Actual source code: ts.c
1: #include <petsc/private/tsimpl.h>
2: #include <petscdmshell.h>
3: #include <petscdmda.h>
4: #include <petscviewer.h>
5: #include <petscdraw.h>
6: #include <petscconvest.h>
8: #define SkipSmallValue(a,b,tol) if (PetscAbsScalar(a)< tol || PetscAbsScalar(b)< tol) continue;
10: /* Logging support */
11: PetscClassId TS_CLASSID, DMTS_CLASSID;
12: PetscLogEvent TS_Step, TS_PseudoComputeTimeStep, TS_FunctionEval, TS_JacobianEval;
14: const char *const TSExactFinalTimeOptions[] = {"UNSPECIFIED","STEPOVER","INTERPOLATE","MATCHSTEP","TSExactFinalTimeOption","TS_EXACTFINALTIME_",NULL};
16: static PetscErrorCode TSAdaptSetDefaultType(TSAdapt adapt,TSAdaptType default_type)
17: {
23: if (!((PetscObject)adapt)->type_name) {
24: TSAdaptSetType(adapt,default_type);
25: }
26: return(0);
27: }
29: /*@
30: TSSetFromOptions - Sets various TS parameters from user options.
32: Collective on TS
34: Input Parameter:
35: . ts - the TS context obtained from TSCreate()
37: Options Database Keys:
38: + -ts_type <type> - TSEULER, TSBEULER, TSSUNDIALS, TSPSEUDO, TSCN, TSRK, TSTHETA, TSALPHA, TSGLLE, TSSSP, TSGLEE, TSBSYMP, TSIRK
39: . -ts_save_trajectory - checkpoint the solution at each time-step
40: . -ts_max_time <time> - maximum time to compute to
41: . -ts_max_steps <steps> - maximum number of time-steps to take
42: . -ts_init_time <time> - initial time to start computation
43: . -ts_final_time <time> - final time to compute to (deprecated: use -ts_max_time)
44: . -ts_dt <dt> - initial time step
45: . -ts_exact_final_time <stepover,interpolate,matchstep> - whether to stop at the exact given final time and how to compute the solution at that time
46: . -ts_max_snes_failures <maxfailures> - Maximum number of nonlinear solve failures allowed
47: . -ts_max_reject <maxrejects> - Maximum number of step rejections before step fails
48: . -ts_error_if_step_fails <true,false> - Error if no step succeeds
49: . -ts_rtol <rtol> - relative tolerance for local truncation error
50: . -ts_atol <atol> Absolute tolerance for local truncation error
51: . -ts_rhs_jacobian_test_mult -mat_shell_test_mult_view - test the Jacobian at each iteration against finite difference with RHS function
52: . -ts_rhs_jacobian_test_mult_transpose -mat_shell_test_mult_transpose_view - test the Jacobian at each iteration against finite difference with RHS function
53: . -ts_adjoint_solve <yes,no> After solving the ODE/DAE solve the adjoint problem (requires -ts_save_trajectory)
54: . -ts_fd_color - Use finite differences with coloring to compute IJacobian
55: . -ts_monitor - print information at each timestep
56: . -ts_monitor_cancel - Cancel all monitors
57: . -ts_monitor_lg_solution - Monitor solution graphically
58: . -ts_monitor_lg_error - Monitor error graphically
59: . -ts_monitor_error - Monitors norm of error
60: . -ts_monitor_lg_timestep - Monitor timestep size graphically
61: . -ts_monitor_lg_timestep_log - Monitor log timestep size graphically
62: . -ts_monitor_lg_snes_iterations - Monitor number nonlinear iterations for each timestep graphically
63: . -ts_monitor_lg_ksp_iterations - Monitor number nonlinear iterations for each timestep graphically
64: . -ts_monitor_sp_eig - Monitor eigenvalues of linearized operator graphically
65: . -ts_monitor_draw_solution - Monitor solution graphically
66: . -ts_monitor_draw_solution_phase <xleft,yleft,xright,yright> - Monitor solution graphically with phase diagram, requires problem with exactly 2 degrees of freedom
67: . -ts_monitor_draw_error - Monitor error graphically, requires use to have provided TSSetSolutionFunction()
68: . -ts_monitor_solution [ascii binary draw][:filename][:viewerformat] - monitors the solution at each timestep
69: . -ts_monitor_solution_vtk <filename.vts,filename.vtu> - Save each time step to a binary file, use filename-%%03D.vts (filename-%%03D.vtu)
70: - -ts_monitor_envelope - determine maximum and minimum value of each component of the solution over the solution time
72: Notes:
73: See SNESSetFromOptions() and KSPSetFromOptions() for how to control the nonlinear and linear solves used by the time-stepper.
75: Certain SNES options get reset for each new nonlinear solver, for example -snes_lag_jacobian <its> and -snes_lag_preconditioner <its>, in order
76: to retain them over the multiple nonlinear solves that TS uses you mush also provide -snes_lag_jacobian_persists true and
77: -snes_lag_preconditioner_persists true
79: Developer Note:
80: We should unify all the -ts_monitor options in the way that -xxx_view has been unified
82: Level: beginner
84: .seealso: TSGetType()
85: @*/
86: PetscErrorCode TSSetFromOptions(TS ts)
87: {
88: PetscBool opt,flg,tflg;
89: PetscErrorCode ierr;
90: char monfilename[PETSC_MAX_PATH_LEN];
91: PetscReal time_step;
92: TSExactFinalTimeOption eftopt;
93: char dir[16];
94: TSIFunction ifun;
95: const char *defaultType;
96: char typeName[256];
101: TSRegisterAll();
102: TSGetIFunction(ts,NULL,&ifun,NULL);
104: PetscObjectOptionsBegin((PetscObject)ts);
105: if (((PetscObject)ts)->type_name) defaultType = ((PetscObject)ts)->type_name;
106: else defaultType = ifun ? TSBEULER : TSEULER;
107: PetscOptionsFList("-ts_type","TS method","TSSetType",TSList,defaultType,typeName,256,&opt);
108: if (opt) {
109: TSSetType(ts,typeName);
110: } else {
111: TSSetType(ts,defaultType);
112: }
114: /* Handle generic TS options */
115: PetscOptionsDeprecated("-ts_final_time","-ts_max_time","3.10",NULL);
116: PetscOptionsReal("-ts_max_time","Maximum time to run to","TSSetMaxTime",ts->max_time,&ts->max_time,NULL);
117: PetscOptionsInt("-ts_max_steps","Maximum number of time steps","TSSetMaxSteps",ts->max_steps,&ts->max_steps,NULL);
118: PetscOptionsReal("-ts_init_time","Initial time","TSSetTime",ts->ptime,&ts->ptime,NULL);
119: PetscOptionsReal("-ts_dt","Initial time step","TSSetTimeStep",ts->time_step,&time_step,&flg);
120: if (flg) {TSSetTimeStep(ts,time_step);}
121: PetscOptionsEnum("-ts_exact_final_time","Option for handling of final time step","TSSetExactFinalTime",TSExactFinalTimeOptions,(PetscEnum)ts->exact_final_time,(PetscEnum*)&eftopt,&flg);
122: if (flg) {TSSetExactFinalTime(ts,eftopt);}
123: PetscOptionsInt("-ts_max_snes_failures","Maximum number of nonlinear solve failures","TSSetMaxSNESFailures",ts->max_snes_failures,&ts->max_snes_failures,NULL);
124: PetscOptionsInt("-ts_max_reject","Maximum number of step rejections before step fails","TSSetMaxStepRejections",ts->max_reject,&ts->max_reject,NULL);
125: PetscOptionsBool("-ts_error_if_step_fails","Error if no step succeeds","TSSetErrorIfStepFails",ts->errorifstepfailed,&ts->errorifstepfailed,NULL);
126: PetscOptionsReal("-ts_rtol","Relative tolerance for local truncation error","TSSetTolerances",ts->rtol,&ts->rtol,NULL);
127: PetscOptionsReal("-ts_atol","Absolute tolerance for local truncation error","TSSetTolerances",ts->atol,&ts->atol,NULL);
129: PetscOptionsBool("-ts_rhs_jacobian_test_mult","Test the RHS Jacobian for consistency with RHS at each solve ","None",ts->testjacobian,&ts->testjacobian,NULL);
130: PetscOptionsBool("-ts_rhs_jacobian_test_mult_transpose","Test the RHS Jacobian transpose for consistency with RHS at each solve ","None",ts->testjacobiantranspose,&ts->testjacobiantranspose,NULL);
131: PetscOptionsBool("-ts_use_splitrhsfunction","Use the split RHS function for multirate solvers ","TSSetUseSplitRHSFunction",ts->use_splitrhsfunction,&ts->use_splitrhsfunction,NULL);
132: #if defined(PETSC_HAVE_SAWS)
133: {
134: PetscBool set;
135: flg = PETSC_FALSE;
136: PetscOptionsBool("-ts_saws_block","Block for SAWs memory snooper at end of TSSolve","PetscObjectSAWsBlock",((PetscObject)ts)->amspublishblock,&flg,&set);
137: if (set) {
138: PetscObjectSAWsSetBlock((PetscObject)ts,flg);
139: }
140: }
141: #endif
143: /* Monitor options */
144: PetscOptionsInt("-ts_monitor_frequency", "Number of time steps between monitor output", "TSMonitorSetFrequency", ts->monitorFrequency, &ts->monitorFrequency, NULL);
145: TSMonitorSetFromOptions(ts,"-ts_monitor","Monitor time and timestep size","TSMonitorDefault",TSMonitorDefault,NULL);
146: TSMonitorSetFromOptions(ts,"-ts_monitor_extreme","Monitor extreme values of the solution","TSMonitorExtreme",TSMonitorExtreme,NULL);
147: TSMonitorSetFromOptions(ts,"-ts_monitor_solution","View the solution at each timestep","TSMonitorSolution",TSMonitorSolution,NULL);
148: TSMonitorSetFromOptions(ts,"-ts_dmswarm_monitor_moments","Monitor moments of particle distribution","TSDMSwarmMonitorMoments",TSDMSwarmMonitorMoments,NULL);
150: PetscOptionsString("-ts_monitor_python","Use Python function","TSMonitorSet",NULL,monfilename,sizeof(monfilename),&flg);
151: if (flg) {PetscPythonMonitorSet((PetscObject)ts,monfilename);}
153: PetscOptionsName("-ts_monitor_lg_solution","Monitor solution graphically","TSMonitorLGSolution",&opt);
154: if (opt) {
155: PetscInt howoften = 1;
156: DM dm;
157: PetscBool net;
159: PetscOptionsInt("-ts_monitor_lg_solution","Monitor solution graphically","TSMonitorLGSolution",howoften,&howoften,NULL);
160: TSGetDM(ts,&dm);
161: PetscObjectTypeCompare((PetscObject)dm,DMNETWORK,&net);
162: if (net) {
163: TSMonitorLGCtxNetwork ctx;
164: TSMonitorLGCtxNetworkCreate(ts,NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,600,400,howoften,&ctx);
165: TSMonitorSet(ts,TSMonitorLGCtxNetworkSolution,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxNetworkDestroy);
166: PetscOptionsBool("-ts_monitor_lg_solution_semilogy","Plot the solution with a semi-log axis","",ctx->semilogy,&ctx->semilogy,NULL);
167: } else {
168: TSMonitorLGCtx ctx;
169: TSMonitorLGCtxCreate(PETSC_COMM_SELF,NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);
170: TSMonitorSet(ts,TSMonitorLGSolution,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);
171: }
172: }
174: PetscOptionsName("-ts_monitor_lg_error","Monitor error graphically","TSMonitorLGError",&opt);
175: if (opt) {
176: TSMonitorLGCtx ctx;
177: PetscInt howoften = 1;
179: PetscOptionsInt("-ts_monitor_lg_error","Monitor error graphically","TSMonitorLGError",howoften,&howoften,NULL);
180: TSMonitorLGCtxCreate(PETSC_COMM_SELF,NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);
181: TSMonitorSet(ts,TSMonitorLGError,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);
182: }
183: TSMonitorSetFromOptions(ts,"-ts_monitor_error","View the error at each timestep","TSMonitorError",TSMonitorError,NULL);
185: PetscOptionsName("-ts_monitor_lg_timestep","Monitor timestep size graphically","TSMonitorLGTimeStep",&opt);
186: if (opt) {
187: TSMonitorLGCtx ctx;
188: PetscInt howoften = 1;
190: PetscOptionsInt("-ts_monitor_lg_timestep","Monitor timestep size graphically","TSMonitorLGTimeStep",howoften,&howoften,NULL);
191: TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);
192: TSMonitorSet(ts,TSMonitorLGTimeStep,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);
193: }
194: PetscOptionsName("-ts_monitor_lg_timestep_log","Monitor log timestep size graphically","TSMonitorLGTimeStep",&opt);
195: if (opt) {
196: TSMonitorLGCtx ctx;
197: PetscInt howoften = 1;
199: PetscOptionsInt("-ts_monitor_lg_timestep_log","Monitor log timestep size graphically","TSMonitorLGTimeStep",howoften,&howoften,NULL);
200: TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);
201: TSMonitorSet(ts,TSMonitorLGTimeStep,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);
202: ctx->semilogy = PETSC_TRUE;
203: }
205: PetscOptionsName("-ts_monitor_lg_snes_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGSNESIterations",&opt);
206: if (opt) {
207: TSMonitorLGCtx ctx;
208: PetscInt howoften = 1;
210: PetscOptionsInt("-ts_monitor_lg_snes_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGSNESIterations",howoften,&howoften,NULL);
211: TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);
212: TSMonitorSet(ts,TSMonitorLGSNESIterations,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);
213: }
214: PetscOptionsName("-ts_monitor_lg_ksp_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGKSPIterations",&opt);
215: if (opt) {
216: TSMonitorLGCtx ctx;
217: PetscInt howoften = 1;
219: PetscOptionsInt("-ts_monitor_lg_ksp_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGKSPIterations",howoften,&howoften,NULL);
220: TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);
221: TSMonitorSet(ts,TSMonitorLGKSPIterations,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);
222: }
223: PetscOptionsName("-ts_monitor_sp_eig","Monitor eigenvalues of linearized operator graphically","TSMonitorSPEig",&opt);
224: if (opt) {
225: TSMonitorSPEigCtx ctx;
226: PetscInt howoften = 1;
228: PetscOptionsInt("-ts_monitor_sp_eig","Monitor eigenvalues of linearized operator graphically","TSMonitorSPEig",howoften,&howoften,NULL);
229: TSMonitorSPEigCtxCreate(PETSC_COMM_SELF,NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);
230: TSMonitorSet(ts,TSMonitorSPEig,ctx,(PetscErrorCode (*)(void**))TSMonitorSPEigCtxDestroy);
231: }
232: PetscOptionsName("-ts_monitor_sp_swarm","Display particle phase from the DMSwarm","TSMonitorSPSwarm",&opt);
233: if (opt) {
234: TSMonitorSPCtx ctx;
235: PetscInt howoften = 1;
236: PetscOptionsInt("-ts_monitor_sp_swarm","Display particles phase from the DMSwarm","TSMonitorSPSwarm",howoften,&howoften,NULL);
237: TSMonitorSPCtxCreate(PETSC_COMM_SELF, NULL, NULL, PETSC_DECIDE, PETSC_DECIDE, 300, 300, howoften, &ctx);
238: TSMonitorSet(ts, TSMonitorSPSwarmSolution, ctx, (PetscErrorCode (*)(void**))TSMonitorSPCtxDestroy);
239: }
240: opt = PETSC_FALSE;
241: PetscOptionsName("-ts_monitor_draw_solution","Monitor solution graphically","TSMonitorDrawSolution",&opt);
242: if (opt) {
243: TSMonitorDrawCtx ctx;
244: PetscInt howoften = 1;
246: PetscOptionsInt("-ts_monitor_draw_solution","Monitor solution graphically","TSMonitorDrawSolution",howoften,&howoften,NULL);
247: TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),NULL,"Computed Solution",PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);
248: TSMonitorSet(ts,TSMonitorDrawSolution,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);
249: }
250: opt = PETSC_FALSE;
251: PetscOptionsName("-ts_monitor_draw_solution_phase","Monitor solution graphically","TSMonitorDrawSolutionPhase",&opt);
252: if (opt) {
253: TSMonitorDrawCtx ctx;
254: PetscReal bounds[4];
255: PetscInt n = 4;
256: PetscDraw draw;
257: PetscDrawAxis axis;
259: PetscOptionsRealArray("-ts_monitor_draw_solution_phase","Monitor solution graphically","TSMonitorDrawSolutionPhase",bounds,&n,NULL);
260: if (n != 4) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Must provide bounding box of phase field");
261: TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,300,300,1,&ctx);
262: PetscViewerDrawGetDraw(ctx->viewer,0,&draw);
263: PetscViewerDrawGetDrawAxis(ctx->viewer,0,&axis);
264: PetscDrawAxisSetLimits(axis,bounds[0],bounds[2],bounds[1],bounds[3]);
265: PetscDrawAxisSetLabels(axis,"Phase Diagram","Variable 1","Variable 2");
266: TSMonitorSet(ts,TSMonitorDrawSolutionPhase,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);
267: }
268: opt = PETSC_FALSE;
269: PetscOptionsName("-ts_monitor_draw_error","Monitor error graphically","TSMonitorDrawError",&opt);
270: if (opt) {
271: TSMonitorDrawCtx ctx;
272: PetscInt howoften = 1;
274: PetscOptionsInt("-ts_monitor_draw_error","Monitor error graphically","TSMonitorDrawError",howoften,&howoften,NULL);
275: TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),NULL,"Error",PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);
276: TSMonitorSet(ts,TSMonitorDrawError,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);
277: }
278: opt = PETSC_FALSE;
279: PetscOptionsName("-ts_monitor_draw_solution_function","Monitor solution provided by TSMonitorSetSolutionFunction() graphically","TSMonitorDrawSolutionFunction",&opt);
280: if (opt) {
281: TSMonitorDrawCtx ctx;
282: PetscInt howoften = 1;
284: PetscOptionsInt("-ts_monitor_draw_solution_function","Monitor solution provided by TSMonitorSetSolutionFunction() graphically","TSMonitorDrawSolutionFunction",howoften,&howoften,NULL);
285: TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),NULL,"Solution provided by user function",PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);
286: TSMonitorSet(ts,TSMonitorDrawSolutionFunction,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);
287: }
289: opt = PETSC_FALSE;
290: PetscOptionsString("-ts_monitor_solution_vtk","Save each time step to a binary file, use filename-%%03D.vts","TSMonitorSolutionVTK",NULL,monfilename,sizeof(monfilename),&flg);
291: if (flg) {
292: const char *ptr,*ptr2;
293: char *filetemplate;
294: if (!monfilename[0]) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"-ts_monitor_solution_vtk requires a file template, e.g. filename-%%03D.vts");
295: /* Do some cursory validation of the input. */
296: PetscStrstr(monfilename,"%",(char**)&ptr);
297: if (!ptr) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"-ts_monitor_solution_vtk requires a file template, e.g. filename-%%03D.vts");
298: for (ptr++; ptr && *ptr; ptr++) {
299: PetscStrchr("DdiouxX",*ptr,(char**)&ptr2);
300: if (!ptr2 && (*ptr < '0' || '9' < *ptr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Invalid file template argument to -ts_monitor_solution_vtk, should look like filename-%%03D.vts");
301: if (ptr2) break;
302: }
303: PetscStrallocpy(monfilename,&filetemplate);
304: TSMonitorSet(ts,TSMonitorSolutionVTK,filetemplate,(PetscErrorCode (*)(void**))TSMonitorSolutionVTKDestroy);
305: }
307: PetscOptionsString("-ts_monitor_dmda_ray","Display a ray of the solution","None","y=0",dir,sizeof(dir),&flg);
308: if (flg) {
309: TSMonitorDMDARayCtx *rayctx;
310: int ray = 0;
311: DMDirection ddir;
312: DM da;
313: PetscMPIInt rank;
315: if (dir[1] != '=') SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Unknown ray %s",dir);
316: if (dir[0] == 'x') ddir = DM_X;
317: else if (dir[0] == 'y') ddir = DM_Y;
318: else SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Unknown ray %s",dir);
319: sscanf(dir+2,"%d",&ray);
321: PetscInfo2(((PetscObject)ts),"Displaying DMDA ray %c = %d\n",dir[0],ray);
322: PetscNew(&rayctx);
323: TSGetDM(ts,&da);
324: DMDAGetRay(da,ddir,ray,&rayctx->ray,&rayctx->scatter);
325: MPI_Comm_rank(PetscObjectComm((PetscObject)ts),&rank);
326: if (rank == 0) {
327: PetscViewerDrawOpen(PETSC_COMM_SELF,NULL,NULL,0,0,600,300,&rayctx->viewer);
328: }
329: rayctx->lgctx = NULL;
330: TSMonitorSet(ts,TSMonitorDMDARay,rayctx,TSMonitorDMDARayDestroy);
331: }
332: PetscOptionsString("-ts_monitor_lg_dmda_ray","Display a ray of the solution","None","x=0",dir,sizeof(dir),&flg);
333: if (flg) {
334: TSMonitorDMDARayCtx *rayctx;
335: int ray = 0;
336: DMDirection ddir;
337: DM da;
338: PetscInt howoften = 1;
340: if (dir[1] != '=') SETERRQ1(PetscObjectComm((PetscObject) ts), PETSC_ERR_ARG_WRONG, "Malformed ray %s", dir);
341: if (dir[0] == 'x') ddir = DM_X;
342: else if (dir[0] == 'y') ddir = DM_Y;
343: else SETERRQ1(PetscObjectComm((PetscObject) ts), PETSC_ERR_ARG_WRONG, "Unknown ray direction %s", dir);
344: sscanf(dir+2, "%d", &ray);
346: PetscInfo2(((PetscObject) ts),"Displaying LG DMDA ray %c = %d\n", dir[0], ray);
347: PetscNew(&rayctx);
348: TSGetDM(ts, &da);
349: DMDAGetRay(da, ddir, ray, &rayctx->ray, &rayctx->scatter);
350: TSMonitorLGCtxCreate(PETSC_COMM_SELF,NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,600,400,howoften,&rayctx->lgctx);
351: TSMonitorSet(ts, TSMonitorLGDMDARay, rayctx, TSMonitorDMDARayDestroy);
352: }
354: PetscOptionsName("-ts_monitor_envelope","Monitor maximum and minimum value of each component of the solution","TSMonitorEnvelope",&opt);
355: if (opt) {
356: TSMonitorEnvelopeCtx ctx;
358: TSMonitorEnvelopeCtxCreate(ts,&ctx);
359: TSMonitorSet(ts,TSMonitorEnvelope,ctx,(PetscErrorCode (*)(void**))TSMonitorEnvelopeCtxDestroy);
360: }
361: flg = PETSC_FALSE;
362: PetscOptionsBool("-ts_monitor_cancel","Remove all monitors","TSMonitorCancel",flg,&flg,&opt);
363: if (opt && flg) {TSMonitorCancel(ts);}
365: flg = PETSC_FALSE;
366: PetscOptionsBool("-ts_fd_color", "Use finite differences with coloring to compute IJacobian", "TSComputeJacobianDefaultColor", flg, &flg, NULL);
367: if (flg) {
368: DM dm;
369: DMTS tdm;
371: TSGetDM(ts, &dm);
372: DMGetDMTS(dm, &tdm);
373: tdm->ijacobianctx = NULL;
374: TSSetIJacobian(ts, NULL, NULL, TSComputeIJacobianDefaultColor, NULL);
375: PetscInfo(ts, "Setting default finite difference coloring Jacobian matrix\n");
376: }
378: /* Handle specific TS options */
379: if (ts->ops->setfromoptions) {
380: (*ts->ops->setfromoptions)(PetscOptionsObject,ts);
381: }
383: /* Handle TSAdapt options */
384: TSGetAdapt(ts,&ts->adapt);
385: TSAdaptSetDefaultType(ts->adapt,ts->default_adapt_type);
386: TSAdaptSetFromOptions(PetscOptionsObject,ts->adapt);
388: /* TS trajectory must be set after TS, since it may use some TS options above */
389: tflg = ts->trajectory ? PETSC_TRUE : PETSC_FALSE;
390: PetscOptionsBool("-ts_save_trajectory","Save the solution at each timestep","TSSetSaveTrajectory",tflg,&tflg,NULL);
391: if (tflg) {
392: TSSetSaveTrajectory(ts);
393: }
395: TSAdjointSetFromOptions(PetscOptionsObject,ts);
397: /* process any options handlers added with PetscObjectAddOptionsHandler() */
398: PetscObjectProcessOptionsHandlers(PetscOptionsObject,(PetscObject)ts);
399: PetscOptionsEnd();
401: if (ts->trajectory) {
402: TSTrajectorySetFromOptions(ts->trajectory,ts);
403: }
405: /* why do we have to do this here and not during TSSetUp? */
406: TSGetSNES(ts,&ts->snes);
407: if (ts->problem_type == TS_LINEAR) {
408: PetscObjectTypeCompareAny((PetscObject)ts->snes,&flg,SNESKSPONLY,SNESKSPTRANSPOSEONLY,"");
409: if (!flg) { SNESSetType(ts->snes,SNESKSPONLY); }
410: }
411: SNESSetFromOptions(ts->snes);
412: return(0);
413: }
415: /*@
416: TSGetTrajectory - Gets the trajectory from a TS if it exists
418: Collective on TS
420: Input Parameters:
421: . ts - the TS context obtained from TSCreate()
423: Output Parameters:
424: . tr - the TSTrajectory object, if it exists
426: Note: This routine should be called after all TS options have been set
428: Level: advanced
430: .seealso: TSGetTrajectory(), TSAdjointSolve(), TSTrajectory, TSTrajectoryCreate()
432: @*/
433: PetscErrorCode TSGetTrajectory(TS ts,TSTrajectory *tr)
434: {
437: *tr = ts->trajectory;
438: return(0);
439: }
441: /*@
442: TSSetSaveTrajectory - Causes the TS to save its solutions as it iterates forward in time in a TSTrajectory object
444: Collective on TS
446: Input Parameter:
447: . ts - the TS context obtained from TSCreate()
449: Options Database:
450: + -ts_save_trajectory - saves the trajectory to a file
451: - -ts_trajectory_type type
453: Note: This routine should be called after all TS options have been set
455: The TSTRAJECTORYVISUALIZATION files can be loaded into Python with $PETSC_DIR/lib/petsc/bin/PetscBinaryIOTrajectory.py and
456: MATLAB with $PETSC_DIR/share/petsc/matlab/PetscReadBinaryTrajectory.m
458: Level: intermediate
460: .seealso: TSGetTrajectory(), TSAdjointSolve()
462: @*/
463: PetscErrorCode TSSetSaveTrajectory(TS ts)
464: {
469: if (!ts->trajectory) {
470: TSTrajectoryCreate(PetscObjectComm((PetscObject)ts),&ts->trajectory);
471: }
472: return(0);
473: }
475: /*@
476: TSResetTrajectory - Destroys and recreates the internal TSTrajectory object
478: Collective on TS
480: Input Parameters:
481: . ts - the TS context obtained from TSCreate()
483: Level: intermediate
485: .seealso: TSGetTrajectory(), TSAdjointSolve()
487: @*/
488: PetscErrorCode TSResetTrajectory(TS ts)
489: {
494: if (ts->trajectory) {
495: TSTrajectoryDestroy(&ts->trajectory);
496: TSTrajectoryCreate(PetscObjectComm((PetscObject)ts),&ts->trajectory);
497: }
498: return(0);
499: }
501: /*@
502: TSComputeRHSJacobian - Computes the Jacobian matrix that has been
503: set with TSSetRHSJacobian().
505: Collective on TS
507: Input Parameters:
508: + ts - the TS context
509: . t - current timestep
510: - U - input vector
512: Output Parameters:
513: + A - Jacobian matrix
514: - B - optional preconditioning matrix
516: Notes:
517: Most users should not need to explicitly call this routine, as it
518: is used internally within the nonlinear solvers.
520: Level: developer
522: .seealso: TSSetRHSJacobian(), KSPSetOperators()
523: @*/
524: PetscErrorCode TSComputeRHSJacobian(TS ts,PetscReal t,Vec U,Mat A,Mat B)
525: {
526: PetscErrorCode ierr;
527: PetscObjectState Ustate;
528: PetscObjectId Uid;
529: DM dm;
530: DMTS tsdm;
531: TSRHSJacobian rhsjacobianfunc;
532: void *ctx;
533: TSRHSFunction rhsfunction;
539: TSGetDM(ts,&dm);
540: DMGetDMTS(dm,&tsdm);
541: DMTSGetRHSFunction(dm,&rhsfunction,NULL);
542: DMTSGetRHSJacobian(dm,&rhsjacobianfunc,&ctx);
543: PetscObjectStateGet((PetscObject)U,&Ustate);
544: PetscObjectGetId((PetscObject)U,&Uid);
546: if (ts->rhsjacobian.time == t && (ts->problem_type == TS_LINEAR || (ts->rhsjacobian.Xid == Uid && ts->rhsjacobian.Xstate == Ustate)) && (rhsfunction != TSComputeRHSFunctionLinear)) return(0);
548: if (ts->rhsjacobian.shift && ts->rhsjacobian.reuse) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Should not call TSComputeRHSJacobian() on a shifted matrix (shift=%lf) when RHSJacobian is reusable.",ts->rhsjacobian.shift);
549: if (rhsjacobianfunc) {
550: PetscLogEventBegin(TS_JacobianEval,ts,U,A,B);
551: PetscStackPush("TS user Jacobian function");
552: (*rhsjacobianfunc)(ts,t,U,A,B,ctx);
553: PetscStackPop;
554: ts->rhsjacs++;
555: PetscLogEventEnd(TS_JacobianEval,ts,U,A,B);
556: } else {
557: MatZeroEntries(A);
558: if (B && A != B) {MatZeroEntries(B);}
559: }
560: ts->rhsjacobian.time = t;
561: ts->rhsjacobian.shift = 0;
562: ts->rhsjacobian.scale = 1.;
563: PetscObjectGetId((PetscObject)U,&ts->rhsjacobian.Xid);
564: PetscObjectStateGet((PetscObject)U,&ts->rhsjacobian.Xstate);
565: return(0);
566: }
568: /*@
569: TSComputeRHSFunction - Evaluates the right-hand-side function.
571: Collective on TS
573: Input Parameters:
574: + ts - the TS context
575: . t - current time
576: - U - state vector
578: Output Parameter:
579: . y - right hand side
581: Note:
582: Most users should not need to explicitly call this routine, as it
583: is used internally within the nonlinear solvers.
585: Level: developer
587: .seealso: TSSetRHSFunction(), TSComputeIFunction()
588: @*/
589: PetscErrorCode TSComputeRHSFunction(TS ts,PetscReal t,Vec U,Vec y)
590: {
592: TSRHSFunction rhsfunction;
593: TSIFunction ifunction;
594: void *ctx;
595: DM dm;
601: TSGetDM(ts,&dm);
602: DMTSGetRHSFunction(dm,&rhsfunction,&ctx);
603: DMTSGetIFunction(dm,&ifunction,NULL);
605: if (!rhsfunction && !ifunction) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSFunction() and / or TSSetIFunction()");
607: if (rhsfunction) {
608: PetscLogEventBegin(TS_FunctionEval,ts,U,y,0);
609: VecLockReadPush(U);
610: PetscStackPush("TS user right-hand-side function");
611: (*rhsfunction)(ts,t,U,y,ctx);
612: PetscStackPop;
613: VecLockReadPop(U);
614: ts->rhsfuncs++;
615: PetscLogEventEnd(TS_FunctionEval,ts,U,y,0);
616: } else {
617: VecZeroEntries(y);
618: }
619: return(0);
620: }
622: /*@
623: TSComputeSolutionFunction - Evaluates the solution function.
625: Collective on TS
627: Input Parameters:
628: + ts - the TS context
629: - t - current time
631: Output Parameter:
632: . U - the solution
634: Note:
635: Most users should not need to explicitly call this routine, as it
636: is used internally within the nonlinear solvers.
638: Level: developer
640: .seealso: TSSetSolutionFunction(), TSSetRHSFunction(), TSComputeIFunction()
641: @*/
642: PetscErrorCode TSComputeSolutionFunction(TS ts,PetscReal t,Vec U)
643: {
644: PetscErrorCode ierr;
645: TSSolutionFunction solutionfunction;
646: void *ctx;
647: DM dm;
652: TSGetDM(ts,&dm);
653: DMTSGetSolutionFunction(dm,&solutionfunction,&ctx);
655: if (solutionfunction) {
656: PetscStackPush("TS user solution function");
657: (*solutionfunction)(ts,t,U,ctx);
658: PetscStackPop;
659: }
660: return(0);
661: }
662: /*@
663: TSComputeForcingFunction - Evaluates the forcing function.
665: Collective on TS
667: Input Parameters:
668: + ts - the TS context
669: - t - current time
671: Output Parameter:
672: . U - the function value
674: Note:
675: Most users should not need to explicitly call this routine, as it
676: is used internally within the nonlinear solvers.
678: Level: developer
680: .seealso: TSSetSolutionFunction(), TSSetRHSFunction(), TSComputeIFunction()
681: @*/
682: PetscErrorCode TSComputeForcingFunction(TS ts,PetscReal t,Vec U)
683: {
684: PetscErrorCode ierr, (*forcing)(TS,PetscReal,Vec,void*);
685: void *ctx;
686: DM dm;
691: TSGetDM(ts,&dm);
692: DMTSGetForcingFunction(dm,&forcing,&ctx);
694: if (forcing) {
695: PetscStackPush("TS user forcing function");
696: (*forcing)(ts,t,U,ctx);
697: PetscStackPop;
698: }
699: return(0);
700: }
702: static PetscErrorCode TSGetRHSVec_Private(TS ts,Vec *Frhs)
703: {
704: Vec F;
708: *Frhs = NULL;
709: TSGetIFunction(ts,&F,NULL,NULL);
710: if (!ts->Frhs) {
711: VecDuplicate(F,&ts->Frhs);
712: }
713: *Frhs = ts->Frhs;
714: return(0);
715: }
717: PetscErrorCode TSGetRHSMats_Private(TS ts,Mat *Arhs,Mat *Brhs)
718: {
719: Mat A,B;
721: TSIJacobian ijacobian;
724: if (Arhs) *Arhs = NULL;
725: if (Brhs) *Brhs = NULL;
726: TSGetIJacobian(ts,&A,&B,&ijacobian,NULL);
727: if (Arhs) {
728: if (!ts->Arhs) {
729: if (ijacobian) {
730: MatDuplicate(A,MAT_DO_NOT_COPY_VALUES,&ts->Arhs);
731: TSSetMatStructure(ts,SAME_NONZERO_PATTERN);
732: } else {
733: ts->Arhs = A;
734: PetscObjectReference((PetscObject)A);
735: }
736: } else {
737: PetscBool flg;
738: SNESGetUseMatrixFree(ts->snes,NULL,&flg);
739: /* Handle case where user provided only RHSJacobian and used -snes_mf_operator */
740: if (flg && !ijacobian && ts->Arhs == ts->Brhs) {
741: PetscObjectDereference((PetscObject)ts->Arhs);
742: ts->Arhs = A;
743: PetscObjectReference((PetscObject)A);
744: }
745: }
746: *Arhs = ts->Arhs;
747: }
748: if (Brhs) {
749: if (!ts->Brhs) {
750: if (A != B) {
751: if (ijacobian) {
752: MatDuplicate(B,MAT_DO_NOT_COPY_VALUES,&ts->Brhs);
753: } else {
754: ts->Brhs = B;
755: PetscObjectReference((PetscObject)B);
756: }
757: } else {
758: PetscObjectReference((PetscObject)ts->Arhs);
759: ts->Brhs = ts->Arhs;
760: }
761: }
762: *Brhs = ts->Brhs;
763: }
764: return(0);
765: }
767: /*@
768: TSComputeIFunction - Evaluates the DAE residual written in implicit form F(t,U,Udot)=0
770: Collective on TS
772: Input Parameters:
773: + ts - the TS context
774: . t - current time
775: . U - state vector
776: . Udot - time derivative of state vector
777: - imex - flag indicates if the method is IMEX so that the RHSFunction should be kept separate
779: Output Parameter:
780: . Y - right hand side
782: Note:
783: Most users should not need to explicitly call this routine, as it
784: is used internally within the nonlinear solvers.
786: If the user did did not write their equations in implicit form, this
787: function recasts them in implicit form.
789: Level: developer
791: .seealso: TSSetIFunction(), TSComputeRHSFunction()
792: @*/
793: PetscErrorCode TSComputeIFunction(TS ts,PetscReal t,Vec U,Vec Udot,Vec Y,PetscBool imex)
794: {
796: TSIFunction ifunction;
797: TSRHSFunction rhsfunction;
798: void *ctx;
799: DM dm;
807: TSGetDM(ts,&dm);
808: DMTSGetIFunction(dm,&ifunction,&ctx);
809: DMTSGetRHSFunction(dm,&rhsfunction,NULL);
811: if (!rhsfunction && !ifunction) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSFunction() and / or TSSetIFunction()");
813: PetscLogEventBegin(TS_FunctionEval,ts,U,Udot,Y);
814: if (ifunction) {
815: PetscStackPush("TS user implicit function");
816: (*ifunction)(ts,t,U,Udot,Y,ctx);
817: PetscStackPop;
818: ts->ifuncs++;
819: }
820: if (imex) {
821: if (!ifunction) {
822: VecCopy(Udot,Y);
823: }
824: } else if (rhsfunction) {
825: if (ifunction) {
826: Vec Frhs;
827: TSGetRHSVec_Private(ts,&Frhs);
828: TSComputeRHSFunction(ts,t,U,Frhs);
829: VecAXPY(Y,-1,Frhs);
830: } else {
831: TSComputeRHSFunction(ts,t,U,Y);
832: VecAYPX(Y,-1,Udot);
833: }
834: }
835: PetscLogEventEnd(TS_FunctionEval,ts,U,Udot,Y);
836: return(0);
837: }
839: /*
840: TSRecoverRHSJacobian - Recover the Jacobian matrix so that one can call TSComputeRHSJacobian() on it.
842: Note:
843: This routine is needed when one switches from TSComputeIJacobian() to TSComputeRHSJacobian() because the Jacobian matrix may be shifted or scaled in TSComputeIJacobian().
845: */
846: static PetscErrorCode TSRecoverRHSJacobian(TS ts,Mat A,Mat B)
847: {
848: PetscErrorCode ierr;
852: if (A != ts->Arhs) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Invalid Amat");
853: if (B != ts->Brhs) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Invalid Bmat");
855: if (ts->rhsjacobian.shift) {
856: MatShift(A,-ts->rhsjacobian.shift);
857: }
858: if (ts->rhsjacobian.scale == -1.) {
859: MatScale(A,-1);
860: }
861: if (B && B == ts->Brhs && A != B) {
862: if (ts->rhsjacobian.shift) {
863: MatShift(B,-ts->rhsjacobian.shift);
864: }
865: if (ts->rhsjacobian.scale == -1.) {
866: MatScale(B,-1);
867: }
868: }
869: ts->rhsjacobian.shift = 0;
870: ts->rhsjacobian.scale = 1.;
871: return(0);
872: }
874: /*@
875: TSComputeIJacobian - Evaluates the Jacobian of the DAE
877: Collective on TS
879: Input
880: Input Parameters:
881: + ts - the TS context
882: . t - current timestep
883: . U - state vector
884: . Udot - time derivative of state vector
885: . shift - shift to apply, see note below
886: - imex - flag indicates if the method is IMEX so that the RHSJacobian should be kept separate
888: Output Parameters:
889: + A - Jacobian matrix
890: - B - matrix from which the preconditioner is constructed; often the same as A
892: Notes:
893: If F(t,U,Udot)=0 is the DAE, the required Jacobian is
895: dF/dU + shift*dF/dUdot
897: Most users should not need to explicitly call this routine, as it
898: is used internally within the nonlinear solvers.
900: Level: developer
902: .seealso: TSSetIJacobian()
903: @*/
904: PetscErrorCode TSComputeIJacobian(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat A,Mat B,PetscBool imex)
905: {
907: TSIJacobian ijacobian;
908: TSRHSJacobian rhsjacobian;
909: DM dm;
910: void *ctx;
921: TSGetDM(ts,&dm);
922: DMTSGetIJacobian(dm,&ijacobian,&ctx);
923: DMTSGetRHSJacobian(dm,&rhsjacobian,NULL);
925: if (!rhsjacobian && !ijacobian) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSJacobian() and / or TSSetIJacobian()");
927: PetscLogEventBegin(TS_JacobianEval,ts,U,A,B);
928: if (ijacobian) {
929: PetscStackPush("TS user implicit Jacobian");
930: (*ijacobian)(ts,t,U,Udot,shift,A,B,ctx);
931: ts->ijacs++;
932: PetscStackPop;
933: }
934: if (imex) {
935: if (!ijacobian) { /* system was written as Udot = G(t,U) */
936: PetscBool assembled;
937: if (rhsjacobian) {
938: Mat Arhs = NULL;
939: TSGetRHSMats_Private(ts,&Arhs,NULL);
940: if (A == Arhs) {
941: if (rhsjacobian == TSComputeRHSJacobianConstant) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Unsupported operation! cannot use TSComputeRHSJacobianConstant"); /* there is no way to reconstruct shift*M-J since J cannot be reevaluated */
942: ts->rhsjacobian.time = PETSC_MIN_REAL;
943: }
944: }
945: MatZeroEntries(A);
946: MatAssembled(A,&assembled);
947: if (!assembled) {
948: MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
949: MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
950: }
951: MatShift(A,shift);
952: if (A != B) {
953: MatZeroEntries(B);
954: MatAssembled(B,&assembled);
955: if (!assembled) {
956: MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
957: MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
958: }
959: MatShift(B,shift);
960: }
961: }
962: } else {
963: Mat Arhs = NULL,Brhs = NULL;
964: if (rhsjacobian) { /* RHSJacobian needs to be converted to part of IJacobian if exists */
965: TSGetRHSMats_Private(ts,&Arhs,&Brhs);
966: }
967: if (Arhs == A) { /* No IJacobian matrix, so we only have the RHS matrix */
968: PetscObjectState Ustate;
969: PetscObjectId Uid;
970: TSRHSFunction rhsfunction;
972: DMTSGetRHSFunction(dm,&rhsfunction,NULL);
973: PetscObjectStateGet((PetscObject)U,&Ustate);
974: PetscObjectGetId((PetscObject)U,&Uid);
975: if ((rhsjacobian == TSComputeRHSJacobianConstant || (ts->rhsjacobian.time == t && (ts->problem_type == TS_LINEAR || (ts->rhsjacobian.Xid == Uid && ts->rhsjacobian.Xstate == Ustate)) && rhsfunction != TSComputeRHSFunctionLinear)) && ts->rhsjacobian.scale == -1.) { /* No need to recompute RHSJacobian */
976: MatShift(A,shift-ts->rhsjacobian.shift); /* revert the old shift and add the new shift with a single call to MatShift */
977: if (A != B) {
978: MatShift(B,shift-ts->rhsjacobian.shift);
979: }
980: } else {
981: PetscBool flg;
983: if (ts->rhsjacobian.reuse) { /* Undo the damage */
984: /* MatScale has a short path for this case.
985: However, this code path is taken the first time TSComputeRHSJacobian is called
986: and the matrices have not been assembled yet */
987: TSRecoverRHSJacobian(ts,A,B);
988: }
989: TSComputeRHSJacobian(ts,t,U,A,B);
990: SNESGetUseMatrixFree(ts->snes,NULL,&flg);
991: /* since -snes_mf_operator uses the full SNES function it does not need to be shifted or scaled here */
992: if (!flg) {
993: MatScale(A,-1);
994: MatShift(A,shift);
995: }
996: if (A != B) {
997: MatScale(B,-1);
998: MatShift(B,shift);
999: }
1000: }
1001: ts->rhsjacobian.scale = -1;
1002: ts->rhsjacobian.shift = shift;
1003: } else if (Arhs) { /* Both IJacobian and RHSJacobian */
1004: if (!ijacobian) { /* No IJacobian provided, but we have a separate RHS matrix */
1005: MatZeroEntries(A);
1006: MatShift(A,shift);
1007: if (A != B) {
1008: MatZeroEntries(B);
1009: MatShift(B,shift);
1010: }
1011: }
1012: TSComputeRHSJacobian(ts,t,U,Arhs,Brhs);
1013: MatAXPY(A,-1,Arhs,ts->axpy_pattern);
1014: if (A != B) {
1015: MatAXPY(B,-1,Brhs,ts->axpy_pattern);
1016: }
1017: }
1018: }
1019: PetscLogEventEnd(TS_JacobianEval,ts,U,A,B);
1020: return(0);
1021: }
1023: /*@C
1024: TSSetRHSFunction - Sets the routine for evaluating the function,
1025: where U_t = G(t,u).
1027: Logically Collective on TS
1029: Input Parameters:
1030: + ts - the TS context obtained from TSCreate()
1031: . r - vector to put the computed right hand side (or NULL to have it created)
1032: . f - routine for evaluating the right-hand-side function
1033: - ctx - [optional] user-defined context for private data for the
1034: function evaluation routine (may be NULL)
1036: Calling sequence of f:
1037: $ PetscErrorCode f(TS ts,PetscReal t,Vec u,Vec F,void *ctx);
1039: + ts - timestep context
1040: . t - current timestep
1041: . u - input vector
1042: . F - function vector
1043: - ctx - [optional] user-defined function context
1045: Level: beginner
1047: Notes:
1048: You must call this function or TSSetIFunction() to define your ODE. You cannot use this function when solving a DAE.
1050: .seealso: TSSetRHSJacobian(), TSSetIJacobian(), TSSetIFunction()
1051: @*/
1052: PetscErrorCode TSSetRHSFunction(TS ts,Vec r,PetscErrorCode (*f)(TS,PetscReal,Vec,Vec,void*),void *ctx)
1053: {
1055: SNES snes;
1056: Vec ralloc = NULL;
1057: DM dm;
1063: TSGetDM(ts,&dm);
1064: DMTSSetRHSFunction(dm,f,ctx);
1065: TSGetSNES(ts,&snes);
1066: if (!r && !ts->dm && ts->vec_sol) {
1067: VecDuplicate(ts->vec_sol,&ralloc);
1068: r = ralloc;
1069: }
1070: SNESSetFunction(snes,r,SNESTSFormFunction,ts);
1071: VecDestroy(&ralloc);
1072: return(0);
1073: }
1075: /*@C
1076: TSSetSolutionFunction - Provide a function that computes the solution of the ODE or DAE
1078: Logically Collective on TS
1080: Input Parameters:
1081: + ts - the TS context obtained from TSCreate()
1082: . f - routine for evaluating the solution
1083: - ctx - [optional] user-defined context for private data for the
1084: function evaluation routine (may be NULL)
1086: Calling sequence of f:
1087: $ PetscErrorCode f(TS ts,PetscReal t,Vec u,void *ctx);
1089: + t - current timestep
1090: . u - output vector
1091: - ctx - [optional] user-defined function context
1093: Options Database:
1094: + -ts_monitor_lg_error - create a graphical monitor of error history, requires user to have provided TSSetSolutionFunction()
1095: - -ts_monitor_draw_error - Monitor error graphically, requires user to have provided TSSetSolutionFunction()
1097: Notes:
1098: This routine is used for testing accuracy of time integration schemes when you already know the solution.
1099: If analytic solutions are not known for your system, consider using the Method of Manufactured Solutions to
1100: create closed-form solutions with non-physical forcing terms.
1102: For low-dimensional problems solved in serial, such as small discrete systems, TSMonitorLGError() can be used to monitor the error history.
1104: Level: beginner
1106: .seealso: TSSetRHSJacobian(), TSSetIJacobian(), TSComputeSolutionFunction(), TSSetForcingFunction(), TSSetSolution(), TSGetSolution(), TSMonitorLGError(), TSMonitorDrawError()
1107: @*/
1108: PetscErrorCode TSSetSolutionFunction(TS ts,PetscErrorCode (*f)(TS,PetscReal,Vec,void*),void *ctx)
1109: {
1111: DM dm;
1115: TSGetDM(ts,&dm);
1116: DMTSSetSolutionFunction(dm,f,ctx);
1117: return(0);
1118: }
1120: /*@C
1121: TSSetForcingFunction - Provide a function that computes a forcing term for a ODE or PDE
1123: Logically Collective on TS
1125: Input Parameters:
1126: + ts - the TS context obtained from TSCreate()
1127: . func - routine for evaluating the forcing function
1128: - ctx - [optional] user-defined context for private data for the
1129: function evaluation routine (may be NULL)
1131: Calling sequence of func:
1132: $ PetscErrorCode func (TS ts,PetscReal t,Vec f,void *ctx);
1134: + t - current timestep
1135: . f - output vector
1136: - ctx - [optional] user-defined function context
1138: Notes:
1139: This routine is useful for testing accuracy of time integration schemes when using the Method of Manufactured Solutions to
1140: create closed-form solutions with a non-physical forcing term. It allows you to use the Method of Manufactored Solution without directly editing the
1141: definition of the problem you are solving and hence possibly introducing bugs.
1143: This replaces the ODE F(u,u_t,t) = 0 the TS is solving with F(u,u_t,t) - func(t) = 0
1145: This forcing function does not depend on the solution to the equations, it can only depend on spatial location, time, and possibly parameters, the
1146: parameters can be passed in the ctx variable.
1148: For low-dimensional problems solved in serial, such as small discrete systems, TSMonitorLGError() can be used to monitor the error history.
1150: Level: beginner
1152: .seealso: TSSetRHSJacobian(), TSSetIJacobian(), TSComputeSolutionFunction(), TSSetSolutionFunction()
1153: @*/
1154: PetscErrorCode TSSetForcingFunction(TS ts,TSForcingFunction func,void *ctx)
1155: {
1157: DM dm;
1161: TSGetDM(ts,&dm);
1162: DMTSSetForcingFunction(dm,func,ctx);
1163: return(0);
1164: }
1166: /*@C
1167: TSSetRHSJacobian - Sets the function to compute the Jacobian of G,
1168: where U_t = G(U,t), as well as the location to store the matrix.
1170: Logically Collective on TS
1172: Input Parameters:
1173: + ts - the TS context obtained from TSCreate()
1174: . Amat - (approximate) Jacobian matrix
1175: . Pmat - matrix from which preconditioner is to be constructed (usually the same as Amat)
1176: . f - the Jacobian evaluation routine
1177: - ctx - [optional] user-defined context for private data for the
1178: Jacobian evaluation routine (may be NULL)
1180: Calling sequence of f:
1181: $ PetscErrorCode f(TS ts,PetscReal t,Vec u,Mat A,Mat B,void *ctx);
1183: + t - current timestep
1184: . u - input vector
1185: . Amat - (approximate) Jacobian matrix
1186: . Pmat - matrix from which preconditioner is to be constructed (usually the same as Amat)
1187: - ctx - [optional] user-defined context for matrix evaluation routine
1189: Notes:
1190: You must set all the diagonal entries of the matrices, if they are zero you must still set them with a zero value
1192: The TS solver may modify the nonzero structure and the entries of the matrices Amat and Pmat between the calls to f()
1193: You should not assume the values are the same in the next call to f() as you set them in the previous call.
1195: Level: beginner
1197: .seealso: SNESComputeJacobianDefaultColor(), TSSetRHSFunction(), TSRHSJacobianSetReuse(), TSSetIJacobian()
1199: @*/
1200: PetscErrorCode TSSetRHSJacobian(TS ts,Mat Amat,Mat Pmat,TSRHSJacobian f,void *ctx)
1201: {
1203: SNES snes;
1204: DM dm;
1205: TSIJacobian ijacobian;
1214: TSGetDM(ts,&dm);
1215: DMTSSetRHSJacobian(dm,f,ctx);
1216: DMTSGetIJacobian(dm,&ijacobian,NULL);
1217: TSGetSNES(ts,&snes);
1218: if (!ijacobian) {
1219: SNESSetJacobian(snes,Amat,Pmat,SNESTSFormJacobian,ts);
1220: }
1221: if (Amat) {
1222: PetscObjectReference((PetscObject)Amat);
1223: MatDestroy(&ts->Arhs);
1224: ts->Arhs = Amat;
1225: }
1226: if (Pmat) {
1227: PetscObjectReference((PetscObject)Pmat);
1228: MatDestroy(&ts->Brhs);
1229: ts->Brhs = Pmat;
1230: }
1231: return(0);
1232: }
1234: /*@C
1235: TSSetIFunction - Set the function to compute F(t,U,U_t) where F() = 0 is the DAE to be solved.
1237: Logically Collective on TS
1239: Input Parameters:
1240: + ts - the TS context obtained from TSCreate()
1241: . r - vector to hold the residual (or NULL to have it created internally)
1242: . f - the function evaluation routine
1243: - ctx - user-defined context for private data for the function evaluation routine (may be NULL)
1245: Calling sequence of f:
1246: $ PetscErrorCode f(TS ts,PetscReal t,Vec u,Vec u_t,Vec F,ctx);
1248: + t - time at step/stage being solved
1249: . u - state vector
1250: . u_t - time derivative of state vector
1251: . F - function vector
1252: - ctx - [optional] user-defined context for matrix evaluation routine
1254: Important:
1255: The user MUST call either this routine or TSSetRHSFunction() to define the ODE. When solving DAEs you must use this function.
1257: Level: beginner
1259: .seealso: TSSetRHSJacobian(), TSSetRHSFunction(), TSSetIJacobian()
1260: @*/
1261: PetscErrorCode TSSetIFunction(TS ts,Vec r,TSIFunction f,void *ctx)
1262: {
1264: SNES snes;
1265: Vec ralloc = NULL;
1266: DM dm;
1272: TSGetDM(ts,&dm);
1273: DMTSSetIFunction(dm,f,ctx);
1275: TSGetSNES(ts,&snes);
1276: if (!r && !ts->dm && ts->vec_sol) {
1277: VecDuplicate(ts->vec_sol,&ralloc);
1278: r = ralloc;
1279: }
1280: SNESSetFunction(snes,r,SNESTSFormFunction,ts);
1281: VecDestroy(&ralloc);
1282: return(0);
1283: }
1285: /*@C
1286: TSGetIFunction - Returns the vector where the implicit residual is stored and the function/context to compute it.
1288: Not Collective
1290: Input Parameter:
1291: . ts - the TS context
1293: Output Parameters:
1294: + r - vector to hold residual (or NULL)
1295: . func - the function to compute residual (or NULL)
1296: - ctx - the function context (or NULL)
1298: Level: advanced
1300: .seealso: TSSetIFunction(), SNESGetFunction()
1301: @*/
1302: PetscErrorCode TSGetIFunction(TS ts,Vec *r,TSIFunction *func,void **ctx)
1303: {
1305: SNES snes;
1306: DM dm;
1310: TSGetSNES(ts,&snes);
1311: SNESGetFunction(snes,r,NULL,NULL);
1312: TSGetDM(ts,&dm);
1313: DMTSGetIFunction(dm,func,ctx);
1314: return(0);
1315: }
1317: /*@C
1318: TSGetRHSFunction - Returns the vector where the right hand side is stored and the function/context to compute it.
1320: Not Collective
1322: Input Parameter:
1323: . ts - the TS context
1325: Output Parameters:
1326: + r - vector to hold computed right hand side (or NULL)
1327: . func - the function to compute right hand side (or NULL)
1328: - ctx - the function context (or NULL)
1330: Level: advanced
1332: .seealso: TSSetRHSFunction(), SNESGetFunction()
1333: @*/
1334: PetscErrorCode TSGetRHSFunction(TS ts,Vec *r,TSRHSFunction *func,void **ctx)
1335: {
1337: SNES snes;
1338: DM dm;
1342: TSGetSNES(ts,&snes);
1343: SNESGetFunction(snes,r,NULL,NULL);
1344: TSGetDM(ts,&dm);
1345: DMTSGetRHSFunction(dm,func,ctx);
1346: return(0);
1347: }
1349: /*@C
1350: TSSetIJacobian - Set the function to compute the matrix dF/dU + a*dF/dU_t where F(t,U,U_t) is the function
1351: provided with TSSetIFunction().
1353: Logically Collective on TS
1355: Input Parameters:
1356: + ts - the TS context obtained from TSCreate()
1357: . Amat - (approximate) Jacobian matrix
1358: . Pmat - matrix used to compute preconditioner (usually the same as Amat)
1359: . f - the Jacobian evaluation routine
1360: - ctx - user-defined context for private data for the Jacobian evaluation routine (may be NULL)
1362: Calling sequence of f:
1363: $ PetscErrorCode f(TS ts,PetscReal t,Vec U,Vec U_t,PetscReal a,Mat Amat,Mat Pmat,void *ctx);
1365: + t - time at step/stage being solved
1366: . U - state vector
1367: . U_t - time derivative of state vector
1368: . a - shift
1369: . Amat - (approximate) Jacobian of F(t,U,W+a*U), equivalent to dF/dU + a*dF/dU_t
1370: . Pmat - matrix used for constructing preconditioner, usually the same as Amat
1371: - ctx - [optional] user-defined context for matrix evaluation routine
1373: Notes:
1374: The matrices Amat and Pmat are exactly the matrices that are used by SNES for the nonlinear solve.
1376: If you know the operator Amat has a null space you can use MatSetNullSpace() and MatSetTransposeNullSpace() to supply the null
1377: space to Amat and the KSP solvers will automatically use that null space as needed during the solution process.
1379: The matrix dF/dU + a*dF/dU_t you provide turns out to be
1380: the Jacobian of F(t,U,W+a*U) where F(t,U,U_t) = 0 is the DAE to be solved.
1381: The time integrator internally approximates U_t by W+a*U where the positive "shift"
1382: a and vector W depend on the integration method, step size, and past states. For example with
1383: the backward Euler method a = 1/dt and W = -a*U(previous timestep) so
1384: W + a*U = a*(U - U(previous timestep)) = (U - U(previous timestep))/dt
1386: You must set all the diagonal entries of the matrices, if they are zero you must still set them with a zero value
1388: The TS solver may modify the nonzero structure and the entries of the matrices Amat and Pmat between the calls to f()
1389: You should not assume the values are the same in the next call to f() as you set them in the previous call.
1391: Level: beginner
1393: .seealso: TSSetIFunction(), TSSetRHSJacobian(), SNESComputeJacobianDefaultColor(), SNESComputeJacobianDefault(), TSSetRHSFunction()
1395: @*/
1396: PetscErrorCode TSSetIJacobian(TS ts,Mat Amat,Mat Pmat,TSIJacobian f,void *ctx)
1397: {
1399: SNES snes;
1400: DM dm;
1409: TSGetDM(ts,&dm);
1410: DMTSSetIJacobian(dm,f,ctx);
1412: TSGetSNES(ts,&snes);
1413: SNESSetJacobian(snes,Amat,Pmat,SNESTSFormJacobian,ts);
1414: return(0);
1415: }
1417: /*@
1418: TSRHSJacobianSetReuse - restore RHS Jacobian before re-evaluating. Without this flag, TS will change the sign and
1419: shift the RHS Jacobian for a finite-time-step implicit solve, in which case the user function will need to recompute
1420: the entire Jacobian. The reuse flag must be set if the evaluation function will assume that the matrix entries have
1421: not been changed by the TS.
1423: Logically Collective
1425: Input Parameters:
1426: + ts - TS context obtained from TSCreate()
1427: - reuse - PETSC_TRUE if the RHS Jacobian
1429: Level: intermediate
1431: .seealso: TSSetRHSJacobian(), TSComputeRHSJacobianConstant()
1432: @*/
1433: PetscErrorCode TSRHSJacobianSetReuse(TS ts,PetscBool reuse)
1434: {
1436: ts->rhsjacobian.reuse = reuse;
1437: return(0);
1438: }
1440: /*@C
1441: TSSetI2Function - Set the function to compute F(t,U,U_t,U_tt) where F = 0 is the DAE to be solved.
1443: Logically Collective on TS
1445: Input Parameters:
1446: + ts - the TS context obtained from TSCreate()
1447: . F - vector to hold the residual (or NULL to have it created internally)
1448: . fun - the function evaluation routine
1449: - ctx - user-defined context for private data for the function evaluation routine (may be NULL)
1451: Calling sequence of fun:
1452: $ PetscErrorCode fun(TS ts,PetscReal t,Vec U,Vec U_t,Vec U_tt,Vec F,ctx);
1454: + t - time at step/stage being solved
1455: . U - state vector
1456: . U_t - time derivative of state vector
1457: . U_tt - second time derivative of state vector
1458: . F - function vector
1459: - ctx - [optional] user-defined context for matrix evaluation routine (may be NULL)
1461: Level: beginner
1463: .seealso: TSSetI2Jacobian(), TSSetIFunction(), TSCreate(), TSSetRHSFunction()
1464: @*/
1465: PetscErrorCode TSSetI2Function(TS ts,Vec F,TSI2Function fun,void *ctx)
1466: {
1467: DM dm;
1473: TSSetIFunction(ts,F,NULL,NULL);
1474: TSGetDM(ts,&dm);
1475: DMTSSetI2Function(dm,fun,ctx);
1476: return(0);
1477: }
1479: /*@C
1480: TSGetI2Function - Returns the vector where the implicit residual is stored and the function/context to compute it.
1482: Not Collective
1484: Input Parameter:
1485: . ts - the TS context
1487: Output Parameters:
1488: + r - vector to hold residual (or NULL)
1489: . fun - the function to compute residual (or NULL)
1490: - ctx - the function context (or NULL)
1492: Level: advanced
1494: .seealso: TSSetIFunction(), SNESGetFunction(), TSCreate()
1495: @*/
1496: PetscErrorCode TSGetI2Function(TS ts,Vec *r,TSI2Function *fun,void **ctx)
1497: {
1499: SNES snes;
1500: DM dm;
1504: TSGetSNES(ts,&snes);
1505: SNESGetFunction(snes,r,NULL,NULL);
1506: TSGetDM(ts,&dm);
1507: DMTSGetI2Function(dm,fun,ctx);
1508: return(0);
1509: }
1511: /*@C
1512: TSSetI2Jacobian - Set the function to compute the matrix dF/dU + v*dF/dU_t + a*dF/dU_tt
1513: where F(t,U,U_t,U_tt) is the function you provided with TSSetI2Function().
1515: Logically Collective on TS
1517: Input Parameters:
1518: + ts - the TS context obtained from TSCreate()
1519: . J - Jacobian matrix
1520: . P - preconditioning matrix for J (may be same as J)
1521: . jac - the Jacobian evaluation routine
1522: - ctx - user-defined context for private data for the Jacobian evaluation routine (may be NULL)
1524: Calling sequence of jac:
1525: $ PetscErrorCode jac(TS ts,PetscReal t,Vec U,Vec U_t,Vec U_tt,PetscReal v,PetscReal a,Mat J,Mat P,void *ctx);
1527: + t - time at step/stage being solved
1528: . U - state vector
1529: . U_t - time derivative of state vector
1530: . U_tt - second time derivative of state vector
1531: . v - shift for U_t
1532: . a - shift for U_tt
1533: . J - Jacobian of G(U) = F(t,U,W+v*U,W'+a*U), equivalent to dF/dU + v*dF/dU_t + a*dF/dU_tt
1534: . P - preconditioning matrix for J, may be same as J
1535: - ctx - [optional] user-defined context for matrix evaluation routine
1537: Notes:
1538: The matrices J and P are exactly the matrices that are used by SNES for the nonlinear solve.
1540: The matrix dF/dU + v*dF/dU_t + a*dF/dU_tt you provide turns out to be
1541: the Jacobian of G(U) = F(t,U,W+v*U,W'+a*U) where F(t,U,U_t,U_tt) = 0 is the DAE to be solved.
1542: The time integrator internally approximates U_t by W+v*U and U_tt by W'+a*U where the positive "shift"
1543: parameters 'v' and 'a' and vectors W, W' depend on the integration method, step size, and past states.
1545: Level: beginner
1547: .seealso: TSSetI2Function(), TSGetI2Jacobian()
1548: @*/
1549: PetscErrorCode TSSetI2Jacobian(TS ts,Mat J,Mat P,TSI2Jacobian jac,void *ctx)
1550: {
1551: DM dm;
1558: TSSetIJacobian(ts,J,P,NULL,NULL);
1559: TSGetDM(ts,&dm);
1560: DMTSSetI2Jacobian(dm,jac,ctx);
1561: return(0);
1562: }
1564: /*@C
1565: TSGetI2Jacobian - Returns the implicit Jacobian at the present timestep.
1567: Not Collective, but parallel objects are returned if TS is parallel
1569: Input Parameter:
1570: . ts - The TS context obtained from TSCreate()
1572: Output Parameters:
1573: + J - The (approximate) Jacobian of F(t,U,U_t,U_tt)
1574: . P - The matrix from which the preconditioner is constructed, often the same as J
1575: . jac - The function to compute the Jacobian matrices
1576: - ctx - User-defined context for Jacobian evaluation routine
1578: Notes:
1579: You can pass in NULL for any return argument you do not need.
1581: Level: advanced
1583: .seealso: TSGetTimeStep(), TSGetMatrices(), TSGetTime(), TSGetStepNumber(), TSSetI2Jacobian(), TSGetI2Function(), TSCreate()
1585: @*/
1586: PetscErrorCode TSGetI2Jacobian(TS ts,Mat *J,Mat *P,TSI2Jacobian *jac,void **ctx)
1587: {
1589: SNES snes;
1590: DM dm;
1593: TSGetSNES(ts,&snes);
1594: SNESSetUpMatrices(snes);
1595: SNESGetJacobian(snes,J,P,NULL,NULL);
1596: TSGetDM(ts,&dm);
1597: DMTSGetI2Jacobian(dm,jac,ctx);
1598: return(0);
1599: }
1601: /*@
1602: TSComputeI2Function - Evaluates the DAE residual written in implicit form F(t,U,U_t,U_tt) = 0
1604: Collective on TS
1606: Input Parameters:
1607: + ts - the TS context
1608: . t - current time
1609: . U - state vector
1610: . V - time derivative of state vector (U_t)
1611: - A - second time derivative of state vector (U_tt)
1613: Output Parameter:
1614: . F - the residual vector
1616: Note:
1617: Most users should not need to explicitly call this routine, as it
1618: is used internally within the nonlinear solvers.
1620: Level: developer
1622: .seealso: TSSetI2Function(), TSGetI2Function()
1623: @*/
1624: PetscErrorCode TSComputeI2Function(TS ts,PetscReal t,Vec U,Vec V,Vec A,Vec F)
1625: {
1626: DM dm;
1627: TSI2Function I2Function;
1628: void *ctx;
1629: TSRHSFunction rhsfunction;
1639: TSGetDM(ts,&dm);
1640: DMTSGetI2Function(dm,&I2Function,&ctx);
1641: DMTSGetRHSFunction(dm,&rhsfunction,NULL);
1643: if (!I2Function) {
1644: TSComputeIFunction(ts,t,U,A,F,PETSC_FALSE);
1645: return(0);
1646: }
1648: PetscLogEventBegin(TS_FunctionEval,ts,U,V,F);
1650: PetscStackPush("TS user implicit function");
1651: I2Function(ts,t,U,V,A,F,ctx);
1652: PetscStackPop;
1654: if (rhsfunction) {
1655: Vec Frhs;
1656: TSGetRHSVec_Private(ts,&Frhs);
1657: TSComputeRHSFunction(ts,t,U,Frhs);
1658: VecAXPY(F,-1,Frhs);
1659: }
1661: PetscLogEventEnd(TS_FunctionEval,ts,U,V,F);
1662: return(0);
1663: }
1665: /*@
1666: TSComputeI2Jacobian - Evaluates the Jacobian of the DAE
1668: Collective on TS
1670: Input Parameters:
1671: + ts - the TS context
1672: . t - current timestep
1673: . U - state vector
1674: . V - time derivative of state vector
1675: . A - second time derivative of state vector
1676: . shiftV - shift to apply, see note below
1677: - shiftA - shift to apply, see note below
1679: Output Parameters:
1680: + J - Jacobian matrix
1681: - P - optional preconditioning matrix
1683: Notes:
1684: If F(t,U,V,A)=0 is the DAE, the required Jacobian is
1686: dF/dU + shiftV*dF/dV + shiftA*dF/dA
1688: Most users should not need to explicitly call this routine, as it
1689: is used internally within the nonlinear solvers.
1691: Level: developer
1693: .seealso: TSSetI2Jacobian()
1694: @*/
1695: PetscErrorCode TSComputeI2Jacobian(TS ts,PetscReal t,Vec U,Vec V,Vec A,PetscReal shiftV,PetscReal shiftA,Mat J,Mat P)
1696: {
1697: DM dm;
1698: TSI2Jacobian I2Jacobian;
1699: void *ctx;
1700: TSRHSJacobian rhsjacobian;
1711: TSGetDM(ts,&dm);
1712: DMTSGetI2Jacobian(dm,&I2Jacobian,&ctx);
1713: DMTSGetRHSJacobian(dm,&rhsjacobian,NULL);
1715: if (!I2Jacobian) {
1716: TSComputeIJacobian(ts,t,U,A,shiftA,J,P,PETSC_FALSE);
1717: return(0);
1718: }
1720: PetscLogEventBegin(TS_JacobianEval,ts,U,J,P);
1722: PetscStackPush("TS user implicit Jacobian");
1723: I2Jacobian(ts,t,U,V,A,shiftV,shiftA,J,P,ctx);
1724: PetscStackPop;
1726: if (rhsjacobian) {
1727: Mat Jrhs,Prhs;
1728: TSGetRHSMats_Private(ts,&Jrhs,&Prhs);
1729: TSComputeRHSJacobian(ts,t,U,Jrhs,Prhs);
1730: MatAXPY(J,-1,Jrhs,ts->axpy_pattern);
1731: if (P != J) {MatAXPY(P,-1,Prhs,ts->axpy_pattern);}
1732: }
1734: PetscLogEventEnd(TS_JacobianEval,ts,U,J,P);
1735: return(0);
1736: }
1738: /*@C
1739: TSSetTransientVariable - sets function to transform from state to transient variables
1741: Logically Collective
1743: Input Parameters:
1744: + ts - time stepping context on which to change the transient variable
1745: . tvar - a function that transforms to transient variables
1746: - ctx - a context for tvar
1748: Calling sequence of tvar:
1749: $ PetscErrorCode tvar(TS ts,Vec p,Vec c,void *ctx);
1751: + ts - timestep context
1752: . p - input vector (primative form)
1753: . c - output vector, transient variables (conservative form)
1754: - ctx - [optional] user-defined function context
1756: Level: advanced
1758: Notes:
1759: This is typically used to transform from primitive to conservative variables so that a time integrator (e.g., TSBDF)
1760: can be conservative. In this context, primitive variables P are used to model the state (e.g., because they lead to
1761: well-conditioned formulations even in limiting cases such as low-Mach or zero porosity). The transient variable is
1762: C(P), specified by calling this function. An IFunction thus receives arguments (P, Cdot) and the IJacobian must be
1763: evaluated via the chain rule, as in
1765: dF/dP + shift * dF/dCdot dC/dP.
1767: .seealso: DMTSSetTransientVariable(), DMTSGetTransientVariable(), TSSetIFunction(), TSSetIJacobian()
1768: @*/
1769: PetscErrorCode TSSetTransientVariable(TS ts,TSTransientVariable tvar,void *ctx)
1770: {
1772: DM dm;
1776: TSGetDM(ts,&dm);
1777: DMTSSetTransientVariable(dm,tvar,ctx);
1778: return(0);
1779: }
1781: /*@
1782: TSComputeTransientVariable - transforms state (primitive) variables to transient (conservative) variables
1784: Logically Collective
1786: Input Parameters:
1787: + ts - TS on which to compute
1788: - U - state vector to be transformed to transient variables
1790: Output Parameters:
1791: . C - transient (conservative) variable
1793: Developer Notes:
1794: If DMTSSetTransientVariable() has not been called, then C is not modified in this routine and C=NULL is allowed.
1795: This makes it safe to call without a guard. One can use TSHasTransientVariable() to check if transient variables are
1796: being used.
1798: Level: developer
1800: .seealso: DMTSSetTransientVariable(), TSComputeIFunction(), TSComputeIJacobian()
1801: @*/
1802: PetscErrorCode TSComputeTransientVariable(TS ts,Vec U,Vec C)
1803: {
1805: DM dm;
1806: DMTS dmts;
1811: TSGetDM(ts,&dm);
1812: DMGetDMTS(dm,&dmts);
1813: if (dmts->ops->transientvar) {
1815: (*dmts->ops->transientvar)(ts,U,C,dmts->transientvarctx);
1816: }
1817: return(0);
1818: }
1820: /*@
1821: TSHasTransientVariable - determine whether transient variables have been set
1823: Logically Collective
1825: Input Parameters:
1826: . ts - TS on which to compute
1828: Output Parameters:
1829: . has - PETSC_TRUE if transient variables have been set
1831: Level: developer
1833: .seealso: DMTSSetTransientVariable(), TSComputeTransientVariable()
1834: @*/
1835: PetscErrorCode TSHasTransientVariable(TS ts,PetscBool *has)
1836: {
1838: DM dm;
1839: DMTS dmts;
1843: TSGetDM(ts,&dm);
1844: DMGetDMTS(dm,&dmts);
1845: *has = dmts->ops->transientvar ? PETSC_TRUE : PETSC_FALSE;
1846: return(0);
1847: }
1849: /*@
1850: TS2SetSolution - Sets the initial solution and time derivative vectors
1851: for use by the TS routines handling second order equations.
1853: Logically Collective on TS
1855: Input Parameters:
1856: + ts - the TS context obtained from TSCreate()
1857: . u - the solution vector
1858: - v - the time derivative vector
1860: Level: beginner
1862: @*/
1863: PetscErrorCode TS2SetSolution(TS ts,Vec u,Vec v)
1864: {
1871: TSSetSolution(ts,u);
1872: PetscObjectReference((PetscObject)v);
1873: VecDestroy(&ts->vec_dot);
1874: ts->vec_dot = v;
1875: return(0);
1876: }
1878: /*@
1879: TS2GetSolution - Returns the solution and time derivative at the present timestep
1880: for second order equations. It is valid to call this routine inside the function
1881: that you are evaluating in order to move to the new timestep. This vector not
1882: changed until the solution at the next timestep has been calculated.
1884: Not Collective, but Vec returned is parallel if TS is parallel
1886: Input Parameter:
1887: . ts - the TS context obtained from TSCreate()
1889: Output Parameters:
1890: + u - the vector containing the solution
1891: - v - the vector containing the time derivative
1893: Level: intermediate
1895: .seealso: TS2SetSolution(), TSGetTimeStep(), TSGetTime()
1897: @*/
1898: PetscErrorCode TS2GetSolution(TS ts,Vec *u,Vec *v)
1899: {
1904: if (u) *u = ts->vec_sol;
1905: if (v) *v = ts->vec_dot;
1906: return(0);
1907: }
1909: /*@C
1910: TSLoad - Loads a KSP that has been stored in binary with KSPView().
1912: Collective on PetscViewer
1914: Input Parameters:
1915: + newdm - the newly loaded TS, this needs to have been created with TSCreate() or
1916: some related function before a call to TSLoad().
1917: - viewer - binary file viewer, obtained from PetscViewerBinaryOpen()
1919: Level: intermediate
1921: Notes:
1922: The type is determined by the data in the file, any type set into the TS before this call is ignored.
1924: Notes for advanced users:
1925: Most users should not need to know the details of the binary storage
1926: format, since TSLoad() and TSView() completely hide these details.
1927: But for anyone who's interested, the standard binary matrix storage
1928: format is
1929: .vb
1930: has not yet been determined
1931: .ve
1933: .seealso: PetscViewerBinaryOpen(), TSView(), MatLoad(), VecLoad()
1934: @*/
1935: PetscErrorCode TSLoad(TS ts, PetscViewer viewer)
1936: {
1938: PetscBool isbinary;
1939: PetscInt classid;
1940: char type[256];
1941: DMTS sdm;
1942: DM dm;
1947: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1948: if (!isbinary) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid viewer; open viewer with PetscViewerBinaryOpen()");
1950: PetscViewerBinaryRead(viewer,&classid,1,NULL,PETSC_INT);
1951: if (classid != TS_FILE_CLASSID) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Not TS next in file");
1952: PetscViewerBinaryRead(viewer,type,256,NULL,PETSC_CHAR);
1953: TSSetType(ts, type);
1954: if (ts->ops->load) {
1955: (*ts->ops->load)(ts,viewer);
1956: }
1957: DMCreate(PetscObjectComm((PetscObject)ts),&dm);
1958: DMLoad(dm,viewer);
1959: TSSetDM(ts,dm);
1960: DMCreateGlobalVector(ts->dm,&ts->vec_sol);
1961: VecLoad(ts->vec_sol,viewer);
1962: DMGetDMTS(ts->dm,&sdm);
1963: DMTSLoad(sdm,viewer);
1964: return(0);
1965: }
1967: #include <petscdraw.h>
1968: #if defined(PETSC_HAVE_SAWS)
1969: #include <petscviewersaws.h>
1970: #endif
1972: /*@C
1973: TSViewFromOptions - View from Options
1975: Collective on TS
1977: Input Parameters:
1978: + A - the application ordering context
1979: . obj - Optional object
1980: - name - command line option
1982: Level: intermediate
1983: .seealso: TS, TSView, PetscObjectViewFromOptions(), TSCreate()
1984: @*/
1985: PetscErrorCode TSViewFromOptions(TS A,PetscObject obj,const char name[])
1986: {
1991: PetscObjectViewFromOptions((PetscObject)A,obj,name);
1992: return(0);
1993: }
1995: /*@C
1996: TSView - Prints the TS data structure.
1998: Collective on TS
2000: Input Parameters:
2001: + ts - the TS context obtained from TSCreate()
2002: - viewer - visualization context
2004: Options Database Key:
2005: . -ts_view - calls TSView() at end of TSStep()
2007: Notes:
2008: The available visualization contexts include
2009: + PETSC_VIEWER_STDOUT_SELF - standard output (default)
2010: - PETSC_VIEWER_STDOUT_WORLD - synchronized standard
2011: output where only the first processor opens
2012: the file. All other processors send their
2013: data to the first processor to print.
2015: The user can open an alternative visualization context with
2016: PetscViewerASCIIOpen() - output to a specified file.
2018: In the debugger you can do "call TSView(ts,0)" to display the TS solver. (The same holds for any PETSc object viewer).
2020: Level: beginner
2022: .seealso: PetscViewerASCIIOpen()
2023: @*/
2024: PetscErrorCode TSView(TS ts,PetscViewer viewer)
2025: {
2027: TSType type;
2028: PetscBool iascii,isstring,isundials,isbinary,isdraw;
2029: DMTS sdm;
2030: #if defined(PETSC_HAVE_SAWS)
2031: PetscBool issaws;
2032: #endif
2036: if (!viewer) {
2037: PetscViewerASCIIGetStdout(PetscObjectComm((PetscObject)ts),&viewer);
2038: }
2042: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
2043: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSTRING,&isstring);
2044: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
2045: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
2046: #if defined(PETSC_HAVE_SAWS)
2047: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSAWS,&issaws);
2048: #endif
2049: if (iascii) {
2050: PetscObjectPrintClassNamePrefixType((PetscObject)ts,viewer);
2051: if (ts->ops->view) {
2052: PetscViewerASCIIPushTab(viewer);
2053: (*ts->ops->view)(ts,viewer);
2054: PetscViewerASCIIPopTab(viewer);
2055: }
2056: if (ts->max_steps < PETSC_MAX_INT) {
2057: PetscViewerASCIIPrintf(viewer," maximum steps=%D\n",ts->max_steps);
2058: }
2059: if (ts->max_time < PETSC_MAX_REAL) {
2060: PetscViewerASCIIPrintf(viewer," maximum time=%g\n",(double)ts->max_time);
2061: }
2062: if (ts->ifuncs) {
2063: PetscViewerASCIIPrintf(viewer," total number of I function evaluations=%D\n",ts->ifuncs);
2064: }
2065: if (ts->ijacs) {
2066: PetscViewerASCIIPrintf(viewer," total number of I Jacobian evaluations=%D\n",ts->ijacs);
2067: }
2068: if (ts->rhsfuncs) {
2069: PetscViewerASCIIPrintf(viewer," total number of RHS function evaluations=%D\n",ts->rhsfuncs);
2070: }
2071: if (ts->rhsjacs) {
2072: PetscViewerASCIIPrintf(viewer," total number of RHS Jacobian evaluations=%D\n",ts->rhsjacs);
2073: }
2074: if (ts->usessnes) {
2075: PetscBool lin;
2076: if (ts->problem_type == TS_NONLINEAR) {
2077: PetscViewerASCIIPrintf(viewer," total number of nonlinear solver iterations=%D\n",ts->snes_its);
2078: }
2079: PetscViewerASCIIPrintf(viewer," total number of linear solver iterations=%D\n",ts->ksp_its);
2080: PetscObjectTypeCompareAny((PetscObject)ts->snes,&lin,SNESKSPONLY,SNESKSPTRANSPOSEONLY,"");
2081: PetscViewerASCIIPrintf(viewer," total number of %slinear solve failures=%D\n",lin ? "" : "non",ts->num_snes_failures);
2082: }
2083: PetscViewerASCIIPrintf(viewer," total number of rejected steps=%D\n",ts->reject);
2084: if (ts->vrtol) {
2085: PetscViewerASCIIPrintf(viewer," using vector of relative error tolerances, ");
2086: } else {
2087: PetscViewerASCIIPrintf(viewer," using relative error tolerance of %g, ",(double)ts->rtol);
2088: }
2089: if (ts->vatol) {
2090: PetscViewerASCIIPrintf(viewer," using vector of absolute error tolerances\n");
2091: } else {
2092: PetscViewerASCIIPrintf(viewer," using absolute error tolerance of %g\n",(double)ts->atol);
2093: }
2094: PetscViewerASCIIPushTab(viewer);
2095: TSAdaptView(ts->adapt,viewer);
2096: PetscViewerASCIIPopTab(viewer);
2097: } else if (isstring) {
2098: TSGetType(ts,&type);
2099: PetscViewerStringSPrintf(viewer," TSType: %-7.7s",type);
2100: if (ts->ops->view) {(*ts->ops->view)(ts,viewer);}
2101: } else if (isbinary) {
2102: PetscInt classid = TS_FILE_CLASSID;
2103: MPI_Comm comm;
2104: PetscMPIInt rank;
2105: char type[256];
2107: PetscObjectGetComm((PetscObject)ts,&comm);
2108: MPI_Comm_rank(comm,&rank);
2109: if (rank == 0) {
2110: PetscViewerBinaryWrite(viewer,&classid,1,PETSC_INT);
2111: PetscStrncpy(type,((PetscObject)ts)->type_name,256);
2112: PetscViewerBinaryWrite(viewer,type,256,PETSC_CHAR);
2113: }
2114: if (ts->ops->view) {
2115: (*ts->ops->view)(ts,viewer);
2116: }
2117: if (ts->adapt) {TSAdaptView(ts->adapt,viewer);}
2118: DMView(ts->dm,viewer);
2119: VecView(ts->vec_sol,viewer);
2120: DMGetDMTS(ts->dm,&sdm);
2121: DMTSView(sdm,viewer);
2122: } else if (isdraw) {
2123: PetscDraw draw;
2124: char str[36];
2125: PetscReal x,y,bottom,h;
2127: PetscViewerDrawGetDraw(viewer,0,&draw);
2128: PetscDrawGetCurrentPoint(draw,&x,&y);
2129: PetscStrcpy(str,"TS: ");
2130: PetscStrcat(str,((PetscObject)ts)->type_name);
2131: PetscDrawStringBoxed(draw,x,y,PETSC_DRAW_BLACK,PETSC_DRAW_BLACK,str,NULL,&h);
2132: bottom = y - h;
2133: PetscDrawPushCurrentPoint(draw,x,bottom);
2134: if (ts->ops->view) {
2135: (*ts->ops->view)(ts,viewer);
2136: }
2137: if (ts->adapt) {TSAdaptView(ts->adapt,viewer);}
2138: if (ts->snes) {SNESView(ts->snes,viewer);}
2139: PetscDrawPopCurrentPoint(draw);
2140: #if defined(PETSC_HAVE_SAWS)
2141: } else if (issaws) {
2142: PetscMPIInt rank;
2143: const char *name;
2145: PetscObjectGetName((PetscObject)ts,&name);
2146: MPI_Comm_rank(PETSC_COMM_WORLD,&rank);
2147: if (!((PetscObject)ts)->amsmem && rank == 0) {
2148: char dir[1024];
2150: PetscObjectViewSAWs((PetscObject)ts,viewer);
2151: PetscSNPrintf(dir,1024,"/PETSc/Objects/%s/time_step",name);
2152: PetscStackCallSAWs(SAWs_Register,(dir,&ts->steps,1,SAWs_READ,SAWs_INT));
2153: PetscSNPrintf(dir,1024,"/PETSc/Objects/%s/time",name);
2154: PetscStackCallSAWs(SAWs_Register,(dir,&ts->ptime,1,SAWs_READ,SAWs_DOUBLE));
2155: }
2156: if (ts->ops->view) {
2157: (*ts->ops->view)(ts,viewer);
2158: }
2159: #endif
2160: }
2161: if (ts->snes && ts->usessnes) {
2162: PetscViewerASCIIPushTab(viewer);
2163: SNESView(ts->snes,viewer);
2164: PetscViewerASCIIPopTab(viewer);
2165: }
2166: DMGetDMTS(ts->dm,&sdm);
2167: DMTSView(sdm,viewer);
2169: PetscViewerASCIIPushTab(viewer);
2170: PetscObjectTypeCompare((PetscObject)ts,TSSUNDIALS,&isundials);
2171: PetscViewerASCIIPopTab(viewer);
2172: return(0);
2173: }
2175: /*@
2176: TSSetApplicationContext - Sets an optional user-defined context for
2177: the timesteppers.
2179: Logically Collective on TS
2181: Input Parameters:
2182: + ts - the TS context obtained from TSCreate()
2183: - usrP - optional user context
2185: Fortran Notes:
2186: To use this from Fortran you must write a Fortran interface definition for this
2187: function that tells Fortran the Fortran derived data type that you are passing in as the ctx argument.
2189: Level: intermediate
2191: .seealso: TSGetApplicationContext()
2192: @*/
2193: PetscErrorCode TSSetApplicationContext(TS ts,void *usrP)
2194: {
2197: ts->user = usrP;
2198: return(0);
2199: }
2201: /*@
2202: TSGetApplicationContext - Gets the user-defined context for the
2203: timestepper.
2205: Not Collective
2207: Input Parameter:
2208: . ts - the TS context obtained from TSCreate()
2210: Output Parameter:
2211: . usrP - user context
2213: Fortran Notes:
2214: To use this from Fortran you must write a Fortran interface definition for this
2215: function that tells Fortran the Fortran derived data type that you are passing in as the ctx argument.
2217: Level: intermediate
2219: .seealso: TSSetApplicationContext()
2220: @*/
2221: PetscErrorCode TSGetApplicationContext(TS ts,void *usrP)
2222: {
2225: *(void**)usrP = ts->user;
2226: return(0);
2227: }
2229: /*@
2230: TSGetStepNumber - Gets the number of steps completed.
2232: Not Collective
2234: Input Parameter:
2235: . ts - the TS context obtained from TSCreate()
2237: Output Parameter:
2238: . steps - number of steps completed so far
2240: Level: intermediate
2242: .seealso: TSGetTime(), TSGetTimeStep(), TSSetPreStep(), TSSetPreStage(), TSSetPostStage(), TSSetPostStep()
2243: @*/
2244: PetscErrorCode TSGetStepNumber(TS ts,PetscInt *steps)
2245: {
2249: *steps = ts->steps;
2250: return(0);
2251: }
2253: /*@
2254: TSSetStepNumber - Sets the number of steps completed.
2256: Logically Collective on TS
2258: Input Parameters:
2259: + ts - the TS context
2260: - steps - number of steps completed so far
2262: Notes:
2263: For most uses of the TS solvers the user need not explicitly call
2264: TSSetStepNumber(), as the step counter is appropriately updated in
2265: TSSolve()/TSStep()/TSRollBack(). Power users may call this routine to
2266: reinitialize timestepping by setting the step counter to zero (and time
2267: to the initial time) to solve a similar problem with different initial
2268: conditions or parameters. Other possible use case is to continue
2269: timestepping from a previously interrupted run in such a way that TS
2270: monitors will be called with a initial nonzero step counter.
2272: Level: advanced
2274: .seealso: TSGetStepNumber(), TSSetTime(), TSSetTimeStep(), TSSetSolution()
2275: @*/
2276: PetscErrorCode TSSetStepNumber(TS ts,PetscInt steps)
2277: {
2281: if (steps < 0) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Step number must be non-negative");
2282: ts->steps = steps;
2283: return(0);
2284: }
2286: /*@
2287: TSSetTimeStep - Allows one to reset the timestep at any time,
2288: useful for simple pseudo-timestepping codes.
2290: Logically Collective on TS
2292: Input Parameters:
2293: + ts - the TS context obtained from TSCreate()
2294: - time_step - the size of the timestep
2296: Level: intermediate
2298: .seealso: TSGetTimeStep(), TSSetTime()
2300: @*/
2301: PetscErrorCode TSSetTimeStep(TS ts,PetscReal time_step)
2302: {
2306: ts->time_step = time_step;
2307: return(0);
2308: }
2310: /*@
2311: TSSetExactFinalTime - Determines whether to adapt the final time step to
2312: match the exact final time, interpolate solution to the exact final time,
2313: or just return at the final time TS computed.
2315: Logically Collective on TS
2317: Input Parameters:
2318: + ts - the time-step context
2319: - eftopt - exact final time option
2321: $ TS_EXACTFINALTIME_STEPOVER - Don't do anything if final time is exceeded
2322: $ TS_EXACTFINALTIME_INTERPOLATE - Interpolate back to final time
2323: $ TS_EXACTFINALTIME_MATCHSTEP - Adapt final time step to match the final time
2325: Options Database:
2326: . -ts_exact_final_time <stepover,interpolate,matchstep> - select the final step at runtime
2328: Warning: If you use the option TS_EXACTFINALTIME_STEPOVER the solution may be at a very different time
2329: then the final time you selected.
2331: Level: beginner
2333: .seealso: TSExactFinalTimeOption, TSGetExactFinalTime()
2334: @*/
2335: PetscErrorCode TSSetExactFinalTime(TS ts,TSExactFinalTimeOption eftopt)
2336: {
2340: ts->exact_final_time = eftopt;
2341: return(0);
2342: }
2344: /*@
2345: TSGetExactFinalTime - Gets the exact final time option.
2347: Not Collective
2349: Input Parameter:
2350: . ts - the TS context
2352: Output Parameter:
2353: . eftopt - exact final time option
2355: Level: beginner
2357: .seealso: TSExactFinalTimeOption, TSSetExactFinalTime()
2358: @*/
2359: PetscErrorCode TSGetExactFinalTime(TS ts,TSExactFinalTimeOption *eftopt)
2360: {
2364: *eftopt = ts->exact_final_time;
2365: return(0);
2366: }
2368: /*@
2369: TSGetTimeStep - Gets the current timestep size.
2371: Not Collective
2373: Input Parameter:
2374: . ts - the TS context obtained from TSCreate()
2376: Output Parameter:
2377: . dt - the current timestep size
2379: Level: intermediate
2381: .seealso: TSSetTimeStep(), TSGetTime()
2383: @*/
2384: PetscErrorCode TSGetTimeStep(TS ts,PetscReal *dt)
2385: {
2389: *dt = ts->time_step;
2390: return(0);
2391: }
2393: /*@
2394: TSGetSolution - Returns the solution at the present timestep. It
2395: is valid to call this routine inside the function that you are evaluating
2396: in order to move to the new timestep. This vector not changed until
2397: the solution at the next timestep has been calculated.
2399: Not Collective, but Vec returned is parallel if TS is parallel
2401: Input Parameter:
2402: . ts - the TS context obtained from TSCreate()
2404: Output Parameter:
2405: . v - the vector containing the solution
2407: Note: If you used TSSetExactFinalTime(ts,TS_EXACTFINALTIME_MATCHSTEP); this does not return the solution at the requested
2408: final time. It returns the solution at the next timestep.
2410: Level: intermediate
2412: .seealso: TSGetTimeStep(), TSGetTime(), TSGetSolveTime(), TSGetSolutionComponents(), TSSetSolutionFunction()
2414: @*/
2415: PetscErrorCode TSGetSolution(TS ts,Vec *v)
2416: {
2420: *v = ts->vec_sol;
2421: return(0);
2422: }
2424: /*@
2425: TSGetSolutionComponents - Returns any solution components at the present
2426: timestep, if available for the time integration method being used.
2427: Solution components are quantities that share the same size and
2428: structure as the solution vector.
2430: Not Collective, but Vec returned is parallel if TS is parallel
2432: Parameters :
2433: + ts - the TS context obtained from TSCreate() (input parameter).
2434: . n - If v is PETSC_NULL, then the number of solution components is
2435: returned through n, else the n-th solution component is
2436: returned in v.
2437: - v - the vector containing the n-th solution component
2438: (may be PETSC_NULL to use this function to find out
2439: the number of solutions components).
2441: Level: advanced
2443: .seealso: TSGetSolution()
2445: @*/
2446: PetscErrorCode TSGetSolutionComponents(TS ts,PetscInt *n,Vec *v)
2447: {
2452: if (!ts->ops->getsolutioncomponents) *n = 0;
2453: else {
2454: (*ts->ops->getsolutioncomponents)(ts,n,v);
2455: }
2456: return(0);
2457: }
2459: /*@
2460: TSGetAuxSolution - Returns an auxiliary solution at the present
2461: timestep, if available for the time integration method being used.
2463: Not Collective, but Vec returned is parallel if TS is parallel
2465: Parameters :
2466: + ts - the TS context obtained from TSCreate() (input parameter).
2467: - v - the vector containing the auxiliary solution
2469: Level: intermediate
2471: .seealso: TSGetSolution()
2473: @*/
2474: PetscErrorCode TSGetAuxSolution(TS ts,Vec *v)
2475: {
2480: if (ts->ops->getauxsolution) {
2481: (*ts->ops->getauxsolution)(ts,v);
2482: } else {
2483: VecZeroEntries(*v);
2484: }
2485: return(0);
2486: }
2488: /*@
2489: TSGetTimeError - Returns the estimated error vector, if the chosen
2490: TSType has an error estimation functionality.
2492: Not Collective, but Vec returned is parallel if TS is parallel
2494: Note: MUST call after TSSetUp()
2496: Parameters :
2497: + ts - the TS context obtained from TSCreate() (input parameter).
2498: . n - current estimate (n=0) or previous one (n=-1)
2499: - v - the vector containing the error (same size as the solution).
2501: Level: intermediate
2503: .seealso: TSGetSolution(), TSSetTimeError()
2505: @*/
2506: PetscErrorCode TSGetTimeError(TS ts,PetscInt n,Vec *v)
2507: {
2512: if (ts->ops->gettimeerror) {
2513: (*ts->ops->gettimeerror)(ts,n,v);
2514: } else {
2515: VecZeroEntries(*v);
2516: }
2517: return(0);
2518: }
2520: /*@
2521: TSSetTimeError - Sets the estimated error vector, if the chosen
2522: TSType has an error estimation functionality. This can be used
2523: to restart such a time integrator with a given error vector.
2525: Not Collective, but Vec returned is parallel if TS is parallel
2527: Parameters :
2528: + ts - the TS context obtained from TSCreate() (input parameter).
2529: - v - the vector containing the error (same size as the solution).
2531: Level: intermediate
2533: .seealso: TSSetSolution(), TSGetTimeError)
2535: @*/
2536: PetscErrorCode TSSetTimeError(TS ts,Vec v)
2537: {
2542: if (!ts->setupcalled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call TSSetUp() first");
2543: if (ts->ops->settimeerror) {
2544: (*ts->ops->settimeerror)(ts,v);
2545: }
2546: return(0);
2547: }
2549: /* ----- Routines to initialize and destroy a timestepper ---- */
2550: /*@
2551: TSSetProblemType - Sets the type of problem to be solved.
2553: Not collective
2555: Input Parameters:
2556: + ts - The TS
2557: - type - One of TS_LINEAR, TS_NONLINEAR where these types refer to problems of the forms
2558: .vb
2559: U_t - A U = 0 (linear)
2560: U_t - A(t) U = 0 (linear)
2561: F(t,U,U_t) = 0 (nonlinear)
2562: .ve
2564: Level: beginner
2566: .seealso: TSSetUp(), TSProblemType, TS
2567: @*/
2568: PetscErrorCode TSSetProblemType(TS ts, TSProblemType type)
2569: {
2574: ts->problem_type = type;
2575: if (type == TS_LINEAR) {
2576: SNES snes;
2577: TSGetSNES(ts,&snes);
2578: SNESSetType(snes,SNESKSPONLY);
2579: }
2580: return(0);
2581: }
2583: /*@C
2584: TSGetProblemType - Gets the type of problem to be solved.
2586: Not collective
2588: Input Parameter:
2589: . ts - The TS
2591: Output Parameter:
2592: . type - One of TS_LINEAR, TS_NONLINEAR where these types refer to problems of the forms
2593: .vb
2594: M U_t = A U
2595: M(t) U_t = A(t) U
2596: F(t,U,U_t)
2597: .ve
2599: Level: beginner
2601: .seealso: TSSetUp(), TSProblemType, TS
2602: @*/
2603: PetscErrorCode TSGetProblemType(TS ts, TSProblemType *type)
2604: {
2608: *type = ts->problem_type;
2609: return(0);
2610: }
2612: /*
2613: Attempt to check/preset a default value for the exact final time option. This is needed at the beginning of TSSolve() and in TSSetUp()
2614: */
2615: static PetscErrorCode TSSetExactFinalTimeDefault(TS ts)
2616: {
2618: PetscBool isnone;
2621: TSGetAdapt(ts,&ts->adapt);
2622: TSAdaptSetDefaultType(ts->adapt,ts->default_adapt_type);
2624: PetscObjectTypeCompare((PetscObject)ts->adapt,TSADAPTNONE,&isnone);
2625: if (!isnone && ts->exact_final_time == TS_EXACTFINALTIME_UNSPECIFIED) {
2626: ts->exact_final_time = TS_EXACTFINALTIME_MATCHSTEP;
2627: } else if (ts->exact_final_time == TS_EXACTFINALTIME_UNSPECIFIED) {
2628: ts->exact_final_time = TS_EXACTFINALTIME_INTERPOLATE;
2629: }
2630: return(0);
2631: }
2633: /*@
2634: TSSetUp - Sets up the internal data structures for the later use of a timestepper.
2636: Collective on TS
2638: Input Parameter:
2639: . ts - the TS context obtained from TSCreate()
2641: Notes:
2642: For basic use of the TS solvers the user need not explicitly call
2643: TSSetUp(), since these actions will automatically occur during
2644: the call to TSStep() or TSSolve(). However, if one wishes to control this
2645: phase separately, TSSetUp() should be called after TSCreate()
2646: and optional routines of the form TSSetXXX(), but before TSStep() and TSSolve().
2648: Level: advanced
2650: .seealso: TSCreate(), TSStep(), TSDestroy(), TSSolve()
2651: @*/
2652: PetscErrorCode TSSetUp(TS ts)
2653: {
2655: DM dm;
2656: PetscErrorCode (*func)(SNES,Vec,Vec,void*);
2657: PetscErrorCode (*jac)(SNES,Vec,Mat,Mat,void*);
2658: TSIFunction ifun;
2659: TSIJacobian ijac;
2660: TSI2Jacobian i2jac;
2661: TSRHSJacobian rhsjac;
2665: if (ts->setupcalled) return(0);
2667: if (!((PetscObject)ts)->type_name) {
2668: TSGetIFunction(ts,NULL,&ifun,NULL);
2669: TSSetType(ts,ifun ? TSBEULER : TSEULER);
2670: }
2672: if (!ts->vec_sol) {
2673: if (ts->dm) {
2674: DMCreateGlobalVector(ts->dm,&ts->vec_sol);
2675: } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call TSSetSolution() first");
2676: }
2678: if (!ts->Jacp && ts->Jacprhs) { /* IJacobianP shares the same matrix with RHSJacobianP if only RHSJacobianP is provided */
2679: PetscObjectReference((PetscObject)ts->Jacprhs);
2680: ts->Jacp = ts->Jacprhs;
2681: }
2683: if (ts->quadraturets) {
2684: TSSetUp(ts->quadraturets);
2685: VecDestroy(&ts->vec_costintegrand);
2686: VecDuplicate(ts->quadraturets->vec_sol,&ts->vec_costintegrand);
2687: }
2689: TSGetRHSJacobian(ts,NULL,NULL,&rhsjac,NULL);
2690: if (rhsjac == TSComputeRHSJacobianConstant) {
2691: Mat Amat,Pmat;
2692: SNES snes;
2693: TSGetSNES(ts,&snes);
2694: SNESGetJacobian(snes,&Amat,&Pmat,NULL,NULL);
2695: /* Matching matrices implies that an IJacobian is NOT set, because if it had been set, the IJacobian's matrix would
2696: * have displaced the RHS matrix */
2697: if (Amat && Amat == ts->Arhs) {
2698: /* we need to copy the values of the matrix because for the constant Jacobian case the user will never set the numerical values in this new location */
2699: MatDuplicate(ts->Arhs,MAT_COPY_VALUES,&Amat);
2700: SNESSetJacobian(snes,Amat,NULL,NULL,NULL);
2701: MatDestroy(&Amat);
2702: }
2703: if (Pmat && Pmat == ts->Brhs) {
2704: MatDuplicate(ts->Brhs,MAT_COPY_VALUES,&Pmat);
2705: SNESSetJacobian(snes,NULL,Pmat,NULL,NULL);
2706: MatDestroy(&Pmat);
2707: }
2708: }
2710: TSGetAdapt(ts,&ts->adapt);
2711: TSAdaptSetDefaultType(ts->adapt,ts->default_adapt_type);
2713: if (ts->ops->setup) {
2714: (*ts->ops->setup)(ts);
2715: }
2717: TSSetExactFinalTimeDefault(ts);
2719: /* In the case where we've set a DMTSFunction or what have you, we need the default SNESFunction
2720: to be set right but can't do it elsewhere due to the overreliance on ctx=ts.
2721: */
2722: TSGetDM(ts,&dm);
2723: DMSNESGetFunction(dm,&func,NULL);
2724: if (!func) {
2725: DMSNESSetFunction(dm,SNESTSFormFunction,ts);
2726: }
2727: /* If the SNES doesn't have a jacobian set and the TS has an ijacobian or rhsjacobian set, set the SNES to use it.
2728: Otherwise, the SNES will use coloring internally to form the Jacobian.
2729: */
2730: DMSNESGetJacobian(dm,&jac,NULL);
2731: DMTSGetIJacobian(dm,&ijac,NULL);
2732: DMTSGetI2Jacobian(dm,&i2jac,NULL);
2733: DMTSGetRHSJacobian(dm,&rhsjac,NULL);
2734: if (!jac && (ijac || i2jac || rhsjac)) {
2735: DMSNESSetJacobian(dm,SNESTSFormJacobian,ts);
2736: }
2738: /* if time integration scheme has a starting method, call it */
2739: if (ts->ops->startingmethod) {
2740: (*ts->ops->startingmethod)(ts);
2741: }
2743: ts->setupcalled = PETSC_TRUE;
2744: return(0);
2745: }
2747: /*@
2748: TSReset - Resets a TS context and removes any allocated Vecs and Mats.
2750: Collective on TS
2752: Input Parameter:
2753: . ts - the TS context obtained from TSCreate()
2755: Level: beginner
2757: .seealso: TSCreate(), TSSetup(), TSDestroy()
2758: @*/
2759: PetscErrorCode TSReset(TS ts)
2760: {
2761: TS_RHSSplitLink ilink = ts->tsrhssplit,next;
2762: PetscErrorCode ierr;
2767: if (ts->ops->reset) {
2768: (*ts->ops->reset)(ts);
2769: }
2770: if (ts->snes) {SNESReset(ts->snes);}
2771: if (ts->adapt) {TSAdaptReset(ts->adapt);}
2773: MatDestroy(&ts->Arhs);
2774: MatDestroy(&ts->Brhs);
2775: VecDestroy(&ts->Frhs);
2776: VecDestroy(&ts->vec_sol);
2777: VecDestroy(&ts->vec_dot);
2778: VecDestroy(&ts->vatol);
2779: VecDestroy(&ts->vrtol);
2780: VecDestroyVecs(ts->nwork,&ts->work);
2782: MatDestroy(&ts->Jacprhs);
2783: MatDestroy(&ts->Jacp);
2784: if (ts->forward_solve) {
2785: TSForwardReset(ts);
2786: }
2787: if (ts->quadraturets) {
2788: TSReset(ts->quadraturets);
2789: VecDestroy(&ts->vec_costintegrand);
2790: }
2791: while (ilink) {
2792: next = ilink->next;
2793: TSDestroy(&ilink->ts);
2794: PetscFree(ilink->splitname);
2795: ISDestroy(&ilink->is);
2796: PetscFree(ilink);
2797: ilink = next;
2798: }
2799: ts->num_rhs_splits = 0;
2800: ts->setupcalled = PETSC_FALSE;
2801: return(0);
2802: }
2804: /*@C
2805: TSDestroy - Destroys the timestepper context that was created
2806: with TSCreate().
2808: Collective on TS
2810: Input Parameter:
2811: . ts - the TS context obtained from TSCreate()
2813: Level: beginner
2815: .seealso: TSCreate(), TSSetUp(), TSSolve()
2816: @*/
2817: PetscErrorCode TSDestroy(TS *ts)
2818: {
2822: if (!*ts) return(0);
2824: if (--((PetscObject)(*ts))->refct > 0) {*ts = NULL; return(0);}
2826: TSReset(*ts);
2827: TSAdjointReset(*ts);
2828: if ((*ts)->forward_solve) {
2829: TSForwardReset(*ts);
2830: }
2831: /* if memory was published with SAWs then destroy it */
2832: PetscObjectSAWsViewOff((PetscObject)*ts);
2833: if ((*ts)->ops->destroy) {(*(*ts)->ops->destroy)((*ts));}
2835: TSTrajectoryDestroy(&(*ts)->trajectory);
2837: TSAdaptDestroy(&(*ts)->adapt);
2838: TSEventDestroy(&(*ts)->event);
2840: SNESDestroy(&(*ts)->snes);
2841: DMDestroy(&(*ts)->dm);
2842: TSMonitorCancel((*ts));
2843: TSAdjointMonitorCancel((*ts));
2845: TSDestroy(&(*ts)->quadraturets);
2846: PetscHeaderDestroy(ts);
2847: return(0);
2848: }
2850: /*@
2851: TSGetSNES - Returns the SNES (nonlinear solver) associated with
2852: a TS (timestepper) context. Valid only for nonlinear problems.
2854: Not Collective, but SNES is parallel if TS is parallel
2856: Input Parameter:
2857: . ts - the TS context obtained from TSCreate()
2859: Output Parameter:
2860: . snes - the nonlinear solver context
2862: Notes:
2863: The user can then directly manipulate the SNES context to set various
2864: options, etc. Likewise, the user can then extract and manipulate the
2865: KSP, KSP, and PC contexts as well.
2867: TSGetSNES() does not work for integrators that do not use SNES; in
2868: this case TSGetSNES() returns NULL in snes.
2870: Level: beginner
2872: @*/
2873: PetscErrorCode TSGetSNES(TS ts,SNES *snes)
2874: {
2880: if (!ts->snes) {
2881: SNESCreate(PetscObjectComm((PetscObject)ts),&ts->snes);
2882: PetscObjectSetOptions((PetscObject)ts->snes,((PetscObject)ts)->options);
2883: SNESSetFunction(ts->snes,NULL,SNESTSFormFunction,ts);
2884: PetscLogObjectParent((PetscObject)ts,(PetscObject)ts->snes);
2885: PetscObjectIncrementTabLevel((PetscObject)ts->snes,(PetscObject)ts,1);
2886: if (ts->dm) {SNESSetDM(ts->snes,ts->dm);}
2887: if (ts->problem_type == TS_LINEAR) {
2888: SNESSetType(ts->snes,SNESKSPONLY);
2889: }
2890: }
2891: *snes = ts->snes;
2892: return(0);
2893: }
2895: /*@
2896: TSSetSNES - Set the SNES (nonlinear solver) to be used by the timestepping context
2898: Collective
2900: Input Parameters:
2901: + ts - the TS context obtained from TSCreate()
2902: - snes - the nonlinear solver context
2904: Notes:
2905: Most users should have the TS created by calling TSGetSNES()
2907: Level: developer
2909: @*/
2910: PetscErrorCode TSSetSNES(TS ts,SNES snes)
2911: {
2913: PetscErrorCode (*func)(SNES,Vec,Mat,Mat,void*);
2918: PetscObjectReference((PetscObject)snes);
2919: SNESDestroy(&ts->snes);
2921: ts->snes = snes;
2923: SNESSetFunction(ts->snes,NULL,SNESTSFormFunction,ts);
2924: SNESGetJacobian(ts->snes,NULL,NULL,&func,NULL);
2925: if (func == SNESTSFormJacobian) {
2926: SNESSetJacobian(ts->snes,NULL,NULL,SNESTSFormJacobian,ts);
2927: }
2928: return(0);
2929: }
2931: /*@
2932: TSGetKSP - Returns the KSP (linear solver) associated with
2933: a TS (timestepper) context.
2935: Not Collective, but KSP is parallel if TS is parallel
2937: Input Parameter:
2938: . ts - the TS context obtained from TSCreate()
2940: Output Parameter:
2941: . ksp - the nonlinear solver context
2943: Notes:
2944: The user can then directly manipulate the KSP context to set various
2945: options, etc. Likewise, the user can then extract and manipulate the
2946: KSP and PC contexts as well.
2948: TSGetKSP() does not work for integrators that do not use KSP;
2949: in this case TSGetKSP() returns NULL in ksp.
2951: Level: beginner
2953: @*/
2954: PetscErrorCode TSGetKSP(TS ts,KSP *ksp)
2955: {
2957: SNES snes;
2962: if (!((PetscObject)ts)->type_name) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_NULL,"KSP is not created yet. Call TSSetType() first");
2963: if (ts->problem_type != TS_LINEAR) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Linear only; use TSGetSNES()");
2964: TSGetSNES(ts,&snes);
2965: SNESGetKSP(snes,ksp);
2966: return(0);
2967: }
2969: /* ----------- Routines to set solver parameters ---------- */
2971: /*@
2972: TSSetMaxSteps - Sets the maximum number of steps to use.
2974: Logically Collective on TS
2976: Input Parameters:
2977: + ts - the TS context obtained from TSCreate()
2978: - maxsteps - maximum number of steps to use
2980: Options Database Keys:
2981: . -ts_max_steps <maxsteps> - Sets maxsteps
2983: Notes:
2984: The default maximum number of steps is 5000
2986: Level: intermediate
2988: .seealso: TSGetMaxSteps(), TSSetMaxTime(), TSSetExactFinalTime()
2989: @*/
2990: PetscErrorCode TSSetMaxSteps(TS ts,PetscInt maxsteps)
2991: {
2995: if (maxsteps < 0) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Maximum number of steps must be non-negative");
2996: ts->max_steps = maxsteps;
2997: return(0);
2998: }
3000: /*@
3001: TSGetMaxSteps - Gets the maximum number of steps to use.
3003: Not Collective
3005: Input Parameters:
3006: . ts - the TS context obtained from TSCreate()
3008: Output Parameter:
3009: . maxsteps - maximum number of steps to use
3011: Level: advanced
3013: .seealso: TSSetMaxSteps(), TSGetMaxTime(), TSSetMaxTime()
3014: @*/
3015: PetscErrorCode TSGetMaxSteps(TS ts,PetscInt *maxsteps)
3016: {
3020: *maxsteps = ts->max_steps;
3021: return(0);
3022: }
3024: /*@
3025: TSSetMaxTime - Sets the maximum (or final) time for timestepping.
3027: Logically Collective on TS
3029: Input Parameters:
3030: + ts - the TS context obtained from TSCreate()
3031: - maxtime - final time to step to
3033: Options Database Keys:
3034: . -ts_max_time <maxtime> - Sets maxtime
3036: Notes:
3037: The default maximum time is 5.0
3039: Level: intermediate
3041: .seealso: TSGetMaxTime(), TSSetMaxSteps(), TSSetExactFinalTime()
3042: @*/
3043: PetscErrorCode TSSetMaxTime(TS ts,PetscReal maxtime)
3044: {
3048: ts->max_time = maxtime;
3049: return(0);
3050: }
3052: /*@
3053: TSGetMaxTime - Gets the maximum (or final) time for timestepping.
3055: Not Collective
3057: Input Parameters:
3058: . ts - the TS context obtained from TSCreate()
3060: Output Parameter:
3061: . maxtime - final time to step to
3063: Level: advanced
3065: .seealso: TSSetMaxTime(), TSGetMaxSteps(), TSSetMaxSteps()
3066: @*/
3067: PetscErrorCode TSGetMaxTime(TS ts,PetscReal *maxtime)
3068: {
3072: *maxtime = ts->max_time;
3073: return(0);
3074: }
3076: /*@
3077: TSSetInitialTimeStep - Deprecated, use TSSetTime() and TSSetTimeStep().
3079: Level: deprecated
3081: @*/
3082: PetscErrorCode TSSetInitialTimeStep(TS ts,PetscReal initial_time,PetscReal time_step)
3083: {
3087: TSSetTime(ts,initial_time);
3088: TSSetTimeStep(ts,time_step);
3089: return(0);
3090: }
3092: /*@
3093: TSGetDuration - Deprecated, use TSGetMaxSteps() and TSGetMaxTime().
3095: Level: deprecated
3097: @*/
3098: PetscErrorCode TSGetDuration(TS ts, PetscInt *maxsteps, PetscReal *maxtime)
3099: {
3102: if (maxsteps) {
3104: *maxsteps = ts->max_steps;
3105: }
3106: if (maxtime) {
3108: *maxtime = ts->max_time;
3109: }
3110: return(0);
3111: }
3113: /*@
3114: TSSetDuration - Deprecated, use TSSetMaxSteps() and TSSetMaxTime().
3116: Level: deprecated
3118: @*/
3119: PetscErrorCode TSSetDuration(TS ts,PetscInt maxsteps,PetscReal maxtime)
3120: {
3125: if (maxsteps >= 0) ts->max_steps = maxsteps;
3126: if (maxtime != PETSC_DEFAULT) ts->max_time = maxtime;
3127: return(0);
3128: }
3130: /*@
3131: TSGetTimeStepNumber - Deprecated, use TSGetStepNumber().
3133: Level: deprecated
3135: @*/
3136: PetscErrorCode TSGetTimeStepNumber(TS ts,PetscInt *steps) { return TSGetStepNumber(ts,steps); }
3138: /*@
3139: TSGetTotalSteps - Deprecated, use TSGetStepNumber().
3141: Level: deprecated
3143: @*/
3144: PetscErrorCode TSGetTotalSteps(TS ts,PetscInt *steps) { return TSGetStepNumber(ts,steps); }
3146: /*@
3147: TSSetSolution - Sets the initial solution vector
3148: for use by the TS routines.
3150: Logically Collective on TS
3152: Input Parameters:
3153: + ts - the TS context obtained from TSCreate()
3154: - u - the solution vector
3156: Level: beginner
3158: .seealso: TSSetSolutionFunction(), TSGetSolution(), TSCreate()
3159: @*/
3160: PetscErrorCode TSSetSolution(TS ts,Vec u)
3161: {
3163: DM dm;
3168: PetscObjectReference((PetscObject)u);
3169: VecDestroy(&ts->vec_sol);
3170: ts->vec_sol = u;
3172: TSGetDM(ts,&dm);
3173: DMShellSetGlobalVector(dm,u);
3174: return(0);
3175: }
3177: /*@C
3178: TSSetPreStep - Sets the general-purpose function
3179: called once at the beginning of each time step.
3181: Logically Collective on TS
3183: Input Parameters:
3184: + ts - The TS context obtained from TSCreate()
3185: - func - The function
3187: Calling sequence of func:
3188: . PetscErrorCode func (TS ts);
3190: Level: intermediate
3192: .seealso: TSSetPreStage(), TSSetPostStage(), TSSetPostStep(), TSStep(), TSRestartStep()
3193: @*/
3194: PetscErrorCode TSSetPreStep(TS ts, PetscErrorCode (*func)(TS))
3195: {
3198: ts->prestep = func;
3199: return(0);
3200: }
3202: /*@
3203: TSPreStep - Runs the user-defined pre-step function.
3205: Collective on TS
3207: Input Parameters:
3208: . ts - The TS context obtained from TSCreate()
3210: Notes:
3211: TSPreStep() is typically used within time stepping implementations,
3212: so most users would not generally call this routine themselves.
3214: Level: developer
3216: .seealso: TSSetPreStep(), TSPreStage(), TSPostStage(), TSPostStep()
3217: @*/
3218: PetscErrorCode TSPreStep(TS ts)
3219: {
3224: if (ts->prestep) {
3225: Vec U;
3226: PetscObjectState sprev,spost;
3228: TSGetSolution(ts,&U);
3229: PetscObjectStateGet((PetscObject)U,&sprev);
3230: PetscStackCallStandard((*ts->prestep),(ts));
3231: PetscObjectStateGet((PetscObject)U,&spost);
3232: if (sprev != spost) {TSRestartStep(ts);}
3233: }
3234: return(0);
3235: }
3237: /*@C
3238: TSSetPreStage - Sets the general-purpose function
3239: called once at the beginning of each stage.
3241: Logically Collective on TS
3243: Input Parameters:
3244: + ts - The TS context obtained from TSCreate()
3245: - func - The function
3247: Calling sequence of func:
3248: . PetscErrorCode func(TS ts, PetscReal stagetime);
3250: Level: intermediate
3252: Note:
3253: There may be several stages per time step. If the solve for a given stage fails, the step may be rejected and retried.
3254: The time step number being computed can be queried using TSGetStepNumber() and the total size of the step being
3255: attempted can be obtained using TSGetTimeStep(). The time at the start of the step is available via TSGetTime().
3257: .seealso: TSSetPostStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext()
3258: @*/
3259: PetscErrorCode TSSetPreStage(TS ts, PetscErrorCode (*func)(TS,PetscReal))
3260: {
3263: ts->prestage = func;
3264: return(0);
3265: }
3267: /*@C
3268: TSSetPostStage - Sets the general-purpose function
3269: called once at the end of each stage.
3271: Logically Collective on TS
3273: Input Parameters:
3274: + ts - The TS context obtained from TSCreate()
3275: - func - The function
3277: Calling sequence of func:
3278: . PetscErrorCode func(TS ts, PetscReal stagetime, PetscInt stageindex, Vec* Y);
3280: Level: intermediate
3282: Note:
3283: There may be several stages per time step. If the solve for a given stage fails, the step may be rejected and retried.
3284: The time step number being computed can be queried using TSGetStepNumber() and the total size of the step being
3285: attempted can be obtained using TSGetTimeStep(). The time at the start of the step is available via TSGetTime().
3287: .seealso: TSSetPreStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext()
3288: @*/
3289: PetscErrorCode TSSetPostStage(TS ts, PetscErrorCode (*func)(TS,PetscReal,PetscInt,Vec*))
3290: {
3293: ts->poststage = func;
3294: return(0);
3295: }
3297: /*@C
3298: TSSetPostEvaluate - Sets the general-purpose function
3299: called once at the end of each step evaluation.
3301: Logically Collective on TS
3303: Input Parameters:
3304: + ts - The TS context obtained from TSCreate()
3305: - func - The function
3307: Calling sequence of func:
3308: . PetscErrorCode func(TS ts);
3310: Level: intermediate
3312: Note:
3313: Semantically, TSSetPostEvaluate() differs from TSSetPostStep() since the function it sets is called before event-handling
3314: thus guaranteeing the same solution (computed by the time-stepper) will be passed to it. On the other hand, TSPostStep()
3315: may be passed a different solution, possibly changed by the event handler. TSPostEvaluate() is called after the next step
3316: solution is evaluated allowing to modify it, if need be. The solution can be obtained with TSGetSolution(), the time step
3317: with TSGetTimeStep(), and the time at the start of the step is available via TSGetTime()
3319: .seealso: TSSetPreStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext()
3320: @*/
3321: PetscErrorCode TSSetPostEvaluate(TS ts, PetscErrorCode (*func)(TS))
3322: {
3325: ts->postevaluate = func;
3326: return(0);
3327: }
3329: /*@
3330: TSPreStage - Runs the user-defined pre-stage function set using TSSetPreStage()
3332: Collective on TS
3334: Input Parameters:
3335: . ts - The TS context obtained from TSCreate()
3336: stagetime - The absolute time of the current stage
3338: Notes:
3339: TSPreStage() is typically used within time stepping implementations,
3340: most users would not generally call this routine themselves.
3342: Level: developer
3344: .seealso: TSPostStage(), TSSetPreStep(), TSPreStep(), TSPostStep()
3345: @*/
3346: PetscErrorCode TSPreStage(TS ts, PetscReal stagetime)
3347: {
3350: if (ts->prestage) {
3351: PetscStackCallStandard((*ts->prestage),(ts,stagetime));
3352: }
3353: return(0);
3354: }
3356: /*@
3357: TSPostStage - Runs the user-defined post-stage function set using TSSetPostStage()
3359: Collective on TS
3361: Input Parameters:
3362: . ts - The TS context obtained from TSCreate()
3363: stagetime - The absolute time of the current stage
3364: stageindex - Stage number
3365: Y - Array of vectors (of size = total number
3366: of stages) with the stage solutions
3368: Notes:
3369: TSPostStage() is typically used within time stepping implementations,
3370: most users would not generally call this routine themselves.
3372: Level: developer
3374: .seealso: TSPreStage(), TSSetPreStep(), TSPreStep(), TSPostStep()
3375: @*/
3376: PetscErrorCode TSPostStage(TS ts, PetscReal stagetime, PetscInt stageindex, Vec *Y)
3377: {
3380: if (ts->poststage) {
3381: PetscStackCallStandard((*ts->poststage),(ts,stagetime,stageindex,Y));
3382: }
3383: return(0);
3384: }
3386: /*@
3387: TSPostEvaluate - Runs the user-defined post-evaluate function set using TSSetPostEvaluate()
3389: Collective on TS
3391: Input Parameters:
3392: . ts - The TS context obtained from TSCreate()
3394: Notes:
3395: TSPostEvaluate() is typically used within time stepping implementations,
3396: most users would not generally call this routine themselves.
3398: Level: developer
3400: .seealso: TSSetPostEvaluate(), TSSetPreStep(), TSPreStep(), TSPostStep()
3401: @*/
3402: PetscErrorCode TSPostEvaluate(TS ts)
3403: {
3408: if (ts->postevaluate) {
3409: Vec U;
3410: PetscObjectState sprev,spost;
3412: TSGetSolution(ts,&U);
3413: PetscObjectStateGet((PetscObject)U,&sprev);
3414: PetscStackCallStandard((*ts->postevaluate),(ts));
3415: PetscObjectStateGet((PetscObject)U,&spost);
3416: if (sprev != spost) {TSRestartStep(ts);}
3417: }
3418: return(0);
3419: }
3421: /*@C
3422: TSSetPostStep - Sets the general-purpose function
3423: called once at the end of each time step.
3425: Logically Collective on TS
3427: Input Parameters:
3428: + ts - The TS context obtained from TSCreate()
3429: - func - The function
3431: Calling sequence of func:
3432: $ func (TS ts);
3434: Notes:
3435: The function set by TSSetPostStep() is called after each successful step. The solution vector X
3436: obtained by TSGetSolution() may be different than that computed at the step end if the event handler
3437: locates an event and TSPostEvent() modifies it. Use TSSetPostEvaluate() if an unmodified solution is needed instead.
3439: Level: intermediate
3441: .seealso: TSSetPreStep(), TSSetPreStage(), TSSetPostEvaluate(), TSGetTimeStep(), TSGetStepNumber(), TSGetTime(), TSRestartStep()
3442: @*/
3443: PetscErrorCode TSSetPostStep(TS ts, PetscErrorCode (*func)(TS))
3444: {
3447: ts->poststep = func;
3448: return(0);
3449: }
3451: /*@
3452: TSPostStep - Runs the user-defined post-step function.
3454: Collective on TS
3456: Input Parameters:
3457: . ts - The TS context obtained from TSCreate()
3459: Notes:
3460: TSPostStep() is typically used within time stepping implementations,
3461: so most users would not generally call this routine themselves.
3463: Level: developer
3465: @*/
3466: PetscErrorCode TSPostStep(TS ts)
3467: {
3472: if (ts->poststep) {
3473: Vec U;
3474: PetscObjectState sprev,spost;
3476: TSGetSolution(ts,&U);
3477: PetscObjectStateGet((PetscObject)U,&sprev);
3478: PetscStackCallStandard((*ts->poststep),(ts));
3479: PetscObjectStateGet((PetscObject)U,&spost);
3480: if (sprev != spost) {TSRestartStep(ts);}
3481: }
3482: return(0);
3483: }
3485: /*@
3486: TSInterpolate - Interpolate the solution computed during the previous step to an arbitrary location in the interval
3488: Collective on TS
3490: Input Parameters:
3491: + ts - time stepping context
3492: - t - time to interpolate to
3494: Output Parameter:
3495: . U - state at given time
3497: Level: intermediate
3499: Developer Notes:
3500: TSInterpolate() and the storing of previous steps/stages should be generalized to support delay differential equations and continuous adjoints.
3502: .seealso: TSSetExactFinalTime(), TSSolve()
3503: @*/
3504: PetscErrorCode TSInterpolate(TS ts,PetscReal t,Vec U)
3505: {
3511: if (t < ts->ptime_prev || t > ts->ptime) SETERRQ3(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Requested time %g not in last time steps [%g,%g]",t,(double)ts->ptime_prev,(double)ts->ptime);
3512: if (!ts->ops->interpolate) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"%s does not provide interpolation",((PetscObject)ts)->type_name);
3513: (*ts->ops->interpolate)(ts,t,U);
3514: return(0);
3515: }
3517: /*@
3518: TSStep - Steps one time step
3520: Collective on TS
3522: Input Parameter:
3523: . ts - the TS context obtained from TSCreate()
3525: Level: developer
3527: Notes:
3528: The public interface for the ODE/DAE solvers is TSSolve(), you should almost for sure be using that routine and not this routine.
3530: The hook set using TSSetPreStep() is called before each attempt to take the step. In general, the time step size may
3531: be changed due to adaptive error controller or solve failures. Note that steps may contain multiple stages.
3533: This may over-step the final time provided in TSSetMaxTime() depending on the time-step used. TSSolve() interpolates to exactly the
3534: time provided in TSSetMaxTime(). One can use TSInterpolate() to determine an interpolated solution within the final timestep.
3536: .seealso: TSCreate(), TSSetUp(), TSDestroy(), TSSolve(), TSSetPreStep(), TSSetPreStage(), TSSetPostStage(), TSInterpolate()
3537: @*/
3538: PetscErrorCode TSStep(TS ts)
3539: {
3540: PetscErrorCode ierr;
3541: static PetscBool cite = PETSC_FALSE;
3542: PetscReal ptime;
3546: PetscCitationsRegister("@article{tspaper,\n"
3547: " title = {{PETSc/TS}: A Modern Scalable {DAE/ODE} Solver Library},\n"
3548: " author = {Abhyankar, Shrirang and Brown, Jed and Constantinescu, Emil and Ghosh, Debojyoti and Smith, Barry F. and Zhang, Hong},\n"
3549: " journal = {arXiv e-preprints},\n"
3550: " eprint = {1806.01437},\n"
3551: " archivePrefix = {arXiv},\n"
3552: " year = {2018}\n}\n",&cite);
3554: TSSetUp(ts);
3555: TSTrajectorySetUp(ts->trajectory,ts);
3557: if (!ts->ops->step) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSStep not implemented for type '%s'",((PetscObject)ts)->type_name);
3558: if (ts->max_time >= PETSC_MAX_REAL && ts->max_steps == PETSC_MAX_INT) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"You must call TSSetMaxTime() or TSSetMaxSteps(), or use -ts_max_time <time> or -ts_max_steps <steps>");
3559: if (ts->exact_final_time == TS_EXACTFINALTIME_UNSPECIFIED) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"You must call TSSetExactFinalTime() or use -ts_exact_final_time <stepover,interpolate,matchstep> before calling TSStep()");
3560: if (ts->exact_final_time == TS_EXACTFINALTIME_MATCHSTEP && !ts->adapt) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Since TS is not adaptive you cannot use TS_EXACTFINALTIME_MATCHSTEP, suggest TS_EXACTFINALTIME_INTERPOLATE");
3562: if (!ts->steps) ts->ptime_prev = ts->ptime;
3563: ptime = ts->ptime; ts->ptime_prev_rollback = ts->ptime_prev;
3564: ts->reason = TS_CONVERGED_ITERATING;
3566: PetscLogEventBegin(TS_Step,ts,0,0,0);
3567: (*ts->ops->step)(ts);
3568: PetscLogEventEnd(TS_Step,ts,0,0,0);
3570: if (ts->reason >= 0) {
3571: ts->ptime_prev = ptime;
3572: ts->steps++;
3573: ts->steprollback = PETSC_FALSE;
3574: ts->steprestart = PETSC_FALSE;
3575: }
3577: if (!ts->reason) {
3578: if (ts->steps >= ts->max_steps) ts->reason = TS_CONVERGED_ITS;
3579: else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME;
3580: }
3582: if (ts->reason < 0 && ts->errorifstepfailed && ts->reason == TS_DIVERGED_NONLINEAR_SOLVE) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s, increase -ts_max_snes_failures or make negative to attempt recovery",TSConvergedReasons[ts->reason]);
3583: if (ts->reason < 0 && ts->errorifstepfailed) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s",TSConvergedReasons[ts->reason]);
3584: return(0);
3585: }
3587: /*@
3588: TSEvaluateWLTE - Evaluate the weighted local truncation error norm
3589: at the end of a time step with a given order of accuracy.
3591: Collective on TS
3593: Input Parameters:
3594: + ts - time stepping context
3595: - wnormtype - norm type, either NORM_2 or NORM_INFINITY
3597: Input/Output Parameter:
3598: . order - optional, desired order for the error evaluation or PETSC_DECIDE;
3599: on output, the actual order of the error evaluation
3601: Output Parameter:
3602: . wlte - the weighted local truncation error norm
3604: Level: advanced
3606: Notes:
3607: If the timestepper cannot evaluate the error in a particular step
3608: (eg. in the first step or restart steps after event handling),
3609: this routine returns wlte=-1.0 .
3611: .seealso: TSStep(), TSAdapt, TSErrorWeightedNorm()
3612: @*/
3613: PetscErrorCode TSEvaluateWLTE(TS ts,NormType wnormtype,PetscInt *order,PetscReal *wlte)
3614: {
3624: if (wnormtype != NORM_2 && wnormtype != NORM_INFINITY) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]);
3625: if (!ts->ops->evaluatewlte) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSEvaluateWLTE not implemented for type '%s'",((PetscObject)ts)->type_name);
3626: (*ts->ops->evaluatewlte)(ts,wnormtype,order,wlte);
3627: return(0);
3628: }
3630: /*@
3631: TSEvaluateStep - Evaluate the solution at the end of a time step with a given order of accuracy.
3633: Collective on TS
3635: Input Parameters:
3636: + ts - time stepping context
3637: . order - desired order of accuracy
3638: - done - whether the step was evaluated at this order (pass NULL to generate an error if not available)
3640: Output Parameter:
3641: . U - state at the end of the current step
3643: Level: advanced
3645: Notes:
3646: This function cannot be called until all stages have been evaluated.
3647: It is normally called by adaptive controllers before a step has been accepted and may also be called by the user after TSStep() has returned.
3649: .seealso: TSStep(), TSAdapt
3650: @*/
3651: PetscErrorCode TSEvaluateStep(TS ts,PetscInt order,Vec U,PetscBool *done)
3652: {
3659: if (!ts->ops->evaluatestep) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSEvaluateStep not implemented for type '%s'",((PetscObject)ts)->type_name);
3660: (*ts->ops->evaluatestep)(ts,order,U,done);
3661: return(0);
3662: }
3664: /*@C
3665: TSGetComputeInitialCondition - Get the function used to automatically compute an initial condition for the timestepping.
3667: Not collective
3669: Input Parameter:
3670: . ts - time stepping context
3672: Output Parameter:
3673: . initConditions - The function which computes an initial condition
3675: Level: advanced
3677: Notes:
3678: The calling sequence for the function is
3679: $ initCondition(TS ts, Vec u)
3680: $ ts - The timestepping context
3681: $ u - The input vector in which the initial condition is stored
3683: .seealso: TSSetComputeInitialCondition(), TSComputeInitialCondition()
3684: @*/
3685: PetscErrorCode TSGetComputeInitialCondition(TS ts, PetscErrorCode (**initCondition)(TS, Vec))
3686: {
3690: *initCondition = ts->ops->initcondition;
3691: return(0);
3692: }
3694: /*@C
3695: TSSetComputeInitialCondition - Set the function used to automatically compute an initial condition for the timestepping.
3697: Logically collective on ts
3699: Input Parameters:
3700: + ts - time stepping context
3701: - initCondition - The function which computes an initial condition
3703: Level: advanced
3705: Calling sequence for initCondition:
3706: $ PetscErrorCode initCondition(TS ts, Vec u)
3708: + ts - The timestepping context
3709: - u - The input vector in which the initial condition is to be stored
3711: .seealso: TSGetComputeInitialCondition(), TSComputeInitialCondition()
3712: @*/
3713: PetscErrorCode TSSetComputeInitialCondition(TS ts, PetscErrorCode (*initCondition)(TS, Vec))
3714: {
3718: ts->ops->initcondition = initCondition;
3719: return(0);
3720: }
3722: /*@
3723: TSComputeInitialCondition - Compute an initial condition for the timestepping using the function previously set.
3725: Collective on ts
3727: Input Parameters:
3728: + ts - time stepping context
3729: - u - The Vec to store the condition in which will be used in TSSolve()
3731: Level: advanced
3733: .seealso: TSGetComputeInitialCondition(), TSSetComputeInitialCondition(), TSSolve()
3734: @*/
3735: PetscErrorCode TSComputeInitialCondition(TS ts, Vec u)
3736: {
3742: if (ts->ops->initcondition) {(*ts->ops->initcondition)(ts, u);}
3743: return(0);
3744: }
3746: /*@C
3747: TSGetComputeExactError - Get the function used to automatically compute the exact error for the timestepping.
3749: Not collective
3751: Input Parameter:
3752: . ts - time stepping context
3754: Output Parameter:
3755: . exactError - The function which computes the solution error
3757: Level: advanced
3759: Calling sequence for exactError:
3760: $ PetscErrorCode exactError(TS ts, Vec u)
3762: + ts - The timestepping context
3763: . u - The approximate solution vector
3764: - e - The input vector in which the error is stored
3766: .seealso: TSGetComputeExactError(), TSComputeExactError()
3767: @*/
3768: PetscErrorCode TSGetComputeExactError(TS ts, PetscErrorCode (**exactError)(TS, Vec, Vec))
3769: {
3773: *exactError = ts->ops->exacterror;
3774: return(0);
3775: }
3777: /*@C
3778: TSSetComputeExactError - Set the function used to automatically compute the exact error for the timestepping.
3780: Logically collective on ts
3782: Input Parameters:
3783: + ts - time stepping context
3784: - exactError - The function which computes the solution error
3786: Level: advanced
3788: Calling sequence for exactError:
3789: $ PetscErrorCode exactError(TS ts, Vec u)
3791: + ts - The timestepping context
3792: . u - The approximate solution vector
3793: - e - The input vector in which the error is stored
3795: .seealso: TSGetComputeExactError(), TSComputeExactError()
3796: @*/
3797: PetscErrorCode TSSetComputeExactError(TS ts, PetscErrorCode (*exactError)(TS, Vec, Vec))
3798: {
3802: ts->ops->exacterror = exactError;
3803: return(0);
3804: }
3806: /*@
3807: TSComputeExactError - Compute the solution error for the timestepping using the function previously set.
3809: Collective on ts
3811: Input Parameters:
3812: + ts - time stepping context
3813: . u - The approximate solution
3814: - e - The Vec used to store the error
3816: Level: advanced
3818: .seealso: TSGetComputeInitialCondition(), TSSetComputeInitialCondition(), TSSolve()
3819: @*/
3820: PetscErrorCode TSComputeExactError(TS ts, Vec u, Vec e)
3821: {
3828: if (ts->ops->exacterror) {(*ts->ops->exacterror)(ts, u, e);}
3829: return(0);
3830: }
3832: /*@
3833: TSSolve - Steps the requested number of timesteps.
3835: Collective on TS
3837: Input Parameters:
3838: + ts - the TS context obtained from TSCreate()
3839: - u - the solution vector (can be null if TSSetSolution() was used and TSSetExactFinalTime(ts,TS_EXACTFINALTIME_MATCHSTEP) was not used,
3840: otherwise must contain the initial conditions and will contain the solution at the final requested time
3842: Level: beginner
3844: Notes:
3845: The final time returned by this function may be different from the time of the internally
3846: held state accessible by TSGetSolution() and TSGetTime() because the method may have
3847: stepped over the final time.
3849: .seealso: TSCreate(), TSSetSolution(), TSStep(), TSGetTime(), TSGetSolveTime()
3850: @*/
3851: PetscErrorCode TSSolve(TS ts,Vec u)
3852: {
3853: Vec solution;
3854: PetscErrorCode ierr;
3860: TSSetExactFinalTimeDefault(ts);
3861: if (ts->exact_final_time == TS_EXACTFINALTIME_INTERPOLATE && u) { /* Need ts->vec_sol to be distinct so it is not overwritten when we interpolate at the end */
3862: if (!ts->vec_sol || u == ts->vec_sol) {
3863: VecDuplicate(u,&solution);
3864: TSSetSolution(ts,solution);
3865: VecDestroy(&solution); /* grant ownership */
3866: }
3867: VecCopy(u,ts->vec_sol);
3868: if (ts->forward_solve) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Sensitivity analysis does not support the mode TS_EXACTFINALTIME_INTERPOLATE");
3869: } else if (u) {
3870: TSSetSolution(ts,u);
3871: }
3872: TSSetUp(ts);
3873: TSTrajectorySetUp(ts->trajectory,ts);
3875: if (ts->max_time >= PETSC_MAX_REAL && ts->max_steps == PETSC_MAX_INT) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"You must call TSSetMaxTime() or TSSetMaxSteps(), or use -ts_max_time <time> or -ts_max_steps <steps>");
3876: if (ts->exact_final_time == TS_EXACTFINALTIME_UNSPECIFIED) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"You must call TSSetExactFinalTime() or use -ts_exact_final_time <stepover,interpolate,matchstep> before calling TSSolve()");
3877: if (ts->exact_final_time == TS_EXACTFINALTIME_MATCHSTEP && !ts->adapt) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Since TS is not adaptive you cannot use TS_EXACTFINALTIME_MATCHSTEP, suggest TS_EXACTFINALTIME_INTERPOLATE");
3879: if (ts->forward_solve) {
3880: TSForwardSetUp(ts);
3881: }
3883: /* reset number of steps only when the step is not restarted. ARKIMEX
3884: restarts the step after an event. Resetting these counters in such case causes
3885: TSTrajectory to incorrectly save the output files
3886: */
3887: /* reset time step and iteration counters */
3888: if (!ts->steps) {
3889: ts->ksp_its = 0;
3890: ts->snes_its = 0;
3891: ts->num_snes_failures = 0;
3892: ts->reject = 0;
3893: ts->steprestart = PETSC_TRUE;
3894: ts->steprollback = PETSC_FALSE;
3895: ts->rhsjacobian.time = PETSC_MIN_REAL;
3896: }
3898: /* make sure initial time step does not overshoot final time */
3899: if (ts->exact_final_time == TS_EXACTFINALTIME_MATCHSTEP) {
3900: PetscReal maxdt = ts->max_time-ts->ptime;
3901: PetscReal dt = ts->time_step;
3903: ts->time_step = dt >= maxdt ? maxdt : (PetscIsCloseAtTol(dt,maxdt,10*PETSC_MACHINE_EPSILON,0) ? maxdt : dt);
3904: }
3905: ts->reason = TS_CONVERGED_ITERATING;
3907: {
3908: PetscViewer viewer;
3909: PetscViewerFormat format;
3910: PetscBool flg;
3911: static PetscBool incall = PETSC_FALSE;
3913: if (!incall) {
3914: /* Estimate the convergence rate of the time discretization */
3915: PetscOptionsGetViewer(PetscObjectComm((PetscObject) ts),((PetscObject)ts)->options, ((PetscObject) ts)->prefix, "-ts_convergence_estimate", &viewer, &format, &flg);
3916: if (flg) {
3917: PetscConvEst conv;
3918: DM dm;
3919: PetscReal *alpha; /* Convergence rate of the solution error for each field in the L_2 norm */
3920: PetscInt Nf;
3921: PetscBool checkTemporal = PETSC_TRUE;
3923: incall = PETSC_TRUE;
3924: PetscOptionsGetBool(((PetscObject)ts)->options, ((PetscObject) ts)->prefix, "-ts_convergence_temporal", &checkTemporal, &flg);
3925: TSGetDM(ts, &dm);
3926: DMGetNumFields(dm, &Nf);
3927: PetscCalloc1(PetscMax(Nf, 1), &alpha);
3928: PetscConvEstCreate(PetscObjectComm((PetscObject) ts), &conv);
3929: PetscConvEstUseTS(conv, checkTemporal);
3930: PetscConvEstSetSolver(conv, (PetscObject) ts);
3931: PetscConvEstSetFromOptions(conv);
3932: PetscConvEstSetUp(conv);
3933: PetscConvEstGetConvRate(conv, alpha);
3934: PetscViewerPushFormat(viewer, format);
3935: PetscConvEstRateView(conv, alpha, viewer);
3936: PetscViewerPopFormat(viewer);
3937: PetscViewerDestroy(&viewer);
3938: PetscConvEstDestroy(&conv);
3939: PetscFree(alpha);
3940: incall = PETSC_FALSE;
3941: }
3942: }
3943: }
3945: TSViewFromOptions(ts,NULL,"-ts_view_pre");
3947: if (ts->ops->solve) { /* This private interface is transitional and should be removed when all implementations are updated. */
3948: (*ts->ops->solve)(ts);
3949: if (u) {VecCopy(ts->vec_sol,u);}
3950: ts->solvetime = ts->ptime;
3951: solution = ts->vec_sol;
3952: } else { /* Step the requested number of timesteps. */
3953: if (ts->steps >= ts->max_steps) ts->reason = TS_CONVERGED_ITS;
3954: else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME;
3956: if (!ts->steps) {
3957: TSTrajectorySet(ts->trajectory,ts,ts->steps,ts->ptime,ts->vec_sol);
3958: TSEventInitialize(ts->event,ts,ts->ptime,ts->vec_sol);
3959: }
3961: while (!ts->reason) {
3962: TSMonitor(ts,ts->steps,ts->ptime,ts->vec_sol);
3963: if (!ts->steprollback) {
3964: TSPreStep(ts);
3965: }
3966: TSStep(ts);
3967: if (ts->testjacobian) {
3968: TSRHSJacobianTest(ts,NULL);
3969: }
3970: if (ts->testjacobiantranspose) {
3971: TSRHSJacobianTestTranspose(ts,NULL);
3972: }
3973: if (ts->quadraturets && ts->costintegralfwd) { /* Must evaluate the cost integral before event is handled. The cost integral value can also be rolled back. */
3974: if (ts->reason >= 0) ts->steps--; /* Revert the step number changed by TSStep() */
3975: TSForwardCostIntegral(ts);
3976: if (ts->reason >= 0) ts->steps++;
3977: }
3978: if (ts->forward_solve) { /* compute forward sensitivities before event handling because postevent() may change RHS and jump conditions may have to be applied */
3979: if (ts->reason >= 0) ts->steps--; /* Revert the step number changed by TSStep() */
3980: TSForwardStep(ts);
3981: if (ts->reason >= 0) ts->steps++;
3982: }
3983: TSPostEvaluate(ts);
3984: TSEventHandler(ts); /* The right-hand side may be changed due to event. Be careful with Any computation using the RHS information after this point. */
3985: if (ts->steprollback) {
3986: TSPostEvaluate(ts);
3987: }
3988: if (!ts->steprollback) {
3989: TSTrajectorySet(ts->trajectory,ts,ts->steps,ts->ptime,ts->vec_sol);
3990: TSPostStep(ts);
3991: }
3992: }
3993: TSMonitor(ts,ts->steps,ts->ptime,ts->vec_sol);
3995: if (ts->exact_final_time == TS_EXACTFINALTIME_INTERPOLATE && ts->ptime > ts->max_time) {
3996: TSInterpolate(ts,ts->max_time,u);
3997: ts->solvetime = ts->max_time;
3998: solution = u;
3999: TSMonitor(ts,-1,ts->solvetime,solution);
4000: } else {
4001: if (u) {VecCopy(ts->vec_sol,u);}
4002: ts->solvetime = ts->ptime;
4003: solution = ts->vec_sol;
4004: }
4005: }
4007: TSViewFromOptions(ts,NULL,"-ts_view");
4008: VecViewFromOptions(solution,(PetscObject)ts,"-ts_view_solution");
4009: PetscObjectSAWsBlock((PetscObject)ts);
4010: if (ts->adjoint_solve) {
4011: TSAdjointSolve(ts);
4012: }
4013: return(0);
4014: }
4016: /*@
4017: TSGetTime - Gets the time of the most recently completed step.
4019: Not Collective
4021: Input Parameter:
4022: . ts - the TS context obtained from TSCreate()
4024: Output Parameter:
4025: . t - the current time. This time may not corresponds to the final time set with TSSetMaxTime(), use TSGetSolveTime().
4027: Level: beginner
4029: Note:
4030: When called during time step evaluation (e.g. during residual evaluation or via hooks set using TSSetPreStep(),
4031: TSSetPreStage(), TSSetPostStage(), or TSSetPostStep()), the time is the time at the start of the step being evaluated.
4033: .seealso: TSGetSolveTime(), TSSetTime(), TSGetTimeStep(), TSGetStepNumber()
4035: @*/
4036: PetscErrorCode TSGetTime(TS ts,PetscReal *t)
4037: {
4041: *t = ts->ptime;
4042: return(0);
4043: }
4045: /*@
4046: TSGetPrevTime - Gets the starting time of the previously completed step.
4048: Not Collective
4050: Input Parameter:
4051: . ts - the TS context obtained from TSCreate()
4053: Output Parameter:
4054: . t - the previous time
4056: Level: beginner
4058: .seealso: TSGetTime(), TSGetSolveTime(), TSGetTimeStep()
4060: @*/
4061: PetscErrorCode TSGetPrevTime(TS ts,PetscReal *t)
4062: {
4066: *t = ts->ptime_prev;
4067: return(0);
4068: }
4070: /*@
4071: TSSetTime - Allows one to reset the time.
4073: Logically Collective on TS
4075: Input Parameters:
4076: + ts - the TS context obtained from TSCreate()
4077: - time - the time
4079: Level: intermediate
4081: .seealso: TSGetTime(), TSSetMaxSteps()
4083: @*/
4084: PetscErrorCode TSSetTime(TS ts, PetscReal t)
4085: {
4089: ts->ptime = t;
4090: return(0);
4091: }
4093: /*@C
4094: TSSetOptionsPrefix - Sets the prefix used for searching for all
4095: TS options in the database.
4097: Logically Collective on TS
4099: Input Parameters:
4100: + ts - The TS context
4101: - prefix - The prefix to prepend to all option names
4103: Notes:
4104: A hyphen (-) must NOT be given at the beginning of the prefix name.
4105: The first character of all runtime options is AUTOMATICALLY the
4106: hyphen.
4108: Level: advanced
4110: .seealso: TSSetFromOptions()
4112: @*/
4113: PetscErrorCode TSSetOptionsPrefix(TS ts,const char prefix[])
4114: {
4116: SNES snes;
4120: PetscObjectSetOptionsPrefix((PetscObject)ts,prefix);
4121: TSGetSNES(ts,&snes);
4122: SNESSetOptionsPrefix(snes,prefix);
4123: return(0);
4124: }
4126: /*@C
4127: TSAppendOptionsPrefix - Appends to the prefix used for searching for all
4128: TS options in the database.
4130: Logically Collective on TS
4132: Input Parameters:
4133: + ts - The TS context
4134: - prefix - The prefix to prepend to all option names
4136: Notes:
4137: A hyphen (-) must NOT be given at the beginning of the prefix name.
4138: The first character of all runtime options is AUTOMATICALLY the
4139: hyphen.
4141: Level: advanced
4143: .seealso: TSGetOptionsPrefix()
4145: @*/
4146: PetscErrorCode TSAppendOptionsPrefix(TS ts,const char prefix[])
4147: {
4149: SNES snes;
4153: PetscObjectAppendOptionsPrefix((PetscObject)ts,prefix);
4154: TSGetSNES(ts,&snes);
4155: SNESAppendOptionsPrefix(snes,prefix);
4156: return(0);
4157: }
4159: /*@C
4160: TSGetOptionsPrefix - Sets the prefix used for searching for all
4161: TS options in the database.
4163: Not Collective
4165: Input Parameter:
4166: . ts - The TS context
4168: Output Parameter:
4169: . prefix - A pointer to the prefix string used
4171: Notes:
4172: On the fortran side, the user should pass in a string 'prifix' of
4173: sufficient length to hold the prefix.
4175: Level: intermediate
4177: .seealso: TSAppendOptionsPrefix()
4178: @*/
4179: PetscErrorCode TSGetOptionsPrefix(TS ts,const char *prefix[])
4180: {
4186: PetscObjectGetOptionsPrefix((PetscObject)ts,prefix);
4187: return(0);
4188: }
4190: /*@C
4191: TSGetRHSJacobian - Returns the Jacobian J at the present timestep.
4193: Not Collective, but parallel objects are returned if TS is parallel
4195: Input Parameter:
4196: . ts - The TS context obtained from TSCreate()
4198: Output Parameters:
4199: + Amat - The (approximate) Jacobian J of G, where U_t = G(U,t) (or NULL)
4200: . Pmat - The matrix from which the preconditioner is constructed, usually the same as Amat (or NULL)
4201: . func - Function to compute the Jacobian of the RHS (or NULL)
4202: - ctx - User-defined context for Jacobian evaluation routine (or NULL)
4204: Notes:
4205: You can pass in NULL for any return argument you do not need.
4207: Level: intermediate
4209: .seealso: TSGetTimeStep(), TSGetMatrices(), TSGetTime(), TSGetStepNumber()
4211: @*/
4212: PetscErrorCode TSGetRHSJacobian(TS ts,Mat *Amat,Mat *Pmat,TSRHSJacobian *func,void **ctx)
4213: {
4215: DM dm;
4218: if (Amat || Pmat) {
4219: SNES snes;
4220: TSGetSNES(ts,&snes);
4221: SNESSetUpMatrices(snes);
4222: SNESGetJacobian(snes,Amat,Pmat,NULL,NULL);
4223: }
4224: TSGetDM(ts,&dm);
4225: DMTSGetRHSJacobian(dm,func,ctx);
4226: return(0);
4227: }
4229: /*@C
4230: TSGetIJacobian - Returns the implicit Jacobian at the present timestep.
4232: Not Collective, but parallel objects are returned if TS is parallel
4234: Input Parameter:
4235: . ts - The TS context obtained from TSCreate()
4237: Output Parameters:
4238: + Amat - The (approximate) Jacobian of F(t,U,U_t)
4239: . Pmat - The matrix from which the preconditioner is constructed, often the same as Amat
4240: . f - The function to compute the matrices
4241: - ctx - User-defined context for Jacobian evaluation routine
4243: Notes:
4244: You can pass in NULL for any return argument you do not need.
4246: Level: advanced
4248: .seealso: TSGetTimeStep(), TSGetRHSJacobian(), TSGetMatrices(), TSGetTime(), TSGetStepNumber()
4250: @*/
4251: PetscErrorCode TSGetIJacobian(TS ts,Mat *Amat,Mat *Pmat,TSIJacobian *f,void **ctx)
4252: {
4254: DM dm;
4257: if (Amat || Pmat) {
4258: SNES snes;
4259: TSGetSNES(ts,&snes);
4260: SNESSetUpMatrices(snes);
4261: SNESGetJacobian(snes,Amat,Pmat,NULL,NULL);
4262: }
4263: TSGetDM(ts,&dm);
4264: DMTSGetIJacobian(dm,f,ctx);
4265: return(0);
4266: }
4268: #include <petsc/private/dmimpl.h>
4269: /*@
4270: TSSetDM - Sets the DM that may be used by some nonlinear solvers or preconditioners under the TS
4272: Logically Collective on ts
4274: Input Parameters:
4275: + ts - the ODE integrator object
4276: - dm - the dm, cannot be NULL
4278: Notes:
4279: A DM can only be used for solving one problem at a time because information about the problem is stored on the DM,
4280: even when not using interfaces like DMTSSetIFunction(). Use DMClone() to get a distinct DM when solving
4281: different problems using the same function space.
4283: Level: intermediate
4285: .seealso: TSGetDM(), SNESSetDM(), SNESGetDM()
4286: @*/
4287: PetscErrorCode TSSetDM(TS ts,DM dm)
4288: {
4290: SNES snes;
4291: DMTS tsdm;
4296: PetscObjectReference((PetscObject)dm);
4297: if (ts->dm) { /* Move the DMTS context over to the new DM unless the new DM already has one */
4298: if (ts->dm->dmts && !dm->dmts) {
4299: DMCopyDMTS(ts->dm,dm);
4300: DMGetDMTS(ts->dm,&tsdm);
4301: if (tsdm->originaldm == ts->dm) { /* Grant write privileges to the replacement DM */
4302: tsdm->originaldm = dm;
4303: }
4304: }
4305: DMDestroy(&ts->dm);
4306: }
4307: ts->dm = dm;
4309: TSGetSNES(ts,&snes);
4310: SNESSetDM(snes,dm);
4311: return(0);
4312: }
4314: /*@
4315: TSGetDM - Gets the DM that may be used by some preconditioners
4317: Not Collective
4319: Input Parameter:
4320: . ts - the preconditioner context
4322: Output Parameter:
4323: . dm - the dm
4325: Level: intermediate
4327: .seealso: TSSetDM(), SNESSetDM(), SNESGetDM()
4328: @*/
4329: PetscErrorCode TSGetDM(TS ts,DM *dm)
4330: {
4335: if (!ts->dm) {
4336: DMShellCreate(PetscObjectComm((PetscObject)ts),&ts->dm);
4337: if (ts->snes) {SNESSetDM(ts->snes,ts->dm);}
4338: }
4339: *dm = ts->dm;
4340: return(0);
4341: }
4343: /*@
4344: SNESTSFormFunction - Function to evaluate nonlinear residual
4346: Logically Collective on SNES
4348: Input Parameters:
4349: + snes - nonlinear solver
4350: . U - the current state at which to evaluate the residual
4351: - ctx - user context, must be a TS
4353: Output Parameter:
4354: . F - the nonlinear residual
4356: Notes:
4357: This function is not normally called by users and is automatically registered with the SNES used by TS.
4358: It is most frequently passed to MatFDColoringSetFunction().
4360: Level: advanced
4362: .seealso: SNESSetFunction(), MatFDColoringSetFunction()
4363: @*/
4364: PetscErrorCode SNESTSFormFunction(SNES snes,Vec U,Vec F,void *ctx)
4365: {
4366: TS ts = (TS)ctx;
4374: (ts->ops->snesfunction)(snes,U,F,ts);
4375: return(0);
4376: }
4378: /*@
4379: SNESTSFormJacobian - Function to evaluate the Jacobian
4381: Collective on SNES
4383: Input Parameters:
4384: + snes - nonlinear solver
4385: . U - the current state at which to evaluate the residual
4386: - ctx - user context, must be a TS
4388: Output Parameters:
4389: + A - the Jacobian
4390: - B - the preconditioning matrix (may be the same as A)
4392: Notes:
4393: This function is not normally called by users and is automatically registered with the SNES used by TS.
4395: Level: developer
4397: .seealso: SNESSetJacobian()
4398: @*/
4399: PetscErrorCode SNESTSFormJacobian(SNES snes,Vec U,Mat A,Mat B,void *ctx)
4400: {
4401: TS ts = (TS)ctx;
4412: (ts->ops->snesjacobian)(snes,U,A,B,ts);
4413: return(0);
4414: }
4416: /*@C
4417: TSComputeRHSFunctionLinear - Evaluate the right hand side via the user-provided Jacobian, for linear problems Udot = A U only
4419: Collective on TS
4421: Input Parameters:
4422: + ts - time stepping context
4423: . t - time at which to evaluate
4424: . U - state at which to evaluate
4425: - ctx - context
4427: Output Parameter:
4428: . F - right hand side
4430: Level: intermediate
4432: Notes:
4433: This function is intended to be passed to TSSetRHSFunction() to evaluate the right hand side for linear problems.
4434: The matrix (and optionally the evaluation context) should be passed to TSSetRHSJacobian().
4436: .seealso: TSSetRHSFunction(), TSSetRHSJacobian(), TSComputeRHSJacobianConstant()
4437: @*/
4438: PetscErrorCode TSComputeRHSFunctionLinear(TS ts,PetscReal t,Vec U,Vec F,void *ctx)
4439: {
4441: Mat Arhs,Brhs;
4444: TSGetRHSMats_Private(ts,&Arhs,&Brhs);
4445: /* undo the damage caused by shifting */
4446: TSRecoverRHSJacobian(ts,Arhs,Brhs);
4447: TSComputeRHSJacobian(ts,t,U,Arhs,Brhs);
4448: MatMult(Arhs,U,F);
4449: return(0);
4450: }
4452: /*@C
4453: TSComputeRHSJacobianConstant - Reuses a Jacobian that is time-independent.
4455: Collective on TS
4457: Input Parameters:
4458: + ts - time stepping context
4459: . t - time at which to evaluate
4460: . U - state at which to evaluate
4461: - ctx - context
4463: Output Parameters:
4464: + A - pointer to operator
4465: - B - pointer to preconditioning matrix
4467: Level: intermediate
4469: Notes:
4470: This function is intended to be passed to TSSetRHSJacobian() to evaluate the Jacobian for linear time-independent problems.
4472: .seealso: TSSetRHSFunction(), TSSetRHSJacobian(), TSComputeRHSFunctionLinear()
4473: @*/
4474: PetscErrorCode TSComputeRHSJacobianConstant(TS ts,PetscReal t,Vec U,Mat A,Mat B,void *ctx)
4475: {
4477: return(0);
4478: }
4480: /*@C
4481: TSComputeIFunctionLinear - Evaluate the left hand side via the user-provided Jacobian, for linear problems only
4483: Collective on TS
4485: Input Parameters:
4486: + ts - time stepping context
4487: . t - time at which to evaluate
4488: . U - state at which to evaluate
4489: . Udot - time derivative of state vector
4490: - ctx - context
4492: Output Parameter:
4493: . F - left hand side
4495: Level: intermediate
4497: Notes:
4498: The assumption here is that the left hand side is of the form A*Udot (and not A*Udot + B*U). For other cases, the
4499: user is required to write their own TSComputeIFunction.
4500: This function is intended to be passed to TSSetIFunction() to evaluate the left hand side for linear problems.
4501: The matrix (and optionally the evaluation context) should be passed to TSSetIJacobian().
4503: Note that using this function is NOT equivalent to using TSComputeRHSFunctionLinear() since that solves Udot = A U
4505: .seealso: TSSetIFunction(), TSSetIJacobian(), TSComputeIJacobianConstant(), TSComputeRHSFunctionLinear()
4506: @*/
4507: PetscErrorCode TSComputeIFunctionLinear(TS ts,PetscReal t,Vec U,Vec Udot,Vec F,void *ctx)
4508: {
4510: Mat A,B;
4513: TSGetIJacobian(ts,&A,&B,NULL,NULL);
4514: TSComputeIJacobian(ts,t,U,Udot,1.0,A,B,PETSC_TRUE);
4515: MatMult(A,Udot,F);
4516: return(0);
4517: }
4519: /*@C
4520: TSComputeIJacobianConstant - Reuses a time-independent for a semi-implicit DAE or ODE
4522: Collective on TS
4524: Input Parameters:
4525: + ts - time stepping context
4526: . t - time at which to evaluate
4527: . U - state at which to evaluate
4528: . Udot - time derivative of state vector
4529: . shift - shift to apply
4530: - ctx - context
4532: Output Parameters:
4533: + A - pointer to operator
4534: - B - pointer to preconditioning matrix
4536: Level: advanced
4538: Notes:
4539: This function is intended to be passed to TSSetIJacobian() to evaluate the Jacobian for linear time-independent problems.
4541: It is only appropriate for problems of the form
4543: $ M Udot = F(U,t)
4545: where M is constant and F is non-stiff. The user must pass M to TSSetIJacobian(). The current implementation only
4546: works with IMEX time integration methods such as TSROSW and TSARKIMEX, since there is no support for de-constructing
4547: an implicit operator of the form
4549: $ shift*M + J
4551: where J is the Jacobian of -F(U). Support may be added in a future version of PETSc, but for now, the user must store
4552: a copy of M or reassemble it when requested.
4554: .seealso: TSSetIFunction(), TSSetIJacobian(), TSComputeIFunctionLinear()
4555: @*/
4556: PetscErrorCode TSComputeIJacobianConstant(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat A,Mat B,void *ctx)
4557: {
4561: MatScale(A, shift / ts->ijacobian.shift);
4562: ts->ijacobian.shift = shift;
4563: return(0);
4564: }
4566: /*@
4567: TSGetEquationType - Gets the type of the equation that TS is solving.
4569: Not Collective
4571: Input Parameter:
4572: . ts - the TS context
4574: Output Parameter:
4575: . equation_type - see TSEquationType
4577: Level: beginner
4579: .seealso: TSSetEquationType(), TSEquationType
4580: @*/
4581: PetscErrorCode TSGetEquationType(TS ts,TSEquationType *equation_type)
4582: {
4586: *equation_type = ts->equation_type;
4587: return(0);
4588: }
4590: /*@
4591: TSSetEquationType - Sets the type of the equation that TS is solving.
4593: Not Collective
4595: Input Parameters:
4596: + ts - the TS context
4597: - equation_type - see TSEquationType
4599: Level: advanced
4601: .seealso: TSGetEquationType(), TSEquationType
4602: @*/
4603: PetscErrorCode TSSetEquationType(TS ts,TSEquationType equation_type)
4604: {
4607: ts->equation_type = equation_type;
4608: return(0);
4609: }
4611: /*@
4612: TSGetConvergedReason - Gets the reason the TS iteration was stopped.
4614: Not Collective
4616: Input Parameter:
4617: . ts - the TS context
4619: Output Parameter:
4620: . reason - negative value indicates diverged, positive value converged, see TSConvergedReason or the
4621: manual pages for the individual convergence tests for complete lists
4623: Level: beginner
4625: Notes:
4626: Can only be called after the call to TSSolve() is complete.
4628: .seealso: TSSetConvergenceTest(), TSConvergedReason
4629: @*/
4630: PetscErrorCode TSGetConvergedReason(TS ts,TSConvergedReason *reason)
4631: {
4635: *reason = ts->reason;
4636: return(0);
4637: }
4639: /*@
4640: TSSetConvergedReason - Sets the reason for handling the convergence of TSSolve.
4642: Logically Collective; reason must contain common value
4644: Input Parameters:
4645: + ts - the TS context
4646: - reason - negative value indicates diverged, positive value converged, see TSConvergedReason or the
4647: manual pages for the individual convergence tests for complete lists
4649: Level: advanced
4651: Notes:
4652: Can only be called while TSSolve() is active.
4654: .seealso: TSConvergedReason
4655: @*/
4656: PetscErrorCode TSSetConvergedReason(TS ts,TSConvergedReason reason)
4657: {
4660: ts->reason = reason;
4661: return(0);
4662: }
4664: /*@
4665: TSGetSolveTime - Gets the time after a call to TSSolve()
4667: Not Collective
4669: Input Parameter:
4670: . ts - the TS context
4672: Output Parameter:
4673: . ftime - the final time. This time corresponds to the final time set with TSSetMaxTime()
4675: Level: beginner
4677: Notes:
4678: Can only be called after the call to TSSolve() is complete.
4680: .seealso: TSSetConvergenceTest(), TSConvergedReason
4681: @*/
4682: PetscErrorCode TSGetSolveTime(TS ts,PetscReal *ftime)
4683: {
4687: *ftime = ts->solvetime;
4688: return(0);
4689: }
4691: /*@
4692: TSGetSNESIterations - Gets the total number of nonlinear iterations
4693: used by the time integrator.
4695: Not Collective
4697: Input Parameter:
4698: . ts - TS context
4700: Output Parameter:
4701: . nits - number of nonlinear iterations
4703: Notes:
4704: This counter is reset to zero for each successive call to TSSolve().
4706: Level: intermediate
4708: .seealso: TSGetKSPIterations()
4709: @*/
4710: PetscErrorCode TSGetSNESIterations(TS ts,PetscInt *nits)
4711: {
4715: *nits = ts->snes_its;
4716: return(0);
4717: }
4719: /*@
4720: TSGetKSPIterations - Gets the total number of linear iterations
4721: used by the time integrator.
4723: Not Collective
4725: Input Parameter:
4726: . ts - TS context
4728: Output Parameter:
4729: . lits - number of linear iterations
4731: Notes:
4732: This counter is reset to zero for each successive call to TSSolve().
4734: Level: intermediate
4736: .seealso: TSGetSNESIterations(), SNESGetKSPIterations()
4737: @*/
4738: PetscErrorCode TSGetKSPIterations(TS ts,PetscInt *lits)
4739: {
4743: *lits = ts->ksp_its;
4744: return(0);
4745: }
4747: /*@
4748: TSGetStepRejections - Gets the total number of rejected steps.
4750: Not Collective
4752: Input Parameter:
4753: . ts - TS context
4755: Output Parameter:
4756: . rejects - number of steps rejected
4758: Notes:
4759: This counter is reset to zero for each successive call to TSSolve().
4761: Level: intermediate
4763: .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetSNESFailures(), TSSetMaxSNESFailures(), TSSetErrorIfStepFails()
4764: @*/
4765: PetscErrorCode TSGetStepRejections(TS ts,PetscInt *rejects)
4766: {
4770: *rejects = ts->reject;
4771: return(0);
4772: }
4774: /*@
4775: TSGetSNESFailures - Gets the total number of failed SNES solves
4777: Not Collective
4779: Input Parameter:
4780: . ts - TS context
4782: Output Parameter:
4783: . fails - number of failed nonlinear solves
4785: Notes:
4786: This counter is reset to zero for each successive call to TSSolve().
4788: Level: intermediate
4790: .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSSetMaxSNESFailures()
4791: @*/
4792: PetscErrorCode TSGetSNESFailures(TS ts,PetscInt *fails)
4793: {
4797: *fails = ts->num_snes_failures;
4798: return(0);
4799: }
4801: /*@
4802: TSSetMaxStepRejections - Sets the maximum number of step rejections before a step fails
4804: Not Collective
4806: Input Parameters:
4807: + ts - TS context
4808: - rejects - maximum number of rejected steps, pass -1 for unlimited
4810: Notes:
4811: The counter is reset to zero for each step
4813: Options Database Key:
4814: . -ts_max_reject - Maximum number of step rejections before a step fails
4816: Level: intermediate
4818: .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxSNESFailures(), TSGetStepRejections(), TSGetSNESFailures(), TSSetErrorIfStepFails(), TSGetConvergedReason()
4819: @*/
4820: PetscErrorCode TSSetMaxStepRejections(TS ts,PetscInt rejects)
4821: {
4824: ts->max_reject = rejects;
4825: return(0);
4826: }
4828: /*@
4829: TSSetMaxSNESFailures - Sets the maximum number of failed SNES solves
4831: Not Collective
4833: Input Parameters:
4834: + ts - TS context
4835: - fails - maximum number of failed nonlinear solves, pass -1 for unlimited
4837: Notes:
4838: The counter is reset to zero for each successive call to TSSolve().
4840: Options Database Key:
4841: . -ts_max_snes_failures - Maximum number of nonlinear solve failures
4843: Level: intermediate
4845: .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSGetSNESFailures(), SNESGetConvergedReason(), TSGetConvergedReason()
4846: @*/
4847: PetscErrorCode TSSetMaxSNESFailures(TS ts,PetscInt fails)
4848: {
4851: ts->max_snes_failures = fails;
4852: return(0);
4853: }
4855: /*@
4856: TSSetErrorIfStepFails - Error if no step succeeds
4858: Not Collective
4860: Input Parameters:
4861: + ts - TS context
4862: - err - PETSC_TRUE to error if no step succeeds, PETSC_FALSE to return without failure
4864: Options Database Key:
4865: . -ts_error_if_step_fails - Error if no step succeeds
4867: Level: intermediate
4869: .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSGetSNESFailures(), TSSetErrorIfStepFails(), TSGetConvergedReason()
4870: @*/
4871: PetscErrorCode TSSetErrorIfStepFails(TS ts,PetscBool err)
4872: {
4875: ts->errorifstepfailed = err;
4876: return(0);
4877: }
4879: /*@
4880: TSGetAdapt - Get the adaptive controller context for the current method
4882: Collective on TS if controller has not been created yet
4884: Input Parameter:
4885: . ts - time stepping context
4887: Output Parameter:
4888: . adapt - adaptive controller
4890: Level: intermediate
4892: .seealso: TSAdapt, TSAdaptSetType(), TSAdaptChoose()
4893: @*/
4894: PetscErrorCode TSGetAdapt(TS ts,TSAdapt *adapt)
4895: {
4901: if (!ts->adapt) {
4902: TSAdaptCreate(PetscObjectComm((PetscObject)ts),&ts->adapt);
4903: PetscLogObjectParent((PetscObject)ts,(PetscObject)ts->adapt);
4904: PetscObjectIncrementTabLevel((PetscObject)ts->adapt,(PetscObject)ts,1);
4905: }
4906: *adapt = ts->adapt;
4907: return(0);
4908: }
4910: /*@
4911: TSSetTolerances - Set tolerances for local truncation error when using adaptive controller
4913: Logically Collective
4915: Input Parameters:
4916: + ts - time integration context
4917: . atol - scalar absolute tolerances, PETSC_DECIDE to leave current value
4918: . vatol - vector of absolute tolerances or NULL, used in preference to atol if present
4919: . rtol - scalar relative tolerances, PETSC_DECIDE to leave current value
4920: - vrtol - vector of relative tolerances or NULL, used in preference to atol if present
4922: Options Database keys:
4923: + -ts_rtol <rtol> - relative tolerance for local truncation error
4924: - -ts_atol <atol> Absolute tolerance for local truncation error
4926: Notes:
4927: With PETSc's implicit schemes for DAE problems, the calculation of the local truncation error
4928: (LTE) includes both the differential and the algebraic variables. If one wants the LTE to be
4929: computed only for the differential or the algebraic part then this can be done using the vector of
4930: tolerances vatol. For example, by setting the tolerance vector with the desired tolerance for the
4931: differential part and infinity for the algebraic part, the LTE calculation will include only the
4932: differential variables.
4934: Level: beginner
4936: .seealso: TS, TSAdapt, TSErrorWeightedNorm(), TSGetTolerances()
4937: @*/
4938: PetscErrorCode TSSetTolerances(TS ts,PetscReal atol,Vec vatol,PetscReal rtol,Vec vrtol)
4939: {
4943: if (atol != PETSC_DECIDE && atol != PETSC_DEFAULT) ts->atol = atol;
4944: if (vatol) {
4945: PetscObjectReference((PetscObject)vatol);
4946: VecDestroy(&ts->vatol);
4947: ts->vatol = vatol;
4948: }
4949: if (rtol != PETSC_DECIDE && rtol != PETSC_DEFAULT) ts->rtol = rtol;
4950: if (vrtol) {
4951: PetscObjectReference((PetscObject)vrtol);
4952: VecDestroy(&ts->vrtol);
4953: ts->vrtol = vrtol;
4954: }
4955: return(0);
4956: }
4958: /*@
4959: TSGetTolerances - Get tolerances for local truncation error when using adaptive controller
4961: Logically Collective
4963: Input Parameter:
4964: . ts - time integration context
4966: Output Parameters:
4967: + atol - scalar absolute tolerances, NULL to ignore
4968: . vatol - vector of absolute tolerances, NULL to ignore
4969: . rtol - scalar relative tolerances, NULL to ignore
4970: - vrtol - vector of relative tolerances, NULL to ignore
4972: Level: beginner
4974: .seealso: TS, TSAdapt, TSErrorWeightedNorm(), TSSetTolerances()
4975: @*/
4976: PetscErrorCode TSGetTolerances(TS ts,PetscReal *atol,Vec *vatol,PetscReal *rtol,Vec *vrtol)
4977: {
4979: if (atol) *atol = ts->atol;
4980: if (vatol) *vatol = ts->vatol;
4981: if (rtol) *rtol = ts->rtol;
4982: if (vrtol) *vrtol = ts->vrtol;
4983: return(0);
4984: }
4986: /*@
4987: TSErrorWeightedNorm2 - compute a weighted 2-norm of the difference between two state vectors
4989: Collective on TS
4991: Input Parameters:
4992: + ts - time stepping context
4993: . U - state vector, usually ts->vec_sol
4994: - Y - state vector to be compared to U
4996: Output Parameters:
4997: + norm - weighted norm, a value of 1.0 means that the error matches the tolerances
4998: . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances
4999: - normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances
5001: Level: developer
5003: .seealso: TSErrorWeightedNorm(), TSErrorWeightedNormInfinity()
5004: @*/
5005: PetscErrorCode TSErrorWeightedNorm2(TS ts,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr)
5006: {
5007: PetscErrorCode ierr;
5008: PetscInt i,n,N,rstart;
5009: PetscInt n_loc,na_loc,nr_loc;
5010: PetscReal n_glb,na_glb,nr_glb;
5011: const PetscScalar *u,*y;
5012: PetscReal sum,suma,sumr,gsum,gsuma,gsumr,diff;
5013: PetscReal tol,tola,tolr;
5014: PetscReal err_loc[6],err_glb[6];
5026: if (U == Y) SETERRQ(PetscObjectComm((PetscObject)U),PETSC_ERR_ARG_IDN,"U and Y cannot be the same vector");
5028: VecGetSize(U,&N);
5029: VecGetLocalSize(U,&n);
5030: VecGetOwnershipRange(U,&rstart,NULL);
5031: VecGetArrayRead(U,&u);
5032: VecGetArrayRead(Y,&y);
5033: sum = 0.; n_loc = 0;
5034: suma = 0.; na_loc = 0;
5035: sumr = 0.; nr_loc = 0;
5036: if (ts->vatol && ts->vrtol) {
5037: const PetscScalar *atol,*rtol;
5038: VecGetArrayRead(ts->vatol,&atol);
5039: VecGetArrayRead(ts->vrtol,&rtol);
5040: for (i=0; i<n; i++) {
5041: SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
5042: diff = PetscAbsScalar(y[i] - u[i]);
5043: tola = PetscRealPart(atol[i]);
5044: if (tola>0.) {
5045: suma += PetscSqr(diff/tola);
5046: na_loc++;
5047: }
5048: tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
5049: if (tolr>0.) {
5050: sumr += PetscSqr(diff/tolr);
5051: nr_loc++;
5052: }
5053: tol=tola+tolr;
5054: if (tol>0.) {
5055: sum += PetscSqr(diff/tol);
5056: n_loc++;
5057: }
5058: }
5059: VecRestoreArrayRead(ts->vatol,&atol);
5060: VecRestoreArrayRead(ts->vrtol,&rtol);
5061: } else if (ts->vatol) { /* vector atol, scalar rtol */
5062: const PetscScalar *atol;
5063: VecGetArrayRead(ts->vatol,&atol);
5064: for (i=0; i<n; i++) {
5065: SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
5066: diff = PetscAbsScalar(y[i] - u[i]);
5067: tola = PetscRealPart(atol[i]);
5068: if (tola>0.) {
5069: suma += PetscSqr(diff/tola);
5070: na_loc++;
5071: }
5072: tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
5073: if (tolr>0.) {
5074: sumr += PetscSqr(diff/tolr);
5075: nr_loc++;
5076: }
5077: tol=tola+tolr;
5078: if (tol>0.) {
5079: sum += PetscSqr(diff/tol);
5080: n_loc++;
5081: }
5082: }
5083: VecRestoreArrayRead(ts->vatol,&atol);
5084: } else if (ts->vrtol) { /* scalar atol, vector rtol */
5085: const PetscScalar *rtol;
5086: VecGetArrayRead(ts->vrtol,&rtol);
5087: for (i=0; i<n; i++) {
5088: SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
5089: diff = PetscAbsScalar(y[i] - u[i]);
5090: tola = ts->atol;
5091: if (tola>0.) {
5092: suma += PetscSqr(diff/tola);
5093: na_loc++;
5094: }
5095: tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
5096: if (tolr>0.) {
5097: sumr += PetscSqr(diff/tolr);
5098: nr_loc++;
5099: }
5100: tol=tola+tolr;
5101: if (tol>0.) {
5102: sum += PetscSqr(diff/tol);
5103: n_loc++;
5104: }
5105: }
5106: VecRestoreArrayRead(ts->vrtol,&rtol);
5107: } else { /* scalar atol, scalar rtol */
5108: for (i=0; i<n; i++) {
5109: SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
5110: diff = PetscAbsScalar(y[i] - u[i]);
5111: tola = ts->atol;
5112: if (tola>0.) {
5113: suma += PetscSqr(diff/tola);
5114: na_loc++;
5115: }
5116: tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
5117: if (tolr>0.) {
5118: sumr += PetscSqr(diff/tolr);
5119: nr_loc++;
5120: }
5121: tol=tola+tolr;
5122: if (tol>0.) {
5123: sum += PetscSqr(diff/tol);
5124: n_loc++;
5125: }
5126: }
5127: }
5128: VecRestoreArrayRead(U,&u);
5129: VecRestoreArrayRead(Y,&y);
5131: err_loc[0] = sum;
5132: err_loc[1] = suma;
5133: err_loc[2] = sumr;
5134: err_loc[3] = (PetscReal)n_loc;
5135: err_loc[4] = (PetscReal)na_loc;
5136: err_loc[5] = (PetscReal)nr_loc;
5138: MPIU_Allreduce(err_loc,err_glb,6,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)ts));
5140: gsum = err_glb[0];
5141: gsuma = err_glb[1];
5142: gsumr = err_glb[2];
5143: n_glb = err_glb[3];
5144: na_glb = err_glb[4];
5145: nr_glb = err_glb[5];
5147: *norm = 0.;
5148: if (n_glb>0.) {*norm = PetscSqrtReal(gsum / n_glb);}
5149: *norma = 0.;
5150: if (na_glb>0.) {*norma = PetscSqrtReal(gsuma / na_glb);}
5151: *normr = 0.;
5152: if (nr_glb>0.) {*normr = PetscSqrtReal(gsumr / nr_glb);}
5154: if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm");
5155: if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma");
5156: if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr");
5157: return(0);
5158: }
5160: /*@
5161: TSErrorWeightedNormInfinity - compute a weighted infinity-norm of the difference between two state vectors
5163: Collective on TS
5165: Input Parameters:
5166: + ts - time stepping context
5167: . U - state vector, usually ts->vec_sol
5168: - Y - state vector to be compared to U
5170: Output Parameters:
5171: + norm - weighted norm, a value of 1.0 means that the error matches the tolerances
5172: . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances
5173: - normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances
5175: Level: developer
5177: .seealso: TSErrorWeightedNorm(), TSErrorWeightedNorm2()
5178: @*/
5179: PetscErrorCode TSErrorWeightedNormInfinity(TS ts,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr)
5180: {
5181: PetscErrorCode ierr;
5182: PetscInt i,n,N,rstart;
5183: const PetscScalar *u,*y;
5184: PetscReal max,gmax,maxa,gmaxa,maxr,gmaxr;
5185: PetscReal tol,tola,tolr,diff;
5186: PetscReal err_loc[3],err_glb[3];
5198: if (U == Y) SETERRQ(PetscObjectComm((PetscObject)U),PETSC_ERR_ARG_IDN,"U and Y cannot be the same vector");
5200: VecGetSize(U,&N);
5201: VecGetLocalSize(U,&n);
5202: VecGetOwnershipRange(U,&rstart,NULL);
5203: VecGetArrayRead(U,&u);
5204: VecGetArrayRead(Y,&y);
5206: max=0.;
5207: maxa=0.;
5208: maxr=0.;
5210: if (ts->vatol && ts->vrtol) { /* vector atol, vector rtol */
5211: const PetscScalar *atol,*rtol;
5212: VecGetArrayRead(ts->vatol,&atol);
5213: VecGetArrayRead(ts->vrtol,&rtol);
5215: for (i=0; i<n; i++) {
5216: SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
5217: diff = PetscAbsScalar(y[i] - u[i]);
5218: tola = PetscRealPart(atol[i]);
5219: tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
5220: tol = tola+tolr;
5221: if (tola>0.) {
5222: maxa = PetscMax(maxa,diff / tola);
5223: }
5224: if (tolr>0.) {
5225: maxr = PetscMax(maxr,diff / tolr);
5226: }
5227: if (tol>0.) {
5228: max = PetscMax(max,diff / tol);
5229: }
5230: }
5231: VecRestoreArrayRead(ts->vatol,&atol);
5232: VecRestoreArrayRead(ts->vrtol,&rtol);
5233: } else if (ts->vatol) { /* vector atol, scalar rtol */
5234: const PetscScalar *atol;
5235: VecGetArrayRead(ts->vatol,&atol);
5236: for (i=0; i<n; i++) {
5237: SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
5238: diff = PetscAbsScalar(y[i] - u[i]);
5239: tola = PetscRealPart(atol[i]);
5240: tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
5241: tol = tola+tolr;
5242: if (tola>0.) {
5243: maxa = PetscMax(maxa,diff / tola);
5244: }
5245: if (tolr>0.) {
5246: maxr = PetscMax(maxr,diff / tolr);
5247: }
5248: if (tol>0.) {
5249: max = PetscMax(max,diff / tol);
5250: }
5251: }
5252: VecRestoreArrayRead(ts->vatol,&atol);
5253: } else if (ts->vrtol) { /* scalar atol, vector rtol */
5254: const PetscScalar *rtol;
5255: VecGetArrayRead(ts->vrtol,&rtol);
5257: for (i=0; i<n; i++) {
5258: SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
5259: diff = PetscAbsScalar(y[i] - u[i]);
5260: tola = ts->atol;
5261: tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
5262: tol = tola+tolr;
5263: if (tola>0.) {
5264: maxa = PetscMax(maxa,diff / tola);
5265: }
5266: if (tolr>0.) {
5267: maxr = PetscMax(maxr,diff / tolr);
5268: }
5269: if (tol>0.) {
5270: max = PetscMax(max,diff / tol);
5271: }
5272: }
5273: VecRestoreArrayRead(ts->vrtol,&rtol);
5274: } else { /* scalar atol, scalar rtol */
5276: for (i=0; i<n; i++) {
5277: SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
5278: diff = PetscAbsScalar(y[i] - u[i]);
5279: tola = ts->atol;
5280: tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
5281: tol = tola+tolr;
5282: if (tola>0.) {
5283: maxa = PetscMax(maxa,diff / tola);
5284: }
5285: if (tolr>0.) {
5286: maxr = PetscMax(maxr,diff / tolr);
5287: }
5288: if (tol>0.) {
5289: max = PetscMax(max,diff / tol);
5290: }
5291: }
5292: }
5293: VecRestoreArrayRead(U,&u);
5294: VecRestoreArrayRead(Y,&y);
5295: err_loc[0] = max;
5296: err_loc[1] = maxa;
5297: err_loc[2] = maxr;
5298: MPIU_Allreduce(err_loc,err_glb,3,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)ts));
5299: gmax = err_glb[0];
5300: gmaxa = err_glb[1];
5301: gmaxr = err_glb[2];
5303: *norm = gmax;
5304: *norma = gmaxa;
5305: *normr = gmaxr;
5306: if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm");
5307: if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma");
5308: if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr");
5309: return(0);
5310: }
5312: /*@
5313: TSErrorWeightedNorm - compute a weighted norm of the difference between two state vectors based on supplied absolute and relative tolerances
5315: Collective on TS
5317: Input Parameters:
5318: + ts - time stepping context
5319: . U - state vector, usually ts->vec_sol
5320: . Y - state vector to be compared to U
5321: - wnormtype - norm type, either NORM_2 or NORM_INFINITY
5323: Output Parameters:
5324: + norm - weighted norm, a value of 1.0 achieves a balance between absolute and relative tolerances
5325: . norma - weighted norm, a value of 1.0 means that the error meets the absolute tolerance set by the user
5326: - normr - weighted norm, a value of 1.0 means that the error meets the relative tolerance set by the user
5328: Options Database Keys:
5329: . -ts_adapt_wnormtype <wnormtype> - 2, INFINITY
5331: Level: developer
5333: .seealso: TSErrorWeightedNormInfinity(), TSErrorWeightedNorm2(), TSErrorWeightedENorm
5334: @*/
5335: PetscErrorCode TSErrorWeightedNorm(TS ts,Vec U,Vec Y,NormType wnormtype,PetscReal *norm,PetscReal *norma,PetscReal *normr)
5336: {
5340: if (wnormtype == NORM_2) {
5341: TSErrorWeightedNorm2(ts,U,Y,norm,norma,normr);
5342: } else if (wnormtype == NORM_INFINITY) {
5343: TSErrorWeightedNormInfinity(ts,U,Y,norm,norma,normr);
5344: } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]);
5345: return(0);
5346: }
5348: /*@
5349: TSErrorWeightedENorm2 - compute a weighted 2 error norm based on supplied absolute and relative tolerances
5351: Collective on TS
5353: Input Parameters:
5354: + ts - time stepping context
5355: . E - error vector
5356: . U - state vector, usually ts->vec_sol
5357: - Y - state vector, previous time step
5359: Output Parameters:
5360: + norm - weighted norm, a value of 1.0 means that the error matches the tolerances
5361: . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances
5362: - normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances
5364: Level: developer
5366: .seealso: TSErrorWeightedENorm(), TSErrorWeightedENormInfinity()
5367: @*/
5368: PetscErrorCode TSErrorWeightedENorm2(TS ts,Vec E,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr)
5369: {
5370: PetscErrorCode ierr;
5371: PetscInt i,n,N,rstart;
5372: PetscInt n_loc,na_loc,nr_loc;
5373: PetscReal n_glb,na_glb,nr_glb;
5374: const PetscScalar *e,*u,*y;
5375: PetscReal err,sum,suma,sumr,gsum,gsuma,gsumr;
5376: PetscReal tol,tola,tolr;
5377: PetscReal err_loc[6],err_glb[6];
5393: VecGetSize(E,&N);
5394: VecGetLocalSize(E,&n);
5395: VecGetOwnershipRange(E,&rstart,NULL);
5396: VecGetArrayRead(E,&e);
5397: VecGetArrayRead(U,&u);
5398: VecGetArrayRead(Y,&y);
5399: sum = 0.; n_loc = 0;
5400: suma = 0.; na_loc = 0;
5401: sumr = 0.; nr_loc = 0;
5402: if (ts->vatol && ts->vrtol) {
5403: const PetscScalar *atol,*rtol;
5404: VecGetArrayRead(ts->vatol,&atol);
5405: VecGetArrayRead(ts->vrtol,&rtol);
5406: for (i=0; i<n; i++) {
5407: SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
5408: err = PetscAbsScalar(e[i]);
5409: tola = PetscRealPart(atol[i]);
5410: if (tola>0.) {
5411: suma += PetscSqr(err/tola);
5412: na_loc++;
5413: }
5414: tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
5415: if (tolr>0.) {
5416: sumr += PetscSqr(err/tolr);
5417: nr_loc++;
5418: }
5419: tol=tola+tolr;
5420: if (tol>0.) {
5421: sum += PetscSqr(err/tol);
5422: n_loc++;
5423: }
5424: }
5425: VecRestoreArrayRead(ts->vatol,&atol);
5426: VecRestoreArrayRead(ts->vrtol,&rtol);
5427: } else if (ts->vatol) { /* vector atol, scalar rtol */
5428: const PetscScalar *atol;
5429: VecGetArrayRead(ts->vatol,&atol);
5430: for (i=0; i<n; i++) {
5431: SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
5432: err = PetscAbsScalar(e[i]);
5433: tola = PetscRealPart(atol[i]);
5434: if (tola>0.) {
5435: suma += PetscSqr(err/tola);
5436: na_loc++;
5437: }
5438: tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
5439: if (tolr>0.) {
5440: sumr += PetscSqr(err/tolr);
5441: nr_loc++;
5442: }
5443: tol=tola+tolr;
5444: if (tol>0.) {
5445: sum += PetscSqr(err/tol);
5446: n_loc++;
5447: }
5448: }
5449: VecRestoreArrayRead(ts->vatol,&atol);
5450: } else if (ts->vrtol) { /* scalar atol, vector rtol */
5451: const PetscScalar *rtol;
5452: VecGetArrayRead(ts->vrtol,&rtol);
5453: for (i=0; i<n; i++) {
5454: SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
5455: err = PetscAbsScalar(e[i]);
5456: tola = ts->atol;
5457: if (tola>0.) {
5458: suma += PetscSqr(err/tola);
5459: na_loc++;
5460: }
5461: tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
5462: if (tolr>0.) {
5463: sumr += PetscSqr(err/tolr);
5464: nr_loc++;
5465: }
5466: tol=tola+tolr;
5467: if (tol>0.) {
5468: sum += PetscSqr(err/tol);
5469: n_loc++;
5470: }
5471: }
5472: VecRestoreArrayRead(ts->vrtol,&rtol);
5473: } else { /* scalar atol, scalar rtol */
5474: for (i=0; i<n; i++) {
5475: SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
5476: err = PetscAbsScalar(e[i]);
5477: tola = ts->atol;
5478: if (tola>0.) {
5479: suma += PetscSqr(err/tola);
5480: na_loc++;
5481: }
5482: tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
5483: if (tolr>0.) {
5484: sumr += PetscSqr(err/tolr);
5485: nr_loc++;
5486: }
5487: tol=tola+tolr;
5488: if (tol>0.) {
5489: sum += PetscSqr(err/tol);
5490: n_loc++;
5491: }
5492: }
5493: }
5494: VecRestoreArrayRead(E,&e);
5495: VecRestoreArrayRead(U,&u);
5496: VecRestoreArrayRead(Y,&y);
5498: err_loc[0] = sum;
5499: err_loc[1] = suma;
5500: err_loc[2] = sumr;
5501: err_loc[3] = (PetscReal)n_loc;
5502: err_loc[4] = (PetscReal)na_loc;
5503: err_loc[5] = (PetscReal)nr_loc;
5505: MPIU_Allreduce(err_loc,err_glb,6,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)ts));
5507: gsum = err_glb[0];
5508: gsuma = err_glb[1];
5509: gsumr = err_glb[2];
5510: n_glb = err_glb[3];
5511: na_glb = err_glb[4];
5512: nr_glb = err_glb[5];
5514: *norm = 0.;
5515: if (n_glb>0.) {*norm = PetscSqrtReal(gsum / n_glb);}
5516: *norma = 0.;
5517: if (na_glb>0.) {*norma = PetscSqrtReal(gsuma / na_glb);}
5518: *normr = 0.;
5519: if (nr_glb>0.) {*normr = PetscSqrtReal(gsumr / nr_glb);}
5521: if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm");
5522: if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma");
5523: if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr");
5524: return(0);
5525: }
5527: /*@
5528: TSErrorWeightedENormInfinity - compute a weighted infinity error norm based on supplied absolute and relative tolerances
5529: Collective on TS
5531: Input Parameters:
5532: + ts - time stepping context
5533: . E - error vector
5534: . U - state vector, usually ts->vec_sol
5535: - Y - state vector, previous time step
5537: Output Parameters:
5538: + norm - weighted norm, a value of 1.0 means that the error matches the tolerances
5539: . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances
5540: - normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances
5542: Level: developer
5544: .seealso: TSErrorWeightedENorm(), TSErrorWeightedENorm2()
5545: @*/
5546: PetscErrorCode TSErrorWeightedENormInfinity(TS ts,Vec E,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr)
5547: {
5548: PetscErrorCode ierr;
5549: PetscInt i,n,N,rstart;
5550: const PetscScalar *e,*u,*y;
5551: PetscReal err,max,gmax,maxa,gmaxa,maxr,gmaxr;
5552: PetscReal tol,tola,tolr;
5553: PetscReal err_loc[3],err_glb[3];
5569: VecGetSize(E,&N);
5570: VecGetLocalSize(E,&n);
5571: VecGetOwnershipRange(E,&rstart,NULL);
5572: VecGetArrayRead(E,&e);
5573: VecGetArrayRead(U,&u);
5574: VecGetArrayRead(Y,&y);
5576: max=0.;
5577: maxa=0.;
5578: maxr=0.;
5580: if (ts->vatol && ts->vrtol) { /* vector atol, vector rtol */
5581: const PetscScalar *atol,*rtol;
5582: VecGetArrayRead(ts->vatol,&atol);
5583: VecGetArrayRead(ts->vrtol,&rtol);
5585: for (i=0; i<n; i++) {
5586: SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
5587: err = PetscAbsScalar(e[i]);
5588: tola = PetscRealPart(atol[i]);
5589: tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
5590: tol = tola+tolr;
5591: if (tola>0.) {
5592: maxa = PetscMax(maxa,err / tola);
5593: }
5594: if (tolr>0.) {
5595: maxr = PetscMax(maxr,err / tolr);
5596: }
5597: if (tol>0.) {
5598: max = PetscMax(max,err / tol);
5599: }
5600: }
5601: VecRestoreArrayRead(ts->vatol,&atol);
5602: VecRestoreArrayRead(ts->vrtol,&rtol);
5603: } else if (ts->vatol) { /* vector atol, scalar rtol */
5604: const PetscScalar *atol;
5605: VecGetArrayRead(ts->vatol,&atol);
5606: for (i=0; i<n; i++) {
5607: SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
5608: err = PetscAbsScalar(e[i]);
5609: tola = PetscRealPart(atol[i]);
5610: tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
5611: tol = tola+tolr;
5612: if (tola>0.) {
5613: maxa = PetscMax(maxa,err / tola);
5614: }
5615: if (tolr>0.) {
5616: maxr = PetscMax(maxr,err / tolr);
5617: }
5618: if (tol>0.) {
5619: max = PetscMax(max,err / tol);
5620: }
5621: }
5622: VecRestoreArrayRead(ts->vatol,&atol);
5623: } else if (ts->vrtol) { /* scalar atol, vector rtol */
5624: const PetscScalar *rtol;
5625: VecGetArrayRead(ts->vrtol,&rtol);
5627: for (i=0; i<n; i++) {
5628: SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
5629: err = PetscAbsScalar(e[i]);
5630: tola = ts->atol;
5631: tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
5632: tol = tola+tolr;
5633: if (tola>0.) {
5634: maxa = PetscMax(maxa,err / tola);
5635: }
5636: if (tolr>0.) {
5637: maxr = PetscMax(maxr,err / tolr);
5638: }
5639: if (tol>0.) {
5640: max = PetscMax(max,err / tol);
5641: }
5642: }
5643: VecRestoreArrayRead(ts->vrtol,&rtol);
5644: } else { /* scalar atol, scalar rtol */
5646: for (i=0; i<n; i++) {
5647: SkipSmallValue(y[i],u[i],ts->adapt->ignore_max);
5648: err = PetscAbsScalar(e[i]);
5649: tola = ts->atol;
5650: tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
5651: tol = tola+tolr;
5652: if (tola>0.) {
5653: maxa = PetscMax(maxa,err / tola);
5654: }
5655: if (tolr>0.) {
5656: maxr = PetscMax(maxr,err / tolr);
5657: }
5658: if (tol>0.) {
5659: max = PetscMax(max,err / tol);
5660: }
5661: }
5662: }
5663: VecRestoreArrayRead(E,&e);
5664: VecRestoreArrayRead(U,&u);
5665: VecRestoreArrayRead(Y,&y);
5666: err_loc[0] = max;
5667: err_loc[1] = maxa;
5668: err_loc[2] = maxr;
5669: MPIU_Allreduce(err_loc,err_glb,3,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)ts));
5670: gmax = err_glb[0];
5671: gmaxa = err_glb[1];
5672: gmaxr = err_glb[2];
5674: *norm = gmax;
5675: *norma = gmaxa;
5676: *normr = gmaxr;
5677: if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm");
5678: if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma");
5679: if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr");
5680: return(0);
5681: }
5683: /*@
5684: TSErrorWeightedENorm - compute a weighted error norm based on supplied absolute and relative tolerances
5686: Collective on TS
5688: Input Parameters:
5689: + ts - time stepping context
5690: . E - error vector
5691: . U - state vector, usually ts->vec_sol
5692: . Y - state vector, previous time step
5693: - wnormtype - norm type, either NORM_2 or NORM_INFINITY
5695: Output Parameters:
5696: + norm - weighted norm, a value of 1.0 achieves a balance between absolute and relative tolerances
5697: . norma - weighted norm, a value of 1.0 means that the error meets the absolute tolerance set by the user
5698: - normr - weighted norm, a value of 1.0 means that the error meets the relative tolerance set by the user
5700: Options Database Keys:
5701: . -ts_adapt_wnormtype <wnormtype> - 2, INFINITY
5703: Level: developer
5705: .seealso: TSErrorWeightedENormInfinity(), TSErrorWeightedENorm2(), TSErrorWeightedNormInfinity(), TSErrorWeightedNorm2()
5706: @*/
5707: PetscErrorCode TSErrorWeightedENorm(TS ts,Vec E,Vec U,Vec Y,NormType wnormtype,PetscReal *norm,PetscReal *norma,PetscReal *normr)
5708: {
5712: if (wnormtype == NORM_2) {
5713: TSErrorWeightedENorm2(ts,E,U,Y,norm,norma,normr);
5714: } else if (wnormtype == NORM_INFINITY) {
5715: TSErrorWeightedENormInfinity(ts,E,U,Y,norm,norma,normr);
5716: } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]);
5717: return(0);
5718: }
5720: /*@
5721: TSSetCFLTimeLocal - Set the local CFL constraint relative to forward Euler
5723: Logically Collective on TS
5725: Input Parameters:
5726: + ts - time stepping context
5727: - cfltime - maximum stable time step if using forward Euler (value can be different on each process)
5729: Note:
5730: After calling this function, the global CFL time can be obtained by calling TSGetCFLTime()
5732: Level: intermediate
5734: .seealso: TSGetCFLTime(), TSADAPTCFL
5735: @*/
5736: PetscErrorCode TSSetCFLTimeLocal(TS ts,PetscReal cfltime)
5737: {
5740: ts->cfltime_local = cfltime;
5741: ts->cfltime = -1.;
5742: return(0);
5743: }
5745: /*@
5746: TSGetCFLTime - Get the maximum stable time step according to CFL criteria applied to forward Euler
5748: Collective on TS
5750: Input Parameter:
5751: . ts - time stepping context
5753: Output Parameter:
5754: . cfltime - maximum stable time step for forward Euler
5756: Level: advanced
5758: .seealso: TSSetCFLTimeLocal()
5759: @*/
5760: PetscErrorCode TSGetCFLTime(TS ts,PetscReal *cfltime)
5761: {
5765: if (ts->cfltime < 0) {
5766: MPIU_Allreduce(&ts->cfltime_local,&ts->cfltime,1,MPIU_REAL,MPIU_MIN,PetscObjectComm((PetscObject)ts));
5767: }
5768: *cfltime = ts->cfltime;
5769: return(0);
5770: }
5772: /*@
5773: TSVISetVariableBounds - Sets the lower and upper bounds for the solution vector. xl <= x <= xu
5775: Input Parameters:
5776: + ts - the TS context.
5777: . xl - lower bound.
5778: - xu - upper bound.
5780: Notes:
5781: If this routine is not called then the lower and upper bounds are set to
5782: PETSC_NINFINITY and PETSC_INFINITY respectively during SNESSetUp().
5784: Level: advanced
5786: @*/
5787: PetscErrorCode TSVISetVariableBounds(TS ts, Vec xl, Vec xu)
5788: {
5790: SNES snes;
5793: TSGetSNES(ts,&snes);
5794: SNESVISetVariableBounds(snes,xl,xu);
5795: return(0);
5796: }
5798: /*@
5799: TSComputeLinearStability - computes the linear stability function at a point
5801: Collective on TS
5803: Input Parameters:
5804: + ts - the TS context
5805: - xr,xi - real and imaginary part of input arguments
5807: Output Parameters:
5808: . yr,yi - real and imaginary part of function value
5810: Level: developer
5812: .seealso: TSSetRHSFunction(), TSComputeIFunction()
5813: @*/
5814: PetscErrorCode TSComputeLinearStability(TS ts,PetscReal xr,PetscReal xi,PetscReal *yr,PetscReal *yi)
5815: {
5820: if (!ts->ops->linearstability) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Linearized stability function not provided for this method");
5821: (*ts->ops->linearstability)(ts,xr,xi,yr,yi);
5822: return(0);
5823: }
5825: /*@
5826: TSRestartStep - Flags the solver to restart the next step
5828: Collective on TS
5830: Input Parameter:
5831: . ts - the TS context obtained from TSCreate()
5833: Level: advanced
5835: Notes:
5836: Multistep methods like BDF or Runge-Kutta methods with FSAL property require restarting the solver in the event of
5837: discontinuities. These discontinuities may be introduced as a consequence of explicitly modifications to the solution
5838: vector (which PETSc attempts to detect and handle) or problem coefficients (which PETSc is not able to detect). For
5839: the sake of correctness and maximum safety, users are expected to call TSRestart() whenever they introduce
5840: discontinuities in callback routines (e.g. prestep and poststep routines, or implicit/rhs function routines with
5841: discontinuous source terms).
5843: .seealso: TSSolve(), TSSetPreStep(), TSSetPostStep()
5844: @*/
5845: PetscErrorCode TSRestartStep(TS ts)
5846: {
5849: ts->steprestart = PETSC_TRUE;
5850: return(0);
5851: }
5853: /*@
5854: TSRollBack - Rolls back one time step
5856: Collective on TS
5858: Input Parameter:
5859: . ts - the TS context obtained from TSCreate()
5861: Level: advanced
5863: .seealso: TSCreate(), TSSetUp(), TSDestroy(), TSSolve(), TSSetPreStep(), TSSetPreStage(), TSInterpolate()
5864: @*/
5865: PetscErrorCode TSRollBack(TS ts)
5866: {
5871: if (ts->steprollback) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"TSRollBack already called");
5872: if (!ts->ops->rollback) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSRollBack not implemented for type '%s'",((PetscObject)ts)->type_name);
5873: (*ts->ops->rollback)(ts);
5874: ts->time_step = ts->ptime - ts->ptime_prev;
5875: ts->ptime = ts->ptime_prev;
5876: ts->ptime_prev = ts->ptime_prev_rollback;
5877: ts->steps--;
5878: ts->steprollback = PETSC_TRUE;
5879: return(0);
5880: }
5882: /*@
5883: TSGetStages - Get the number of stages and stage values
5885: Input Parameter:
5886: . ts - the TS context obtained from TSCreate()
5888: Output Parameters:
5889: + ns - the number of stages
5890: - Y - the current stage vectors
5892: Level: advanced
5894: Notes: Both ns and Y can be NULL.
5896: .seealso: TSCreate()
5897: @*/
5898: PetscErrorCode TSGetStages(TS ts,PetscInt *ns,Vec **Y)
5899: {
5906: if (!ts->ops->getstages) {
5907: if (ns) *ns = 0;
5908: if (Y) *Y = NULL;
5909: } else {
5910: (*ts->ops->getstages)(ts,ns,Y);
5911: }
5912: return(0);
5913: }
5915: /*@C
5916: TSComputeIJacobianDefaultColor - Computes the Jacobian using finite differences and coloring to exploit matrix sparsity.
5918: Collective on SNES
5920: Input Parameters:
5921: + ts - the TS context
5922: . t - current timestep
5923: . U - state vector
5924: . Udot - time derivative of state vector
5925: . shift - shift to apply, see note below
5926: - ctx - an optional user context
5928: Output Parameters:
5929: + J - Jacobian matrix (not altered in this routine)
5930: - B - newly computed Jacobian matrix to use with preconditioner (generally the same as J)
5932: Level: intermediate
5934: Notes:
5935: If F(t,U,Udot)=0 is the DAE, the required Jacobian is
5937: dF/dU + shift*dF/dUdot
5939: Most users should not need to explicitly call this routine, as it
5940: is used internally within the nonlinear solvers.
5942: This will first try to get the coloring from the DM. If the DM type has no coloring
5943: routine, then it will try to get the coloring from the matrix. This requires that the
5944: matrix have nonzero entries precomputed.
5946: .seealso: TSSetIJacobian(), MatFDColoringCreate(), MatFDColoringSetFunction()
5947: @*/
5948: PetscErrorCode TSComputeIJacobianDefaultColor(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat J,Mat B,void *ctx)
5949: {
5950: SNES snes;
5951: MatFDColoring color;
5952: PetscBool hascolor, matcolor = PETSC_FALSE;
5956: PetscOptionsGetBool(((PetscObject)ts)->options,((PetscObject) ts)->prefix, "-ts_fd_color_use_mat", &matcolor, NULL);
5957: PetscObjectQuery((PetscObject) B, "TSMatFDColoring", (PetscObject *) &color);
5958: if (!color) {
5959: DM dm;
5960: ISColoring iscoloring;
5962: TSGetDM(ts, &dm);
5963: DMHasColoring(dm, &hascolor);
5964: if (hascolor && !matcolor) {
5965: DMCreateColoring(dm, IS_COLORING_GLOBAL, &iscoloring);
5966: MatFDColoringCreate(B, iscoloring, &color);
5967: MatFDColoringSetFunction(color, (PetscErrorCode (*)(void)) SNESTSFormFunction, (void *) ts);
5968: MatFDColoringSetFromOptions(color);
5969: MatFDColoringSetUp(B, iscoloring, color);
5970: ISColoringDestroy(&iscoloring);
5971: } else {
5972: MatColoring mc;
5974: MatColoringCreate(B, &mc);
5975: MatColoringSetDistance(mc, 2);
5976: MatColoringSetType(mc, MATCOLORINGSL);
5977: MatColoringSetFromOptions(mc);
5978: MatColoringApply(mc, &iscoloring);
5979: MatColoringDestroy(&mc);
5980: MatFDColoringCreate(B, iscoloring, &color);
5981: MatFDColoringSetFunction(color, (PetscErrorCode (*)(void)) SNESTSFormFunction, (void *) ts);
5982: MatFDColoringSetFromOptions(color);
5983: MatFDColoringSetUp(B, iscoloring, color);
5984: ISColoringDestroy(&iscoloring);
5985: }
5986: PetscObjectCompose((PetscObject) B, "TSMatFDColoring", (PetscObject) color);
5987: PetscObjectDereference((PetscObject) color);
5988: }
5989: TSGetSNES(ts, &snes);
5990: MatFDColoringApply(B, color, U, snes);
5991: if (J != B) {
5992: MatAssemblyBegin(J, MAT_FINAL_ASSEMBLY);
5993: MatAssemblyEnd(J, MAT_FINAL_ASSEMBLY);
5994: }
5995: return(0);
5996: }
5998: /*@
5999: TSSetFunctionDomainError - Set a function that tests if the current state vector is valid
6001: Input Parameters:
6002: + ts - the TS context
6003: - func - function called within TSFunctionDomainError
6005: Calling sequence of func:
6006: $ PetscErrorCode func(TS ts,PetscReal time,Vec state,PetscBool reject)
6008: + ts - the TS context
6009: . time - the current time (of the stage)
6010: . state - the state to check if it is valid
6011: - reject - (output parameter) PETSC_FALSE if the state is acceptable, PETSC_TRUE if not acceptable
6013: Level: intermediate
6015: Notes:
6016: If an implicit ODE solver is being used then, in addition to providing this routine, the
6017: user's code should call SNESSetFunctionDomainError() when domain errors occur during
6018: function evaluations where the functions are provided by TSSetIFunction() or TSSetRHSFunction().
6019: Use TSGetSNES() to obtain the SNES object
6021: Developer Notes:
6022: The naming of this function is inconsistent with the SNESSetFunctionDomainError()
6023: since one takes a function pointer and the other does not.
6025: .seealso: TSAdaptCheckStage(), TSFunctionDomainError(), SNESSetFunctionDomainError(), TSGetSNES()
6026: @*/
6028: PetscErrorCode TSSetFunctionDomainError(TS ts, PetscErrorCode (*func)(TS,PetscReal,Vec,PetscBool*))
6029: {
6032: ts->functiondomainerror = func;
6033: return(0);
6034: }
6036: /*@
6037: TSFunctionDomainError - Checks if the current state is valid
6039: Input Parameters:
6040: + ts - the TS context
6041: . stagetime - time of the simulation
6042: - Y - state vector to check.
6044: Output Parameter:
6045: . accept - Set to PETSC_FALSE if the current state vector is valid.
6047: Note:
6048: This function is called by the TS integration routines and calls the user provided function (set with TSSetFunctionDomainError())
6049: to check if the current state is valid.
6051: Level: developer
6053: .seealso: TSSetFunctionDomainError()
6054: @*/
6055: PetscErrorCode TSFunctionDomainError(TS ts,PetscReal stagetime,Vec Y,PetscBool* accept)
6056: {
6059: *accept = PETSC_TRUE;
6060: if (ts->functiondomainerror) {
6061: PetscStackCallStandard((*ts->functiondomainerror),(ts,stagetime,Y,accept));
6062: }
6063: return(0);
6064: }
6066: /*@C
6067: TSClone - This function clones a time step object.
6069: Collective
6071: Input Parameter:
6072: . tsin - The input TS
6074: Output Parameter:
6075: . tsout - The output TS (cloned)
6077: Notes:
6078: This function is used to create a clone of a TS object. It is used in ARKIMEX for initializing the slope for first stage explicit methods. It will likely be replaced in the future with a mechanism of switching methods on the fly.
6080: When using TSDestroy() on a clone the user has to first reset the correct TS reference in the embedded SNES object: e.g.: by running SNES snes_dup=NULL; TSGetSNES(ts,&snes_dup); TSSetSNES(ts,snes_dup);
6082: Level: developer
6084: .seealso: TSCreate(), TSSetType(), TSSetUp(), TSDestroy(), TSSetProblemType()
6085: @*/
6086: PetscErrorCode TSClone(TS tsin, TS *tsout)
6087: {
6088: TS t;
6090: SNES snes_start;
6091: DM dm;
6092: TSType type;
6096: *tsout = NULL;
6098: PetscHeaderCreate(t, TS_CLASSID, "TS", "Time stepping", "TS", PetscObjectComm((PetscObject)tsin), TSDestroy, TSView);
6100: /* General TS description */
6101: t->numbermonitors = 0;
6102: t->monitorFrequency = 1;
6103: t->setupcalled = 0;
6104: t->ksp_its = 0;
6105: t->snes_its = 0;
6106: t->nwork = 0;
6107: t->rhsjacobian.time = PETSC_MIN_REAL;
6108: t->rhsjacobian.scale = 1.;
6109: t->ijacobian.shift = 1.;
6111: TSGetSNES(tsin,&snes_start);
6112: TSSetSNES(t,snes_start);
6114: TSGetDM(tsin,&dm);
6115: TSSetDM(t,dm);
6117: t->adapt = tsin->adapt;
6118: PetscObjectReference((PetscObject)t->adapt);
6120: t->trajectory = tsin->trajectory;
6121: PetscObjectReference((PetscObject)t->trajectory);
6123: t->event = tsin->event;
6124: if (t->event) t->event->refct++;
6126: t->problem_type = tsin->problem_type;
6127: t->ptime = tsin->ptime;
6128: t->ptime_prev = tsin->ptime_prev;
6129: t->time_step = tsin->time_step;
6130: t->max_time = tsin->max_time;
6131: t->steps = tsin->steps;
6132: t->max_steps = tsin->max_steps;
6133: t->equation_type = tsin->equation_type;
6134: t->atol = tsin->atol;
6135: t->rtol = tsin->rtol;
6136: t->max_snes_failures = tsin->max_snes_failures;
6137: t->max_reject = tsin->max_reject;
6138: t->errorifstepfailed = tsin->errorifstepfailed;
6140: TSGetType(tsin,&type);
6141: TSSetType(t,type);
6143: t->vec_sol = NULL;
6145: t->cfltime = tsin->cfltime;
6146: t->cfltime_local = tsin->cfltime_local;
6147: t->exact_final_time = tsin->exact_final_time;
6149: PetscMemcpy(t->ops,tsin->ops,sizeof(struct _TSOps));
6151: if (((PetscObject)tsin)->fortran_func_pointers) {
6152: PetscInt i;
6153: PetscMalloc((10)*sizeof(void(*)(void)),&((PetscObject)t)->fortran_func_pointers);
6154: for (i=0; i<10; i++) {
6155: ((PetscObject)t)->fortran_func_pointers[i] = ((PetscObject)tsin)->fortran_func_pointers[i];
6156: }
6157: }
6158: *tsout = t;
6159: return(0);
6160: }
6162: static PetscErrorCode RHSWrapperFunction_TSRHSJacobianTest(void* ctx,Vec x,Vec y)
6163: {
6165: TS ts = (TS) ctx;
6168: TSComputeRHSFunction(ts,0,x,y);
6169: return(0);
6170: }
6172: /*@
6173: TSRHSJacobianTest - Compares the multiply routine provided to the MATSHELL with differencing on the TS given RHS function.
6175: Logically Collective on TS
6177: Input Parameters:
6178: TS - the time stepping routine
6180: Output Parameter:
6181: . flg - PETSC_TRUE if the multiply is likely correct
6183: Options Database:
6184: . -ts_rhs_jacobian_test_mult -mat_shell_test_mult_view - run the test at each timestep of the integrator
6186: Level: advanced
6188: Notes:
6189: This only works for problems defined only the RHS function and Jacobian NOT IFunction and IJacobian
6191: .seealso: MatCreateShell(), MatShellGetContext(), MatShellGetOperation(), MatShellTestMultTranspose(), TSRHSJacobianTestTranspose()
6192: @*/
6193: PetscErrorCode TSRHSJacobianTest(TS ts,PetscBool *flg)
6194: {
6195: Mat J,B;
6197: TSRHSJacobian func;
6198: void* ctx;
6201: TSGetRHSJacobian(ts,&J,&B,&func,&ctx);
6202: (*func)(ts,0.0,ts->vec_sol,J,B,ctx);
6203: MatShellTestMult(J,RHSWrapperFunction_TSRHSJacobianTest,ts->vec_sol,ts,flg);
6204: return(0);
6205: }
6207: /*@C
6208: TSRHSJacobianTestTranspose - Compares the multiply transpose routine provided to the MATSHELL with differencing on the TS given RHS function.
6210: Logically Collective on TS
6212: Input Parameters:
6213: TS - the time stepping routine
6215: Output Parameter:
6216: . flg - PETSC_TRUE if the multiply is likely correct
6218: Options Database:
6219: . -ts_rhs_jacobian_test_mult_transpose -mat_shell_test_mult_transpose_view - run the test at each timestep of the integrator
6221: Notes:
6222: This only works for problems defined only the RHS function and Jacobian NOT IFunction and IJacobian
6224: Level: advanced
6226: .seealso: MatCreateShell(), MatShellGetContext(), MatShellGetOperation(), MatShellTestMultTranspose(), TSRHSJacobianTest()
6227: @*/
6228: PetscErrorCode TSRHSJacobianTestTranspose(TS ts,PetscBool *flg)
6229: {
6230: Mat J,B;
6232: void *ctx;
6233: TSRHSJacobian func;
6236: TSGetRHSJacobian(ts,&J,&B,&func,&ctx);
6237: (*func)(ts,0.0,ts->vec_sol,J,B,ctx);
6238: MatShellTestMultTranspose(J,RHSWrapperFunction_TSRHSJacobianTest,ts->vec_sol,ts,flg);
6239: return(0);
6240: }
6242: /*@
6243: TSSetUseSplitRHSFunction - Use the split RHSFunction when a multirate method is used.
6245: Logically collective
6247: Input Parameters:
6248: + ts - timestepping context
6249: - use_splitrhsfunction - PETSC_TRUE indicates that the split RHSFunction will be used
6251: Options Database:
6252: . -ts_use_splitrhsfunction - <true,false>
6254: Notes:
6255: This is only useful for multirate methods
6257: Level: intermediate
6259: .seealso: TSGetUseSplitRHSFunction()
6260: @*/
6261: PetscErrorCode TSSetUseSplitRHSFunction(TS ts, PetscBool use_splitrhsfunction)
6262: {
6265: ts->use_splitrhsfunction = use_splitrhsfunction;
6266: return(0);
6267: }
6269: /*@
6270: TSGetUseSplitRHSFunction - Gets whether to use the split RHSFunction when a multirate method is used.
6272: Not collective
6274: Input Parameter:
6275: . ts - timestepping context
6277: Output Parameter:
6278: . use_splitrhsfunction - PETSC_TRUE indicates that the split RHSFunction will be used
6280: Level: intermediate
6282: .seealso: TSSetUseSplitRHSFunction()
6283: @*/
6284: PetscErrorCode TSGetUseSplitRHSFunction(TS ts, PetscBool *use_splitrhsfunction)
6285: {
6288: *use_splitrhsfunction = ts->use_splitrhsfunction;
6289: return(0);
6290: }
6292: /*@
6293: TSSetMatStructure - sets the relationship between the nonzero structure of the RHS Jacobian matrix to the IJacobian matrix.
6295: Logically Collective on ts
6297: Input Parameters:
6298: + ts - the time-stepper
6299: - str - the structure (the default is UNKNOWN_NONZERO_PATTERN)
6301: Level: intermediate
6303: Notes:
6304: When the relationship between the nonzero structures is known and supplied the solution process can be much faster
6306: .seealso: MatAXPY(), MatStructure
6307: @*/
6308: PetscErrorCode TSSetMatStructure(TS ts,MatStructure str)
6309: {
6312: ts->axpy_pattern = str;
6313: return(0);
6314: }