_HAVE_SAWS)
1905: PetscBool issaws;
1906: #endif
1908: PetscFunctionBegin;
1910: if (!viewer) PetscCall(PetscViewerASCIIGetStdout(PetscObjectComm((PetscObject)ts), &viewer));
1912: PetscCheckSameComm(ts, 1, viewer, 2);
1914: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &isascii));
1915: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERSTRING, &isstring));
1916: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary));
1917: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERDRAW, &isdraw));
1918: #if defined(PETSC_HAVE_SAWS)
1919: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERSAWS, &issaws));
1920: #endif
1921: if (isascii) {
1922: PetscCall(PetscObjectPrintClassNamePrefixType((PetscObject)ts, viewer));
1923: if (ts->ops->view) {
1924: PetscCall(PetscViewerASCIIPushTab(viewer));
1925: PetscUseTypeMethod(ts, view, viewer);
1926: PetscCall(PetscViewerASCIIPopTab(viewer));
1927: }
1928: PetscCall(PetscViewerASCIIPrintf(viewer, " initial time step=%g\n", (double)ts->initial_time_step));
1929: if (ts->max_steps < PETSC_INT_MAX) PetscCall(PetscViewerASCIIPrintf(viewer, " maximum steps=%" PetscInt_FMT "\n", ts->max_steps));
1930: if (ts->run_steps < PETSC_INT_MAX) PetscCall(PetscViewerASCIIPrintf(viewer, " run steps=%" PetscInt_FMT "\n", ts->run_steps));
1931: if (ts->max_time < PETSC_MAX_REAL) PetscCall(PetscViewerASCIIPrintf(viewer, " maximum time=%g\n", (double)ts->max_time));
1932: if (ts->max_reject != PETSC_UNLIMITED) PetscCall(PetscViewerASCIIPrintf(viewer, " maximum number of step rejections=%" PetscInt_FMT "\n", ts->max_reject));
1933: if (ts->max_snes_failures != PETSC_UNLIMITED) PetscCall(PetscViewerASCIIPrintf(viewer, " maximum number of SNES failures allowed=%" PetscInt_FMT "\n", ts->max_snes_failures));
1934: if (ts->ifuncs) PetscCall(PetscViewerASCIIPrintf(viewer, " total number of I function evaluations=%" PetscInt_FMT "\n", ts->ifuncs));
1935: if (ts->ijacs) PetscCall(PetscViewerASCIIPrintf(viewer, " total number of I Jacobian evaluations=%" PetscInt_FMT "\n", ts->ijacs));
1936: if (ts->rhsfuncs) PetscCall(PetscViewerASCIIPrintf(viewer, " total number of RHS function evaluations=%" PetscInt_FMT "\n", ts->rhsfuncs));
1937: if (ts->rhsjacs) PetscCall(PetscViewerASCIIPrintf(viewer, " total number of RHS Jacobian evaluations=%" PetscInt_FMT "\n", ts->rhsjacs));
1938: if (ts->usessnes) {
1939: PetscBool lin;
1940: if (ts->problem_type == TS_NONLINEAR) PetscCall(PetscViewerASCIIPrintf(viewer, " total number of nonlinear solver iterations=%" PetscInt_FMT "\n", ts->snes_its));
1941: PetscCall(PetscViewerASCIIPrintf(viewer, " total number of linear solver iterations=%" PetscInt_FMT "\n", ts->ksp_its));
1942: PetscCall(PetscObjectTypeCompareAny((PetscObject)ts->snes, &lin, SNESKSPONLY, SNESKSPTRANSPOSEONLY, ""));
1943: PetscCall(PetscViewerASCIIPrintf(viewer, " total number of %slinear solve failures=%" PetscInt_FMT "\n", lin ? "" : "non", ts->num_snes_failures));
1944: }
1945: PetscCall(PetscViewerASCIIPrintf(viewer, " total number of rejected steps=%" PetscInt_FMT "\n", ts->reject));
1946: if (ts->vrtol) PetscCall(PetscViewerASCIIPrintf(viewer, " using vector of relative error tolerances, "));
1947: else PetscCall(PetscViewerASCIIPrintf(viewer, " using relative error tolerance of %g, ", (double)ts->rtol));
1948: if (ts->vatol) PetscCall(PetscViewerASCIIPrintf(viewer, "using vector of absolute error tolerances\n"));
1949: else PetscCall(PetscViewerASCIIPrintf(viewer, "using absolute error tolerance of %g\n", (double)ts->atol));
1950: PetscCall(PetscViewerASCIIPushTab(viewer));
1951: PetscCall(TSAdaptView(ts->adapt, viewer));
1952: PetscCall(PetscViewerASCIIPopTab(viewer));
1953: } else if (isstring) {
1954: PetscCall(TSGetType(ts, &type));
1955: PetscCall(PetscViewerStringSPrintf(viewer, " TSType: %-7.7s", type));
1956: PetscTryTypeMethod(ts, view, viewer);
1957: } else if (isbinary) {
1958: PetscInt classid = TS_FILE_CLASSID;
1959: MPI_Comm comm;
1960: PetscMPIInt rank;
1961: char type[256];
1963: PetscCall(PetscObjectGetComm((PetscObject)ts, &comm));
1964: PetscCallMPI(MPI_Comm_rank(comm, &rank));
1965: if (rank == 0) {
1966: PetscCall(PetscViewerBinaryWrite(viewer, &classid, 1, PETSC_INT));
1967: PetscCall(PetscStrncpy(type, ((PetscObject)ts)->type_name, 256));
1968: PetscCall(PetscViewerBinaryWrite(viewer, type, 256, PETSC_CHAR));
1969: }
1970: PetscTryTypeMethod(ts, view, viewer);
1971: if (ts->adapt) PetscCall(TSAdaptView(ts->adapt, viewer));
1972: PetscCall(DMView(ts->dm, viewer));
1973: PetscCall(VecView(ts->vec_sol, viewer));
1974: PetscCall(DMGetDMTS(ts->dm, &sdm));
1975: PetscCall(DMTSView(sdm, viewer));
1976: } else if (isdraw) {
1977: PetscDraw draw;
1978: char str[36];
1979: PetscReal x, y, bottom, h;
1981: PetscCall(PetscViewerDrawGetDraw(viewer, 0, &draw));
1982: PetscCall(PetscDrawGetCurrentPoint(draw, &x, &y));
1983: PetscCall(PetscStrncpy(str, "TS: ", sizeof(str)));
1984: PetscCall(PetscStrlcat(str, ((PetscObject)ts)->type_name, sizeof(str)));
1985: PetscCall(PetscDrawStringBoxed(draw, x, y, PETSC_DRAW_BLACK, PETSC_DRAW_BLACK, str, NULL, &h));
1986: bottom = y - h;
1987: PetscCall(PetscDrawPushCurrentPoint(draw, x, bottom));
1988: PetscTryTypeMethod(ts, view, viewer);
1989: if (ts->adapt) PetscCall(TSAdaptView(ts->adapt, viewer));
1990: if (ts->snes) PetscCall(SNESView(ts->snes, viewer));
1991: PetscCall(PetscDrawPopCurrentPoint(draw));
1992: #if defined(PETSC_HAVE_SAWS)
1993: } else if (issaws) {
1994: PetscMPIInt rank;
1995: const char *name;
1997: PetscCall(PetscObjectGetName((PetscObject)ts, &name));
1998: PetscCallMPI(MPI_Comm_rank(PETSC_COMM_WORLD, &rank));
1999: if (!((PetscObject)ts)->amsmem && rank == 0) {
2000: char dir[1024];
2002: PetscCall(PetscObjectViewSAWs((PetscObject)ts, viewer));
2003: PetscCall(PetscSNPrintf(dir, 1024, "/PETSc/Objects/%s/time_step", name));
2004: PetscCallSAWs(SAWs_Register, (dir, &ts->steps, 1, SAWs_READ, SAWs_INT));
2005: PetscCall(PetscSNPrintf(dir, 1024, "/PETSc/Objects/%s/time", name));
2006: PetscCallSAWs(SAWs_Register, (dir, &ts->ptime, 1, SAWs_READ, SAWs_DOUBLE));
2007: }
2008: PetscTryTypeMethod(ts, view, viewer);
2009: #endif
2010: }
2011: if (ts->snes && ts->usessnes) {
2012: PetscCall(PetscViewerASCIIPushTab(viewer));
2013: PetscCall(SNESView(ts->snes, viewer));
2014: PetscCall(PetscViewerASCIIPopTab(viewer));
2015: }
2016: PetscCall(DMGetDMTS(ts->dm, &sdm));
2017: PetscCall(DMTSView(sdm, viewer));
2019: PetscCall(PetscViewerASCIIPushTab(viewer));
2020: PetscCall(PetscObjectTypeCompare((PetscObject)ts, TSSUNDIALS, &issundials));
2021: PetscCall(PetscViewerASCIIPopTab(viewer));
2022: PetscFunctionReturn(PETSC_SUCCESS);
2023: }
2025: /*@
2026: TSSetApplicationContext - Sets an optional user-defined context for the timesteppers that may be accessed, for example inside the user provided
2027: `TS` callbacks with `TSGetApplicationContext()`
2029: Logically Collective
2031: Input Parameters:
2032: + ts - the `TS` context obtained from `TSCreate()`
2033: - ctx - user context
2035: Level: intermediate
2037: Fortran Note:
2038: This only works when `ctx` is a Fortran derived type (it cannot be a `PetscObject`), we recommend writing a Fortran interface definition for this
2039: function that tells the Fortran compiler the derived data type that is passed in as the `ctx` argument. See `TSGetApplicationContext()` for
2040: an example.
2042: .seealso: [](ch_ts), `TS`, `TSGetApplicationContext()`
2043: @*/
2044: PetscErrorCode TSSetApplicationContext(TS ts, PetscCtx ctx)
2045: {
2046: PetscFunctionBegin;
2048: ts->ctx = ctx;
2049: PetscFunctionReturn(PETSC_SUCCESS);
2050: }
2052: /*@
2053: TSGetApplicationContext - Gets the user-defined context for the
2054: timestepper that was set with `TSSetApplicationContext()`
2056: Not Collective
2058: Input Parameter:
2059: . ts - the `TS` context obtained from `TSCreate()`
2061: Output Parameter:
2062: . ctx - a pointer to the user context
2064: Level: intermediate
2066: Fortran Notes:
2067: This only works when the context is a Fortran derived type or a `PetscObject`. Declare `ctx` with
2068: .vb
2069: type(tUsertype), pointer :: ctx
2070: .ve
2072: .seealso: [](ch_ts), `TS`, `TSSetApplicationContext()`
2073: @*/
2074: PetscErrorCode TSGetApplicationContext(TS ts, PetscCtxRt ctx)
2075: {
2076: PetscFunctionBegin;
2078: *(void **)ctx = ts->ctx;
2079: PetscFunctionReturn(PETSC_SUCCESS);
2080: }
2082: /*@
2083: TSGetStepNumber - Gets the number of time steps completed.
2085: Not Collective
2087: Input Parameter:
2088: . ts - the `TS` context obtained from `TSCreate()`
2090: Output Parameter:
2091: . steps - number of steps completed so far
2093: Level: intermediate
2095: .seealso: [](ch_ts), `TS`, `TSGetTime()`, `TSGetTimeStep()`, `TSSetPreStep()`, `TSSetPreStage()`, `TSSetPostStage()`, `TSSetPostStep()`
2096: @*/
2097: PetscErrorCode TSGetStepNumber(TS ts, PetscInt *steps)
2098: {
2099: PetscFunctionBegin;
2101: PetscAssertPointer(steps, 2);
2102: *steps = ts->steps;
2103: PetscFunctionReturn(PETSC_SUCCESS);
2104: }
2106: /*@
2107: TSSetStepNumber - Sets the number of steps completed.
2109: Logically Collective
2111: Input Parameters:
2112: + ts - the `TS` context
2113: - steps - number of steps completed so far
2115: Level: developer
2117: Note:
2118: For most uses of the `TS` solvers the user need not explicitly call
2119: `TSSetStepNumber()`, as the step counter is appropriately updated in
2120: `TSSolve()`/`TSStep()`/`TSRollBack()`. Power users may call this routine to
2121: reinitialize timestepping by setting the step counter to zero (and time
2122: to the initial time) to solve a similar problem with different initial
2123: conditions or parameters. Other possible use case is to continue
2124: timestepping from a previously interrupted run in such a way that `TS`
2125: monitors will be called with a initial nonzero step counter.
2127: .seealso: [](ch_ts), `TS`, `TSGetStepNumber()`, `TSSetTime()`, `TSSetTimeStep()`, `TSSetSolution()`
2128: @*/
2129: PetscErrorCode TSSetStepNumber(TS ts, PetscInt steps)
2130: {
2131: PetscFunctionBegin;
2134: PetscCheck(steps >= 0, PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_OUTOFRANGE, "Step number must be non-negative");
2135: ts->steps = steps;
2136: PetscFunctionReturn(PETSC_SUCCESS);
2137: }
2139: /*@
2140: TSSetTimeStep - Allows one to reset the timestep at any time.
2142: Logically Collective
2144: Input Parameters:
2145: + ts - the `TS` context obtained from `TSCreate()`
2146: - time_step - the size of the timestep
2148: Options Database Key:
2149: . -ts_time_step dt - provide the initial time step
2151: Level: intermediate
2153: Notes:
2154: This is only a suggestion, the actual initial time step used may differ
2156: If this is called after `TSSetUp()`, it will not change the initial time step value printed by `TSView()`
2158: .seealso: [](ch_ts), `TS`, `TSPSEUDO`, `TSGetTimeStep()`, `TSSetTime()`
2159: @*/
2160: PetscErrorCode TSSetTimeStep(TS ts, PetscReal time_step)
2161: {
2162: PetscFunctionBegin;
2165: ts->time_step = time_step;
2166: if (ts->setupcalled == PETSC_FALSE) ts->initial_time_step = time_step;
2167: PetscFunctionReturn(PETSC_SUCCESS);
2168: }
2170: /*@
2171: TSSetExactFinalTime - Determines whether to adapt the final time step to
2172: match the exact final time, to interpolate the solution to the exact final time,
2173: or to just return at the final time `TS` computed (which may be slightly larger
2174: than the requested final time).
2176: Logically Collective
2178: Input Parameters:
2179: + ts - the time-step context
2180: - eftopt - exact final time option
2181: .vb
2182: TS_EXACTFINALTIME_STEPOVER - Don't do anything if final time is exceeded, just use it
2183: TS_EXACTFINALTIME_INTERPOLATE - Interpolate back to final time if the final time is exceeded
2184: TS_EXACTFINALTIME_MATCHSTEP - Adapt final time step to ensure the computed final time exactly equals the requested final time
2185: .ve
2187: Options Database Key:
2188: . -ts_exact_final_time stepover,interpolate,matchstep - select the final step approach at runtime
2190: Level: beginner
2192: Note:
2193: If you use the option `TS_EXACTFINALTIME_STEPOVER` the solution may be at a very different time
2194: then the final time you selected.
2196: .seealso: [](ch_ts), `TS`, `TSExactFinalTimeOption`, `TSGetExactFinalTime()`
2197: @*/
2198: PetscErrorCode TSSetExactFinalTime(TS ts, TSExactFinalTimeOption eftopt)
2199: {
2200: PetscFunctionBegin;
2203: ts->exact_final_time = eftopt;
2204: PetscFunctionReturn(PETSC_SUCCESS);
2205: }
2207: /*@
2208: TSGetExactFinalTime - Gets the exact final time option set with `TSSetExactFinalTime()`
2210: Not Collective
2212: Input Parameter:
2213: . ts - the `TS` context
2215: Output Parameter:
2216: . eftopt - exact final time option
2218: Level: beginner
2220: .seealso: [](ch_ts), `TS`, `TSExactFinalTimeOption`, `TSSetExactFinalTime()`
2221: @*/
2222: PetscErrorCode TSGetExactFinalTime(TS ts, TSExactFinalTimeOption *eftopt)
2223: {
2224: PetscFunctionBegin;
2226: PetscAssertPointer(eftopt, 2);
2227: *eftopt = ts->exact_final_time;
2228: PetscFunctionReturn(PETSC_SUCCESS);
2229: }
2231: /*@
2232: TSGetTimeStep - Gets the current timestep size.
2234: Not Collective
2236: Input Parameter:
2237: . ts - the `TS` context obtained from `TSCreate()`
2239: Output Parameter:
2240: . dt - the current timestep size
2242: Level: intermediate
2244: .seealso: [](ch_ts), `TS`, `TSSetTimeStep()`, `TSGetTime()`
2245: @*/
2246: PetscErrorCode TSGetTimeStep(TS ts, PetscReal *dt)
2247: {
2248: PetscFunctionBegin;
2250: PetscAssertPointer(dt, 2);
2251: *dt = ts->time_step;
2252: PetscFunctionReturn(PETSC_SUCCESS);
2253: }
2255: /*@
2256: TSGetSolution - Returns the solution at the present timestep. It
2257: is valid to call this routine inside the function that you are evaluating
2258: in order to move to the new timestep. This vector not changed until
2259: the solution at the next timestep has been calculated.
2261: Not Collective, but v returned is parallel if ts is parallel
2263: Input Parameter:
2264: . ts - the `TS` context obtained from `TSCreate()`
2266: Output Parameter:
2267: . v - the vector containing the solution
2269: Level: intermediate
2271: Note:
2272: If you used `TSSetExactFinalTime`(ts,`TS_EXACTFINALTIME_MATCHSTEP`); this does not return the solution at the requested
2273: final time. It returns the solution at the next timestep.
2275: .seealso: [](ch_ts), `TS`, `TSGetTimeStep()`, `TSGetTime()`, `TSGetSolveTime()`, `TSGetSolutionComponents()`, `TSSetSolutionFunction()`
2276: @*/
2277: PetscErrorCode TSGetSolution(TS ts, Vec *v)
2278: {
2279: PetscFunctionBegin;
2281: PetscAssertPointer(v, 2);
2282: *v = ts->vec_sol;
2283: PetscFunctionReturn(PETSC_SUCCESS);
2284: }
2286: /*@
2287: TSGetSolutionComponents - Returns any solution components at the present
2288: timestep, if available for the time integration method being used.
2289: Solution components are quantities that share the same size and
2290: structure as the solution vector.
2292: Not Collective, but v returned is parallel if ts is parallel
2294: Input Parameters:
2295: + ts - the `TS` context obtained from `TSCreate()` (input parameter).
2296: . n - If v is `NULL`, then the number of solution components is
2297: returned through n, else the n-th solution component is
2298: returned in v.
2299: - v - the vector containing the n-th solution component
2300: (may be `NULL` to use this function to find out
2301: the number of solutions components).
2303: Level: advanced
2305: .seealso: [](ch_ts), `TS`, `TSGetSolution()`
2306: @*/
2307: PetscErrorCode TSGetSolutionComponents(TS ts, PetscInt *n, Vec *v)
2308: {
2309: PetscFunctionBegin;
2311: if (!ts->ops->getsolutioncomponents) *n = 0;
2312: else PetscUseTypeMethod(ts, getsolutioncomponents, n, v);
2313: PetscFunctionReturn(PETSC_SUCCESS);
2314: }
2316: /*@
2317: TSGetAuxSolution - Returns an auxiliary solution at the present
2318: timestep, if available for the time integration method being used.
2320: Not Collective, but v returned is parallel if ts is parallel
2322: Input Parameters:
2323: + ts - the `TS` context obtained from `TSCreate()` (input parameter).
2324: - v - the vector containing the auxiliary solution
2326: Level: intermediate
2328: .seealso: [](ch_ts), `TS`, `TSGetSolution()`
2329: @*/
2330: PetscErrorCode TSGetAuxSolution(TS ts, Vec *v)
2331: {
2332: PetscFunctionBegin;
2334: if (ts->ops->getauxsolution) PetscUseTypeMethod(ts, getauxsolution, v);
2335: else PetscCall(VecZeroEntries(*v));
2336: PetscFunctionReturn(PETSC_SUCCESS);
2337: }
2339: /*@
2340: TSGetTimeError - Returns the estimated error vector, if the chosen
2341: `TSType` has an error estimation functionality and `TSSetTimeError()` was called
2343: Not Collective, but v returned is parallel if ts is parallel
2345: Input Parameters:
2346: + ts - the `TS` context obtained from `TSCreate()` (input parameter).
2347: . n - current estimate (n=0) or previous one (n=-1)
2348: - v - the vector containing the error (same size as the solution).
2350: Level: intermediate
2352: Note:
2353: MUST call after `TSSetUp()`
2355: .seealso: [](ch_ts), `TSGetSolution()`, `TSSetTimeError()`
2356: @*/
2357: PetscErrorCode TSGetTimeError(TS ts, PetscInt n, Vec *v)
2358: {
2359: PetscFunctionBegin;
2361: if (ts->ops->gettimeerror) PetscUseTypeMethod(ts, gettimeerror, n, v);
2362: else PetscCall(VecZeroEntries(*v));
2363: PetscFunctionReturn(PETSC_SUCCESS);
2364: }
2366: /*@
2367: TSSetTimeError - Sets the estimated error vector, if the chosen
2368: `TSType` has an error estimation functionality. This can be used
2369: to restart such a time integrator with a given error vector.
2371: Not Collective, but v returned is parallel if ts is parallel
2373: Input Parameters:
2374: + ts - the `TS` context obtained from `TSCreate()` (input parameter).
2375: - v - the vector containing the error (same size as the solution).
2377: Level: intermediate
2379: .seealso: [](ch_ts), `TS`, `TSSetSolution()`, `TSGetTimeError()`
2380: @*/
2381: PetscErrorCode TSSetTimeError(TS ts, Vec v)
2382: {
2383: PetscFunctionBegin;
2385: PetscCheck(ts->setupcalled, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Must call TSSetUp() first");
2386: PetscTryTypeMethod(ts, settimeerror, v);
2387: PetscFunctionReturn(PETSC_SUCCESS);
2388: }
2390: /* ----- Routines to initialize and destroy a timestepper ---- */
2391: /*@
2392: TSSetProblemType - Sets the type of problem to be solved.
2394: Not collective
2396: Input Parameters:
2397: + ts - The `TS`
2398: - type - One of `TS_LINEAR`, `TS_NONLINEAR` where these types refer to problems of the forms
2399: .vb
2400: U_t - A U = 0 (linear)
2401: U_t - A(t) U = 0 (linear)
2402: F(t,U,U_t) = 0 (nonlinear)
2403: .ve
2405: Level: beginner
2407: .seealso: [](ch_ts), `TSSetUp()`, `TSProblemType`, `TS`
2408: @*/
2409: PetscErrorCode TSSetProblemType(TS ts, TSProblemType type)
2410: {
2411: PetscFunctionBegin;
2413: ts->problem_type = type;
2414: if (type == TS_LINEAR) {
2415: SNES snes;
2416: PetscCall(TSGetSNES(ts, &snes));
2417: PetscCall(SNESSetType(snes, SNESKSPONLY));
2418: }
2419: PetscFunctionReturn(PETSC_SUCCESS);
2420: }
2422: /*@
2423: TSGetProblemType - Gets the type of problem to be solved.
2425: Not collective
2427: Input Parameter:
2428: . ts - The `TS`
2430: Output Parameter:
2431: . type - One of `TS_LINEAR`, `TS_NONLINEAR` where these types refer to problems of the forms
2432: .vb
2433: M U_t = A U
2434: M(t) U_t = A(t) U
2435: F(t,U,U_t)
2436: .ve
2438: Level: beginner
2440: .seealso: [](ch_ts), `TSSetUp()`, `TSProblemType`, `TS`
2441: @*/
2442: PetscErrorCode TSGetProblemType(TS ts, TSProblemType *type)
2443: {
2444: PetscFunctionBegin;
2446: PetscAssertPointer(type, 2);
2447: *type = ts->problem_type;
2448: PetscFunctionReturn(PETSC_SUCCESS);
2449: }
2451: /*
2452: Attempt to check/preset a default value for the exact final time option. This is needed at the beginning of TSSolve() and in TSSetUp()
2453: */
2454: static PetscErrorCode TSSetExactFinalTimeDefault(TS ts)
2455: {
2456: PetscBool isnone;
2458: PetscFunctionBegin;
2459: PetscCall(TSGetAdapt(ts, &ts->adapt));
2460: PetscCall(TSAdaptSetDefaultType(ts->adapt, ts->default_adapt_type));
2462: PetscCall(PetscObjectTypeCompare((PetscObject)ts->adapt, TSADAPTNONE, &isnone));
2463: if (!isnone && ts->exact_final_time == TS_EXACTFINALTIME_UNSPECIFIED) ts->exact_final_time = TS_EXACTFINALTIME_MATCHSTEP;
2464: else if (ts->exact_final_time == TS_EXACTFINALTIME_UNSPECIFIED) ts->exact_final_time = TS_EXACTFINALTIME_INTERPOLATE;
2465: PetscFunctionReturn(PETSC_SUCCESS);
2466: }
2468: /*@
2469: TSSetUp - Sets up the internal data structures for the later use of a timestepper.
2471: Collective
2473: Input Parameter:
2474: . ts - the `TS` context obtained from `TSCreate()`
2476: Level: advanced
2478: Note:
2479: For basic use of the `TS` solvers the user need not explicitly call
2480: `TSSetUp()`, since these actions will automatically occur during
2481: the call to `TSStep()` or `TSSolve()`. However, if one wishes to control this
2482: phase separately, `TSSetUp()` should be called after `TSCreate()`
2483: and optional routines of the form TSSetXXX(), but before `TSStep()` and `TSSolve()`.
2485: .seealso: [](ch_ts), `TSCreate()`, `TS`, `TSStep()`, `TSDestroy()`, `TSSolve()`
2486: @*/
2487: PetscErrorCode TSSetUp(TS ts)
2488: {
2489: DM dm;
2490: PetscErrorCode (*func)(SNES, Vec, Vec, void *);
2491: PetscErrorCode (*jac)(SNES, Vec, Mat, Mat, void *);
2492: TSIFunctionFn *ifun;
2493: TSIJacobianFn *ijac;
2494: TSI2JacobianFn *i2jac;
2495: TSRHSJacobianFn *rhsjac;
2497: PetscFunctionBegin;
2499: if (ts->setupcalled) PetscFunctionReturn(PETSC_SUCCESS);
2501: if (!((PetscObject)ts)->type_name) {
2502: PetscCall(TSGetIFunction(ts, NULL, &ifun, NULL));
2503: PetscCall(TSSetType(ts, ifun ? TSBEULER : TSEULER));
2504: }
2506: if (!ts->vec_sol) {
2507: PetscCheck(ts->dm, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Must call TSSetSolution() first");
2508: PetscCall(DMCreateGlobalVector(ts->dm, &ts->vec_sol));
2509: }
2511: if (!ts->Jacp && ts->Jacprhs) { /* IJacobianP shares the same matrix with RHSJacobianP if only RHSJacobianP is provided */
2512: PetscCall(PetscObjectReference((PetscObject)ts->Jacprhs));
2513: ts->Jacp = ts->Jacprhs;
2514: }
2516: if (ts->quadraturets) {
2517: PetscCall(TSSetUp(ts->quadraturets));
2518: PetscCall(VecDestroy(&ts->vec_costintegrand));
2519: PetscCall(VecDuplicate(ts->quadraturets->vec_sol, &ts->vec_costintegrand));
2520: }
2522: PetscCall(TSGetRHSJacobian(ts, NULL, NULL, &rhsjac, NULL));
2523: if (rhsjac == TSComputeRHSJacobianConstant) {
2524: Mat Amat, Pmat;
2525: SNES snes;
2526: PetscCall(TSGetSNES(ts, &snes));
2527: PetscCall(SNESGetJacobian(snes, &Amat, &Pmat, NULL, NULL));
2528: /* Matching matrices implies that an IJacobian is NOT set, because if it had been set, the IJacobian's matrix would
2529: * have displaced the RHS matrix */
2530: if (Amat && Amat == ts->Arhs) {
2531: /* 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 */
2532: PetscCall(MatDuplicate(ts->Arhs, MAT_COPY_VALUES, &Amat));
2533: PetscCall(SNESSetJacobian(snes, Amat, NULL, NULL, NULL));
2534: PetscCall(MatDestroy(&Amat));
2535: }
2536: if (Pmat && Pmat == ts->Brhs) {
2537: PetscCall(MatDuplicate(ts->Brhs, MAT_COPY_VALUES, &Pmat));
2538: PetscCall(SNESSetJacobian(snes, NULL, Pmat, NULL, NULL));
2539: PetscCall(MatDestroy(&Pmat));
2540: }
2541: }
2543: PetscCall(TSGetAdapt(ts, &ts->adapt));
2544: PetscCall(TSAdaptSetDefaultType(ts->adapt, ts->default_adapt_type));
2546: PetscTryTypeMethod(ts, setup);
2548: PetscCall(TSSetExactFinalTimeDefault(ts));
2550: /* In the case where we've set a DMTSFunction or what have you, we need the default SNESFunction
2551: to be set right but can't do it elsewhere due to the overreliance on ctx=ts.
2552: */
2553: PetscCall(TSGetDM(ts, &dm));
2554: PetscCall(DMSNESGetFunction(dm, &func, NULL));
2555: if (!func) PetscCall(DMSNESSetFunction(dm, SNESTSFormFunction, ts));
2557: /* If the SNES doesn't have a jacobian set and the TS has an ijacobian or rhsjacobian set, set the SNES to use it.
2558: Otherwise, the SNES will use coloring internally to form the Jacobian.
2559: */
2560: PetscCall(DMSNESGetJacobian(dm, &jac, NULL));
2561: PetscCall(DMTSGetIJacobian(dm, &ijac, NULL));
2562: PetscCall(DMTSGetI2Jacobian(dm, &i2jac, NULL));
2563: PetscCall(DMTSGetRHSJacobian(dm, &rhsjac, NULL));
2564: if (!jac && (ijac || i2jac || rhsjac)) PetscCall(DMSNESSetJacobian(dm, SNESTSFormJacobian, ts));
2566: /* if time integration scheme has a starting method, call it */
2567: PetscTryTypeMethod(ts, startingmethod);
2569: ts->setupcalled = PETSC_TRUE;
2570: PetscFunctionReturn(PETSC_SUCCESS);
2571: }
2573: /*@
2574: TSReset - Resets a `TS` context to the state it was in before `TSSetUp()` was called and removes any allocated `Vec` and `Mat` from its data structures
2576: Collective
2578: Input Parameter:
2579: . ts - the `TS` context obtained from `TSCreate()`
2581: Level: developer
2583: Notes:
2584: Any options set on the `TS` object, including those set with `TSSetFromOptions()` remain.
2586: See also `TSSetResize()` to change the size of the system being integrated (for example by adaptive mesh refinement) during the time integration.
2588: .seealso: [](ch_ts), `TS`, `TSCreate()`, `TSSetUp()`, `TSDestroy()`, `TSSetResize()`
2589: @*/
2590: PetscErrorCode TSReset(TS ts)
2591: {
2592: TS_RHSSplitLink ilink = ts->tsrhssplit, next;
2594: PetscFunctionBegin;
2597: PetscTryTypeMethod(ts, reset);
2598: if (ts->snes) PetscCall(SNESReset(ts->snes));
2599: if (ts->adapt) PetscCall(TSAdaptReset(ts->adapt));
2601: PetscCall(MatDestroy(&ts->Arhs));
2602: PetscCall(MatDestroy(&ts->Brhs));
2603: PetscCall(VecDestroy(&ts->Frhs));
2604: PetscCall(VecDestroy(&ts->vec_sol));
2605: PetscCall(VecDestroy(&ts->vec_sol0));
2606: PetscCall(VecDestroy(&ts->vec_dot));
2607: PetscCall(VecDestroy(&ts->vatol));
2608: PetscCall(VecDestroy(&ts->vrtol));
2609: PetscCall(VecDestroyVecs(ts->nwork, &ts->work));
2611: PetscCall(MatDestroy(&ts->Jacprhs));
2612: PetscCall(MatDestroy(&ts->Jacp));
2613: if (ts->forward_solve) PetscCall(TSForwardReset(ts));
2614: if (ts->quadraturets) {
2615: PetscCall(TSReset(ts->quadraturets));
2616: PetscCall(VecDestroy(&ts->vec_costintegrand));
2617: }
2618: while (ilink) {
2619: next = ilink->next;
2620: PetscCall(TSDestroy(&ilink->ts));
2621: PetscCall(PetscFree(ilink->splitname));
2622: PetscCall(ISDestroy(&ilink->is));
2623: PetscCall(PetscFree(ilink));
2624: ilink = next;
2625: }
2626: ts->tsrhssplit = NULL;
2627: ts->num_rhs_splits = 0;
2628: if (ts->eval_times) {
2629: PetscCall(PetscFree(ts->eval_times->time_points));
2630: PetscCall(PetscFree(ts->eval_times->sol_times));
2631: PetscCall(VecDestroyVecs(ts->eval_times->num_time_points, &ts->eval_times->sol_vecs));
2632: PetscCall(PetscFree(ts->eval_times));
2633: }
2634: ts->rhsjacobian.time = PETSC_MIN_REAL;
2635: ts->rhsjacobian.scale = 1.0;
2636: ts->ijacobian.shift = 1.0;
2637: ts->setupcalled = PETSC_FALSE;
2638: PetscFunctionReturn(PETSC_SUCCESS);
2639: }
2641: static PetscErrorCode TSResizeReset(TS);
2643: /*@
2644: TSDestroy - Destroys the timestepper context that was created
2645: with `TSCreate()`.
2647: Collective
2649: Input Parameter:
2650: . ts - the `TS` context obtained from `TSCreate()`
2652: Level: beginner
2654: .seealso: [](ch_ts), `TS`, `TSCreate()`, `TSSetUp()`, `TSSolve()`
2655: @*/
2656: PetscErrorCode TSDestroy(TS *ts)
2657: {
2658: PetscFunctionBegin;
2659: if (!*ts) PetscFunctionReturn(PETSC_SUCCESS);
2661: if (--((PetscObject)*ts)->refct > 0) {
2662: *ts = NULL;
2663: PetscFunctionReturn(PETSC_SUCCESS);
2664: }
2666: PetscCall(TSReset(*ts));
2667: PetscCall(TSAdjointReset(*ts));
2668: if ((*ts)->forward_solve) PetscCall(TSForwardReset(*ts));
2669: PetscCall(TSResizeReset(*ts));
2671: /* if memory was published with SAWs then destroy it */
2672: PetscCall(PetscObjectSAWsViewOff((PetscObject)*ts));
2673: PetscTryTypeMethod(*ts, destroy);
2675: PetscCall(TSTrajectoryDestroy(&(*ts)->trajectory));
2677: PetscCall(TSAdaptDestroy(&(*ts)->adapt));
2678: PetscCall(TSEventDestroy(&(*ts)->event));
2680: PetscCall(SNESDestroy(&(*ts)->snes));
2681: PetscCall(SNESDestroy(&(*ts)->snesrhssplit));
2682: PetscCall(DMDestroy(&(*ts)->dm));
2683: PetscCall(TSMonitorCancel(*ts));
2684: PetscCall(TSAdjointMonitorCancel(*ts));
2686: PetscCall(TSDestroy(&(*ts)->quadraturets));
2687: PetscCall(PetscHeaderDestroy(ts));
2688: PetscFunctionReturn(PETSC_SUCCESS);
2689: }
2691: /*@
2692: TSGetSNES - Returns the `SNES` (nonlinear solver) associated with
2693: a `TS` (timestepper) context. Valid only for nonlinear problems.
2695: Not Collective, but snes is parallel if ts is parallel
2697: Input Parameter:
2698: . ts - the `TS` context obtained from `TSCreate()`
2700: Output Parameter:
2701: . snes - the nonlinear solver context
2703: Level: beginner
2705: Notes:
2706: The user can then directly manipulate the `SNES` context to set various
2707: options, etc. Likewise, the user can then extract and manipulate the
2708: `KSP`, and `PC` contexts as well.
2710: `TSGetSNES()` does not work for integrators that do not use `SNES`; in
2711: this case `TSGetSNES()` returns `NULL` in `snes`.
2713: .seealso: [](ch_ts), `TS`, `SNES`, `TSCreate()`, `TSSetUp()`, `TSSolve()`
2714: @*/
2715: PetscErrorCode TSGetSNES(TS ts, SNES *snes)
2716: {
2717: PetscFunctionBegin;
2719: PetscAssertPointer(snes, 2);
2720: if (!ts->snes) {
2721: PetscCall(SNESCreate(PetscObjectComm((PetscObject)ts), &ts->snes));
2722: PetscCall(PetscObjectSetOptions((PetscObject)ts->snes, ((PetscObject)ts)->options));
2723: PetscCall(SNESSetFunction(ts->snes, NULL, SNESTSFormFunction, ts));
2724: PetscCall(PetscObjectIncrementTabLevel((PetscObject)ts->snes, (PetscObject)ts, 1));
2725: if (ts->dm) PetscCall(SNESSetDM(ts->snes, ts->dm));
2726: if (ts->problem_type == TS_LINEAR) PetscCall(SNESSetType(ts->snes, SNESKSPONLY));
2727: }
2728: *snes = ts->snes;
2729: PetscFunctionReturn(PETSC_SUCCESS);
2730: }
2732: /*@
2733: TSSetSNES - Set the `SNES` (nonlinear solver) to be used by the `TS` timestepping context
2735: Collective
2737: Input Parameters:
2738: + ts - the `TS` context obtained from `TSCreate()`
2739: - snes - the nonlinear solver context
2741: Level: developer
2743: Note:
2744: Most users should have the `TS` created by calling `TSGetSNES()`
2746: .seealso: [](ch_ts), `TS`, `SNES`, `TSCreate()`, `TSSetUp()`, `TSSolve()`, `TSGetSNES()`
2747: @*/
2748: PetscErrorCode TSSetSNES(TS ts, SNES snes)
2749: {
2750: PetscErrorCode (*func)(SNES, Vec, Mat, Mat, void *);
2752: PetscFunctionBegin;
2755: PetscCall(PetscObjectReference((PetscObject)snes));
2756: PetscCall(SNESDestroy(&ts->snes));
2758: ts->snes = snes;
2760: PetscCall(SNESSetFunction(ts->snes, NULL, SNESTSFormFunction, ts));
2761: PetscCall(SNESGetJacobian(ts->snes, NULL, NULL, &func, NULL));
2762: if (func == SNESTSFormJacobian) PetscCall(SNESSetJacobian(ts->snes, NULL, NULL, SNESTSFormJacobian, ts));
2763: PetscFunctionReturn(PETSC_SUCCESS);
2764: }
2766: /*@
2767: TSGetKSP - Returns the `KSP` (linear solver) associated with
2768: a `TS` (timestepper) context.
2770: Not Collective, but `ksp` is parallel if `ts` is parallel
2772: Input Parameter:
2773: . ts - the `TS` context obtained from `TSCreate()`
2775: Output Parameter:
2776: . ksp - the nonlinear solver context
2778: Level: beginner
2780: Notes:
2781: The user can then directly manipulate the `KSP` context to set various
2782: options, etc. Likewise, the user can then extract and manipulate the
2783: `PC` context as well.
2785: `TSGetKSP()` does not work for integrators that do not use `KSP`;
2786: in this case `TSGetKSP()` returns `NULL` in `ksp`.
2788: .seealso: [](ch_ts), `TS`, `SNES`, `KSP`, `TSCreate()`, `TSSetUp()`, `TSSolve()`, `TSGetSNES()`
2789: @*/
2790: PetscErrorCode TSGetKSP(TS ts, KSP *ksp)
2791: {
2792: SNES snes;
2794: PetscFunctionBegin;
2796: PetscAssertPointer(ksp, 2);
2797: PetscCheck(((PetscObject)ts)->type_name, PETSC_COMM_SELF, PETSC_ERR_ARG_NULL, "KSP is not created yet. Call TSSetType() first");
2798: PetscCheck(ts->problem_type == TS_LINEAR, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Linear only; use TSGetSNES()");
2799: PetscCall(TSGetSNES(ts, &snes));
2800: PetscCall(SNESGetKSP(snes, ksp));
2801: PetscFunctionReturn(PETSC_SUCCESS);
2802: }
2804: /* ----------- Routines to set solver parameters ---------- */
2806: /*@
2807: TSSetMaxSteps - Sets the maximum number of steps to use.
2809: Logically Collective
2811: Input Parameters:
2812: + ts - the `TS` context obtained from `TSCreate()`
2813: - maxsteps - maximum number of steps to use
2815: Options Database Key:
2816: . -ts_max_steps maxsteps - Sets maxsteps
2818: Level: intermediate
2820: Note:
2821: Use `PETSC_DETERMINE` to reset the maximum number of steps to the default from when the object's type was set
2823: The default maximum number of steps is 5,000
2825: Fortran Note:
2826: Use `PETSC_DETERMINE_INTEGER`
2828: .seealso: [](ch_ts), `TS`, `TSGetMaxSteps()`, `TSSetMaxTime()`, `TSSetExactFinalTime()`
2829: @*/
2830: PetscErrorCode TSSetMaxSteps(TS ts, PetscInt maxsteps)
2831: {
2832: PetscFunctionBegin;
2835: if (maxsteps == PETSC_DETERMINE) {
2836: ts->max_steps = ts->default_max_steps;
2837: } else {
2838: PetscCheck(maxsteps >= 0, PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_OUTOFRANGE, "Maximum number of steps must be non-negative");
2839: ts->max_steps = maxsteps;
2840: }
2841: PetscFunctionReturn(PETSC_SUCCESS);
2842: }
2844: /*@
2845: TSGetMaxSteps - Gets the maximum number of steps to use.
2847: Not Collective
2849: Input Parameter:
2850: . ts - the `TS` context obtained from `TSCreate()`
2852: Output Parameter:
2853: . maxsteps - maximum number of steps to use
2855: Level: advanced
2857: .seealso: [](ch_ts), `TS`, `TSSetMaxSteps()`, `TSGetMaxTime()`, `TSSetMaxTime()`
2858: @*/
2859: PetscErrorCode TSGetMaxSteps(TS ts, PetscInt *maxsteps)
2860: {
2861: PetscFunctionBegin;
2863: PetscAssertPointer(maxsteps, 2);
2864: *maxsteps = ts->max_steps;
2865: PetscFunctionReturn(PETSC_SUCCESS);
2866: }
2868: /*@
2869: TSSetRunSteps - Sets the maximum number of steps to take in each call to `TSSolve()`.
2871: If the step count when `TSSolve()` is `start_step`, this will stop the simulation once `current_step - start_step >= run_steps`.
2872: Comparatively, `TSSetMaxSteps()` will stop if `current_step >= max_steps`.
2873: The simulation will stop when either condition is reached.
2875: Logically Collective
2877: Input Parameters:
2878: + ts - the `TS` context obtained from `TSCreate()`
2879: - runsteps - maximum number of steps to take in each call to `TSSolve()`;
2881: Options Database Key:
2882: . -ts_run_steps runsteps - Sets runsteps
2884: Level: intermediate
2886: Note:
2887: The default is `PETSC_UNLIMITED`
2889: .seealso: [](ch_ts), `TS`, `TSGetRunSteps()`, `TSSetMaxTime()`, `TSSetExactFinalTime()`, `TSSetMaxSteps()`
2890: @*/
2891: PetscErrorCode TSSetRunSteps(TS ts, PetscInt runsteps)
2892: {
2893: PetscFunctionBegin;
2896: if (runsteps == PETSC_DETERMINE) {
2897: ts->run_steps = PETSC_UNLIMITED;
2898: } else {
2899: PetscCheck(runsteps >= 0, PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_OUTOFRANGE, "Max number of steps to take in each call to TSSolve must be non-negative");
2900: ts->run_steps = runsteps;
2901: }
2902: PetscFunctionReturn(PETSC_SUCCESS);
2903: }
2905: /*@
2906: TSGetRunSteps - Gets the maximum number of steps to take in each call to `TSSolve()`.
2908: Not Collective
2910: Input Parameter:
2911: . ts - the `TS` context obtained from `TSCreate()`
2913: Output Parameter:
2914: . runsteps - maximum number of steps to take in each call to `TSSolve`.
2916: Level: advanced
2918: .seealso: [](ch_ts), `TS`, `TSSetRunSteps()`, `TSGetMaxTime()`, `TSSetMaxTime()`, `TSGetMaxSteps()`
2919: @*/
2920: PetscErrorCode TSGetRunSteps(TS ts, PetscInt *runsteps)
2921: {
2922: PetscFunctionBegin;
2924: PetscAssertPointer(runsteps, 2);
2925: *runsteps = ts->run_steps;
2926: PetscFunctionReturn(PETSC_SUCCESS);
2927: }
2929: /*@
2930: TSSetMaxTime - Sets the maximum (or final) time for timestepping.
2932: Logically Collective
2934: Input Parameters:
2935: + ts - the `TS` context obtained from `TSCreate()`
2936: - maxtime - final time to step to
2938: Options Database Key:
2939: . -ts_max_time maxtime - Sets maxtime
2941: Level: intermediate
2943: Notes:
2944: Use `PETSC_DETERMINE` to reset the maximum time to the default from when the object's type was set
2946: The default maximum time is 5.0
2948: Fortran Note:
2949: Use `PETSC_DETERMINE_REAL`
2951: .seealso: [](ch_ts), `TS`, `TSGetMaxTime()`, `TSSetMaxSteps()`, `TSSetExactFinalTime()`
2952: @*/
2953: PetscErrorCode TSSetMaxTime(TS ts, PetscReal maxtime)
2954: {
2955: PetscFunctionBegin;
2958: if (maxtime == PETSC_DETERMINE) {
2959: ts->max_time = ts->default_max_time;
2960: } else {
2961: ts->max_time = maxtime;
2962: }
2963: PetscFunctionReturn(PETSC_SUCCESS);
2964: }
2966: /*@
2967: TSGetMaxTime - Gets the maximum (or final) time for timestepping.
2969: Not Collective
2971: Input Parameter:
2972: . ts - the `TS` context obtained from `TSCreate()`
2974: Output Parameter:
2975: . maxtime - final time to step to
2977: Level: advanced
2979: .seealso: [](ch_ts), `TS`, `TSSetMaxTime()`, `TSGetMaxSteps()`, `TSSetMaxSteps()`
2980: @*/
2981: PetscErrorCode TSGetMaxTime(TS ts, PetscReal *maxtime)
2982: {
2983: PetscFunctionBegin;
2985: PetscAssertPointer(maxtime, 2);
2986: *maxtime = ts->max_time;
2987: PetscFunctionReturn(PETSC_SUCCESS);
2988: }
2990: // PetscClangLinter pragma disable: -fdoc-*
2991: /*@
2992: TSSetInitialTimeStep - Deprecated, use `TSSetTime()` and `TSSetTimeStep()`.
2994: Level: deprecated
2996: @*/
2997: PetscErrorCode TSSetInitialTimeStep(TS ts, PetscReal initial_time, PetscReal time_step)
2998: {
2999: PetscFunctionBegin;
3001: PetscCall(TSSetTime(ts, initial_time));
3002: PetscCall(TSSetTimeStep(ts, time_step));
3003: PetscFunctionReturn(PETSC_SUCCESS);
3004: }
3006: // PetscClangLinter pragma disable: -fdoc-*
3007: /*@
3008: TSGetDuration - Deprecated, use `TSGetMaxSteps()` and `TSGetMaxTime()`.
3010: Level: deprecated
3012: @*/
3013: PetscErrorCode TSGetDuration(TS ts, PetscInt *maxsteps, PetscReal *maxtime)
3014: {
3015: PetscFunctionBegin;
3017: if (maxsteps) {
3018: PetscAssertPointer(maxsteps, 2);
3019: *maxsteps = ts->max_steps;
3020: }
3021: if (maxtime) {
3022: PetscAssertPointer(maxtime, 3);
3023: *maxtime = ts->max_time;
3024: }
3025: PetscFunctionReturn(PETSC_SUCCESS);
3026: }
3028: // PetscClangLinter pragma disable: -fdoc-*
3029: /*@
3030: TSSetDuration - Deprecated, use `TSSetMaxSteps()` and `TSSetMaxTime()`.
3032: Level: deprecated
3034: @*/
3035: PetscErrorCode TSSetDuration(TS ts, PetscInt maxsteps, PetscReal maxtime)
3036: {
3037: PetscFunctionBegin;
3038: if (maxsteps != PETSC_CURRENT) PetscCall(TSSetMaxSteps(ts, maxsteps));
3039: if (maxtime != (PetscReal)PETSC_CURRENT) PetscCall(TSSetMaxTime(ts, maxtime));
3040: PetscFunctionReturn(PETSC_SUCCESS);
3041: }
3043: // PetscClangLinter pragma disable: -fdoc-*
3044: /*@
3045: TSGetTimeStepNumber - Deprecated, use `TSGetStepNumber()`.
3047: Level: deprecated
3049: @*/
3050: PetscErrorCode TSGetTimeStepNumber(TS ts, PetscInt *steps)
3051: {
3052: return TSGetStepNumber(ts, steps);
3053: }
3055: // PetscClangLinter pragma disable: -fdoc-*
3056: /*@
3057: TSGetTotalSteps - Deprecated, use `TSGetStepNumber()`.
3059: Level: deprecated
3061: @*/
3062: PetscErrorCode TSGetTotalSteps(TS ts, PetscInt *steps)
3063: {
3064: return TSGetStepNumber(ts, steps);
3065: }
3067: /*@
3068: TSSetSolution - Sets the initial solution vector
3069: for use by the `TS` routines.
3071: Logically Collective
3073: Input Parameters:
3074: + ts - the `TS` context obtained from `TSCreate()`
3075: - u - the solution vector
3077: Level: beginner
3079: .seealso: [](ch_ts), `TS`, `TSSetSolutionFunction()`, `TSGetSolution()`, `TSCreate()`
3080: @*/
3081: PetscErrorCode TSSetSolution(TS ts, Vec u)
3082: {
3083: DM dm;
3085: PetscFunctionBegin;
3088: PetscCall(PetscObjectReference((PetscObject)u));
3089: PetscCall(VecDestroy(&ts->vec_sol));
3090: ts->vec_sol = u;
3092: PetscCall(TSGetDM(ts, &dm));
3093: PetscCall(DMShellSetGlobalVector(dm, u));
3094: PetscFunctionReturn(PETSC_SUCCESS);
3095: }
3097: /*@C
3098: TSSetPreStep - Sets the general-purpose function
3099: called once at the beginning of each time step.
3101: Logically Collective
3103: Input Parameters:
3104: + ts - The `TS` context obtained from `TSCreate()`
3105: - func - The function
3107: Calling sequence of `func`:
3108: . ts - the `TS` context
3110: Level: intermediate
3112: .seealso: [](ch_ts), `TS`, `TSSetPreStage()`, `TSSetPostStage()`, `TSSetPostStep()`, `TSStep()`, `TSRestartStep()`
3113: @*/
3114: PetscErrorCode TSSetPreStep(TS ts, PetscErrorCode (*func)(TS ts))
3115: {
3116: PetscFunctionBegin;
3118: ts->prestep = func;
3119: PetscFunctionReturn(PETSC_SUCCESS);
3120: }
3122: /*@
3123: TSPreStep - Runs the user-defined pre-step function provided with `TSSetPreStep()`
3125: Collective
3127: Input Parameter:
3128: . ts - The `TS` context obtained from `TSCreate()`
3130: Level: developer
3132: Note:
3133: `TSPreStep()` is typically used within time stepping implementations,
3134: so most users would not generally call this routine themselves.
3136: .seealso: [](ch_ts), `TS`, `TSSetPreStep()`, `TSPreStage()`, `TSPostStage()`, `TSPostStep()`
3137: @*/
3138: PetscErrorCode TSPreStep(TS ts)
3139: {
3140: PetscFunctionBegin;
3142: if (ts->prestep) {
3143: Vec U;
3144: PetscObjectId idprev;
3145: PetscBool sameObject;
3146: PetscObjectState sprev, spost;
3148: PetscCall(TSGetSolution(ts, &U));
3149: PetscCall(PetscObjectGetId((PetscObject)U, &idprev));
3150: PetscCall(PetscObjectStateGet((PetscObject)U, &sprev));
3151: PetscCallBack("TS callback preset", (*ts->prestep)(ts));
3152: PetscCall(TSGetSolution(ts, &U));
3153: PetscCall(PetscObjectCompareId((PetscObject)U, idprev, &sameObject));
3154: PetscCall(PetscObjectStateGet((PetscObject)U, &spost));
3155: if (!sameObject || sprev != spost) PetscCall(TSRestartStep(ts));
3156: }
3157: PetscFunctionReturn(PETSC_SUCCESS);
3158: }
3160: /*@C
3161: TSSetPreStage - Sets the general-purpose function
3162: called once at the beginning of each stage.
3164: Logically Collective
3166: Input Parameters:
3167: + ts - The `TS` context obtained from `TSCreate()`
3168: - func - The function
3170: Calling sequence of `func`:
3171: + ts - the `TS` context
3172: - stagetime - the stage time
3174: Level: intermediate
3176: Note:
3177: There may be several stages per time step. If the solve for a given stage fails, the step may be rejected and retried.
3178: The time step number being computed can be queried using `TSGetStepNumber()` and the total size of the step being
3179: attempted can be obtained using `TSGetTimeStep()`. The time at the start of the step is available via `TSGetTime()`.
3181: .seealso: [](ch_ts), `TS`, `TSSetPostStage()`, `TSSetPreStep()`, `TSSetPostStep()`, `TSGetApplicationContext()`
3182: @*/
3183: PetscErrorCode TSSetPreStage(TS ts, PetscErrorCode (*func)(TS ts, PetscReal stagetime))
3184: {
3185: PetscFunctionBegin;
3187: ts->prestage = func;
3188: PetscFunctionReturn(PETSC_SUCCESS);
3189: }
3191: /*@C
3192: TSSetPostStage - Sets the general-purpose function
3193: called once at the end of each stage.
3195: Logically Collective
3197: Input Parameters:
3198: + ts - The `TS` context obtained from `TSCreate()`
3199: - func - The function
3201: Calling sequence of `func`:
3202: + ts - the `TS` context
3203: . stagetime - the stage time
3204: . stageindex - the stage index
3205: - Y - Array of vectors (of size = total number of stages) with the stage solutions
3207: Level: intermediate
3209: Note:
3210: There may be several stages per time step. If the solve for a given stage fails, the step may be rejected and retried.
3211: The time step number being computed can be queried using `TSGetStepNumber()` and the total size of the step being
3212: attempted can be obtained using `TSGetTimeStep()`. The time at the start of the step is available via `TSGetTime()`.
3214: .seealso: [](ch_ts), `TS`, `TSSetPreStage()`, `TSSetPreStep()`, `TSSetPostStep()`, `TSGetApplicationContext()`
3215: @*/
3216: PetscErrorCode TSSetPostStage(TS ts, PetscErrorCode (*func)(TS ts, PetscReal stagetime, PetscInt stageindex, Vec *Y))
3217: {
3218: PetscFunctionBegin;
3220: ts->poststage = func;
3221: PetscFunctionReturn(PETSC_SUCCESS);
3222: }
3224: /*@C
3225: TSSetPostEvaluate - Sets the general-purpose function
3226: called at the end of each step evaluation.
3228: Logically Collective
3230: Input Parameters:
3231: + ts - The `TS` context obtained from `TSCreate()`
3232: - func - The function
3234: Calling sequence of `func`:
3235: . ts - the `TS` context
3237: Level: intermediate
3239: Note:
3240: The function set by `TSSetPostEvaluate()` is called after the solution is evaluated, or after the step rollback.
3241: Inside the `func` callback, the solution vector can be obtained with `TSGetSolution()`, and modified, if need be.
3242: The time step can be obtained with `TSGetTimeStep()`, and the time at the start of the step - via `TSGetTime()`.
3243: The potential changes to the solution vector introduced by event handling (`postevent()`) are not relevant for `TSSetPostEvaluate()`,
3244: but are relevant for `TSSetPostStep()`, according to the function call scheme in `TSSolve()`, as shown below
3245: .vb
3246: ...
3247: Step()
3248: PostEvaluate()
3249: EventHandling()
3250: step_rollback ? PostEvaluate() : PostStep()
3251: ...
3252: .ve
3253: where EventHandling() may result in one of the following three outcomes
3254: .vb
3255: (1) | successful step | solution intact
3256: (2) | successful step | solution modified by `postevent()`
3257: (3) | step_rollback | solution rolled back
3258: .ve
3260: .seealso: [](ch_ts), `TS`, `TSSetPreStage()`, `TSSetPreStep()`, `TSSetPostStep()`, `TSGetApplicationContext()`
3261: @*/
3262: PetscErrorCode TSSetPostEvaluate(TS ts, PetscErrorCode (*func)(TS ts))
3263: {
3264: PetscFunctionBegin;
3266: ts->postevaluate = func;
3267: PetscFunctionReturn(PETSC_SUCCESS);
3268: }
3270: /*@
3271: TSPreStage - Runs the user-defined pre-stage function set using `TSSetPreStage()`
3273: Collective
3275: Input Parameters:
3276: + ts - The `TS` context obtained from `TSCreate()`
3277: - stagetime - The absolute time of the current stage
3279: Level: developer
3281: Note:
3282: `TSPreStage()` is typically used within time stepping implementations,
3283: most users would not generally call this routine themselves.
3285: .seealso: [](ch_ts), `TS`, `TSPostStage()`, `TSSetPreStep()`, `TSPreStep()`, `TSPostStep()`
3286: @*/
3287: PetscErrorCode TSPreStage(TS ts, PetscReal stagetime)
3288: {
3289: PetscFunctionBegin;
3291: if (ts->prestage) PetscCallBack("TS callback prestage", (*ts->prestage)(ts, stagetime));
3292: PetscFunctionReturn(PETSC_SUCCESS);
3293: }
3295: /*@
3296: TSPostStage - Runs the user-defined post-stage function set using `TSSetPostStage()`
3298: Collective
3300: Input Parameters:
3301: + ts - The `TS` context obtained from `TSCreate()`
3302: . stagetime - The absolute time of the current stage
3303: . stageindex - Stage number
3304: - Y - Array of vectors (of size = total number of stages) with the stage solutions
3306: Level: developer
3308: Note:
3309: `TSPostStage()` is typically used within time stepping implementations,
3310: most users would not generally call this routine themselves.
3312: .seealso: [](ch_ts), `TS`, `TSPreStage()`, `TSSetPreStep()`, `TSPreStep()`, `TSPostStep()`
3313: @*/
3314: PetscErrorCode TSPostStage(TS ts, PetscReal stagetime, PetscInt stageindex, Vec Y[])
3315: {
3316: PetscFunctionBegin;
3318: if (ts->poststage) PetscCallBack("TS callback poststage", (*ts->poststage)(ts, stagetime, stageindex, Y));
3319: PetscFunctionReturn(PETSC_SUCCESS);
3320: }
3322: /*@
3323: TSPostEvaluate - Runs the user-defined post-evaluate function set using `TSSetPostEvaluate()`
3325: Collective
3327: Input Parameter:
3328: . ts - The `TS` context obtained from `TSCreate()`
3330: Level: developer
3332: Note:
3333: `TSPostEvaluate()` is typically used within time stepping implementations,
3334: most users would not generally call this routine themselves.
3336: .seealso: [](ch_ts), `TS`, `TSSetPostEvaluate()`, `TSSetPreStep()`, `TSPreStep()`, `TSPostStep()`
3337: @*/
3338: PetscErrorCode TSPostEvaluate(TS ts)
3339: {
3340: PetscFunctionBegin;
3342: if (ts->postevaluate) {
3343: Vec U;
3344: PetscObjectState sprev, spost;
3346: PetscCall(TSGetSolution(ts, &U));
3347: PetscCall(PetscObjectStateGet((PetscObject)U, &sprev));
3348: PetscCallBack("TS callback postevaluate", (*ts->postevaluate)(ts));
3349: PetscCall(PetscObjectStateGet((PetscObject)U, &spost));
3350: if (sprev != spost) PetscCall(TSRestartStep(ts));
3351: }
3352: PetscFunctionReturn(PETSC_SUCCESS);
3353: }
3355: /*@C
3356: TSSetPostStep - Sets the general-purpose function
3357: called once at the end of each successful time step.
3359: Logically Collective
3361: Input Parameters:
3362: + ts - The `TS` context obtained from `TSCreate()`
3363: - func - The function
3365: Calling sequence of `func`:
3366: . ts - the `TS` context
3368: Level: intermediate
3370: Note:
3371: The function set by `TSSetPostStep()` is called after each successful step. If the event handler locates an event at the
3372: given step, and `postevent()` modifies the solution vector, the solution vector obtained by `TSGetSolution()` inside `func` will
3373: contain the changes. To get the solution without these changes, use `TSSetPostEvaluate()` to set the appropriate callback.
3374: The scheme of the relevant function calls in `TSSolve()` is shown below
3375: .vb
3376: ...
3377: Step()
3378: PostEvaluate()
3379: EventHandling()
3380: step_rollback ? PostEvaluate() : PostStep()
3381: ...
3382: .ve
3383: where EventHandling() may result in one of the following three outcomes
3384: .vb
3385: (1) | successful step | solution intact
3386: (2) | successful step | solution modified by `postevent()`
3387: (3) | step_rollback | solution rolled back
3388: .ve
3390: .seealso: [](ch_ts), `TS`, `TSSetPreStep()`, `TSSetPreStage()`, `TSSetPostEvaluate()`, `TSGetTimeStep()`, `TSGetStepNumber()`, `TSGetTime()`, `TSRestartStep()`
3391: @*/
3392: PetscErrorCode TSSetPostStep(TS ts, PetscErrorCode (*func)(TS ts))
3393: {
3394: PetscFunctionBegin;
3396: ts->poststep = func;
3397: PetscFunctionReturn(PETSC_SUCCESS);
3398: }
3400: /*@
3401: TSPostStep - Runs the user-defined post-step function that was set with `TSSetPostStep()`
3403: Collective
3405: Input Parameter:
3406: . ts - The `TS` context obtained from `TSCreate()`
3408: Note:
3409: `TSPostStep()` is typically used within time stepping implementations,
3410: so most users would not generally call this routine themselves.
3412: Level: developer
3414: .seealso: [](ch_ts), `TS`, `TSSetPreStep()`, `TSSetPreStage()`, `TSSetPostEvaluate()`, `TSGetTimeStep()`, `TSGetStepNumber()`, `TSGetTime()`, `TSSetPostStep()`
3415: @*/
3416: PetscErrorCode TSPostStep(TS ts)
3417: {
3418: PetscFunctionBegin;
3420: if (ts->poststep) {
3421: Vec U;
3422: PetscObjectId idprev;
3423: PetscBool sameObject;
3424: PetscObjectState sprev, spost;
3426: PetscCall(TSGetSolution(ts, &U));
3427: PetscCall(PetscObjectGetId((PetscObject)U, &idprev));
3428: PetscCall(PetscObjectStateGet((PetscObject)U, &sprev));
3429: PetscCallBack("TS callback poststep", (*ts->poststep)(ts));
3430: PetscCall(TSGetSolution(ts, &U));
3431: PetscCall(PetscObjectCompareId((PetscObject)U, idprev, &sameObject));
3432: PetscCall(PetscObjectStateGet((PetscObject)U, &spost));
3433: if (!sameObject || sprev != spost) PetscCall(TSRestartStep(ts));
3434: }
3435: PetscFunctionReturn(PETSC_SUCCESS);
3436: }
3438: /*@
3439: TSInterpolate - Interpolate the solution computed during the previous step to an arbitrary location in the interval
3441: Collective
3443: Input Parameters:
3444: + ts - time stepping context
3445: - t - time to interpolate to
3447: Output Parameter:
3448: . U - state at given time
3450: Level: intermediate
3452: Developer Notes:
3453: `TSInterpolate()` and the storing of previous steps/stages should be generalized to support delay differential equations and continuous adjoints.
3455: .seealso: [](ch_ts), `TS`, `TSSetExactFinalTime()`, `TSSolve()`
3456: @*/
3457: PetscErrorCode TSInterpolate(TS ts, PetscReal t, Vec U)
3458: {
3459: PetscFunctionBegin;
3462: 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);
3463: PetscUseTypeMethod(ts, interpolate, t, U);
3464: PetscFunctionReturn(PETSC_SUCCESS);
3465: }
3467: /*@
3468: TSStep - Steps one time step
3470: Collective
3472: Input Parameter:
3473: . ts - the `TS` context obtained from `TSCreate()`
3475: Level: developer
3477: Notes:
3478: The public interface for the ODE/DAE solvers is `TSSolve()`, you should almost for sure be using that routine and not this routine.
3480: The hook set using `TSSetPreStep()` is called before each attempt to take the step. In general, the time step size may
3481: be changed due to adaptive error controller or solve failures. Note that steps may contain multiple stages.
3483: This may over-step the final time provided in `TSSetMaxTime()` depending on the time-step used. `TSSolve()` interpolates to exactly the
3484: time provided in `TSSetMaxTime()`. One can use `TSInterpolate()` to determine an interpolated solution within the final timestep.
3486: .seealso: [](ch_ts), `TS`, `TSCreate()`, `TSSetUp()`, `TSDestroy()`, `TSSolve()`, `TSSetPreStep()`, `TSSetPreStage()`, `TSSetPostStage()`, `TSInterpolate()`
3487: @*/
3488: PetscErrorCode TSStep(TS ts)
3489: {
3490: static PetscBool cite = PETSC_FALSE;
3491: PetscReal ptime;
3493: PetscFunctionBegin;
3495: PetscCall(PetscCitationsRegister("@article{tspaper,\n"
3496: " title = {{PETSc/TS}: A Modern Scalable {DAE/ODE} Solver Library},\n"
3497: " author = {Abhyankar, Shrirang and Brown, Jed and Constantinescu, Emil and Ghosh, Debojyoti and Smith, Barry F. and Zhang, Hong},\n"
3498: " journal = {arXiv e-preprints},\n"
3499: " eprint = {1806.01437},\n"
3500: " archivePrefix = {arXiv},\n"
3501: " year = {2018}\n}\n",
3502: &cite));
3503: PetscCall(TSSetUp(ts));
3504: PetscCall(TSTrajectorySetUp(ts->trajectory, ts));
3505: if (ts->eval_times)
3506: ts->eval_times->worktol = 0; /* In each step of TSSolve() 'eval_times->worktol' will be meaningfully defined (later) only once:
3507: in TSAdaptChoose() or TSEvent_dt_cap(), and then reused till the end of the step */
3509: PetscCheck(ts->max_time < PETSC_MAX_REAL || ts->run_steps != PETSC_INT_MAX || ts->max_steps != PETSC_INT_MAX, PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_WRONGSTATE, "You must call TSSetMaxTime(), TSSetMaxSteps(), or TSSetRunSteps() or use -ts_max_time <time>, -ts_max_steps <steps>, -ts_run_steps <steps>");
3510: 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()");
3511: 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");
3513: if (!ts->vec_sol0) PetscCall(VecDuplicate(ts->vec_sol, &ts->vec_sol0));
3514: PetscCall(VecCopy(ts->vec_sol, ts->vec_sol0));
3515: ts->time_step0 = ts->time_step;
3517: if (!ts->steps) ts->ptime_prev = ts->ptime;
3518: ptime = ts->ptime;
3520: ts->ptime_prev_rollback = ts->ptime_prev;
3521: ts->reason = TS_CONVERGED_ITERATING;
3523: PetscCall(PetscLogEventBegin(TS_Step, ts, 0, 0, 0));
3524: PetscUseTypeMethod(ts, step);
3525: PetscCall(PetscLogEventEnd(TS_Step, ts, 0, 0, 0));
3527: if (ts->reason >= 0) {
3528: ts->ptime_prev = ptime;
3529: ts->steps++;
3530: ts->steprollback = PETSC_FALSE;
3531: ts->steprestart = PETSC_FALSE;
3532: ts->stepresize = PETSC_FALSE;
3533: }
3535: if (ts->reason < 0 && ts->errorifstepfailed) {
3536: PetscCall(TSMonitorCancel(ts));
3537: if (ts->usessnes && ts->snes) PetscCall(SNESMonitorCancel(ts->snes));
3538: 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 use unlimited to attempt recovery", TSConvergedReasons[ts->reason]);
3539: SETERRQ(PetscObjectComm((PetscObject)ts), PETSC_ERR_NOT_CONVERGED, "TSStep has failed due to %s", TSConvergedReasons[ts->reason]);
3540: }
3541: PetscFunctionReturn(PETSC_SUCCESS);
3542: }
3544: /*@
3545: TSEvaluateWLTE - Evaluate the weighted local truncation error norm
3546: at the end of a time step with a given order of accuracy.
3548: Collective
3550: Input Parameters:
3551: + ts - time stepping context
3552: - wnormtype - norm type, either `NORM_2` or `NORM_INFINITY`
3554: Input/Output Parameter:
3555: . order - optional, desired order for the error evaluation or `PETSC_DECIDE`;
3556: on output, the actual order of the error evaluation
3558: Output Parameter:
3559: . wlte - the weighted local truncation error norm
3561: Level: advanced
3563: Note:
3564: If the timestepper cannot evaluate the error in a particular step
3565: (eg. in the first step or restart steps after event handling),
3566: this routine returns wlte=-1.0 .
3568: .seealso: [](ch_ts), `TS`, `TSStep()`, `TSAdapt`, `TSErrorWeightedNorm()`
3569: @*/
3570: PetscErrorCode TSEvaluateWLTE(TS ts, NormType wnormtype, PetscInt *order, PetscReal *wlte)
3571: {
3572: PetscFunctionBegin;
3576: if (order) PetscAssertPointer(order, 3);
3578: PetscAssertPointer(wlte, 4);
3579: PetscCheck(wnormtype == NORM_2 || wnormtype == NORM_INFINITY, PetscObjectComm((PetscObject)ts), PETSC_ERR_SUP, "No support for norm type %s", NormTypes[wnormtype]);
3580: PetscUseTypeMethod(ts, evaluatewlte, wnormtype, order, wlte);
3581: PetscFunctionReturn(PETSC_SUCCESS);
3582: }
3584: /*@
3585: TSEvaluateStep - Evaluate the solution at the end of a time step with a given order of accuracy.
3587: Collective
3589: Input Parameters:
3590: + ts - time stepping context
3591: . order - desired order of accuracy
3592: - done - whether the step was evaluated at this order (pass `NULL` to generate an error if not available)
3594: Output Parameter:
3595: . U - state at the end of the current step
3597: Level: advanced
3599: Notes:
3600: This function cannot be called until all stages have been evaluated.
3602: 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.
3604: .seealso: [](ch_ts), `TS`, `TSStep()`, `TSAdapt`
3605: @*/
3606: PetscErrorCode TSEvaluateStep(TS ts, PetscInt order, Vec U, PetscBool *done)
3607: {
3608: PetscFunctionBegin;
3612: PetscUseTypeMethod(ts, evaluatestep, order, U, done);
3613: PetscFunctionReturn(PETSC_SUCCESS);
3614: }
3616: /*@C
3617: TSGetComputeInitialCondition - Get the function used to automatically compute an initial condition for the timestepping.
3619: Not collective
3621: Input Parameter:
3622: . ts - time stepping context
3624: Output Parameter:
3625: . initCondition - The function which computes an initial condition
3627: Calling sequence of `initCondition`:
3628: + ts - The timestepping context
3629: - u - The input vector in which the initial condition is stored
3631: Level: advanced
3633: .seealso: [](ch_ts), `TS`, `TSSetComputeInitialCondition()`, `TSComputeInitialCondition()`
3634: @*/
3635: PetscErrorCode TSGetComputeInitialCondition(TS ts, PetscErrorCode (**initCondition)(TS ts, Vec u))
3636: {
3637: PetscFunctionBegin;
3639: PetscAssertPointer(initCondition, 2);
3640: *initCondition = ts->ops->initcondition;
3641: PetscFunctionReturn(PETSC_SUCCESS);
3642: }
3644: /*@C
3645: TSSetComputeInitialCondition - Set the function used to automatically compute an initial condition for the timestepping.
3647: Logically collective
3649: Input Parameters:
3650: + ts - time stepping context
3651: - initCondition - The function which computes an initial condition
3653: Calling sequence of `initCondition`:
3654: + ts - The timestepping context
3655: - e - The input vector in which the initial condition is to be stored
3657: Level: advanced
3659: .seealso: [](ch_ts), `TS`, `TSGetComputeInitialCondition()`, `TSComputeInitialCondition()`
3660: @*/
3661: PetscErrorCode TSSetComputeInitialCondition(TS ts, PetscErrorCode (*initCondition)(TS ts, Vec e))
3662: {
3663: PetscFunctionBegin;
3666: ts->ops->initcondition = initCondition;
3667: PetscFunctionReturn(PETSC_SUCCESS);
3668: }
3670: /*@
3671: TSComputeInitialCondition - Compute an initial condition for the timestepping using the function previously set with `TSSetComputeInitialCondition()`
3673: Collective
3675: Input Parameters:
3676: + ts - time stepping context
3677: - u - The `Vec` to store the condition in which will be used in `TSSolve()`
3679: Level: advanced
3681: .seealso: [](ch_ts), `TS`, `TSGetComputeInitialCondition()`, `TSSetComputeInitialCondition()`, `TSSolve()`
3682: @*/
3683: PetscErrorCode TSComputeInitialCondition(TS ts, Vec u)
3684: {
3685: PetscFunctionBegin;
3688: PetscTryTypeMethod(ts, initcondition, u);
3689: PetscFunctionReturn(PETSC_SUCCESS);
3690: }
3692: /*@C
3693: TSGetComputeExactError - Get the function used to automatically compute the exact error for the timestepping.
3695: Not collective
3697: Input Parameter:
3698: . ts - time stepping context
3700: Output Parameter:
3701: . exactError - The function which computes the solution error
3703: Calling sequence of `exactError`:
3704: + ts - The timestepping context
3705: . u - The approximate solution vector
3706: - e - The vector in which the error is stored
3708: Level: advanced
3710: .seealso: [](ch_ts), `TS`, `TSComputeExactError()`
3711: @*/
3712: PetscErrorCode TSGetComputeExactError(TS ts, PetscErrorCode (**exactError)(TS ts, Vec u, Vec e))
3713: {
3714: PetscFunctionBegin;
3716: PetscAssertPointer(exactError, 2);
3717: *exactError = ts->ops->exacterror;
3718: PetscFunctionReturn(PETSC_SUCCESS);
3719: }
3721: /*@C
3722: TSSetComputeExactError - Set the function used to automatically compute the exact error for the timestepping.
3724: Logically collective
3726: Input Parameters:
3727: + ts - time stepping context
3728: - exactError - The function which computes the solution error
3730: Calling sequence of `exactError`:
3731: + ts - The timestepping context
3732: . u - The approximate solution vector
3733: - e - The vector in which the error is stored
3735: Level: advanced
3737: .seealso: [](ch_ts), `TS`, `TSGetComputeExactError()`, `TSComputeExactError()`
3738: @*/
3739: PetscErrorCode TSSetComputeExactError(TS ts, PetscErrorCode (*exactError)(TS ts, Vec u, Vec e))
3740: {
3741: PetscFunctionBegin;
3744: ts->ops->exacterror = exactError;
3745: PetscFunctionReturn(PETSC_SUCCESS);
3746: }
3748: /*@
3749: TSComputeExactError - Compute the solution error for the timestepping using the function previously set with `TSSetComputeExactError()`
3751: Collective
3753: Input Parameters:
3754: + ts - time stepping context
3755: . u - The approximate solution
3756: - e - The `Vec` used to store the error
3758: Level: advanced
3760: .seealso: [](ch_ts), `TS`, `TSGetComputeInitialCondition()`, `TSSetComputeInitialCondition()`, `TSSolve()`
3761: @*/
3762: PetscErrorCode TSComputeExactError(TS ts, Vec u, Vec e)
3763: {
3764: PetscFunctionBegin;
3768: PetscTryTypeMethod(ts, exacterror, u, e);
3769: PetscFunctionReturn(PETSC_SUCCESS);
3770: }
3772: /*@C
3773: TSSetResize - Sets the resize callbacks.
3775: Logically Collective
3777: Input Parameters:
3778: + ts - The `TS` context obtained from `TSCreate()`
3779: . rollback - Whether a resize will restart the step
3780: . setup - The setup function
3781: . transfer - The transfer function
3782: - ctx - [optional] The user-defined context
3784: Calling sequence of `setup`:
3785: + ts - the `TS` context
3786: . step - the current step
3787: . time - the current time
3788: . state - the current vector of state
3789: . resize - (output parameter) `PETSC_TRUE` if need resizing, `PETSC_FALSE` otherwise
3790: - ctx - user defined context
3792: Calling sequence of `transfer`:
3793: + ts - the `TS` context
3794: . nv - the number of vectors to be transferred
3795: . vecsin - array of vectors to be transferred
3796: . vecsout - array of transferred vectors
3797: - ctx - user defined context
3799: Notes:
3800: The `setup` function is called inside `TSSolve()` after `TSEventHandler()` or after `TSPostStep()`
3801: depending on the `rollback` value: if `rollback` is true, then these callbacks behave as error indicators
3802: and will flag the need to remesh and restart the current step. Otherwise, they will simply flag the solver
3803: that the size of the discrete problem has changed.
3804: In both cases, the solver will collect the needed vectors that will be
3805: transferred from the old to the new sizes using the `transfer` callback. These vectors will include the
3806: current solution vector, and other vectors needed by the specific solver used.
3807: For example, `TSBDF` uses previous solutions vectors to solve for the next time step.
3808: Other application specific objects associated with the solver, i.e. Jacobian matrices and `DM`,
3809: will be automatically reset if the sizes are changed and they must be specified again by the user
3810: inside the `transfer` function.
3811: The input and output arrays passed to `transfer` are allocated by PETSc.
3812: Vectors in `vecsout` must be created by the user.
3813: Ownership of vectors in `vecsout` is transferred to PETSc.
3815: Level: advanced
3817: .seealso: [](ch_ts), `TS`, `TSSetDM()`, `TSSetIJacobian()`, `TSSetRHSJacobian()`
3818: @*/
3819: PetscErrorCode TSSetResize(TS ts, PetscBool rollback, PetscErrorCode (*setup)(TS ts, PetscInt step, PetscReal time, Vec state, PetscBool *resize, PetscCtx ctx), PetscErrorCode (*transfer)(TS ts, PetscInt nv, Vec vecsin[], Vec vecsout[], PetscCtx ctx), PetscCtx ctx)
3820: {
3821: PetscFunctionBegin;
3823: ts->resizerollback = rollback;
3824: ts->resizesetup = setup;
3825: ts->resizetransfer = transfer;
3826: ts->resizectx = ctx;
3827: PetscFunctionReturn(PETSC_SUCCESS);
3828: }
3830: /*
3831: TSResizeRegisterOrRetrieve - Register or import vectors transferred with `TSResize()`.
3833: Collective
3835: Input Parameters:
3836: + ts - The `TS` context obtained from `TSCreate()`
3837: - flg - If `PETSC_TRUE` each TS implementation (e.g. `TSBDF`) will register vectors to be transferred, if `PETSC_FALSE` vectors will be imported from transferred vectors.
3839: Level: developer
3841: Note:
3842: `TSResizeRegisterOrRetrieve()` is declared PETSC_INTERN since it is
3843: used within time stepping implementations,
3844: so most users would not generally call this routine themselves.
3846: .seealso: [](ch_ts), `TS`, `TSSetResize()`
3847: @*/
3848: static PetscErrorCode TSResizeRegisterOrRetrieve(TS ts, PetscBool flg)
3849: {
3850: PetscFunctionBegin;
3852: PetscTryTypeMethod(ts, resizeregister, flg);
3853: /* PetscTryTypeMethod(adapt, resizeregister, flg); */
3854: PetscFunctionReturn(PETSC_SUCCESS);
3855: }
3857: static PetscErrorCode TSResizeReset(TS ts)
3858: {
3859: PetscFunctionBegin;
3861: PetscCall(PetscObjectListDestroy(&ts->resizetransferobjs));
3862: PetscFunctionReturn(PETSC_SUCCESS);
3863: }
3865: static PetscErrorCode TSResizeTransferVecs(TS ts, PetscInt cnt, Vec vecsin[], Vec vecsout[])
3866: {
3867: PetscFunctionBegin;
3870: for (PetscInt i = 0; i < cnt; i++) PetscCall(VecLockReadPush(vecsin[i]));
3871: if (ts->resizetransfer) {
3872: PetscCall(PetscInfo(ts, "Transferring %" PetscInt_FMT " vectors\n", cnt));
3873: PetscCallBack("TS callback resize transfer", (*ts->resizetransfer)(ts, cnt, vecsin, vecsout, ts->resizectx));
3874: }
3875: for (PetscInt i = 0; i < cnt; i++) PetscCall(VecLockReadPop(vecsin[i]));
3876: PetscFunctionReturn(PETSC_SUCCESS);
3877: }
3879: /*@C
3880: TSResizeRegisterVec - Register a vector to be transferred with `TSResize()`.
3882: Collective
3884: Input Parameters:
3885: + ts - The `TS` context obtained from `TSCreate()`
3886: . name - A string identifying the vector
3887: - vec - The vector
3889: Level: developer
3891: Note:
3892: `TSResizeRegisterVec()` is typically used within time stepping implementations,
3893: so most users would not generally call this routine themselves.
3895: .seealso: [](ch_ts), `TS`, `TSSetResize()`, `TSResize()`, `TSResizeRetrieveVec()`
3896: @*/
3897: PetscErrorCode TSResizeRegisterVec(TS ts, const char name[], Vec vec)
3898: {
3899: PetscFunctionBegin;
3901: PetscAssertPointer(name, 2);
3903: PetscCall(PetscObjectListAdd(&ts->resizetransferobjs, name, (PetscObject)vec));
3904: PetscFunctionReturn(PETSC_SUCCESS);
3905: }
3907: /*@C
3908: TSResizeRetrieveVec - Retrieve a vector registered with `TSResizeRegisterVec()`.
3910: Collective
3912: Input Parameters:
3913: + ts - The `TS` context obtained from `TSCreate()`
3914: . name - A string identifying the vector
3915: - vec - The vector
3917: Level: developer
3919: Note:
3920: `TSResizeRetrieveVec()` is typically used within time stepping implementations,
3921: so most users would not generally call this routine themselves.
3923: .seealso: [](ch_ts), `TS`, `TSSetResize()`, `TSResize()`, `TSResizeRegisterVec()`
3924: @*/
3925: PetscErrorCode TSResizeRetrieveVec(TS ts, const char name[], Vec *vec)
3926: {
3927: PetscFunctionBegin;
3929: PetscAssertPointer(name, 2);
3930: PetscAssertPointer(vec, 3);
3931: PetscCall(PetscObjectListFind(ts->resizetransferobjs, name, (PetscObject *)vec));
3932: PetscFunctionReturn(PETSC_SUCCESS);
3933: }
3935: static PetscErrorCode TSResizeGetVecArray(TS ts, PetscInt *nv, const char **names[], Vec *vecs[])
3936: {
3937: PetscInt cnt;
3938: PetscObjectList tmp;
3939: Vec *vecsin = NULL;
3940: const char **namesin = NULL;
3942: PetscFunctionBegin;
3943: for (tmp = ts->resizetransferobjs, cnt = 0; tmp; tmp = tmp->next)
3944: if (tmp->obj && tmp->obj->classid == VEC_CLASSID) cnt++;
3945: if (names) PetscCall(PetscMalloc1(cnt, &namesin));
3946: if (vecs) PetscCall(PetscMalloc1(cnt, &vecsin));
3947: for (tmp = ts->resizetransferobjs, cnt = 0; tmp; tmp = tmp->next) {
3948: if (tmp->obj && tmp->obj->classid == VEC_CLASSID) {
3949: if (vecs) vecsin[cnt] = (Vec)tmp->obj;
3950: if (names) namesin[cnt] = tmp->name;
3951: cnt++;
3952: }
3953: }
3954: if (nv) *nv = cnt;
3955: if (names) *names = namesin;
3956: if (vecs) *vecs = vecsin;
3957: PetscFunctionReturn(PETSC_SUCCESS);
3958: }
3960: /*@
3961: TSResize - Runs the user-defined transfer functions provided with `TSSetResize()`
3963: Collective
3965: Input Parameter:
3966: . ts - The `TS` context obtained from `TSCreate()`
3968: Level: developer
3970: Note:
3971: `TSResize()` is typically used within time stepping implementations,
3972: so most users would not generally call this routine themselves.
3974: .seealso: [](ch_ts), `TS`, `TSSetResize()`
3975: @*/
3976: PetscErrorCode TSResize(TS ts)
3977: {
3978: PetscInt nv = 0;
3979: const char **names = NULL;
3980: Vec *vecsin = NULL;
3981: const char *solname = "ts:vec_sol";
3983: PetscFunctionBegin;
3985: if (!ts->resizesetup) PetscFunctionReturn(PETSC_SUCCESS);
3986: if (ts->resizesetup) {
3987: PetscCall(VecLockReadPush(ts->vec_sol));
3988: PetscCallBack("TS callback resize setup", (*ts->resizesetup)(ts, ts->steps, ts->ptime, ts->vec_sol, &ts->stepresize, ts->resizectx));
3989: PetscCall(VecLockReadPop(ts->vec_sol));
3990: if (ts->stepresize) {
3991: if (ts->resizerollback) {
3992: PetscCall(TSRollBack(ts));
3993: ts->time_step = ts->time_step0;
3994: }
3995: PetscCall(TSResizeRegisterVec(ts, solname, ts->vec_sol));
3996: PetscCall(TSResizeRegisterOrRetrieve(ts, PETSC_TRUE)); /* specific impls register their own objects */
3997: }
3998: }
4000: PetscCall(TSResizeGetVecArray(ts, &nv, &names, &vecsin));
4001: if (nv) {
4002: Vec *vecsout, vecsol;
4004: /* Reset internal objects */
4005: PetscCall(TSReset(ts));
4007: /* Transfer needed vectors (users can call SetJacobian, SetDM, etc. here) */
4008: PetscCall(PetscCalloc1(nv, &vecsout));
4009: PetscCall(TSResizeTransferVecs(ts, nv, vecsin, vecsout));
4010: for (PetscInt i = 0; i < nv; i++) {
4011: const char *name;
4012: char *oname;
4014: PetscCall(PetscObjectGetName((PetscObject)vecsin[i], &name));
4015: PetscCall(PetscStrallocpy(name, &oname));
4016: PetscCall(TSResizeRegisterVec(ts, names[i], vecsout[i]));
4017: if (vecsout[i]) PetscCall(PetscObjectSetName((PetscObject)vecsout[i], oname));
4018: PetscCall(PetscFree(oname));
4019: PetscCall(VecDestroy(&vecsout[i]));
4020: }
4021: PetscCall(PetscFree(vecsout));
4022: PetscCall(TSResizeRegisterOrRetrieve(ts, PETSC_FALSE)); /* specific impls import the transferred objects */
4024: PetscCall(TSResizeRetrieveVec(ts, solname, &vecsol));
4025: if (vecsol) PetscCall(TSSetSolution(ts, vecsol));
4026: PetscAssert(ts->vec_sol, PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_NULL, "Missing TS solution");
4027: }
4029: PetscCall(PetscFree(names));
4030: PetscCall(PetscFree(vecsin));
4031: PetscCall(TSResizeReset(ts));
4032: PetscFunctionReturn(PETSC_SUCCESS);
4033: }
4035: /*@
4036: TSSolve - Steps the requested number of timesteps.
4038: Collective
4040: Input Parameters:
4041: + ts - the `TS` context obtained from `TSCreate()`
4042: - u - the solution vector (can be null if `TSSetSolution()` was used and `TSSetExactFinalTime`(ts,`TS_EXACTFINALTIME_MATCHSTEP`) was not used,
4043: otherwise it must contain the initial conditions and will contain the solution at the final requested time
4045: Level: beginner
4047: Notes:
4048: The final time returned by this function may be different from the time of the internally
4049: held state accessible by `TSGetSolution()` and `TSGetTime()` because the method may have
4050: stepped over the final time.
4052: .seealso: [](ch_ts), `TS`, `TSCreate()`, `TSSetSolution()`, `TSStep()`, `TSGetTime()`, `TSGetSolveTime()`
4053: @*/
4054: PetscErrorCode TSSolve(TS ts, Vec u)
4055: {
4056: Vec solution;
4058: PetscFunctionBegin;
4062: PetscCall(TSSetExactFinalTimeDefault(ts));
4063: 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 */
4064: if (!ts->vec_sol || u == ts->vec_sol) {
4065: PetscCall(VecDuplicate(u, &solution));
4066: PetscCall(TSSetSolution(ts, solution));
4067: PetscCall(VecDestroy(&solution)); /* grant ownership */
4068: }
4069: PetscCall(VecCopy(u, ts->vec_sol));
4070: PetscCheck(!ts->forward_solve, PetscObjectComm((PetscObject)ts), PETSC_ERR_SUP, "Sensitivity analysis does not support the mode TS_EXACTFINALTIME_INTERPOLATE");
4071: } else if (u) PetscCall(TSSetSolution(ts, u));
4072: PetscCall(TSSetUp(ts));
4073: PetscCall(TSTrajectorySetUp(ts->trajectory, ts));
4075: PetscCheck(ts->max_time < PETSC_MAX_REAL || ts->run_steps != PETSC_INT_MAX || ts->max_steps != PETSC_INT_MAX, PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_WRONGSTATE, "You must call TSSetMaxTime(), TSSetMaxSteps(), or TSSetRunSteps() or use -ts_max_time <time>, -ts_max_steps <steps>, -ts_run_steps <steps>");
4076: 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()");
4077: 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");
4078: PetscCheck(!(ts->eval_times && ts->exact_final_time != TS_EXACTFINALTIME_MATCHSTEP), PetscObjectComm((PetscObject)ts), PETSC_ERR_SUP, "You must use TS_EXACTFINALTIME_MATCHSTEP when using time span or evaluation times");
4080: if (ts->eval_times) {
4081: if (!ts->eval_times->sol_vecs) PetscCall(VecDuplicateVecs(ts->vec_sol, ts->eval_times->num_time_points, &ts->eval_times->sol_vecs));
4082: for (PetscInt i = 0; i < ts->eval_times->num_time_points; i++) {
4083: PetscBool is_close = PetscIsCloseAtTol(ts->ptime, ts->eval_times->time_points[i], ts->eval_times->reltol * ts->time_step + ts->eval_times->abstol, 0);
4084: if (ts->ptime <= ts->eval_times->time_points[i] || is_close) {
4085: ts->eval_times->time_point_idx = i;
4087: PetscBool is_ptime_in_sol_times = PETSC_FALSE; // If current solution has already been saved, we should not save it again
4088: if (ts->eval_times->sol_idx > 0) is_ptime_in_sol_times = PetscIsCloseAtTol(ts->ptime, ts->eval_times->sol_times[ts->eval_times->sol_idx - 1], ts->eval_times->reltol * ts->time_step + ts->eval_times->abstol, 0);
4089: if (is_close && !is_ptime_in_sol_times) {
4090: PetscCall(VecCopy(ts->vec_sol, ts->eval_times->sol_vecs[ts->eval_times->sol_idx]));
4091: ts->eval_times->sol_times[ts->eval_times->sol_idx] = ts->ptime;
4092: ts->eval_times->sol_idx++;
4093: ts->eval_times->time_point_idx++;
4094: }
4095: break;
4096: }
4097: }
4098: }
4100: if (ts->forward_solve) PetscCall(TSForwardSetUp(ts));
4102: /* reset number of steps only when the step is not restarted. ARKIMEX
4103: restarts the step after an event. Resetting these counters in such case causes
4104: TSTrajectory to incorrectly save the output files
4105: */
4106: /* reset time step and iteration counters */
4107: if (!ts->steps) {
4108: ts->ksp_its = 0;
4109: ts->snes_its = 0;
4110: ts->num_snes_failures = 0;
4111: ts->reject = 0;
4112: ts->steprestart = PETSC_TRUE;
4113: ts->steprollback = PETSC_FALSE;
4114: ts->stepresize = PETSC_FALSE;
4115: ts->rhsjacobian.time = PETSC_MIN_REAL;
4116: }
4118: /* make sure initial time step does not overshoot final time or the next point in evaluation times */
4119: if (ts->exact_final_time == TS_EXACTFINALTIME_MATCHSTEP) {
4120: PetscReal maxdt;
4121: PetscReal dt = ts->time_step;
4123: if (ts->eval_times) maxdt = ts->eval_times->time_points[ts->eval_times->time_point_idx] - ts->ptime;
4124: else maxdt = ts->max_time - ts->ptime;
4125: ts->time_step = dt >= maxdt ? maxdt : (PetscIsCloseAtTol(dt, maxdt, 10 * PETSC_MACHINE_EPSILON, 0) ? maxdt : dt);
4126: }
4127: ts->reason = TS_CONVERGED_ITERATING;
4129: {
4130: PetscViewer viewer;
4131: PetscViewerFormat format;
4132: PetscBool flg;
4133: static PetscBool incall = PETSC_FALSE;
4135: if (!incall) {
4136: /* Estimate the convergence rate of the time discretization */
4137: PetscCall(PetscOptionsCreateViewer(PetscObjectComm((PetscObject)ts), ((PetscObject)ts)->options, ((PetscObject)ts)->prefix, "-ts_convergence_estimate", &viewer, &format, &flg));
4138: if (flg) {
4139: PetscConvEst conv;
4140: DM dm;
4141: PetscReal *alpha; /* Convergence rate of the solution error for each field in the L_2 norm */
4142: PetscInt Nf;
4143: PetscBool checkTemporal = PETSC_TRUE;
4145: incall = PETSC_TRUE;
4146: PetscCall(PetscOptionsGetBool(((PetscObject)ts)->options, ((PetscObject)ts)->prefix, "-ts_convergence_temporal", &checkTemporal, &flg));
4147: PetscCall(TSGetDM(ts, &dm));
4148: PetscCall(DMGetNumFields(dm, &Nf));
4149: PetscCall(PetscCalloc1(PetscMax(Nf, 1), &alpha));
4150: PetscCall(PetscConvEstCreate(PetscObjectComm((PetscObject)ts), &conv));
4151: PetscCall(PetscConvEstUseTS(conv, checkTemporal));
4152: PetscCall(PetscConvEstSetSolver(conv, (PetscObject)ts));
4153: PetscCall(PetscConvEstSetFromOptions(conv));
4154: PetscCall(PetscConvEstSetUp(conv));
4155: PetscCall(PetscConvEstGetConvRate(conv, alpha));
4156: PetscCall(PetscViewerPushFormat(viewer, format));
4157: PetscCall(PetscConvEstRateView(conv, alpha, viewer));
4158: PetscCall(PetscViewerPopFormat(viewer));
4159: PetscCall(PetscViewerDestroy(&viewer));
4160: PetscCall(PetscConvEstDestroy(&conv));
4161: PetscCall(PetscFree(alpha));
4162: incall = PETSC_FALSE;
4163: }
4164: }
4165: }
4167: PetscCall(TSViewFromOptions(ts, NULL, "-ts_view_pre"));
4169: if (ts->ops->solve) { /* This private interface is transitional and should be removed when all implementations are updated. */
4170: PetscUseTypeMethod(ts, solve);
4171: if (u) PetscCall(VecCopy(ts->vec_sol, u));
4172: ts->solvetime = ts->ptime;
4173: solution = ts->vec_sol;
4174: } else { /* Step the requested number of timesteps. */
4175: if (ts->steps >= ts->max_steps) ts->reason = TS_CONVERGED_ITS;
4176: else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME;
4178: if (!ts->steps) {
4179: PetscCall(TSTrajectorySet(ts->trajectory, ts, ts->steps, ts->ptime, ts->vec_sol));
4180: PetscCall(TSEventInitialize(ts->event, ts, ts->ptime, ts->vec_sol));
4181: }
4183: ts->start_step = ts->steps; // records starting step
4184: while (!ts->reason) {
4185: PetscCall(TSMonitor(ts, ts->steps, ts->ptime, ts->vec_sol));
4186: if (!ts->steprollback || (ts->stepresize && ts->resizerollback)) PetscCall(TSPreStep(ts));
4187: PetscCall(TSStep(ts));
4188: if (ts->testjacobian) PetscCall(TSRHSJacobianTest(ts, NULL));
4189: if (ts->testjacobiantranspose) PetscCall(TSRHSJacobianTestTranspose(ts, NULL));
4190: if (ts->quadraturets && ts->costintegralfwd) { /* Must evaluate the cost integral before event is handled. The cost integral value can also be rolled back. */
4191: if (ts->reason >= 0) ts->steps--; /* Revert the step number changed by TSStep() */
4192: PetscCall(TSForwardCostIntegral(ts));
4193: if (ts->reason >= 0) ts->steps++;
4194: }
4195: if (ts->forward_solve) { /* compute forward sensitivities before event handling because postevent() may change RHS and jump conditions may have to be applied */
4196: if (ts->reason >= 0) ts->steps--; /* Revert the step number changed by TSStep() */
4197: PetscCall(TSForwardStep(ts));
4198: if (ts->reason >= 0) ts->steps++;
4199: }
4200: PetscCall(TSPostEvaluate(ts));
4201: 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. */
4202: if (ts->steprollback) PetscCall(TSPostEvaluate(ts));
4203: if (!ts->steprollback && ts->resizerollback) PetscCall(TSResize(ts));
4204: /* check convergence */
4205: if (!ts->reason) {
4206: if ((ts->steps - ts->start_step) >= ts->run_steps) ts->reason = TS_CONVERGED_ITS;
4207: else if (ts->steps >= ts->max_steps) ts->reason = TS_CONVERGED_ITS;
4208: else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME;
4209: }
4210: if (!ts->steprollback) {
4211: PetscCall(TSTrajectorySet(ts->trajectory, ts, ts->steps, ts->ptime, ts->vec_sol));
4212: PetscCall(TSPostStep(ts));
4213: if (!ts->resizerollback) PetscCall(TSResize(ts));
4215: if (ts->eval_times && ts->eval_times->time_point_idx < ts->eval_times->num_time_points && ts->reason >= 0) {
4216: PetscCheck(ts->eval_times->worktol > 0, PetscObjectComm((PetscObject)ts), PETSC_ERR_PLIB, "Unexpected state !(eval_times->worktol > 0) in TSSolve()");
4217: if (PetscIsCloseAtTol(ts->ptime, ts->eval_times->time_points[ts->eval_times->time_point_idx], ts->eval_times->worktol, 0)) {
4218: ts->eval_times->sol_times[ts->eval_times->sol_idx] = ts->ptime;
4219: PetscCall(VecCopy(ts->vec_sol, ts->eval_times->sol_vecs[ts->eval_times->sol_idx]));
4220: ts->eval_times->sol_idx++;
4221: ts->eval_times->time_point_idx++;
4222: }
4223: }
4224: }
4225: }
4226: PetscCall(TSMonitor(ts, ts->steps, ts->ptime, ts->vec_sol));
4228: if (ts->exact_final_time == TS_EXACTFINALTIME_INTERPOLATE && ts->ptime > ts->max_time) {
4229: if (!u) u = ts->vec_sol;
4230: PetscCall(TSInterpolate(ts, ts->max_time, u));
4231: ts->solvetime = ts->max_time;
4232: solution = u;
4233: PetscCall(TSMonitor(ts, -1, ts->solvetime, solution));
4234: } else {
4235: if (u) PetscCall(VecCopy(ts->vec_sol, u));
4236: ts->solvetime = ts->ptime;
4237: solution = ts->vec_sol;
4238: }
4239: }
4241: PetscCall(TSViewFromOptions(ts, NULL, "-ts_view"));
4242: PetscCall(VecViewFromOptions(solution, (PetscObject)ts, "-ts_view_solution"));
4243: PetscCall(PetscObjectSAWsBlock((PetscObject)ts));
4244: if (ts->adjoint_solve) PetscCall(TSAdjointSolve(ts));
4245: PetscFunctionReturn(PETSC_SUCCESS);
4246: }
4248: /*@
4249: TSGetTime - Gets the time of the most recently completed step.
4251: Not Collective
4253: Input Parameter:
4254: . ts - the `TS` context obtained from `TSCreate()`
4256: Output Parameter:
4257: . t - the current time. This time may not corresponds to the final time set with `TSSetMaxTime()`, use `TSGetSolveTime()`.
4259: Level: beginner
4261: Note:
4262: When called during time step evaluation (e.g. during residual evaluation or via hooks set using `TSSetPreStep()`,
4263: `TSSetPreStage()`, `TSSetPostStage()`, or `TSSetPostStep()`), the time is the time at the start of the step being evaluated.
4265: .seealso: [](ch_ts), `TS`, `TSGetSolveTime()`, `TSSetTime()`, `TSGetTimeStep()`, `TSGetStepNumber()`
4266: @*/
4267: PetscErrorCode TSGetTime(TS ts, PetscReal *t)
4268: {
4269: PetscFunctionBegin;
4271: PetscAssertPointer(t, 2);
4272: *t = ts->ptime;
4273: PetscFunctionReturn(PETSC_SUCCESS);
4274: }
4276: /*@
4277: TSGetPrevTime - Gets the starting time of the previously completed step.
4279: Not Collective
4281: Input Parameter:
4282: . ts - the `TS` context obtained from `TSCreate()`
4284: Output Parameter:
4285: . t - the previous time
4287: Level: beginner
4289: .seealso: [](ch_ts), `TS`, `TSGetTime()`, `TSGetSolveTime()`, `TSGetTimeStep()`
4290: @*/
4291: PetscErrorCode TSGetPrevTime(TS ts, PetscReal *t)
4292: {
4293: PetscFunctionBegin;
4295: PetscAssertPointer(t, 2);
4296: *t = ts->ptime_prev;
4297: PetscFunctionReturn(PETSC_SUCCESS);
4298: }
4300: /*@
4301: TSSetTime - Allows one to reset the time.
4303: Logically Collective
4305: Input Parameters:
4306: + ts - the `TS` context obtained from `TSCreate()`
4307: - t - the time
4309: Level: intermediate
4311: .seealso: [](ch_ts), `TS`, `TSGetTime()`, `TSSetMaxSteps()`
4312: @*/
4313: PetscErrorCode TSSetTime(TS ts, PetscReal t)
4314: {
4315: PetscFunctionBegin;
4318: ts->ptime = t;
4319: PetscFunctionReturn(PETSC_SUCCESS);
4320: }
4322: /*@
4323: TSSetOptionsPrefix - Sets the prefix used for searching for all
4324: TS options in the database.
4326: Logically Collective
4328: Input Parameters:
4329: + ts - The `TS` context
4330: - prefix - The prefix to prepend to all option names
4332: Level: advanced
4334: Note:
4335: A hyphen (-) must NOT be given at the beginning of the prefix name.
4336: The first character of all runtime options is AUTOMATICALLY the
4337: hyphen.
4339: .seealso: [](ch_ts), `TS`, `TSSetFromOptions()`, `TSAppendOptionsPrefix()`
4340: @*/
4341: PetscErrorCode TSSetOptionsPrefix(TS ts, const char prefix[])
4342: {
4343: SNES snes;
4345: PetscFunctionBegin;
4347: PetscCall(PetscObjectSetOptionsPrefix((PetscObject)ts, prefix));
4348: PetscCall(TSGetSNES(ts, &snes));
4349: PetscCall(SNESSetOptionsPrefix(snes, prefix));
4350: PetscFunctionReturn(PETSC_SUCCESS);
4351: }
4353: /*@
4354: TSAppendOptionsPrefix - Appends to the prefix used for searching for all
4355: TS options in the database.
4357: Logically Collective
4359: Input Parameters:
4360: + ts - The `TS` context
4361: - prefix - The prefix to prepend to all option names
4363: Level: advanced
4365: Note:
4366: A hyphen (-) must NOT be given at the beginning of the prefix name.
4367: The first character of all runtime options is AUTOMATICALLY the
4368: hyphen.
4370: .seealso: [](ch_ts), `TS`, `TSGetOptionsPrefix()`, `TSSetOptionsPrefix()`, `TSSetFromOptions()`
4371: @*/
4372: PetscErrorCode TSAppendOptionsPrefix(TS ts, const char prefix[])
4373: {
4374: SNES snes;
4376: PetscFunctionBegin;
4378: PetscCall(PetscObjectAppendOptionsPrefix((PetscObject)ts, prefix));
4379: PetscCall(TSGetSNES(ts, &snes));
4380: PetscCall(SNESAppendOptionsPrefix(snes, prefix));
4381: PetscFunctionReturn(PETSC_SUCCESS);
4382: }
4384: /*@
4385: TSGetOptionsPrefix - Sets the prefix used for searching for all
4386: `TS` options in the database.
4388: Not Collective
4390: Input Parameter:
4391: . ts - The `TS` context
4393: Output Parameter:
4394: . prefix - A pointer to the prefix string used
4396: Level: intermediate
4398: .seealso: [](ch_ts), `TS`, `TSAppendOptionsPrefix()`, `TSSetFromOptions()`
4399: @*/
4400: PetscErrorCode TSGetOptionsPrefix(TS ts, const char *prefix[])
4401: {
4402: PetscFunctionBegin;
4404: PetscAssertPointer(prefix, 2);
4405: PetscCall(PetscObjectGetOptionsPrefix((PetscObject)ts, prefix));
4406: PetscFunctionReturn(PETSC_SUCCESS);
4407: }
4409: /*@C
4410: TSGetRHSJacobian - Returns the Jacobian J at the present timestep.
4412: Not Collective, but parallel objects are returned if ts is parallel
4414: Input Parameter:
4415: . ts - The `TS` context obtained from `TSCreate()`
4417: Output Parameters:
4418: + Amat - The (approximate) Jacobian J of G, where U_t = G(U,t) (or `NULL`)
4419: . Pmat - The matrix from which the preconditioner is constructed, usually the same as `Amat` (or `NULL`)
4420: . func - Function to compute the Jacobian of the RHS (or `NULL`)
4421: - ctx - User-defined context for Jacobian evaluation routine (or `NULL`)
4423: Level: intermediate
4425: Note:
4426: You can pass in `NULL` for any return argument you do not need.
4428: .seealso: [](ch_ts), `TS`, `TSGetTimeStep()`, `TSGetMatrices()`, `TSGetTime()`, `TSGetStepNumber()`
4429: @*/
4430: PetscErrorCode TSGetRHSJacobian(TS ts, Mat *Amat, Mat *Pmat, TSRHSJacobianFn **func, PetscCtxRt ctx)
4431: {
4432: DM dm;
4434: PetscFunctionBegin;
4435: if (Amat || Pmat) {
4436: SNES snes;
4437: PetscCall(TSGetSNES(ts, &snes));
4438: PetscCall(SNESSetUpMatrices(snes));
4439: PetscCall(SNESGetJacobian(snes, Amat, Pmat, NULL, NULL));
4440: }
4441: PetscCall(TSGetDM(ts, &dm));
4442: PetscCall(DMTSGetRHSJacobian(dm, func, ctx));
4443: PetscFunctionReturn(PETSC_SUCCESS);
4444: }
4446: /*@C
4447: TSGetIJacobian - Returns the implicit Jacobian at the present timestep.
4449: Not Collective, but parallel objects are returned if ts is parallel
4451: Input Parameter:
4452: . ts - The `TS` context obtained from `TSCreate()`
4454: Output Parameters:
4455: + Amat - The (approximate) Jacobian of F(t,U,U_t)
4456: . Pmat - The matrix from which the preconditioner is constructed, often the same as `Amat`
4457: . f - The function to compute the matrices
4458: - ctx - User-defined context for Jacobian evaluation routine
4460: Level: advanced
4462: Note:
4463: You can pass in `NULL` for any return argument you do not need.
4465: .seealso: [](ch_ts), `TS`, `TSGetTimeStep()`, `TSGetRHSJacobian()`, `TSGetMatrices()`, `TSGetTime()`, `TSGetStepNumber()`
4466: @*/
4467: PetscErrorCode TSGetIJacobian(TS ts, Mat *Amat, Mat *Pmat, TSIJacobianFn **f, PetscCtxRt ctx)
4468: {
4469: DM dm;
4471: PetscFunctionBegin;
4472: if (Amat || Pmat) {
4473: SNES snes;
4474: PetscCall(TSGetSNES(ts, &snes));
4475: PetscCall(SNESSetUpMatrices(snes));
4476: PetscCall(SNESGetJacobian(snes, Amat, Pmat, NULL, NULL));
4477: }
4478: PetscCall(TSGetDM(ts, &dm));
4479: PetscCall(DMTSGetIJacobian(dm, f, ctx));
4480: PetscFunctionReturn(PETSC_SUCCESS);
4481: }
4483: #include <petsc/private/dmimpl.h>
4484: /*@
4485: TSSetDM - Sets the `DM` that may be used by some nonlinear solvers or preconditioners under the `TS`
4487: Logically Collective
4489: Input Parameters:
4490: + ts - the `TS` integrator object
4491: - dm - the dm, cannot be `NULL`
4493: Level: intermediate
4495: Notes:
4496: A `DM` can only be used for solving one problem at a time because information about the problem is stored on the `DM`,
4497: even when not using interfaces like `DMTSSetIFunction()`. Use `DMClone()` to get a distinct `DM` when solving
4498: different problems using the same function space.
4500: .seealso: [](ch_ts), `TS`, `DM`, `TSGetDM()`, `SNESSetDM()`, `SNESGetDM()`
4501: @*/
4502: PetscErrorCode TSSetDM(TS ts, DM dm)
4503: {
4504: SNES snes;
4505: DMTS tsdm;
4507: PetscFunctionBegin;
4510: PetscCall(PetscObjectReference((PetscObject)dm));
4511: if (ts->dm) { /* Move the DMTS context over to the new DM unless the new DM already has one */
4512: if (ts->dm->dmts && !dm->dmts) {
4513: PetscCall(DMCopyDMTS(ts->dm, dm));
4514: PetscCall(DMGetDMTS(ts->dm, &tsdm));
4515: /* Grant write privileges to the replacement DM */
4516: if (tsdm->originaldm == ts->dm) tsdm->originaldm = dm;
4517: }
4518: PetscCall(DMDestroy(&ts->dm));
4519: }
4520: ts->dm = dm;
4522: PetscCall(TSGetSNES(ts, &snes));
4523: PetscCall(SNESSetDM(snes, dm));
4524: PetscFunctionReturn(PETSC_SUCCESS);
4525: }
4527: /*@
4528: TSGetDM - Gets the `DM` that may be used by some preconditioners
4530: Not Collective
4532: Input Parameter:
4533: . ts - the `TS`
4535: Output Parameter:
4536: . dm - the `DM`
4538: Level: intermediate
4540: .seealso: [](ch_ts), `TS`, `DM`, `TSSetDM()`, `SNESSetDM()`, `SNESGetDM()`
4541: @*/
4542: PetscErrorCode TSGetDM(TS ts, DM *dm)
4543: {
4544: PetscFunctionBegin;
4546: if (!ts->dm) {
4547: PetscCall(DMShellCreate(PetscObjectComm((PetscObject)ts), &ts->dm));
4548: if (ts->snes) PetscCall(SNESSetDM(ts->snes, ts->dm));
4549: }
4550: *dm = ts->dm;
4551: PetscFunctionReturn(PETSC_SUCCESS);
4552: }
4554: /*@
4555: SNESTSFormFunction - Function to evaluate nonlinear residual defined by an ODE solver algorithm implemented within `TS`
4557: Logically Collective
4559: Input Parameters:
4560: + snes - nonlinear solver
4561: . U - the current state at which to evaluate the residual
4562: - ctx - user context, must be a `TS`
4564: Output Parameter:
4565: . F - the nonlinear residual
4567: Level: developer
4569: Note:
4570: This function is not normally called by users and is automatically registered with the `SNES` used by `TS`.
4571: It is most frequently passed to `MatFDColoringSetFunction()`.
4573: .seealso: [](ch_ts), `SNESSetFunction()`, `MatFDColoringSetFunction()`
4574: @*/
4575: PetscErrorCode SNESTSFormFunction(SNES snes, Vec U, Vec F, PetscCtx ctx)
4576: {
4577: TS ts = (TS)ctx;
4579: PetscFunctionBegin;
4584: PetscCheck(ts->ops->snesfunction, PetscObjectComm((PetscObject)ts), PETSC_ERR_SUP, "No method snesfunction for TS of type %s", ((PetscObject)ts)->type_name);
4585: PetscCall((*ts->ops->snesfunction)(snes, U, F, ts));
4586: PetscFunctionReturn(PETSC_SUCCESS);
4587: }
4589: /*@
4590: SNESTSFormJacobian - Function to evaluate the Jacobian defined by an ODE solver algorithm implemented within `TS`
4592: Collective
4594: Input Parameters:
4595: + snes - nonlinear solver
4596: . U - the current state at which to evaluate the residual
4597: - ctx - user context, must be a `TS`
4599: Output Parameters:
4600: + A - the Jacobian
4601: - B - the matrix used to construct the preconditioner (often the same as `A`)
4603: Level: developer
4605: Note:
4606: This function is not normally called by users and is automatically registered with the `SNES` used by `TS`.
4608: .seealso: [](ch_ts), `SNESSetJacobian()`
4609: @*/
4610: PetscErrorCode SNESTSFormJacobian(SNES snes, Vec U, Mat A, Mat B, PetscCtx ctx)
4611: {
4612: TS ts = (TS)ctx;
4614: PetscFunctionBegin;
4620: PetscCheck(ts->ops->snesjacobian, PetscObjectComm((PetscObject)ts), PETSC_ERR_SUP, "No method snesjacobian for TS of type %s", ((PetscObject)ts)->type_name);
4621: PetscCall((*ts->ops->snesjacobian)(snes, U, A, B, ts));
4622: PetscFunctionReturn(PETSC_SUCCESS);
4623: }
4625: /*@C
4626: TSComputeRHSFunctionLinear - Evaluate the right-hand side via the user-provided Jacobian, for linear problems Udot = A U only
4628: Collective
4630: Input Parameters:
4631: + ts - time stepping context
4632: . t - time at which to evaluate
4633: . U - state at which to evaluate
4634: - ctx - context
4636: Output Parameter:
4637: . F - right-hand side
4639: Level: intermediate
4641: Note:
4642: This function is intended to be passed to `TSSetRHSFunction()` to evaluate the right-hand side for linear problems.
4643: The matrix (and optionally the evaluation context) should be passed to `TSSetRHSJacobian()`.
4645: .seealso: [](ch_ts), `TS`, `TSSetRHSFunction()`, `TSSetRHSJacobian()`, `TSComputeRHSJacobianConstant()`
4646: @*/
4647: PetscErrorCode TSComputeRHSFunctionLinear(TS ts, PetscReal t, Vec U, Vec F, PetscCtx ctx)
4648: {
4649: Mat Arhs, Brhs;
4651: PetscFunctionBegin;
4652: PetscCall(TSGetRHSMats_Private(ts, &Arhs, &Brhs));
4653: /* undo the damage caused by shifting */
4654: PetscCall(TSRecoverRHSJacobian(ts, Arhs, Brhs));
4655: PetscCall(TSComputeRHSJacobian(ts, t, U, Arhs, Brhs));
4656: PetscCall(MatMult(Arhs, U, F));
4657: PetscFunctionReturn(PETSC_SUCCESS);
4658: }
4660: /*@C
4661: TSComputeRHSJacobianConstant - Reuses a Jacobian that is time-independent.
4663: Collective
4665: Input Parameters:
4666: + ts - time stepping context
4667: . t - time at which to evaluate
4668: . U - state at which to evaluate
4669: - ctx - context
4671: Output Parameters:
4672: + A - Jacobian
4673: - B - matrix used to construct the preconditioner, often the same as `A`
4675: Level: intermediate
4677: Note:
4678: This function is intended to be passed to `TSSetRHSJacobian()` to evaluate the Jacobian for linear time-independent problems.
4680: .seealso: [](ch_ts), `TS`, `TSSetRHSFunction()`, `TSSetRHSJacobian()`, `TSComputeRHSFunctionLinear()`
4681: @*/
4682: PetscErrorCode TSComputeRHSJacobianConstant(TS ts, PetscReal t, Vec U, Mat A, Mat B, PetscCtx ctx)
4683: {
4684: PetscFunctionBegin;
4685: PetscFunctionReturn(PETSC_SUCCESS);
4686: }
4688: /*@C
4689: TSComputeIFunctionLinear - Evaluate the left hand side via the user-provided Jacobian, for linear problems only
4691: Collective
4693: Input Parameters:
4694: + ts - time stepping context
4695: . t - time at which to evaluate
4696: . U - state at which to evaluate
4697: . Udot - time derivative of state vector
4698: - ctx - context
4700: Output Parameter:
4701: . F - left hand side
4703: Level: intermediate
4705: Notes:
4706: 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
4707: user is required to write their own `TSComputeIFunction()`.
4708: This function is intended to be passed to `TSSetIFunction()` to evaluate the left hand side for linear problems.
4709: The matrix (and optionally the evaluation context) should be passed to `TSSetIJacobian()`.
4711: Note that using this function is NOT equivalent to using `TSComputeRHSFunctionLinear()` since that solves Udot = A U
4713: .seealso: [](ch_ts), `TS`, `TSSetIFunction()`, `TSSetIJacobian()`, `TSComputeIJacobianConstant()`, `TSComputeRHSFunctionLinear()`
4714: @*/
4715: PetscErrorCode TSComputeIFunctionLinear(TS ts, PetscReal t, Vec U, Vec Udot, Vec F, PetscCtx ctx)
4716: {
4717: Mat A, B;
4719: PetscFunctionBegin;
4720: PetscCall(TSGetIJacobian(ts, &A, &B, NULL, NULL));
4721: PetscCall(TSComputeIJacobian(ts, t, U, Udot, 1.0, A, B, PETSC_TRUE));
4722: PetscCall(MatMult(A, Udot, F));
4723: PetscFunctionReturn(PETSC_SUCCESS);
4724: }
4726: /*@C
4727: TSComputeIJacobianConstant - Reuses the matrix previously computed with the provided `TSIJacobianFn` for a semi-implicit DAE or ODE
4729: Collective
4731: Input Parameters:
4732: + ts - time stepping context
4733: . t - time at which to evaluate
4734: . U - state at which to evaluate
4735: . Udot - time derivative of state vector
4736: . shift - shift to apply
4737: - ctx - context
4739: Output Parameters:
4740: + A - pointer to operator
4741: - B - pointer to matrix from which the preconditioner is built (often `A`)
4743: Level: advanced
4745: Notes:
4746: This function is intended to be passed to `TSSetIJacobian()` to evaluate the Jacobian for linear time-independent problems.
4748: It is only appropriate for problems of the form
4750: $$
4751: M \dot{U} = F(U,t)
4752: $$
4754: where M is constant and F is non-stiff. The user must pass M to `TSSetIJacobian()`. The current implementation only
4755: works with IMEX time integration methods such as `TSROSW` and `TSARKIMEX`, since there is no support for de-constructing
4756: an implicit operator of the form
4758: $$
4759: shift*M + J
4760: $$
4762: 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
4763: a copy of M or reassemble it when requested.
4765: .seealso: [](ch_ts), `TS`, `TSROSW`, `TSARKIMEX`, `TSSetIFunction()`, `TSSetIJacobian()`, `TSComputeIFunctionLinear()`
4766: @*/
4767: PetscErrorCode TSComputeIJacobianConstant(TS ts, PetscReal t, Vec U, Vec Udot, PetscReal shift, Mat A, Mat B, PetscCtx ctx)
4768: {
4769: PetscFunctionBegin;
4770: PetscCall(MatScale(A, shift / ts->ijacobian.shift));
4771: ts->ijacobian.shift = shift;
4772: PetscFunctionReturn(PETSC_SUCCESS);
4773: }
4775: /*@
4776: TSGetEquationType - Gets the type of the equation that `TS` is solving.
4778: Not Collective
4780: Input Parameter:
4781: . ts - the `TS` context
4783: Output Parameter:
4784: . equation_type - see `TSEquationType`
4786: Level: beginner
4788: .seealso: [](ch_ts), `TS`, `TSSetEquationType()`, `TSEquationType`
4789: @*/
4790: PetscErrorCode TSGetEquationType(TS ts, TSEquationType *equation_type)
4791: {
4792: PetscFunctionBegin;
4794: PetscAssertPointer(equation_type, 2);
4795: *equation_type = ts->equation_type;
4796: PetscFunctionReturn(PETSC_SUCCESS);
4797: }
4799: /*@
4800: TSSetEquationType - Sets the type of the equation that `TS` is solving.
4802: Not Collective
4804: Input Parameters:
4805: + ts - the `TS` context
4806: - equation_type - see `TSEquationType`
4808: Level: advanced
4810: .seealso: [](ch_ts), `TS`, `TSGetEquationType()`, `TSEquationType`
4811: @*/
4812: PetscErrorCode TSSetEquationType(TS ts, TSEquationType equation_type)
4813: {
4814: PetscFunctionBegin;
4816: ts->equation_type = equation_type;
4817: PetscFunctionReturn(PETSC_SUCCESS);
4818: }
4820: /*@
4821: TSGetConvergedReason - Gets the reason the `TS` iteration was stopped.
4823: Not Collective
4825: Input Parameter:
4826: . ts - the `TS` context
4828: Output Parameter:
4829: . reason - negative value indicates diverged, positive value converged, see `TSConvergedReason` or the
4830: manual pages for the individual convergence tests for complete lists
4832: Level: beginner
4834: Note:
4835: Can only be called after the call to `TSSolve()` is complete.
4837: .seealso: [](ch_ts), `TS`, `TSSolve()`, `TSConvergedReason`
4838: @*/
4839: PetscErrorCode TSGetConvergedReason(TS ts, TSConvergedReason *reason)
4840: {
4841: PetscFunctionBegin;
4843: PetscAssertPointer(reason, 2);
4844: *reason = ts->reason;
4845: PetscFunctionReturn(PETSC_SUCCESS);
4846: }
4848: /*@
4849: TSSetConvergedReason - Sets the reason for handling the convergence of `TSSolve()`.
4851: Logically Collective; reason must contain common value
4853: Input Parameters:
4854: + ts - the `TS` context
4855: - reason - negative value indicates diverged, positive value converged, see `TSConvergedReason` or the
4856: manual pages for the individual convergence tests for complete lists
4858: Level: advanced
4860: Note:
4861: Can only be called while `TSSolve()` is active.
4863: .seealso: [](ch_ts), `TS`, `TSSolve()`, `TSConvergedReason`
4864: @*/
4865: PetscErrorCode TSSetConvergedReason(TS ts, TSConvergedReason reason)
4866: {
4867: PetscFunctionBegin;
4869: ts->reason = reason;
4870: PetscFunctionReturn(PETSC_SUCCESS);
4871: }
4873: /*@
4874: TSGetSolveTime - Gets the time after a call to `TSSolve()`
4876: Not Collective
4878: Input Parameter:
4879: . ts - the `TS` context
4881: Output Parameter:
4882: . ftime - the final time. This time corresponds to the final time set with `TSSetMaxTime()`
4884: Level: beginner
4886: Note:
4887: Can only be called after the call to `TSSolve()` is complete.
4889: .seealso: [](ch_ts), `TS`, `TSSolve()`, `TSConvergedReason`
4890: @*/
4891: PetscErrorCode TSGetSolveTime(TS ts, PetscReal *ftime)
4892: {
4893: PetscFunctionBegin;
4895: PetscAssertPointer(ftime, 2);
4896: *ftime = ts->solvetime;
4897: PetscFunctionReturn(PETSC_SUCCESS);
4898: }
4900: /*@
4901: TSGetSNESIterations - Gets the total number of nonlinear iterations
4902: used by the time integrator.
4904: Not Collective
4906: Input Parameter:
4907: . ts - `TS` context
4909: Output Parameter:
4910: . nits - number of nonlinear iterations
4912: Level: intermediate
4914: Note:
4915: This counter is reset to zero for each successive call to `TSSolve()`.
4917: .seealso: [](ch_ts), `TS`, `TSSolve()`, `TSGetKSPIterations()`
4918: @*/
4919: PetscErrorCode TSGetSNESIterations(TS ts, PetscInt *nits)
4920: {
4921: PetscFunctionBegin;
4923: PetscAssertPointer(nits, 2);
4924: *nits = ts->snes_its;
4925: PetscFunctionReturn(PETSC_SUCCESS);
4926: }
4928: /*@
4929: TSGetKSPIterations - Gets the total number of linear iterations
4930: used by the time integrator.
4932: Not Collective
4934: Input Parameter:
4935: . ts - `TS` context
4937: Output Parameter:
4938: . lits - number of linear iterations
4940: Level: intermediate
4942: Note:
4943: This counter is reset to zero for each successive call to `TSSolve()`.
4945: .seealso: [](ch_ts), `TS`, `TSSolve()`, `TSGetSNESIterations()`
4946: @*/
4947: PetscErrorCode TSGetKSPIterations(TS ts, PetscInt *lits)
4948: {
4949: PetscFunctionBegin;
4951: PetscAssertPointer(lits, 2);
4952: *lits = ts->ksp_its;
4953: PetscFunctionReturn(PETSC_SUCCESS);
4954: }
4956: /*@
4957: TSGetStepRejections - Gets the total number of rejected steps.
4959: Not Collective
4961: Input Parameter:
4962: . ts - `TS` context
4964: Output Parameter:
4965: . rejects - number of steps rejected
4967: Level: intermediate
4969: Note:
4970: This counter is reset to zero for each successive call to `TSSolve()`.
4972: .seealso: [](ch_ts), `TS`, `TSSolve()`, `TSGetSNESIterations()`, `TSGetKSPIterations()`, `TSSetMaxStepRejections()`, `TSGetSNESFailures()`, `TSSetMaxSNESFailures()`, `TSSetErrorIfStepFails()`
4973: @*/
4974: PetscErrorCode TSGetStepRejections(TS ts, PetscInt *rejects)
4975: {
4976: PetscFunctionBegin;
4978: PetscAssertPointer(rejects, 2);
4979: *rejects = ts->reject;
4980: PetscFunctionReturn(PETSC_SUCCESS);
4981: }
4983: /*@
4984: TSGetSNESFailures - Gets the total number of failed `SNES` solves in a `TS`
4986: Not Collective
4988: Input Parameter:
4989: . ts - `TS` context
4991: Output Parameter:
4992: . fails - number of failed nonlinear solves
4994: Level: intermediate
4996: Note:
4997: This counter is reset to zero for each successive call to `TSSolve()`.
4999: .seealso: [](ch_ts), `TS`, `TSSolve()`, `TSGetSNESIterations()`, `TSGetKSPIterations()`, `TSSetMaxStepRejections()`, `TSGetStepRejections()`, `TSSetMaxSNESFailures()`
5000: @*/
5001: PetscErrorCode TSGetSNESFailures(TS ts, PetscInt *fails)
5002: {
5003: PetscFunctionBegin;
5005: PetscAssertPointer(fails, 2);
5006: *fails = ts->num_snes_failures;
5007: PetscFunctionReturn(PETSC_SUCCESS);
5008: }
5010: /*@
5011: TSSetMaxStepRejections - Sets the maximum number of step rejections allowed in a single time-step attempt before a time step fails in `TSSolve()` with `TS_DIVERGED_STEP_REJECTED`
5013: Not Collective
5015: Input Parameters:
5016: + ts - `TS` context
5017: - rejects - maximum number of rejected steps, pass `PETSC_UNLIMITED` for unlimited
5019: Options Database Key:
5020: . -ts_max_step_rejections - Maximum number of step rejections before a step fails
5022: Level: intermediate
5024: Developer Note:
5025: The options database name is incorrect.
5027: .seealso: [](ch_ts), `TS`, `SNES`, `TSGetSNESIterations()`, `TSGetKSPIterations()`, `TSSetMaxSNESFailures()`, `TSGetStepRejections()`, `TSGetSNESFailures()`, `TSSetErrorIfStepFails()`,
5028: `TSGetConvergedReason()`, `TSSolve()`, `TS_DIVERGED_STEP_REJECTED`
5029: @*/
5030: PetscErrorCode TSSetMaxStepRejections(TS ts, PetscInt rejects)
5031: {
5032: PetscFunctionBegin;
5034: if (rejects == PETSC_UNLIMITED || rejects == -1) {
5035: ts->max_reject = PETSC_UNLIMITED;
5036: } else {
5037: PetscCheck(rejects >= 0, PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_OUTOFRANGE, "Cannot have a negative maximum number of rejections");
5038: ts->max_reject = rejects;
5039: }
5040: PetscFunctionReturn(PETSC_SUCCESS);
5041: }
5043: /*@
5044: TSSetMaxSNESFailures - Sets the maximum number of failed `SNES` solves allowed before `TSSolve()` is ended with a `TSConvergedReason` of `TS_DIVERGED_NONLINEAR_SOLVE`
5046: Not Collective
5048: Input Parameters:
5049: + ts - `TS` context
5050: - fails - maximum number of failed nonlinear solves, pass `PETSC_UNLIMITED` to allow any number of failures.
5052: Options Database Key:
5053: . -ts_max_snes_failures - Maximum number of nonlinear solve failures
5055: Level: intermediate
5057: .seealso: [](ch_ts), `TS`, `SNES`, `TSGetSNESIterations()`, `TSGetKSPIterations()`, `TSSetMaxStepRejections()`, `TSGetStepRejections()`, `TSGetSNESFailures()`, `SNESGetConvergedReason()`,
5058: `TSGetConvergedReason()`, `TS_DIVERGED_NONLINEAR_SOLVE`, `TSConvergedReason`
5059: @*/
5060: PetscErrorCode TSSetMaxSNESFailures(TS ts, PetscInt fails)
5061: {
5062: PetscFunctionBegin;
5064: if (fails == PETSC_UNLIMITED || fails == -1) {
5065: ts->max_snes_failures = PETSC_UNLIMITED;
5066: } else {
5067: PetscCheck(fails >= 0, PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_OUTOFRANGE, "Cannot have a negative maximum number of failures");
5068: ts->max_snes_failures = fails;
5069: }
5070: PetscFunctionReturn(PETSC_SUCCESS);
5071: }
5073: /*@
5074: TSSetErrorIfStepFails - Immediately error if no step succeeds during `TSSolve()`
5076: Not Collective
5078: Input Parameters:
5079: + ts - `TS` context
5080: - err - `PETSC_TRUE` to error if no step succeeds, `PETSC_FALSE` to return without failure
5082: Options Database Key:
5083: . -ts_error_if_step_fails - Error if no step succeeds
5085: Level: intermediate
5087: .seealso: [](ch_ts), `TS`, `TSGetSNESIterations()`, `TSGetKSPIterations()`, `TSSetMaxStepRejections()`, `TSGetStepRejections()`, `TSGetSNESFailures()`, `TSGetConvergedReason()`
5088: @*/
5089: PetscErrorCode TSSetErrorIfStepFails(TS ts, PetscBool err)
5090: {
5091: PetscFunctionBegin;
5093: ts->errorifstepfailed = err;
5094: PetscFunctionReturn(PETSC_SUCCESS);
5095: }
5097: /*@
5098: TSGetAdapt - Get the adaptive controller context for the current method
5100: Collective if controller has not yet been created
5102: Input Parameter:
5103: . ts - time stepping context
5105: Output Parameter:
5106: . adapt - adaptive controller
5108: Level: intermediate
5110: .seealso: [](ch_ts), `TS`, `TSAdapt`, `TSAdaptSetType()`, `TSAdaptChoose()`
5111: @*/
5112: PetscErrorCode TSGetAdapt(TS ts, TSAdapt *adapt)
5113: {
5114: PetscFunctionBegin;
5116: PetscAssertPointer(adapt, 2);
5117: if (!ts->adapt) {
5118: PetscCall(TSAdaptCreate(PetscObjectComm((PetscObject)ts), &ts->adapt));
5119: PetscCall(PetscObjectIncrementTabLevel((PetscObject)ts->adapt, (PetscObject)ts, 1));
5120: }
5121: *adapt = ts->adapt;
5122: PetscFunctionReturn(PETSC_SUCCESS);
5123: }
5125: /*@
5126: TSSetTolerances - Set tolerances for local truncation error when using an adaptive controller
5128: Logically Collective
5130: Input Parameters:
5131: + ts - time integration context
5132: . atol - scalar absolute tolerances
5133: . vatol - vector of absolute tolerances or `NULL`, used in preference to `atol` if present
5134: . rtol - scalar relative tolerances
5135: - vrtol - vector of relative tolerances or `NULL`, used in preference to `rtol` if present
5137: Options Database Keys:
5138: + -ts_rtol rtol - relative tolerance for local truncation error
5139: - -ts_atol atol - Absolute tolerance for local truncation error
5141: Level: beginner
5143: Notes:
5144: `PETSC_CURRENT` or `PETSC_DETERMINE` may be used for `atol` or `rtol` to indicate the current value
5145: or the default value from when the object's type was set.
5147: With PETSc's implicit schemes for DAE problems, the calculation of the local truncation error
5148: (LTE) includes both the differential and the algebraic variables. If one wants the LTE to be
5149: computed only for the differential or the algebraic part then this can be done using the vector of
5150: tolerances vatol. For example, by setting the tolerance vector with the desired tolerance for the
5151: differential part and infinity for the algebraic part, the LTE calculation will include only the
5152: differential variables.
5154: Fortran Note:
5155: Use `PETSC_CURRENT_INTEGER` or `PETSC_DETERMINE_INTEGER`.
5157: .seealso: [](ch_ts), `TS`, `TSAdapt`, `TSErrorWeightedNorm()`, `TSGetTolerances()`
5158: @*/
5159: PetscErrorCode TSSetTolerances(TS ts, PetscReal atol, Vec vatol, PetscReal rtol, Vec vrtol)
5160: {
5161: PetscFunctionBegin;
5162: if (atol == (PetscReal)PETSC_DETERMINE) {
5163: ts->atol = ts->default_atol;
5164: } else if (atol != (PetscReal)PETSC_CURRENT) {
5165: PetscCheck(atol >= 0.0, PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_OUTOFRANGE, "Absolute tolerance %g must be non-negative", (double)atol);
5166: ts->atol = atol;
5167: }
5169: if (vatol) {
5170: PetscCall(PetscObjectReference((PetscObject)vatol));
5171: PetscCall(VecDestroy(&ts->vatol));
5172: ts->vatol = vatol;
5173: }
5175: if (rtol == (PetscReal)PETSC_DETERMINE) {
5176: ts->rtol = ts->default_rtol;
5177: } else if (rtol != (PetscReal)PETSC_CURRENT) {
5178: PetscCheck(rtol >= 0.0, PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_OUTOFRANGE, "Relative tolerance %g must be non-negative", (double)rtol);
5179: ts->rtol = rtol;
5180: }
5182: if (vrtol) {
5183: PetscCall(PetscObjectReference((PetscObject)vrtol));
5184: PetscCall(VecDestroy(&ts->vrtol));
5185: ts->vrtol = vrtol;
5186: }
5187: PetscFunctionReturn(PETSC_SUCCESS);
5188: }
5190: /*@
5191: TSGetTolerances - Get tolerances for local truncation error when using adaptive controller
5193: Logically Collective
5195: Input Parameter:
5196: . ts - time integration context
5198: Output Parameters:
5199: + atol - scalar absolute tolerances, `NULL` to ignore
5200: . vatol - vector of absolute tolerances, `NULL` to ignore
5201: . rtol - scalar relative tolerances, `NULL` to ignore
5202: - vrtol - vector of relative tolerances, `NULL` to ignore
5204: Level: beginner
5206: .seealso: [](ch_ts), `TS`, `TSAdapt`, `TSErrorWeightedNorm()`, `TSSetTolerances()`
5207: @*/
5208: PetscErrorCode TSGetTolerances(TS ts, PetscReal *atol, Vec *vatol, PetscReal *rtol, Vec *vrtol)
5209: {
5210: PetscFunctionBegin;
5211: if (atol) *atol = ts->atol;
5212: if (vatol) *vatol = ts->vatol;
5213: if (rtol) *rtol = ts->rtol;
5214: if (vrtol) *vrtol = ts->vrtol;
5215: PetscFunctionReturn(PETSC_SUCCESS);
5216: }
5218: /*@
5219: TSErrorWeightedNorm - compute a weighted norm of the difference between two state vectors based on supplied absolute and relative tolerances
5221: Collective
5223: Input Parameters:
5224: + ts - time stepping context
5225: . U - state vector, usually ts->vec_sol
5226: . Y - state vector to be compared to U
5227: - wnormtype - norm type, either `NORM_2` or `NORM_INFINITY`
5229: Output Parameters:
5230: + norm - weighted norm, a value of 1.0 achieves a balance between absolute and relative tolerances
5231: . norma - weighted norm, a value of 1.0 means that the error meets the absolute tolerance set by the user
5232: - normr - weighted norm, a value of 1.0 means that the error meets the relative tolerance set by the user
5234: Options Database Key:
5235: . -ts_adapt_wnormtype wnormtype - 2, INFINITY
5237: Level: developer
5239: .seealso: [](ch_ts), `TS`, `VecErrorWeightedNorms()`, `TSErrorWeightedENorm()`
5240: @*/
5241: PetscErrorCode TSErrorWeightedNorm(TS ts, Vec U, Vec Y, NormType wnormtype, PetscReal *norm, PetscReal *norma, PetscReal *normr)
5242: {
5243: PetscInt norma_loc, norm_loc, normr_loc;
5245: PetscFunctionBegin;
5250: PetscAssertPointer(norm, 5);
5251: PetscAssertPointer(norma, 6);
5252: PetscAssertPointer(normr, 7);
5253: PetscCall(VecErrorWeightedNorms(U, Y, NULL, wnormtype, ts->atol, ts->vatol, ts->rtol, ts->vrtol, ts->adapt->ignore_max, norm, &norm_loc, norma, &norma_loc, normr, &normr_loc));
5254: if (wnormtype == NORM_2) {
5255: if (norm_loc) *norm = PetscSqrtReal(PetscSqr(*norm) / norm_loc);
5256: if (norma_loc) *norma = PetscSqrtReal(PetscSqr(*norma) / norma_loc);
5257: if (normr_loc) *normr = PetscSqrtReal(PetscSqr(*normr) / normr_loc);
5258: }
5259: PetscCheck(!PetscIsInfOrNanScalar(*norm), PetscObjectComm((PetscObject)ts), PETSC_ERR_FP, "Infinite or not-a-number generated in norm");
5260: PetscCheck(!PetscIsInfOrNanScalar(*norma), PetscObjectComm((PetscObject)ts), PETSC_ERR_FP, "Infinite or not-a-number generated in norma");
5261: PetscCheck(!PetscIsInfOrNanScalar(*normr), PetscObjectComm((PetscObject)ts), PETSC_ERR_FP, "Infinite or not-a-number generated in normr");
5262: PetscFunctionReturn(PETSC_SUCCESS);
5263: }
5265: /*@
5266: TSErrorWeightedENorm - compute a weighted error norm based on supplied absolute and relative tolerances
5268: Collective
5270: Input Parameters:
5271: + ts - time stepping context
5272: . E - error vector
5273: . U - state vector, usually ts->vec_sol
5274: . Y - state vector, previous time step
5275: - wnormtype - norm type, either `NORM_2` or `NORM_INFINITY`
5277: Output Parameters:
5278: + norm - weighted norm, a value of 1.0 achieves a balance between absolute and relative tolerances
5279: . norma - weighted norm, a value of 1.0 means that the error meets the absolute tolerance set by the user
5280: - normr - weighted norm, a value of 1.0 means that the error meets the relative tolerance set by the user
5282: Options Database Key:
5283: . -ts_adapt_wnormtype wnormtype - 2, INFINITY
5285: Level: developer
5287: .seealso: [](ch_ts), `TS`, `VecErrorWeightedNorms()`, `TSErrorWeightedNorm()`
5288: @*/
5289: PetscErrorCode TSErrorWeightedENorm(TS ts, Vec E, Vec U, Vec Y, NormType wnormtype, PetscReal *norm, PetscReal *norma, PetscReal *normr)
5290: {
5291: PetscInt norma_loc, norm_loc, normr_loc;
5293: PetscFunctionBegin;
5295: PetscCall(VecErrorWeightedNorms(U, Y, E, wnormtype, ts->atol, ts->vatol, ts->rtol, ts->vrtol, ts->adapt->ignore_max, norm, &norm_loc, norma, &norma_loc, normr, &normr_loc));
5296: if (wnormtype == NORM_2) {
5297: if (norm_loc) *norm = PetscSqrtReal(PetscSqr(*norm) / norm_loc);
5298: if (norma_loc) *norma = PetscSqrtReal(PetscSqr(*norma) / norma_loc);
5299: if (normr_loc) *normr = PetscSqrtReal(PetscSqr(*normr) / normr_loc);
5300: }
5301: PetscCheck(!PetscIsInfOrNanScalar(*norm), PetscObjectComm((PetscObject)ts), PETSC_ERR_FP, "Infinite or not-a-number generated in norm");
5302: PetscCheck(!PetscIsInfOrNanScalar(*norma), PetscObjectComm((PetscObject)ts), PETSC_ERR_FP, "Infinite or not-a-number generated in norma");
5303: PetscCheck(!PetscIsInfOrNanScalar(*normr), PetscObjectComm((PetscObject)ts), PETSC_ERR_FP, "Infinite or not-a-number generated in normr");
5304: PetscFunctionReturn(PETSC_SUCCESS);
5305: }
5307: /*@
5308: TSSetCFLTimeLocal - Set the local CFL constraint relative to forward Euler
5310: Logically Collective
5312: Input Parameters:
5313: + ts - time stepping context
5314: - cfltime - maximum stable time step if using forward Euler (value can be different on each process)
5316: Note:
5317: After calling this function, the global CFL time can be obtained by calling TSGetCFLTime()
5319: Level: intermediate
5321: .seealso: [](ch_ts), `TSGetCFLTime()`, `TSADAPTCFL`
5322: @*/
5323: PetscErrorCode TSSetCFLTimeLocal(TS ts, PetscReal cfltime)
5324: {
5325: PetscFunctionBegin;
5327: ts->cfltime_local = cfltime;
5328: ts->cfltime = -1.;
5329: PetscFunctionReturn(PETSC_SUCCESS);
5330: }
5332: /*@
5333: TSGetCFLTime - Get the maximum stable time step according to CFL criteria applied to forward Euler
5335: Collective
5337: Input Parameter:
5338: . ts - time stepping context
5340: Output Parameter:
5341: . cfltime - maximum stable time step for forward Euler
5343: Level: advanced
5345: .seealso: [](ch_ts), `TSSetCFLTimeLocal()`
5346: @*/
5347: PetscErrorCode TSGetCFLTime(TS ts, PetscReal *cfltime)
5348: {
5349: PetscFunctionBegin;
5350: if (ts->cfltime < 0) PetscCallMPI(MPIU_Allreduce(&ts->cfltime_local, &ts->cfltime, 1, MPIU_REAL, MPIU_MIN, PetscObjectComm((PetscObject)ts)));
5351: *cfltime = ts->cfltime;
5352: PetscFunctionReturn(PETSC_SUCCESS);
5353: }
5355: /*@
5356: TSVISetVariableBounds - Sets the lower and upper bounds for the solution vector. xl <= x <= xu
5358: Input Parameters:
5359: + ts - the `TS` context.
5360: . xl - lower bound.
5361: - xu - upper bound.
5363: Level: advanced
5365: Note:
5366: If this routine is not called then the lower and upper bounds are set to
5367: `PETSC_NINFINITY` and `PETSC_INFINITY` respectively during `SNESSetUp()`.
5369: .seealso: [](ch_ts), `TS`
5370: @*/
5371: PetscErrorCode TSVISetVariableBounds(TS ts, Vec xl, Vec xu)
5372: {
5373: SNES snes;
5375: PetscFunctionBegin;
5376: PetscCall(TSGetSNES(ts, &snes));
5377: PetscCall(SNESVISetVariableBounds(snes, xl, xu));
5378: PetscFunctionReturn(PETSC_SUCCESS);
5379: }
5381: /*@
5382: TSComputeLinearStability - computes the linear stability function at a point
5384: Collective
5386: Input Parameters:
5387: + ts - the `TS` context
5388: . xr - real part of input argument
5389: - xi - imaginary part of input argument
5391: Output Parameters:
5392: + yr - real part of function value
5393: - yi - imaginary part of function value
5395: Level: developer
5397: .seealso: [](ch_ts), `TS`, `TSSetRHSFunction()`, `TSComputeIFunction()`
5398: @*/
5399: PetscErrorCode TSComputeLinearStability(TS ts, PetscReal xr, PetscReal xi, PetscReal *yr, PetscReal *yi)
5400: {
5401: PetscFunctionBegin;
5403: PetscUseTypeMethod(ts, linearstability, xr, xi, yr, yi);
5404: PetscFunctionReturn(PETSC_SUCCESS);
5405: }
5407: /*@
5408: TSRestartStep - Flags the solver to restart the next step
5410: Collective
5412: Input Parameter:
5413: . ts - the `TS` context obtained from `TSCreate()`
5415: Level: advanced
5417: Notes:
5418: Multistep methods like `TSBDF` or Runge-Kutta methods with FSAL property require restarting the solver in the event of
5419: discontinuities. These discontinuities may be introduced as a consequence of explicitly modifications to the solution
5420: vector (which PETSc attempts to detect and handle) or problem coefficients (which PETSc is not able to detect). For
5421: the sake of correctness and maximum safety, users are expected to call `TSRestart()` whenever they introduce
5422: discontinuities in callback routines (e.g. prestep and poststep routines, or implicit/rhs function routines with
5423: discontinuous source terms).
5425: .seealso: [](ch_ts), `TS`, `TSBDF`, `TSSolve()`, `TSSetPreStep()`, `TSSetPostStep()`
5426: @*/
5427: PetscErrorCode TSRestartStep(TS ts)
5428: {
5429: PetscFunctionBegin;
5431: ts->steprestart = PETSC_TRUE;
5432: PetscFunctionReturn(PETSC_SUCCESS);
5433: }
5435: /*@
5436: TSRollBack - Rolls back one time step
5438: Collective
5440: Input Parameter:
5441: . ts - the `TS` context obtained from `TSCreate()`
5443: Level: advanced
5445: .seealso: [](ch_ts), `TS`, `TSGetStepRollBack()`, `TSCreate()`, `TSSetUp()`, `TSDestroy()`, `TSSolve()`, `TSSetPreStep()`, `TSSetPreStage()`, `TSInterpolate()`
5446: @*/
5447: PetscErrorCode TSRollBack(TS ts)
5448: {
5449: PetscFunctionBegin;
5451: PetscCheck(!ts->steprollback, PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_WRONGSTATE, "TSRollBack already called");
5452: PetscTryTypeMethod(ts, rollback);
5453: PetscCall(VecCopy(ts->vec_sol0, ts->vec_sol));
5454: ts->time_step = ts->ptime - ts->ptime_prev;
5455: ts->ptime = ts->ptime_prev;
5456: ts->ptime_prev = ts->ptime_prev_rollback;
5457: ts->steps--;
5458: ts->steprollback = PETSC_TRUE;
5459: PetscFunctionReturn(PETSC_SUCCESS);
5460: }
5462: /*@
5463: TSGetStepRollBack - Get the internal flag indicating if you are rolling back a step
5465: Not collective
5467: Input Parameter:
5468: . ts - the `TS` context obtained from `TSCreate()`
5470: Output Parameter:
5471: . flg - the rollback flag
5473: Level: advanced
5475: .seealso: [](ch_ts), `TS`, `TSCreate()`, `TSRollBack()`
5476: @*/
5477: PetscErrorCode TSGetStepRollBack(TS ts, PetscBool *flg)
5478: {
5479: PetscFunctionBegin;
5481: PetscAssertPointer(flg, 2);
5482: *flg = ts->steprollback;
5483: PetscFunctionReturn(PETSC_SUCCESS);
5484: }
5486: /*@
5487: TSGetStepResize - Get the internal flag indicating if the current step is after a resize.
5489: Not collective
5491: Input Parameter:
5492: . ts - the `TS` context obtained from `TSCreate()`
5494: Output Parameter:
5495: . flg - the resize flag
5497: Level: advanced
5499: .seealso: [](ch_ts), `TS`, `TSCreate()`, `TSSetResize()`
5500: @*/
5501: PetscErrorCode TSGetStepResize(TS ts, PetscBool *flg)
5502: {
5503: PetscFunctionBegin;
5505: PetscAssertPointer(flg, 2);
5506: *flg = ts->stepresize;
5507: PetscFunctionReturn(PETSC_SUCCESS);
5508: }
5510: /*@
5511: TSGetStages - Get the number of stages and stage values
5513: Input Parameter:
5514: . ts - the `TS` context obtained from `TSCreate()`
5516: Output Parameters:
5517: + ns - the number of stages
5518: - Y - the current stage vectors
5520: Level: advanced
5522: Note:
5523: Both `ns` and `Y` can be `NULL`.
5525: .seealso: [](ch_ts), `TS`, `TSCreate()`
5526: @*/
5527: PetscErrorCode TSGetStages(TS ts, PetscInt *ns, Vec **Y)
5528: {
5529: PetscFunctionBegin;
5531: if (ns) PetscAssertPointer(ns, 2);
5532: if (Y) PetscAssertPointer(Y, 3);
5533: if (!ts->ops->getstages) {
5534: if (ns) *ns = 0;
5535: if (Y) *Y = NULL;
5536: } else PetscUseTypeMethod(ts, getstages, ns, Y);
5537: PetscFunctionReturn(PETSC_SUCCESS);
5538: }
5540: /*@C
5541: TSComputeIJacobianDefaultColor - Computes the Jacobian using finite differences and coloring to exploit matrix sparsity.
5543: Collective
5545: Input Parameters:
5546: + ts - the `TS` context
5547: . t - current timestep
5548: . U - state vector
5549: . Udot - time derivative of state vector
5550: . shift - shift to apply, see note below
5551: - ctx - an optional user context
5553: Output Parameters:
5554: + J - Jacobian matrix (not altered in this routine)
5555: - B - newly computed Jacobian matrix to use with preconditioner (generally the same as `J`)
5557: Level: intermediate
5559: Notes:
5560: If F(t,U,Udot)=0 is the DAE, the required Jacobian is
5562: dF/dU + shift*dF/dUdot
5564: Most users should not need to explicitly call this routine, as it
5565: is used internally within the nonlinear solvers.
5567: This will first try to get the coloring from the `DM`. If the `DM` type has no coloring
5568: routine, then it will try to get the coloring from the matrix. This requires that the
5569: matrix have nonzero entries precomputed.
5571: .seealso: [](ch_ts), `TS`, `TSSetIJacobian()`, `MatFDColoringCreate()`, `MatFDColoringSetFunction()`
5572: @*/
5573: PetscErrorCode TSComputeIJacobianDefaultColor(TS ts, PetscReal t, Vec U, Vec Udot, PetscReal shift, Mat J, Mat B, PetscCtx ctx)
5574: {
5575: SNES snes;
5576: MatFDColoring color;
5577: PetscBool hascolor, matcolor = PETSC_FALSE;
5579: PetscFunctionBegin;
5580: PetscCall(PetscOptionsGetBool(((PetscObject)ts)->options, ((PetscObject)ts)->prefix, "-ts_fd_color_use_mat", &matcolor, NULL));
5581: PetscCall(PetscObjectQuery((PetscObject)B, "TSMatFDColoring", (PetscObject *)&color));
5582: if (!color) {
5583: DM dm;
5584: ISColoring iscoloring;
5586: PetscCall(TSGetDM(ts, &dm));
5587: PetscCall(DMHasColoring(dm, &hascolor));
5588: if (hascolor && !matcolor) {
5589: PetscCall(DMCreateColoring(dm, IS_COLORING_GLOBAL, &iscoloring));
5590: PetscCall(MatFDColoringCreate(B, iscoloring, &color));
5591: PetscCall(MatFDColoringSetFunction(color, (MatFDColoringFn *)SNESTSFormFunction, (void *)ts));
5592: PetscCall(MatFDColoringSetFromOptions(color));
5593: PetscCall(MatFDColoringSetUp(B, iscoloring, color));
5594: PetscCall(ISColoringDestroy(&iscoloring));
5595: } else {
5596: MatColoring mc;
5598: PetscCall(MatColoringCreate(B, &mc));
5599: PetscCall(MatColoringSetDistance(mc, 2));
5600: PetscCall(MatColoringSetType(mc, MATCOLORINGSL));
5601: PetscCall(MatColoringSetFromOptions(mc));
5602: PetscCall(MatColoringApply(mc, &iscoloring));
5603: PetscCall(MatColoringDestroy(&mc));
5604: PetscCall(MatFDColoringCreate(B, iscoloring, &color));
5605: PetscCall(MatFDColoringSetFunction(color, (MatFDColoringFn *)SNESTSFormFunction, (void *)ts));
5606: PetscCall(MatFDColoringSetFromOptions(color));
5607: PetscCall(MatFDColoringSetUp(B, iscoloring, color));
5608: PetscCall(ISColoringDestroy(&iscoloring));
5609: }
5610: PetscCall(PetscObjectCompose((PetscObject)B, "TSMatFDColoring", (PetscObject)color));
5611: PetscCall(PetscObjectDereference((PetscObject)color));
5612: }
5613: PetscCall(TSGetSNES(ts, &snes));
5614: PetscCall(MatFDColoringApply(B, color, U, snes));
5615: if (J != B) {
5616: PetscCall(MatAssemblyBegin(J, MAT_FINAL_ASSEMBLY));
5617: PetscCall(MatAssemblyEnd(J, MAT_FINAL_ASSEMBLY));
5618: }
5619: PetscFunctionReturn(PETSC_SUCCESS);
5620: }
5622: /*@C
5623: TSSetFunctionDomainError - Set a function that tests if the current state vector is valid
5625: Logically collective
5627: Input Parameters:
5628: + ts - the `TS` context
5629: - func - function called within `TSFunctionDomainError()`
5631: Calling sequence of `func`:
5632: + ts - the `TS` context
5633: . time - the current time (of the stage)
5634: . state - the state to check if it is valid
5635: - accept - (output parameter) `PETSC_FALSE` if the state is not acceptable, `PETSC_TRUE` if acceptable
5637: Level: intermediate
5639: Notes:
5640: `accept` must be collectively specified.
5641: If an implicit ODE solver is being used then, in addition to providing this routine, the
5642: user's code should call `SNESSetFunctionDomainError()` when domain errors occur during
5643: function evaluations where the functions are provided by `TSSetIFunction()` or `TSSetRHSFunction()`.
5644: Use `TSGetSNES()` to obtain the `SNES` object
5646: Developer Notes:
5647: The naming of this function is inconsistent with the `SNESSetFunctionDomainError()`
5648: since one takes a function pointer and the other does not.
5650: .seealso: [](ch_ts), `TSAdaptCheckStage()`, `TSFunctionDomainError()`, `SNESSetFunctionDomainError()`, `TSGetSNES()`
5651: @*/
5652: PetscErrorCode TSSetFunctionDomainError(TS ts, PetscErrorCode (*func)(TS ts, PetscReal time, Vec state, PetscBool *accept))
5653: {
5654: PetscFunctionBegin;
5656: ts->functiondomainerror = func;
5657: PetscFunctionReturn(PETSC_SUCCESS);
5658: }
5660: /*@
5661: TSFunctionDomainError - Checks if the current state is valid
5663: Collective
5665: Input Parameters:
5666: + ts - the `TS` context
5667: . stagetime - time of the simulation
5668: - Y - state vector to check.
5670: Output Parameter:
5671: . accept - Set to `PETSC_FALSE` if the current state vector is valid.
5673: Level: developer
5675: Note:
5676: This function is called by the `TS` integration routines and calls the user provided function (set with `TSSetFunctionDomainError()`)
5677: to check if the current state is valid.
5679: .seealso: [](ch_ts), `TS`, `TSSetFunctionDomainError()`
5680: @*/
5681: PetscErrorCode TSFunctionDomainError(TS ts, PetscReal stagetime, Vec Y, PetscBool *accept)
5682: {
5683: PetscFunctionBegin;
5687: PetscAssertPointer(accept, 4);
5688: *accept = PETSC_TRUE;
5689: if (ts->functiondomainerror) PetscCall((*ts->functiondomainerror)(ts, stagetime, Y, accept));
5690: PetscFunctionReturn(PETSC_SUCCESS);
5691: }
5693: /*@
5694: TSClone - This function clones a time step `TS` object.
5696: Collective
5698: Input Parameter:
5699: . tsin - The input `TS`
5701: Output Parameter:
5702: . tsout - The output `TS` (cloned)
5704: Level: developer
5706: Notes:
5707: 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.
5708: It will likely be replaced in the future with a mechanism of switching methods on the fly.
5710: 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
5711: .vb
5712: SNES snes_dup = NULL;
5713: TSGetSNES(ts,&snes_dup);
5714: TSSetSNES(ts,snes_dup);
5715: .ve
5717: .seealso: [](ch_ts), `TS`, `SNES`, `TSCreate()`, `TSSetType()`, `TSSetUp()`, `TSDestroy()`, `TSSetProblemType()`
5718: @*/
5719: PetscErrorCode TSClone(TS tsin, TS *tsout)
5720: {
5721: TS t;
5722: SNES snes_start;
5723: DM dm;
5724: TSType type;
5726: PetscFunctionBegin;
5727: PetscAssertPointer(tsin, 1);
5728: *tsout = NULL;
5730: PetscCall(PetscHeaderCreate(t, TS_CLASSID, "TS", "Time stepping", "TS", PetscObjectComm((PetscObject)tsin), TSDestroy, TSView));
5732: /* General TS description */
5733: t->numbermonitors = 0;
5734: t->setupcalled = PETSC_FALSE;
5735: t->ksp_its = 0;
5736: t->snes_its = 0;
5737: t->nwork = 0;
5738: t->rhsjacobian.time = PETSC_MIN_REAL;
5739: t->rhsjacobian.scale = 1.;
5740: t->ijacobian.shift = 1.;
5742: PetscCall(TSGetSNES(tsin, &snes_start));
5743: PetscCall(TSSetSNES(t, snes_start));
5745: PetscCall(TSGetDM(tsin, &dm));
5746: PetscCall(TSSetDM(t, dm));
5748: t->adapt = tsin->adapt;
5749: PetscCall(PetscObjectReference((PetscObject)t->adapt));
5751: t->trajectory = tsin->trajectory;
5752: PetscCall(PetscObjectReference((PetscObject)t->trajectory));
5754: t->event = tsin->event;
5755: if (t->event) t->event->refct++;
5757: t->problem_type = tsin->problem_type;
5758: t->ptime = tsin->ptime;
5759: t->ptime_prev = tsin->ptime_prev;
5760: t->time_step = tsin->time_step;
5761: t->max_time = tsin->max_time;
5762: t->steps = tsin->steps;
5763: t->max_steps = tsin->max_steps;
5764: t->equation_type = tsin->equation_type;
5765: t->atol = tsin->atol;
5766: t->rtol = tsin->rtol;
5767: t->max_snes_failures = tsin->max_snes_failures;
5768: t->max_reject = tsin->max_reject;
5769: t->errorifstepfailed = tsin->errorifstepfailed;
5771: PetscCall(TSGetType(tsin, &type));
5772: PetscCall(TSSetType(t, type));
5774: t->vec_sol = NULL;
5776: t->cfltime = tsin->cfltime;
5777: t->cfltime_local = tsin->cfltime_local;
5778: t->exact_final_time = tsin->exact_final_time;
5780: t->ops[0] = tsin->ops[0];
5782: if (((PetscObject)tsin)->fortran_func_pointers) {
5783: PetscInt i;
5784: PetscCall(PetscMalloc((10) * sizeof(PetscFortranCallbackFn *), &((PetscObject)t)->fortran_func_pointers));
5785: for (i = 0; i < 10; i++) ((PetscObject)t)->fortran_func_pointers[i] = ((PetscObject)tsin)->fortran_func_pointers[i];
5786: }
5787: *tsout = t;
5788: PetscFunctionReturn(PETSC_SUCCESS);
5789: }
5791: static PetscErrorCode RHSWrapperFunction_TSRHSJacobianTest(PetscCtx ctx, Vec x, Vec y)
5792: {
5793: TS ts = (TS)ctx;
5795: PetscFunctionBegin;
5796: PetscCall(TSComputeRHSFunction(ts, 0, x, y));
5797: PetscFunctionReturn(PETSC_SUCCESS);
5798: }
5800: /*@
5801: TSRHSJacobianTest - Compares the multiply routine provided to the `MATSHELL` with differencing on the `TS` given RHS function.
5803: Logically Collective
5805: Input Parameter:
5806: . ts - the time stepping routine
5808: Output Parameter:
5809: . flg - `PETSC_TRUE` if the multiply is likely correct
5811: Options Database Key:
5812: . -ts_rhs_jacobian_test_mult -mat_shell_test_mult_view - run the test at each timestep of the integrator
5814: Level: advanced
5816: Note:
5817: This only works for problems defined using `TSSetRHSFunction()` and Jacobian NOT `TSSetIFunction()` and Jacobian
5819: .seealso: [](ch_ts), `TS`, `Mat`, `MATSHELL`, `MatCreateShell()`, `MatShellGetContext()`, `MatShellGetOperation()`, `MatShellTestMultTranspose()`, `TSRHSJacobianTestTranspose()`
5820: @*/
5821: PetscErrorCode TSRHSJacobianTest(TS ts, PetscBool *flg)
5822: {
5823: Mat J, B;
5824: TSRHSJacobianFn *func;
5825: void *ctx;
5827: PetscFunctionBegin;
5828: PetscCall(TSGetRHSJacobian(ts, &J, &B, &func, &ctx));
5829: PetscCall((*func)(ts, 0.0, ts->vec_sol, J, B, ctx));
5830: PetscCall(MatShellTestMult(J, RHSWrapperFunction_TSRHSJacobianTest, ts->vec_sol, ts, flg));
5831: PetscFunctionReturn(PETSC_SUCCESS);
5832: }
5834: /*@
5835: TSRHSJacobianTestTranspose - Compares the multiply transpose routine provided to the `MATSHELL` with differencing on the `TS` given RHS function.
5837: Logically Collective
5839: Input Parameter:
5840: . ts - the time stepping routine
5842: Output Parameter:
5843: . flg - `PETSC_TRUE` if the multiply is likely correct
5845: Options Database Key:
5846: . -ts_rhs_jacobian_test_mult_transpose -mat_shell_test_mult_transpose_view - run the test at each timestep of the integrator
5848: Level: advanced
5850: Notes:
5851: This only works for problems defined using `TSSetRHSFunction()` and Jacobian NOT `TSSetIFunction()` and Jacobian
5853: .seealso: [](ch_ts), `TS`, `Mat`, `MatCreateShell()`, `MatShellGetContext()`, `MatShellGetOperation()`, `MatShellTestMultTranspose()`, `TSRHSJacobianTest()`
5854: @*/
5855: PetscErrorCode TSRHSJacobianTestTranspose(TS ts, PetscBool *flg)
5856: {
5857: Mat J, B;
5858: void *ctx;
5859: TSRHSJacobianFn *func;
5861: PetscFunctionBegin;
5862: PetscCall(TSGetRHSJacobian(ts, &J, &B, &func, &ctx));
5863: PetscCall((*func)(ts, 0.0, ts->vec_sol, J, B, ctx));
5864: PetscCall(MatShellTestMultTranspose(J, RHSWrapperFunction_TSRHSJacobianTest, ts->vec_sol, ts, flg));
5865: PetscFunctionReturn(PETSC_SUCCESS);
5866: }
5868: /*@
5869: TSSetUseSplitRHSFunction - Use the split RHSFunction when a multirate method is used.
5871: Logically Collective
5873: Input Parameters:
5874: + ts - timestepping context
5875: - use_splitrhsfunction - `PETSC_TRUE` indicates that the split RHSFunction will be used
5877: Options Database Key:
5878: . -ts_use_splitrhsfunction (true|false) - use the split RHS function for multirate solvers
5880: Level: intermediate
5882: Note:
5883: This is only for multirate methods
5885: .seealso: [](ch_ts), `TS`, `TSGetUseSplitRHSFunction()`
5886: @*/
5887: PetscErrorCode TSSetUseSplitRHSFunction(TS ts, PetscBool use_splitrhsfunction)
5888: {
5889: PetscFunctionBegin;
5891: ts->use_splitrhsfunction = use_splitrhsfunction;
5892: PetscFunctionReturn(PETSC_SUCCESS);
5893: }
5895: /*@
5896: TSGetUseSplitRHSFunction - Gets whether to use the split RHSFunction when a multirate method is used.
5898: Not Collective
5900: Input Parameter:
5901: . ts - timestepping context
5903: Output Parameter:
5904: . use_splitrhsfunction - `PETSC_TRUE` indicates that the split RHSFunction will be used
5906: Level: intermediate
5908: .seealso: [](ch_ts), `TS`, `TSSetUseSplitRHSFunction()`
5909: @*/
5910: PetscErrorCode TSGetUseSplitRHSFunction(TS ts, PetscBool *use_splitrhsfunction)
5911: {
5912: PetscFunctionBegin;
5914: *use_splitrhsfunction = ts->use_splitrhsfunction;
5915: PetscFunctionReturn(PETSC_SUCCESS);
5916: }
5918: /*@
5919: TSSetMatStructure - sets the relationship between the nonzero structure of the RHS Jacobian matrix to the IJacobian matrix.
5921: Logically Collective
5923: Input Parameters:
5924: + ts - the time-stepper
5925: - str - the structure (the default is `UNKNOWN_NONZERO_PATTERN`)
5927: Level: intermediate
5929: Note:
5930: When the relationship between the nonzero structures is known and supplied the solution process can be much faster
5932: .seealso: [](ch_ts), `TS`, `MatAXPY()`, `MatStructure`
5933: @*/
5934: PetscErrorCode TSSetMatStructure(TS ts, MatStructure str)
5935: {
5936: PetscFunctionBegin;
5938: ts->axpy_pattern = str;
5939: PetscFunctionReturn(PETSC_SUCCESS);
5940: }
5942: /*@
5943: TSSetEvaluationTimes - sets the evaluation points. The solution will be computed and stored for each time requested
5945: Collective
5947: Input Parameters:
5948: + ts - the time-stepper
5949: . n - number of the time points
5950: - time_points - array of the time points, must be increasing
5952: Options Database Key:
5953: . -ts_eval_times t0,...,tn - Sets the evaluation times
5955: Level: intermediate
5957: Notes:
5958: The elements in `time_points` must be all increasing. They correspond to the intermediate points to be saved.
5960: `TS_EXACTFINALTIME_MATCHSTEP` must be used to make the last time step in each sub-interval match the intermediate points specified.
5962: The intermediate solutions are saved in a vector array that can be accessed with `TSGetEvaluationSolutions()`. Thus using evaluation times may
5963: pressure the memory system when using a large number of time points.
5965: .seealso: [](ch_ts), `TS`, `TSGetEvaluationTimes()`, `TSGetEvaluationSolutions()`, `TSSetTimeSpan()`
5966: @*/
5967: PetscErrorCode TSSetEvaluationTimes(TS ts, PetscInt n, PetscReal time_points[])
5968: {
5969: PetscBool is_sorted;
5971: PetscFunctionBegin;
5973: if (ts->eval_times) { // Reset eval_times
5974: ts->eval_times->sol_idx = 0;
5975: ts->eval_times->time_point_idx = 0;
5976: if (n != ts->eval_times->num_time_points) {
5977: PetscCall(PetscFree(ts->eval_times->time_points));
5978: PetscCall(PetscFree(ts->eval_times->sol_times));
5979: PetscCall(VecDestroyVecs(ts->eval_times->num_time_points, &ts->eval_times->sol_vecs));
5980: } else {
5981: PetscCall(PetscArrayzero(ts->eval_times->sol_times, n));
5982: for (PetscInt i = 0; i < n; i++) PetscCall(VecZeroEntries(ts->eval_times->sol_vecs[i]));
5983: }
5984: } else { // Create/initialize eval_times
5985: TSEvaluationTimes eval_times;
5986: PetscCall(PetscNew(&eval_times));
5987: PetscCall(PetscMalloc1(n, &eval_times->time_points));
5988: PetscCall(PetscMalloc1(n, &eval_times->sol_times));
5989: eval_times->reltol = 1e-6;
5990: eval_times->abstol = 10 * PETSC_MACHINE_EPSILON;
5991: eval_times->worktol = 0;
5992: ts->eval_times = eval_times;
5993: }
5994: ts->eval_times->num_time_points = n;
5995: PetscCall(PetscSortedReal(n, time_points, &is_sorted));
5996: PetscCheck(is_sorted, PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_WRONG, "time_points array must be sorted");
5997: PetscCall(PetscArraycpy(ts->eval_times->time_points, time_points, n));
5998: // Note: ts->vec_sol not guaranteed to exist, so ts->eval_times->sol_vecs allocated at TSSolve time
5999: PetscFunctionReturn(PETSC_SUCCESS);
6000: }
6002: /*@C
6003: TSGetEvaluationTimes - gets the evaluation times set with `TSSetEvaluationTimes()`
6005: Not Collective
6007: Input Parameter:
6008: . ts - the time-stepper
6010: Output Parameters:
6011: + n - number of the time points
6012: - time_points - array of the time points
6014: Level: beginner
6016: Note:
6017: The values obtained are valid until the `TS` object is destroyed.
6019: Both `n` and `time_points` can be `NULL`.
6021: Also used to see time points set by `TSSetTimeSpan()`.
6023: .seealso: [](ch_ts), `TS`, `TSSetEvaluationTimes()`, `TSGetEvaluationSolutions()`
6024: @*/
6025: PetscErrorCode TSGetEvaluationTimes(TS ts, PetscInt *n, const PetscReal *time_points[])
6026: {
6027: PetscFunctionBegin;
6029: if (n) PetscAssertPointer(n, 2);
6030: if (time_points) PetscAssertPointer(time_points, 3);
6031: if (!ts->eval_times) {
6032: if (n) *n = 0;
6033: if (time_points) *time_points = NULL;
6034: } else {
6035: if (n) *n = ts->eval_times->num_time_points;
6036: if (time_points) *time_points = ts->eval_times->time_points;
6037: }
6038: PetscFunctionReturn(PETSC_SUCCESS);
6039: }
6041: /*@C
6042: TSGetEvaluationSolutions - Get the number of solutions and the solutions at the evaluation time points specified
6044: Input Parameter:
6045: . ts - the `TS` context obtained from `TSCreate()`
6047: Output Parameters:
6048: + nsol - the number of solutions
6049: . sol_times - array of solution times corresponding to the solution vectors. See note below
6050: - Sols - the solution vectors
6052: Level: intermediate
6054: Notes:
6055: Both `nsol` and `Sols` can be `NULL`.
6057: Some time points in the evaluation points may be skipped by `TS` so that `nsol` is less than the number of points specified by `TSSetEvaluationTimes()`.
6058: For example, manipulating the step size, especially with a reduced precision, may cause `TS` to step over certain evaluation times.
6060: Also used to see view solutions requested by `TSSetTimeSpan()`.
6062: .seealso: [](ch_ts), `TS`, `TSSetEvaluationTimes()`, `TSGetEvaluationTimes()`
6063: @*/
6064: PetscErrorCode TSGetEvaluationSolutions(TS ts, PetscInt *nsol, const PetscReal *sol_times[], Vec *Sols[])
6065: {
6066: PetscFunctionBegin;
6068: if (nsol) PetscAssertPointer(nsol, 2);
6069: if (sol_times) PetscAssertPointer(sol_times, 3);
6070: if (Sols) PetscAssertPointer(Sols, 4);
6071: if (!ts->eval_times) {
6072: if (nsol) *nsol = 0;
6073: if (sol_times) *sol_times = NULL;
6074: if (Sols) *Sols = NULL;
6075: } else {
6076: if (nsol) *nsol = ts->eval_times->sol_idx;
6077: if (sol_times) *sol_times = ts->eval_times->sol_times;
6078: if (Sols) *Sols = ts->eval_times->sol_vecs;
6079: }
6080: PetscFunctionReturn(PETSC_SUCCESS);
6081: }
6083: /*@
6084: TSSetTimeSpan - sets the time span. The solution will be computed and stored for each time requested in the span
6086: Collective
6088: Input Parameters:
6089: + ts - the time-stepper
6090: . n - number of the time points (>=2)
6091: - span_times - array of the time points, must be increasing. The first element and the last element are the initial time and the final time respectively.
6093: Options Database Key:
6094: . -ts_time_span t0,...,tf - Sets the time span
6096: Level: intermediate
6098: Notes:
6099: This function is identical to `TSSetEvaluationTimes()`, except that it also sets the initial time and final time for the `ts` to the first and last `span_times` entries.
6101: The elements in `span_times` must be all increasing. They correspond to the intermediate points to be saved.
6103: `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 `TSGetEvaluationSolutions()`. Thus using time span may
6106: pressure the memory system when using a large number of span points.
6108: .seealso: [](ch_ts), `TS`, `TSSetEvaluationTimes()`, `TSGetEvaluationTimes()`, `TSGetEvaluationSolutions()`
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: PetscCall(TSSetEvaluationTimes(ts, n, span_times));
6116: PetscCall(TSSetTime(ts, span_times[0]));
6117: PetscCall(TSSetMaxTime(ts, span_times[n - 1]));
6118: PetscFunctionReturn(PETSC_SUCCESS);
6119: }
6121: /*@
6122: TSPruneIJacobianColor - Remove nondiagonal zeros in the Jacobian matrix and update the `MatMFFD` coloring information.
6124: Collective
6126: Input Parameters:
6127: + ts - the `TS` context
6128: . J - Jacobian matrix (not altered in this routine)
6129: - B - newly computed Jacobian matrix to use with preconditioner
6131: Level: intermediate
6133: Notes:
6134: This function improves the `MatFDColoring` performance when the Jacobian matrix was over-allocated or contains
6135: many constant zeros entries, which is typically the case when the matrix is generated by a `DM`
6136: and multiple fields are involved.
6138: Users need to make sure that the Jacobian matrix is properly filled to reflect the sparsity
6139: structure. For `MatFDColoring`, the values of nonzero entries are not important. So one can
6140: usually call `TSComputeIJacobian()` with randomized input vectors to generate a dummy Jacobian.
6141: `TSComputeIJacobian()` should be called before `TSSolve()` but after `TSSetUp()`.
6143: .seealso: [](ch_ts), `TS`, `MatFDColoring`, `TSComputeIJacobianDefaultColor()`, `MatEliminateZeros()`, `MatFDColoringCreate()`, `MatFDColoringSetFunction()`
6144: @*/
6145: PetscErrorCode TSPruneIJacobianColor(TS ts, Mat J, Mat B)
6146: {
6147: MatColoring mc = NULL;
6148: ISColoring iscoloring = NULL;
6149: MatFDColoring matfdcoloring = NULL;
6151: PetscFunctionBegin;
6152: /* Generate new coloring after eliminating zeros in the matrix */
6153: PetscCall(MatEliminateZeros(B, PETSC_TRUE));
6154: PetscCall(MatColoringCreate(B, &mc));
6155: PetscCall(MatColoringSetDistance(mc, 2));
6156: PetscCall(MatColoringSetType(mc, MATCOLORINGSL));
6157: PetscCall(MatColoringSetFromOptions(mc));
6158: PetscCall(MatColoringApply(mc, &iscoloring));
6159: PetscCall(MatColoringDestroy(&mc));
6160: /* Replace the old coloring with the new one */
6161: PetscCall(MatFDColoringCreate(B, iscoloring, &matfdcoloring));
6162: PetscCall(MatFDColoringSetFunction(matfdcoloring, (MatFDColoringFn *)SNESTSFormFunction, (void *)ts));
6163: PetscCall(MatFDColoringSetFromOptions(matfdcoloring));
6164: PetscCall(MatFDColoringSetUp(B, iscoloring, matfdcoloring));
6165: PetscCall(PetscObjectCompose((PetscObject)B, "TSMatFDColoring", (PetscObject)matfdcoloring));
6166: PetscCall(PetscObjectDereference((PetscObject)matfdcoloring));
6167: PetscCall(ISColoringDestroy(&iscoloring));
6168: PetscFunctionReturn(PETSC_SUCCESS);
6169: }