xref: /petsc/src/ts/interface/ts.c (revision 287c2655d648353bfb2fc9b0abbaccecc8a8143c)
1 
2 #include <petsc/private/tsimpl.h>        /*I "petscts.h"  I*/
3 #include <petscdmshell.h>
4 #include <petscdmda.h>
5 #include <petscviewer.h>
6 #include <petscdraw.h>
7 
8 /* Logging support */
9 PetscClassId  TS_CLASSID, DMTS_CLASSID;
10 PetscLogEvent TS_AdjointStep, TS_Step, TS_PseudoComputeTimeStep, TS_FunctionEval, TS_JacobianEval;
11 
12 const char *const TSExactFinalTimeOptions[] = {"UNSPECIFIED","STEPOVER","INTERPOLATE","MATCHSTEP","TSExactFinalTimeOption","TS_EXACTFINALTIME_",0};
13 
14 struct _n_TSMonitorDrawCtx {
15   PetscViewer   viewer;
16   Vec           initialsolution;
17   PetscBool     showinitial;
18   PetscInt      howoften;  /* when > 0 uses step % howoften, when negative only final solution plotted */
19   PetscBool     showtimestepandtime;
20 };
21 
22 /*@C
23    TSMonitorSetFromOptions - Sets a monitor function and viewer appropriate for the type indicated by the user
24 
25    Collective on TS
26 
27    Input Parameters:
28 +  ts - TS object you wish to monitor
29 .  name - the monitor type one is seeking
30 .  help - message indicating what monitoring is done
31 .  manual - manual page for the monitor
32 .  monitor - the monitor function
33 -  monitorsetup - a function that is called once ONLY if the user selected this monitor that may set additional features of the TS or PetscViewer objects
34 
35    Level: developer
36 
37 .seealso: PetscOptionsGetViewer(), PetscOptionsGetReal(), PetscOptionsHasName(), PetscOptionsGetString(),
38           PetscOptionsGetIntArray(), PetscOptionsGetRealArray(), PetscOptionsBool()
39           PetscOptionsInt(), PetscOptionsString(), PetscOptionsReal(), PetscOptionsBool(),
40           PetscOptionsName(), PetscOptionsBegin(), PetscOptionsEnd(), PetscOptionsHead(),
41           PetscOptionsStringArray(),PetscOptionsRealArray(), PetscOptionsScalar(),
42           PetscOptionsBoolGroupBegin(), PetscOptionsBoolGroup(), PetscOptionsBoolGroupEnd(),
43           PetscOptionsFList(), PetscOptionsEList()
44 @*/
45 PetscErrorCode  TSMonitorSetFromOptions(TS ts,const char name[],const char help[], const char manual[],PetscErrorCode (*monitor)(TS,PetscInt,PetscReal,Vec,PetscViewerAndFormat*),PetscErrorCode (*monitorsetup)(TS,PetscViewerAndFormat*))
46 {
47   PetscErrorCode    ierr;
48   PetscViewer       viewer;
49   PetscViewerFormat format;
50   PetscBool         flg;
51 
52   PetscFunctionBegin;
53   ierr = PetscOptionsGetViewer(PetscObjectComm((PetscObject)ts),((PetscObject)ts)->prefix,name,&viewer,&format,&flg);CHKERRQ(ierr);
54   if (flg) {
55     PetscViewerAndFormat *vf;
56     ierr = PetscViewerAndFormatCreate(viewer,format,&vf);CHKERRQ(ierr);
57     ierr = PetscObjectDereference((PetscObject)viewer);CHKERRQ(ierr);
58     if (monitorsetup) {
59       ierr = (*monitorsetup)(ts,vf);CHKERRQ(ierr);
60     }
61     ierr = TSMonitorSet(ts,(PetscErrorCode (*)(TS,PetscInt,PetscReal,Vec,void*))monitor,vf,(PetscErrorCode (*)(void**))PetscViewerAndFormatDestroy);CHKERRQ(ierr);
62   }
63   PetscFunctionReturn(0);
64 }
65 
66 /*@C
67    TSAdjointMonitorGradient - monitors the first lambda gradient
68 
69    Level: intermediate
70 
71 .keywords: TS, set, monitor
72 
73 .seealso: TSAdjointMonitorSet()
74 @*/
75 PetscErrorCode TSAdjointMonitorGradient(TS ts,PetscInt step,PetscReal ptime,Vec v,PetscInt numcost,Vec *lambda,Vec *mu,PetscViewerAndFormat *vf)
76 {
77   PetscErrorCode ierr;
78   PetscViewer    viewer = vf->viewer;
79 
80   PetscFunctionBegin;
81   PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,4);
82   ierr = PetscViewerPushFormat(viewer,vf->format);CHKERRQ(ierr);
83   ierr = VecView(lambda[0],viewer);CHKERRQ(ierr);
84   ierr = PetscViewerPopFormat(viewer);CHKERRQ(ierr);
85   PetscFunctionReturn(0);
86 }
87 
88 /*@C
89    TSAdjointMonitorSetFromOptions - Sets a monitor function and viewer appropriate for the type indicated by the user
90 
91    Collective on TS
92 
93    Input Parameters:
94 +  ts - TS object you wish to monitor
95 .  name - the monitor type one is seeking
96 .  help - message indicating what monitoring is done
97 .  manual - manual page for the monitor
98 .  monitor - the monitor function
99 -  monitorsetup - a function that is called once ONLY if the user selected this monitor that may set additional features of the TS or PetscViewer objects
100 
101    Level: developer
102 
103 .seealso: PetscOptionsGetViewer(), PetscOptionsGetReal(), PetscOptionsHasName(), PetscOptionsGetString(),
104           PetscOptionsGetIntArray(), PetscOptionsGetRealArray(), PetscOptionsBool()
105           PetscOptionsInt(), PetscOptionsString(), PetscOptionsReal(), PetscOptionsBool(),
106           PetscOptionsName(), PetscOptionsBegin(), PetscOptionsEnd(), PetscOptionsHead(),
107           PetscOptionsStringArray(),PetscOptionsRealArray(), PetscOptionsScalar(),
108           PetscOptionsBoolGroupBegin(), PetscOptionsBoolGroup(), PetscOptionsBoolGroupEnd(),
109           PetscOptionsFList(), PetscOptionsEList()
110 @*/
111 PetscErrorCode  TSAdjointMonitorSetFromOptions(TS ts,const char name[],const char help[], const char manual[],PetscErrorCode (*monitor)(TS,PetscInt,PetscReal,Vec,PetscInt,Vec*,Vec*,PetscViewerAndFormat*),PetscErrorCode (*monitorsetup)(TS,PetscViewerAndFormat*))
112 {
113   PetscErrorCode    ierr;
114   PetscViewer       viewer;
115   PetscViewerFormat format;
116   PetscBool         flg;
117 
118   PetscFunctionBegin;
119   ierr = PetscOptionsGetViewer(PetscObjectComm((PetscObject)ts),((PetscObject)ts)->prefix,name,&viewer,&format,&flg);CHKERRQ(ierr);
120   if (flg) {
121     PetscViewerAndFormat *vf;
122     ierr = PetscViewerAndFormatCreate(viewer,format,&vf);CHKERRQ(ierr);
123     ierr = PetscObjectDereference((PetscObject)viewer);CHKERRQ(ierr);
124     if (monitorsetup) {
125       ierr = (*monitorsetup)(ts,vf);CHKERRQ(ierr);
126     }
127     ierr = TSAdjointMonitorSet(ts,(PetscErrorCode (*)(TS,PetscInt,PetscReal,Vec,PetscInt,Vec*,Vec*,void*))monitor,vf,(PetscErrorCode (*)(void**))PetscViewerAndFormatDestroy);CHKERRQ(ierr);
128   }
129   PetscFunctionReturn(0);
130 }
131 
132 static PetscErrorCode TSAdaptSetDefaultType(TSAdapt adapt,TSAdaptType default_type)
133 {
134   PetscErrorCode ierr;
135 
136   PetscFunctionBegin;
137   PetscValidHeaderSpecific(adapt,TSADAPT_CLASSID,1);
138   PetscValidCharPointer(default_type,2);
139   if (!((PetscObject)adapt)->type_name) {
140     ierr = TSAdaptSetType(adapt,default_type);CHKERRQ(ierr);
141   }
142   PetscFunctionReturn(0);
143 }
144 
145 /*@
146    TSSetFromOptions - Sets various TS parameters from user options.
147 
148    Collective on TS
149 
150    Input Parameter:
151 .  ts - the TS context obtained from TSCreate()
152 
153    Options Database Keys:
154 +  -ts_type <type> - TSEULER, TSBEULER, TSSUNDIALS, TSPSEUDO, TSCN, TSRK, TSTHETA, TSALPHA, TSGLLE, TSSSP, TSGLEE
155 .  -ts_save_trajectory - checkpoint the solution at each time-step
156 .  -ts_max_steps <maxsteps> - maximum number of time-steps to take
157 .  -ts_final_time <time> - maximum time to compute to
158 .  -ts_dt <dt> - initial time step
159 .  -ts_exact_final_time <stepover,interpolate,matchstep> whether to stop at the exact given final time and how to compute the solution at that ti,e
160 .  -ts_max_snes_failures <maxfailures> - Maximum number of nonlinear solve failures allowed
161 .  -ts_max_reject <maxrejects> - Maximum number of step rejections before step fails
162 .  -ts_error_if_step_fails <true,false> - Error if no step succeeds
163 .  -ts_rtol <rtol> - relative tolerance for local truncation error
164 .  -ts_atol <atol> Absolute tolerance for local truncation error
165 .  -ts_adjoint_solve <yes,no> After solving the ODE/DAE solve the adjoint problem (requires -ts_save_trajectory)
166 .  -ts_fd_color - Use finite differences with coloring to compute IJacobian
167 .  -ts_monitor - print information at each timestep
168 .  -ts_monitor_lg_solution - Monitor solution graphically
169 .  -ts_monitor_lg_error - Monitor error graphically
170 .  -ts_monitor_lg_timestep - Monitor timestep size graphically
171 .  -ts_monitor_lg_snes_iterations - Monitor number nonlinear iterations for each timestep graphically
172 .  -ts_monitor_lg_ksp_iterations - Monitor number nonlinear iterations for each timestep graphically
173 .  -ts_monitor_sp_eig - Monitor eigenvalues of linearized operator graphically
174 .  -ts_monitor_draw_solution - Monitor solution graphically
175 .  -ts_monitor_draw_solution_phase  <xleft,yleft,xright,yright> - Monitor solution graphically with phase diagram, requires problem with exactly 2 degrees of freedom
176 .  -ts_monitor_draw_error - Monitor error graphically, requires use to have provided TSSetSolutionFunction()
177 .  -ts_monitor_solution [ascii binary draw][:filename][:viewerformat] - monitors the solution at each timestep
178 .  -ts_monitor_solution_vtk <filename.vts,filename.vtu> - Save each time step to a binary file, use filename-%%03D.vts (filename-%%03D.vtu)
179 .  -ts_monitor_envelope - determine maximum and minimum value of each component of the solution over the solution time
180 .  -ts_adjoint_monitor - print information at each adjoint time step
181 -  -ts_adjoint_monitor_draw_sensi - monitor the sensitivity of the first cost function wrt initial conditions (lambda[0]) graphically
182 
183    Developer Note: We should unify all the -ts_monitor options in the way that -xxx_view has been unified
184 
185    Level: beginner
186 
187 .keywords: TS, timestep, set, options, database
188 
189 .seealso: TSGetType()
190 @*/
191 PetscErrorCode  TSSetFromOptions(TS ts)
192 {
193   PetscBool              opt,flg,tflg;
194   PetscErrorCode         ierr;
195   char                   monfilename[PETSC_MAX_PATH_LEN];
196   PetscReal              time_step;
197   TSExactFinalTimeOption eftopt;
198   char                   dir[16];
199   TSIFunction            ifun;
200   const char             *defaultType;
201   char                   typeName[256];
202 
203   PetscFunctionBegin;
204   PetscValidHeaderSpecific(ts, TS_CLASSID,1);
205 
206   ierr = TSRegisterAll();CHKERRQ(ierr);
207   ierr = TSGetIFunction(ts,NULL,&ifun,NULL);CHKERRQ(ierr);
208 
209   ierr = PetscObjectOptionsBegin((PetscObject)ts);CHKERRQ(ierr);
210   if (((PetscObject)ts)->type_name)
211     defaultType = ((PetscObject)ts)->type_name;
212   else
213     defaultType = ifun ? TSBEULER : TSEULER;
214   ierr = PetscOptionsFList("-ts_type","TS method","TSSetType",TSList,defaultType,typeName,256,&opt);CHKERRQ(ierr);
215   if (opt) {
216     ierr = TSSetType(ts,typeName);CHKERRQ(ierr);
217   } else {
218     ierr = TSSetType(ts,defaultType);CHKERRQ(ierr);
219   }
220 
221   /* Handle generic TS options */
222   ierr = PetscOptionsInt("-ts_max_steps","Maximum number of time steps","TSSetDuration",ts->max_steps,&ts->max_steps,NULL);CHKERRQ(ierr);
223   ierr = PetscOptionsReal("-ts_final_time","Time to run to","TSSetDuration",ts->max_time,&ts->max_time,NULL);CHKERRQ(ierr);
224   ierr = PetscOptionsReal("-ts_init_time","Initial time","TSSetTime",ts->ptime,&ts->ptime,NULL);CHKERRQ(ierr);
225   ierr = PetscOptionsReal("-ts_dt","Initial time step","TSSetTimeStep",ts->time_step,&time_step,&flg);CHKERRQ(ierr);
226   if (flg) {ierr = TSSetTimeStep(ts,time_step);CHKERRQ(ierr);}
227   ierr = PetscOptionsEnum("-ts_exact_final_time","Option for handling of final time step","TSSetExactFinalTime",TSExactFinalTimeOptions,(PetscEnum)ts->exact_final_time,(PetscEnum*)&eftopt,&flg);CHKERRQ(ierr);
228   if (flg) {ierr = TSSetExactFinalTime(ts,eftopt);CHKERRQ(ierr);}
229   ierr = PetscOptionsInt("-ts_max_snes_failures","Maximum number of nonlinear solve failures","TSSetMaxSNESFailures",ts->max_snes_failures,&ts->max_snes_failures,NULL);CHKERRQ(ierr);
230   ierr = PetscOptionsInt("-ts_max_reject","Maximum number of step rejections before step fails","TSSetMaxStepRejections",ts->max_reject,&ts->max_reject,NULL);CHKERRQ(ierr);
231   ierr = PetscOptionsBool("-ts_error_if_step_fails","Error if no step succeeds","TSSetErrorIfStepFails",ts->errorifstepfailed,&ts->errorifstepfailed,NULL);CHKERRQ(ierr);
232   ierr = PetscOptionsReal("-ts_rtol","Relative tolerance for local truncation error","TSSetTolerances",ts->rtol,&ts->rtol,NULL);CHKERRQ(ierr);
233   ierr = PetscOptionsReal("-ts_atol","Absolute tolerance for local truncation error","TSSetTolerances",ts->atol,&ts->atol,NULL);CHKERRQ(ierr);
234 
235 #if defined(PETSC_HAVE_SAWS)
236   {
237   PetscBool set;
238   flg  = PETSC_FALSE;
239   ierr = PetscOptionsBool("-ts_saws_block","Block for SAWs memory snooper at end of TSSolve","PetscObjectSAWsBlock",((PetscObject)ts)->amspublishblock,&flg,&set);CHKERRQ(ierr);
240   if (set) {
241     ierr = PetscObjectSAWsSetBlock((PetscObject)ts,flg);CHKERRQ(ierr);
242   }
243   }
244 #endif
245 
246   /* Monitor options */
247   ierr = TSMonitorSetFromOptions(ts,"-ts_monitor","Monitor time and timestep size","TSMonitorDefault",TSMonitorDefault,NULL);CHKERRQ(ierr);
248   ierr = TSMonitorSetFromOptions(ts,"-ts_monitor_solution","View the solution at each timestep","TSMonitorSolution",TSMonitorSolution,NULL);CHKERRQ(ierr);
249   ierr = TSAdjointMonitorSetFromOptions(ts,"-ts_adjoint_monitor","Monitor adjoint timestep size","TSAdjointMonitorDefault",TSAdjointMonitorDefault,NULL);CHKERRQ(ierr);
250   ierr = TSAdjointMonitorSetFromOptions(ts,"-ts_adjoint_monitor_gradient","Monitor gradient in the adjoint computation","TSAdjointMonitorGradient",TSAdjointMonitorGradient,NULL);CHKERRQ(ierr);
251 
252   ierr = PetscOptionsString("-ts_monitor_python","Use Python function","TSMonitorSet",0,monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr);
253   if (flg) {ierr = PetscPythonMonitorSet((PetscObject)ts,monfilename);CHKERRQ(ierr);}
254 
255   ierr = PetscOptionsName("-ts_monitor_lg_solution","Monitor solution graphically","TSMonitorLGSolution",&opt);CHKERRQ(ierr);
256   if (opt) {
257     TSMonitorLGCtx ctx;
258     PetscInt       howoften = 1;
259 
260     ierr = PetscOptionsInt("-ts_monitor_lg_solution","Monitor solution graphically","TSMonitorLGSolution",howoften,&howoften,NULL);CHKERRQ(ierr);
261     ierr = TSMonitorLGCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);CHKERRQ(ierr);
262     ierr = TSMonitorSet(ts,TSMonitorLGSolution,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr);
263   }
264 
265   ierr = PetscOptionsName("-ts_monitor_lg_error","Monitor error graphically","TSMonitorLGError",&opt);CHKERRQ(ierr);
266   if (opt) {
267     TSMonitorLGCtx ctx;
268     PetscInt       howoften = 1;
269 
270     ierr = PetscOptionsInt("-ts_monitor_lg_error","Monitor error graphically","TSMonitorLGError",howoften,&howoften,NULL);CHKERRQ(ierr);
271     ierr = TSMonitorLGCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);CHKERRQ(ierr);
272     ierr = TSMonitorSet(ts,TSMonitorLGError,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr);
273   }
274 
275   ierr = PetscOptionsName("-ts_monitor_lg_timestep","Monitor timestep size graphically","TSMonitorLGTimeStep",&opt);CHKERRQ(ierr);
276   if (opt) {
277     TSMonitorLGCtx ctx;
278     PetscInt       howoften = 1;
279 
280     ierr = PetscOptionsInt("-ts_monitor_lg_timestep","Monitor timestep size graphically","TSMonitorLGTimeStep",howoften,&howoften,NULL);CHKERRQ(ierr);
281     ierr = TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);CHKERRQ(ierr);
282     ierr = TSMonitorSet(ts,TSMonitorLGTimeStep,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr);
283   }
284   ierr = PetscOptionsName("-ts_monitor_lg_snes_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGSNESIterations",&opt);CHKERRQ(ierr);
285   if (opt) {
286     TSMonitorLGCtx ctx;
287     PetscInt       howoften = 1;
288 
289     ierr = PetscOptionsInt("-ts_monitor_lg_snes_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGSNESIterations",howoften,&howoften,NULL);CHKERRQ(ierr);
290     ierr = TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);CHKERRQ(ierr);
291     ierr = TSMonitorSet(ts,TSMonitorLGSNESIterations,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr);
292   }
293   ierr = PetscOptionsName("-ts_monitor_lg_ksp_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGKSPIterations",&opt);CHKERRQ(ierr);
294   if (opt) {
295     TSMonitorLGCtx ctx;
296     PetscInt       howoften = 1;
297 
298     ierr = PetscOptionsInt("-ts_monitor_lg_ksp_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGKSPIterations",howoften,&howoften,NULL);CHKERRQ(ierr);
299     ierr = TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);CHKERRQ(ierr);
300     ierr = TSMonitorSet(ts,TSMonitorLGKSPIterations,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr);
301   }
302   ierr = PetscOptionsName("-ts_monitor_sp_eig","Monitor eigenvalues of linearized operator graphically","TSMonitorSPEig",&opt);CHKERRQ(ierr);
303   if (opt) {
304     TSMonitorSPEigCtx ctx;
305     PetscInt          howoften = 1;
306 
307     ierr = PetscOptionsInt("-ts_monitor_sp_eig","Monitor eigenvalues of linearized operator graphically","TSMonitorSPEig",howoften,&howoften,NULL);CHKERRQ(ierr);
308     ierr = TSMonitorSPEigCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);CHKERRQ(ierr);
309     ierr = TSMonitorSet(ts,TSMonitorSPEig,ctx,(PetscErrorCode (*)(void**))TSMonitorSPEigCtxDestroy);CHKERRQ(ierr);
310   }
311   opt  = PETSC_FALSE;
312   ierr = PetscOptionsName("-ts_monitor_draw_solution","Monitor solution graphically","TSMonitorDrawSolution",&opt);CHKERRQ(ierr);
313   if (opt) {
314     TSMonitorDrawCtx ctx;
315     PetscInt         howoften = 1;
316 
317     ierr = PetscOptionsInt("-ts_monitor_draw_solution","Monitor solution graphically","TSMonitorDrawSolution",howoften,&howoften,NULL);CHKERRQ(ierr);
318     ierr = TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);CHKERRQ(ierr);
319     ierr = TSMonitorSet(ts,TSMonitorDrawSolution,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);CHKERRQ(ierr);
320   }
321   opt  = PETSC_FALSE;
322   ierr = PetscOptionsName("-ts_adjoint_monitor_draw_sensi","Monitor adjoint sensitivities (lambda only) graphically","TSAdjointMonitorDrawSensi",&opt);CHKERRQ(ierr);
323   if (opt) {
324     TSMonitorDrawCtx ctx;
325     PetscInt         howoften = 1;
326 
327     ierr = PetscOptionsInt("-ts_adjoint_monitor_draw_sensi","Monitor adjoint sensitivities (lambda only) graphically","TSAdjointMonitorDrawSensi",howoften,&howoften,NULL);CHKERRQ(ierr);
328     ierr = TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);CHKERRQ(ierr);
329     ierr = TSAdjointMonitorSet(ts,TSAdjointMonitorDrawSensi,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);CHKERRQ(ierr);
330   }
331   opt  = PETSC_FALSE;
332   ierr = PetscOptionsName("-ts_monitor_draw_solution_phase","Monitor solution graphically","TSMonitorDrawSolutionPhase",&opt);CHKERRQ(ierr);
333   if (opt) {
334     TSMonitorDrawCtx ctx;
335     PetscReal        bounds[4];
336     PetscInt         n = 4;
337     PetscDraw        draw;
338     PetscDrawAxis    axis;
339 
340     ierr = PetscOptionsRealArray("-ts_monitor_draw_solution_phase","Monitor solution graphically","TSMonitorDrawSolutionPhase",bounds,&n,NULL);CHKERRQ(ierr);
341     if (n != 4) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Must provide bounding box of phase field");
342     ierr = TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,1,&ctx);CHKERRQ(ierr);
343     ierr = PetscViewerDrawGetDraw(ctx->viewer,0,&draw);CHKERRQ(ierr);
344     ierr = PetscViewerDrawGetDrawAxis(ctx->viewer,0,&axis);CHKERRQ(ierr);
345     ierr = PetscDrawAxisSetLimits(axis,bounds[0],bounds[2],bounds[1],bounds[3]);CHKERRQ(ierr);
346     ierr = PetscDrawAxisSetLabels(axis,"Phase Diagram","Variable 1","Variable 2");CHKERRQ(ierr);
347     ierr = TSMonitorSet(ts,TSMonitorDrawSolutionPhase,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);CHKERRQ(ierr);
348   }
349   opt  = PETSC_FALSE;
350   ierr = PetscOptionsName("-ts_monitor_draw_error","Monitor error graphically","TSMonitorDrawError",&opt);CHKERRQ(ierr);
351   if (opt) {
352     TSMonitorDrawCtx ctx;
353     PetscInt         howoften = 1;
354 
355     ierr = PetscOptionsInt("-ts_monitor_draw_error","Monitor error graphically","TSMonitorDrawError",howoften,&howoften,NULL);CHKERRQ(ierr);
356     ierr = TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);CHKERRQ(ierr);
357     ierr = TSMonitorSet(ts,TSMonitorDrawError,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);CHKERRQ(ierr);
358   }
359 
360   opt  = PETSC_FALSE;
361   ierr = PetscOptionsString("-ts_monitor_solution_vtk","Save each time step to a binary file, use filename-%%03D.vts","TSMonitorSolutionVTK",0,monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr);
362   if (flg) {
363     const char *ptr,*ptr2;
364     char       *filetemplate;
365     if (!monfilename[0]) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"-ts_monitor_solution_vtk requires a file template, e.g. filename-%%03D.vts");
366     /* Do some cursory validation of the input. */
367     ierr = PetscStrstr(monfilename,"%",(char**)&ptr);CHKERRQ(ierr);
368     if (!ptr) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"-ts_monitor_solution_vtk requires a file template, e.g. filename-%%03D.vts");
369     for (ptr++; ptr && *ptr; ptr++) {
370       ierr = PetscStrchr("DdiouxX",*ptr,(char**)&ptr2);CHKERRQ(ierr);
371       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");
372       if (ptr2) break;
373     }
374     ierr = PetscStrallocpy(monfilename,&filetemplate);CHKERRQ(ierr);
375     ierr = TSMonitorSet(ts,TSMonitorSolutionVTK,filetemplate,(PetscErrorCode (*)(void**))TSMonitorSolutionVTKDestroy);CHKERRQ(ierr);
376   }
377 
378   ierr = PetscOptionsString("-ts_monitor_dmda_ray","Display a ray of the solution","None","y=0",dir,16,&flg);CHKERRQ(ierr);
379   if (flg) {
380     TSMonitorDMDARayCtx *rayctx;
381     int                  ray = 0;
382     DMDADirection        ddir;
383     DM                   da;
384     PetscMPIInt          rank;
385 
386     if (dir[1] != '=') SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Unknown ray %s",dir);
387     if (dir[0] == 'x') ddir = DMDA_X;
388     else if (dir[0] == 'y') ddir = DMDA_Y;
389     else SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Unknown ray %s",dir);
390     sscanf(dir+2,"%d",&ray);
391 
392     ierr = PetscInfo2(((PetscObject)ts),"Displaying DMDA ray %c = %D\n",dir[0],ray);CHKERRQ(ierr);
393     ierr = PetscNew(&rayctx);CHKERRQ(ierr);
394     ierr = TSGetDM(ts,&da);CHKERRQ(ierr);
395     ierr = DMDAGetRay(da,ddir,ray,&rayctx->ray,&rayctx->scatter);CHKERRQ(ierr);
396     ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)ts),&rank);CHKERRQ(ierr);
397     if (!rank) {
398       ierr = PetscViewerDrawOpen(PETSC_COMM_SELF,0,0,0,0,600,300,&rayctx->viewer);CHKERRQ(ierr);
399     }
400     rayctx->lgctx = NULL;
401     ierr = TSMonitorSet(ts,TSMonitorDMDARay,rayctx,TSMonitorDMDARayDestroy);CHKERRQ(ierr);
402   }
403   ierr = PetscOptionsString("-ts_monitor_lg_dmda_ray","Display a ray of the solution","None","x=0",dir,16,&flg);CHKERRQ(ierr);
404   if (flg) {
405     TSMonitorDMDARayCtx *rayctx;
406     int                 ray = 0;
407     DMDADirection       ddir;
408     DM                  da;
409     PetscInt            howoften = 1;
410 
411     if (dir[1] != '=') SETERRQ1(PetscObjectComm((PetscObject) ts), PETSC_ERR_ARG_WRONG, "Malformed ray %s", dir);
412     if      (dir[0] == 'x') ddir = DMDA_X;
413     else if (dir[0] == 'y') ddir = DMDA_Y;
414     else SETERRQ1(PetscObjectComm((PetscObject) ts), PETSC_ERR_ARG_WRONG, "Unknown ray direction %s", dir);
415     sscanf(dir+2, "%d", &ray);
416 
417     ierr = PetscInfo2(((PetscObject) ts),"Displaying LG DMDA ray %c = %D\n", dir[0], ray);CHKERRQ(ierr);
418     ierr = PetscNew(&rayctx);CHKERRQ(ierr);
419     ierr = TSGetDM(ts, &da);CHKERRQ(ierr);
420     ierr = DMDAGetRay(da, ddir, ray, &rayctx->ray, &rayctx->scatter);CHKERRQ(ierr);
421     ierr = TSMonitorLGCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,600,400,howoften,&rayctx->lgctx);CHKERRQ(ierr);
422     ierr = TSMonitorSet(ts, TSMonitorLGDMDARay, rayctx, TSMonitorDMDARayDestroy);CHKERRQ(ierr);
423   }
424 
425   ierr = PetscOptionsName("-ts_monitor_envelope","Monitor maximum and minimum value of each component of the solution","TSMonitorEnvelope",&opt);CHKERRQ(ierr);
426   if (opt) {
427     TSMonitorEnvelopeCtx ctx;
428 
429     ierr = TSMonitorEnvelopeCtxCreate(ts,&ctx);CHKERRQ(ierr);
430     ierr = TSMonitorSet(ts,TSMonitorEnvelope,ctx,(PetscErrorCode (*)(void**))TSMonitorEnvelopeCtxDestroy);CHKERRQ(ierr);
431   }
432 
433   flg  = PETSC_FALSE;
434   ierr = PetscOptionsBool("-ts_fd_color", "Use finite differences with coloring to compute IJacobian", "TSComputeJacobianDefaultColor", flg, &flg, NULL);CHKERRQ(ierr);
435   if (flg) {
436     DM   dm;
437     DMTS tdm;
438 
439     ierr = TSGetDM(ts, &dm);CHKERRQ(ierr);
440     ierr = DMGetDMTS(dm, &tdm);CHKERRQ(ierr);
441     tdm->ijacobianctx = NULL;
442     ierr = TSSetIJacobian(ts, NULL, NULL, TSComputeIJacobianDefaultColor, 0);CHKERRQ(ierr);
443     ierr = PetscInfo(ts, "Setting default finite difference coloring Jacobian matrix\n");CHKERRQ(ierr);
444   }
445 
446   /* Handle TSAdapt options */
447   ierr = TSGetAdapt(ts,&ts->adapt);CHKERRQ(ierr);
448   ierr = TSAdaptSetDefaultType(ts->adapt,ts->default_adapt_type);CHKERRQ(ierr);
449   ierr = TSAdaptSetFromOptions(PetscOptionsObject,ts->adapt);CHKERRQ(ierr);
450 
451   /* Handle specific TS options */
452   if (ts->ops->setfromoptions) {
453     ierr = (*ts->ops->setfromoptions)(PetscOptionsObject,ts);CHKERRQ(ierr);
454   }
455 
456   /* TS trajectory must be set after TS, since it may use some TS options above */
457   tflg = ts->trajectory ? PETSC_TRUE : PETSC_FALSE;
458   ierr = PetscOptionsBool("-ts_save_trajectory","Save the solution at each timestep","TSSetSaveTrajectory",tflg,&tflg,NULL);CHKERRQ(ierr);
459   if (tflg) {
460     ierr = TSSetSaveTrajectory(ts);CHKERRQ(ierr);
461   }
462   tflg = ts->adjoint_solve ? PETSC_TRUE : PETSC_FALSE;
463   ierr = PetscOptionsBool("-ts_adjoint_solve","Solve the adjoint problem immediately after solving the forward problem","",tflg,&tflg,&flg);CHKERRQ(ierr);
464   if (flg) {
465     ierr = TSSetSaveTrajectory(ts);CHKERRQ(ierr);
466     ts->adjoint_solve = tflg;
467   }
468 
469   /* process any options handlers added with PetscObjectAddOptionsHandler() */
470   ierr = PetscObjectProcessOptionsHandlers(PetscOptionsObject,(PetscObject)ts);CHKERRQ(ierr);
471   ierr = PetscOptionsEnd();CHKERRQ(ierr);
472 
473   if (ts->trajectory) {
474     ierr = TSTrajectorySetFromOptions(ts->trajectory,ts);CHKERRQ(ierr);
475   }
476 
477   ierr = TSGetSNES(ts,&ts->snes);CHKERRQ(ierr);
478   if (ts->problem_type == TS_LINEAR) {ierr = SNESSetType(ts->snes,SNESKSPONLY);CHKERRQ(ierr);}
479   ierr = SNESSetFromOptions(ts->snes);CHKERRQ(ierr);
480   PetscFunctionReturn(0);
481 }
482 
483 /*@
484    TSGetTrajectory - Gets the trajectory from a TS if it exists
485 
486    Collective on TS
487 
488    Input Parameters:
489 .  ts - the TS context obtained from TSCreate()
490 
491    Output Parameters;
492 .  tr - the TSTrajectory object, if it exists
493 
494    Note: This routine should be called after all TS options have been set
495 
496    Level: advanced
497 
498 .seealso: TSGetTrajectory(), TSAdjointSolve(), TSTrajectory, TSTrajectoryCreate()
499 
500 .keywords: TS, set, checkpoint,
501 @*/
502 PetscErrorCode  TSGetTrajectory(TS ts,TSTrajectory *tr)
503 {
504   PetscFunctionBegin;
505   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
506   *tr = ts->trajectory;
507   PetscFunctionReturn(0);
508 }
509 
510 /*@
511    TSSetSaveTrajectory - Causes the TS to save its solutions as it iterates forward in time in a TSTrajectory object
512 
513    Collective on TS
514 
515    Input Parameters:
516 .  ts - the TS context obtained from TSCreate()
517 
518    Options Database:
519 +  -ts_save_trajectory - saves the trajectory to a file
520 -  -ts_trajectory_type type
521 
522 Note: This routine should be called after all TS options have been set
523 
524     The TSTRAJECTORYVISUALIZATION files can be loaded into Python with $PETSC_DIR/bin/PetscBinaryIOTrajectory.py and
525    MATLAB with $PETSC_DIR/share/petsc/matlab/PetscReadBinaryTrajectory.m
526 
527    Level: intermediate
528 
529 .seealso: TSGetTrajectory(), TSAdjointSolve(), TSTrajectoryType, TSSetTrajectoryType()
530 
531 .keywords: TS, set, checkpoint,
532 @*/
533 PetscErrorCode  TSSetSaveTrajectory(TS ts)
534 {
535   PetscErrorCode ierr;
536 
537   PetscFunctionBegin;
538   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
539   if (!ts->trajectory) {
540     ierr = TSTrajectoryCreate(PetscObjectComm((PetscObject)ts),&ts->trajectory);CHKERRQ(ierr);
541     ierr = TSTrajectorySetFromOptions(ts->trajectory,ts);CHKERRQ(ierr);
542   }
543   PetscFunctionReturn(0);
544 }
545 
546 /*@
547    TSComputeRHSJacobian - Computes the Jacobian matrix that has been
548       set with TSSetRHSJacobian().
549 
550    Collective on TS and Vec
551 
552    Input Parameters:
553 +  ts - the TS context
554 .  t - current timestep
555 -  U - input vector
556 
557    Output Parameters:
558 +  A - Jacobian matrix
559 .  B - optional preconditioning matrix
560 -  flag - flag indicating matrix structure
561 
562    Notes:
563    Most users should not need to explicitly call this routine, as it
564    is used internally within the nonlinear solvers.
565 
566    See KSPSetOperators() for important information about setting the
567    flag parameter.
568 
569    Level: developer
570 
571 .keywords: SNES, compute, Jacobian, matrix
572 
573 .seealso:  TSSetRHSJacobian(), KSPSetOperators()
574 @*/
575 PetscErrorCode  TSComputeRHSJacobian(TS ts,PetscReal t,Vec U,Mat A,Mat B)
576 {
577   PetscErrorCode ierr;
578   PetscObjectState Ustate;
579   DM             dm;
580   DMTS           tsdm;
581   TSRHSJacobian  rhsjacobianfunc;
582   void           *ctx;
583   TSIJacobian    ijacobianfunc;
584   TSRHSFunction  rhsfunction;
585 
586   PetscFunctionBegin;
587   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
588   PetscValidHeaderSpecific(U,VEC_CLASSID,3);
589   PetscCheckSameComm(ts,1,U,3);
590   ierr = TSGetDM(ts,&dm);CHKERRQ(ierr);
591   ierr = DMGetDMTS(dm,&tsdm);CHKERRQ(ierr);
592   ierr = DMTSGetRHSJacobian(dm,&rhsjacobianfunc,&ctx);CHKERRQ(ierr);
593   ierr = DMTSGetIJacobian(dm,&ijacobianfunc,NULL);CHKERRQ(ierr);
594   ierr = DMTSGetRHSFunction(dm,&rhsfunction,&ctx);CHKERRQ(ierr);
595   ierr = PetscObjectStateGet((PetscObject)U,&Ustate);CHKERRQ(ierr);
596   if (ts->rhsjacobian.time == t && (ts->problem_type == TS_LINEAR || (ts->rhsjacobian.X == U && ts->rhsjacobian.Xstate == Ustate)) && (rhsfunction != TSComputeRHSFunctionLinear)) {
597     PetscFunctionReturn(0);
598   }
599 
600   if (!rhsjacobianfunc && !ijacobianfunc) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSJacobian() and / or TSSetIJacobian()");
601 
602   if (ts->rhsjacobian.reuse) {
603     ierr = MatShift(A,-ts->rhsjacobian.shift);CHKERRQ(ierr);
604     ierr = MatScale(A,1./ts->rhsjacobian.scale);CHKERRQ(ierr);
605     if (A != B) {
606       ierr = MatShift(B,-ts->rhsjacobian.shift);CHKERRQ(ierr);
607       ierr = MatScale(B,1./ts->rhsjacobian.scale);CHKERRQ(ierr);
608     }
609     ts->rhsjacobian.shift = 0;
610     ts->rhsjacobian.scale = 1.;
611   }
612 
613   if (rhsjacobianfunc) {
614     PetscBool missing;
615     ierr = PetscLogEventBegin(TS_JacobianEval,ts,U,A,B);CHKERRQ(ierr);
616     PetscStackPush("TS user Jacobian function");
617     ierr = (*rhsjacobianfunc)(ts,t,U,A,B,ctx);CHKERRQ(ierr);
618     PetscStackPop;
619     ierr = PetscLogEventEnd(TS_JacobianEval,ts,U,A,B);CHKERRQ(ierr);
620     if (A) {
621       ierr = MatMissingDiagonal(A,&missing,NULL);CHKERRQ(ierr);
622       if (missing) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Amat passed to TSSetRHSJacobian() must have all diagonal entries set, if they are zero you must still set them with a zero value");
623     }
624     if (B && B != A) {
625       ierr = MatMissingDiagonal(B,&missing,NULL);CHKERRQ(ierr);
626       if (missing) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Bmat passed to TSSetRHSJacobian() must have all diagonal entries set, if they are zero you must still set them with a zero value");
627     }
628   } else {
629     ierr = MatZeroEntries(A);CHKERRQ(ierr);
630     if (A != B) {ierr = MatZeroEntries(B);CHKERRQ(ierr);}
631   }
632   ts->rhsjacobian.time       = t;
633   ts->rhsjacobian.X          = U;
634   ierr                       = PetscObjectStateGet((PetscObject)U,&ts->rhsjacobian.Xstate);CHKERRQ(ierr);
635   PetscFunctionReturn(0);
636 }
637 
638 /*@
639    TSComputeRHSFunction - Evaluates the right-hand-side function.
640 
641    Collective on TS and Vec
642 
643    Input Parameters:
644 +  ts - the TS context
645 .  t - current time
646 -  U - state vector
647 
648    Output Parameter:
649 .  y - right hand side
650 
651    Note:
652    Most users should not need to explicitly call this routine, as it
653    is used internally within the nonlinear solvers.
654 
655    Level: developer
656 
657 .keywords: TS, compute
658 
659 .seealso: TSSetRHSFunction(), TSComputeIFunction()
660 @*/
661 PetscErrorCode TSComputeRHSFunction(TS ts,PetscReal t,Vec U,Vec y)
662 {
663   PetscErrorCode ierr;
664   TSRHSFunction  rhsfunction;
665   TSIFunction    ifunction;
666   void           *ctx;
667   DM             dm;
668 
669   PetscFunctionBegin;
670   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
671   PetscValidHeaderSpecific(U,VEC_CLASSID,3);
672   PetscValidHeaderSpecific(y,VEC_CLASSID,4);
673   ierr = TSGetDM(ts,&dm);CHKERRQ(ierr);
674   ierr = DMTSGetRHSFunction(dm,&rhsfunction,&ctx);CHKERRQ(ierr);
675   ierr = DMTSGetIFunction(dm,&ifunction,NULL);CHKERRQ(ierr);
676 
677   if (!rhsfunction && !ifunction) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSFunction() and / or TSSetIFunction()");
678 
679   ierr = PetscLogEventBegin(TS_FunctionEval,ts,U,y,0);CHKERRQ(ierr);
680   if (rhsfunction) {
681     PetscStackPush("TS user right-hand-side function");
682     ierr = (*rhsfunction)(ts,t,U,y,ctx);CHKERRQ(ierr);
683     PetscStackPop;
684   } else {
685     ierr = VecZeroEntries(y);CHKERRQ(ierr);
686   }
687 
688   ierr = PetscLogEventEnd(TS_FunctionEval,ts,U,y,0);CHKERRQ(ierr);
689   PetscFunctionReturn(0);
690 }
691 
692 /*@
693    TSComputeSolutionFunction - Evaluates the solution function.
694 
695    Collective on TS and Vec
696 
697    Input Parameters:
698 +  ts - the TS context
699 -  t - current time
700 
701    Output Parameter:
702 .  U - the solution
703 
704    Note:
705    Most users should not need to explicitly call this routine, as it
706    is used internally within the nonlinear solvers.
707 
708    Level: developer
709 
710 .keywords: TS, compute
711 
712 .seealso: TSSetSolutionFunction(), TSSetRHSFunction(), TSComputeIFunction()
713 @*/
714 PetscErrorCode TSComputeSolutionFunction(TS ts,PetscReal t,Vec U)
715 {
716   PetscErrorCode     ierr;
717   TSSolutionFunction solutionfunction;
718   void               *ctx;
719   DM                 dm;
720 
721   PetscFunctionBegin;
722   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
723   PetscValidHeaderSpecific(U,VEC_CLASSID,3);
724   ierr = TSGetDM(ts,&dm);CHKERRQ(ierr);
725   ierr = DMTSGetSolutionFunction(dm,&solutionfunction,&ctx);CHKERRQ(ierr);
726 
727   if (solutionfunction) {
728     PetscStackPush("TS user solution function");
729     ierr = (*solutionfunction)(ts,t,U,ctx);CHKERRQ(ierr);
730     PetscStackPop;
731   }
732   PetscFunctionReturn(0);
733 }
734 /*@
735    TSComputeForcingFunction - Evaluates the forcing function.
736 
737    Collective on TS and Vec
738 
739    Input Parameters:
740 +  ts - the TS context
741 -  t - current time
742 
743    Output Parameter:
744 .  U - the function value
745 
746    Note:
747    Most users should not need to explicitly call this routine, as it
748    is used internally within the nonlinear solvers.
749 
750    Level: developer
751 
752 .keywords: TS, compute
753 
754 .seealso: TSSetSolutionFunction(), TSSetRHSFunction(), TSComputeIFunction()
755 @*/
756 PetscErrorCode TSComputeForcingFunction(TS ts,PetscReal t,Vec U)
757 {
758   PetscErrorCode     ierr, (*forcing)(TS,PetscReal,Vec,void*);
759   void               *ctx;
760   DM                 dm;
761 
762   PetscFunctionBegin;
763   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
764   PetscValidHeaderSpecific(U,VEC_CLASSID,3);
765   ierr = TSGetDM(ts,&dm);CHKERRQ(ierr);
766   ierr = DMTSGetForcingFunction(dm,&forcing,&ctx);CHKERRQ(ierr);
767 
768   if (forcing) {
769     PetscStackPush("TS user forcing function");
770     ierr = (*forcing)(ts,t,U,ctx);CHKERRQ(ierr);
771     PetscStackPop;
772   }
773   PetscFunctionReturn(0);
774 }
775 
776 static PetscErrorCode TSGetRHSVec_Private(TS ts,Vec *Frhs)
777 {
778   Vec            F;
779   PetscErrorCode ierr;
780 
781   PetscFunctionBegin;
782   *Frhs = NULL;
783   ierr  = TSGetIFunction(ts,&F,NULL,NULL);CHKERRQ(ierr);
784   if (!ts->Frhs) {
785     ierr = VecDuplicate(F,&ts->Frhs);CHKERRQ(ierr);
786   }
787   *Frhs = ts->Frhs;
788   PetscFunctionReturn(0);
789 }
790 
791 static PetscErrorCode TSGetRHSMats_Private(TS ts,Mat *Arhs,Mat *Brhs)
792 {
793   Mat            A,B;
794   PetscErrorCode ierr;
795 
796   PetscFunctionBegin;
797   if (Arhs) *Arhs = NULL;
798   if (Brhs) *Brhs = NULL;
799   ierr = TSGetIJacobian(ts,&A,&B,NULL,NULL);CHKERRQ(ierr);
800   if (Arhs) {
801     if (!ts->Arhs) {
802       ierr = MatDuplicate(A,MAT_DO_NOT_COPY_VALUES,&ts->Arhs);CHKERRQ(ierr);
803     }
804     *Arhs = ts->Arhs;
805   }
806   if (Brhs) {
807     if (!ts->Brhs) {
808       if (A != B) {
809         ierr = MatDuplicate(B,MAT_DO_NOT_COPY_VALUES,&ts->Brhs);CHKERRQ(ierr);
810       } else {
811         ierr = PetscObjectReference((PetscObject)ts->Arhs);CHKERRQ(ierr);
812         ts->Brhs = ts->Arhs;
813       }
814     }
815     *Brhs = ts->Brhs;
816   }
817   PetscFunctionReturn(0);
818 }
819 
820 /*@
821    TSComputeIFunction - Evaluates the DAE residual written in implicit form F(t,U,Udot)=0
822 
823    Collective on TS and Vec
824 
825    Input Parameters:
826 +  ts - the TS context
827 .  t - current time
828 .  U - state vector
829 .  Udot - time derivative of state vector
830 -  imex - flag indicates if the method is IMEX so that the RHSFunction should be kept separate
831 
832    Output Parameter:
833 .  Y - right hand side
834 
835    Note:
836    Most users should not need to explicitly call this routine, as it
837    is used internally within the nonlinear solvers.
838 
839    If the user did did not write their equations in implicit form, this
840    function recasts them in implicit form.
841 
842    Level: developer
843 
844 .keywords: TS, compute
845 
846 .seealso: TSSetIFunction(), TSComputeRHSFunction()
847 @*/
848 PetscErrorCode TSComputeIFunction(TS ts,PetscReal t,Vec U,Vec Udot,Vec Y,PetscBool imex)
849 {
850   PetscErrorCode ierr;
851   TSIFunction    ifunction;
852   TSRHSFunction  rhsfunction;
853   void           *ctx;
854   DM             dm;
855 
856   PetscFunctionBegin;
857   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
858   PetscValidHeaderSpecific(U,VEC_CLASSID,3);
859   PetscValidHeaderSpecific(Udot,VEC_CLASSID,4);
860   PetscValidHeaderSpecific(Y,VEC_CLASSID,5);
861 
862   ierr = TSGetDM(ts,&dm);CHKERRQ(ierr);
863   ierr = DMTSGetIFunction(dm,&ifunction,&ctx);CHKERRQ(ierr);
864   ierr = DMTSGetRHSFunction(dm,&rhsfunction,NULL);CHKERRQ(ierr);
865 
866   if (!rhsfunction && !ifunction) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSFunction() and / or TSSetIFunction()");
867 
868   ierr = PetscLogEventBegin(TS_FunctionEval,ts,U,Udot,Y);CHKERRQ(ierr);
869   if (ifunction) {
870     PetscStackPush("TS user implicit function");
871     ierr = (*ifunction)(ts,t,U,Udot,Y,ctx);CHKERRQ(ierr);
872     PetscStackPop;
873   }
874   if (imex) {
875     if (!ifunction) {
876       ierr = VecCopy(Udot,Y);CHKERRQ(ierr);
877     }
878   } else if (rhsfunction) {
879     if (ifunction) {
880       Vec Frhs;
881       ierr = TSGetRHSVec_Private(ts,&Frhs);CHKERRQ(ierr);
882       ierr = TSComputeRHSFunction(ts,t,U,Frhs);CHKERRQ(ierr);
883       ierr = VecAXPY(Y,-1,Frhs);CHKERRQ(ierr);
884     } else {
885       ierr = TSComputeRHSFunction(ts,t,U,Y);CHKERRQ(ierr);
886       ierr = VecAYPX(Y,-1,Udot);CHKERRQ(ierr);
887     }
888   }
889   ierr = PetscLogEventEnd(TS_FunctionEval,ts,U,Udot,Y);CHKERRQ(ierr);
890   PetscFunctionReturn(0);
891 }
892 
893 /*@
894    TSComputeIJacobian - Evaluates the Jacobian of the DAE
895 
896    Collective on TS and Vec
897 
898    Input
899       Input Parameters:
900 +  ts - the TS context
901 .  t - current timestep
902 .  U - state vector
903 .  Udot - time derivative of state vector
904 .  shift - shift to apply, see note below
905 -  imex - flag indicates if the method is IMEX so that the RHSJacobian should be kept separate
906 
907    Output Parameters:
908 +  A - Jacobian matrix
909 .  B - optional preconditioning matrix
910 -  flag - flag indicating matrix structure
911 
912    Notes:
913    If F(t,U,Udot)=0 is the DAE, the required Jacobian is
914 
915    dF/dU + shift*dF/dUdot
916 
917    Most users should not need to explicitly call this routine, as it
918    is used internally within the nonlinear solvers.
919 
920    Level: developer
921 
922 .keywords: TS, compute, Jacobian, matrix
923 
924 .seealso:  TSSetIJacobian()
925 @*/
926 PetscErrorCode TSComputeIJacobian(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat A,Mat B,PetscBool imex)
927 {
928   PetscErrorCode ierr;
929   TSIJacobian    ijacobian;
930   TSRHSJacobian  rhsjacobian;
931   DM             dm;
932   void           *ctx;
933 
934   PetscFunctionBegin;
935   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
936   PetscValidHeaderSpecific(U,VEC_CLASSID,3);
937   PetscValidHeaderSpecific(Udot,VEC_CLASSID,4);
938   PetscValidPointer(A,6);
939   PetscValidHeaderSpecific(A,MAT_CLASSID,6);
940   PetscValidPointer(B,7);
941   PetscValidHeaderSpecific(B,MAT_CLASSID,7);
942 
943   ierr = TSGetDM(ts,&dm);CHKERRQ(ierr);
944   ierr = DMTSGetIJacobian(dm,&ijacobian,&ctx);CHKERRQ(ierr);
945   ierr = DMTSGetRHSJacobian(dm,&rhsjacobian,NULL);CHKERRQ(ierr);
946 
947   if (!rhsjacobian && !ijacobian) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSJacobian() and / or TSSetIJacobian()");
948 
949   ierr = PetscLogEventBegin(TS_JacobianEval,ts,U,A,B);CHKERRQ(ierr);
950   if (ijacobian) {
951     PetscBool missing;
952     PetscStackPush("TS user implicit Jacobian");
953     ierr = (*ijacobian)(ts,t,U,Udot,shift,A,B,ctx);CHKERRQ(ierr);
954     PetscStackPop;
955     if (A) {
956       ierr = MatMissingDiagonal(A,&missing,NULL);CHKERRQ(ierr);
957       if (missing) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Amat passed to TSSetIJacobian() must have all diagonal entries set, if they are zero you must still set them with a zero value");
958     }
959     if (B && B != A) {
960       ierr = MatMissingDiagonal(B,&missing,NULL);CHKERRQ(ierr);
961       if (missing) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Bmat passed to TSSetIJacobian() must have all diagonal entries set, if they are zero you must still set them with a zero value");
962     }
963   }
964   if (imex) {
965     if (!ijacobian) {  /* system was written as Udot = G(t,U) */
966       PetscBool assembled;
967       ierr = MatZeroEntries(A);CHKERRQ(ierr);
968       ierr = MatAssembled(A,&assembled);CHKERRQ(ierr);
969       if (!assembled) {
970         ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
971         ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
972       }
973       ierr = MatShift(A,shift);CHKERRQ(ierr);
974       if (A != B) {
975         ierr = MatZeroEntries(B);CHKERRQ(ierr);
976         ierr = MatAssembled(B,&assembled);CHKERRQ(ierr);
977         if (!assembled) {
978           ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
979           ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
980         }
981         ierr = MatShift(B,shift);CHKERRQ(ierr);
982       }
983     }
984   } else {
985     Mat Arhs = NULL,Brhs = NULL;
986     if (rhsjacobian) {
987       ierr = TSGetRHSMats_Private(ts,&Arhs,&Brhs);CHKERRQ(ierr);
988       ierr = TSComputeRHSJacobian(ts,t,U,Arhs,Brhs);CHKERRQ(ierr);
989     }
990     if (Arhs == A) {           /* No IJacobian, so we only have the RHS matrix */
991       ts->rhsjacobian.scale = -1;
992       ts->rhsjacobian.shift = shift;
993       ierr = MatScale(A,-1);CHKERRQ(ierr);
994       ierr = MatShift(A,shift);CHKERRQ(ierr);
995       if (A != B) {
996         ierr = MatScale(B,-1);CHKERRQ(ierr);
997         ierr = MatShift(B,shift);CHKERRQ(ierr);
998       }
999     } else if (Arhs) {          /* Both IJacobian and RHSJacobian */
1000       MatStructure axpy = DIFFERENT_NONZERO_PATTERN;
1001       if (!ijacobian) {         /* No IJacobian provided, but we have a separate RHS matrix */
1002         ierr = MatZeroEntries(A);CHKERRQ(ierr);
1003         ierr = MatShift(A,shift);CHKERRQ(ierr);
1004         if (A != B) {
1005           ierr = MatZeroEntries(B);CHKERRQ(ierr);
1006           ierr = MatShift(B,shift);CHKERRQ(ierr);
1007         }
1008       }
1009       ierr = MatAXPY(A,-1,Arhs,axpy);CHKERRQ(ierr);
1010       if (A != B) {
1011         ierr = MatAXPY(B,-1,Brhs,axpy);CHKERRQ(ierr);
1012       }
1013     }
1014   }
1015   ierr = PetscLogEventEnd(TS_JacobianEval,ts,U,A,B);CHKERRQ(ierr);
1016   PetscFunctionReturn(0);
1017 }
1018 
1019 /*@C
1020     TSSetRHSFunction - Sets the routine for evaluating the function,
1021     where U_t = G(t,u).
1022 
1023     Logically Collective on TS
1024 
1025     Input Parameters:
1026 +   ts - the TS context obtained from TSCreate()
1027 .   r - vector to put the computed right hand side (or NULL to have it created)
1028 .   f - routine for evaluating the right-hand-side function
1029 -   ctx - [optional] user-defined context for private data for the
1030           function evaluation routine (may be NULL)
1031 
1032     Calling sequence of func:
1033 $     func (TS ts,PetscReal t,Vec u,Vec F,void *ctx);
1034 
1035 +   t - current timestep
1036 .   u - input vector
1037 .   F - function vector
1038 -   ctx - [optional] user-defined function context
1039 
1040     Level: beginner
1041 
1042     Notes: You must call this function or TSSetIFunction() to define your ODE. You cannot use this function when solving a DAE.
1043 
1044 .keywords: TS, timestep, set, right-hand-side, function
1045 
1046 .seealso: TSSetRHSJacobian(), TSSetIJacobian(), TSSetIFunction()
1047 @*/
1048 PetscErrorCode  TSSetRHSFunction(TS ts,Vec r,PetscErrorCode (*f)(TS,PetscReal,Vec,Vec,void*),void *ctx)
1049 {
1050   PetscErrorCode ierr;
1051   SNES           snes;
1052   Vec            ralloc = NULL;
1053   DM             dm;
1054 
1055   PetscFunctionBegin;
1056   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
1057   if (r) PetscValidHeaderSpecific(r,VEC_CLASSID,2);
1058 
1059   ierr = TSGetDM(ts,&dm);CHKERRQ(ierr);
1060   ierr = DMTSSetRHSFunction(dm,f,ctx);CHKERRQ(ierr);
1061   ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr);
1062   if (!r && !ts->dm && ts->vec_sol) {
1063     ierr = VecDuplicate(ts->vec_sol,&ralloc);CHKERRQ(ierr);
1064     r = ralloc;
1065   }
1066   ierr = SNESSetFunction(snes,r,SNESTSFormFunction,ts);CHKERRQ(ierr);
1067   ierr = VecDestroy(&ralloc);CHKERRQ(ierr);
1068   PetscFunctionReturn(0);
1069 }
1070 
1071 /*@C
1072     TSSetSolutionFunction - Provide a function that computes the solution of the ODE or DAE
1073 
1074     Logically Collective on TS
1075 
1076     Input Parameters:
1077 +   ts - the TS context obtained from TSCreate()
1078 .   f - routine for evaluating the solution
1079 -   ctx - [optional] user-defined context for private data for the
1080           function evaluation routine (may be NULL)
1081 
1082     Calling sequence of func:
1083 $     func (TS ts,PetscReal t,Vec u,void *ctx);
1084 
1085 +   t - current timestep
1086 .   u - output vector
1087 -   ctx - [optional] user-defined function context
1088 
1089     Notes:
1090     This routine is used for testing accuracy of time integration schemes when you already know the solution.
1091     If analytic solutions are not known for your system, consider using the Method of Manufactured Solutions to
1092     create closed-form solutions with non-physical forcing terms.
1093 
1094     For low-dimensional problems solved in serial, such as small discrete systems, TSMonitorLGError() can be used to monitor the error history.
1095 
1096     Level: beginner
1097 
1098 .keywords: TS, timestep, set, right-hand-side, function
1099 
1100 .seealso: TSSetRHSJacobian(), TSSetIJacobian(), TSComputeSolutionFunction(), TSSetForcingFunction()
1101 @*/
1102 PetscErrorCode  TSSetSolutionFunction(TS ts,PetscErrorCode (*f)(TS,PetscReal,Vec,void*),void *ctx)
1103 {
1104   PetscErrorCode ierr;
1105   DM             dm;
1106 
1107   PetscFunctionBegin;
1108   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
1109   ierr = TSGetDM(ts,&dm);CHKERRQ(ierr);
1110   ierr = DMTSSetSolutionFunction(dm,f,ctx);CHKERRQ(ierr);
1111   PetscFunctionReturn(0);
1112 }
1113 
1114 /*@C
1115     TSSetForcingFunction - Provide a function that computes a forcing term for a ODE or PDE
1116 
1117     Logically Collective on TS
1118 
1119     Input Parameters:
1120 +   ts - the TS context obtained from TSCreate()
1121 .   func - routine for evaluating the forcing function
1122 -   ctx - [optional] user-defined context for private data for the
1123           function evaluation routine (may be NULL)
1124 
1125     Calling sequence of func:
1126 $     func (TS ts,PetscReal t,Vec f,void *ctx);
1127 
1128 +   t - current timestep
1129 .   f - output vector
1130 -   ctx - [optional] user-defined function context
1131 
1132     Notes:
1133     This routine is useful for testing accuracy of time integration schemes when using the Method of Manufactured Solutions to
1134     create closed-form solutions with a non-physical forcing term. It allows you to use the Method of Manufactored Solution without directly editing the
1135     definition of the problem you are solving and hence possibly introducing bugs.
1136 
1137     This replaces the ODE F(u,u_t,t) = 0 the TS is solving with F(u,u_t,t) - func(t) = 0
1138 
1139     This forcing function does not depend on the solution to the equations, it can only depend on spatial location, time, and possibly parameters, the
1140     parameters can be passed in the ctx variable.
1141 
1142     For low-dimensional problems solved in serial, such as small discrete systems, TSMonitorLGError() can be used to monitor the error history.
1143 
1144     Level: beginner
1145 
1146 .keywords: TS, timestep, set, right-hand-side, function
1147 
1148 .seealso: TSSetRHSJacobian(), TSSetIJacobian(), TSComputeSolutionFunction(), TSSetSolutionFunction()
1149 @*/
1150 PetscErrorCode  TSSetForcingFunction(TS ts,TSForcingFunction func,void *ctx)
1151 {
1152   PetscErrorCode ierr;
1153   DM             dm;
1154 
1155   PetscFunctionBegin;
1156   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
1157   ierr = TSGetDM(ts,&dm);CHKERRQ(ierr);
1158   ierr = DMTSSetForcingFunction(dm,func,ctx);CHKERRQ(ierr);
1159   PetscFunctionReturn(0);
1160 }
1161 
1162 /*@C
1163    TSSetRHSJacobian - Sets the function to compute the Jacobian of G,
1164    where U_t = G(U,t), as well as the location to store the matrix.
1165 
1166    Logically Collective on TS
1167 
1168    Input Parameters:
1169 +  ts  - the TS context obtained from TSCreate()
1170 .  Amat - (approximate) Jacobian matrix
1171 .  Pmat - matrix from which preconditioner is to be constructed (usually the same as Amat)
1172 .  f   - the Jacobian evaluation routine
1173 -  ctx - [optional] user-defined context for private data for the
1174          Jacobian evaluation routine (may be NULL)
1175 
1176    Calling sequence of f:
1177 $     func (TS ts,PetscReal t,Vec u,Mat A,Mat B,void *ctx);
1178 
1179 +  t - current timestep
1180 .  u - input vector
1181 .  Amat - (approximate) Jacobian matrix
1182 .  Pmat - matrix from which preconditioner is to be constructed (usually the same as Amat)
1183 -  ctx - [optional] user-defined context for matrix evaluation routine
1184 
1185    Notes:
1186    You must set all the diagonal entries of the matrices, if they are zero you must still set them with a zero value
1187 
1188    The TS solver may modify the nonzero structure and the entries of the matrices Amat and Pmat between the calls to f()
1189    You should not assume the values are the same in the next call to f() as you set them in the previous call.
1190 
1191    Level: beginner
1192 
1193 .keywords: TS, timestep, set, right-hand-side, Jacobian
1194 
1195 .seealso: SNESComputeJacobianDefaultColor(), TSSetRHSFunction(), TSRHSJacobianSetReuse(), TSSetIJacobian()
1196 
1197 @*/
1198 PetscErrorCode  TSSetRHSJacobian(TS ts,Mat Amat,Mat Pmat,TSRHSJacobian f,void *ctx)
1199 {
1200   PetscErrorCode ierr;
1201   SNES           snes;
1202   DM             dm;
1203   TSIJacobian    ijacobian;
1204 
1205   PetscFunctionBegin;
1206   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
1207   if (Amat) PetscValidHeaderSpecific(Amat,MAT_CLASSID,2);
1208   if (Pmat) PetscValidHeaderSpecific(Pmat,MAT_CLASSID,3);
1209   if (Amat) PetscCheckSameComm(ts,1,Amat,2);
1210   if (Pmat) PetscCheckSameComm(ts,1,Pmat,3);
1211 
1212   ierr = TSGetDM(ts,&dm);CHKERRQ(ierr);
1213   ierr = DMTSSetRHSJacobian(dm,f,ctx);CHKERRQ(ierr);
1214   if (f == TSComputeRHSJacobianConstant) {
1215     /* Handle this case automatically for the user; otherwise user should call themselves. */
1216     ierr = TSRHSJacobianSetReuse(ts,PETSC_TRUE);CHKERRQ(ierr);
1217   }
1218   ierr = DMTSGetIJacobian(dm,&ijacobian,NULL);CHKERRQ(ierr);
1219   ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr);
1220   if (!ijacobian) {
1221     ierr = SNESSetJacobian(snes,Amat,Pmat,SNESTSFormJacobian,ts);CHKERRQ(ierr);
1222   }
1223   if (Amat) {
1224     ierr = PetscObjectReference((PetscObject)Amat);CHKERRQ(ierr);
1225     ierr = MatDestroy(&ts->Arhs);CHKERRQ(ierr);
1226     ts->Arhs = Amat;
1227   }
1228   if (Pmat) {
1229     ierr = PetscObjectReference((PetscObject)Pmat);CHKERRQ(ierr);
1230     ierr = MatDestroy(&ts->Brhs);CHKERRQ(ierr);
1231     ts->Brhs = Pmat;
1232   }
1233   PetscFunctionReturn(0);
1234 }
1235 
1236 
1237 /*@C
1238    TSSetIFunction - Set the function to compute F(t,U,U_t) where F() = 0 is the DAE to be solved.
1239 
1240    Logically Collective on TS
1241 
1242    Input Parameters:
1243 +  ts  - the TS context obtained from TSCreate()
1244 .  r   - vector to hold the residual (or NULL to have it created internally)
1245 .  f   - the function evaluation routine
1246 -  ctx - user-defined context for private data for the function evaluation routine (may be NULL)
1247 
1248    Calling sequence of f:
1249 $  f(TS ts,PetscReal t,Vec u,Vec u_t,Vec F,ctx);
1250 
1251 +  t   - time at step/stage being solved
1252 .  u   - state vector
1253 .  u_t - time derivative of state vector
1254 .  F   - function vector
1255 -  ctx - [optional] user-defined context for matrix evaluation routine
1256 
1257    Important:
1258    The user MUST call either this routine or TSSetRHSFunction() to define the ODE.  When solving DAEs you must use this function.
1259 
1260    Level: beginner
1261 
1262 .keywords: TS, timestep, set, DAE, Jacobian
1263 
1264 .seealso: TSSetRHSJacobian(), TSSetRHSFunction(), TSSetIJacobian()
1265 @*/
1266 PetscErrorCode  TSSetIFunction(TS ts,Vec r,TSIFunction f,void *ctx)
1267 {
1268   PetscErrorCode ierr;
1269   SNES           snes;
1270   Vec            ralloc = NULL;
1271   DM             dm;
1272 
1273   PetscFunctionBegin;
1274   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
1275   if (r) PetscValidHeaderSpecific(r,VEC_CLASSID,2);
1276 
1277   ierr = TSGetDM(ts,&dm);CHKERRQ(ierr);
1278   ierr = DMTSSetIFunction(dm,f,ctx);CHKERRQ(ierr);
1279 
1280   ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr);
1281   if (!r && !ts->dm && ts->vec_sol) {
1282     ierr = VecDuplicate(ts->vec_sol,&ralloc);CHKERRQ(ierr);
1283     r  = ralloc;
1284   }
1285   ierr = SNESSetFunction(snes,r,SNESTSFormFunction,ts);CHKERRQ(ierr);
1286   ierr = VecDestroy(&ralloc);CHKERRQ(ierr);
1287   PetscFunctionReturn(0);
1288 }
1289 
1290 /*@C
1291    TSGetIFunction - Returns the vector where the implicit residual is stored and the function/contex to compute it.
1292 
1293    Not Collective
1294 
1295    Input Parameter:
1296 .  ts - the TS context
1297 
1298    Output Parameter:
1299 +  r - vector to hold residual (or NULL)
1300 .  func - the function to compute residual (or NULL)
1301 -  ctx - the function context (or NULL)
1302 
1303    Level: advanced
1304 
1305 .keywords: TS, nonlinear, get, function
1306 
1307 .seealso: TSSetIFunction(), SNESGetFunction()
1308 @*/
1309 PetscErrorCode TSGetIFunction(TS ts,Vec *r,TSIFunction *func,void **ctx)
1310 {
1311   PetscErrorCode ierr;
1312   SNES           snes;
1313   DM             dm;
1314 
1315   PetscFunctionBegin;
1316   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
1317   ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr);
1318   ierr = SNESGetFunction(snes,r,NULL,NULL);CHKERRQ(ierr);
1319   ierr = TSGetDM(ts,&dm);CHKERRQ(ierr);
1320   ierr = DMTSGetIFunction(dm,func,ctx);CHKERRQ(ierr);
1321   PetscFunctionReturn(0);
1322 }
1323 
1324 /*@C
1325    TSGetRHSFunction - Returns the vector where the right hand side is stored and the function/context to compute it.
1326 
1327    Not Collective
1328 
1329    Input Parameter:
1330 .  ts - the TS context
1331 
1332    Output Parameter:
1333 +  r - vector to hold computed right hand side (or NULL)
1334 .  func - the function to compute right hand side (or NULL)
1335 -  ctx - the function context (or NULL)
1336 
1337    Level: advanced
1338 
1339 .keywords: TS, nonlinear, get, function
1340 
1341 .seealso: TSSetRHSFunction(), SNESGetFunction()
1342 @*/
1343 PetscErrorCode TSGetRHSFunction(TS ts,Vec *r,TSRHSFunction *func,void **ctx)
1344 {
1345   PetscErrorCode ierr;
1346   SNES           snes;
1347   DM             dm;
1348 
1349   PetscFunctionBegin;
1350   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
1351   ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr);
1352   ierr = SNESGetFunction(snes,r,NULL,NULL);CHKERRQ(ierr);
1353   ierr = TSGetDM(ts,&dm);CHKERRQ(ierr);
1354   ierr = DMTSGetRHSFunction(dm,func,ctx);CHKERRQ(ierr);
1355   PetscFunctionReturn(0);
1356 }
1357 
1358 /*@C
1359    TSSetIJacobian - Set the function to compute the matrix dF/dU + a*dF/dU_t where F(t,U,U_t) is the function
1360         provided with TSSetIFunction().
1361 
1362    Logically Collective on TS
1363 
1364    Input Parameters:
1365 +  ts  - the TS context obtained from TSCreate()
1366 .  Amat - (approximate) Jacobian matrix
1367 .  Pmat - matrix used to compute preconditioner (usually the same as Amat)
1368 .  f   - the Jacobian evaluation routine
1369 -  ctx - user-defined context for private data for the Jacobian evaluation routine (may be NULL)
1370 
1371    Calling sequence of f:
1372 $  f(TS ts,PetscReal t,Vec U,Vec U_t,PetscReal a,Mat Amat,Mat Pmat,void *ctx);
1373 
1374 +  t    - time at step/stage being solved
1375 .  U    - state vector
1376 .  U_t  - time derivative of state vector
1377 .  a    - shift
1378 .  Amat - (approximate) Jacobian of F(t,U,W+a*U), equivalent to dF/dU + a*dF/dU_t
1379 .  Pmat - matrix used for constructing preconditioner, usually the same as Amat
1380 -  ctx  - [optional] user-defined context for matrix evaluation routine
1381 
1382    Notes:
1383    The matrices Amat and Pmat are exactly the matrices that are used by SNES for the nonlinear solve.
1384 
1385    If you know the operator Amat has a null space you can use MatSetNullSpace() and MatSetTransposeNullSpace() to supply the null
1386    space to Amat and the KSP solvers will automatically use that null space as needed during the solution process.
1387 
1388    The matrix dF/dU + a*dF/dU_t you provide turns out to be
1389    the Jacobian of F(t,U,W+a*U) where F(t,U,U_t) = 0 is the DAE to be solved.
1390    The time integrator internally approximates U_t by W+a*U where the positive "shift"
1391    a and vector W depend on the integration method, step size, and past states. For example with
1392    the backward Euler method a = 1/dt and W = -a*U(previous timestep) so
1393    W + a*U = a*(U - U(previous timestep)) = (U - U(previous timestep))/dt
1394 
1395    You must set all the diagonal entries of the matrices, if they are zero you must still set them with a zero value
1396 
1397    The TS solver may modify the nonzero structure and the entries of the matrices Amat and Pmat between the calls to f()
1398    You should not assume the values are the same in the next call to f() as you set them in the previous call.
1399 
1400    Level: beginner
1401 
1402 .keywords: TS, timestep, DAE, Jacobian
1403 
1404 .seealso: TSSetIFunction(), TSSetRHSJacobian(), SNESComputeJacobianDefaultColor(), SNESComputeJacobianDefault(), TSSetRHSFunction()
1405 
1406 @*/
1407 PetscErrorCode  TSSetIJacobian(TS ts,Mat Amat,Mat Pmat,TSIJacobian f,void *ctx)
1408 {
1409   PetscErrorCode ierr;
1410   SNES           snes;
1411   DM             dm;
1412 
1413   PetscFunctionBegin;
1414   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
1415   if (Amat) PetscValidHeaderSpecific(Amat,MAT_CLASSID,2);
1416   if (Pmat) PetscValidHeaderSpecific(Pmat,MAT_CLASSID,3);
1417   if (Amat) PetscCheckSameComm(ts,1,Amat,2);
1418   if (Pmat) PetscCheckSameComm(ts,1,Pmat,3);
1419 
1420   ierr = TSGetDM(ts,&dm);CHKERRQ(ierr);
1421   ierr = DMTSSetIJacobian(dm,f,ctx);CHKERRQ(ierr);
1422 
1423   ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr);
1424   ierr = SNESSetJacobian(snes,Amat,Pmat,SNESTSFormJacobian,ts);CHKERRQ(ierr);
1425   PetscFunctionReturn(0);
1426 }
1427 
1428 /*@
1429    TSRHSJacobianSetReuse - restore RHS Jacobian before re-evaluating.  Without this flag, TS will change the sign and
1430    shift the RHS Jacobian for a finite-time-step implicit solve, in which case the user function will need to recompute
1431    the entire Jacobian.  The reuse flag must be set if the evaluation function will assume that the matrix entries have
1432    not been changed by the TS.
1433 
1434    Logically Collective
1435 
1436    Input Arguments:
1437 +  ts - TS context obtained from TSCreate()
1438 -  reuse - PETSC_TRUE if the RHS Jacobian
1439 
1440    Level: intermediate
1441 
1442 .seealso: TSSetRHSJacobian(), TSComputeRHSJacobianConstant()
1443 @*/
1444 PetscErrorCode TSRHSJacobianSetReuse(TS ts,PetscBool reuse)
1445 {
1446   PetscFunctionBegin;
1447   ts->rhsjacobian.reuse = reuse;
1448   PetscFunctionReturn(0);
1449 }
1450 
1451 /*@C
1452    TSSetI2Function - Set the function to compute F(t,U,U_t,U_tt) where F = 0 is the DAE to be solved.
1453 
1454    Logically Collective on TS
1455 
1456    Input Parameters:
1457 +  ts  - the TS context obtained from TSCreate()
1458 .  F   - vector to hold the residual (or NULL to have it created internally)
1459 .  fun - the function evaluation routine
1460 -  ctx - user-defined context for private data for the function evaluation routine (may be NULL)
1461 
1462    Calling sequence of fun:
1463 $  fun(TS ts,PetscReal t,Vec U,Vec U_t,Vec U_tt,Vec F,ctx);
1464 
1465 +  t    - time at step/stage being solved
1466 .  U    - state vector
1467 .  U_t  - time derivative of state vector
1468 .  U_tt - second time derivative of state vector
1469 .  F    - function vector
1470 -  ctx  - [optional] user-defined context for matrix evaluation routine (may be NULL)
1471 
1472    Level: beginner
1473 
1474 .keywords: TS, timestep, set, ODE, DAE, Function
1475 
1476 .seealso: TSSetI2Jacobian()
1477 @*/
1478 PetscErrorCode TSSetI2Function(TS ts,Vec F,TSI2Function fun,void *ctx)
1479 {
1480   DM             dm;
1481   PetscErrorCode ierr;
1482 
1483   PetscFunctionBegin;
1484   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
1485   if (F) PetscValidHeaderSpecific(F,VEC_CLASSID,2);
1486   ierr = TSSetIFunction(ts,F,NULL,NULL);CHKERRQ(ierr);
1487   ierr = TSGetDM(ts,&dm);CHKERRQ(ierr);
1488   ierr = DMTSSetI2Function(dm,fun,ctx);CHKERRQ(ierr);
1489   PetscFunctionReturn(0);
1490 }
1491 
1492 /*@C
1493   TSGetI2Function - Returns the vector where the implicit residual is stored and the function/contex to compute it.
1494 
1495   Not Collective
1496 
1497   Input Parameter:
1498 . ts - the TS context
1499 
1500   Output Parameter:
1501 + r - vector to hold residual (or NULL)
1502 . fun - the function to compute residual (or NULL)
1503 - ctx - the function context (or NULL)
1504 
1505   Level: advanced
1506 
1507 .keywords: TS, nonlinear, get, function
1508 
1509 .seealso: TSSetI2Function(), SNESGetFunction()
1510 @*/
1511 PetscErrorCode TSGetI2Function(TS ts,Vec *r,TSI2Function *fun,void **ctx)
1512 {
1513   PetscErrorCode ierr;
1514   SNES           snes;
1515   DM             dm;
1516 
1517   PetscFunctionBegin;
1518   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
1519   ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr);
1520   ierr = SNESGetFunction(snes,r,NULL,NULL);CHKERRQ(ierr);
1521   ierr = TSGetDM(ts,&dm);CHKERRQ(ierr);
1522   ierr = DMTSGetI2Function(dm,fun,ctx);CHKERRQ(ierr);
1523   PetscFunctionReturn(0);
1524 }
1525 
1526 /*@C
1527    TSSetI2Jacobian - Set the function to compute the matrix dF/dU + v*dF/dU_t  + a*dF/dU_tt
1528         where F(t,U,U_t,U_tt) is the function you provided with TSSetI2Function().
1529 
1530    Logically Collective on TS
1531 
1532    Input Parameters:
1533 +  ts  - the TS context obtained from TSCreate()
1534 .  J   - Jacobian matrix
1535 .  P   - preconditioning matrix for J (may be same as J)
1536 .  jac - the Jacobian evaluation routine
1537 -  ctx - user-defined context for private data for the Jacobian evaluation routine (may be NULL)
1538 
1539    Calling sequence of jac:
1540 $  jac(TS ts,PetscReal t,Vec U,Vec U_t,Vec U_tt,PetscReal v,PetscReal a,Mat J,Mat P,void *ctx);
1541 
1542 +  t    - time at step/stage being solved
1543 .  U    - state vector
1544 .  U_t  - time derivative of state vector
1545 .  U_tt - second time derivative of state vector
1546 .  v    - shift for U_t
1547 .  a    - shift for U_tt
1548 .  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
1549 .  P    - preconditioning matrix for J, may be same as J
1550 -  ctx  - [optional] user-defined context for matrix evaluation routine
1551 
1552    Notes:
1553    The matrices J and P are exactly the matrices that are used by SNES for the nonlinear solve.
1554 
1555    The matrix dF/dU + v*dF/dU_t + a*dF/dU_tt you provide turns out to be
1556    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.
1557    The time integrator internally approximates U_t by W+v*U and U_tt by W'+a*U  where the positive "shift"
1558    parameters 'v' and 'a' and vectors W, W' depend on the integration method, step size, and past states.
1559 
1560    Level: beginner
1561 
1562 .keywords: TS, timestep, set, ODE, DAE, Jacobian
1563 
1564 .seealso: TSSetI2Function()
1565 @*/
1566 PetscErrorCode TSSetI2Jacobian(TS ts,Mat J,Mat P,TSI2Jacobian jac,void *ctx)
1567 {
1568   DM             dm;
1569   PetscErrorCode ierr;
1570 
1571   PetscFunctionBegin;
1572   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
1573   if (J) PetscValidHeaderSpecific(J,MAT_CLASSID,2);
1574   if (P) PetscValidHeaderSpecific(P,MAT_CLASSID,3);
1575   ierr = TSSetIJacobian(ts,J,P,NULL,NULL);CHKERRQ(ierr);
1576   ierr = TSGetDM(ts,&dm);CHKERRQ(ierr);
1577   ierr = DMTSSetI2Jacobian(dm,jac,ctx);CHKERRQ(ierr);
1578   PetscFunctionReturn(0);
1579 }
1580 
1581 /*@C
1582   TSGetI2Jacobian - Returns the implicit Jacobian at the present timestep.
1583 
1584   Not Collective, but parallel objects are returned if TS is parallel
1585 
1586   Input Parameter:
1587 . ts  - The TS context obtained from TSCreate()
1588 
1589   Output Parameters:
1590 + J  - The (approximate) Jacobian of F(t,U,U_t,U_tt)
1591 . P - The matrix from which the preconditioner is constructed, often the same as J
1592 . jac - The function to compute the Jacobian matrices
1593 - ctx - User-defined context for Jacobian evaluation routine
1594 
1595   Notes: You can pass in NULL for any return argument you do not need.
1596 
1597   Level: advanced
1598 
1599 .seealso: TSGetTimeStep(), TSGetMatrices(), TSGetTime(), TSGetTimeStepNumber()
1600 
1601 .keywords: TS, timestep, get, matrix, Jacobian
1602 @*/
1603 PetscErrorCode  TSGetI2Jacobian(TS ts,Mat *J,Mat *P,TSI2Jacobian *jac,void **ctx)
1604 {
1605   PetscErrorCode ierr;
1606   SNES           snes;
1607   DM             dm;
1608 
1609   PetscFunctionBegin;
1610   ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr);
1611   ierr = SNESSetUpMatrices(snes);CHKERRQ(ierr);
1612   ierr = SNESGetJacobian(snes,J,P,NULL,NULL);CHKERRQ(ierr);
1613   ierr = TSGetDM(ts,&dm);CHKERRQ(ierr);
1614   ierr = DMTSGetI2Jacobian(dm,jac,ctx);CHKERRQ(ierr);
1615   PetscFunctionReturn(0);
1616 }
1617 
1618 /*@
1619   TSComputeI2Function - Evaluates the DAE residual written in implicit form F(t,U,U_t,U_tt) = 0
1620 
1621   Collective on TS and Vec
1622 
1623   Input Parameters:
1624 + ts - the TS context
1625 . t - current time
1626 . U - state vector
1627 . V - time derivative of state vector (U_t)
1628 - A - second time derivative of state vector (U_tt)
1629 
1630   Output Parameter:
1631 . F - the residual vector
1632 
1633   Note:
1634   Most users should not need to explicitly call this routine, as it
1635   is used internally within the nonlinear solvers.
1636 
1637   Level: developer
1638 
1639 .keywords: TS, compute, function, vector
1640 
1641 .seealso: TSSetI2Function()
1642 @*/
1643 PetscErrorCode TSComputeI2Function(TS ts,PetscReal t,Vec U,Vec V,Vec A,Vec F)
1644 {
1645   DM             dm;
1646   TSI2Function   I2Function;
1647   void           *ctx;
1648   TSRHSFunction  rhsfunction;
1649   PetscErrorCode ierr;
1650 
1651   PetscFunctionBegin;
1652   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
1653   PetscValidHeaderSpecific(U,VEC_CLASSID,3);
1654   PetscValidHeaderSpecific(V,VEC_CLASSID,4);
1655   PetscValidHeaderSpecific(A,VEC_CLASSID,5);
1656   PetscValidHeaderSpecific(F,VEC_CLASSID,6);
1657 
1658   ierr = TSGetDM(ts,&dm);CHKERRQ(ierr);
1659   ierr = DMTSGetI2Function(dm,&I2Function,&ctx);CHKERRQ(ierr);
1660   ierr = DMTSGetRHSFunction(dm,&rhsfunction,NULL);CHKERRQ(ierr);
1661 
1662   if (!I2Function) {
1663     ierr = TSComputeIFunction(ts,t,U,A,F,PETSC_FALSE);CHKERRQ(ierr);
1664     PetscFunctionReturn(0);
1665   }
1666 
1667   ierr = PetscLogEventBegin(TS_FunctionEval,ts,U,V,F);CHKERRQ(ierr);
1668 
1669   PetscStackPush("TS user implicit function");
1670   ierr = I2Function(ts,t,U,V,A,F,ctx);CHKERRQ(ierr);
1671   PetscStackPop;
1672 
1673   if (rhsfunction) {
1674     Vec Frhs;
1675     ierr = TSGetRHSVec_Private(ts,&Frhs);CHKERRQ(ierr);
1676     ierr = TSComputeRHSFunction(ts,t,U,Frhs);CHKERRQ(ierr);
1677     ierr = VecAXPY(F,-1,Frhs);CHKERRQ(ierr);
1678   }
1679 
1680   ierr = PetscLogEventEnd(TS_FunctionEval,ts,U,V,F);CHKERRQ(ierr);
1681   PetscFunctionReturn(0);
1682 }
1683 
1684 /*@
1685   TSComputeI2Jacobian - Evaluates the Jacobian of the DAE
1686 
1687   Collective on TS and Vec
1688 
1689   Input Parameters:
1690 + ts - the TS context
1691 . t - current timestep
1692 . U - state vector
1693 . V - time derivative of state vector
1694 . A - second time derivative of state vector
1695 . shiftV - shift to apply, see note below
1696 - shiftA - shift to apply, see note below
1697 
1698   Output Parameters:
1699 + J - Jacobian matrix
1700 - P - optional preconditioning matrix
1701 
1702   Notes:
1703   If F(t,U,V,A)=0 is the DAE, the required Jacobian is
1704 
1705   dF/dU + shiftV*dF/dV + shiftA*dF/dA
1706 
1707   Most users should not need to explicitly call this routine, as it
1708   is used internally within the nonlinear solvers.
1709 
1710   Level: developer
1711 
1712 .keywords: TS, compute, Jacobian, matrix
1713 
1714 .seealso:  TSSetI2Jacobian()
1715 @*/
1716 PetscErrorCode TSComputeI2Jacobian(TS ts,PetscReal t,Vec U,Vec V,Vec A,PetscReal shiftV,PetscReal shiftA,Mat J,Mat P)
1717 {
1718   DM             dm;
1719   TSI2Jacobian   I2Jacobian;
1720   void           *ctx;
1721   TSRHSJacobian  rhsjacobian;
1722   PetscErrorCode ierr;
1723 
1724   PetscFunctionBegin;
1725   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
1726   PetscValidHeaderSpecific(U,VEC_CLASSID,3);
1727   PetscValidHeaderSpecific(V,VEC_CLASSID,4);
1728   PetscValidHeaderSpecific(A,VEC_CLASSID,5);
1729   PetscValidHeaderSpecific(J,MAT_CLASSID,8);
1730   PetscValidHeaderSpecific(P,MAT_CLASSID,9);
1731 
1732   ierr = TSGetDM(ts,&dm);CHKERRQ(ierr);
1733   ierr = DMTSGetI2Jacobian(dm,&I2Jacobian,&ctx);CHKERRQ(ierr);
1734   ierr = DMTSGetRHSJacobian(dm,&rhsjacobian,NULL);CHKERRQ(ierr);
1735 
1736   if (!I2Jacobian) {
1737     ierr = TSComputeIJacobian(ts,t,U,A,shiftA,J,P,PETSC_FALSE);CHKERRQ(ierr);
1738     PetscFunctionReturn(0);
1739   }
1740 
1741   ierr = PetscLogEventBegin(TS_JacobianEval,ts,U,J,P);CHKERRQ(ierr);
1742 
1743   PetscStackPush("TS user implicit Jacobian");
1744   ierr = I2Jacobian(ts,t,U,V,A,shiftV,shiftA,J,P,ctx);CHKERRQ(ierr);
1745   PetscStackPop;
1746 
1747   if (rhsjacobian) {
1748     Mat Jrhs,Prhs; MatStructure axpy = DIFFERENT_NONZERO_PATTERN;
1749     ierr = TSGetRHSMats_Private(ts,&Jrhs,&Prhs);CHKERRQ(ierr);
1750     ierr = TSComputeRHSJacobian(ts,t,U,Jrhs,Prhs);CHKERRQ(ierr);
1751     ierr = MatAXPY(J,-1,Jrhs,axpy);CHKERRQ(ierr);
1752     if (P != J) {ierr = MatAXPY(P,-1,Prhs,axpy);CHKERRQ(ierr);}
1753   }
1754 
1755   ierr = PetscLogEventEnd(TS_JacobianEval,ts,U,J,P);CHKERRQ(ierr);
1756   PetscFunctionReturn(0);
1757 }
1758 
1759 /*@
1760    TS2SetSolution - Sets the initial solution and time derivative vectors
1761    for use by the TS routines handling second order equations.
1762 
1763    Logically Collective on TS and Vec
1764 
1765    Input Parameters:
1766 +  ts - the TS context obtained from TSCreate()
1767 .  u - the solution vector
1768 -  v - the time derivative vector
1769 
1770    Level: beginner
1771 
1772 .keywords: TS, timestep, set, solution, initial conditions
1773 @*/
1774 PetscErrorCode  TS2SetSolution(TS ts,Vec u,Vec v)
1775 {
1776   PetscErrorCode ierr;
1777 
1778   PetscFunctionBegin;
1779   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
1780   PetscValidHeaderSpecific(u,VEC_CLASSID,2);
1781   PetscValidHeaderSpecific(v,VEC_CLASSID,3);
1782   ierr = TSSetSolution(ts,u);CHKERRQ(ierr);
1783   ierr = PetscObjectReference((PetscObject)v);CHKERRQ(ierr);
1784   ierr = VecDestroy(&ts->vec_dot);CHKERRQ(ierr);
1785   ts->vec_dot = v;
1786   PetscFunctionReturn(0);
1787 }
1788 
1789 /*@
1790    TS2GetSolution - Returns the solution and time derivative at the present timestep
1791    for second order equations. It is valid to call this routine inside the function
1792    that you are evaluating in order to move to the new timestep. This vector not
1793    changed until the solution at the next timestep has been calculated.
1794 
1795    Not Collective, but Vec returned is parallel if TS is parallel
1796 
1797    Input Parameter:
1798 .  ts - the TS context obtained from TSCreate()
1799 
1800    Output Parameter:
1801 +  u - the vector containing the solution
1802 -  v - the vector containing the time derivative
1803 
1804    Level: intermediate
1805 
1806 .seealso: TS2SetSolution(), TSGetTimeStep(), TSGetTime()
1807 
1808 .keywords: TS, timestep, get, solution
1809 @*/
1810 PetscErrorCode  TS2GetSolution(TS ts,Vec *u,Vec *v)
1811 {
1812   PetscFunctionBegin;
1813   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
1814   if (u) PetscValidPointer(u,2);
1815   if (v) PetscValidPointer(v,3);
1816   if (u) *u = ts->vec_sol;
1817   if (v) *v = ts->vec_dot;
1818   PetscFunctionReturn(0);
1819 }
1820 
1821 /*@C
1822   TSLoad - Loads a KSP that has been stored in binary  with KSPView().
1823 
1824   Collective on PetscViewer
1825 
1826   Input Parameters:
1827 + newdm - the newly loaded TS, this needs to have been created with TSCreate() or
1828            some related function before a call to TSLoad().
1829 - viewer - binary file viewer, obtained from PetscViewerBinaryOpen()
1830 
1831    Level: intermediate
1832 
1833   Notes:
1834    The type is determined by the data in the file, any type set into the TS before this call is ignored.
1835 
1836   Notes for advanced users:
1837   Most users should not need to know the details of the binary storage
1838   format, since TSLoad() and TSView() completely hide these details.
1839   But for anyone who's interested, the standard binary matrix storage
1840   format is
1841 .vb
1842      has not yet been determined
1843 .ve
1844 
1845 .seealso: PetscViewerBinaryOpen(), TSView(), MatLoad(), VecLoad()
1846 @*/
1847 PetscErrorCode  TSLoad(TS ts, PetscViewer viewer)
1848 {
1849   PetscErrorCode ierr;
1850   PetscBool      isbinary;
1851   PetscInt       classid;
1852   char           type[256];
1853   DMTS           sdm;
1854   DM             dm;
1855 
1856   PetscFunctionBegin;
1857   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
1858   PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,2);
1859   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr);
1860   if (!isbinary) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid viewer; open viewer with PetscViewerBinaryOpen()");
1861 
1862   ierr = PetscViewerBinaryRead(viewer,&classid,1,NULL,PETSC_INT);CHKERRQ(ierr);
1863   if (classid != TS_FILE_CLASSID) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Not TS next in file");
1864   ierr = PetscViewerBinaryRead(viewer,type,256,NULL,PETSC_CHAR);CHKERRQ(ierr);
1865   ierr = TSSetType(ts, type);CHKERRQ(ierr);
1866   if (ts->ops->load) {
1867     ierr = (*ts->ops->load)(ts,viewer);CHKERRQ(ierr);
1868   }
1869   ierr = DMCreate(PetscObjectComm((PetscObject)ts),&dm);CHKERRQ(ierr);
1870   ierr = DMLoad(dm,viewer);CHKERRQ(ierr);
1871   ierr = TSSetDM(ts,dm);CHKERRQ(ierr);
1872   ierr = DMCreateGlobalVector(ts->dm,&ts->vec_sol);CHKERRQ(ierr);
1873   ierr = VecLoad(ts->vec_sol,viewer);CHKERRQ(ierr);
1874   ierr = DMGetDMTS(ts->dm,&sdm);CHKERRQ(ierr);
1875   ierr = DMTSLoad(sdm,viewer);CHKERRQ(ierr);
1876   PetscFunctionReturn(0);
1877 }
1878 
1879 #include <petscdraw.h>
1880 #if defined(PETSC_HAVE_SAWS)
1881 #include <petscviewersaws.h>
1882 #endif
1883 /*@C
1884     TSView - Prints the TS data structure.
1885 
1886     Collective on TS
1887 
1888     Input Parameters:
1889 +   ts - the TS context obtained from TSCreate()
1890 -   viewer - visualization context
1891 
1892     Options Database Key:
1893 .   -ts_view - calls TSView() at end of TSStep()
1894 
1895     Notes:
1896     The available visualization contexts include
1897 +     PETSC_VIEWER_STDOUT_SELF - standard output (default)
1898 -     PETSC_VIEWER_STDOUT_WORLD - synchronized standard
1899          output where only the first processor opens
1900          the file.  All other processors send their
1901          data to the first processor to print.
1902 
1903     The user can open an alternative visualization context with
1904     PetscViewerASCIIOpen() - output to a specified file.
1905 
1906     Level: beginner
1907 
1908 .keywords: TS, timestep, view
1909 
1910 .seealso: PetscViewerASCIIOpen()
1911 @*/
1912 PetscErrorCode  TSView(TS ts,PetscViewer viewer)
1913 {
1914   PetscErrorCode ierr;
1915   TSType         type;
1916   PetscBool      iascii,isstring,isundials,isbinary,isdraw;
1917   DMTS           sdm;
1918 #if defined(PETSC_HAVE_SAWS)
1919   PetscBool      issaws;
1920 #endif
1921 
1922   PetscFunctionBegin;
1923   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
1924   if (!viewer) {
1925     ierr = PetscViewerASCIIGetStdout(PetscObjectComm((PetscObject)ts),&viewer);CHKERRQ(ierr);
1926   }
1927   PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,2);
1928   PetscCheckSameComm(ts,1,viewer,2);
1929 
1930   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr);
1931   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSTRING,&isstring);CHKERRQ(ierr);
1932   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr);
1933   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr);
1934 #if defined(PETSC_HAVE_SAWS)
1935   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSAWS,&issaws);CHKERRQ(ierr);
1936 #endif
1937   if (iascii) {
1938     ierr = PetscObjectPrintClassNamePrefixType((PetscObject)ts,viewer);CHKERRQ(ierr);
1939     ierr = PetscViewerASCIIPrintf(viewer,"  maximum steps=%D\n",ts->max_steps);CHKERRQ(ierr);
1940     ierr = PetscViewerASCIIPrintf(viewer,"  maximum time=%g\n",(double)ts->max_time);CHKERRQ(ierr);
1941     if (ts->problem_type == TS_NONLINEAR) {
1942       ierr = PetscViewerASCIIPrintf(viewer,"  total number of nonlinear solver iterations=%D\n",ts->snes_its);CHKERRQ(ierr);
1943       ierr = PetscViewerASCIIPrintf(viewer,"  total number of nonlinear solve failures=%D\n",ts->num_snes_failures);CHKERRQ(ierr);
1944     }
1945     ierr = PetscViewerASCIIPrintf(viewer,"  total number of linear solver iterations=%D\n",ts->ksp_its);CHKERRQ(ierr);
1946     ierr = PetscViewerASCIIPrintf(viewer,"  total number of rejected steps=%D\n",ts->reject);CHKERRQ(ierr);
1947     if (ts->vrtol) {
1948       ierr = PetscViewerASCIIPrintf(viewer,"  using vector of relative error tolerances, ");CHKERRQ(ierr);
1949     } else {
1950       ierr = PetscViewerASCIIPrintf(viewer,"  using relative error tolerance of %g, ",(double)ts->rtol);CHKERRQ(ierr);
1951     }
1952     if (ts->vatol) {
1953       ierr = PetscViewerASCIIPrintf(viewer,"  using vector of absolute error tolerances\n");CHKERRQ(ierr);
1954     } else {
1955       ierr = PetscViewerASCIIPrintf(viewer,"  using absolute error tolerance of %g\n",(double)ts->atol);CHKERRQ(ierr);
1956     }
1957     ierr = DMGetDMTS(ts->dm,&sdm);CHKERRQ(ierr);
1958     ierr = DMTSView(sdm,viewer);CHKERRQ(ierr);
1959     if (ts->ops->view) {
1960       ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr);
1961       ierr = (*ts->ops->view)(ts,viewer);CHKERRQ(ierr);
1962       ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr);
1963     }
1964   } else if (isstring) {
1965     ierr = TSGetType(ts,&type);CHKERRQ(ierr);
1966     ierr = PetscViewerStringSPrintf(viewer," %-7.7s",type);CHKERRQ(ierr);
1967   } else if (isbinary) {
1968     PetscInt    classid = TS_FILE_CLASSID;
1969     MPI_Comm    comm;
1970     PetscMPIInt rank;
1971     char        type[256];
1972 
1973     ierr = PetscObjectGetComm((PetscObject)ts,&comm);CHKERRQ(ierr);
1974     ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr);
1975     if (!rank) {
1976       ierr = PetscViewerBinaryWrite(viewer,&classid,1,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr);
1977       ierr = PetscStrncpy(type,((PetscObject)ts)->type_name,256);CHKERRQ(ierr);
1978       ierr = PetscViewerBinaryWrite(viewer,type,256,PETSC_CHAR,PETSC_FALSE);CHKERRQ(ierr);
1979     }
1980     if (ts->ops->view) {
1981       ierr = (*ts->ops->view)(ts,viewer);CHKERRQ(ierr);
1982     }
1983     ierr = DMView(ts->dm,viewer);CHKERRQ(ierr);
1984     ierr = VecView(ts->vec_sol,viewer);CHKERRQ(ierr);
1985     ierr = DMGetDMTS(ts->dm,&sdm);CHKERRQ(ierr);
1986     ierr = DMTSView(sdm,viewer);CHKERRQ(ierr);
1987   } else if (isdraw) {
1988     PetscDraw draw;
1989     char      str[36];
1990     PetscReal x,y,bottom,h;
1991 
1992     ierr   = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr);
1993     ierr   = PetscDrawGetCurrentPoint(draw,&x,&y);CHKERRQ(ierr);
1994     ierr   = PetscStrcpy(str,"TS: ");CHKERRQ(ierr);
1995     ierr   = PetscStrcat(str,((PetscObject)ts)->type_name);CHKERRQ(ierr);
1996     ierr   = PetscDrawStringBoxed(draw,x,y,PETSC_DRAW_BLACK,PETSC_DRAW_BLACK,str,NULL,&h);CHKERRQ(ierr);
1997     bottom = y - h;
1998     ierr   = PetscDrawPushCurrentPoint(draw,x,bottom);CHKERRQ(ierr);
1999     if (ts->ops->view) {
2000       ierr = (*ts->ops->view)(ts,viewer);CHKERRQ(ierr);
2001     }
2002     ierr = PetscDrawPopCurrentPoint(draw);CHKERRQ(ierr);
2003 #if defined(PETSC_HAVE_SAWS)
2004   } else if (issaws) {
2005     PetscMPIInt rank;
2006     const char  *name;
2007 
2008     ierr = PetscObjectGetName((PetscObject)ts,&name);CHKERRQ(ierr);
2009     ierr = MPI_Comm_rank(PETSC_COMM_WORLD,&rank);CHKERRQ(ierr);
2010     if (!((PetscObject)ts)->amsmem && !rank) {
2011       char       dir[1024];
2012 
2013       ierr = PetscObjectViewSAWs((PetscObject)ts,viewer);CHKERRQ(ierr);
2014       ierr = PetscSNPrintf(dir,1024,"/PETSc/Objects/%s/time_step",name);CHKERRQ(ierr);
2015       PetscStackCallSAWs(SAWs_Register,(dir,&ts->steps,1,SAWs_READ,SAWs_INT));
2016       ierr = PetscSNPrintf(dir,1024,"/PETSc/Objects/%s/time",name);CHKERRQ(ierr);
2017       PetscStackCallSAWs(SAWs_Register,(dir,&ts->ptime,1,SAWs_READ,SAWs_DOUBLE));
2018     }
2019     if (ts->ops->view) {
2020       ierr = (*ts->ops->view)(ts,viewer);CHKERRQ(ierr);
2021     }
2022 #endif
2023   }
2024 
2025   ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr);
2026   ierr = PetscObjectTypeCompare((PetscObject)ts,TSSUNDIALS,&isundials);CHKERRQ(ierr);
2027   ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr);
2028   PetscFunctionReturn(0);
2029 }
2030 
2031 
2032 /*@
2033    TSSetApplicationContext - Sets an optional user-defined context for
2034    the timesteppers.
2035 
2036    Logically Collective on TS
2037 
2038    Input Parameters:
2039 +  ts - the TS context obtained from TSCreate()
2040 -  usrP - optional user context
2041 
2042    Fortran Notes: To use this from Fortran you must write a Fortran interface definition for this
2043     function that tells Fortran the Fortran derived data type that you are passing in as the ctx argument.
2044 
2045    Level: intermediate
2046 
2047 .keywords: TS, timestep, set, application, context
2048 
2049 .seealso: TSGetApplicationContext()
2050 @*/
2051 PetscErrorCode  TSSetApplicationContext(TS ts,void *usrP)
2052 {
2053   PetscFunctionBegin;
2054   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
2055   ts->user = usrP;
2056   PetscFunctionReturn(0);
2057 }
2058 
2059 /*@
2060     TSGetApplicationContext - Gets the user-defined context for the
2061     timestepper.
2062 
2063     Not Collective
2064 
2065     Input Parameter:
2066 .   ts - the TS context obtained from TSCreate()
2067 
2068     Output Parameter:
2069 .   usrP - user context
2070 
2071    Fortran Notes: To use this from Fortran you must write a Fortran interface definition for this
2072     function that tells Fortran the Fortran derived data type that you are passing in as the ctx argument.
2073 
2074     Level: intermediate
2075 
2076 .keywords: TS, timestep, get, application, context
2077 
2078 .seealso: TSSetApplicationContext()
2079 @*/
2080 PetscErrorCode  TSGetApplicationContext(TS ts,void *usrP)
2081 {
2082   PetscFunctionBegin;
2083   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
2084   *(void**)usrP = ts->user;
2085   PetscFunctionReturn(0);
2086 }
2087 
2088 /*@
2089    TSGetTimeStepNumber - Gets the number of time steps completed.
2090 
2091    Not Collective
2092 
2093    Input Parameter:
2094 .  ts - the TS context obtained from TSCreate()
2095 
2096    Output Parameter:
2097 .  iter - number of steps completed so far
2098 
2099    Level: intermediate
2100 
2101 .keywords: TS, timestep, get, iteration, number
2102 .seealso: TSGetTime(), TSGetTimeStep(), TSSetPreStep(), TSSetPreStage(), TSSetPostStage(), TSSetPostStep()
2103 @*/
2104 PetscErrorCode  TSGetTimeStepNumber(TS ts,PetscInt *iter)
2105 {
2106   PetscFunctionBegin;
2107   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
2108   PetscValidIntPointer(iter,2);
2109   *iter = ts->steps;
2110   PetscFunctionReturn(0);
2111 }
2112 
2113 /*@
2114    TSSetInitialTimeStep - Sets the initial timestep to be used,
2115    as well as the initial time.
2116 
2117    Logically Collective on TS
2118 
2119    Input Parameters:
2120 +  ts - the TS context obtained from TSCreate()
2121 .  initial_time - the initial time
2122 -  time_step - the size of the timestep
2123 
2124    Level: intermediate
2125 
2126 .seealso: TSSetTimeStep(), TSGetTimeStep()
2127 
2128 .keywords: TS, set, initial, timestep
2129 @*/
2130 PetscErrorCode  TSSetInitialTimeStep(TS ts,PetscReal initial_time,PetscReal time_step)
2131 {
2132   PetscErrorCode ierr;
2133 
2134   PetscFunctionBegin;
2135   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
2136   ierr = TSSetTimeStep(ts,time_step);CHKERRQ(ierr);
2137   ierr = TSSetTime(ts,initial_time);CHKERRQ(ierr);
2138   PetscFunctionReturn(0);
2139 }
2140 
2141 /*@
2142    TSSetTimeStep - Allows one to reset the timestep at any time,
2143    useful for simple pseudo-timestepping codes.
2144 
2145    Logically Collective on TS
2146 
2147    Input Parameters:
2148 +  ts - the TS context obtained from TSCreate()
2149 -  time_step - the size of the timestep
2150 
2151    Level: intermediate
2152 
2153 .seealso: TSSetInitialTimeStep(), TSGetTimeStep()
2154 
2155 .keywords: TS, set, timestep
2156 @*/
2157 PetscErrorCode  TSSetTimeStep(TS ts,PetscReal time_step)
2158 {
2159   PetscFunctionBegin;
2160   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
2161   PetscValidLogicalCollectiveReal(ts,time_step,2);
2162   ts->time_step = time_step;
2163   PetscFunctionReturn(0);
2164 }
2165 
2166 /*@
2167    TSSetExactFinalTime - Determines whether to adapt the final time step to
2168      match the exact final time, interpolate solution to the exact final time,
2169      or just return at the final time TS computed.
2170 
2171   Logically Collective on TS
2172 
2173    Input Parameter:
2174 +   ts - the time-step context
2175 -   eftopt - exact final time option
2176 
2177 $  TS_EXACTFINALTIME_STEPOVER    - Don't do anything if final time is exceeded
2178 $  TS_EXACTFINALTIME_INTERPOLATE - Interpolate back to final time
2179 $  TS_EXACTFINALTIME_MATCHSTEP - Adapt final time step to match the final time
2180 
2181    Options Database:
2182 .   -ts_exact_final_time <stepover,interpolate,matchstep> - select the final step at runtime
2183 
2184    Warning: If you use the option TS_EXACTFINALTIME_STEPOVER the solution may be at a very different time
2185     then the final time you selected.
2186 
2187    Level: beginner
2188 
2189 .seealso: TSExactFinalTimeOption
2190 @*/
2191 PetscErrorCode  TSSetExactFinalTime(TS ts,TSExactFinalTimeOption eftopt)
2192 {
2193   PetscFunctionBegin;
2194   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
2195   PetscValidLogicalCollectiveEnum(ts,eftopt,2);
2196   ts->exact_final_time = eftopt;
2197   PetscFunctionReturn(0);
2198 }
2199 
2200 /*@
2201    TSGetTimeStep - Gets the current timestep size.
2202 
2203    Not Collective
2204 
2205    Input Parameter:
2206 .  ts - the TS context obtained from TSCreate()
2207 
2208    Output Parameter:
2209 .  dt - the current timestep size
2210 
2211    Level: intermediate
2212 
2213 .seealso: TSSetInitialTimeStep(), TSGetTimeStep()
2214 
2215 .keywords: TS, get, timestep
2216 @*/
2217 PetscErrorCode  TSGetTimeStep(TS ts,PetscReal *dt)
2218 {
2219   PetscFunctionBegin;
2220   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
2221   PetscValidRealPointer(dt,2);
2222   *dt = ts->time_step;
2223   PetscFunctionReturn(0);
2224 }
2225 
2226 /*@
2227    TSGetSolution - Returns the solution at the present timestep. It
2228    is valid to call this routine inside the function that you are evaluating
2229    in order to move to the new timestep. This vector not changed until
2230    the solution at the next timestep has been calculated.
2231 
2232    Not Collective, but Vec returned is parallel if TS is parallel
2233 
2234    Input Parameter:
2235 .  ts - the TS context obtained from TSCreate()
2236 
2237    Output Parameter:
2238 .  v - the vector containing the solution
2239 
2240    Note: If you used TSSetExactFinalTime(ts,TS_EXACTFINALTIME_MATCHSTEP); this does not return the solution at the requested
2241    final time. It returns the solution at the next timestep.
2242 
2243    Level: intermediate
2244 
2245 .seealso: TSGetTimeStep(), TSGetTime(), TSGetSolveTime(), TSGetSolutionComponents()
2246 
2247 .keywords: TS, timestep, get, solution
2248 @*/
2249 PetscErrorCode  TSGetSolution(TS ts,Vec *v)
2250 {
2251   PetscFunctionBegin;
2252   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
2253   PetscValidPointer(v,2);
2254   *v = ts->vec_sol;
2255   PetscFunctionReturn(0);
2256 }
2257 
2258 /*@
2259    TSGetSolutionComponents - Returns any solution components at the present
2260    timestep, if available for the time integration method being used.
2261    Solution components are quantities that share the same size and
2262    structure as the solution vector.
2263 
2264    Not Collective, but Vec returned is parallel if TS is parallel
2265 
2266    Parameters :
2267 .  ts - the TS context obtained from TSCreate() (input parameter).
2268 .  n - If v is PETSC_NULL, then the number of solution components is
2269        returned through n, else the n-th solution component is
2270        returned in v.
2271 .  v - the vector containing the n-th solution component
2272        (may be PETSC_NULL to use this function to find out
2273         the number of solutions components).
2274 
2275    Level: advanced
2276 
2277 .seealso: TSGetSolution()
2278 
2279 .keywords: TS, timestep, get, solution
2280 @*/
2281 PetscErrorCode  TSGetSolutionComponents(TS ts,PetscInt *n,Vec *v)
2282 {
2283   PetscErrorCode ierr;
2284 
2285   PetscFunctionBegin;
2286   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
2287   if (!ts->ops->getsolutioncomponents) *n = 0;
2288   else {
2289     ierr = (*ts->ops->getsolutioncomponents)(ts,n,v);CHKERRQ(ierr);
2290   }
2291   PetscFunctionReturn(0);
2292 }
2293 
2294 /*@
2295    TSGetAuxSolution - Returns an auxiliary solution at the present
2296    timestep, if available for the time integration method being used.
2297 
2298    Not Collective, but Vec returned is parallel if TS is parallel
2299 
2300    Parameters :
2301 .  ts - the TS context obtained from TSCreate() (input parameter).
2302 .  v - the vector containing the auxiliary solution
2303 
2304    Level: intermediate
2305 
2306 .seealso: TSGetSolution()
2307 
2308 .keywords: TS, timestep, get, solution
2309 @*/
2310 PetscErrorCode  TSGetAuxSolution(TS ts,Vec *v)
2311 {
2312   PetscErrorCode ierr;
2313 
2314   PetscFunctionBegin;
2315   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
2316   if (ts->ops->getauxsolution) {
2317     ierr = (*ts->ops->getauxsolution)(ts,v);CHKERRQ(ierr);
2318   } else {
2319     ierr = VecZeroEntries(*v); CHKERRQ(ierr);
2320   }
2321   PetscFunctionReturn(0);
2322 }
2323 
2324 /*@
2325    TSGetTimeError - Returns the estimated error vector, if the chosen
2326    TSType has an error estimation functionality.
2327 
2328    Not Collective, but Vec returned is parallel if TS is parallel
2329 
2330    Note: MUST call after TSSetUp()
2331 
2332    Parameters :
2333 .  ts - the TS context obtained from TSCreate() (input parameter).
2334 .  n - current estimate (n=0) or previous one (n=-1)
2335 .  v - the vector containing the error (same size as the solution).
2336 
2337    Level: intermediate
2338 
2339 .seealso: TSGetSolution(), TSSetTimeError()
2340 
2341 .keywords: TS, timestep, get, error
2342 @*/
2343 PetscErrorCode  TSGetTimeError(TS ts,PetscInt n,Vec *v)
2344 {
2345   PetscErrorCode ierr;
2346 
2347   PetscFunctionBegin;
2348   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
2349   if (ts->ops->gettimeerror) {
2350     ierr = (*ts->ops->gettimeerror)(ts,n,v);CHKERRQ(ierr);
2351   } else {
2352     ierr = VecZeroEntries(*v);CHKERRQ(ierr);
2353   }
2354   PetscFunctionReturn(0);
2355 }
2356 
2357 /*@
2358    TSSetTimeError - Sets the estimated error vector, if the chosen
2359    TSType has an error estimation functionality. This can be used
2360    to restart such a time integrator with a given error vector.
2361 
2362    Not Collective, but Vec returned is parallel if TS is parallel
2363 
2364    Parameters :
2365 .  ts - the TS context obtained from TSCreate() (input parameter).
2366 .  v - the vector containing the error (same size as the solution).
2367 
2368    Level: intermediate
2369 
2370 .seealso: TSSetSolution(), TSGetTimeError)
2371 
2372 .keywords: TS, timestep, get, error
2373 @*/
2374 PetscErrorCode  TSSetTimeError(TS ts,Vec v)
2375 {
2376   PetscErrorCode ierr;
2377 
2378   PetscFunctionBegin;
2379   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
2380   if (!ts->setupcalled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call TSSetUp() first");
2381   if (ts->ops->settimeerror) {
2382     ierr = (*ts->ops->settimeerror)(ts,v);CHKERRQ(ierr);
2383   }
2384   PetscFunctionReturn(0);
2385 }
2386 
2387 /*@
2388    TSGetCostGradients - Returns the gradients from the TSAdjointSolve()
2389 
2390    Not Collective, but Vec returned is parallel if TS is parallel
2391 
2392    Input Parameter:
2393 .  ts - the TS context obtained from TSCreate()
2394 
2395    Output Parameter:
2396 +  lambda - vectors containing the gradients of the cost functions with respect to the ODE/DAE solution variables
2397 -  mu - vectors containing the gradients of the cost functions with respect to the problem parameters
2398 
2399    Level: intermediate
2400 
2401 .seealso: TSGetTimeStep()
2402 
2403 .keywords: TS, timestep, get, sensitivity
2404 @*/
2405 PetscErrorCode  TSGetCostGradients(TS ts,PetscInt *numcost,Vec **lambda,Vec **mu)
2406 {
2407   PetscFunctionBegin;
2408   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
2409   if (numcost) *numcost = ts->numcost;
2410   if (lambda)  *lambda  = ts->vecs_sensi;
2411   if (mu)      *mu      = ts->vecs_sensip;
2412   PetscFunctionReturn(0);
2413 }
2414 
2415 /* ----- Routines to initialize and destroy a timestepper ---- */
2416 /*@
2417   TSSetProblemType - Sets the type of problem to be solved.
2418 
2419   Not collective
2420 
2421   Input Parameters:
2422 + ts   - The TS
2423 - type - One of TS_LINEAR, TS_NONLINEAR where these types refer to problems of the forms
2424 .vb
2425          U_t - A U = 0      (linear)
2426          U_t - A(t) U = 0   (linear)
2427          F(t,U,U_t) = 0     (nonlinear)
2428 .ve
2429 
2430    Level: beginner
2431 
2432 .keywords: TS, problem type
2433 .seealso: TSSetUp(), TSProblemType, TS
2434 @*/
2435 PetscErrorCode  TSSetProblemType(TS ts, TSProblemType type)
2436 {
2437   PetscErrorCode ierr;
2438 
2439   PetscFunctionBegin;
2440   PetscValidHeaderSpecific(ts, TS_CLASSID,1);
2441   ts->problem_type = type;
2442   if (type == TS_LINEAR) {
2443     SNES snes;
2444     ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr);
2445     ierr = SNESSetType(snes,SNESKSPONLY);CHKERRQ(ierr);
2446   }
2447   PetscFunctionReturn(0);
2448 }
2449 
2450 /*@C
2451   TSGetProblemType - Gets the type of problem to be solved.
2452 
2453   Not collective
2454 
2455   Input Parameter:
2456 . ts   - The TS
2457 
2458   Output Parameter:
2459 . type - One of TS_LINEAR, TS_NONLINEAR where these types refer to problems of the forms
2460 .vb
2461          M U_t = A U
2462          M(t) U_t = A(t) U
2463          F(t,U,U_t)
2464 .ve
2465 
2466    Level: beginner
2467 
2468 .keywords: TS, problem type
2469 .seealso: TSSetUp(), TSProblemType, TS
2470 @*/
2471 PetscErrorCode  TSGetProblemType(TS ts, TSProblemType *type)
2472 {
2473   PetscFunctionBegin;
2474   PetscValidHeaderSpecific(ts, TS_CLASSID,1);
2475   PetscValidIntPointer(type,2);
2476   *type = ts->problem_type;
2477   PetscFunctionReturn(0);
2478 }
2479 
2480 /*@
2481    TSSetUp - Sets up the internal data structures for the later use
2482    of a timestepper.
2483 
2484    Collective on TS
2485 
2486    Input Parameter:
2487 .  ts - the TS context obtained from TSCreate()
2488 
2489    Notes:
2490    For basic use of the TS solvers the user need not explicitly call
2491    TSSetUp(), since these actions will automatically occur during
2492    the call to TSStep().  However, if one wishes to control this
2493    phase separately, TSSetUp() should be called after TSCreate()
2494    and optional routines of the form TSSetXXX(), but before TSStep().
2495 
2496    Level: advanced
2497 
2498 .keywords: TS, timestep, setup
2499 
2500 .seealso: TSCreate(), TSStep(), TSDestroy()
2501 @*/
2502 PetscErrorCode  TSSetUp(TS ts)
2503 {
2504   PetscErrorCode ierr;
2505   DM             dm;
2506   PetscErrorCode (*func)(SNES,Vec,Vec,void*);
2507   PetscErrorCode (*jac)(SNES,Vec,Mat,Mat,void*);
2508   TSIFunction    ifun;
2509   TSIJacobian    ijac;
2510   TSI2Jacobian   i2jac;
2511   TSRHSJacobian  rhsjac;
2512   PetscBool      isnone;
2513 
2514   PetscFunctionBegin;
2515   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
2516   if (ts->setupcalled) PetscFunctionReturn(0);
2517 
2518   if (!((PetscObject)ts)->type_name) {
2519     ierr = TSGetIFunction(ts,NULL,&ifun,NULL);CHKERRQ(ierr);
2520     ierr = TSSetType(ts,ifun ? TSBEULER : TSEULER);CHKERRQ(ierr);
2521   }
2522 
2523   if (!ts->vec_sol) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call TSSetSolution() first");
2524 
2525   if (ts->rhsjacobian.reuse) {
2526     Mat Amat,Pmat;
2527     SNES snes;
2528     ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr);
2529     ierr = SNESGetJacobian(snes,&Amat,&Pmat,NULL,NULL);CHKERRQ(ierr);
2530     /* Matching matrices implies that an IJacobian is NOT set, because if it had been set, the IJacobian's matrix would
2531      * have displaced the RHS matrix */
2532     if (Amat == ts->Arhs) {
2533       ierr = MatDuplicate(ts->Arhs,MAT_DO_NOT_COPY_VALUES,&Amat);CHKERRQ(ierr);
2534       ierr = SNESSetJacobian(snes,Amat,NULL,NULL,NULL);CHKERRQ(ierr);
2535       ierr = MatDestroy(&Amat);CHKERRQ(ierr);
2536     }
2537     if (Pmat == ts->Brhs) {
2538       ierr = MatDuplicate(ts->Brhs,MAT_DO_NOT_COPY_VALUES,&Pmat);CHKERRQ(ierr);
2539       ierr = SNESSetJacobian(snes,NULL,Pmat,NULL,NULL);CHKERRQ(ierr);
2540       ierr = MatDestroy(&Pmat);CHKERRQ(ierr);
2541     }
2542   }
2543 
2544   ierr = TSGetAdapt(ts,&ts->adapt);CHKERRQ(ierr);
2545   ierr = TSAdaptSetDefaultType(ts->adapt,ts->default_adapt_type);CHKERRQ(ierr);
2546 
2547   if (ts->ops->setup) {
2548     ierr = (*ts->ops->setup)(ts);CHKERRQ(ierr);
2549   }
2550 
2551   /* Attempt to check/preset a default value for the exact final time option */
2552   ierr = PetscObjectTypeCompare((PetscObject)ts->adapt,TSADAPTNONE,&isnone);CHKERRQ(ierr);
2553   if (!isnone && ts->exact_final_time == TS_EXACTFINALTIME_UNSPECIFIED)
2554     ts->exact_final_time = TS_EXACTFINALTIME_MATCHSTEP;
2555 
2556   /* In the case where we've set a DMTSFunction or what have you, we need the default SNESFunction
2557      to be set right but can't do it elsewhere due to the overreliance on ctx=ts.
2558    */
2559   ierr = TSGetDM(ts,&dm);CHKERRQ(ierr);
2560   ierr = DMSNESGetFunction(dm,&func,NULL);CHKERRQ(ierr);
2561   if (!func) {
2562     ierr = DMSNESSetFunction(dm,SNESTSFormFunction,ts);CHKERRQ(ierr);
2563   }
2564   /* If the SNES doesn't have a jacobian set and the TS has an ijacobian or rhsjacobian set, set the SNES to use it.
2565      Otherwise, the SNES will use coloring internally to form the Jacobian.
2566    */
2567   ierr = DMSNESGetJacobian(dm,&jac,NULL);CHKERRQ(ierr);
2568   ierr = DMTSGetIJacobian(dm,&ijac,NULL);CHKERRQ(ierr);
2569   ierr = DMTSGetI2Jacobian(dm,&i2jac,NULL);CHKERRQ(ierr);
2570   ierr = DMTSGetRHSJacobian(dm,&rhsjac,NULL);CHKERRQ(ierr);
2571   if (!jac && (ijac || i2jac || rhsjac)) {
2572     ierr = DMSNESSetJacobian(dm,SNESTSFormJacobian,ts);CHKERRQ(ierr);
2573   }
2574 
2575   /* if time integration scheme has a starting method, call it */
2576   if (ts->ops->startingmethod) {
2577     ierr = (*ts->ops->startingmethod)(ts);CHKERRQ(ierr);
2578   }
2579 
2580   ts->setupcalled = PETSC_TRUE;
2581   PetscFunctionReturn(0);
2582 }
2583 
2584 /*@
2585    TSAdjointSetUp - Sets up the internal data structures for the later use
2586    of an adjoint solver
2587 
2588    Collective on TS
2589 
2590    Input Parameter:
2591 .  ts - the TS context obtained from TSCreate()
2592 
2593    Level: advanced
2594 
2595 .keywords: TS, timestep, setup
2596 
2597 .seealso: TSCreate(), TSAdjointStep(), TSSetCostGradients()
2598 @*/
2599 PetscErrorCode  TSAdjointSetUp(TS ts)
2600 {
2601   PetscErrorCode ierr;
2602 
2603   PetscFunctionBegin;
2604   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
2605   if (ts->adjointsetupcalled) PetscFunctionReturn(0);
2606   if (!ts->vecs_sensi) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call TSSetCostGradients() first");
2607 
2608   if (ts->vec_costintegral) { /* if there is integral in the cost function*/
2609     ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&ts->vecs_drdy);CHKERRQ(ierr);
2610     if (ts->vecs_sensip){
2611       ierr = VecDuplicateVecs(ts->vecs_sensip[0],ts->numcost,&ts->vecs_drdp);CHKERRQ(ierr);
2612     }
2613   }
2614 
2615   if (ts->ops->adjointsetup) {
2616     ierr = (*ts->ops->adjointsetup)(ts);CHKERRQ(ierr);
2617   }
2618   ts->adjointsetupcalled = PETSC_TRUE;
2619   PetscFunctionReturn(0);
2620 }
2621 
2622 /*@
2623    TSReset - Resets a TS context and removes any allocated Vecs and Mats.
2624 
2625    Collective on TS
2626 
2627    Input Parameter:
2628 .  ts - the TS context obtained from TSCreate()
2629 
2630    Level: beginner
2631 
2632 .keywords: TS, timestep, reset
2633 
2634 .seealso: TSCreate(), TSSetup(), TSDestroy()
2635 @*/
2636 PetscErrorCode  TSReset(TS ts)
2637 {
2638   PetscErrorCode ierr;
2639 
2640   PetscFunctionBegin;
2641   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
2642 
2643   if (ts->ops->reset) {
2644     ierr = (*ts->ops->reset)(ts);CHKERRQ(ierr);
2645   }
2646   if (ts->snes) {ierr = SNESReset(ts->snes);CHKERRQ(ierr);}
2647   if (ts->adapt) {ierr = TSAdaptReset(ts->adapt);CHKERRQ(ierr);}
2648 
2649   ierr = MatDestroy(&ts->Arhs);CHKERRQ(ierr);
2650   ierr = MatDestroy(&ts->Brhs);CHKERRQ(ierr);
2651   ierr = VecDestroy(&ts->Frhs);CHKERRQ(ierr);
2652   ierr = VecDestroy(&ts->vec_sol);CHKERRQ(ierr);
2653   ierr = VecDestroy(&ts->vec_dot);CHKERRQ(ierr);
2654   ierr = VecDestroy(&ts->vatol);CHKERRQ(ierr);
2655   ierr = VecDestroy(&ts->vrtol);CHKERRQ(ierr);
2656   ierr = VecDestroyVecs(ts->nwork,&ts->work);CHKERRQ(ierr);
2657 
2658  if (ts->vec_costintegral) {
2659     ierr = VecDestroyVecs(ts->numcost,&ts->vecs_drdy);CHKERRQ(ierr);
2660     if (ts->vecs_drdp){
2661       ierr = VecDestroyVecs(ts->numcost,&ts->vecs_drdp);CHKERRQ(ierr);
2662     }
2663   }
2664   ts->vecs_sensi  = NULL;
2665   ts->vecs_sensip = NULL;
2666   ierr = MatDestroy(&ts->Jacp);CHKERRQ(ierr);
2667   ierr = VecDestroy(&ts->vec_costintegral);CHKERRQ(ierr);
2668   ierr = VecDestroy(&ts->vec_costintegrand);CHKERRQ(ierr);
2669   ts->setupcalled = PETSC_FALSE;
2670   PetscFunctionReturn(0);
2671 }
2672 
2673 /*@
2674    TSDestroy - Destroys the timestepper context that was created
2675    with TSCreate().
2676 
2677    Collective on TS
2678 
2679    Input Parameter:
2680 .  ts - the TS context obtained from TSCreate()
2681 
2682    Level: beginner
2683 
2684 .keywords: TS, timestepper, destroy
2685 
2686 .seealso: TSCreate(), TSSetUp(), TSSolve()
2687 @*/
2688 PetscErrorCode  TSDestroy(TS *ts)
2689 {
2690   PetscErrorCode ierr;
2691 
2692   PetscFunctionBegin;
2693   if (!*ts) PetscFunctionReturn(0);
2694   PetscValidHeaderSpecific((*ts),TS_CLASSID,1);
2695   if (--((PetscObject)(*ts))->refct > 0) {*ts = 0; PetscFunctionReturn(0);}
2696 
2697   ierr = TSReset((*ts));CHKERRQ(ierr);
2698 
2699   /* if memory was published with SAWs then destroy it */
2700   ierr = PetscObjectSAWsViewOff((PetscObject)*ts);CHKERRQ(ierr);
2701   if ((*ts)->ops->destroy) {ierr = (*(*ts)->ops->destroy)((*ts));CHKERRQ(ierr);}
2702 
2703   ierr = TSTrajectoryDestroy(&(*ts)->trajectory);CHKERRQ(ierr);
2704 
2705   ierr = TSAdaptDestroy(&(*ts)->adapt);CHKERRQ(ierr);
2706   ierr = TSEventDestroy(&(*ts)->event);CHKERRQ(ierr);
2707 
2708   ierr = SNESDestroy(&(*ts)->snes);CHKERRQ(ierr);
2709   ierr = DMDestroy(&(*ts)->dm);CHKERRQ(ierr);
2710   ierr = TSMonitorCancel((*ts));CHKERRQ(ierr);
2711   ierr = TSAdjointMonitorCancel((*ts));CHKERRQ(ierr);
2712 
2713   ierr = PetscHeaderDestroy(ts);CHKERRQ(ierr);
2714   PetscFunctionReturn(0);
2715 }
2716 
2717 /*@
2718    TSGetSNES - Returns the SNES (nonlinear solver) associated with
2719    a TS (timestepper) context. Valid only for nonlinear problems.
2720 
2721    Not Collective, but SNES is parallel if TS is parallel
2722 
2723    Input Parameter:
2724 .  ts - the TS context obtained from TSCreate()
2725 
2726    Output Parameter:
2727 .  snes - the nonlinear solver context
2728 
2729    Notes:
2730    The user can then directly manipulate the SNES context to set various
2731    options, etc.  Likewise, the user can then extract and manipulate the
2732    KSP, KSP, and PC contexts as well.
2733 
2734    TSGetSNES() does not work for integrators that do not use SNES; in
2735    this case TSGetSNES() returns NULL in snes.
2736 
2737    Level: beginner
2738 
2739 .keywords: timestep, get, SNES
2740 @*/
2741 PetscErrorCode  TSGetSNES(TS ts,SNES *snes)
2742 {
2743   PetscErrorCode ierr;
2744 
2745   PetscFunctionBegin;
2746   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
2747   PetscValidPointer(snes,2);
2748   if (!ts->snes) {
2749     ierr = SNESCreate(PetscObjectComm((PetscObject)ts),&ts->snes);CHKERRQ(ierr);
2750     ierr = SNESSetFunction(ts->snes,NULL,SNESTSFormFunction,ts);CHKERRQ(ierr);
2751     ierr = PetscLogObjectParent((PetscObject)ts,(PetscObject)ts->snes);CHKERRQ(ierr);
2752     ierr = PetscObjectIncrementTabLevel((PetscObject)ts->snes,(PetscObject)ts,1);CHKERRQ(ierr);
2753     if (ts->dm) {ierr = SNESSetDM(ts->snes,ts->dm);CHKERRQ(ierr);}
2754     if (ts->problem_type == TS_LINEAR) {
2755       ierr = SNESSetType(ts->snes,SNESKSPONLY);CHKERRQ(ierr);
2756     }
2757   }
2758   *snes = ts->snes;
2759   PetscFunctionReturn(0);
2760 }
2761 
2762 /*@
2763    TSSetSNES - Set the SNES (nonlinear solver) to be used by the timestepping context
2764 
2765    Collective
2766 
2767    Input Parameter:
2768 +  ts - the TS context obtained from TSCreate()
2769 -  snes - the nonlinear solver context
2770 
2771    Notes:
2772    Most users should have the TS created by calling TSGetSNES()
2773 
2774    Level: developer
2775 
2776 .keywords: timestep, set, SNES
2777 @*/
2778 PetscErrorCode TSSetSNES(TS ts,SNES snes)
2779 {
2780   PetscErrorCode ierr;
2781   PetscErrorCode (*func)(SNES,Vec,Mat,Mat,void*);
2782 
2783   PetscFunctionBegin;
2784   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
2785   PetscValidHeaderSpecific(snes,SNES_CLASSID,2);
2786   ierr = PetscObjectReference((PetscObject)snes);CHKERRQ(ierr);
2787   ierr = SNESDestroy(&ts->snes);CHKERRQ(ierr);
2788 
2789   ts->snes = snes;
2790 
2791   ierr = SNESSetFunction(ts->snes,NULL,SNESTSFormFunction,ts);CHKERRQ(ierr);
2792   ierr = SNESGetJacobian(ts->snes,NULL,NULL,&func,NULL);CHKERRQ(ierr);
2793   if (func == SNESTSFormJacobian) {
2794     ierr = SNESSetJacobian(ts->snes,NULL,NULL,SNESTSFormJacobian,ts);CHKERRQ(ierr);
2795   }
2796   PetscFunctionReturn(0);
2797 }
2798 
2799 /*@
2800    TSGetKSP - Returns the KSP (linear solver) associated with
2801    a TS (timestepper) context.
2802 
2803    Not Collective, but KSP is parallel if TS is parallel
2804 
2805    Input Parameter:
2806 .  ts - the TS context obtained from TSCreate()
2807 
2808    Output Parameter:
2809 .  ksp - the nonlinear solver context
2810 
2811    Notes:
2812    The user can then directly manipulate the KSP context to set various
2813    options, etc.  Likewise, the user can then extract and manipulate the
2814    KSP and PC contexts as well.
2815 
2816    TSGetKSP() does not work for integrators that do not use KSP;
2817    in this case TSGetKSP() returns NULL in ksp.
2818 
2819    Level: beginner
2820 
2821 .keywords: timestep, get, KSP
2822 @*/
2823 PetscErrorCode  TSGetKSP(TS ts,KSP *ksp)
2824 {
2825   PetscErrorCode ierr;
2826   SNES           snes;
2827 
2828   PetscFunctionBegin;
2829   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
2830   PetscValidPointer(ksp,2);
2831   if (!((PetscObject)ts)->type_name) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_NULL,"KSP is not created yet. Call TSSetType() first");
2832   if (ts->problem_type != TS_LINEAR) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Linear only; use TSGetSNES()");
2833   ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr);
2834   ierr = SNESGetKSP(snes,ksp);CHKERRQ(ierr);
2835   PetscFunctionReturn(0);
2836 }
2837 
2838 /* ----------- Routines to set solver parameters ---------- */
2839 
2840 /*@
2841    TSGetDuration - Gets the maximum number of timesteps to use and
2842    maximum time for iteration.
2843 
2844    Not Collective
2845 
2846    Input Parameters:
2847 +  ts       - the TS context obtained from TSCreate()
2848 .  maxsteps - maximum number of iterations to use, or NULL
2849 -  maxtime  - final time to iterate to, or NULL
2850 
2851    Level: intermediate
2852 
2853 .keywords: TS, timestep, get, maximum, iterations, time
2854 @*/
2855 PetscErrorCode  TSGetDuration(TS ts, PetscInt *maxsteps, PetscReal *maxtime)
2856 {
2857   PetscFunctionBegin;
2858   PetscValidHeaderSpecific(ts, TS_CLASSID,1);
2859   if (maxsteps) {
2860     PetscValidIntPointer(maxsteps,2);
2861     *maxsteps = ts->max_steps;
2862   }
2863   if (maxtime) {
2864     PetscValidScalarPointer(maxtime,3);
2865     *maxtime = ts->max_time;
2866   }
2867   PetscFunctionReturn(0);
2868 }
2869 
2870 /*@
2871    TSSetDuration - Sets the maximum number of timesteps to use and
2872    maximum time for iteration.
2873 
2874    Logically Collective on TS
2875 
2876    Input Parameters:
2877 +  ts - the TS context obtained from TSCreate()
2878 .  maxsteps - maximum number of iterations to use
2879 -  maxtime - final time to iterate to
2880 
2881    Options Database Keys:
2882 .  -ts_max_steps <maxsteps> - Sets maxsteps
2883 .  -ts_final_time <maxtime> - Sets maxtime
2884 
2885    Notes:
2886    The default maximum number of iterations is 5000. Default time is 5.0
2887 
2888    Level: intermediate
2889 
2890 .keywords: TS, timestep, set, maximum, iterations
2891 
2892 .seealso: TSSetExactFinalTime()
2893 @*/
2894 PetscErrorCode  TSSetDuration(TS ts,PetscInt maxsteps,PetscReal maxtime)
2895 {
2896   PetscFunctionBegin;
2897   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
2898   PetscValidLogicalCollectiveInt(ts,maxsteps,2);
2899   PetscValidLogicalCollectiveReal(ts,maxtime,2);
2900   if (maxsteps >= 0) ts->max_steps = maxsteps;
2901   if (maxtime != PETSC_DEFAULT) ts->max_time = maxtime;
2902   PetscFunctionReturn(0);
2903 }
2904 
2905 /*@
2906    TSSetSolution - Sets the initial solution vector
2907    for use by the TS routines.
2908 
2909    Logically Collective on TS and Vec
2910 
2911    Input Parameters:
2912 +  ts - the TS context obtained from TSCreate()
2913 -  u - the solution vector
2914 
2915    Level: beginner
2916 
2917 .keywords: TS, timestep, set, solution, initial conditions
2918 @*/
2919 PetscErrorCode  TSSetSolution(TS ts,Vec u)
2920 {
2921   PetscErrorCode ierr;
2922   DM             dm;
2923 
2924   PetscFunctionBegin;
2925   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
2926   PetscValidHeaderSpecific(u,VEC_CLASSID,2);
2927   ierr = PetscObjectReference((PetscObject)u);CHKERRQ(ierr);
2928   ierr = VecDestroy(&ts->vec_sol);CHKERRQ(ierr);
2929   ts->vec_sol = u;
2930 
2931   ierr = TSGetDM(ts,&dm);CHKERRQ(ierr);
2932   ierr = DMShellSetGlobalVector(dm,u);CHKERRQ(ierr);
2933   PetscFunctionReturn(0);
2934 }
2935 
2936 /*@
2937    TSAdjointSetSteps - Sets the number of steps the adjoint solver should take backward in time
2938 
2939    Logically Collective on TS
2940 
2941    Input Parameters:
2942 +  ts - the TS context obtained from TSCreate()
2943 .  steps - number of steps to use
2944 
2945    Level: intermediate
2946 
2947    Notes: Normally one does not call this and TSAdjointSolve() integrates back to the original timestep. One can call this
2948           so as to integrate back to less than the original timestep
2949 
2950 .keywords: TS, timestep, set, maximum, iterations
2951 
2952 .seealso: TSSetExactFinalTime()
2953 @*/
2954 PetscErrorCode  TSAdjointSetSteps(TS ts,PetscInt steps)
2955 {
2956   PetscFunctionBegin;
2957   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
2958   PetscValidLogicalCollectiveInt(ts,steps,2);
2959   if (steps < 0) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Cannot step back a negative number of steps");
2960   if (steps > ts->total_steps) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Cannot step back more than the total number of forward steps");
2961   ts->adjoint_max_steps = steps;
2962   PetscFunctionReturn(0);
2963 }
2964 
2965 /*@
2966    TSSetCostGradients - Sets the initial value of the gradients of the cost function w.r.t. initial conditions and w.r.t. the problem parameters
2967       for use by the TSAdjoint routines.
2968 
2969    Logically Collective on TS and Vec
2970 
2971    Input Parameters:
2972 +  ts - the TS context obtained from TSCreate()
2973 .  lambda - gradients with respect to the initial condition variables, the dimension and parallel layout of these vectors is the same as the ODE solution vector
2974 -  mu - gradients with respect to the parameters, the number of entries in these vectors is the same as the number of parameters
2975 
2976    Level: beginner
2977 
2978    Notes: the entries in these vectors must be correctly initialized with the values lamda_i = df/dy|finaltime  mu_i = df/dp|finaltime
2979 
2980 .keywords: TS, timestep, set, sensitivity, initial conditions
2981 @*/
2982 PetscErrorCode  TSSetCostGradients(TS ts,PetscInt numcost,Vec *lambda,Vec *mu)
2983 {
2984   PetscFunctionBegin;
2985   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
2986   PetscValidPointer(lambda,2);
2987   ts->vecs_sensi  = lambda;
2988   ts->vecs_sensip = mu;
2989   if (ts->numcost && ts->numcost!=numcost) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"The number of cost functions (2rd parameter of TSSetCostIntegrand()) is inconsistent with the one set by TSSetCostIntegrand");
2990   ts->numcost  = numcost;
2991   PetscFunctionReturn(0);
2992 }
2993 
2994 /*@C
2995   TSAdjointSetRHSJacobian - Sets the function that computes the Jacobian of G w.r.t. the parameters p where y_t = G(y,p,t), as well as the location to store the matrix.
2996 
2997   Logically Collective on TS
2998 
2999   Input Parameters:
3000 + ts   - The TS context obtained from TSCreate()
3001 - func - The function
3002 
3003   Calling sequence of func:
3004 $ func (TS ts,PetscReal t,Vec y,Mat A,void *ctx);
3005 +   t - current timestep
3006 .   y - input vector (current ODE solution)
3007 .   A - output matrix
3008 -   ctx - [optional] user-defined function context
3009 
3010   Level: intermediate
3011 
3012   Notes: Amat has the same number of rows and the same row parallel layout as u, Amat has the same number of columns and parallel layout as p
3013 
3014 .keywords: TS, sensitivity
3015 .seealso:
3016 @*/
3017 PetscErrorCode  TSAdjointSetRHSJacobian(TS ts,Mat Amat,PetscErrorCode (*func)(TS,PetscReal,Vec,Mat,void*),void *ctx)
3018 {
3019   PetscErrorCode ierr;
3020 
3021   PetscFunctionBegin;
3022   PetscValidHeaderSpecific(ts, TS_CLASSID,1);
3023   if (Amat) PetscValidHeaderSpecific(Amat,MAT_CLASSID,2);
3024 
3025   ts->rhsjacobianp    = func;
3026   ts->rhsjacobianpctx = ctx;
3027   if(Amat) {
3028     ierr = PetscObjectReference((PetscObject)Amat);CHKERRQ(ierr);
3029     ierr = MatDestroy(&ts->Jacp);CHKERRQ(ierr);
3030     ts->Jacp = Amat;
3031   }
3032   PetscFunctionReturn(0);
3033 }
3034 
3035 /*@C
3036   TSAdjointComputeRHSJacobian - Runs the user-defined Jacobian function.
3037 
3038   Collective on TS
3039 
3040   Input Parameters:
3041 . ts   - The TS context obtained from TSCreate()
3042 
3043   Level: developer
3044 
3045 .keywords: TS, sensitivity
3046 .seealso: TSAdjointSetRHSJacobian()
3047 @*/
3048 PetscErrorCode  TSAdjointComputeRHSJacobian(TS ts,PetscReal t,Vec X,Mat Amat)
3049 {
3050   PetscErrorCode ierr;
3051 
3052   PetscFunctionBegin;
3053   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
3054   PetscValidHeaderSpecific(X,VEC_CLASSID,3);
3055   PetscValidPointer(Amat,4);
3056 
3057   PetscStackPush("TS user JacobianP function for sensitivity analysis");
3058   ierr = (*ts->rhsjacobianp)(ts,t,X,Amat,ts->rhsjacobianpctx); CHKERRQ(ierr);
3059   PetscStackPop;
3060   PetscFunctionReturn(0);
3061 }
3062 
3063 /*@C
3064     TSSetCostIntegrand - Sets the routine for evaluating the integral term in one or more cost functions
3065 
3066     Logically Collective on TS
3067 
3068     Input Parameters:
3069 +   ts - the TS context obtained from TSCreate()
3070 .   numcost - number of gradients to be computed, this is the number of cost functions
3071 .   rf - routine for evaluating the integrand function
3072 .   drdyf - function that computes the gradients of the r's with respect to y,NULL if not a function y
3073 .   drdpf - function that computes the gradients of the r's with respect to p, NULL if not a function of p
3074 .   fwd - flag indicating whether to evaluate cost integral in the forward run or the adjoint run
3075 -   ctx - [optional] user-defined context for private data for the function evaluation routine (may be NULL)
3076 
3077     Calling sequence of rf:
3078 $     rf(TS ts,PetscReal t,Vec y,Vec f[],void *ctx);
3079 
3080 +   t - current timestep
3081 .   y - input vector
3082 .   f - function result; one vector entry for each cost function
3083 -   ctx - [optional] user-defined function context
3084 
3085    Calling sequence of drdyf:
3086 $    PetscErroCode drdyf(TS ts,PetscReal t,Vec y,Vec *drdy,void *ctx);
3087 
3088    Calling sequence of drdpf:
3089 $    PetscErroCode drdpf(TS ts,PetscReal t,Vec y,Vec *drdp,void *ctx);
3090 
3091     Level: intermediate
3092 
3093     Notes: For optimization there is generally a single cost function, numcost = 1. For sensitivities there may be multiple cost functions
3094 
3095 .keywords: TS, sensitivity analysis, timestep, set, quadrature, function
3096 
3097 .seealso: TSAdjointSetRHSJacobian(),TSGetCostGradients(), TSSetCostGradients()
3098 @*/
3099 PetscErrorCode  TSSetCostIntegrand(TS ts,PetscInt numcost,PetscErrorCode (*rf)(TS,PetscReal,Vec,Vec,void*),
3100                                                           PetscErrorCode (*drdyf)(TS,PetscReal,Vec,Vec*,void*),
3101                                                           PetscErrorCode (*drdpf)(TS,PetscReal,Vec,Vec*,void*),
3102                                                           PetscBool fwd,void *ctx)
3103 {
3104   PetscErrorCode ierr;
3105 
3106   PetscFunctionBegin;
3107   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
3108   if (ts->numcost && ts->numcost!=numcost) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"The number of cost functions (2rd parameter of TSSetCostIntegrand()) is inconsistent with the one set by TSSetCostGradients()");
3109   if (!ts->numcost) ts->numcost=numcost;
3110 
3111   ts->costintegralfwd  = fwd; /* Evaluate the cost integral in forward run if fwd is true */
3112   ierr                 = VecCreateSeq(PETSC_COMM_SELF,numcost,&ts->vec_costintegral);CHKERRQ(ierr);
3113   ierr                 = VecDuplicate(ts->vec_costintegral,&ts->vec_costintegrand);CHKERRQ(ierr);
3114   ts->costintegrand    = rf;
3115   ts->costintegrandctx = ctx;
3116   ts->drdyfunction     = drdyf;
3117   ts->drdpfunction     = drdpf;
3118   PetscFunctionReturn(0);
3119 }
3120 
3121 /*@
3122    TSGetCostIntegral - Returns the values of the integral term in the cost functions.
3123    It is valid to call the routine after a backward run.
3124 
3125    Not Collective
3126 
3127    Input Parameter:
3128 .  ts - the TS context obtained from TSCreate()
3129 
3130    Output Parameter:
3131 .  v - the vector containing the integrals for each cost function
3132 
3133    Level: intermediate
3134 
3135 .seealso: TSSetCostIntegrand()
3136 
3137 .keywords: TS, sensitivity analysis
3138 @*/
3139 PetscErrorCode  TSGetCostIntegral(TS ts,Vec *v)
3140 {
3141   PetscFunctionBegin;
3142   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
3143   PetscValidPointer(v,2);
3144   *v = ts->vec_costintegral;
3145   PetscFunctionReturn(0);
3146 }
3147 
3148 /*@
3149    TSAdjointComputeCostIntegrand - Evaluates the integral function in the cost functions.
3150 
3151    Input Parameters:
3152 +  ts - the TS context
3153 .  t - current time
3154 -  y - state vector, i.e. current solution
3155 
3156    Output Parameter:
3157 .  q - vector of size numcost to hold the outputs
3158 
3159    Note:
3160    Most users should not need to explicitly call this routine, as it
3161    is used internally within the sensitivity analysis context.
3162 
3163    Level: developer
3164 
3165 .keywords: TS, compute
3166 
3167 .seealso: TSSetCostIntegrand()
3168 @*/
3169 PetscErrorCode TSAdjointComputeCostIntegrand(TS ts,PetscReal t,Vec y,Vec q)
3170 {
3171   PetscErrorCode ierr;
3172 
3173   PetscFunctionBegin;
3174   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
3175   PetscValidHeaderSpecific(y,VEC_CLASSID,3);
3176   PetscValidHeaderSpecific(q,VEC_CLASSID,4);
3177 
3178   ierr = PetscLogEventBegin(TS_FunctionEval,ts,y,q,0);CHKERRQ(ierr);
3179   if (ts->costintegrand) {
3180     PetscStackPush("TS user integrand in the cost function");
3181     ierr = (*ts->costintegrand)(ts,t,y,q,ts->costintegrandctx);CHKERRQ(ierr);
3182     PetscStackPop;
3183   } else {
3184     ierr = VecZeroEntries(q);CHKERRQ(ierr);
3185   }
3186 
3187   ierr = PetscLogEventEnd(TS_FunctionEval,ts,y,q,0);CHKERRQ(ierr);
3188   PetscFunctionReturn(0);
3189 }
3190 
3191 /*@
3192   TSAdjointComputeDRDYFunction - Runs the user-defined DRDY function.
3193 
3194   Collective on TS
3195 
3196   Input Parameters:
3197 . ts   - The TS context obtained from TSCreate()
3198 
3199   Notes:
3200   TSAdjointComputeDRDYFunction() is typically used for sensitivity implementation,
3201   so most users would not generally call this routine themselves.
3202 
3203   Level: developer
3204 
3205 .keywords: TS, sensitivity
3206 .seealso: TSAdjointComputeDRDYFunction()
3207 @*/
3208 PetscErrorCode  TSAdjointComputeDRDYFunction(TS ts,PetscReal t,Vec y,Vec *drdy)
3209 {
3210   PetscErrorCode ierr;
3211 
3212   PetscFunctionBegin;
3213   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
3214   PetscValidHeaderSpecific(y,VEC_CLASSID,3);
3215 
3216   PetscStackPush("TS user DRDY function for sensitivity analysis");
3217   ierr = (*ts->drdyfunction)(ts,t,y,drdy,ts->costintegrandctx); CHKERRQ(ierr);
3218   PetscStackPop;
3219   PetscFunctionReturn(0);
3220 }
3221 
3222 /*@
3223   TSAdjointComputeDRDPFunction - Runs the user-defined DRDP function.
3224 
3225   Collective on TS
3226 
3227   Input Parameters:
3228 . ts   - The TS context obtained from TSCreate()
3229 
3230   Notes:
3231   TSDRDPFunction() is typically used for sensitivity implementation,
3232   so most users would not generally call this routine themselves.
3233 
3234   Level: developer
3235 
3236 .keywords: TS, sensitivity
3237 .seealso: TSAdjointSetDRDPFunction()
3238 @*/
3239 PetscErrorCode  TSAdjointComputeDRDPFunction(TS ts,PetscReal t,Vec y,Vec *drdp)
3240 {
3241   PetscErrorCode ierr;
3242 
3243   PetscFunctionBegin;
3244   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
3245   PetscValidHeaderSpecific(y,VEC_CLASSID,3);
3246 
3247   PetscStackPush("TS user DRDP function for sensitivity analysis");
3248   ierr = (*ts->drdpfunction)(ts,t,y,drdp,ts->costintegrandctx); CHKERRQ(ierr);
3249   PetscStackPop;
3250   PetscFunctionReturn(0);
3251 }
3252 
3253 /*@C
3254   TSSetPreStep - Sets the general-purpose function
3255   called once at the beginning of each time step.
3256 
3257   Logically Collective on TS
3258 
3259   Input Parameters:
3260 + ts   - The TS context obtained from TSCreate()
3261 - func - The function
3262 
3263   Calling sequence of func:
3264 . func (TS ts);
3265 
3266   Level: intermediate
3267 
3268 .keywords: TS, timestep
3269 .seealso: TSSetPreStage(), TSSetPostStage(), TSSetPostStep(), TSStep()
3270 @*/
3271 PetscErrorCode  TSSetPreStep(TS ts, PetscErrorCode (*func)(TS))
3272 {
3273   PetscFunctionBegin;
3274   PetscValidHeaderSpecific(ts, TS_CLASSID,1);
3275   ts->prestep = func;
3276   PetscFunctionReturn(0);
3277 }
3278 
3279 /*@
3280   TSPreStep - Runs the user-defined pre-step function.
3281 
3282   Collective on TS
3283 
3284   Input Parameters:
3285 . ts   - The TS context obtained from TSCreate()
3286 
3287   Notes:
3288   TSPreStep() is typically used within time stepping implementations,
3289   so most users would not generally call this routine themselves.
3290 
3291   Level: developer
3292 
3293 .keywords: TS, timestep
3294 .seealso: TSSetPreStep(), TSPreStage(), TSPostStage(), TSPostStep()
3295 @*/
3296 PetscErrorCode  TSPreStep(TS ts)
3297 {
3298   PetscErrorCode ierr;
3299 
3300   PetscFunctionBegin;
3301   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
3302   if (ts->prestep) {
3303     PetscStackCallStandard((*ts->prestep),(ts));
3304   }
3305   PetscFunctionReturn(0);
3306 }
3307 
3308 /*@C
3309   TSSetPreStage - Sets the general-purpose function
3310   called once at the beginning of each stage.
3311 
3312   Logically Collective on TS
3313 
3314   Input Parameters:
3315 + ts   - The TS context obtained from TSCreate()
3316 - func - The function
3317 
3318   Calling sequence of func:
3319 . PetscErrorCode func(TS ts, PetscReal stagetime);
3320 
3321   Level: intermediate
3322 
3323   Note:
3324   There may be several stages per time step. If the solve for a given stage fails, the step may be rejected and retried.
3325   The time step number being computed can be queried using TSGetTimeStepNumber() and the total size of the step being
3326   attempted can be obtained using TSGetTimeStep(). The time at the start of the step is available via TSGetTime().
3327 
3328 .keywords: TS, timestep
3329 .seealso: TSSetPostStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext()
3330 @*/
3331 PetscErrorCode  TSSetPreStage(TS ts, PetscErrorCode (*func)(TS,PetscReal))
3332 {
3333   PetscFunctionBegin;
3334   PetscValidHeaderSpecific(ts, TS_CLASSID,1);
3335   ts->prestage = func;
3336   PetscFunctionReturn(0);
3337 }
3338 
3339 /*@C
3340   TSSetPostStage - Sets the general-purpose function
3341   called once at the end of each stage.
3342 
3343   Logically Collective on TS
3344 
3345   Input Parameters:
3346 + ts   - The TS context obtained from TSCreate()
3347 - func - The function
3348 
3349   Calling sequence of func:
3350 . PetscErrorCode func(TS ts, PetscReal stagetime, PetscInt stageindex, Vec* Y);
3351 
3352   Level: intermediate
3353 
3354   Note:
3355   There may be several stages per time step. If the solve for a given stage fails, the step may be rejected and retried.
3356   The time step number being computed can be queried using TSGetTimeStepNumber() and the total size of the step being
3357   attempted can be obtained using TSGetTimeStep(). The time at the start of the step is available via TSGetTime().
3358 
3359 .keywords: TS, timestep
3360 .seealso: TSSetPreStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext()
3361 @*/
3362 PetscErrorCode  TSSetPostStage(TS ts, PetscErrorCode (*func)(TS,PetscReal,PetscInt,Vec*))
3363 {
3364   PetscFunctionBegin;
3365   PetscValidHeaderSpecific(ts, TS_CLASSID,1);
3366   ts->poststage = func;
3367   PetscFunctionReturn(0);
3368 }
3369 
3370 /*@C
3371   TSSetPostEvaluate - Sets the general-purpose function
3372   called once at the end of each step evaluation.
3373 
3374   Logically Collective on TS
3375 
3376   Input Parameters:
3377 + ts   - The TS context obtained from TSCreate()
3378 - func - The function
3379 
3380   Calling sequence of func:
3381 . PetscErrorCode func(TS ts);
3382 
3383   Level: intermediate
3384 
3385   Note:
3386   Semantically, TSSetPostEvaluate() differs from TSSetPostStep() since the function it sets is called before event-handling
3387   thus guaranteeing the same solution (computed by the time-stepper) will be passed to it. On the other hand, TSPostStep()
3388   may be passed a different solution, possibly changed by the event handler. TSPostEvaluate() is called after the next step
3389   solution is evaluated allowing to modify it, if need be. The solution can be obtained with TSGetSolution(), the time step
3390   with TSGetTimeStep(), and the time at the start of the step is available via TSGetTime()
3391 
3392 .keywords: TS, timestep
3393 .seealso: TSSetPreStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext()
3394 @*/
3395 PetscErrorCode  TSSetPostEvaluate(TS ts, PetscErrorCode (*func)(TS))
3396 {
3397   PetscFunctionBegin;
3398   PetscValidHeaderSpecific(ts, TS_CLASSID,1);
3399   ts->postevaluate = func;
3400   PetscFunctionReturn(0);
3401 }
3402 
3403 /*@
3404   TSPreStage - Runs the user-defined pre-stage function set using TSSetPreStage()
3405 
3406   Collective on TS
3407 
3408   Input Parameters:
3409 . ts          - The TS context obtained from TSCreate()
3410   stagetime   - The absolute time of the current stage
3411 
3412   Notes:
3413   TSPreStage() is typically used within time stepping implementations,
3414   most users would not generally call this routine themselves.
3415 
3416   Level: developer
3417 
3418 .keywords: TS, timestep
3419 .seealso: TSPostStage(), TSSetPreStep(), TSPreStep(), TSPostStep()
3420 @*/
3421 PetscErrorCode  TSPreStage(TS ts, PetscReal stagetime)
3422 {
3423   PetscErrorCode ierr;
3424 
3425   PetscFunctionBegin;
3426   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
3427   if (ts->prestage) {
3428     PetscStackCallStandard((*ts->prestage),(ts,stagetime));
3429   }
3430   PetscFunctionReturn(0);
3431 }
3432 
3433 /*@
3434   TSPostStage - Runs the user-defined post-stage function set using TSSetPostStage()
3435 
3436   Collective on TS
3437 
3438   Input Parameters:
3439 . ts          - The TS context obtained from TSCreate()
3440   stagetime   - The absolute time of the current stage
3441   stageindex  - Stage number
3442   Y           - Array of vectors (of size = total number
3443                 of stages) with the stage solutions
3444 
3445   Notes:
3446   TSPostStage() is typically used within time stepping implementations,
3447   most users would not generally call this routine themselves.
3448 
3449   Level: developer
3450 
3451 .keywords: TS, timestep
3452 .seealso: TSPreStage(), TSSetPreStep(), TSPreStep(), TSPostStep()
3453 @*/
3454 PetscErrorCode  TSPostStage(TS ts, PetscReal stagetime, PetscInt stageindex, Vec *Y)
3455 {
3456   PetscErrorCode ierr;
3457 
3458   PetscFunctionBegin;
3459   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
3460   if (ts->poststage) {
3461     PetscStackCallStandard((*ts->poststage),(ts,stagetime,stageindex,Y));
3462   }
3463   PetscFunctionReturn(0);
3464 }
3465 
3466 /*@
3467   TSPostEvaluate - Runs the user-defined post-evaluate function set using TSSetPostEvaluate()
3468 
3469   Collective on TS
3470 
3471   Input Parameters:
3472 . ts          - The TS context obtained from TSCreate()
3473 
3474   Notes:
3475   TSPostEvaluate() is typically used within time stepping implementations,
3476   most users would not generally call this routine themselves.
3477 
3478   Level: developer
3479 
3480 .keywords: TS, timestep
3481 .seealso: TSSetPostEvaluate(), TSSetPreStep(), TSPreStep(), TSPostStep()
3482 @*/
3483 PetscErrorCode  TSPostEvaluate(TS ts)
3484 {
3485   PetscErrorCode ierr;
3486 
3487   PetscFunctionBegin;
3488   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
3489   if (ts->postevaluate) {
3490     PetscStackCallStandard((*ts->postevaluate),(ts));
3491   }
3492   PetscFunctionReturn(0);
3493 }
3494 
3495 /*@C
3496   TSSetPostStep - Sets the general-purpose function
3497   called once at the end of each time step.
3498 
3499   Logically Collective on TS
3500 
3501   Input Parameters:
3502 + ts   - The TS context obtained from TSCreate()
3503 - func - The function
3504 
3505   Calling sequence of func:
3506 $ func (TS ts);
3507 
3508   Notes:
3509   The function set by TSSetPostStep() is called after each successful step. The solution vector X
3510   obtained by TSGetSolution() may be different than that computed at the step end if the event handler
3511   locates an event and TSPostEvent() modifies it. Use TSSetPostEvaluate() if an unmodified solution is needed instead.
3512 
3513   Level: intermediate
3514 
3515 .keywords: TS, timestep
3516 .seealso: TSSetPreStep(), TSSetPreStage(), TSSetPostEvaluate(), TSGetTimeStep(), TSGetTimeStepNumber(), TSGetTime()
3517 @*/
3518 PetscErrorCode  TSSetPostStep(TS ts, PetscErrorCode (*func)(TS))
3519 {
3520   PetscFunctionBegin;
3521   PetscValidHeaderSpecific(ts, TS_CLASSID,1);
3522   ts->poststep = func;
3523   PetscFunctionReturn(0);
3524 }
3525 
3526 /*@
3527   TSPostStep - Runs the user-defined post-step function.
3528 
3529   Collective on TS
3530 
3531   Input Parameters:
3532 . ts   - The TS context obtained from TSCreate()
3533 
3534   Notes:
3535   TSPostStep() is typically used within time stepping implementations,
3536   so most users would not generally call this routine themselves.
3537 
3538   Level: developer
3539 
3540 .keywords: TS, timestep
3541 @*/
3542 PetscErrorCode  TSPostStep(TS ts)
3543 {
3544   PetscErrorCode ierr;
3545 
3546   PetscFunctionBegin;
3547   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
3548   if (ts->poststep) {
3549     PetscStackCallStandard((*ts->poststep),(ts));
3550   }
3551   PetscFunctionReturn(0);
3552 }
3553 
3554 /* ------------ Routines to set performance monitoring options ----------- */
3555 
3556 /*@C
3557    TSMonitorSet - Sets an ADDITIONAL function that is to be used at every
3558    timestep to display the iteration's  progress.
3559 
3560    Logically Collective on TS
3561 
3562    Input Parameters:
3563 +  ts - the TS context obtained from TSCreate()
3564 .  monitor - monitoring routine
3565 .  mctx - [optional] user-defined context for private data for the
3566              monitor routine (use NULL if no context is desired)
3567 -  monitordestroy - [optional] routine that frees monitor context
3568           (may be NULL)
3569 
3570    Calling sequence of monitor:
3571 $    int monitor(TS ts,PetscInt steps,PetscReal time,Vec u,void *mctx)
3572 
3573 +    ts - the TS context
3574 .    steps - iteration number (after the final time step the monitor routine may be called with a step of -1, this indicates the solution has been interpolated to this time)
3575 .    time - current time
3576 .    u - current iterate
3577 -    mctx - [optional] monitoring context
3578 
3579    Notes:
3580    This routine adds an additional monitor to the list of monitors that
3581    already has been loaded.
3582 
3583    Fortran notes: Only a single monitor function can be set for each TS object
3584 
3585    Level: intermediate
3586 
3587 .keywords: TS, timestep, set, monitor
3588 
3589 .seealso: TSMonitorDefault(), TSMonitorCancel()
3590 @*/
3591 PetscErrorCode  TSMonitorSet(TS ts,PetscErrorCode (*monitor)(TS,PetscInt,PetscReal,Vec,void*),void *mctx,PetscErrorCode (*mdestroy)(void**))
3592 {
3593   PetscErrorCode ierr;
3594   PetscInt       i;
3595   PetscBool      identical;
3596 
3597   PetscFunctionBegin;
3598   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
3599   for (i=0; i<ts->numbermonitors;i++) {
3600     ierr = PetscMonitorCompare((PetscErrorCode (*)(void))monitor,mctx,mdestroy,(PetscErrorCode (*)(void))ts->monitor[i],ts->monitorcontext[i],ts->monitordestroy[i],&identical);CHKERRQ(ierr);
3601     if (identical) PetscFunctionReturn(0);
3602   }
3603   if (ts->numbermonitors >= MAXTSMONITORS) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Too many monitors set");
3604   ts->monitor[ts->numbermonitors]          = monitor;
3605   ts->monitordestroy[ts->numbermonitors]   = mdestroy;
3606   ts->monitorcontext[ts->numbermonitors++] = (void*)mctx;
3607   PetscFunctionReturn(0);
3608 }
3609 
3610 /*@C
3611    TSMonitorCancel - Clears all the monitors that have been set on a time-step object.
3612 
3613    Logically Collective on TS
3614 
3615    Input Parameters:
3616 .  ts - the TS context obtained from TSCreate()
3617 
3618    Notes:
3619    There is no way to remove a single, specific monitor.
3620 
3621    Level: intermediate
3622 
3623 .keywords: TS, timestep, set, monitor
3624 
3625 .seealso: TSMonitorDefault(), TSMonitorSet()
3626 @*/
3627 PetscErrorCode  TSMonitorCancel(TS ts)
3628 {
3629   PetscErrorCode ierr;
3630   PetscInt       i;
3631 
3632   PetscFunctionBegin;
3633   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
3634   for (i=0; i<ts->numbermonitors; i++) {
3635     if (ts->monitordestroy[i]) {
3636       ierr = (*ts->monitordestroy[i])(&ts->monitorcontext[i]);CHKERRQ(ierr);
3637     }
3638   }
3639   ts->numbermonitors = 0;
3640   PetscFunctionReturn(0);
3641 }
3642 
3643 /*@C
3644    TSMonitorDefault - The Default monitor, prints the timestep and time for each step
3645 
3646    Level: intermediate
3647 
3648 .keywords: TS, set, monitor
3649 
3650 .seealso:  TSMonitorSet()
3651 @*/
3652 PetscErrorCode TSMonitorDefault(TS ts,PetscInt step,PetscReal ptime,Vec v,PetscViewerAndFormat *vf)
3653 {
3654   PetscErrorCode ierr;
3655   PetscViewer    viewer =  vf->viewer;
3656   PetscBool      iascii,ibinary;
3657 
3658   PetscFunctionBegin;
3659   PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,4);
3660   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr);
3661   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&ibinary);CHKERRQ(ierr);
3662   ierr = PetscViewerPushFormat(viewer,vf->format);CHKERRQ(ierr);
3663   if (iascii) {
3664     ierr = PetscViewerASCIIAddTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr);
3665     if (step == -1){ /* this indicates it is an interpolated solution */
3666       ierr = PetscViewerASCIIPrintf(viewer,"Interpolated solution at time %g between steps %D and %D\n",(double)ptime,ts->steps-1,ts->steps);CHKERRQ(ierr);
3667     } else {
3668       ierr = PetscViewerASCIIPrintf(viewer,"%D TS dt %g time %g%s",step,(double)ts->time_step,(double)ptime,ts->steprollback ? " (r)\n" : "\n");CHKERRQ(ierr);
3669     }
3670     ierr = PetscViewerASCIISubtractTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr);
3671   } else if (ibinary) {
3672     PetscMPIInt rank;
3673     ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)viewer),&rank);CHKERRQ(ierr);
3674     if (!rank) {
3675       PetscBool skipHeader;
3676       PetscInt  classid = REAL_FILE_CLASSID;
3677 
3678       ierr = PetscViewerBinaryGetSkipHeader(viewer,&skipHeader);CHKERRQ(ierr);
3679       if (!skipHeader) {
3680          ierr = PetscViewerBinaryWrite(viewer,&classid,1,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr);
3681        }
3682       ierr = PetscRealView(1,&ptime,viewer);CHKERRQ(ierr);
3683     } else {
3684       ierr = PetscRealView(0,&ptime,viewer);CHKERRQ(ierr);
3685     }
3686   }
3687   ierr = PetscViewerPopFormat(viewer);CHKERRQ(ierr);
3688   PetscFunctionReturn(0);
3689 }
3690 
3691 /*@C
3692    TSAdjointMonitorSet - Sets an ADDITIONAL function that is to be used at every
3693    timestep to display the iteration's  progress.
3694 
3695    Logically Collective on TS
3696 
3697    Input Parameters:
3698 +  ts - the TS context obtained from TSCreate()
3699 .  adjointmonitor - monitoring routine
3700 .  adjointmctx - [optional] user-defined context for private data for the
3701              monitor routine (use NULL if no context is desired)
3702 -  adjointmonitordestroy - [optional] routine that frees monitor context
3703           (may be NULL)
3704 
3705    Calling sequence of monitor:
3706 $    int adjointmonitor(TS ts,PetscInt steps,PetscReal time,Vec u,PetscInt numcost,Vec *lambda, Vec *mu,void *adjointmctx)
3707 
3708 +    ts - the TS context
3709 .    steps - iteration number (after the final time step the monitor routine is called with a step of -1, this is at the final time which may have
3710                                been interpolated to)
3711 .    time - current time
3712 .    u - current iterate
3713 .    numcost - number of cost functionos
3714 .    lambda - sensitivities to initial conditions
3715 .    mu - sensitivities to parameters
3716 -    adjointmctx - [optional] adjoint monitoring context
3717 
3718    Notes:
3719    This routine adds an additional monitor to the list of monitors that
3720    already has been loaded.
3721 
3722    Fortran notes: Only a single monitor function can be set for each TS object
3723 
3724    Level: intermediate
3725 
3726 .keywords: TS, timestep, set, adjoint, monitor
3727 
3728 .seealso: TSAdjointMonitorCancel()
3729 @*/
3730 PetscErrorCode  TSAdjointMonitorSet(TS ts,PetscErrorCode (*adjointmonitor)(TS,PetscInt,PetscReal,Vec,PetscInt,Vec*,Vec*,void*),void *adjointmctx,PetscErrorCode (*adjointmdestroy)(void**))
3731 {
3732   PetscErrorCode ierr;
3733   PetscInt       i;
3734   PetscBool      identical;
3735 
3736   PetscFunctionBegin;
3737   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
3738   for (i=0; i<ts->numbermonitors;i++) {
3739     ierr = PetscMonitorCompare((PetscErrorCode (*)(void))adjointmonitor,adjointmctx,adjointmdestroy,(PetscErrorCode (*)(void))ts->adjointmonitor[i],ts->adjointmonitorcontext[i],ts->adjointmonitordestroy[i],&identical);CHKERRQ(ierr);
3740     if (identical) PetscFunctionReturn(0);
3741   }
3742   if (ts->numberadjointmonitors >= MAXTSMONITORS) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Too many adjoint monitors set");
3743   ts->adjointmonitor[ts->numberadjointmonitors]          = adjointmonitor;
3744   ts->adjointmonitordestroy[ts->numberadjointmonitors]   = adjointmdestroy;
3745   ts->adjointmonitorcontext[ts->numberadjointmonitors++] = (void*)adjointmctx;
3746   PetscFunctionReturn(0);
3747 }
3748 
3749 /*@C
3750    TSAdjointMonitorCancel - Clears all the adjoint monitors that have been set on a time-step object.
3751 
3752    Logically Collective on TS
3753 
3754    Input Parameters:
3755 .  ts - the TS context obtained from TSCreate()
3756 
3757    Notes:
3758    There is no way to remove a single, specific monitor.
3759 
3760    Level: intermediate
3761 
3762 .keywords: TS, timestep, set, adjoint, monitor
3763 
3764 .seealso: TSAdjointMonitorSet()
3765 @*/
3766 PetscErrorCode  TSAdjointMonitorCancel(TS ts)
3767 {
3768   PetscErrorCode ierr;
3769   PetscInt       i;
3770 
3771   PetscFunctionBegin;
3772   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
3773   for (i=0; i<ts->numberadjointmonitors; i++) {
3774     if (ts->adjointmonitordestroy[i]) {
3775       ierr = (*ts->adjointmonitordestroy[i])(&ts->adjointmonitorcontext[i]);CHKERRQ(ierr);
3776     }
3777   }
3778   ts->numberadjointmonitors = 0;
3779   PetscFunctionReturn(0);
3780 }
3781 
3782 /*@C
3783    TSAdjointMonitorDefault - the default monitor of adjoint computations
3784 
3785    Level: intermediate
3786 
3787 .keywords: TS, set, monitor
3788 
3789 .seealso: TSAdjointMonitorSet()
3790 @*/
3791 PetscErrorCode TSAdjointMonitorDefault(TS ts,PetscInt step,PetscReal ptime,Vec v,PetscInt numcost,Vec *lambda,Vec *mu,PetscViewerAndFormat *vf)
3792 {
3793   PetscErrorCode ierr;
3794   PetscViewer    viewer = vf->viewer;
3795 
3796   PetscFunctionBegin;
3797   PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,4);
3798   ierr = PetscViewerPushFormat(viewer,vf->format);CHKERRQ(ierr);
3799   ierr = PetscViewerASCIIAddTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr);
3800   ierr = PetscViewerASCIIPrintf(viewer,"%D TS dt %g time %g%s",step,(double)ts->time_step,(double)ptime,ts->steprollback ? " (r)\n" : "\n");CHKERRQ(ierr);
3801   ierr = PetscViewerASCIISubtractTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr);
3802   ierr = PetscViewerPopFormat(viewer);CHKERRQ(ierr);
3803   PetscFunctionReturn(0);
3804 }
3805 
3806 /*@
3807    TSInterpolate - Interpolate the solution computed during the previous step to an arbitrary location in the interval
3808 
3809    Collective on TS
3810 
3811    Input Argument:
3812 +  ts - time stepping context
3813 -  t - time to interpolate to
3814 
3815    Output Argument:
3816 .  U - state at given time
3817 
3818    Level: intermediate
3819 
3820    Developer Notes:
3821    TSInterpolate() and the storing of previous steps/stages should be generalized to support delay differential equations and continuous adjoints.
3822 
3823 .keywords: TS, set
3824 
3825 .seealso: TSSetExactFinalTime(), TSSolve()
3826 @*/
3827 PetscErrorCode TSInterpolate(TS ts,PetscReal t,Vec U)
3828 {
3829   PetscErrorCode ierr;
3830 
3831   PetscFunctionBegin;
3832   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
3833   PetscValidHeaderSpecific(U,VEC_CLASSID,3);
3834   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);
3835   if (!ts->ops->interpolate) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"%s does not provide interpolation",((PetscObject)ts)->type_name);
3836   ierr = (*ts->ops->interpolate)(ts,t,U);CHKERRQ(ierr);
3837   PetscFunctionReturn(0);
3838 }
3839 
3840 /*@
3841    TSStep - Steps one time step
3842 
3843    Collective on TS
3844 
3845    Input Parameter:
3846 .  ts - the TS context obtained from TSCreate()
3847 
3848    Level: developer
3849 
3850    Notes:
3851    The public interface for the ODE/DAE solvers is TSSolve(), you should almost for sure be using that routine and not this routine.
3852 
3853    The hook set using TSSetPreStep() is called before each attempt to take the step. In general, the time step size may
3854    be changed due to adaptive error controller or solve failures. Note that steps may contain multiple stages.
3855 
3856    This may over-step the final time provided in TSSetDuration() depending on the time-step used. TSSolve() interpolates to exactly the
3857    time provided in TSSetDuration(). One can use TSInterpolate() to determine an interpolated solution within the final timestep.
3858 
3859 .keywords: TS, timestep, solve
3860 
3861 .seealso: TSCreate(), TSSetUp(), TSDestroy(), TSSolve(), TSSetPreStep(), TSSetPreStage(), TSSetPostStage(), TSInterpolate()
3862 @*/
3863 PetscErrorCode  TSStep(TS ts)
3864 {
3865   PetscErrorCode   ierr;
3866   static PetscBool cite = PETSC_FALSE;
3867   PetscReal        ptime;
3868 
3869   PetscFunctionBegin;
3870   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
3871   ierr = PetscCitationsRegister("@techreport{tspaper,\n"
3872                                 "  title       = {{PETSc/TS}: A Modern Scalable {DAE/ODE} Solver Library},\n"
3873                                 "  author      = {Shrirang Abhyankar and Jed Brown and Emil Constantinescu and Debojyoti Ghosh and Barry F. Smith},\n"
3874                                 "  type        = {Preprint},\n"
3875                                 "  number      = {ANL/MCS-P5061-0114},\n"
3876                                 "  institution = {Argonne National Laboratory},\n"
3877                                 "  year        = {2014}\n}\n",&cite);CHKERRQ(ierr);
3878 
3879   ierr = TSSetUp(ts);CHKERRQ(ierr);
3880   ierr = TSTrajectorySetUp(ts->trajectory,ts);CHKERRQ(ierr);
3881 
3882   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()");
3883   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");
3884 
3885   if (!ts->steps) ts->ptime_prev = ts->ptime;
3886   ts->reason = TS_CONVERGED_ITERATING;
3887   ptime = ts->ptime; ts->ptime_prev_rollback = ts->ptime_prev;
3888   if (!ts->ops->step) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSStep not implemented for type '%s'",((PetscObject)ts)->type_name);
3889   ierr = PetscLogEventBegin(TS_Step,ts,0,0,0);CHKERRQ(ierr);
3890   ierr = (*ts->ops->step)(ts);CHKERRQ(ierr);
3891   ierr = PetscLogEventEnd(TS_Step,ts,0,0,0);CHKERRQ(ierr);
3892   ts->ptime_prev = ptime;
3893   ts->steps++; ts->total_steps++;
3894   ts->steprollback = PETSC_FALSE;
3895   ts->steprestart  = PETSC_FALSE;
3896 
3897   if (ts->reason < 0) {
3898     if (ts->errorifstepfailed) {
3899       if (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]);
3900       else SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s",TSConvergedReasons[ts->reason]);
3901     }
3902   } else if (!ts->reason) {
3903     if (ts->steps >= ts->max_steps)     ts->reason = TS_CONVERGED_ITS;
3904     else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME;
3905   }
3906   PetscFunctionReturn(0);
3907 }
3908 
3909 /*@
3910    TSAdjointStep - Steps one time step backward in the adjoint run
3911 
3912    Collective on TS
3913 
3914    Input Parameter:
3915 .  ts - the TS context obtained from TSCreate()
3916 
3917    Level: intermediate
3918 
3919 .keywords: TS, adjoint, step
3920 
3921 .seealso: TSAdjointSetUp(), TSAdjointSolve()
3922 @*/
3923 PetscErrorCode  TSAdjointStep(TS ts)
3924 {
3925   DM               dm;
3926   PetscErrorCode   ierr;
3927 
3928   PetscFunctionBegin;
3929   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
3930   ierr = TSGetDM(ts,&dm);CHKERRQ(ierr);
3931   ierr = TSAdjointSetUp(ts);CHKERRQ(ierr);
3932 
3933   ierr = VecViewFromOptions(ts->vec_sol,(PetscObject)ts,"-ts_view_solution");CHKERRQ(ierr);
3934 
3935   ts->reason = TS_CONVERGED_ITERATING;
3936   ts->ptime_prev = ts->ptime;
3937   if (!ts->ops->adjointstep) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed because the adjoint of  %s has not been implemented, try other time stepping methods for adjoint sensitivity analysis",((PetscObject)ts)->type_name);
3938   ierr = PetscLogEventBegin(TS_AdjointStep,ts,0,0,0);CHKERRQ(ierr);
3939   ierr = (*ts->ops->adjointstep)(ts);CHKERRQ(ierr);
3940   ierr = PetscLogEventEnd(TS_AdjointStep,ts,0,0,0);CHKERRQ(ierr);
3941   ts->steps++; ts->total_steps--;
3942 
3943   if (ts->reason < 0) {
3944     if (ts->errorifstepfailed) {
3945       if (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]);
3946       else if (ts->reason == TS_DIVERGED_STEP_REJECTED) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s, increase -ts_max_reject or make negative to attempt recovery",TSConvergedReasons[ts->reason]);
3947       else SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s",TSConvergedReasons[ts->reason]);
3948     }
3949   } else if (!ts->reason) {
3950     if (ts->steps >= ts->adjoint_max_steps) ts->reason = TS_CONVERGED_ITS;
3951   }
3952   PetscFunctionReturn(0);
3953 }
3954 
3955 /*@
3956    TSEvaluateWLTE - Evaluate the weighted local truncation error norm
3957    at the end of a time step with a given order of accuracy.
3958 
3959    Collective on TS
3960 
3961    Input Arguments:
3962 +  ts - time stepping context
3963 .  wnormtype - norm type, either NORM_2 or NORM_INFINITY
3964 -  order - optional, desired order for the error evaluation or PETSC_DECIDE
3965 
3966    Output Arguments:
3967 +  order - optional, the actual order of the error evaluation
3968 -  wlte - the weighted local truncation error norm
3969 
3970    Level: advanced
3971 
3972    Notes:
3973    If the timestepper cannot evaluate the error in a particular step
3974    (eg. in the first step or restart steps after event handling),
3975    this routine returns wlte=-1.0 .
3976 
3977 .seealso: TSStep(), TSAdapt, TSErrorWeightedNorm()
3978 @*/
3979 PetscErrorCode TSEvaluateWLTE(TS ts,NormType wnormtype,PetscInt *order,PetscReal *wlte)
3980 {
3981   PetscErrorCode ierr;
3982 
3983   PetscFunctionBegin;
3984   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
3985   PetscValidType(ts,1);
3986   PetscValidLogicalCollectiveEnum(ts,wnormtype,4);
3987   if (order) PetscValidIntPointer(order,3);
3988   if (order) PetscValidLogicalCollectiveInt(ts,*order,3);
3989   PetscValidRealPointer(wlte,4);
3990   if (wnormtype != NORM_2 && wnormtype != NORM_INFINITY) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]);
3991   if (!ts->ops->evaluatewlte) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSEvaluateWLTE not implemented for type '%s'",((PetscObject)ts)->type_name);
3992   ierr = (*ts->ops->evaluatewlte)(ts,wnormtype,order,wlte);CHKERRQ(ierr);
3993   PetscFunctionReturn(0);
3994 }
3995 
3996 /*@
3997    TSEvaluateStep - Evaluate the solution at the end of a time step with a given order of accuracy.
3998 
3999    Collective on TS
4000 
4001    Input Arguments:
4002 +  ts - time stepping context
4003 .  order - desired order of accuracy
4004 -  done - whether the step was evaluated at this order (pass NULL to generate an error if not available)
4005 
4006    Output Arguments:
4007 .  U - state at the end of the current step
4008 
4009    Level: advanced
4010 
4011    Notes:
4012    This function cannot be called until all stages have been evaluated.
4013    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.
4014 
4015 .seealso: TSStep(), TSAdapt
4016 @*/
4017 PetscErrorCode TSEvaluateStep(TS ts,PetscInt order,Vec U,PetscBool *done)
4018 {
4019   PetscErrorCode ierr;
4020 
4021   PetscFunctionBegin;
4022   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
4023   PetscValidType(ts,1);
4024   PetscValidHeaderSpecific(U,VEC_CLASSID,3);
4025   if (!ts->ops->evaluatestep) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSEvaluateStep not implemented for type '%s'",((PetscObject)ts)->type_name);
4026   ierr = (*ts->ops->evaluatestep)(ts,order,U,done);CHKERRQ(ierr);
4027   PetscFunctionReturn(0);
4028 }
4029 
4030 /*@
4031  TSForwardCostIntegral - Evaluate the cost integral in the forward run.
4032 
4033  Collective on TS
4034 
4035  Input Arguments:
4036  .  ts - time stepping context
4037 
4038  Level: advanced
4039 
4040  Notes:
4041  This function cannot be called until TSStep() has been completed.
4042 
4043  .seealso: TSSolve(), TSAdjointCostIntegral()
4044  @*/
4045 PetscErrorCode TSForwardCostIntegral(TS ts)
4046 {
4047     PetscErrorCode ierr;
4048     PetscValidHeaderSpecific(ts,TS_CLASSID,1);
4049     if (!ts->ops->forwardintegral) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"%s does not provide integral evaluation in the forward run",((PetscObject)ts)->type_name);
4050     ierr = (*ts->ops->forwardintegral)(ts);CHKERRQ(ierr);
4051     PetscFunctionReturn(0);
4052 }
4053 
4054 /*@
4055    TSSolve - Steps the requested number of timesteps.
4056 
4057    Collective on TS
4058 
4059    Input Parameter:
4060 +  ts - the TS context obtained from TSCreate()
4061 -  u - the solution vector  (can be null if TSSetSolution() was used and TSSetExactFinalTime(ts,TS_EXACTFINALTIME_MATCHSTEP) was not used,
4062                              otherwise must contain the initial conditions and will contain the solution at the final requested time
4063 
4064    Level: beginner
4065 
4066    Notes:
4067    The final time returned by this function may be different from the time of the internally
4068    held state accessible by TSGetSolution() and TSGetTime() because the method may have
4069    stepped over the final time.
4070 
4071 .keywords: TS, timestep, solve
4072 
4073 .seealso: TSCreate(), TSSetSolution(), TSStep(), TSGetTime(), TSGetSolveTime()
4074 @*/
4075 PetscErrorCode TSSolve(TS ts,Vec u)
4076 {
4077   Vec               solution;
4078   PetscErrorCode    ierr;
4079 
4080   PetscFunctionBegin;
4081   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
4082   if (u) PetscValidHeaderSpecific(u,VEC_CLASSID,2);
4083 
4084   if (ts->exact_final_time == TS_EXACTFINALTIME_INTERPOLATE) {   /* Need ts->vec_sol to be distinct so it is not overwritten when we interpolate at the end */
4085     PetscValidHeaderSpecific(u,VEC_CLASSID,2);
4086     if (!ts->vec_sol || u == ts->vec_sol) {
4087       ierr = VecDuplicate(u,&solution);CHKERRQ(ierr);
4088       ierr = TSSetSolution(ts,solution);CHKERRQ(ierr);
4089       ierr = VecDestroy(&solution);CHKERRQ(ierr); /* grant ownership */
4090     }
4091     ierr = VecCopy(u,ts->vec_sol);CHKERRQ(ierr);
4092   } else if (u) {
4093     ierr = TSSetSolution(ts,u);CHKERRQ(ierr);
4094   }
4095   ierr = TSSetUp(ts);CHKERRQ(ierr);
4096   ierr = TSTrajectorySetUp(ts->trajectory,ts);CHKERRQ(ierr);
4097 
4098   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()");
4099   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");
4100 
4101   /* reset number of steps only when the step is not restarted. ARKIMEX
4102      restarts the step after an event. Resetting these counters in such a case causes
4103      TSTrajectory to incorrectly save the output files
4104   */
4105 
4106   ts->steps             = 0;
4107   ts->ksp_its           = 0;
4108   ts->snes_its          = 0;
4109   ts->num_snes_failures = 0;
4110   ts->reject            = 0;
4111   ts->reason            = TS_CONVERGED_ITERATING;
4112 
4113   ierr = TSViewFromOptions(ts,NULL,"-ts_view_pre");CHKERRQ(ierr);
4114 
4115   if (ts->ops->solve) { /* This private interface is transitional and should be removed when all implementations are updated. */
4116     ierr = (*ts->ops->solve)(ts);CHKERRQ(ierr);
4117     if (u) {ierr = VecCopy(ts->vec_sol,u);CHKERRQ(ierr);}
4118     ts->solvetime = ts->ptime;
4119     solution = ts->vec_sol;
4120   } else { /* Step the requested number of timesteps. */
4121     if (ts->steps >= ts->max_steps)     ts->reason = TS_CONVERGED_ITS;
4122     else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME;
4123 
4124     ierr = TSTrajectorySet(ts->trajectory,ts,ts->total_steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr);
4125     ierr = TSEventInitialize(ts->event,ts,ts->ptime,ts->vec_sol);CHKERRQ(ierr);
4126 
4127     ts->steprollback = PETSC_FALSE;
4128     ts->steprestart  = PETSC_TRUE;
4129 
4130     while (!ts->reason) {
4131       ierr = TSMonitor(ts,ts->total_steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr);
4132       if (!ts->steprollback) {
4133         ierr = TSPreStep(ts);CHKERRQ(ierr);
4134       }
4135       ierr = TSStep(ts);CHKERRQ(ierr);
4136       if (ts->vec_costintegral && ts->costintegralfwd) { /* Must evaluate the cost integral before event is handled. The cost integral value can also be rolled back. */
4137         ierr = TSForwardCostIntegral(ts);CHKERRQ(ierr);
4138       }
4139       ierr = TSPostEvaluate(ts);CHKERRQ(ierr);
4140       ierr = TSEventHandler(ts);CHKERRQ(ierr); /* The right-hand side may be changed due to event. Be careful with Any computation using the RHS information after this point. */
4141       if (!ts->steprollback) {
4142         ierr = TSTrajectorySet(ts->trajectory,ts,ts->total_steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr);
4143         ierr = TSPostStep(ts);CHKERRQ(ierr);
4144       }
4145     }
4146     ierr = TSMonitor(ts,ts->total_steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr);
4147 
4148     if (ts->exact_final_time == TS_EXACTFINALTIME_INTERPOLATE && ts->ptime > ts->max_time) {
4149       ierr = TSInterpolate(ts,ts->max_time,u);CHKERRQ(ierr);
4150       ts->solvetime = ts->max_time;
4151       solution = u;
4152       ierr = TSMonitor(ts,-1,ts->solvetime,solution);CHKERRQ(ierr);
4153     } else {
4154       if (u) {ierr = VecCopy(ts->vec_sol,u);CHKERRQ(ierr);}
4155       ts->solvetime = ts->ptime;
4156       solution = ts->vec_sol;
4157     }
4158   }
4159 
4160   ierr = TSViewFromOptions(ts,NULL,"-ts_view");CHKERRQ(ierr);
4161   ierr = VecViewFromOptions(solution,NULL,"-ts_view_solution");CHKERRQ(ierr);
4162   ierr = PetscObjectSAWsBlock((PetscObject)ts);CHKERRQ(ierr);
4163   if (ts->adjoint_solve) {
4164     ierr = TSAdjointSolve(ts);CHKERRQ(ierr);
4165   }
4166   PetscFunctionReturn(0);
4167 }
4168 
4169 /*@
4170  TSAdjointCostIntegral - Evaluate the cost integral in the adjoint run.
4171 
4172  Collective on TS
4173 
4174  Input Arguments:
4175  .  ts - time stepping context
4176 
4177  Level: advanced
4178 
4179  Notes:
4180  This function cannot be called until TSAdjointStep() has been completed.
4181 
4182  .seealso: TSAdjointSolve(), TSAdjointStep
4183  @*/
4184 PetscErrorCode TSAdjointCostIntegral(TS ts)
4185 {
4186     PetscErrorCode ierr;
4187     PetscValidHeaderSpecific(ts,TS_CLASSID,1);
4188     if (!ts->ops->adjointintegral) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"%s does not provide integral evaluation in the adjoint run",((PetscObject)ts)->type_name);
4189     ierr = (*ts->ops->adjointintegral)(ts);CHKERRQ(ierr);
4190     PetscFunctionReturn(0);
4191 }
4192 
4193 /*@
4194    TSAdjointSolve - Solves the discrete ajoint problem for an ODE/DAE
4195 
4196    Collective on TS
4197 
4198    Input Parameter:
4199 .  ts - the TS context obtained from TSCreate()
4200 
4201    Options Database:
4202 . -ts_adjoint_view_solution <viewerinfo> - views the first gradient with respect to the initial conditions
4203 
4204    Level: intermediate
4205 
4206    Notes:
4207    This must be called after a call to TSSolve() that solves the forward problem
4208 
4209    By default this will integrate back to the initial time, one can use TSAdjointSetSteps() to step back to a later time
4210 
4211 .keywords: TS, timestep, solve
4212 
4213 .seealso: TSCreate(), TSSetCostGradients(), TSSetSolution(), TSAdjointStep()
4214 @*/
4215 PetscErrorCode TSAdjointSolve(TS ts)
4216 {
4217   PetscErrorCode    ierr;
4218 
4219   PetscFunctionBegin;
4220   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
4221   ierr = TSAdjointSetUp(ts);CHKERRQ(ierr);
4222 
4223   /* reset time step and iteration counters */
4224   ts->steps             = 0;
4225   ts->ksp_its           = 0;
4226   ts->snes_its          = 0;
4227   ts->num_snes_failures = 0;
4228   ts->reject            = 0;
4229   ts->reason            = TS_CONVERGED_ITERATING;
4230 
4231   if (!ts->adjoint_max_steps) ts->adjoint_max_steps = ts->total_steps;
4232 
4233   if (ts->steps >= ts->adjoint_max_steps)     ts->reason = TS_CONVERGED_ITS;
4234   while (!ts->reason) {
4235     ierr = TSTrajectoryGet(ts->trajectory,ts,ts->total_steps,&ts->ptime);CHKERRQ(ierr);
4236     ierr = TSAdjointMonitor(ts,ts->total_steps,ts->ptime,ts->vec_sol,ts->numcost,ts->vecs_sensi,ts->vecs_sensip);CHKERRQ(ierr);
4237     ierr = TSAdjointEventHandler(ts);CHKERRQ(ierr);
4238     ierr = TSAdjointStep(ts);CHKERRQ(ierr);
4239     if (ts->vec_costintegral && !ts->costintegralfwd) {
4240       ierr = TSAdjointCostIntegral(ts);CHKERRQ(ierr);
4241     }
4242   }
4243   ierr = TSTrajectoryGet(ts->trajectory,ts,ts->total_steps,&ts->ptime);CHKERRQ(ierr);
4244   ierr = TSAdjointMonitor(ts,ts->total_steps,ts->ptime,ts->vec_sol,ts->numcost,ts->vecs_sensi,ts->vecs_sensip);CHKERRQ(ierr);
4245   ts->solvetime = ts->ptime;
4246   ierr = TSTrajectoryViewFromOptions(ts->trajectory,NULL,"-ts_trajectory_view");CHKERRQ(ierr);
4247   ierr = VecViewFromOptions(ts->vecs_sensi[0],(PetscObject) ts, "-ts_adjoint_view_solution");CHKERRQ(ierr);
4248   PetscFunctionReturn(0);
4249 }
4250 
4251 /*@C
4252    TSMonitor - Runs all user-provided monitor routines set using TSMonitorSet()
4253 
4254    Collective on TS
4255 
4256    Input Parameters:
4257 +  ts - time stepping context obtained from TSCreate()
4258 .  step - step number that has just completed
4259 .  ptime - model time of the state
4260 -  u - state at the current model time
4261 
4262    Notes:
4263    TSMonitor() is typically used automatically within the time stepping implementations.
4264    Users would almost never call this routine directly.
4265 
4266    A step of -1 indicates that the monitor is being called on a solution obtained by interpolating from computed solutions
4267 
4268    Level: developer
4269 
4270 .keywords: TS, timestep
4271 @*/
4272 PetscErrorCode TSMonitor(TS ts,PetscInt step,PetscReal ptime,Vec u)
4273 {
4274   DM             dm;
4275   PetscInt       i,n = ts->numbermonitors;
4276   PetscErrorCode ierr;
4277 
4278   PetscFunctionBegin;
4279   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
4280   PetscValidHeaderSpecific(u,VEC_CLASSID,4);
4281 
4282   ierr = TSGetDM(ts,&dm);CHKERRQ(ierr);
4283   ierr = DMSetOutputSequenceNumber(dm,step,ptime);CHKERRQ(ierr);
4284 
4285   ierr = VecLockPush(u);CHKERRQ(ierr);
4286   for (i=0; i<n; i++) {
4287     ierr = (*ts->monitor[i])(ts,step,ptime,u,ts->monitorcontext[i]);CHKERRQ(ierr);
4288   }
4289   ierr = VecLockPop(u);CHKERRQ(ierr);
4290   PetscFunctionReturn(0);
4291 }
4292 
4293 /*@C
4294    TSAdjointMonitor - Runs all user-provided adjoint monitor routines set using TSAdjointMonitorSet()
4295 
4296    Collective on TS
4297 
4298    Input Parameters:
4299 +  ts - time stepping context obtained from TSCreate()
4300 .  step - step number that has just completed
4301 .  ptime - model time of the state
4302 .  u - state at the current model time
4303 .  numcost - number of cost functions (dimension of lambda  or mu)
4304 .  lambda - vectors containing the gradients of the cost functions with respect to the ODE/DAE solution variables
4305 -  mu - vectors containing the gradients of the cost functions with respect to the problem parameters
4306 
4307    Notes:
4308    TSAdjointMonitor() is typically used automatically within the time stepping implementations.
4309    Users would almost never call this routine directly.
4310 
4311    Level: developer
4312 
4313 .keywords: TS, timestep
4314 @*/
4315 PetscErrorCode TSAdjointMonitor(TS ts,PetscInt step,PetscReal ptime,Vec u,PetscInt numcost,Vec *lambda, Vec *mu)
4316 {
4317   PetscErrorCode ierr;
4318   PetscInt       i,n = ts->numberadjointmonitors;
4319 
4320   PetscFunctionBegin;
4321   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
4322   PetscValidHeaderSpecific(u,VEC_CLASSID,4);
4323   ierr = VecLockPush(u);CHKERRQ(ierr);
4324   for (i=0; i<n; i++) {
4325     ierr = (*ts->adjointmonitor[i])(ts,step,ptime,u,numcost,lambda,mu,ts->adjointmonitorcontext[i]);CHKERRQ(ierr);
4326   }
4327   ierr = VecLockPop(u);CHKERRQ(ierr);
4328   PetscFunctionReturn(0);
4329 }
4330 
4331 /* ------------------------------------------------------------------------*/
4332 /*@C
4333    TSMonitorLGCtxCreate - Creates a TSMonitorLGCtx context for use with
4334    TS to monitor the solution process graphically in various ways
4335 
4336    Collective on TS
4337 
4338    Input Parameters:
4339 +  host - the X display to open, or null for the local machine
4340 .  label - the title to put in the title bar
4341 .  x, y - the screen coordinates of the upper left coordinate of the window
4342 .  m, n - the screen width and height in pixels
4343 -  howoften - if positive then determines the frequency of the plotting, if -1 then only at the final time
4344 
4345    Output Parameter:
4346 .  ctx - the context
4347 
4348    Options Database Key:
4349 +  -ts_monitor_lg_timestep - automatically sets line graph monitor
4350 .  -ts_monitor_lg_solution - monitor the solution (or certain values of the solution by calling TSMonitorLGSetDisplayVariables() or TSMonitorLGCtxSetDisplayVariables())
4351 .  -ts_monitor_lg_error -  monitor the error
4352 .  -ts_monitor_lg_ksp_iterations - monitor the number of KSP iterations needed for each timestep
4353 .  -ts_monitor_lg_snes_iterations - monitor the number of SNES iterations needed for each timestep
4354 -  -lg_use_markers <true,false> - mark the data points (at each time step) on the plot; default is true
4355 
4356    Notes:
4357    Use TSMonitorLGCtxDestroy() to destroy.
4358 
4359    One can provide a function that transforms the solution before plotting it with TSMonitorLGCtxSetTransform() or TSMonitorLGSetTransform()
4360 
4361    Many of the functions that control the monitoring have two forms: TSMonitorLGSet/GetXXXX() and TSMonitorLGCtxSet/GetXXXX() the first take a TS object as the
4362    first argument (if that TS object does not have a TSMonitorLGCtx associated with it the function call is ignored) and the second takes a TSMonitorLGCtx object
4363    as the first argument.
4364 
4365    One can control the names displayed for each solution or error variable with TSMonitorLGCtxSetVariableNames() or TSMonitorLGSetVariableNames()
4366 
4367 
4368    Level: intermediate
4369 
4370 .keywords: TS, monitor, line graph, residual
4371 
4372 .seealso: TSMonitorLGTimeStep(), TSMonitorSet(), TSMonitorLGSolution(), TSMonitorLGError(), TSMonitorDefault(), VecView(),
4373            TSMonitorLGCtxCreate(), TSMonitorLGCtxSetVariableNames(), TSMonitorLGCtxGetVariableNames(),
4374            TSMonitorLGSetVariableNames(), TSMonitorLGGetVariableNames(), TSMonitorLGSetDisplayVariables(), TSMonitorLGCtxSetDisplayVariables(),
4375            TSMonitorLGCtxSetTransform(), TSMonitorLGSetTransform(), TSMonitorLGError(), TSMonitorLGSNESIterations(), TSMonitorLGKSPIterations(),
4376            TSMonitorEnvelopeCtxCreate(), TSMonitorEnvelopeGetBounds(), TSMonitorEnvelopeCtxDestroy(), TSMonitorEnvelop()
4377 
4378 @*/
4379 PetscErrorCode  TSMonitorLGCtxCreate(MPI_Comm comm,const char host[],const char label[],int x,int y,int m,int n,PetscInt howoften,TSMonitorLGCtx *ctx)
4380 {
4381   PetscDraw      draw;
4382   PetscErrorCode ierr;
4383 
4384   PetscFunctionBegin;
4385   ierr = PetscNew(ctx);CHKERRQ(ierr);
4386   ierr = PetscDrawCreate(comm,host,label,x,y,m,n,&draw);CHKERRQ(ierr);
4387   ierr = PetscDrawSetFromOptions(draw);CHKERRQ(ierr);
4388   ierr = PetscDrawLGCreate(draw,1,&(*ctx)->lg);CHKERRQ(ierr);
4389   ierr = PetscDrawLGSetFromOptions((*ctx)->lg);CHKERRQ(ierr);
4390   ierr = PetscDrawDestroy(&draw);CHKERRQ(ierr);
4391   (*ctx)->howoften = howoften;
4392   PetscFunctionReturn(0);
4393 }
4394 
4395 PetscErrorCode TSMonitorLGTimeStep(TS ts,PetscInt step,PetscReal ptime,Vec v,void *monctx)
4396 {
4397   TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx;
4398   PetscReal      x   = ptime,y;
4399   PetscErrorCode ierr;
4400 
4401   PetscFunctionBegin;
4402   if (step < 0) PetscFunctionReturn(0); /* -1 indicates an interpolated solution */
4403   if (!step) {
4404     PetscDrawAxis axis;
4405     ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr);
4406     ierr = PetscDrawAxisSetLabels(axis,"Timestep as function of time","Time","Time Step");CHKERRQ(ierr);
4407     ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr);
4408   }
4409   ierr = TSGetTimeStep(ts,&y);CHKERRQ(ierr);
4410   ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr);
4411   if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) {
4412     ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr);
4413     ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr);
4414   }
4415   PetscFunctionReturn(0);
4416 }
4417 
4418 /*@C
4419    TSMonitorLGCtxDestroy - Destroys a line graph context that was created
4420    with TSMonitorLGCtxCreate().
4421 
4422    Collective on TSMonitorLGCtx
4423 
4424    Input Parameter:
4425 .  ctx - the monitor context
4426 
4427    Level: intermediate
4428 
4429 .keywords: TS, monitor, line graph, destroy
4430 
4431 .seealso: TSMonitorLGCtxCreate(),  TSMonitorSet(), TSMonitorLGTimeStep();
4432 @*/
4433 PetscErrorCode  TSMonitorLGCtxDestroy(TSMonitorLGCtx *ctx)
4434 {
4435   PetscErrorCode ierr;
4436 
4437   PetscFunctionBegin;
4438   if ((*ctx)->transformdestroy) {
4439     ierr = ((*ctx)->transformdestroy)((*ctx)->transformctx);CHKERRQ(ierr);
4440   }
4441   ierr = PetscDrawLGDestroy(&(*ctx)->lg);CHKERRQ(ierr);
4442   ierr = PetscStrArrayDestroy(&(*ctx)->names);CHKERRQ(ierr);
4443   ierr = PetscStrArrayDestroy(&(*ctx)->displaynames);CHKERRQ(ierr);
4444   ierr = PetscFree((*ctx)->displayvariables);CHKERRQ(ierr);
4445   ierr = PetscFree((*ctx)->displayvalues);CHKERRQ(ierr);
4446   ierr = PetscFree(*ctx);CHKERRQ(ierr);
4447   PetscFunctionReturn(0);
4448 }
4449 
4450 /*@
4451    TSGetTime - Gets the time of the most recently completed step.
4452 
4453    Not Collective
4454 
4455    Input Parameter:
4456 .  ts - the TS context obtained from TSCreate()
4457 
4458    Output Parameter:
4459 .  t  - the current time. This time may not corresponds to the final time set with TSSetDuration(), use TSGetSolveTime().
4460 
4461    Level: beginner
4462 
4463    Note:
4464    When called during time step evaluation (e.g. during residual evaluation or via hooks set using TSSetPreStep(),
4465    TSSetPreStage(), TSSetPostStage(), or TSSetPostStep()), the time is the time at the start of the step being evaluated.
4466 
4467 .seealso: TSSetInitialTimeStep(), TSGetTimeStep(), TSGetSolveTime()
4468 
4469 .keywords: TS, get, time
4470 @*/
4471 PetscErrorCode  TSGetTime(TS ts,PetscReal *t)
4472 {
4473   PetscFunctionBegin;
4474   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
4475   PetscValidRealPointer(t,2);
4476   *t = ts->ptime;
4477   PetscFunctionReturn(0);
4478 }
4479 
4480 /*@
4481    TSGetPrevTime - Gets the starting time of the previously completed step.
4482 
4483    Not Collective
4484 
4485    Input Parameter:
4486 .  ts - the TS context obtained from TSCreate()
4487 
4488    Output Parameter:
4489 .  t  - the previous time
4490 
4491    Level: beginner
4492 
4493 .seealso: TSSetInitialTimeStep(), TSGetTimeStep()
4494 
4495 .keywords: TS, get, time
4496 @*/
4497 PetscErrorCode  TSGetPrevTime(TS ts,PetscReal *t)
4498 {
4499   PetscFunctionBegin;
4500   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
4501   PetscValidRealPointer(t,2);
4502   *t = ts->ptime_prev;
4503   PetscFunctionReturn(0);
4504 }
4505 
4506 /*@
4507    TSSetTime - Allows one to reset the time.
4508 
4509    Logically Collective on TS
4510 
4511    Input Parameters:
4512 +  ts - the TS context obtained from TSCreate()
4513 -  time - the time
4514 
4515    Level: intermediate
4516 
4517 .seealso: TSGetTime(), TSSetDuration()
4518 
4519 .keywords: TS, set, time
4520 @*/
4521 PetscErrorCode  TSSetTime(TS ts, PetscReal t)
4522 {
4523   PetscFunctionBegin;
4524   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
4525   PetscValidLogicalCollectiveReal(ts,t,2);
4526   ts->ptime = t;
4527   PetscFunctionReturn(0);
4528 }
4529 
4530 /*@C
4531    TSSetOptionsPrefix - Sets the prefix used for searching for all
4532    TS options in the database.
4533 
4534    Logically Collective on TS
4535 
4536    Input Parameter:
4537 +  ts     - The TS context
4538 -  prefix - The prefix to prepend to all option names
4539 
4540    Notes:
4541    A hyphen (-) must NOT be given at the beginning of the prefix name.
4542    The first character of all runtime options is AUTOMATICALLY the
4543    hyphen.
4544 
4545    Level: advanced
4546 
4547 .keywords: TS, set, options, prefix, database
4548 
4549 .seealso: TSSetFromOptions()
4550 
4551 @*/
4552 PetscErrorCode  TSSetOptionsPrefix(TS ts,const char prefix[])
4553 {
4554   PetscErrorCode ierr;
4555   SNES           snes;
4556 
4557   PetscFunctionBegin;
4558   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
4559   ierr = PetscObjectSetOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr);
4560   ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr);
4561   ierr = SNESSetOptionsPrefix(snes,prefix);CHKERRQ(ierr);
4562   PetscFunctionReturn(0);
4563 }
4564 
4565 
4566 /*@C
4567    TSAppendOptionsPrefix - Appends to the prefix used for searching for all
4568    TS options in the database.
4569 
4570    Logically Collective on TS
4571 
4572    Input Parameter:
4573 +  ts     - The TS context
4574 -  prefix - The prefix to prepend to all option names
4575 
4576    Notes:
4577    A hyphen (-) must NOT be given at the beginning of the prefix name.
4578    The first character of all runtime options is AUTOMATICALLY the
4579    hyphen.
4580 
4581    Level: advanced
4582 
4583 .keywords: TS, append, options, prefix, database
4584 
4585 .seealso: TSGetOptionsPrefix()
4586 
4587 @*/
4588 PetscErrorCode  TSAppendOptionsPrefix(TS ts,const char prefix[])
4589 {
4590   PetscErrorCode ierr;
4591   SNES           snes;
4592 
4593   PetscFunctionBegin;
4594   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
4595   ierr = PetscObjectAppendOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr);
4596   ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr);
4597   ierr = SNESAppendOptionsPrefix(snes,prefix);CHKERRQ(ierr);
4598   PetscFunctionReturn(0);
4599 }
4600 
4601 /*@C
4602    TSGetOptionsPrefix - Sets the prefix used for searching for all
4603    TS options in the database.
4604 
4605    Not Collective
4606 
4607    Input Parameter:
4608 .  ts - The TS context
4609 
4610    Output Parameter:
4611 .  prefix - A pointer to the prefix string used
4612 
4613    Notes: On the fortran side, the user should pass in a string 'prifix' of
4614    sufficient length to hold the prefix.
4615 
4616    Level: intermediate
4617 
4618 .keywords: TS, get, options, prefix, database
4619 
4620 .seealso: TSAppendOptionsPrefix()
4621 @*/
4622 PetscErrorCode  TSGetOptionsPrefix(TS ts,const char *prefix[])
4623 {
4624   PetscErrorCode ierr;
4625 
4626   PetscFunctionBegin;
4627   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
4628   PetscValidPointer(prefix,2);
4629   ierr = PetscObjectGetOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr);
4630   PetscFunctionReturn(0);
4631 }
4632 
4633 /*@C
4634    TSGetRHSJacobian - Returns the Jacobian J at the present timestep.
4635 
4636    Not Collective, but parallel objects are returned if TS is parallel
4637 
4638    Input Parameter:
4639 .  ts  - The TS context obtained from TSCreate()
4640 
4641    Output Parameters:
4642 +  Amat - The (approximate) Jacobian J of G, where U_t = G(U,t)  (or NULL)
4643 .  Pmat - The matrix from which the preconditioner is constructed, usually the same as Amat  (or NULL)
4644 .  func - Function to compute the Jacobian of the RHS  (or NULL)
4645 -  ctx - User-defined context for Jacobian evaluation routine  (or NULL)
4646 
4647    Notes: You can pass in NULL for any return argument you do not need.
4648 
4649    Level: intermediate
4650 
4651 .seealso: TSGetTimeStep(), TSGetMatrices(), TSGetTime(), TSGetTimeStepNumber()
4652 
4653 .keywords: TS, timestep, get, matrix, Jacobian
4654 @*/
4655 PetscErrorCode  TSGetRHSJacobian(TS ts,Mat *Amat,Mat *Pmat,TSRHSJacobian *func,void **ctx)
4656 {
4657   PetscErrorCode ierr;
4658   DM             dm;
4659 
4660   PetscFunctionBegin;
4661   if (Amat || Pmat) {
4662     SNES snes;
4663     ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr);
4664     ierr = SNESSetUpMatrices(snes);CHKERRQ(ierr);
4665     ierr = SNESGetJacobian(snes,Amat,Pmat,NULL,NULL);CHKERRQ(ierr);
4666   }
4667   ierr = TSGetDM(ts,&dm);CHKERRQ(ierr);
4668   ierr = DMTSGetRHSJacobian(dm,func,ctx);CHKERRQ(ierr);
4669   PetscFunctionReturn(0);
4670 }
4671 
4672 /*@C
4673    TSGetIJacobian - Returns the implicit Jacobian at the present timestep.
4674 
4675    Not Collective, but parallel objects are returned if TS is parallel
4676 
4677    Input Parameter:
4678 .  ts  - The TS context obtained from TSCreate()
4679 
4680    Output Parameters:
4681 +  Amat  - The (approximate) Jacobian of F(t,U,U_t)
4682 .  Pmat - The matrix from which the preconditioner is constructed, often the same as Amat
4683 .  f   - The function to compute the matrices
4684 - ctx - User-defined context for Jacobian evaluation routine
4685 
4686    Notes: You can pass in NULL for any return argument you do not need.
4687 
4688    Level: advanced
4689 
4690 .seealso: TSGetTimeStep(), TSGetRHSJacobian(), TSGetMatrices(), TSGetTime(), TSGetTimeStepNumber()
4691 
4692 .keywords: TS, timestep, get, matrix, Jacobian
4693 @*/
4694 PetscErrorCode  TSGetIJacobian(TS ts,Mat *Amat,Mat *Pmat,TSIJacobian *f,void **ctx)
4695 {
4696   PetscErrorCode ierr;
4697   DM             dm;
4698 
4699   PetscFunctionBegin;
4700   if (Amat || Pmat) {
4701     SNES snes;
4702     ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr);
4703     ierr = SNESSetUpMatrices(snes);CHKERRQ(ierr);
4704     ierr = SNESGetJacobian(snes,Amat,Pmat,NULL,NULL);CHKERRQ(ierr);
4705   }
4706   ierr = TSGetDM(ts,&dm);CHKERRQ(ierr);
4707   ierr = DMTSGetIJacobian(dm,f,ctx);CHKERRQ(ierr);
4708   PetscFunctionReturn(0);
4709 }
4710 
4711 
4712 /*@C
4713    TSMonitorDrawSolution - Monitors progress of the TS solvers by calling
4714    VecView() for the solution at each timestep
4715 
4716    Collective on TS
4717 
4718    Input Parameters:
4719 +  ts - the TS context
4720 .  step - current time-step
4721 .  ptime - current time
4722 -  dummy - either a viewer or NULL
4723 
4724    Options Database:
4725 .   -ts_monitor_draw_solution_initial - show initial solution as well as current solution
4726 
4727    Notes: the initial solution and current solution are not display with a common axis scaling so generally the option -ts_monitor_draw_solution_initial
4728        will look bad
4729 
4730    Level: intermediate
4731 
4732 .keywords: TS,  vector, monitor, view
4733 
4734 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView()
4735 @*/
4736 PetscErrorCode  TSMonitorDrawSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy)
4737 {
4738   PetscErrorCode   ierr;
4739   TSMonitorDrawCtx ictx = (TSMonitorDrawCtx)dummy;
4740   PetscDraw        draw;
4741 
4742   PetscFunctionBegin;
4743   if (!step && ictx->showinitial) {
4744     if (!ictx->initialsolution) {
4745       ierr = VecDuplicate(u,&ictx->initialsolution);CHKERRQ(ierr);
4746     }
4747     ierr = VecCopy(u,ictx->initialsolution);CHKERRQ(ierr);
4748   }
4749   if (!(((ictx->howoften > 0) && (!(step % ictx->howoften))) || ((ictx->howoften == -1) && ts->reason))) PetscFunctionReturn(0);
4750 
4751   if (ictx->showinitial) {
4752     PetscReal pause;
4753     ierr = PetscViewerDrawGetPause(ictx->viewer,&pause);CHKERRQ(ierr);
4754     ierr = PetscViewerDrawSetPause(ictx->viewer,0.0);CHKERRQ(ierr);
4755     ierr = VecView(ictx->initialsolution,ictx->viewer);CHKERRQ(ierr);
4756     ierr = PetscViewerDrawSetPause(ictx->viewer,pause);CHKERRQ(ierr);
4757     ierr = PetscViewerDrawSetHold(ictx->viewer,PETSC_TRUE);CHKERRQ(ierr);
4758   }
4759   ierr = VecView(u,ictx->viewer);CHKERRQ(ierr);
4760   if (ictx->showtimestepandtime) {
4761     PetscReal xl,yl,xr,yr,h;
4762     char      time[32];
4763 
4764     ierr = PetscViewerDrawGetDraw(ictx->viewer,0,&draw);CHKERRQ(ierr);
4765     ierr = PetscSNPrintf(time,32,"Timestep %d Time %g",(int)step,(double)ptime);CHKERRQ(ierr);
4766     ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr);
4767     h    = yl + .95*(yr - yl);
4768     ierr = PetscDrawStringCentered(draw,.5*(xl+xr),h,PETSC_DRAW_BLACK,time);CHKERRQ(ierr);
4769     ierr = PetscDrawFlush(draw);CHKERRQ(ierr);
4770   }
4771 
4772   if (ictx->showinitial) {
4773     ierr = PetscViewerDrawSetHold(ictx->viewer,PETSC_FALSE);CHKERRQ(ierr);
4774   }
4775   PetscFunctionReturn(0);
4776 }
4777 
4778 /*@C
4779    TSAdjointMonitorDrawSensi - Monitors progress of the adjoint TS solvers by calling
4780    VecView() for the sensitivities to initial states at each timestep
4781 
4782    Collective on TS
4783 
4784    Input Parameters:
4785 +  ts - the TS context
4786 .  step - current time-step
4787 .  ptime - current time
4788 .  u - current state
4789 .  numcost - number of cost functions
4790 .  lambda - sensitivities to initial conditions
4791 .  mu - sensitivities to parameters
4792 -  dummy - either a viewer or NULL
4793 
4794    Level: intermediate
4795 
4796 .keywords: TS,  vector, adjoint, monitor, view
4797 
4798 .seealso: TSAdjointMonitorSet(), TSAdjointMonitorDefault(), VecView()
4799 @*/
4800 PetscErrorCode  TSAdjointMonitorDrawSensi(TS ts,PetscInt step,PetscReal ptime,Vec u,PetscInt numcost,Vec *lambda,Vec *mu,void *dummy)
4801 {
4802   PetscErrorCode   ierr;
4803   TSMonitorDrawCtx ictx = (TSMonitorDrawCtx)dummy;
4804   PetscDraw        draw;
4805   PetscReal        xl,yl,xr,yr,h;
4806   char             time[32];
4807 
4808   PetscFunctionBegin;
4809   if (!(((ictx->howoften > 0) && (!(step % ictx->howoften))) || ((ictx->howoften == -1) && ts->reason))) PetscFunctionReturn(0);
4810 
4811   ierr = VecView(lambda[0],ictx->viewer);CHKERRQ(ierr);
4812   ierr = PetscViewerDrawGetDraw(ictx->viewer,0,&draw);CHKERRQ(ierr);
4813   ierr = PetscSNPrintf(time,32,"Timestep %d Time %g",(int)step,(double)ptime);CHKERRQ(ierr);
4814   ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr);
4815   h    = yl + .95*(yr - yl);
4816   ierr = PetscDrawStringCentered(draw,.5*(xl+xr),h,PETSC_DRAW_BLACK,time);CHKERRQ(ierr);
4817   ierr = PetscDrawFlush(draw);CHKERRQ(ierr);
4818   PetscFunctionReturn(0);
4819 }
4820 
4821 /*@C
4822    TSMonitorDrawSolutionPhase - Monitors progress of the TS solvers by plotting the solution as a phase diagram
4823 
4824    Collective on TS
4825 
4826    Input Parameters:
4827 +  ts - the TS context
4828 .  step - current time-step
4829 .  ptime - current time
4830 -  dummy - either a viewer or NULL
4831 
4832    Level: intermediate
4833 
4834 .keywords: TS,  vector, monitor, view
4835 
4836 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView()
4837 @*/
4838 PetscErrorCode  TSMonitorDrawSolutionPhase(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy)
4839 {
4840   PetscErrorCode    ierr;
4841   TSMonitorDrawCtx  ictx = (TSMonitorDrawCtx)dummy;
4842   PetscDraw         draw;
4843   PetscDrawAxis     axis;
4844   PetscInt          n;
4845   PetscMPIInt       size;
4846   PetscReal         U0,U1,xl,yl,xr,yr,h;
4847   char              time[32];
4848   const PetscScalar *U;
4849 
4850   PetscFunctionBegin;
4851   ierr = MPI_Comm_size(PetscObjectComm((PetscObject)ts),&size);CHKERRQ(ierr);
4852   if (size != 1) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Only allowed for sequential runs");
4853   ierr = VecGetSize(u,&n);CHKERRQ(ierr);
4854   if (n != 2) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Only for ODEs with two unknowns");
4855 
4856   ierr = PetscViewerDrawGetDraw(ictx->viewer,0,&draw);CHKERRQ(ierr);
4857   ierr = PetscViewerDrawGetDrawAxis(ictx->viewer,0,&axis);CHKERRQ(ierr);
4858   ierr = PetscDrawAxisGetLimits(axis,&xl,&xr,&yl,&yr);CHKERRQ(ierr);
4859   if (!step) {
4860     ierr = PetscDrawClear(draw);CHKERRQ(ierr);
4861     ierr = PetscDrawAxisDraw(axis);CHKERRQ(ierr);
4862   }
4863 
4864   ierr = VecGetArrayRead(u,&U);CHKERRQ(ierr);
4865   U0 = PetscRealPart(U[0]);
4866   U1 = PetscRealPart(U[1]);
4867   ierr = VecRestoreArrayRead(u,&U);CHKERRQ(ierr);
4868   if ((U0 < xl) || (U1 < yl) || (U0 > xr) || (U1 > yr)) PetscFunctionReturn(0);
4869 
4870   ierr = PetscDrawCollectiveBegin(draw);CHKERRQ(ierr);
4871   ierr = PetscDrawPoint(draw,U0,U1,PETSC_DRAW_BLACK);CHKERRQ(ierr);
4872   if (ictx->showtimestepandtime) {
4873     ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr);
4874     ierr = PetscSNPrintf(time,32,"Timestep %d Time %g",(int)step,(double)ptime);CHKERRQ(ierr);
4875     h    = yl + .95*(yr - yl);
4876     ierr = PetscDrawStringCentered(draw,.5*(xl+xr),h,PETSC_DRAW_BLACK,time);CHKERRQ(ierr);
4877   }
4878   ierr = PetscDrawCollectiveEnd(draw);CHKERRQ(ierr);
4879   ierr = PetscDrawFlush(draw);CHKERRQ(ierr);
4880   ierr = PetscDrawSave(draw);CHKERRQ(ierr);
4881   PetscFunctionReturn(0);
4882 }
4883 
4884 
4885 /*@C
4886    TSMonitorDrawCtxDestroy - Destroys the monitor context for TSMonitorDrawSolution()
4887 
4888    Collective on TS
4889 
4890    Input Parameters:
4891 .    ctx - the monitor context
4892 
4893    Level: intermediate
4894 
4895 .keywords: TS,  vector, monitor, view
4896 
4897 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorDrawSolution(), TSMonitorDrawError()
4898 @*/
4899 PetscErrorCode  TSMonitorDrawCtxDestroy(TSMonitorDrawCtx *ictx)
4900 {
4901   PetscErrorCode ierr;
4902 
4903   PetscFunctionBegin;
4904   ierr = PetscViewerDestroy(&(*ictx)->viewer);CHKERRQ(ierr);
4905   ierr = VecDestroy(&(*ictx)->initialsolution);CHKERRQ(ierr);
4906   ierr = PetscFree(*ictx);CHKERRQ(ierr);
4907   PetscFunctionReturn(0);
4908 }
4909 
4910 /*@C
4911    TSMonitorDrawCtxCreate - Creates the monitor context for TSMonitorDrawCtx
4912 
4913    Collective on TS
4914 
4915    Input Parameter:
4916 .    ts - time-step context
4917 
4918    Output Patameter:
4919 .    ctx - the monitor context
4920 
4921    Options Database:
4922 .   -ts_monitor_draw_solution_initial - show initial solution as well as current solution
4923 
4924    Level: intermediate
4925 
4926 .keywords: TS,  vector, monitor, view
4927 
4928 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorDrawCtx()
4929 @*/
4930 PetscErrorCode  TSMonitorDrawCtxCreate(MPI_Comm comm,const char host[],const char label[],int x,int y,int m,int n,PetscInt howoften,TSMonitorDrawCtx *ctx)
4931 {
4932   PetscErrorCode   ierr;
4933 
4934   PetscFunctionBegin;
4935   ierr = PetscNew(ctx);CHKERRQ(ierr);
4936   ierr = PetscViewerDrawOpen(comm,host,label,x,y,m,n,&(*ctx)->viewer);CHKERRQ(ierr);
4937   ierr = PetscViewerSetFromOptions((*ctx)->viewer);CHKERRQ(ierr);
4938 
4939   (*ctx)->howoften    = howoften;
4940   (*ctx)->showinitial = PETSC_FALSE;
4941   ierr = PetscOptionsGetBool(NULL,NULL,"-ts_monitor_draw_solution_initial",&(*ctx)->showinitial,NULL);CHKERRQ(ierr);
4942 
4943   (*ctx)->showtimestepandtime = PETSC_FALSE;
4944   ierr = PetscOptionsGetBool(NULL,NULL,"-ts_monitor_draw_solution_show_time",&(*ctx)->showtimestepandtime,NULL);CHKERRQ(ierr);
4945   PetscFunctionReturn(0);
4946 }
4947 
4948 /*@C
4949    TSMonitorDrawError - Monitors progress of the TS solvers by calling
4950    VecView() for the error at each timestep
4951 
4952    Collective on TS
4953 
4954    Input Parameters:
4955 +  ts - the TS context
4956 .  step - current time-step
4957 .  ptime - current time
4958 -  dummy - either a viewer or NULL
4959 
4960    Level: intermediate
4961 
4962 .keywords: TS,  vector, monitor, view
4963 
4964 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView()
4965 @*/
4966 PetscErrorCode  TSMonitorDrawError(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy)
4967 {
4968   PetscErrorCode   ierr;
4969   TSMonitorDrawCtx ctx    = (TSMonitorDrawCtx)dummy;
4970   PetscViewer      viewer = ctx->viewer;
4971   Vec              work;
4972 
4973   PetscFunctionBegin;
4974   if (!(((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason))) PetscFunctionReturn(0);
4975   ierr = VecDuplicate(u,&work);CHKERRQ(ierr);
4976   ierr = TSComputeSolutionFunction(ts,ptime,work);CHKERRQ(ierr);
4977   ierr = VecAXPY(work,-1.0,u);CHKERRQ(ierr);
4978   ierr = VecView(work,viewer);CHKERRQ(ierr);
4979   ierr = VecDestroy(&work);CHKERRQ(ierr);
4980   PetscFunctionReturn(0);
4981 }
4982 
4983 #include <petsc/private/dmimpl.h>
4984 /*@
4985    TSSetDM - Sets the DM that may be used by some nonlinear solvers or preconditioners under the TS
4986 
4987    Logically Collective on TS and DM
4988 
4989    Input Parameters:
4990 +  ts - the ODE integrator object
4991 -  dm - the dm, cannot be NULL
4992 
4993    Level: intermediate
4994 
4995 
4996 .seealso: TSGetDM(), SNESSetDM(), SNESGetDM()
4997 @*/
4998 PetscErrorCode  TSSetDM(TS ts,DM dm)
4999 {
5000   PetscErrorCode ierr;
5001   SNES           snes;
5002   DMTS           tsdm;
5003 
5004   PetscFunctionBegin;
5005   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
5006   PetscValidHeaderSpecific(dm,DM_CLASSID,2);
5007   ierr = PetscObjectReference((PetscObject)dm);CHKERRQ(ierr);
5008   if (ts->dm) {               /* Move the DMTS context over to the new DM unless the new DM already has one */
5009     if (ts->dm->dmts && !dm->dmts) {
5010       ierr = DMCopyDMTS(ts->dm,dm);CHKERRQ(ierr);
5011       ierr = DMGetDMTS(ts->dm,&tsdm);CHKERRQ(ierr);
5012       if (tsdm->originaldm == ts->dm) { /* Grant write privileges to the replacement DM */
5013         tsdm->originaldm = dm;
5014       }
5015     }
5016     ierr = DMDestroy(&ts->dm);CHKERRQ(ierr);
5017   }
5018   ts->dm = dm;
5019 
5020   ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr);
5021   ierr = SNESSetDM(snes,dm);CHKERRQ(ierr);
5022   PetscFunctionReturn(0);
5023 }
5024 
5025 /*@
5026    TSGetDM - Gets the DM that may be used by some preconditioners
5027 
5028    Not Collective
5029 
5030    Input Parameter:
5031 . ts - the preconditioner context
5032 
5033    Output Parameter:
5034 .  dm - the dm
5035 
5036    Level: intermediate
5037 
5038 
5039 .seealso: TSSetDM(), SNESSetDM(), SNESGetDM()
5040 @*/
5041 PetscErrorCode  TSGetDM(TS ts,DM *dm)
5042 {
5043   PetscErrorCode ierr;
5044 
5045   PetscFunctionBegin;
5046   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
5047   if (!ts->dm) {
5048     ierr = DMShellCreate(PetscObjectComm((PetscObject)ts),&ts->dm);CHKERRQ(ierr);
5049     if (ts->snes) {ierr = SNESSetDM(ts->snes,ts->dm);CHKERRQ(ierr);}
5050   }
5051   *dm = ts->dm;
5052   PetscFunctionReturn(0);
5053 }
5054 
5055 /*@
5056    SNESTSFormFunction - Function to evaluate nonlinear residual
5057 
5058    Logically Collective on SNES
5059 
5060    Input Parameter:
5061 + snes - nonlinear solver
5062 . U - the current state at which to evaluate the residual
5063 - ctx - user context, must be a TS
5064 
5065    Output Parameter:
5066 . F - the nonlinear residual
5067 
5068    Notes:
5069    This function is not normally called by users and is automatically registered with the SNES used by TS.
5070    It is most frequently passed to MatFDColoringSetFunction().
5071 
5072    Level: advanced
5073 
5074 .seealso: SNESSetFunction(), MatFDColoringSetFunction()
5075 @*/
5076 PetscErrorCode  SNESTSFormFunction(SNES snes,Vec U,Vec F,void *ctx)
5077 {
5078   TS             ts = (TS)ctx;
5079   PetscErrorCode ierr;
5080 
5081   PetscFunctionBegin;
5082   PetscValidHeaderSpecific(snes,SNES_CLASSID,1);
5083   PetscValidHeaderSpecific(U,VEC_CLASSID,2);
5084   PetscValidHeaderSpecific(F,VEC_CLASSID,3);
5085   PetscValidHeaderSpecific(ts,TS_CLASSID,4);
5086   ierr = (ts->ops->snesfunction)(snes,U,F,ts);CHKERRQ(ierr);
5087   PetscFunctionReturn(0);
5088 }
5089 
5090 /*@
5091    SNESTSFormJacobian - Function to evaluate the Jacobian
5092 
5093    Collective on SNES
5094 
5095    Input Parameter:
5096 + snes - nonlinear solver
5097 . U - the current state at which to evaluate the residual
5098 - ctx - user context, must be a TS
5099 
5100    Output Parameter:
5101 + A - the Jacobian
5102 . B - the preconditioning matrix (may be the same as A)
5103 - flag - indicates any structure change in the matrix
5104 
5105    Notes:
5106    This function is not normally called by users and is automatically registered with the SNES used by TS.
5107 
5108    Level: developer
5109 
5110 .seealso: SNESSetJacobian()
5111 @*/
5112 PetscErrorCode  SNESTSFormJacobian(SNES snes,Vec U,Mat A,Mat B,void *ctx)
5113 {
5114   TS             ts = (TS)ctx;
5115   PetscErrorCode ierr;
5116 
5117   PetscFunctionBegin;
5118   PetscValidHeaderSpecific(snes,SNES_CLASSID,1);
5119   PetscValidHeaderSpecific(U,VEC_CLASSID,2);
5120   PetscValidPointer(A,3);
5121   PetscValidHeaderSpecific(A,MAT_CLASSID,3);
5122   PetscValidPointer(B,4);
5123   PetscValidHeaderSpecific(B,MAT_CLASSID,4);
5124   PetscValidHeaderSpecific(ts,TS_CLASSID,6);
5125   ierr = (ts->ops->snesjacobian)(snes,U,A,B,ts);CHKERRQ(ierr);
5126   PetscFunctionReturn(0);
5127 }
5128 
5129 /*@C
5130    TSComputeRHSFunctionLinear - Evaluate the right hand side via the user-provided Jacobian, for linear problems Udot = A U only
5131 
5132    Collective on TS
5133 
5134    Input Arguments:
5135 +  ts - time stepping context
5136 .  t - time at which to evaluate
5137 .  U - state at which to evaluate
5138 -  ctx - context
5139 
5140    Output Arguments:
5141 .  F - right hand side
5142 
5143    Level: intermediate
5144 
5145    Notes:
5146    This function is intended to be passed to TSSetRHSFunction() to evaluate the right hand side for linear problems.
5147    The matrix (and optionally the evaluation context) should be passed to TSSetRHSJacobian().
5148 
5149 .seealso: TSSetRHSFunction(), TSSetRHSJacobian(), TSComputeRHSJacobianConstant()
5150 @*/
5151 PetscErrorCode TSComputeRHSFunctionLinear(TS ts,PetscReal t,Vec U,Vec F,void *ctx)
5152 {
5153   PetscErrorCode ierr;
5154   Mat            Arhs,Brhs;
5155 
5156   PetscFunctionBegin;
5157   ierr = TSGetRHSMats_Private(ts,&Arhs,&Brhs);CHKERRQ(ierr);
5158   ierr = TSComputeRHSJacobian(ts,t,U,Arhs,Brhs);CHKERRQ(ierr);
5159   ierr = MatMult(Arhs,U,F);CHKERRQ(ierr);
5160   PetscFunctionReturn(0);
5161 }
5162 
5163 /*@C
5164    TSComputeRHSJacobianConstant - Reuses a Jacobian that is time-independent.
5165 
5166    Collective on TS
5167 
5168    Input Arguments:
5169 +  ts - time stepping context
5170 .  t - time at which to evaluate
5171 .  U - state at which to evaluate
5172 -  ctx - context
5173 
5174    Output Arguments:
5175 +  A - pointer to operator
5176 .  B - pointer to preconditioning matrix
5177 -  flg - matrix structure flag
5178 
5179    Level: intermediate
5180 
5181    Notes:
5182    This function is intended to be passed to TSSetRHSJacobian() to evaluate the Jacobian for linear time-independent problems.
5183 
5184 .seealso: TSSetRHSFunction(), TSSetRHSJacobian(), TSComputeRHSFunctionLinear()
5185 @*/
5186 PetscErrorCode TSComputeRHSJacobianConstant(TS ts,PetscReal t,Vec U,Mat A,Mat B,void *ctx)
5187 {
5188   PetscFunctionBegin;
5189   PetscFunctionReturn(0);
5190 }
5191 
5192 /*@C
5193    TSComputeIFunctionLinear - Evaluate the left hand side via the user-provided Jacobian, for linear problems only
5194 
5195    Collective on TS
5196 
5197    Input Arguments:
5198 +  ts - time stepping context
5199 .  t - time at which to evaluate
5200 .  U - state at which to evaluate
5201 .  Udot - time derivative of state vector
5202 -  ctx - context
5203 
5204    Output Arguments:
5205 .  F - left hand side
5206 
5207    Level: intermediate
5208 
5209    Notes:
5210    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
5211    user is required to write their own TSComputeIFunction.
5212    This function is intended to be passed to TSSetIFunction() to evaluate the left hand side for linear problems.
5213    The matrix (and optionally the evaluation context) should be passed to TSSetIJacobian().
5214 
5215    Note that using this function is NOT equivalent to using TSComputeRHSFunctionLinear() since that solves Udot = A U
5216 
5217 .seealso: TSSetIFunction(), TSSetIJacobian(), TSComputeIJacobianConstant(), TSComputeRHSFunctionLinear()
5218 @*/
5219 PetscErrorCode TSComputeIFunctionLinear(TS ts,PetscReal t,Vec U,Vec Udot,Vec F,void *ctx)
5220 {
5221   PetscErrorCode ierr;
5222   Mat            A,B;
5223 
5224   PetscFunctionBegin;
5225   ierr = TSGetIJacobian(ts,&A,&B,NULL,NULL);CHKERRQ(ierr);
5226   ierr = TSComputeIJacobian(ts,t,U,Udot,1.0,A,B,PETSC_TRUE);CHKERRQ(ierr);
5227   ierr = MatMult(A,Udot,F);CHKERRQ(ierr);
5228   PetscFunctionReturn(0);
5229 }
5230 
5231 /*@C
5232    TSComputeIJacobianConstant - Reuses a time-independent for a semi-implicit DAE or ODE
5233 
5234    Collective on TS
5235 
5236    Input Arguments:
5237 +  ts - time stepping context
5238 .  t - time at which to evaluate
5239 .  U - state at which to evaluate
5240 .  Udot - time derivative of state vector
5241 .  shift - shift to apply
5242 -  ctx - context
5243 
5244    Output Arguments:
5245 +  A - pointer to operator
5246 .  B - pointer to preconditioning matrix
5247 -  flg - matrix structure flag
5248 
5249    Level: advanced
5250 
5251    Notes:
5252    This function is intended to be passed to TSSetIJacobian() to evaluate the Jacobian for linear time-independent problems.
5253 
5254    It is only appropriate for problems of the form
5255 
5256 $     M Udot = F(U,t)
5257 
5258   where M is constant and F is non-stiff.  The user must pass M to TSSetIJacobian().  The current implementation only
5259   works with IMEX time integration methods such as TSROSW and TSARKIMEX, since there is no support for de-constructing
5260   an implicit operator of the form
5261 
5262 $    shift*M + J
5263 
5264   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
5265   a copy of M or reassemble it when requested.
5266 
5267 .seealso: TSSetIFunction(), TSSetIJacobian(), TSComputeIFunctionLinear()
5268 @*/
5269 PetscErrorCode TSComputeIJacobianConstant(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat A,Mat B,void *ctx)
5270 {
5271   PetscErrorCode ierr;
5272 
5273   PetscFunctionBegin;
5274   ierr = MatScale(A, shift / ts->ijacobian.shift);CHKERRQ(ierr);
5275   ts->ijacobian.shift = shift;
5276   PetscFunctionReturn(0);
5277 }
5278 
5279 /*@
5280    TSGetEquationType - Gets the type of the equation that TS is solving.
5281 
5282    Not Collective
5283 
5284    Input Parameter:
5285 .  ts - the TS context
5286 
5287    Output Parameter:
5288 .  equation_type - see TSEquationType
5289 
5290    Level: beginner
5291 
5292 .keywords: TS, equation type
5293 
5294 .seealso: TSSetEquationType(), TSEquationType
5295 @*/
5296 PetscErrorCode  TSGetEquationType(TS ts,TSEquationType *equation_type)
5297 {
5298   PetscFunctionBegin;
5299   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
5300   PetscValidPointer(equation_type,2);
5301   *equation_type = ts->equation_type;
5302   PetscFunctionReturn(0);
5303 }
5304 
5305 /*@
5306    TSSetEquationType - Sets the type of the equation that TS is solving.
5307 
5308    Not Collective
5309 
5310    Input Parameter:
5311 +  ts - the TS context
5312 -  equation_type - see TSEquationType
5313 
5314    Level: advanced
5315 
5316 .keywords: TS, equation type
5317 
5318 .seealso: TSGetEquationType(), TSEquationType
5319 @*/
5320 PetscErrorCode  TSSetEquationType(TS ts,TSEquationType equation_type)
5321 {
5322   PetscFunctionBegin;
5323   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
5324   ts->equation_type = equation_type;
5325   PetscFunctionReturn(0);
5326 }
5327 
5328 /*@
5329    TSGetConvergedReason - Gets the reason the TS iteration was stopped.
5330 
5331    Not Collective
5332 
5333    Input Parameter:
5334 .  ts - the TS context
5335 
5336    Output Parameter:
5337 .  reason - negative value indicates diverged, positive value converged, see TSConvergedReason or the
5338             manual pages for the individual convergence tests for complete lists
5339 
5340    Level: beginner
5341 
5342    Notes:
5343    Can only be called after the call to TSSolve() is complete.
5344 
5345 .keywords: TS, nonlinear, set, convergence, test
5346 
5347 .seealso: TSSetConvergenceTest(), TSConvergedReason
5348 @*/
5349 PetscErrorCode  TSGetConvergedReason(TS ts,TSConvergedReason *reason)
5350 {
5351   PetscFunctionBegin;
5352   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
5353   PetscValidPointer(reason,2);
5354   *reason = ts->reason;
5355   PetscFunctionReturn(0);
5356 }
5357 
5358 /*@
5359    TSSetConvergedReason - Sets the reason for handling the convergence of TSSolve.
5360 
5361    Not Collective
5362 
5363    Input Parameter:
5364 +  ts - the TS context
5365 .  reason - negative value indicates diverged, positive value converged, see TSConvergedReason or the
5366             manual pages for the individual convergence tests for complete lists
5367 
5368    Level: advanced
5369 
5370    Notes:
5371    Can only be called during TSSolve() is active.
5372 
5373 .keywords: TS, nonlinear, set, convergence, test
5374 
5375 .seealso: TSConvergedReason
5376 @*/
5377 PetscErrorCode  TSSetConvergedReason(TS ts,TSConvergedReason reason)
5378 {
5379   PetscFunctionBegin;
5380   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
5381   ts->reason = reason;
5382   PetscFunctionReturn(0);
5383 }
5384 
5385 /*@
5386    TSGetSolveTime - Gets the time after a call to TSSolve()
5387 
5388    Not Collective
5389 
5390    Input Parameter:
5391 .  ts - the TS context
5392 
5393    Output Parameter:
5394 .  ftime - the final time. This time corresponds to the final time set with TSSetDuration()
5395 
5396    Level: beginner
5397 
5398    Notes:
5399    Can only be called after the call to TSSolve() is complete.
5400 
5401 .keywords: TS, nonlinear, set, convergence, test
5402 
5403 .seealso: TSSetConvergenceTest(), TSConvergedReason
5404 @*/
5405 PetscErrorCode  TSGetSolveTime(TS ts,PetscReal *ftime)
5406 {
5407   PetscFunctionBegin;
5408   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
5409   PetscValidPointer(ftime,2);
5410   *ftime = ts->solvetime;
5411   PetscFunctionReturn(0);
5412 }
5413 
5414 /*@
5415    TSGetTotalSteps - Gets the total number of steps done since the last call to TSSetUp() or TSCreate()
5416 
5417    Not Collective
5418 
5419    Input Parameter:
5420 .  ts - the TS context
5421 
5422    Output Parameter:
5423 .  steps - the number of steps
5424 
5425    Level: beginner
5426 
5427    Notes:
5428    Includes the number of steps for all calls to TSSolve() since TSSetUp() was called
5429 
5430 .keywords: TS, nonlinear, set, convergence, test
5431 
5432 .seealso: TSSetConvergenceTest(), TSConvergedReason
5433 @*/
5434 PetscErrorCode  TSGetTotalSteps(TS ts,PetscInt *steps)
5435 {
5436   PetscFunctionBegin;
5437   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
5438   PetscValidPointer(steps,2);
5439   *steps = ts->total_steps;
5440   PetscFunctionReturn(0);
5441 }
5442 
5443 /*@
5444    TSGetSNESIterations - Gets the total number of nonlinear iterations
5445    used by the time integrator.
5446 
5447    Not Collective
5448 
5449    Input Parameter:
5450 .  ts - TS context
5451 
5452    Output Parameter:
5453 .  nits - number of nonlinear iterations
5454 
5455    Notes:
5456    This counter is reset to zero for each successive call to TSSolve().
5457 
5458    Level: intermediate
5459 
5460 .keywords: TS, get, number, nonlinear, iterations
5461 
5462 .seealso:  TSGetKSPIterations()
5463 @*/
5464 PetscErrorCode TSGetSNESIterations(TS ts,PetscInt *nits)
5465 {
5466   PetscFunctionBegin;
5467   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
5468   PetscValidIntPointer(nits,2);
5469   *nits = ts->snes_its;
5470   PetscFunctionReturn(0);
5471 }
5472 
5473 /*@
5474    TSGetKSPIterations - Gets the total number of linear iterations
5475    used by the time integrator.
5476 
5477    Not Collective
5478 
5479    Input Parameter:
5480 .  ts - TS context
5481 
5482    Output Parameter:
5483 .  lits - number of linear iterations
5484 
5485    Notes:
5486    This counter is reset to zero for each successive call to TSSolve().
5487 
5488    Level: intermediate
5489 
5490 .keywords: TS, get, number, linear, iterations
5491 
5492 .seealso:  TSGetSNESIterations(), SNESGetKSPIterations()
5493 @*/
5494 PetscErrorCode TSGetKSPIterations(TS ts,PetscInt *lits)
5495 {
5496   PetscFunctionBegin;
5497   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
5498   PetscValidIntPointer(lits,2);
5499   *lits = ts->ksp_its;
5500   PetscFunctionReturn(0);
5501 }
5502 
5503 /*@
5504    TSGetStepRejections - Gets the total number of rejected steps.
5505 
5506    Not Collective
5507 
5508    Input Parameter:
5509 .  ts - TS context
5510 
5511    Output Parameter:
5512 .  rejects - number of steps rejected
5513 
5514    Notes:
5515    This counter is reset to zero for each successive call to TSSolve().
5516 
5517    Level: intermediate
5518 
5519 .keywords: TS, get, number
5520 
5521 .seealso:  TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetSNESFailures(), TSSetMaxSNESFailures(), TSSetErrorIfStepFails()
5522 @*/
5523 PetscErrorCode TSGetStepRejections(TS ts,PetscInt *rejects)
5524 {
5525   PetscFunctionBegin;
5526   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
5527   PetscValidIntPointer(rejects,2);
5528   *rejects = ts->reject;
5529   PetscFunctionReturn(0);
5530 }
5531 
5532 /*@
5533    TSGetSNESFailures - Gets the total number of failed SNES solves
5534 
5535    Not Collective
5536 
5537    Input Parameter:
5538 .  ts - TS context
5539 
5540    Output Parameter:
5541 .  fails - number of failed nonlinear solves
5542 
5543    Notes:
5544    This counter is reset to zero for each successive call to TSSolve().
5545 
5546    Level: intermediate
5547 
5548 .keywords: TS, get, number
5549 
5550 .seealso:  TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSSetMaxSNESFailures()
5551 @*/
5552 PetscErrorCode TSGetSNESFailures(TS ts,PetscInt *fails)
5553 {
5554   PetscFunctionBegin;
5555   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
5556   PetscValidIntPointer(fails,2);
5557   *fails = ts->num_snes_failures;
5558   PetscFunctionReturn(0);
5559 }
5560 
5561 /*@
5562    TSSetMaxStepRejections - Sets the maximum number of step rejections before a step fails
5563 
5564    Not Collective
5565 
5566    Input Parameter:
5567 +  ts - TS context
5568 -  rejects - maximum number of rejected steps, pass -1 for unlimited
5569 
5570    Notes:
5571    The counter is reset to zero for each step
5572 
5573    Options Database Key:
5574  .  -ts_max_reject - Maximum number of step rejections before a step fails
5575 
5576    Level: intermediate
5577 
5578 .keywords: TS, set, maximum, number
5579 
5580 .seealso:  TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxSNESFailures(), TSGetStepRejections(), TSGetSNESFailures(), TSSetErrorIfStepFails(), TSGetConvergedReason()
5581 @*/
5582 PetscErrorCode TSSetMaxStepRejections(TS ts,PetscInt rejects)
5583 {
5584   PetscFunctionBegin;
5585   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
5586   ts->max_reject = rejects;
5587   PetscFunctionReturn(0);
5588 }
5589 
5590 /*@
5591    TSSetMaxSNESFailures - Sets the maximum number of failed SNES solves
5592 
5593    Not Collective
5594 
5595    Input Parameter:
5596 +  ts - TS context
5597 -  fails - maximum number of failed nonlinear solves, pass -1 for unlimited
5598 
5599    Notes:
5600    The counter is reset to zero for each successive call to TSSolve().
5601 
5602    Options Database Key:
5603  .  -ts_max_snes_failures - Maximum number of nonlinear solve failures
5604 
5605    Level: intermediate
5606 
5607 .keywords: TS, set, maximum, number
5608 
5609 .seealso:  TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSGetSNESFailures(), SNESGetConvergedReason(), TSGetConvergedReason()
5610 @*/
5611 PetscErrorCode TSSetMaxSNESFailures(TS ts,PetscInt fails)
5612 {
5613   PetscFunctionBegin;
5614   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
5615   ts->max_snes_failures = fails;
5616   PetscFunctionReturn(0);
5617 }
5618 
5619 /*@
5620    TSSetErrorIfStepFails - Error if no step succeeds
5621 
5622    Not Collective
5623 
5624    Input Parameter:
5625 +  ts - TS context
5626 -  err - PETSC_TRUE to error if no step succeeds, PETSC_FALSE to return without failure
5627 
5628    Options Database Key:
5629  .  -ts_error_if_step_fails - Error if no step succeeds
5630 
5631    Level: intermediate
5632 
5633 .keywords: TS, set, error
5634 
5635 .seealso:  TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSGetSNESFailures(), TSSetErrorIfStepFails(), TSGetConvergedReason()
5636 @*/
5637 PetscErrorCode TSSetErrorIfStepFails(TS ts,PetscBool err)
5638 {
5639   PetscFunctionBegin;
5640   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
5641   ts->errorifstepfailed = err;
5642   PetscFunctionReturn(0);
5643 }
5644 
5645 /*@C
5646    TSMonitorSolution - Monitors progress of the TS solvers by VecView() for the solution at each timestep. Normally the viewer is a binary file or a PetscDraw object
5647 
5648    Collective on TS
5649 
5650    Input Parameters:
5651 +  ts - the TS context
5652 .  step - current time-step
5653 .  ptime - current time
5654 .  u - current state
5655 -  vf - viewer and its format
5656 
5657    Level: intermediate
5658 
5659 .keywords: TS,  vector, monitor, view
5660 
5661 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView()
5662 @*/
5663 PetscErrorCode  TSMonitorSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,PetscViewerAndFormat *vf)
5664 {
5665   PetscErrorCode ierr;
5666 
5667   PetscFunctionBegin;
5668   ierr = PetscViewerPushFormat(vf->viewer,vf->format);CHKERRQ(ierr);
5669   ierr = VecView(u,vf->viewer);CHKERRQ(ierr);
5670   ierr = PetscViewerPopFormat(vf->viewer);CHKERRQ(ierr);
5671   PetscFunctionReturn(0);
5672 }
5673 
5674 /*@C
5675    TSMonitorSolutionVTK - Monitors progress of the TS solvers by VecView() for the solution at each timestep.
5676 
5677    Collective on TS
5678 
5679    Input Parameters:
5680 +  ts - the TS context
5681 .  step - current time-step
5682 .  ptime - current time
5683 .  u - current state
5684 -  filenametemplate - string containing a format specifier for the integer time step (e.g. %03D)
5685 
5686    Level: intermediate
5687 
5688    Notes:
5689    The VTK format does not allow writing multiple time steps in the same file, therefore a different file will be written for each time step.
5690    These are named according to the file name template.
5691 
5692    This function is normally passed as an argument to TSMonitorSet() along with TSMonitorSolutionVTKDestroy().
5693 
5694 .keywords: TS,  vector, monitor, view
5695 
5696 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView()
5697 @*/
5698 PetscErrorCode TSMonitorSolutionVTK(TS ts,PetscInt step,PetscReal ptime,Vec u,void *filenametemplate)
5699 {
5700   PetscErrorCode ierr;
5701   char           filename[PETSC_MAX_PATH_LEN];
5702   PetscViewer    viewer;
5703 
5704   PetscFunctionBegin;
5705   if (step < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */
5706   ierr = PetscSNPrintf(filename,sizeof(filename),(const char*)filenametemplate,step);CHKERRQ(ierr);
5707   ierr = PetscViewerVTKOpen(PetscObjectComm((PetscObject)ts),filename,FILE_MODE_WRITE,&viewer);CHKERRQ(ierr);
5708   ierr = VecView(u,viewer);CHKERRQ(ierr);
5709   ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr);
5710   PetscFunctionReturn(0);
5711 }
5712 
5713 /*@C
5714    TSMonitorSolutionVTKDestroy - Destroy context for monitoring
5715 
5716    Collective on TS
5717 
5718    Input Parameters:
5719 .  filenametemplate - string containing a format specifier for the integer time step (e.g. %03D)
5720 
5721    Level: intermediate
5722 
5723    Note:
5724    This function is normally passed to TSMonitorSet() along with TSMonitorSolutionVTK().
5725 
5726 .keywords: TS,  vector, monitor, view
5727 
5728 .seealso: TSMonitorSet(), TSMonitorSolutionVTK()
5729 @*/
5730 PetscErrorCode TSMonitorSolutionVTKDestroy(void *filenametemplate)
5731 {
5732   PetscErrorCode ierr;
5733 
5734   PetscFunctionBegin;
5735   ierr = PetscFree(*(char**)filenametemplate);CHKERRQ(ierr);
5736   PetscFunctionReturn(0);
5737 }
5738 
5739 /*@
5740    TSGetAdapt - Get the adaptive controller context for the current method
5741 
5742    Collective on TS if controller has not been created yet
5743 
5744    Input Arguments:
5745 .  ts - time stepping context
5746 
5747    Output Arguments:
5748 .  adapt - adaptive controller
5749 
5750    Level: intermediate
5751 
5752 .seealso: TSAdapt, TSAdaptSetType(), TSAdaptChoose()
5753 @*/
5754 PetscErrorCode TSGetAdapt(TS ts,TSAdapt *adapt)
5755 {
5756   PetscErrorCode ierr;
5757 
5758   PetscFunctionBegin;
5759   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
5760   PetscValidPointer(adapt,2);
5761   if (!ts->adapt) {
5762     ierr = TSAdaptCreate(PetscObjectComm((PetscObject)ts),&ts->adapt);CHKERRQ(ierr);
5763     ierr = PetscLogObjectParent((PetscObject)ts,(PetscObject)ts->adapt);CHKERRQ(ierr);
5764     ierr = PetscObjectIncrementTabLevel((PetscObject)ts->adapt,(PetscObject)ts,1);CHKERRQ(ierr);
5765   }
5766   *adapt = ts->adapt;
5767   PetscFunctionReturn(0);
5768 }
5769 
5770 /*@
5771    TSSetTolerances - Set tolerances for local truncation error when using adaptive controller
5772 
5773    Logically Collective
5774 
5775    Input Arguments:
5776 +  ts - time integration context
5777 .  atol - scalar absolute tolerances, PETSC_DECIDE to leave current value
5778 .  vatol - vector of absolute tolerances or NULL, used in preference to atol if present
5779 .  rtol - scalar relative tolerances, PETSC_DECIDE to leave current value
5780 -  vrtol - vector of relative tolerances or NULL, used in preference to atol if present
5781 
5782    Options Database keys:
5783 +  -ts_rtol <rtol> - relative tolerance for local truncation error
5784 -  -ts_atol <atol> Absolute tolerance for local truncation error
5785 
5786    Notes:
5787    With PETSc's implicit schemes for DAE problems, the calculation of the local truncation error
5788    (LTE) includes both the differential and the algebraic variables. If one wants the LTE to be
5789    computed only for the differential or the algebraic part then this can be done using the vector of
5790    tolerances vatol. For example, by setting the tolerance vector with the desired tolerance for the
5791    differential part and infinity for the algebraic part, the LTE calculation will include only the
5792    differential variables.
5793 
5794    Level: beginner
5795 
5796 .seealso: TS, TSAdapt, TSVecNormWRMS(), TSGetTolerances()
5797 @*/
5798 PetscErrorCode TSSetTolerances(TS ts,PetscReal atol,Vec vatol,PetscReal rtol,Vec vrtol)
5799 {
5800   PetscErrorCode ierr;
5801 
5802   PetscFunctionBegin;
5803   if (atol != PETSC_DECIDE && atol != PETSC_DEFAULT) ts->atol = atol;
5804   if (vatol) {
5805     ierr = PetscObjectReference((PetscObject)vatol);CHKERRQ(ierr);
5806     ierr = VecDestroy(&ts->vatol);CHKERRQ(ierr);
5807     ts->vatol = vatol;
5808   }
5809   if (rtol != PETSC_DECIDE && rtol != PETSC_DEFAULT) ts->rtol = rtol;
5810   if (vrtol) {
5811     ierr = PetscObjectReference((PetscObject)vrtol);CHKERRQ(ierr);
5812     ierr = VecDestroy(&ts->vrtol);CHKERRQ(ierr);
5813     ts->vrtol = vrtol;
5814   }
5815   PetscFunctionReturn(0);
5816 }
5817 
5818 /*@
5819    TSGetTolerances - Get tolerances for local truncation error when using adaptive controller
5820 
5821    Logically Collective
5822 
5823    Input Arguments:
5824 .  ts - time integration context
5825 
5826    Output Arguments:
5827 +  atol - scalar absolute tolerances, NULL to ignore
5828 .  vatol - vector of absolute tolerances, NULL to ignore
5829 .  rtol - scalar relative tolerances, NULL to ignore
5830 -  vrtol - vector of relative tolerances, NULL to ignore
5831 
5832    Level: beginner
5833 
5834 .seealso: TS, TSAdapt, TSVecNormWRMS(), TSSetTolerances()
5835 @*/
5836 PetscErrorCode TSGetTolerances(TS ts,PetscReal *atol,Vec *vatol,PetscReal *rtol,Vec *vrtol)
5837 {
5838   PetscFunctionBegin;
5839   if (atol)  *atol  = ts->atol;
5840   if (vatol) *vatol = ts->vatol;
5841   if (rtol)  *rtol  = ts->rtol;
5842   if (vrtol) *vrtol = ts->vrtol;
5843   PetscFunctionReturn(0);
5844 }
5845 
5846 /*@
5847    TSErrorWeightedNorm2 - compute a weighted 2-norm of the difference between two state vectors
5848 
5849    Collective on TS
5850 
5851    Input Arguments:
5852 +  ts - time stepping context
5853 .  U - state vector, usually ts->vec_sol
5854 -  Y - state vector to be compared to U
5855 
5856    Output Arguments:
5857 .  norm - weighted norm, a value of 1.0 means that the error matches the tolerances
5858 .  norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances
5859 .  normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances
5860 
5861    Level: developer
5862 
5863 .seealso: TSErrorWeightedNorm(), TSErrorWeightedNormInfinity()
5864 @*/
5865 PetscErrorCode TSErrorWeightedNorm2(TS ts,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr)
5866 {
5867   PetscErrorCode    ierr;
5868   PetscInt          i,n,N,rstart;
5869   PetscInt          n_loc,na_loc,nr_loc;
5870   PetscReal         n_glb,na_glb,nr_glb;
5871   const PetscScalar *u,*y;
5872   PetscReal         sum,suma,sumr,gsum,gsuma,gsumr,diff;
5873   PetscReal         tol,tola,tolr;
5874   PetscReal         err_loc[6],err_glb[6];
5875 
5876   PetscFunctionBegin;
5877   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
5878   PetscValidHeaderSpecific(U,VEC_CLASSID,2);
5879   PetscValidHeaderSpecific(Y,VEC_CLASSID,3);
5880   PetscValidType(U,2);
5881   PetscValidType(Y,3);
5882   PetscCheckSameComm(U,2,Y,3);
5883   PetscValidPointer(norm,4);
5884   PetscValidPointer(norma,5);
5885   PetscValidPointer(normr,6);
5886   if (U == Y) SETERRQ(PetscObjectComm((PetscObject)U),PETSC_ERR_ARG_IDN,"U and Y cannot be the same vector");
5887 
5888   ierr = VecGetSize(U,&N);CHKERRQ(ierr);
5889   ierr = VecGetLocalSize(U,&n);CHKERRQ(ierr);
5890   ierr = VecGetOwnershipRange(U,&rstart,NULL);CHKERRQ(ierr);
5891   ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr);
5892   ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr);
5893   sum  = 0.; n_loc  = 0;
5894   suma = 0.; na_loc = 0;
5895   sumr = 0.; nr_loc = 0;
5896   if (ts->vatol && ts->vrtol) {
5897     const PetscScalar *atol,*rtol;
5898     ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr);
5899     ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr);
5900     for (i=0; i<n; i++) {
5901       diff = PetscAbsScalar(y[i] - u[i]);
5902       tola = PetscRealPart(atol[i]);
5903       if(tola>0.){
5904         suma  += PetscSqr(diff/tola);
5905         na_loc++;
5906       }
5907       tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
5908       if(tolr>0.){
5909         sumr  += PetscSqr(diff/tolr);
5910         nr_loc++;
5911       }
5912       tol=tola+tolr;
5913       if(tol>0.){
5914         sum  += PetscSqr(diff/tol);
5915         n_loc++;
5916       }
5917     }
5918     ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr);
5919     ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr);
5920   } else if (ts->vatol) {       /* vector atol, scalar rtol */
5921     const PetscScalar *atol;
5922     ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr);
5923     for (i=0; i<n; i++) {
5924       diff = PetscAbsScalar(y[i] - u[i]);
5925       tola = PetscRealPart(atol[i]);
5926       if(tola>0.){
5927         suma  += PetscSqr(diff/tola);
5928         na_loc++;
5929       }
5930       tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
5931       if(tolr>0.){
5932         sumr  += PetscSqr(diff/tolr);
5933         nr_loc++;
5934       }
5935       tol=tola+tolr;
5936       if(tol>0.){
5937         sum  += PetscSqr(diff/tol);
5938         n_loc++;
5939       }
5940     }
5941     ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr);
5942   } else if (ts->vrtol) {       /* scalar atol, vector rtol */
5943     const PetscScalar *rtol;
5944     ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr);
5945     for (i=0; i<n; i++) {
5946       diff = PetscAbsScalar(y[i] - u[i]);
5947       tola = ts->atol;
5948       if(tola>0.){
5949         suma  += PetscSqr(diff/tola);
5950         na_loc++;
5951       }
5952       tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
5953       if(tolr>0.){
5954         sumr  += PetscSqr(diff/tolr);
5955         nr_loc++;
5956       }
5957       tol=tola+tolr;
5958       if(tol>0.){
5959         sum  += PetscSqr(diff/tol);
5960         n_loc++;
5961       }
5962     }
5963     ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr);
5964   } else {                      /* scalar atol, scalar rtol */
5965     for (i=0; i<n; i++) {
5966       diff = PetscAbsScalar(y[i] - u[i]);
5967      tola = ts->atol;
5968       if(tola>0.){
5969         suma  += PetscSqr(diff/tola);
5970         na_loc++;
5971       }
5972       tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
5973       if(tolr>0.){
5974         sumr  += PetscSqr(diff/tolr);
5975         nr_loc++;
5976       }
5977       tol=tola+tolr;
5978       if(tol>0.){
5979         sum  += PetscSqr(diff/tol);
5980         n_loc++;
5981       }
5982     }
5983   }
5984   ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr);
5985   ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr);
5986 
5987   err_loc[0] = sum;
5988   err_loc[1] = suma;
5989   err_loc[2] = sumr;
5990   err_loc[3] = (PetscReal)n_loc;
5991   err_loc[4] = (PetscReal)na_loc;
5992   err_loc[5] = (PetscReal)nr_loc;
5993 
5994   ierr = MPIU_Allreduce(err_loc,err_glb,6,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr);
5995 
5996   gsum   = err_glb[0];
5997   gsuma  = err_glb[1];
5998   gsumr  = err_glb[2];
5999   n_glb  = err_glb[3];
6000   na_glb = err_glb[4];
6001   nr_glb = err_glb[5];
6002 
6003   *norm  = 0.;
6004   if(n_glb>0. ){*norm  = PetscSqrtReal(gsum  / n_glb );}
6005   *norma = 0.;
6006   if(na_glb>0.){*norma = PetscSqrtReal(gsuma / na_glb);}
6007   *normr = 0.;
6008   if(nr_glb>0.){*normr = PetscSqrtReal(gsumr / nr_glb);}
6009 
6010   if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm");
6011   if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma");
6012   if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr");
6013   PetscFunctionReturn(0);
6014 }
6015 
6016 /*@
6017    TSErrorWeightedNormInfinity - compute a weighted infinity-norm of the difference between two state vectors
6018 
6019    Collective on TS
6020 
6021    Input Arguments:
6022 +  ts - time stepping context
6023 .  U - state vector, usually ts->vec_sol
6024 -  Y - state vector to be compared to U
6025 
6026    Output Arguments:
6027 .  norm - weighted norm, a value of 1.0 means that the error matches the tolerances
6028 .  norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances
6029 .  normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances
6030 
6031    Level: developer
6032 
6033 .seealso: TSErrorWeightedNorm(), TSErrorWeightedNorm2()
6034 @*/
6035 PetscErrorCode TSErrorWeightedNormInfinity(TS ts,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr)
6036 {
6037   PetscErrorCode    ierr;
6038   PetscInt          i,n,N,rstart;
6039   const PetscScalar *u,*y;
6040   PetscReal         max,gmax,maxa,gmaxa,maxr,gmaxr;
6041   PetscReal         tol,tola,tolr,diff;
6042   PetscReal         err_loc[3],err_glb[3];
6043 
6044   PetscFunctionBegin;
6045   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
6046   PetscValidHeaderSpecific(U,VEC_CLASSID,2);
6047   PetscValidHeaderSpecific(Y,VEC_CLASSID,3);
6048   PetscValidType(U,2);
6049   PetscValidType(Y,3);
6050   PetscCheckSameComm(U,2,Y,3);
6051   PetscValidPointer(norm,4);
6052   PetscValidPointer(norma,5);
6053   PetscValidPointer(normr,6);
6054   if (U == Y) SETERRQ(PetscObjectComm((PetscObject)U),PETSC_ERR_ARG_IDN,"U and Y cannot be the same vector");
6055 
6056   ierr = VecGetSize(U,&N);CHKERRQ(ierr);
6057   ierr = VecGetLocalSize(U,&n);CHKERRQ(ierr);
6058   ierr = VecGetOwnershipRange(U,&rstart,NULL);CHKERRQ(ierr);
6059   ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr);
6060   ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr);
6061 
6062   max=0.;
6063   maxa=0.;
6064   maxr=0.;
6065 
6066   if (ts->vatol && ts->vrtol) {     /* vector atol, vector rtol */
6067     const PetscScalar *atol,*rtol;
6068     ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr);
6069     ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr);
6070 
6071     for (i=0; i<n; i++) {
6072       diff = PetscAbsScalar(y[i] - u[i]);
6073       tola = PetscRealPart(atol[i]);
6074       tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
6075       tol  = tola+tolr;
6076       if(tola>0.){
6077         maxa = PetscMax(maxa,diff / tola);
6078       }
6079       if(tolr>0.){
6080         maxr = PetscMax(maxr,diff / tolr);
6081       }
6082       if(tol>0.){
6083         max = PetscMax(max,diff / tol);
6084       }
6085     }
6086     ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr);
6087     ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr);
6088   } else if (ts->vatol) {       /* vector atol, scalar rtol */
6089     const PetscScalar *atol;
6090     ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr);
6091     for (i=0; i<n; i++) {
6092       diff = PetscAbsScalar(y[i] - u[i]);
6093       tola = PetscRealPart(atol[i]);
6094       tolr = ts->rtol  * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
6095       tol  = tola+tolr;
6096       if(tola>0.){
6097         maxa = PetscMax(maxa,diff / tola);
6098       }
6099       if(tolr>0.){
6100         maxr = PetscMax(maxr,diff / tolr);
6101       }
6102       if(tol>0.){
6103         max = PetscMax(max,diff / tol);
6104       }
6105     }
6106     ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr);
6107   } else if (ts->vrtol) {       /* scalar atol, vector rtol */
6108     const PetscScalar *rtol;
6109     ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr);
6110 
6111     for (i=0; i<n; i++) {
6112       diff = PetscAbsScalar(y[i] - u[i]);
6113       tola = ts->atol;
6114       tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
6115       tol  = tola+tolr;
6116       if(tola>0.){
6117         maxa = PetscMax(maxa,diff / tola);
6118       }
6119       if(tolr>0.){
6120         maxr = PetscMax(maxr,diff / tolr);
6121       }
6122       if(tol>0.){
6123         max = PetscMax(max,diff / tol);
6124       }
6125     }
6126     ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr);
6127   } else {                      /* scalar atol, scalar rtol */
6128 
6129     for (i=0; i<n; i++) {
6130       diff = PetscAbsScalar(y[i] - u[i]);
6131       tola = ts->atol;
6132       tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
6133       tol  = tola+tolr;
6134       if(tola>0.){
6135         maxa = PetscMax(maxa,diff / tola);
6136       }
6137       if(tolr>0.){
6138         maxr = PetscMax(maxr,diff / tolr);
6139       }
6140       if(tol>0.){
6141         max = PetscMax(max,diff / tol);
6142       }
6143     }
6144   }
6145   ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr);
6146   ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr);
6147   err_loc[0] = max;
6148   err_loc[1] = maxa;
6149   err_loc[2] = maxr;
6150   ierr  = MPIU_Allreduce(err_loc,err_glb,3,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr);
6151   gmax   = err_glb[0];
6152   gmaxa  = err_glb[1];
6153   gmaxr  = err_glb[2];
6154 
6155   *norm = gmax;
6156   *norma = gmaxa;
6157   *normr = gmaxr;
6158   if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm");
6159     if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma");
6160     if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr");
6161   PetscFunctionReturn(0);
6162 }
6163 
6164 /*@
6165    TSErrorWeightedNorm - compute a weighted norm of the difference between two state vectors based on supplied absolute and relative tolerances
6166 
6167    Collective on TS
6168 
6169    Input Arguments:
6170 +  ts - time stepping context
6171 .  U - state vector, usually ts->vec_sol
6172 .  Y - state vector to be compared to U
6173 -  wnormtype - norm type, either NORM_2 or NORM_INFINITY
6174 
6175    Output Arguments:
6176 .  norm  - weighted norm, a value of 1.0 achieves a balance between absolute and relative tolerances
6177 .  norma - weighted norm, a value of 1.0 means that the error meets the absolute tolerance set by the user
6178 .  normr - weighted norm, a value of 1.0 means that the error meets the relative tolerance set by the user
6179 
6180    Options Database Keys:
6181 .  -ts_adapt_wnormtype <wnormtype> - 2, INFINITY
6182 
6183    Level: developer
6184 
6185 .seealso: TSErrorWeightedNormInfinity(), TSErrorWeightedNorm2(), TSErrorWeightedENorm
6186 @*/
6187 PetscErrorCode TSErrorWeightedNorm(TS ts,Vec U,Vec Y,NormType wnormtype,PetscReal *norm,PetscReal *norma,PetscReal *normr)
6188 {
6189   PetscErrorCode ierr;
6190 
6191   PetscFunctionBegin;
6192   if (wnormtype == NORM_2) {
6193     ierr = TSErrorWeightedNorm2(ts,U,Y,norm,norma,normr);CHKERRQ(ierr);
6194   } else if(wnormtype == NORM_INFINITY) {
6195     ierr = TSErrorWeightedNormInfinity(ts,U,Y,norm,norma,normr);CHKERRQ(ierr);
6196   } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]);
6197   PetscFunctionReturn(0);
6198 }
6199 
6200 
6201 /*@
6202    TSErrorWeightedENorm2 - compute a weighted 2 error norm based on supplied absolute and relative tolerances
6203 
6204    Collective on TS
6205 
6206    Input Arguments:
6207 +  ts - time stepping context
6208 .  E - error vector
6209 .  U - state vector, usually ts->vec_sol
6210 -  Y - state vector, previous time step
6211 
6212    Output Arguments:
6213 .  norm - weighted norm, a value of 1.0 means that the error matches the tolerances
6214 .  norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances
6215 .  normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances
6216 
6217    Level: developer
6218 
6219 .seealso: TSErrorWeightedENorm(), TSErrorWeightedENormInfinity()
6220 @*/
6221 PetscErrorCode TSErrorWeightedENorm2(TS ts,Vec E,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr)
6222 {
6223   PetscErrorCode    ierr;
6224   PetscInt          i,n,N,rstart;
6225   PetscInt          n_loc,na_loc,nr_loc;
6226   PetscReal         n_glb,na_glb,nr_glb;
6227   const PetscScalar *e,*u,*y;
6228   PetscReal         err,sum,suma,sumr,gsum,gsuma,gsumr;
6229   PetscReal         tol,tola,tolr;
6230   PetscReal         err_loc[6],err_glb[6];
6231 
6232   PetscFunctionBegin;
6233   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
6234   PetscValidHeaderSpecific(E,VEC_CLASSID,2);
6235   PetscValidHeaderSpecific(U,VEC_CLASSID,3);
6236   PetscValidHeaderSpecific(Y,VEC_CLASSID,4);
6237   PetscValidType(E,2);
6238   PetscValidType(U,3);
6239   PetscValidType(Y,4);
6240   PetscCheckSameComm(E,2,U,3);
6241   PetscCheckSameComm(U,2,Y,3);
6242   PetscValidPointer(norm,5);
6243   PetscValidPointer(norma,6);
6244   PetscValidPointer(normr,7);
6245 
6246   ierr = VecGetSize(E,&N);CHKERRQ(ierr);
6247   ierr = VecGetLocalSize(E,&n);CHKERRQ(ierr);
6248   ierr = VecGetOwnershipRange(E,&rstart,NULL);CHKERRQ(ierr);
6249   ierr = VecGetArrayRead(E,&e);CHKERRQ(ierr);
6250   ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr);
6251   ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr);
6252   sum  = 0.; n_loc  = 0;
6253   suma = 0.; na_loc = 0;
6254   sumr = 0.; nr_loc = 0;
6255   if (ts->vatol && ts->vrtol) {
6256     const PetscScalar *atol,*rtol;
6257     ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr);
6258     ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr);
6259     for (i=0; i<n; i++) {
6260       err = PetscAbsScalar(e[i]);
6261       tola = PetscRealPart(atol[i]);
6262       if(tola>0.){
6263         suma  += PetscSqr(err/tola);
6264         na_loc++;
6265       }
6266       tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
6267       if(tolr>0.){
6268         sumr  += PetscSqr(err/tolr);
6269         nr_loc++;
6270       }
6271       tol=tola+tolr;
6272       if(tol>0.){
6273         sum  += PetscSqr(err/tol);
6274         n_loc++;
6275       }
6276     }
6277     ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr);
6278     ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr);
6279   } else if (ts->vatol) {       /* vector atol, scalar rtol */
6280     const PetscScalar *atol;
6281     ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr);
6282     for (i=0; i<n; i++) {
6283       err = PetscAbsScalar(e[i]);
6284       tola = PetscRealPart(atol[i]);
6285       if(tola>0.){
6286         suma  += PetscSqr(err/tola);
6287         na_loc++;
6288       }
6289       tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
6290       if(tolr>0.){
6291         sumr  += PetscSqr(err/tolr);
6292         nr_loc++;
6293       }
6294       tol=tola+tolr;
6295       if(tol>0.){
6296         sum  += PetscSqr(err/tol);
6297         n_loc++;
6298       }
6299     }
6300     ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr);
6301   } else if (ts->vrtol) {       /* scalar atol, vector rtol */
6302     const PetscScalar *rtol;
6303     ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr);
6304     for (i=0; i<n; i++) {
6305       err = PetscAbsScalar(e[i]);
6306       tola = ts->atol;
6307       if(tola>0.){
6308         suma  += PetscSqr(err/tola);
6309         na_loc++;
6310       }
6311       tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
6312       if(tolr>0.){
6313         sumr  += PetscSqr(err/tolr);
6314         nr_loc++;
6315       }
6316       tol=tola+tolr;
6317       if(tol>0.){
6318         sum  += PetscSqr(err/tol);
6319         n_loc++;
6320       }
6321     }
6322     ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr);
6323   } else {                      /* scalar atol, scalar rtol */
6324     for (i=0; i<n; i++) {
6325       err = PetscAbsScalar(e[i]);
6326      tola = ts->atol;
6327       if(tola>0.){
6328         suma  += PetscSqr(err/tola);
6329         na_loc++;
6330       }
6331       tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
6332       if(tolr>0.){
6333         sumr  += PetscSqr(err/tolr);
6334         nr_loc++;
6335       }
6336       tol=tola+tolr;
6337       if(tol>0.){
6338         sum  += PetscSqr(err/tol);
6339         n_loc++;
6340       }
6341     }
6342   }
6343   ierr = VecRestoreArrayRead(E,&e);CHKERRQ(ierr);
6344   ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr);
6345   ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr);
6346 
6347   err_loc[0] = sum;
6348   err_loc[1] = suma;
6349   err_loc[2] = sumr;
6350   err_loc[3] = (PetscReal)n_loc;
6351   err_loc[4] = (PetscReal)na_loc;
6352   err_loc[5] = (PetscReal)nr_loc;
6353 
6354   ierr = MPIU_Allreduce(err_loc,err_glb,6,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr);
6355 
6356   gsum   = err_glb[0];
6357   gsuma  = err_glb[1];
6358   gsumr  = err_glb[2];
6359   n_glb  = err_glb[3];
6360   na_glb = err_glb[4];
6361   nr_glb = err_glb[5];
6362 
6363   *norm  = 0.;
6364   if(n_glb>0. ){*norm  = PetscSqrtReal(gsum  / n_glb );}
6365   *norma = 0.;
6366   if(na_glb>0.){*norma = PetscSqrtReal(gsuma / na_glb);}
6367   *normr = 0.;
6368   if(nr_glb>0.){*normr = PetscSqrtReal(gsumr / nr_glb);}
6369 
6370   if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm");
6371   if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma");
6372   if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr");
6373   PetscFunctionReturn(0);
6374 }
6375 
6376 /*@
6377    TSErrorWeightedENormInfinity - compute a weighted infinity error norm based on supplied absolute and relative tolerances
6378    Collective on TS
6379 
6380    Input Arguments:
6381 +  ts - time stepping context
6382 .  E - error vector
6383 .  U - state vector, usually ts->vec_sol
6384 -  Y - state vector, previous time step
6385 
6386    Output Arguments:
6387 .  norm - weighted norm, a value of 1.0 means that the error matches the tolerances
6388 .  norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances
6389 .  normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances
6390 
6391    Level: developer
6392 
6393 .seealso: TSErrorWeightedENorm(), TSErrorWeightedENorm2()
6394 @*/
6395 PetscErrorCode TSErrorWeightedENormInfinity(TS ts,Vec E,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr)
6396 {
6397   PetscErrorCode    ierr;
6398   PetscInt          i,n,N,rstart;
6399   const PetscScalar *e,*u,*y;
6400   PetscReal         err,max,gmax,maxa,gmaxa,maxr,gmaxr;
6401   PetscReal         tol,tola,tolr;
6402   PetscReal         err_loc[3],err_glb[3];
6403 
6404   PetscFunctionBegin;
6405   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
6406   PetscValidHeaderSpecific(E,VEC_CLASSID,2);
6407   PetscValidHeaderSpecific(U,VEC_CLASSID,3);
6408   PetscValidHeaderSpecific(Y,VEC_CLASSID,4);
6409   PetscValidType(E,2);
6410   PetscValidType(U,3);
6411   PetscValidType(Y,4);
6412   PetscCheckSameComm(E,2,U,3);
6413   PetscCheckSameComm(U,2,Y,3);
6414   PetscValidPointer(norm,5);
6415   PetscValidPointer(norma,6);
6416   PetscValidPointer(normr,7);
6417 
6418   ierr = VecGetSize(E,&N);CHKERRQ(ierr);
6419   ierr = VecGetLocalSize(E,&n);CHKERRQ(ierr);
6420   ierr = VecGetOwnershipRange(E,&rstart,NULL);CHKERRQ(ierr);
6421   ierr = VecGetArrayRead(E,&e);CHKERRQ(ierr);
6422   ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr);
6423   ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr);
6424 
6425   max=0.;
6426   maxa=0.;
6427   maxr=0.;
6428 
6429   if (ts->vatol && ts->vrtol) {     /* vector atol, vector rtol */
6430     const PetscScalar *atol,*rtol;
6431     ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr);
6432     ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr);
6433 
6434     for (i=0; i<n; i++) {
6435       err = PetscAbsScalar(e[i]);
6436       tola = PetscRealPart(atol[i]);
6437       tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
6438       tol  = tola+tolr;
6439       if(tola>0.){
6440         maxa = PetscMax(maxa,err / tola);
6441       }
6442       if(tolr>0.){
6443         maxr = PetscMax(maxr,err / tolr);
6444       }
6445       if(tol>0.){
6446         max = PetscMax(max,err / tol);
6447       }
6448     }
6449     ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr);
6450     ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr);
6451   } else if (ts->vatol) {       /* vector atol, scalar rtol */
6452     const PetscScalar *atol;
6453     ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr);
6454     for (i=0; i<n; i++) {
6455       err = PetscAbsScalar(e[i]);
6456       tola = PetscRealPart(atol[i]);
6457       tolr = ts->rtol  * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
6458       tol  = tola+tolr;
6459       if(tola>0.){
6460         maxa = PetscMax(maxa,err / tola);
6461       }
6462       if(tolr>0.){
6463         maxr = PetscMax(maxr,err / tolr);
6464       }
6465       if(tol>0.){
6466         max = PetscMax(max,err / tol);
6467       }
6468     }
6469     ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr);
6470   } else if (ts->vrtol) {       /* scalar atol, vector rtol */
6471     const PetscScalar *rtol;
6472     ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr);
6473 
6474     for (i=0; i<n; i++) {
6475       err = PetscAbsScalar(e[i]);
6476       tola = ts->atol;
6477       tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
6478       tol  = tola+tolr;
6479       if(tola>0.){
6480         maxa = PetscMax(maxa,err / tola);
6481       }
6482       if(tolr>0.){
6483         maxr = PetscMax(maxr,err / tolr);
6484       }
6485       if(tol>0.){
6486         max = PetscMax(max,err / tol);
6487       }
6488     }
6489     ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr);
6490   } else {                      /* scalar atol, scalar rtol */
6491 
6492     for (i=0; i<n; i++) {
6493       err = PetscAbsScalar(e[i]);
6494       tola = ts->atol;
6495       tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i]));
6496       tol  = tola+tolr;
6497       if(tola>0.){
6498         maxa = PetscMax(maxa,err / tola);
6499       }
6500       if(tolr>0.){
6501         maxr = PetscMax(maxr,err / tolr);
6502       }
6503       if(tol>0.){
6504         max = PetscMax(max,err / tol);
6505       }
6506     }
6507   }
6508   ierr = VecRestoreArrayRead(E,&e);CHKERRQ(ierr);
6509   ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr);
6510   ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr);
6511   err_loc[0] = max;
6512   err_loc[1] = maxa;
6513   err_loc[2] = maxr;
6514   ierr  = MPIU_Allreduce(err_loc,err_glb,3,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr);
6515   gmax   = err_glb[0];
6516   gmaxa  = err_glb[1];
6517   gmaxr  = err_glb[2];
6518 
6519   *norm = gmax;
6520   *norma = gmaxa;
6521   *normr = gmaxr;
6522   if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm");
6523     if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma");
6524     if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr");
6525   PetscFunctionReturn(0);
6526 }
6527 
6528 /*@
6529    TSErrorWeightedENorm - compute a weighted error norm based on supplied absolute and relative tolerances
6530 
6531    Collective on TS
6532 
6533    Input Arguments:
6534 +  ts - time stepping context
6535 .  E - error vector
6536 .  U - state vector, usually ts->vec_sol
6537 .  Y - state vector, previous time step
6538 -  wnormtype - norm type, either NORM_2 or NORM_INFINITY
6539 
6540    Output Arguments:
6541 .  norm  - weighted norm, a value of 1.0 achieves a balance between absolute and relative tolerances
6542 .  norma - weighted norm, a value of 1.0 means that the error meets the absolute tolerance set by the user
6543 .  normr - weighted norm, a value of 1.0 means that the error meets the relative tolerance set by the user
6544 
6545    Options Database Keys:
6546 .  -ts_adapt_wnormtype <wnormtype> - 2, INFINITY
6547 
6548    Level: developer
6549 
6550 .seealso: TSErrorWeightedENormInfinity(), TSErrorWeightedENorm2(), TSErrorWeightedNormInfinity(), TSErrorWeightedNorm2()
6551 @*/
6552 PetscErrorCode TSErrorWeightedENorm(TS ts,Vec E,Vec U,Vec Y,NormType wnormtype,PetscReal *norm,PetscReal *norma,PetscReal *normr)
6553 {
6554   PetscErrorCode ierr;
6555 
6556   PetscFunctionBegin;
6557   if (wnormtype == NORM_2) {
6558     ierr = TSErrorWeightedENorm2(ts,E,U,Y,norm,norma,normr);CHKERRQ(ierr);
6559   } else if(wnormtype == NORM_INFINITY) {
6560     ierr = TSErrorWeightedENormInfinity(ts,E,U,Y,norm,norma,normr);CHKERRQ(ierr);
6561   } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]);
6562   PetscFunctionReturn(0);
6563 }
6564 
6565 
6566 /*@
6567    TSSetCFLTimeLocal - Set the local CFL constraint relative to forward Euler
6568 
6569    Logically Collective on TS
6570 
6571    Input Arguments:
6572 +  ts - time stepping context
6573 -  cfltime - maximum stable time step if using forward Euler (value can be different on each process)
6574 
6575    Note:
6576    After calling this function, the global CFL time can be obtained by calling TSGetCFLTime()
6577 
6578    Level: intermediate
6579 
6580 .seealso: TSGetCFLTime(), TSADAPTCFL
6581 @*/
6582 PetscErrorCode TSSetCFLTimeLocal(TS ts,PetscReal cfltime)
6583 {
6584   PetscFunctionBegin;
6585   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
6586   ts->cfltime_local = cfltime;
6587   ts->cfltime       = -1.;
6588   PetscFunctionReturn(0);
6589 }
6590 
6591 /*@
6592    TSGetCFLTime - Get the maximum stable time step according to CFL criteria applied to forward Euler
6593 
6594    Collective on TS
6595 
6596    Input Arguments:
6597 .  ts - time stepping context
6598 
6599    Output Arguments:
6600 .  cfltime - maximum stable time step for forward Euler
6601 
6602    Level: advanced
6603 
6604 .seealso: TSSetCFLTimeLocal()
6605 @*/
6606 PetscErrorCode TSGetCFLTime(TS ts,PetscReal *cfltime)
6607 {
6608   PetscErrorCode ierr;
6609 
6610   PetscFunctionBegin;
6611   if (ts->cfltime < 0) {
6612     ierr = MPIU_Allreduce(&ts->cfltime_local,&ts->cfltime,1,MPIU_REAL,MPIU_MIN,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr);
6613   }
6614   *cfltime = ts->cfltime;
6615   PetscFunctionReturn(0);
6616 }
6617 
6618 /*@
6619    TSVISetVariableBounds - Sets the lower and upper bounds for the solution vector. xl <= x <= xu
6620 
6621    Input Parameters:
6622 .  ts   - the TS context.
6623 .  xl   - lower bound.
6624 .  xu   - upper bound.
6625 
6626    Notes:
6627    If this routine is not called then the lower and upper bounds are set to
6628    PETSC_NINFINITY and PETSC_INFINITY respectively during SNESSetUp().
6629 
6630    Level: advanced
6631 
6632 @*/
6633 PetscErrorCode TSVISetVariableBounds(TS ts, Vec xl, Vec xu)
6634 {
6635   PetscErrorCode ierr;
6636   SNES           snes;
6637 
6638   PetscFunctionBegin;
6639   ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr);
6640   ierr = SNESVISetVariableBounds(snes,xl,xu);CHKERRQ(ierr);
6641   PetscFunctionReturn(0);
6642 }
6643 
6644 #if defined(PETSC_HAVE_MATLAB_ENGINE)
6645 #include <mex.h>
6646 
6647 typedef struct {char *funcname; mxArray *ctx;} TSMatlabContext;
6648 
6649 /*
6650    TSComputeFunction_Matlab - Calls the function that has been set with
6651                          TSSetFunctionMatlab().
6652 
6653    Collective on TS
6654 
6655    Input Parameters:
6656 +  snes - the TS context
6657 -  u - input vector
6658 
6659    Output Parameter:
6660 .  y - function vector, as set by TSSetFunction()
6661 
6662    Notes:
6663    TSComputeFunction() is typically used within nonlinear solvers
6664    implementations, so most users would not generally call this routine
6665    themselves.
6666 
6667    Level: developer
6668 
6669 .keywords: TS, nonlinear, compute, function
6670 
6671 .seealso: TSSetFunction(), TSGetFunction()
6672 */
6673 PetscErrorCode  TSComputeFunction_Matlab(TS snes,PetscReal time,Vec u,Vec udot,Vec y, void *ctx)
6674 {
6675   PetscErrorCode  ierr;
6676   TSMatlabContext *sctx = (TSMatlabContext*)ctx;
6677   int             nlhs  = 1,nrhs = 7;
6678   mxArray         *plhs[1],*prhs[7];
6679   long long int   lx = 0,lxdot = 0,ly = 0,ls = 0;
6680 
6681   PetscFunctionBegin;
6682   PetscValidHeaderSpecific(snes,TS_CLASSID,1);
6683   PetscValidHeaderSpecific(u,VEC_CLASSID,3);
6684   PetscValidHeaderSpecific(udot,VEC_CLASSID,4);
6685   PetscValidHeaderSpecific(y,VEC_CLASSID,5);
6686   PetscCheckSameComm(snes,1,u,3);
6687   PetscCheckSameComm(snes,1,y,5);
6688 
6689   ierr = PetscMemcpy(&ls,&snes,sizeof(snes));CHKERRQ(ierr);
6690   ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr);
6691   ierr = PetscMemcpy(&lxdot,&udot,sizeof(udot));CHKERRQ(ierr);
6692   ierr = PetscMemcpy(&ly,&y,sizeof(u));CHKERRQ(ierr);
6693 
6694   prhs[0] =  mxCreateDoubleScalar((double)ls);
6695   prhs[1] =  mxCreateDoubleScalar(time);
6696   prhs[2] =  mxCreateDoubleScalar((double)lx);
6697   prhs[3] =  mxCreateDoubleScalar((double)lxdot);
6698   prhs[4] =  mxCreateDoubleScalar((double)ly);
6699   prhs[5] =  mxCreateString(sctx->funcname);
6700   prhs[6] =  sctx->ctx;
6701   ierr    =  mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSComputeFunctionInternal");CHKERRQ(ierr);
6702   ierr    =  mxGetScalar(plhs[0]);CHKERRQ(ierr);
6703   mxDestroyArray(prhs[0]);
6704   mxDestroyArray(prhs[1]);
6705   mxDestroyArray(prhs[2]);
6706   mxDestroyArray(prhs[3]);
6707   mxDestroyArray(prhs[4]);
6708   mxDestroyArray(prhs[5]);
6709   mxDestroyArray(plhs[0]);
6710   PetscFunctionReturn(0);
6711 }
6712 
6713 
6714 /*
6715    TSSetFunctionMatlab - Sets the function evaluation routine and function
6716    vector for use by the TS routines in solving ODEs
6717    equations from MATLAB. Here the function is a string containing the name of a MATLAB function
6718 
6719    Logically Collective on TS
6720 
6721    Input Parameters:
6722 +  ts - the TS context
6723 -  func - function evaluation routine
6724 
6725    Calling sequence of func:
6726 $    func (TS ts,PetscReal time,Vec u,Vec udot,Vec f,void *ctx);
6727 
6728    Level: beginner
6729 
6730 .keywords: TS, nonlinear, set, function
6731 
6732 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction()
6733 */
6734 PetscErrorCode  TSSetFunctionMatlab(TS ts,const char *func,mxArray *ctx)
6735 {
6736   PetscErrorCode  ierr;
6737   TSMatlabContext *sctx;
6738 
6739   PetscFunctionBegin;
6740   /* currently sctx is memory bleed */
6741   ierr = PetscNew(&sctx);CHKERRQ(ierr);
6742   ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr);
6743   /*
6744      This should work, but it doesn't
6745   sctx->ctx = ctx;
6746   mexMakeArrayPersistent(sctx->ctx);
6747   */
6748   sctx->ctx = mxDuplicateArray(ctx);
6749 
6750   ierr = TSSetIFunction(ts,NULL,TSComputeFunction_Matlab,sctx);CHKERRQ(ierr);
6751   PetscFunctionReturn(0);
6752 }
6753 
6754 /*
6755    TSComputeJacobian_Matlab - Calls the function that has been set with
6756                          TSSetJacobianMatlab().
6757 
6758    Collective on TS
6759 
6760    Input Parameters:
6761 +  ts - the TS context
6762 .  u - input vector
6763 .  A, B - the matrices
6764 -  ctx - user context
6765 
6766    Level: developer
6767 
6768 .keywords: TS, nonlinear, compute, function
6769 
6770 .seealso: TSSetFunction(), TSGetFunction()
6771 @*/
6772 PetscErrorCode  TSComputeJacobian_Matlab(TS ts,PetscReal time,Vec u,Vec udot,PetscReal shift,Mat A,Mat B,void *ctx)
6773 {
6774   PetscErrorCode  ierr;
6775   TSMatlabContext *sctx = (TSMatlabContext*)ctx;
6776   int             nlhs  = 2,nrhs = 9;
6777   mxArray         *plhs[2],*prhs[9];
6778   long long int   lx = 0,lxdot = 0,lA = 0,ls = 0, lB = 0;
6779 
6780   PetscFunctionBegin;
6781   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
6782   PetscValidHeaderSpecific(u,VEC_CLASSID,3);
6783 
6784   /* call Matlab function in ctx with arguments u and y */
6785 
6786   ierr = PetscMemcpy(&ls,&ts,sizeof(ts));CHKERRQ(ierr);
6787   ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr);
6788   ierr = PetscMemcpy(&lxdot,&udot,sizeof(u));CHKERRQ(ierr);
6789   ierr = PetscMemcpy(&lA,A,sizeof(u));CHKERRQ(ierr);
6790   ierr = PetscMemcpy(&lB,B,sizeof(u));CHKERRQ(ierr);
6791 
6792   prhs[0] =  mxCreateDoubleScalar((double)ls);
6793   prhs[1] =  mxCreateDoubleScalar((double)time);
6794   prhs[2] =  mxCreateDoubleScalar((double)lx);
6795   prhs[3] =  mxCreateDoubleScalar((double)lxdot);
6796   prhs[4] =  mxCreateDoubleScalar((double)shift);
6797   prhs[5] =  mxCreateDoubleScalar((double)lA);
6798   prhs[6] =  mxCreateDoubleScalar((double)lB);
6799   prhs[7] =  mxCreateString(sctx->funcname);
6800   prhs[8] =  sctx->ctx;
6801   ierr    =  mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSComputeJacobianInternal");CHKERRQ(ierr);
6802   ierr    =  mxGetScalar(plhs[0]);CHKERRQ(ierr);
6803   mxDestroyArray(prhs[0]);
6804   mxDestroyArray(prhs[1]);
6805   mxDestroyArray(prhs[2]);
6806   mxDestroyArray(prhs[3]);
6807   mxDestroyArray(prhs[4]);
6808   mxDestroyArray(prhs[5]);
6809   mxDestroyArray(prhs[6]);
6810   mxDestroyArray(prhs[7]);
6811   mxDestroyArray(plhs[0]);
6812   mxDestroyArray(plhs[1]);
6813   PetscFunctionReturn(0);
6814 }
6815 
6816 
6817 /*
6818    TSSetJacobianMatlab - Sets the Jacobian function evaluation routine and two empty Jacobian matrices
6819    vector for use by the TS routines in solving ODEs from MATLAB. Here the function is a string containing the name of a MATLAB function
6820 
6821    Logically Collective on TS
6822 
6823    Input Parameters:
6824 +  ts - the TS context
6825 .  A,B - Jacobian matrices
6826 .  func - function evaluation routine
6827 -  ctx - user context
6828 
6829    Calling sequence of func:
6830 $    flag = func (TS ts,PetscReal time,Vec u,Vec udot,Mat A,Mat B,void *ctx);
6831 
6832 
6833    Level: developer
6834 
6835 .keywords: TS, nonlinear, set, function
6836 
6837 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction()
6838 */
6839 PetscErrorCode  TSSetJacobianMatlab(TS ts,Mat A,Mat B,const char *func,mxArray *ctx)
6840 {
6841   PetscErrorCode  ierr;
6842   TSMatlabContext *sctx;
6843 
6844   PetscFunctionBegin;
6845   /* currently sctx is memory bleed */
6846   ierr = PetscNew(&sctx);CHKERRQ(ierr);
6847   ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr);
6848   /*
6849      This should work, but it doesn't
6850   sctx->ctx = ctx;
6851   mexMakeArrayPersistent(sctx->ctx);
6852   */
6853   sctx->ctx = mxDuplicateArray(ctx);
6854 
6855   ierr = TSSetIJacobian(ts,A,B,TSComputeJacobian_Matlab,sctx);CHKERRQ(ierr);
6856   PetscFunctionReturn(0);
6857 }
6858 
6859 /*
6860    TSMonitor_Matlab - Calls the function that has been set with TSMonitorSetMatlab().
6861 
6862    Collective on TS
6863 
6864 .seealso: TSSetFunction(), TSGetFunction()
6865 @*/
6866 PetscErrorCode  TSMonitor_Matlab(TS ts,PetscInt it, PetscReal time,Vec u, void *ctx)
6867 {
6868   PetscErrorCode  ierr;
6869   TSMatlabContext *sctx = (TSMatlabContext*)ctx;
6870   int             nlhs  = 1,nrhs = 6;
6871   mxArray         *plhs[1],*prhs[6];
6872   long long int   lx = 0,ls = 0;
6873 
6874   PetscFunctionBegin;
6875   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
6876   PetscValidHeaderSpecific(u,VEC_CLASSID,4);
6877 
6878   ierr = PetscMemcpy(&ls,&ts,sizeof(ts));CHKERRQ(ierr);
6879   ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr);
6880 
6881   prhs[0] =  mxCreateDoubleScalar((double)ls);
6882   prhs[1] =  mxCreateDoubleScalar((double)it);
6883   prhs[2] =  mxCreateDoubleScalar((double)time);
6884   prhs[3] =  mxCreateDoubleScalar((double)lx);
6885   prhs[4] =  mxCreateString(sctx->funcname);
6886   prhs[5] =  sctx->ctx;
6887   ierr    =  mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSMonitorInternal");CHKERRQ(ierr);
6888   ierr    =  mxGetScalar(plhs[0]);CHKERRQ(ierr);
6889   mxDestroyArray(prhs[0]);
6890   mxDestroyArray(prhs[1]);
6891   mxDestroyArray(prhs[2]);
6892   mxDestroyArray(prhs[3]);
6893   mxDestroyArray(prhs[4]);
6894   mxDestroyArray(plhs[0]);
6895   PetscFunctionReturn(0);
6896 }
6897 
6898 
6899 /*
6900    TSMonitorSetMatlab - Sets the monitor function from Matlab
6901 
6902    Level: developer
6903 
6904 .keywords: TS, nonlinear, set, function
6905 
6906 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction()
6907 */
6908 PetscErrorCode  TSMonitorSetMatlab(TS ts,const char *func,mxArray *ctx)
6909 {
6910   PetscErrorCode  ierr;
6911   TSMatlabContext *sctx;
6912 
6913   PetscFunctionBegin;
6914   /* currently sctx is memory bleed */
6915   ierr = PetscNew(&sctx);CHKERRQ(ierr);
6916   ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr);
6917   /*
6918      This should work, but it doesn't
6919   sctx->ctx = ctx;
6920   mexMakeArrayPersistent(sctx->ctx);
6921   */
6922   sctx->ctx = mxDuplicateArray(ctx);
6923 
6924   ierr = TSMonitorSet(ts,TSMonitor_Matlab,sctx,NULL);CHKERRQ(ierr);
6925   PetscFunctionReturn(0);
6926 }
6927 #endif
6928 
6929 /*@C
6930    TSMonitorLGSolution - Monitors progress of the TS solvers by plotting each component of the solution vector
6931        in a time based line graph
6932 
6933    Collective on TS
6934 
6935    Input Parameters:
6936 +  ts - the TS context
6937 .  step - current time-step
6938 .  ptime - current time
6939 .  u - current solution
6940 -  dctx - the TSMonitorLGCtx object that contains all the options for the monitoring, this is created with TSMonitorLGCtxCreate()
6941 
6942    Options Database:
6943 .   -ts_monitor_lg_solution_variables
6944 
6945    Level: intermediate
6946 
6947    Notes: Each process in a parallel run displays its component solutions in a separate window
6948 
6949 .keywords: TS,  vector, monitor, view
6950 
6951 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGCtxCreate(), TSMonitorLGCtxSetVariableNames(), TSMonitorLGCtxGetVariableNames(),
6952            TSMonitorLGSetVariableNames(), TSMonitorLGGetVariableNames(), TSMonitorLGSetDisplayVariables(), TSMonitorLGCtxSetDisplayVariables(),
6953            TSMonitorLGCtxSetTransform(), TSMonitorLGSetTransform(), TSMonitorLGError(), TSMonitorLGSNESIterations(), TSMonitorLGKSPIterations(),
6954            TSMonitorEnvelopeCtxCreate(), TSMonitorEnvelopeGetBounds(), TSMonitorEnvelopeCtxDestroy(), TSMonitorEnvelop()
6955 @*/
6956 PetscErrorCode  TSMonitorLGSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dctx)
6957 {
6958   PetscErrorCode    ierr;
6959   TSMonitorLGCtx    ctx = (TSMonitorLGCtx)dctx;
6960   const PetscScalar *yy;
6961   Vec               v;
6962 
6963   PetscFunctionBegin;
6964   if (step < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */
6965   if (!step) {
6966     PetscDrawAxis axis;
6967     PetscInt      dim;
6968     ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr);
6969     ierr = PetscDrawAxisSetLabels(axis,"Solution as function of time","Time","Solution");CHKERRQ(ierr);
6970     if (!ctx->names) {
6971       PetscBool flg;
6972       /* user provides names of variables to plot but no names has been set so assume names are integer values */
6973       ierr = PetscOptionsHasName(((PetscObject)ts)->options,((PetscObject)ts)->prefix,"-ts_monitor_lg_solution_variables",&flg);CHKERRQ(ierr);
6974       if (flg) {
6975         PetscInt i,n;
6976         char     **names;
6977         ierr = VecGetSize(u,&n);CHKERRQ(ierr);
6978         ierr = PetscMalloc1(n+1,&names);CHKERRQ(ierr);
6979         for (i=0; i<n; i++) {
6980           ierr = PetscMalloc1(5,&names[i]);CHKERRQ(ierr);
6981           ierr = PetscSNPrintf(names[i],5,"%D",i);CHKERRQ(ierr);
6982         }
6983         names[n] = NULL;
6984         ctx->names = names;
6985       }
6986     }
6987     if (ctx->names && !ctx->displaynames) {
6988       char      **displaynames;
6989       PetscBool flg;
6990       ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr);
6991       ierr = PetscMalloc1(dim+1,&displaynames);CHKERRQ(ierr);
6992       ierr = PetscMemzero(displaynames,(dim+1)*sizeof(char*));CHKERRQ(ierr);
6993       ierr = PetscOptionsGetStringArray(((PetscObject)ts)->options,((PetscObject)ts)->prefix,"-ts_monitor_lg_solution_variables",displaynames,&dim,&flg);CHKERRQ(ierr);
6994       if (flg) {
6995         ierr = TSMonitorLGCtxSetDisplayVariables(ctx,(const char *const *)displaynames);CHKERRQ(ierr);
6996       }
6997       ierr = PetscStrArrayDestroy(&displaynames);CHKERRQ(ierr);
6998     }
6999     if (ctx->displaynames) {
7000       ierr = PetscDrawLGSetDimension(ctx->lg,ctx->ndisplayvariables);CHKERRQ(ierr);
7001       ierr = PetscDrawLGSetLegend(ctx->lg,(const char *const *)ctx->displaynames);CHKERRQ(ierr);
7002     } else if (ctx->names) {
7003       ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr);
7004       ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr);
7005       ierr = PetscDrawLGSetLegend(ctx->lg,(const char *const *)ctx->names);CHKERRQ(ierr);
7006     } else {
7007       ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr);
7008       ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr);
7009     }
7010     ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr);
7011   }
7012 
7013   if (!ctx->transform) v = u;
7014   else {ierr = (*ctx->transform)(ctx->transformctx,u,&v);CHKERRQ(ierr);}
7015   ierr = VecGetArrayRead(v,&yy);CHKERRQ(ierr);
7016   if (ctx->displaynames) {
7017     PetscInt i;
7018     for (i=0; i<ctx->ndisplayvariables; i++)
7019       ctx->displayvalues[i] = PetscRealPart(yy[ctx->displayvariables[i]]);
7020     ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,ctx->displayvalues);CHKERRQ(ierr);
7021   } else {
7022 #if defined(PETSC_USE_COMPLEX)
7023     PetscInt  i,n;
7024     PetscReal *yreal;
7025     ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr);
7026     ierr = PetscMalloc1(n,&yreal);CHKERRQ(ierr);
7027     for (i=0; i<n; i++) yreal[i] = PetscRealPart(yy[i]);
7028     ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yreal);CHKERRQ(ierr);
7029     ierr = PetscFree(yreal);CHKERRQ(ierr);
7030 #else
7031     ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yy);CHKERRQ(ierr);
7032 #endif
7033   }
7034   ierr = VecRestoreArrayRead(v,&yy);CHKERRQ(ierr);
7035   if (ctx->transform) {ierr = VecDestroy(&v);CHKERRQ(ierr);}
7036 
7037   if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) {
7038     ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr);
7039     ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr);
7040   }
7041   PetscFunctionReturn(0);
7042 }
7043 
7044 
7045 /*@C
7046    TSMonitorLGSetVariableNames - Sets the name of each component in the solution vector so that it may be displayed in the plot
7047 
7048    Collective on TS
7049 
7050    Input Parameters:
7051 +  ts - the TS context
7052 -  names - the names of the components, final string must be NULL
7053 
7054    Level: intermediate
7055 
7056    Notes: If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored
7057 
7058 .keywords: TS,  vector, monitor, view
7059 
7060 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables(), TSMonitorLGCtxSetVariableNames()
7061 @*/
7062 PetscErrorCode  TSMonitorLGSetVariableNames(TS ts,const char * const *names)
7063 {
7064   PetscErrorCode    ierr;
7065   PetscInt          i;
7066 
7067   PetscFunctionBegin;
7068   for (i=0; i<ts->numbermonitors; i++) {
7069     if (ts->monitor[i] == TSMonitorLGSolution) {
7070       ierr = TSMonitorLGCtxSetVariableNames((TSMonitorLGCtx)ts->monitorcontext[i],names);CHKERRQ(ierr);
7071       break;
7072     }
7073   }
7074   PetscFunctionReturn(0);
7075 }
7076 
7077 /*@C
7078    TSMonitorLGCtxSetVariableNames - Sets the name of each component in the solution vector so that it may be displayed in the plot
7079 
7080    Collective on TS
7081 
7082    Input Parameters:
7083 +  ts - the TS context
7084 -  names - the names of the components, final string must be NULL
7085 
7086    Level: intermediate
7087 
7088 .keywords: TS,  vector, monitor, view
7089 
7090 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables(), TSMonitorLGSetVariableNames()
7091 @*/
7092 PetscErrorCode  TSMonitorLGCtxSetVariableNames(TSMonitorLGCtx ctx,const char * const *names)
7093 {
7094   PetscErrorCode    ierr;
7095 
7096   PetscFunctionBegin;
7097   ierr = PetscStrArrayDestroy(&ctx->names);CHKERRQ(ierr);
7098   ierr = PetscStrArrayallocpy(names,&ctx->names);CHKERRQ(ierr);
7099   PetscFunctionReturn(0);
7100 }
7101 
7102 /*@C
7103    TSMonitorLGGetVariableNames - Gets the name of each component in the solution vector so that it may be displayed in the plot
7104 
7105    Collective on TS
7106 
7107    Input Parameter:
7108 .  ts - the TS context
7109 
7110    Output Parameter:
7111 .  names - the names of the components, final string must be NULL
7112 
7113    Level: intermediate
7114 
7115    Notes: If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored
7116 
7117 .keywords: TS,  vector, monitor, view
7118 
7119 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables()
7120 @*/
7121 PetscErrorCode  TSMonitorLGGetVariableNames(TS ts,const char *const **names)
7122 {
7123   PetscInt       i;
7124 
7125   PetscFunctionBegin;
7126   *names = NULL;
7127   for (i=0; i<ts->numbermonitors; i++) {
7128     if (ts->monitor[i] == TSMonitorLGSolution) {
7129       TSMonitorLGCtx  ctx = (TSMonitorLGCtx) ts->monitorcontext[i];
7130       *names = (const char *const *)ctx->names;
7131       break;
7132     }
7133   }
7134   PetscFunctionReturn(0);
7135 }
7136 
7137 /*@C
7138    TSMonitorLGCtxSetDisplayVariables - Sets the variables that are to be display in the monitor
7139 
7140    Collective on TS
7141 
7142    Input Parameters:
7143 +  ctx - the TSMonitorLG context
7144 .  displaynames - the names of the components, final string must be NULL
7145 
7146    Level: intermediate
7147 
7148 .keywords: TS,  vector, monitor, view
7149 
7150 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames()
7151 @*/
7152 PetscErrorCode  TSMonitorLGCtxSetDisplayVariables(TSMonitorLGCtx ctx,const char * const *displaynames)
7153 {
7154   PetscInt          j = 0,k;
7155   PetscErrorCode    ierr;
7156 
7157   PetscFunctionBegin;
7158   if (!ctx->names) PetscFunctionReturn(0);
7159   ierr = PetscStrArrayDestroy(&ctx->displaynames);CHKERRQ(ierr);
7160   ierr = PetscStrArrayallocpy(displaynames,&ctx->displaynames);CHKERRQ(ierr);
7161   while (displaynames[j]) j++;
7162   ctx->ndisplayvariables = j;
7163   ierr = PetscMalloc1(ctx->ndisplayvariables,&ctx->displayvariables);CHKERRQ(ierr);
7164   ierr = PetscMalloc1(ctx->ndisplayvariables,&ctx->displayvalues);CHKERRQ(ierr);
7165   j = 0;
7166   while (displaynames[j]) {
7167     k = 0;
7168     while (ctx->names[k]) {
7169       PetscBool flg;
7170       ierr = PetscStrcmp(displaynames[j],ctx->names[k],&flg);CHKERRQ(ierr);
7171       if (flg) {
7172         ctx->displayvariables[j] = k;
7173         break;
7174       }
7175       k++;
7176     }
7177     j++;
7178   }
7179   PetscFunctionReturn(0);
7180 }
7181 
7182 
7183 /*@C
7184    TSMonitorLGSetDisplayVariables - Sets the variables that are to be display in the monitor
7185 
7186    Collective on TS
7187 
7188    Input Parameters:
7189 +  ts - the TS context
7190 .  displaynames - the names of the components, final string must be NULL
7191 
7192    Notes: If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored
7193 
7194    Level: intermediate
7195 
7196 .keywords: TS,  vector, monitor, view
7197 
7198 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames()
7199 @*/
7200 PetscErrorCode  TSMonitorLGSetDisplayVariables(TS ts,const char * const *displaynames)
7201 {
7202   PetscInt          i;
7203   PetscErrorCode    ierr;
7204 
7205   PetscFunctionBegin;
7206   for (i=0; i<ts->numbermonitors; i++) {
7207     if (ts->monitor[i] == TSMonitorLGSolution) {
7208       ierr = TSMonitorLGCtxSetDisplayVariables((TSMonitorLGCtx)ts->monitorcontext[i],displaynames);CHKERRQ(ierr);
7209       break;
7210     }
7211   }
7212   PetscFunctionReturn(0);
7213 }
7214 
7215 /*@C
7216    TSMonitorLGSetTransform - Solution vector will be transformed by provided function before being displayed
7217 
7218    Collective on TS
7219 
7220    Input Parameters:
7221 +  ts - the TS context
7222 .  transform - the transform function
7223 .  destroy - function to destroy the optional context
7224 -  ctx - optional context used by transform function
7225 
7226    Notes: If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored
7227 
7228    Level: intermediate
7229 
7230 .keywords: TS,  vector, monitor, view
7231 
7232 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames(), TSMonitorLGCtxSetTransform()
7233 @*/
7234 PetscErrorCode  TSMonitorLGSetTransform(TS ts,PetscErrorCode (*transform)(void*,Vec,Vec*),PetscErrorCode (*destroy)(void*),void *tctx)
7235 {
7236   PetscInt          i;
7237   PetscErrorCode    ierr;
7238 
7239   PetscFunctionBegin;
7240   for (i=0; i<ts->numbermonitors; i++) {
7241     if (ts->monitor[i] == TSMonitorLGSolution) {
7242       ierr = TSMonitorLGCtxSetTransform((TSMonitorLGCtx)ts->monitorcontext[i],transform,destroy,tctx);CHKERRQ(ierr);
7243     }
7244   }
7245   PetscFunctionReturn(0);
7246 }
7247 
7248 /*@C
7249    TSMonitorLGCtxSetTransform - Solution vector will be transformed by provided function before being displayed
7250 
7251    Collective on TSLGCtx
7252 
7253    Input Parameters:
7254 +  ts - the TS context
7255 .  transform - the transform function
7256 .  destroy - function to destroy the optional context
7257 -  ctx - optional context used by transform function
7258 
7259    Level: intermediate
7260 
7261 .keywords: TS,  vector, monitor, view
7262 
7263 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames(), TSMonitorLGSetTransform()
7264 @*/
7265 PetscErrorCode  TSMonitorLGCtxSetTransform(TSMonitorLGCtx ctx,PetscErrorCode (*transform)(void*,Vec,Vec*),PetscErrorCode (*destroy)(void*),void *tctx)
7266 {
7267   PetscFunctionBegin;
7268   ctx->transform    = transform;
7269   ctx->transformdestroy = destroy;
7270   ctx->transformctx = tctx;
7271   PetscFunctionReturn(0);
7272 }
7273 
7274 /*@C
7275    TSMonitorLGError - Monitors progress of the TS solvers by plotting each component of the solution vector
7276        in a time based line graph
7277 
7278    Collective on TS
7279 
7280    Input Parameters:
7281 +  ts - the TS context
7282 .  step - current time-step
7283 .  ptime - current time
7284 .  u - current solution
7285 -  dctx - TSMonitorLGCtx object created with TSMonitorLGCtxCreate()
7286 
7287    Level: intermediate
7288 
7289    Notes: Each process in a parallel run displays its component errors in a separate window
7290 
7291    The user must provide the solution using TSSetSolutionFunction() to use this monitor.
7292 
7293    Options Database Keys:
7294 .  -ts_monitor_lg_error - create a graphical monitor of error history
7295 
7296 .keywords: TS,  vector, monitor, view
7297 
7298 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSSetSolutionFunction()
7299 @*/
7300 PetscErrorCode  TSMonitorLGError(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy)
7301 {
7302   PetscErrorCode    ierr;
7303   TSMonitorLGCtx    ctx = (TSMonitorLGCtx)dummy;
7304   const PetscScalar *yy;
7305   Vec               y;
7306 
7307   PetscFunctionBegin;
7308   if (!step) {
7309     PetscDrawAxis axis;
7310     PetscInt      dim;
7311     ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr);
7312     ierr = PetscDrawAxisSetLabels(axis,"Error in solution as function of time","Time","Solution");CHKERRQ(ierr);
7313     ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr);
7314     ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr);
7315     ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr);
7316   }
7317   ierr = VecDuplicate(u,&y);CHKERRQ(ierr);
7318   ierr = TSComputeSolutionFunction(ts,ptime,y);CHKERRQ(ierr);
7319   ierr = VecAXPY(y,-1.0,u);CHKERRQ(ierr);
7320   ierr = VecGetArrayRead(y,&yy);CHKERRQ(ierr);
7321 #if defined(PETSC_USE_COMPLEX)
7322   {
7323     PetscReal *yreal;
7324     PetscInt  i,n;
7325     ierr = VecGetLocalSize(y,&n);CHKERRQ(ierr);
7326     ierr = PetscMalloc1(n,&yreal);CHKERRQ(ierr);
7327     for (i=0; i<n; i++) yreal[i] = PetscRealPart(yy[i]);
7328     ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yreal);CHKERRQ(ierr);
7329     ierr = PetscFree(yreal);CHKERRQ(ierr);
7330   }
7331 #else
7332   ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yy);CHKERRQ(ierr);
7333 #endif
7334   ierr = VecRestoreArrayRead(y,&yy);CHKERRQ(ierr);
7335   ierr = VecDestroy(&y);CHKERRQ(ierr);
7336   if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) {
7337     ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr);
7338     ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr);
7339   }
7340   PetscFunctionReturn(0);
7341 }
7342 
7343 PetscErrorCode TSMonitorLGSNESIterations(TS ts,PetscInt n,PetscReal ptime,Vec v,void *monctx)
7344 {
7345   TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx;
7346   PetscReal      x   = ptime,y;
7347   PetscErrorCode ierr;
7348   PetscInt       its;
7349 
7350   PetscFunctionBegin;
7351   if (n < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */
7352   if (!n) {
7353     PetscDrawAxis axis;
7354     ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr);
7355     ierr = PetscDrawAxisSetLabels(axis,"Nonlinear iterations as function of time","Time","SNES Iterations");CHKERRQ(ierr);
7356     ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr);
7357     ctx->snes_its = 0;
7358   }
7359   ierr = TSGetSNESIterations(ts,&its);CHKERRQ(ierr);
7360   y    = its - ctx->snes_its;
7361   ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr);
7362   if (((ctx->howoften > 0) && (!(n % ctx->howoften)) && (n > -1)) || ((ctx->howoften == -1) && (n == -1))) {
7363     ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr);
7364     ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr);
7365   }
7366   ctx->snes_its = its;
7367   PetscFunctionReturn(0);
7368 }
7369 
7370 PetscErrorCode TSMonitorLGKSPIterations(TS ts,PetscInt n,PetscReal ptime,Vec v,void *monctx)
7371 {
7372   TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx;
7373   PetscReal      x   = ptime,y;
7374   PetscErrorCode ierr;
7375   PetscInt       its;
7376 
7377   PetscFunctionBegin;
7378   if (n < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */
7379   if (!n) {
7380     PetscDrawAxis axis;
7381     ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr);
7382     ierr = PetscDrawAxisSetLabels(axis,"Linear iterations as function of time","Time","KSP Iterations");CHKERRQ(ierr);
7383     ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr);
7384     ctx->ksp_its = 0;
7385   }
7386   ierr = TSGetKSPIterations(ts,&its);CHKERRQ(ierr);
7387   y    = its - ctx->ksp_its;
7388   ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr);
7389   if (((ctx->howoften > 0) && (!(n % ctx->howoften)) && (n > -1)) || ((ctx->howoften == -1) && (n == -1))) {
7390     ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr);
7391     ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr);
7392   }
7393   ctx->ksp_its = its;
7394   PetscFunctionReturn(0);
7395 }
7396 
7397 /*@
7398    TSComputeLinearStability - computes the linear stability function at a point
7399 
7400    Collective on TS and Vec
7401 
7402    Input Parameters:
7403 +  ts - the TS context
7404 -  xr,xi - real and imaginary part of input arguments
7405 
7406    Output Parameters:
7407 .  yr,yi - real and imaginary part of function value
7408 
7409    Level: developer
7410 
7411 .keywords: TS, compute
7412 
7413 .seealso: TSSetRHSFunction(), TSComputeIFunction()
7414 @*/
7415 PetscErrorCode TSComputeLinearStability(TS ts,PetscReal xr,PetscReal xi,PetscReal *yr,PetscReal *yi)
7416 {
7417   PetscErrorCode ierr;
7418 
7419   PetscFunctionBegin;
7420   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
7421   if (!ts->ops->linearstability) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Linearized stability function not provided for this method");
7422   ierr = (*ts->ops->linearstability)(ts,xr,xi,yr,yi);CHKERRQ(ierr);
7423   PetscFunctionReturn(0);
7424 }
7425 
7426 /* ------------------------------------------------------------------------*/
7427 /*@C
7428    TSMonitorEnvelopeCtxCreate - Creates a context for use with TSMonitorEnvelope()
7429 
7430    Collective on TS
7431 
7432    Input Parameters:
7433 .  ts  - the ODE solver object
7434 
7435    Output Parameter:
7436 .  ctx - the context
7437 
7438    Level: intermediate
7439 
7440 .keywords: TS, monitor, line graph, residual, seealso
7441 
7442 .seealso: TSMonitorLGTimeStep(), TSMonitorSet(), TSMonitorLGSolution(), TSMonitorLGError()
7443 
7444 @*/
7445 PetscErrorCode  TSMonitorEnvelopeCtxCreate(TS ts,TSMonitorEnvelopeCtx *ctx)
7446 {
7447   PetscErrorCode ierr;
7448 
7449   PetscFunctionBegin;
7450   ierr = PetscNew(ctx);CHKERRQ(ierr);
7451   PetscFunctionReturn(0);
7452 }
7453 
7454 /*@C
7455    TSMonitorEnvelope - Monitors the maximum and minimum value of each component of the solution
7456 
7457    Collective on TS
7458 
7459    Input Parameters:
7460 +  ts - the TS context
7461 .  step - current time-step
7462 .  ptime - current time
7463 .  u  - current solution
7464 -  dctx - the envelope context
7465 
7466    Options Database:
7467 .  -ts_monitor_envelope
7468 
7469    Level: intermediate
7470 
7471    Notes: after a solve you can use TSMonitorEnvelopeGetBounds() to access the envelope
7472 
7473 .keywords: TS,  vector, monitor, view
7474 
7475 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorEnvelopeGetBounds(), TSMonitorEnvelopeCtxCreate()
7476 @*/
7477 PetscErrorCode  TSMonitorEnvelope(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dctx)
7478 {
7479   PetscErrorCode       ierr;
7480   TSMonitorEnvelopeCtx ctx = (TSMonitorEnvelopeCtx)dctx;
7481 
7482   PetscFunctionBegin;
7483   if (!ctx->max) {
7484     ierr = VecDuplicate(u,&ctx->max);CHKERRQ(ierr);
7485     ierr = VecDuplicate(u,&ctx->min);CHKERRQ(ierr);
7486     ierr = VecCopy(u,ctx->max);CHKERRQ(ierr);
7487     ierr = VecCopy(u,ctx->min);CHKERRQ(ierr);
7488   } else {
7489     ierr = VecPointwiseMax(ctx->max,u,ctx->max);CHKERRQ(ierr);
7490     ierr = VecPointwiseMin(ctx->min,u,ctx->min);CHKERRQ(ierr);
7491   }
7492   PetscFunctionReturn(0);
7493 }
7494 
7495 
7496 /*@C
7497    TSMonitorEnvelopeGetBounds - Gets the bounds for the components of the solution
7498 
7499    Collective on TS
7500 
7501    Input Parameter:
7502 .  ts - the TS context
7503 
7504    Output Parameter:
7505 +  max - the maximum values
7506 -  min - the minimum values
7507 
7508    Notes: If the TS does not have a TSMonitorEnvelopeCtx associated with it then this function is ignored
7509 
7510    Level: intermediate
7511 
7512 .keywords: TS,  vector, monitor, view
7513 
7514 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables()
7515 @*/
7516 PetscErrorCode  TSMonitorEnvelopeGetBounds(TS ts,Vec *max,Vec *min)
7517 {
7518   PetscInt i;
7519 
7520   PetscFunctionBegin;
7521   if (max) *max = NULL;
7522   if (min) *min = NULL;
7523   for (i=0; i<ts->numbermonitors; i++) {
7524     if (ts->monitor[i] == TSMonitorEnvelope) {
7525       TSMonitorEnvelopeCtx  ctx = (TSMonitorEnvelopeCtx) ts->monitorcontext[i];
7526       if (max) *max = ctx->max;
7527       if (min) *min = ctx->min;
7528       break;
7529     }
7530   }
7531   PetscFunctionReturn(0);
7532 }
7533 
7534 /*@C
7535    TSMonitorEnvelopeCtxDestroy - Destroys a context that was created  with TSMonitorEnvelopeCtxCreate().
7536 
7537    Collective on TSMonitorEnvelopeCtx
7538 
7539    Input Parameter:
7540 .  ctx - the monitor context
7541 
7542    Level: intermediate
7543 
7544 .keywords: TS, monitor, line graph, destroy
7545 
7546 .seealso: TSMonitorLGCtxCreate(),  TSMonitorSet(), TSMonitorLGTimeStep()
7547 @*/
7548 PetscErrorCode  TSMonitorEnvelopeCtxDestroy(TSMonitorEnvelopeCtx *ctx)
7549 {
7550   PetscErrorCode ierr;
7551 
7552   PetscFunctionBegin;
7553   ierr = VecDestroy(&(*ctx)->min);CHKERRQ(ierr);
7554   ierr = VecDestroy(&(*ctx)->max);CHKERRQ(ierr);
7555   ierr = PetscFree(*ctx);CHKERRQ(ierr);
7556   PetscFunctionReturn(0);
7557 }
7558 
7559 /*@
7560    TSRollBack - Rolls back one time step
7561 
7562    Collective on TS
7563 
7564    Input Parameter:
7565 .  ts - the TS context obtained from TSCreate()
7566 
7567    Level: advanced
7568 
7569 .keywords: TS, timestep, rollback
7570 
7571 .seealso: TSCreate(), TSSetUp(), TSDestroy(), TSSolve(), TSSetPreStep(), TSSetPreStage(), TSInterpolate()
7572 @*/
7573 PetscErrorCode  TSRollBack(TS ts)
7574 {
7575   PetscErrorCode ierr;
7576 
7577   PetscFunctionBegin;
7578   PetscValidHeaderSpecific(ts, TS_CLASSID,1);
7579   if (ts->steprollback) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"TSRollBack already called");
7580   if (!ts->ops->rollback) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSRollBack not implemented for type '%s'",((PetscObject)ts)->type_name);
7581   ierr = (*ts->ops->rollback)(ts);CHKERRQ(ierr);
7582   ts->time_step = ts->ptime - ts->ptime_prev;
7583   ts->ptime = ts->ptime_prev;
7584   ts->ptime_prev = ts->ptime_prev_rollback;
7585   ts->steps--; ts->total_steps--;
7586   ierr = TSPostEvaluate(ts);CHKERRQ(ierr);
7587   ts->steprollback = PETSC_TRUE;
7588   PetscFunctionReturn(0);
7589 }
7590 
7591 /*@
7592    TSGetStages - Get the number of stages and stage values
7593 
7594    Input Parameter:
7595 .  ts - the TS context obtained from TSCreate()
7596 
7597    Level: advanced
7598 
7599 .keywords: TS, getstages
7600 
7601 .seealso: TSCreate()
7602 @*/
7603 PetscErrorCode  TSGetStages(TS ts,PetscInt *ns,Vec **Y)
7604 {
7605   PetscErrorCode ierr;
7606 
7607   PetscFunctionBegin;
7608   PetscValidHeaderSpecific(ts, TS_CLASSID,1);
7609   PetscValidPointer(ns,2);
7610 
7611   if (!ts->ops->getstages) *ns=0;
7612   else {
7613     ierr = (*ts->ops->getstages)(ts,ns,Y);CHKERRQ(ierr);
7614   }
7615   PetscFunctionReturn(0);
7616 }
7617 
7618 /*@C
7619   TSComputeIJacobianDefaultColor - Computes the Jacobian using finite differences and coloring to exploit matrix sparsity.
7620 
7621   Collective on SNES
7622 
7623   Input Parameters:
7624 + ts - the TS context
7625 . t - current timestep
7626 . U - state vector
7627 . Udot - time derivative of state vector
7628 . shift - shift to apply, see note below
7629 - ctx - an optional user context
7630 
7631   Output Parameters:
7632 + J - Jacobian matrix (not altered in this routine)
7633 - B - newly computed Jacobian matrix to use with preconditioner (generally the same as J)
7634 
7635   Level: intermediate
7636 
7637   Notes:
7638   If F(t,U,Udot)=0 is the DAE, the required Jacobian is
7639 
7640   dF/dU + shift*dF/dUdot
7641 
7642   Most users should not need to explicitly call this routine, as it
7643   is used internally within the nonlinear solvers.
7644 
7645   This will first try to get the coloring from the DM.  If the DM type has no coloring
7646   routine, then it will try to get the coloring from the matrix.  This requires that the
7647   matrix have nonzero entries precomputed.
7648 
7649 .keywords: TS, finite differences, Jacobian, coloring, sparse
7650 .seealso: TSSetIJacobian(), MatFDColoringCreate(), MatFDColoringSetFunction()
7651 @*/
7652 PetscErrorCode TSComputeIJacobianDefaultColor(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat J,Mat B,void *ctx)
7653 {
7654   SNES           snes;
7655   MatFDColoring  color;
7656   PetscBool      hascolor, matcolor = PETSC_FALSE;
7657   PetscErrorCode ierr;
7658 
7659   PetscFunctionBegin;
7660   ierr = PetscOptionsGetBool(((PetscObject)ts)->options,((PetscObject) ts)->prefix, "-ts_fd_color_use_mat", &matcolor, NULL);CHKERRQ(ierr);
7661   ierr = PetscObjectQuery((PetscObject) B, "TSMatFDColoring", (PetscObject *) &color);CHKERRQ(ierr);
7662   if (!color) {
7663     DM         dm;
7664     ISColoring iscoloring;
7665 
7666     ierr = TSGetDM(ts, &dm);CHKERRQ(ierr);
7667     ierr = DMHasColoring(dm, &hascolor);CHKERRQ(ierr);
7668     if (hascolor && !matcolor) {
7669       ierr = DMCreateColoring(dm, IS_COLORING_GLOBAL, &iscoloring);CHKERRQ(ierr);
7670       ierr = MatFDColoringCreate(B, iscoloring, &color);CHKERRQ(ierr);
7671       ierr = MatFDColoringSetFunction(color, (PetscErrorCode (*)(void)) SNESTSFormFunction, (void *) ts);CHKERRQ(ierr);
7672       ierr = MatFDColoringSetFromOptions(color);CHKERRQ(ierr);
7673       ierr = MatFDColoringSetUp(B, iscoloring, color);CHKERRQ(ierr);
7674       ierr = ISColoringDestroy(&iscoloring);CHKERRQ(ierr);
7675     } else {
7676       MatColoring mc;
7677 
7678       ierr = MatColoringCreate(B, &mc);CHKERRQ(ierr);
7679       ierr = MatColoringSetDistance(mc, 2);CHKERRQ(ierr);
7680       ierr = MatColoringSetType(mc, MATCOLORINGSL);CHKERRQ(ierr);
7681       ierr = MatColoringSetFromOptions(mc);CHKERRQ(ierr);
7682       ierr = MatColoringApply(mc, &iscoloring);CHKERRQ(ierr);
7683       ierr = MatColoringDestroy(&mc);CHKERRQ(ierr);
7684       ierr = MatFDColoringCreate(B, iscoloring, &color);CHKERRQ(ierr);
7685       ierr = MatFDColoringSetFunction(color, (PetscErrorCode (*)(void)) SNESTSFormFunction, (void *) ts);CHKERRQ(ierr);
7686       ierr = MatFDColoringSetFromOptions(color);CHKERRQ(ierr);
7687       ierr = MatFDColoringSetUp(B, iscoloring, color);CHKERRQ(ierr);
7688       ierr = ISColoringDestroy(&iscoloring);CHKERRQ(ierr);
7689     }
7690     ierr = PetscObjectCompose((PetscObject) B, "TSMatFDColoring", (PetscObject) color);CHKERRQ(ierr);
7691     ierr = PetscObjectDereference((PetscObject) color);CHKERRQ(ierr);
7692   }
7693   ierr = TSGetSNES(ts, &snes);CHKERRQ(ierr);
7694   ierr = MatFDColoringApply(B, color, U, snes);CHKERRQ(ierr);
7695   if (J != B) {
7696     ierr = MatAssemblyBegin(J, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
7697     ierr = MatAssemblyEnd(J, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
7698   }
7699   PetscFunctionReturn(0);
7700 }
7701 
7702 /*@
7703     TSSetFunctionDomainError - Set the function testing if the current state vector is valid
7704 
7705     Input Parameters:
7706     ts - the TS context
7707     func - function called within TSFunctionDomainError
7708 
7709     Level: intermediate
7710 
7711 .keywords: TS, state, domain
7712 .seealso: TSAdaptCheckStage(), TSFunctionDomainError()
7713 @*/
7714 
7715 PetscErrorCode TSSetFunctionDomainError(TS ts, PetscErrorCode (*func)(TS,PetscReal,Vec,PetscBool*))
7716 {
7717   PetscFunctionBegin;
7718   PetscValidHeaderSpecific(ts, TS_CLASSID,1);
7719   ts->functiondomainerror = func;
7720   PetscFunctionReturn(0);
7721 }
7722 
7723 /*@
7724     TSFunctionDomainError - Check if the current state is valid
7725 
7726     Input Parameters:
7727     ts - the TS context
7728     stagetime - time of the simulation
7729     Y - state vector to check.
7730 
7731     Output Parameter:
7732     accept - Set to PETSC_FALSE if the current state vector is valid.
7733 
7734     Note:
7735     This function should be used to ensure the state is in a valid part of the space.
7736     For example, one can ensure here all values are positive.
7737 
7738     Level: advanced
7739 @*/
7740 PetscErrorCode TSFunctionDomainError(TS ts,PetscReal stagetime,Vec Y,PetscBool* accept)
7741 {
7742   PetscErrorCode ierr;
7743 
7744   PetscFunctionBegin;
7745 
7746   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
7747   *accept = PETSC_TRUE;
7748   if (ts->functiondomainerror) {
7749     PetscStackCallStandard((*ts->functiondomainerror),(ts,stagetime,Y,accept));
7750   }
7751   PetscFunctionReturn(0);
7752 }
7753 
7754 /*@C
7755   TSClone - This function clones a time step object.
7756 
7757   Collective on MPI_Comm
7758 
7759   Input Parameter:
7760 . tsin    - The input TS
7761 
7762   Output Parameter:
7763 . tsout   - The output TS (cloned)
7764 
7765   Notes:
7766   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.
7767 
7768   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); ierr = TSSetSNES(ts,snes_dup);
7769 
7770   Level: developer
7771 
7772 .keywords: TS, clone
7773 .seealso: TSCreate(), TSSetType(), TSSetUp(), TSDestroy(), TSSetProblemType()
7774 @*/
7775 PetscErrorCode  TSClone(TS tsin, TS *tsout)
7776 {
7777   TS             t;
7778   PetscErrorCode ierr;
7779   SNES           snes_start;
7780   DM             dm;
7781   TSType         type;
7782 
7783   PetscFunctionBegin;
7784   PetscValidPointer(tsin,1);
7785   *tsout = NULL;
7786 
7787   ierr = PetscHeaderCreate(t, TS_CLASSID, "TS", "Time stepping", "TS", PetscObjectComm((PetscObject)tsin), TSDestroy, TSView);CHKERRQ(ierr);
7788 
7789   /* General TS description */
7790   t->numbermonitors    = 0;
7791   t->setupcalled       = 0;
7792   t->ksp_its           = 0;
7793   t->snes_its          = 0;
7794   t->nwork             = 0;
7795   t->rhsjacobian.time  = -1e20;
7796   t->rhsjacobian.scale = 1.;
7797   t->ijacobian.shift   = 1.;
7798 
7799   ierr = TSGetSNES(tsin,&snes_start);CHKERRQ(ierr);
7800   ierr = TSSetSNES(t,snes_start);CHKERRQ(ierr);
7801 
7802   ierr = TSGetDM(tsin,&dm);CHKERRQ(ierr);
7803   ierr = TSSetDM(t,dm);CHKERRQ(ierr);
7804 
7805   t->adapt = tsin->adapt;
7806   ierr = PetscObjectReference((PetscObject)t->adapt);CHKERRQ(ierr);
7807 
7808   t->trajectory = tsin->trajectory;
7809   ierr = PetscObjectReference((PetscObject)t->trajectory);CHKERRQ(ierr);
7810 
7811   t->event = tsin->event;
7812   if (t->event) t->event->refct++;
7813 
7814   t->problem_type      = tsin->problem_type;
7815   t->ptime             = tsin->ptime;
7816   t->ptime_prev        = tsin->ptime_prev;
7817   t->time_step         = tsin->time_step;
7818   t->max_time          = tsin->max_time;
7819   t->steps             = tsin->steps;
7820   t->total_steps       = tsin->total_steps;
7821   t->max_steps         = tsin->max_steps;
7822   t->equation_type     = tsin->equation_type;
7823   t->atol              = tsin->atol;
7824   t->rtol              = tsin->rtol;
7825   t->max_snes_failures = tsin->max_snes_failures;
7826   t->max_reject        = tsin->max_reject;
7827   t->errorifstepfailed = tsin->errorifstepfailed;
7828 
7829   ierr = TSGetType(tsin,&type);CHKERRQ(ierr);
7830   ierr = TSSetType(t,type);CHKERRQ(ierr);
7831 
7832   t->vec_sol           = NULL;
7833 
7834   t->cfltime          = tsin->cfltime;
7835   t->cfltime_local    = tsin->cfltime_local;
7836   t->exact_final_time = tsin->exact_final_time;
7837 
7838   ierr = PetscMemcpy(t->ops,tsin->ops,sizeof(struct _TSOps));CHKERRQ(ierr);
7839 
7840   if (((PetscObject)tsin)->fortran_func_pointers) {
7841     PetscInt i;
7842     ierr = PetscMalloc((10)*sizeof(void(*)(void)),&((PetscObject)t)->fortran_func_pointers);CHKERRQ(ierr);
7843     for (i=0; i<10; i++) {
7844       ((PetscObject)t)->fortran_func_pointers[i] = ((PetscObject)tsin)->fortran_func_pointers[i];
7845     }
7846   }
7847   *tsout = t;
7848   PetscFunctionReturn(0);
7849 }
7850