1 #include <petsc/private/tsimpl.h> /*I "petscts.h" I*/ 2 #include <petscdmshell.h> 3 #include <petscdmda.h> 4 #include <petscviewer.h> 5 #include <petscdraw.h> 6 7 /* Logging support */ 8 PetscClassId TS_CLASSID, DMTS_CLASSID; 9 PetscLogEvent TS_AdjointStep, TS_Step, TS_PseudoComputeTimeStep, TS_FunctionEval, TS_JacobianEval; 10 11 const char *const TSExactFinalTimeOptions[] = {"UNSPECIFIED","STEPOVER","INTERPOLATE","MATCHSTEP","TSExactFinalTimeOption","TS_EXACTFINALTIME_",0}; 12 13 struct _n_TSMonitorDrawCtx { 14 PetscViewer viewer; 15 Vec initialsolution; 16 PetscBool showinitial; 17 PetscInt howoften; /* when > 0 uses step % howoften, when negative only final solution plotted */ 18 PetscBool showtimestepandtime; 19 }; 20 21 /*@C 22 TSMonitorSetFromOptions - Sets a monitor function and viewer appropriate for the type indicated by the user 23 24 Collective on TS 25 26 Input Parameters: 27 + ts - TS object you wish to monitor 28 . name - the monitor type one is seeking 29 . help - message indicating what monitoring is done 30 . manual - manual page for the monitor 31 . monitor - the monitor function 32 - 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 33 34 Level: developer 35 36 .seealso: PetscOptionsGetViewer(), PetscOptionsGetReal(), PetscOptionsHasName(), PetscOptionsGetString(), 37 PetscOptionsGetIntArray(), PetscOptionsGetRealArray(), PetscOptionsBool() 38 PetscOptionsInt(), PetscOptionsString(), PetscOptionsReal(), PetscOptionsBool(), 39 PetscOptionsName(), PetscOptionsBegin(), PetscOptionsEnd(), PetscOptionsHead(), 40 PetscOptionsStringArray(),PetscOptionsRealArray(), PetscOptionsScalar(), 41 PetscOptionsBoolGroupBegin(), PetscOptionsBoolGroup(), PetscOptionsBoolGroupEnd(), 42 PetscOptionsFList(), PetscOptionsEList() 43 @*/ 44 PetscErrorCode TSMonitorSetFromOptions(TS ts,const char name[],const char help[], const char manual[],PetscErrorCode (*monitor)(TS,PetscInt,PetscReal,Vec,PetscViewerAndFormat*),PetscErrorCode (*monitorsetup)(TS,PetscViewerAndFormat*)) 45 { 46 PetscErrorCode ierr; 47 PetscViewer viewer; 48 PetscViewerFormat format; 49 PetscBool flg; 50 51 PetscFunctionBegin; 52 ierr = PetscOptionsGetViewer(PetscObjectComm((PetscObject)ts),((PetscObject)ts)->prefix,name,&viewer,&format,&flg);CHKERRQ(ierr); 53 if (flg) { 54 PetscViewerAndFormat *vf; 55 ierr = PetscViewerAndFormatCreate(viewer,format,&vf);CHKERRQ(ierr); 56 ierr = PetscObjectDereference((PetscObject)viewer);CHKERRQ(ierr); 57 if (monitorsetup) { 58 ierr = (*monitorsetup)(ts,vf);CHKERRQ(ierr); 59 } 60 ierr = TSMonitorSet(ts,(PetscErrorCode (*)(TS,PetscInt,PetscReal,Vec,void*))monitor,vf,(PetscErrorCode (*)(void**))PetscViewerAndFormatDestroy);CHKERRQ(ierr); 61 } 62 PetscFunctionReturn(0); 63 } 64 65 /*@C 66 TSAdjointMonitorSensi - monitors the first lambda sensitivity 67 68 Level: intermediate 69 70 .keywords: TS, set, monitor 71 72 .seealso: TSAdjointMonitorSet() 73 @*/ 74 PetscErrorCode TSAdjointMonitorSensi(TS ts,PetscInt step,PetscReal ptime,Vec v,PetscInt numcost,Vec *lambda,Vec *mu,PetscViewerAndFormat *vf) 75 { 76 PetscErrorCode ierr; 77 PetscViewer viewer = vf->viewer; 78 79 PetscFunctionBegin; 80 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,4); 81 ierr = PetscViewerPushFormat(viewer,vf->format);CHKERRQ(ierr); 82 ierr = VecView(lambda[0],viewer);CHKERRQ(ierr); 83 ierr = PetscViewerPopFormat(viewer);CHKERRQ(ierr); 84 PetscFunctionReturn(0); 85 } 86 87 /*@C 88 TSAdjointMonitorSetFromOptions - Sets a monitor function and viewer appropriate for the type indicated by the user 89 90 Collective on TS 91 92 Input Parameters: 93 + ts - TS object you wish to monitor 94 . name - the monitor type one is seeking 95 . help - message indicating what monitoring is done 96 . manual - manual page for the monitor 97 . monitor - the monitor function 98 - 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 99 100 Level: developer 101 102 .seealso: PetscOptionsGetViewer(), PetscOptionsGetReal(), PetscOptionsHasName(), PetscOptionsGetString(), 103 PetscOptionsGetIntArray(), PetscOptionsGetRealArray(), PetscOptionsBool() 104 PetscOptionsInt(), PetscOptionsString(), PetscOptionsReal(), PetscOptionsBool(), 105 PetscOptionsName(), PetscOptionsBegin(), PetscOptionsEnd(), PetscOptionsHead(), 106 PetscOptionsStringArray(),PetscOptionsRealArray(), PetscOptionsScalar(), 107 PetscOptionsBoolGroupBegin(), PetscOptionsBoolGroup(), PetscOptionsBoolGroupEnd(), 108 PetscOptionsFList(), PetscOptionsEList() 109 @*/ 110 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*)) 111 { 112 PetscErrorCode ierr; 113 PetscViewer viewer; 114 PetscViewerFormat format; 115 PetscBool flg; 116 117 PetscFunctionBegin; 118 ierr = PetscOptionsGetViewer(PetscObjectComm((PetscObject)ts),((PetscObject)ts)->prefix,name,&viewer,&format,&flg);CHKERRQ(ierr); 119 if (flg) { 120 PetscViewerAndFormat *vf; 121 ierr = PetscViewerAndFormatCreate(viewer,format,&vf);CHKERRQ(ierr); 122 ierr = PetscObjectDereference((PetscObject)viewer);CHKERRQ(ierr); 123 if (monitorsetup) { 124 ierr = (*monitorsetup)(ts,vf);CHKERRQ(ierr); 125 } 126 ierr = TSAdjointMonitorSet(ts,(PetscErrorCode (*)(TS,PetscInt,PetscReal,Vec,PetscInt,Vec*,Vec*,void*))monitor,vf,(PetscErrorCode (*)(void**))PetscViewerAndFormatDestroy);CHKERRQ(ierr); 127 } 128 PetscFunctionReturn(0); 129 } 130 131 static PetscErrorCode TSAdaptSetDefaultType(TSAdapt adapt,TSAdaptType default_type) 132 { 133 PetscErrorCode ierr; 134 135 PetscFunctionBegin; 136 PetscValidHeaderSpecific(adapt,TSADAPT_CLASSID,1); 137 PetscValidCharPointer(default_type,2); 138 if (!((PetscObject)adapt)->type_name) { 139 ierr = TSAdaptSetType(adapt,default_type);CHKERRQ(ierr); 140 } 141 PetscFunctionReturn(0); 142 } 143 144 /*@ 145 TSSetFromOptions - Sets various TS parameters from user options. 146 147 Collective on TS 148 149 Input Parameter: 150 . ts - the TS context obtained from TSCreate() 151 152 Options Database Keys: 153 + -ts_type <type> - TSEULER, TSBEULER, TSSUNDIALS, TSPSEUDO, TSCN, TSRK, TSTHETA, TSALPHA, TSGLLE, TSSSP, TSGLEE 154 . -ts_save_trajectory - checkpoint the solution at each time-step 155 . -ts_max_time <time> - maximum time to compute to 156 . -ts_max_steps <steps> - maximum number of time-steps to take 157 . -ts_init_time <time> - initial time to start computation 158 . -ts_final_time <time> - final time to compute to 159 . -ts_dt <dt> - initial time step 160 . -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 161 . -ts_max_snes_failures <maxfailures> - Maximum number of nonlinear solve failures allowed 162 . -ts_max_reject <maxrejects> - Maximum number of step rejections before step fails 163 . -ts_error_if_step_fails <true,false> - Error if no step succeeds 164 . -ts_rtol <rtol> - relative tolerance for local truncation error 165 . -ts_atol <atol> Absolute tolerance for local truncation error 166 . -ts_adjoint_solve <yes,no> After solving the ODE/DAE solve the adjoint problem (requires -ts_save_trajectory) 167 . -ts_fd_color - Use finite differences with coloring to compute IJacobian 168 . -ts_monitor - print information at each timestep 169 . -ts_monitor_lg_solution - Monitor solution graphically 170 . -ts_monitor_lg_error - Monitor error graphically 171 . -ts_monitor_lg_timestep - Monitor timestep size graphically 172 . -ts_monitor_lg_timestep_log - Monitor log timestep size graphically 173 . -ts_monitor_lg_snes_iterations - Monitor number nonlinear iterations for each timestep graphically 174 . -ts_monitor_lg_ksp_iterations - Monitor number nonlinear iterations for each timestep graphically 175 . -ts_monitor_sp_eig - Monitor eigenvalues of linearized operator graphically 176 . -ts_monitor_draw_solution - Monitor solution graphically 177 . -ts_monitor_draw_solution_phase <xleft,yleft,xright,yright> - Monitor solution graphically with phase diagram, requires problem with exactly 2 degrees of freedom 178 . -ts_monitor_draw_error - Monitor error graphically, requires use to have provided TSSetSolutionFunction() 179 . -ts_monitor_solution [ascii binary draw][:filename][:viewerformat] - monitors the solution at each timestep 180 . -ts_monitor_solution_vtk <filename.vts,filename.vtu> - Save each time step to a binary file, use filename-%%03D.vts (filename-%%03D.vtu) 181 . -ts_monitor_envelope - determine maximum and minimum value of each component of the solution over the solution time 182 . -ts_adjoint_monitor - print information at each adjoint time step 183 - -ts_adjoint_monitor_draw_sensi - monitor the sensitivity of the first cost function wrt initial conditions (lambda[0]) graphically 184 185 Developer Note: We should unify all the -ts_monitor options in the way that -xxx_view has been unified 186 187 Level: beginner 188 189 .keywords: TS, timestep, set, options, database 190 191 .seealso: TSGetType() 192 @*/ 193 PetscErrorCode TSSetFromOptions(TS ts) 194 { 195 PetscBool opt,flg,tflg; 196 PetscErrorCode ierr; 197 char monfilename[PETSC_MAX_PATH_LEN]; 198 PetscReal time_step; 199 TSExactFinalTimeOption eftopt; 200 char dir[16]; 201 TSIFunction ifun; 202 const char *defaultType; 203 char typeName[256]; 204 205 PetscFunctionBegin; 206 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 207 208 ierr = TSRegisterAll();CHKERRQ(ierr); 209 ierr = TSGetIFunction(ts,NULL,&ifun,NULL);CHKERRQ(ierr); 210 211 ierr = PetscObjectOptionsBegin((PetscObject)ts);CHKERRQ(ierr); 212 if (((PetscObject)ts)->type_name) 213 defaultType = ((PetscObject)ts)->type_name; 214 else 215 defaultType = ifun ? TSBEULER : TSEULER; 216 ierr = PetscOptionsFList("-ts_type","TS method","TSSetType",TSList,defaultType,typeName,256,&opt);CHKERRQ(ierr); 217 if (opt) { 218 ierr = TSSetType(ts,typeName);CHKERRQ(ierr); 219 } else { 220 ierr = TSSetType(ts,defaultType);CHKERRQ(ierr); 221 } 222 223 /* Handle generic TS options */ 224 ierr = PetscOptionsReal("-ts_max_time","Maximum time to run to","TSSetMaxTime",ts->max_time,&ts->max_time,NULL);CHKERRQ(ierr); 225 ierr = PetscOptionsInt("-ts_max_steps","Maximum number of time steps","TSSetMaxSteps",ts->max_steps,&ts->max_steps,NULL);CHKERRQ(ierr); 226 ierr = PetscOptionsReal("-ts_init_time","Initial time","TSSetTime",ts->ptime,&ts->ptime,NULL);CHKERRQ(ierr); 227 ierr = PetscOptionsReal("-ts_final_time","Final time to run to","TSSetMaxTime",ts->max_time,&ts->max_time,NULL);CHKERRQ(ierr); 228 ierr = PetscOptionsReal("-ts_dt","Initial time step","TSSetTimeStep",ts->time_step,&time_step,&flg);CHKERRQ(ierr); 229 if (flg) {ierr = TSSetTimeStep(ts,time_step);CHKERRQ(ierr);} 230 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); 231 if (flg) {ierr = TSSetExactFinalTime(ts,eftopt);CHKERRQ(ierr);} 232 ierr = PetscOptionsInt("-ts_max_snes_failures","Maximum number of nonlinear solve failures","TSSetMaxSNESFailures",ts->max_snes_failures,&ts->max_snes_failures,NULL);CHKERRQ(ierr); 233 ierr = PetscOptionsInt("-ts_max_reject","Maximum number of step rejections before step fails","TSSetMaxStepRejections",ts->max_reject,&ts->max_reject,NULL);CHKERRQ(ierr); 234 ierr = PetscOptionsBool("-ts_error_if_step_fails","Error if no step succeeds","TSSetErrorIfStepFails",ts->errorifstepfailed,&ts->errorifstepfailed,NULL);CHKERRQ(ierr); 235 ierr = PetscOptionsReal("-ts_rtol","Relative tolerance for local truncation error","TSSetTolerances",ts->rtol,&ts->rtol,NULL);CHKERRQ(ierr); 236 ierr = PetscOptionsReal("-ts_atol","Absolute tolerance for local truncation error","TSSetTolerances",ts->atol,&ts->atol,NULL);CHKERRQ(ierr); 237 238 #if defined(PETSC_HAVE_SAWS) 239 { 240 PetscBool set; 241 flg = PETSC_FALSE; 242 ierr = PetscOptionsBool("-ts_saws_block","Block for SAWs memory snooper at end of TSSolve","PetscObjectSAWsBlock",((PetscObject)ts)->amspublishblock,&flg,&set);CHKERRQ(ierr); 243 if (set) { 244 ierr = PetscObjectSAWsSetBlock((PetscObject)ts,flg);CHKERRQ(ierr); 245 } 246 } 247 #endif 248 249 /* Monitor options */ 250 ierr = TSMonitorSetFromOptions(ts,"-ts_monitor","Monitor time and timestep size","TSMonitorDefault",TSMonitorDefault,NULL);CHKERRQ(ierr); 251 ierr = TSMonitorSetFromOptions(ts,"-ts_monitor_solution","View the solution at each timestep","TSMonitorSolution",TSMonitorSolution,NULL);CHKERRQ(ierr); 252 ierr = TSAdjointMonitorSetFromOptions(ts,"-ts_adjoint_monitor","Monitor adjoint timestep size","TSAdjointMonitorDefault",TSAdjointMonitorDefault,NULL);CHKERRQ(ierr); 253 ierr = TSAdjointMonitorSetFromOptions(ts,"-ts_adjoint_monitor_sensi","Monitor sensitivity in the adjoint computation","TSAdjointMonitorSensi",TSAdjointMonitorSensi,NULL);CHKERRQ(ierr); 254 255 ierr = PetscOptionsString("-ts_monitor_python","Use Python function","TSMonitorSet",0,monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr); 256 if (flg) {ierr = PetscPythonMonitorSet((PetscObject)ts,monfilename);CHKERRQ(ierr);} 257 258 ierr = PetscOptionsName("-ts_monitor_lg_solution","Monitor solution graphically","TSMonitorLGSolution",&opt);CHKERRQ(ierr); 259 if (opt) { 260 TSMonitorLGCtx ctx; 261 PetscInt howoften = 1; 262 263 ierr = PetscOptionsInt("-ts_monitor_lg_solution","Monitor solution graphically","TSMonitorLGSolution",howoften,&howoften,NULL);CHKERRQ(ierr); 264 ierr = TSMonitorLGCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);CHKERRQ(ierr); 265 ierr = TSMonitorSet(ts,TSMonitorLGSolution,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 266 } 267 268 ierr = PetscOptionsName("-ts_monitor_lg_error","Monitor error graphically","TSMonitorLGError",&opt);CHKERRQ(ierr); 269 if (opt) { 270 TSMonitorLGCtx ctx; 271 PetscInt howoften = 1; 272 273 ierr = PetscOptionsInt("-ts_monitor_lg_error","Monitor error graphically","TSMonitorLGError",howoften,&howoften,NULL);CHKERRQ(ierr); 274 ierr = TSMonitorLGCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);CHKERRQ(ierr); 275 ierr = TSMonitorSet(ts,TSMonitorLGError,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 276 } 277 278 ierr = PetscOptionsName("-ts_monitor_lg_timestep","Monitor timestep size graphically","TSMonitorLGTimeStep",&opt);CHKERRQ(ierr); 279 if (opt) { 280 TSMonitorLGCtx ctx; 281 PetscInt howoften = 1; 282 283 ierr = PetscOptionsInt("-ts_monitor_lg_timestep","Monitor timestep size graphically","TSMonitorLGTimeStep",howoften,&howoften,NULL);CHKERRQ(ierr); 284 ierr = TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);CHKERRQ(ierr); 285 ierr = TSMonitorSet(ts,TSMonitorLGTimeStep,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 286 } 287 ierr = PetscOptionsName("-ts_monitor_lg_timestep_log","Monitor log timestep size graphically","TSMonitorLGTimeStep",&opt);CHKERRQ(ierr); 288 if (opt) { 289 TSMonitorLGCtx ctx; 290 PetscInt howoften = 1; 291 292 ierr = PetscOptionsInt("-ts_monitor_lg_timestep_log","Monitor log timestep size graphically","TSMonitorLGTimeStep",howoften,&howoften,NULL);CHKERRQ(ierr); 293 ierr = TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);CHKERRQ(ierr); 294 ierr = TSMonitorSet(ts,TSMonitorLGTimeStep,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 295 ctx->semilogy = PETSC_TRUE; 296 } 297 298 ierr = PetscOptionsName("-ts_monitor_lg_snes_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGSNESIterations",&opt);CHKERRQ(ierr); 299 if (opt) { 300 TSMonitorLGCtx ctx; 301 PetscInt howoften = 1; 302 303 ierr = PetscOptionsInt("-ts_monitor_lg_snes_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGSNESIterations",howoften,&howoften,NULL);CHKERRQ(ierr); 304 ierr = TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);CHKERRQ(ierr); 305 ierr = TSMonitorSet(ts,TSMonitorLGSNESIterations,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 306 } 307 ierr = PetscOptionsName("-ts_monitor_lg_ksp_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGKSPIterations",&opt);CHKERRQ(ierr); 308 if (opt) { 309 TSMonitorLGCtx ctx; 310 PetscInt howoften = 1; 311 312 ierr = PetscOptionsInt("-ts_monitor_lg_ksp_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGKSPIterations",howoften,&howoften,NULL);CHKERRQ(ierr); 313 ierr = TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);CHKERRQ(ierr); 314 ierr = TSMonitorSet(ts,TSMonitorLGKSPIterations,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 315 } 316 ierr = PetscOptionsName("-ts_monitor_sp_eig","Monitor eigenvalues of linearized operator graphically","TSMonitorSPEig",&opt);CHKERRQ(ierr); 317 if (opt) { 318 TSMonitorSPEigCtx ctx; 319 PetscInt howoften = 1; 320 321 ierr = PetscOptionsInt("-ts_monitor_sp_eig","Monitor eigenvalues of linearized operator graphically","TSMonitorSPEig",howoften,&howoften,NULL);CHKERRQ(ierr); 322 ierr = TSMonitorSPEigCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);CHKERRQ(ierr); 323 ierr = TSMonitorSet(ts,TSMonitorSPEig,ctx,(PetscErrorCode (*)(void**))TSMonitorSPEigCtxDestroy);CHKERRQ(ierr); 324 } 325 opt = PETSC_FALSE; 326 ierr = PetscOptionsName("-ts_monitor_draw_solution","Monitor solution graphically","TSMonitorDrawSolution",&opt);CHKERRQ(ierr); 327 if (opt) { 328 TSMonitorDrawCtx ctx; 329 PetscInt howoften = 1; 330 331 ierr = PetscOptionsInt("-ts_monitor_draw_solution","Monitor solution graphically","TSMonitorDrawSolution",howoften,&howoften,NULL);CHKERRQ(ierr); 332 ierr = TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);CHKERRQ(ierr); 333 ierr = TSMonitorSet(ts,TSMonitorDrawSolution,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);CHKERRQ(ierr); 334 } 335 opt = PETSC_FALSE; 336 ierr = PetscOptionsName("-ts_adjoint_monitor_draw_sensi","Monitor adjoint sensitivities (lambda only) graphically","TSAdjointMonitorDrawSensi",&opt);CHKERRQ(ierr); 337 if (opt) { 338 TSMonitorDrawCtx ctx; 339 PetscInt howoften = 1; 340 341 ierr = PetscOptionsInt("-ts_adjoint_monitor_draw_sensi","Monitor adjoint sensitivities (lambda only) graphically","TSAdjointMonitorDrawSensi",howoften,&howoften,NULL);CHKERRQ(ierr); 342 ierr = TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);CHKERRQ(ierr); 343 ierr = TSAdjointMonitorSet(ts,TSAdjointMonitorDrawSensi,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);CHKERRQ(ierr); 344 } 345 opt = PETSC_FALSE; 346 ierr = PetscOptionsName("-ts_monitor_draw_solution_phase","Monitor solution graphically","TSMonitorDrawSolutionPhase",&opt);CHKERRQ(ierr); 347 if (opt) { 348 TSMonitorDrawCtx ctx; 349 PetscReal bounds[4]; 350 PetscInt n = 4; 351 PetscDraw draw; 352 PetscDrawAxis axis; 353 354 ierr = PetscOptionsRealArray("-ts_monitor_draw_solution_phase","Monitor solution graphically","TSMonitorDrawSolutionPhase",bounds,&n,NULL);CHKERRQ(ierr); 355 if (n != 4) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Must provide bounding box of phase field"); 356 ierr = TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,1,&ctx);CHKERRQ(ierr); 357 ierr = PetscViewerDrawGetDraw(ctx->viewer,0,&draw);CHKERRQ(ierr); 358 ierr = PetscViewerDrawGetDrawAxis(ctx->viewer,0,&axis);CHKERRQ(ierr); 359 ierr = PetscDrawAxisSetLimits(axis,bounds[0],bounds[2],bounds[1],bounds[3]);CHKERRQ(ierr); 360 ierr = PetscDrawAxisSetLabels(axis,"Phase Diagram","Variable 1","Variable 2");CHKERRQ(ierr); 361 ierr = TSMonitorSet(ts,TSMonitorDrawSolutionPhase,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);CHKERRQ(ierr); 362 } 363 opt = PETSC_FALSE; 364 ierr = PetscOptionsName("-ts_monitor_draw_error","Monitor error graphically","TSMonitorDrawError",&opt);CHKERRQ(ierr); 365 if (opt) { 366 TSMonitorDrawCtx ctx; 367 PetscInt howoften = 1; 368 369 ierr = PetscOptionsInt("-ts_monitor_draw_error","Monitor error graphically","TSMonitorDrawError",howoften,&howoften,NULL);CHKERRQ(ierr); 370 ierr = TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);CHKERRQ(ierr); 371 ierr = TSMonitorSet(ts,TSMonitorDrawError,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);CHKERRQ(ierr); 372 } 373 374 opt = PETSC_FALSE; 375 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); 376 if (flg) { 377 const char *ptr,*ptr2; 378 char *filetemplate; 379 if (!monfilename[0]) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"-ts_monitor_solution_vtk requires a file template, e.g. filename-%%03D.vts"); 380 /* Do some cursory validation of the input. */ 381 ierr = PetscStrstr(monfilename,"%",(char**)&ptr);CHKERRQ(ierr); 382 if (!ptr) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"-ts_monitor_solution_vtk requires a file template, e.g. filename-%%03D.vts"); 383 for (ptr++; ptr && *ptr; ptr++) { 384 ierr = PetscStrchr("DdiouxX",*ptr,(char**)&ptr2);CHKERRQ(ierr); 385 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"); 386 if (ptr2) break; 387 } 388 ierr = PetscStrallocpy(monfilename,&filetemplate);CHKERRQ(ierr); 389 ierr = TSMonitorSet(ts,TSMonitorSolutionVTK,filetemplate,(PetscErrorCode (*)(void**))TSMonitorSolutionVTKDestroy);CHKERRQ(ierr); 390 } 391 392 ierr = PetscOptionsString("-ts_monitor_dmda_ray","Display a ray of the solution","None","y=0",dir,16,&flg);CHKERRQ(ierr); 393 if (flg) { 394 TSMonitorDMDARayCtx *rayctx; 395 int ray = 0; 396 DMDADirection ddir; 397 DM da; 398 PetscMPIInt rank; 399 400 if (dir[1] != '=') SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Unknown ray %s",dir); 401 if (dir[0] == 'x') ddir = DMDA_X; 402 else if (dir[0] == 'y') ddir = DMDA_Y; 403 else SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Unknown ray %s",dir); 404 sscanf(dir+2,"%d",&ray); 405 406 ierr = PetscInfo2(((PetscObject)ts),"Displaying DMDA ray %c = %D\n",dir[0],ray);CHKERRQ(ierr); 407 ierr = PetscNew(&rayctx);CHKERRQ(ierr); 408 ierr = TSGetDM(ts,&da);CHKERRQ(ierr); 409 ierr = DMDAGetRay(da,ddir,ray,&rayctx->ray,&rayctx->scatter);CHKERRQ(ierr); 410 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)ts),&rank);CHKERRQ(ierr); 411 if (!rank) { 412 ierr = PetscViewerDrawOpen(PETSC_COMM_SELF,0,0,0,0,600,300,&rayctx->viewer);CHKERRQ(ierr); 413 } 414 rayctx->lgctx = NULL; 415 ierr = TSMonitorSet(ts,TSMonitorDMDARay,rayctx,TSMonitorDMDARayDestroy);CHKERRQ(ierr); 416 } 417 ierr = PetscOptionsString("-ts_monitor_lg_dmda_ray","Display a ray of the solution","None","x=0",dir,16,&flg);CHKERRQ(ierr); 418 if (flg) { 419 TSMonitorDMDARayCtx *rayctx; 420 int ray = 0; 421 DMDADirection ddir; 422 DM da; 423 PetscInt howoften = 1; 424 425 if (dir[1] != '=') SETERRQ1(PetscObjectComm((PetscObject) ts), PETSC_ERR_ARG_WRONG, "Malformed ray %s", dir); 426 if (dir[0] == 'x') ddir = DMDA_X; 427 else if (dir[0] == 'y') ddir = DMDA_Y; 428 else SETERRQ1(PetscObjectComm((PetscObject) ts), PETSC_ERR_ARG_WRONG, "Unknown ray direction %s", dir); 429 sscanf(dir+2, "%d", &ray); 430 431 ierr = PetscInfo2(((PetscObject) ts),"Displaying LG DMDA ray %c = %D\n", dir[0], ray);CHKERRQ(ierr); 432 ierr = PetscNew(&rayctx);CHKERRQ(ierr); 433 ierr = TSGetDM(ts, &da);CHKERRQ(ierr); 434 ierr = DMDAGetRay(da, ddir, ray, &rayctx->ray, &rayctx->scatter);CHKERRQ(ierr); 435 ierr = TSMonitorLGCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,600,400,howoften,&rayctx->lgctx);CHKERRQ(ierr); 436 ierr = TSMonitorSet(ts, TSMonitorLGDMDARay, rayctx, TSMonitorDMDARayDestroy);CHKERRQ(ierr); 437 } 438 439 ierr = PetscOptionsName("-ts_monitor_envelope","Monitor maximum and minimum value of each component of the solution","TSMonitorEnvelope",&opt);CHKERRQ(ierr); 440 if (opt) { 441 TSMonitorEnvelopeCtx ctx; 442 443 ierr = TSMonitorEnvelopeCtxCreate(ts,&ctx);CHKERRQ(ierr); 444 ierr = TSMonitorSet(ts,TSMonitorEnvelope,ctx,(PetscErrorCode (*)(void**))TSMonitorEnvelopeCtxDestroy);CHKERRQ(ierr); 445 } 446 447 flg = PETSC_FALSE; 448 ierr = PetscOptionsBool("-ts_fd_color", "Use finite differences with coloring to compute IJacobian", "TSComputeJacobianDefaultColor", flg, &flg, NULL);CHKERRQ(ierr); 449 if (flg) { 450 DM dm; 451 DMTS tdm; 452 453 ierr = TSGetDM(ts, &dm);CHKERRQ(ierr); 454 ierr = DMGetDMTS(dm, &tdm);CHKERRQ(ierr); 455 tdm->ijacobianctx = NULL; 456 ierr = TSSetIJacobian(ts, NULL, NULL, TSComputeIJacobianDefaultColor, 0);CHKERRQ(ierr); 457 ierr = PetscInfo(ts, "Setting default finite difference coloring Jacobian matrix\n");CHKERRQ(ierr); 458 } 459 460 /* Handle specific TS options */ 461 if (ts->ops->setfromoptions) { 462 ierr = (*ts->ops->setfromoptions)(PetscOptionsObject,ts);CHKERRQ(ierr); 463 } 464 465 /* Handle TSAdapt options */ 466 ierr = TSGetAdapt(ts,&ts->adapt);CHKERRQ(ierr); 467 ierr = TSAdaptSetDefaultType(ts->adapt,ts->default_adapt_type);CHKERRQ(ierr); 468 ierr = TSAdaptSetFromOptions(PetscOptionsObject,ts->adapt);CHKERRQ(ierr); 469 470 /* TS trajectory must be set after TS, since it may use some TS options above */ 471 tflg = ts->trajectory ? PETSC_TRUE : PETSC_FALSE; 472 ierr = PetscOptionsBool("-ts_save_trajectory","Save the solution at each timestep","TSSetSaveTrajectory",tflg,&tflg,NULL);CHKERRQ(ierr); 473 if (tflg) { 474 ierr = TSSetSaveTrajectory(ts);CHKERRQ(ierr); 475 } 476 tflg = ts->adjoint_solve ? PETSC_TRUE : PETSC_FALSE; 477 ierr = PetscOptionsBool("-ts_adjoint_solve","Solve the adjoint problem immediately after solving the forward problem","",tflg,&tflg,&flg);CHKERRQ(ierr); 478 if (flg) { 479 ierr = TSSetSaveTrajectory(ts);CHKERRQ(ierr); 480 ts->adjoint_solve = tflg; 481 } 482 483 /* process any options handlers added with PetscObjectAddOptionsHandler() */ 484 ierr = PetscObjectProcessOptionsHandlers(PetscOptionsObject,(PetscObject)ts);CHKERRQ(ierr); 485 ierr = PetscOptionsEnd();CHKERRQ(ierr); 486 487 if (ts->trajectory) { 488 ierr = TSTrajectorySetFromOptions(ts->trajectory,ts);CHKERRQ(ierr); 489 } 490 491 ierr = TSGetSNES(ts,&ts->snes);CHKERRQ(ierr); 492 if (ts->problem_type == TS_LINEAR) {ierr = SNESSetType(ts->snes,SNESKSPONLY);CHKERRQ(ierr);} 493 ierr = SNESSetFromOptions(ts->snes);CHKERRQ(ierr); 494 PetscFunctionReturn(0); 495 } 496 497 /*@ 498 TSGetTrajectory - Gets the trajectory from a TS if it exists 499 500 Collective on TS 501 502 Input Parameters: 503 . ts - the TS context obtained from TSCreate() 504 505 Output Parameters; 506 . tr - the TSTrajectory object, if it exists 507 508 Note: This routine should be called after all TS options have been set 509 510 Level: advanced 511 512 .seealso: TSGetTrajectory(), TSAdjointSolve(), TSTrajectory, TSTrajectoryCreate() 513 514 .keywords: TS, set, checkpoint, 515 @*/ 516 PetscErrorCode TSGetTrajectory(TS ts,TSTrajectory *tr) 517 { 518 PetscFunctionBegin; 519 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 520 *tr = ts->trajectory; 521 PetscFunctionReturn(0); 522 } 523 524 /*@ 525 TSSetSaveTrajectory - Causes the TS to save its solutions as it iterates forward in time in a TSTrajectory object 526 527 Collective on TS 528 529 Input Parameters: 530 . ts - the TS context obtained from TSCreate() 531 532 Options Database: 533 + -ts_save_trajectory - saves the trajectory to a file 534 - -ts_trajectory_type type 535 536 Note: This routine should be called after all TS options have been set 537 538 The TSTRAJECTORYVISUALIZATION files can be loaded into Python with $PETSC_DIR/bin/PetscBinaryIOTrajectory.py and 539 MATLAB with $PETSC_DIR/share/petsc/matlab/PetscReadBinaryTrajectory.m 540 541 Level: intermediate 542 543 .seealso: TSGetTrajectory(), TSAdjointSolve(), TSTrajectoryType, TSSetTrajectoryType() 544 545 .keywords: TS, set, checkpoint, 546 @*/ 547 PetscErrorCode TSSetSaveTrajectory(TS ts) 548 { 549 PetscErrorCode ierr; 550 551 PetscFunctionBegin; 552 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 553 if (!ts->trajectory) { 554 ierr = TSTrajectoryCreate(PetscObjectComm((PetscObject)ts),&ts->trajectory);CHKERRQ(ierr); 555 } 556 PetscFunctionReturn(0); 557 } 558 559 /*@ 560 TSComputeRHSJacobian - Computes the Jacobian matrix that has been 561 set with TSSetRHSJacobian(). 562 563 Collective on TS and Vec 564 565 Input Parameters: 566 + ts - the TS context 567 . t - current timestep 568 - U - input vector 569 570 Output Parameters: 571 + A - Jacobian matrix 572 . B - optional preconditioning matrix 573 - flag - flag indicating matrix structure 574 575 Notes: 576 Most users should not need to explicitly call this routine, as it 577 is used internally within the nonlinear solvers. 578 579 See KSPSetOperators() for important information about setting the 580 flag parameter. 581 582 Level: developer 583 584 .keywords: SNES, compute, Jacobian, matrix 585 586 .seealso: TSSetRHSJacobian(), KSPSetOperators() 587 @*/ 588 PetscErrorCode TSComputeRHSJacobian(TS ts,PetscReal t,Vec U,Mat A,Mat B) 589 { 590 PetscErrorCode ierr; 591 PetscObjectState Ustate; 592 PetscObjectId Uid; 593 DM dm; 594 DMTS tsdm; 595 TSRHSJacobian rhsjacobianfunc; 596 void *ctx; 597 TSIJacobian ijacobianfunc; 598 TSRHSFunction rhsfunction; 599 600 PetscFunctionBegin; 601 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 602 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 603 PetscCheckSameComm(ts,1,U,3); 604 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 605 ierr = DMGetDMTS(dm,&tsdm);CHKERRQ(ierr); 606 ierr = DMTSGetRHSJacobian(dm,&rhsjacobianfunc,&ctx);CHKERRQ(ierr); 607 ierr = DMTSGetIJacobian(dm,&ijacobianfunc,NULL);CHKERRQ(ierr); 608 ierr = DMTSGetRHSFunction(dm,&rhsfunction,&ctx);CHKERRQ(ierr); 609 ierr = PetscObjectStateGet((PetscObject)U,&Ustate);CHKERRQ(ierr); 610 ierr = PetscObjectGetId((PetscObject)U,&Uid);CHKERRQ(ierr); 611 if (ts->rhsjacobian.time == t && (ts->problem_type == TS_LINEAR || (ts->rhsjacobian.Xid == Uid && ts->rhsjacobian.Xstate == Ustate)) && (rhsfunction != TSComputeRHSFunctionLinear)) { 612 PetscFunctionReturn(0); 613 } 614 615 if (!rhsjacobianfunc && !ijacobianfunc) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSJacobian() and / or TSSetIJacobian()"); 616 617 if (ts->rhsjacobian.reuse) { 618 ierr = MatShift(A,-ts->rhsjacobian.shift);CHKERRQ(ierr); 619 ierr = MatScale(A,1./ts->rhsjacobian.scale);CHKERRQ(ierr); 620 if (B && A != B) { 621 ierr = MatShift(B,-ts->rhsjacobian.shift);CHKERRQ(ierr); 622 ierr = MatScale(B,1./ts->rhsjacobian.scale);CHKERRQ(ierr); 623 } 624 ts->rhsjacobian.shift = 0; 625 ts->rhsjacobian.scale = 1.; 626 } 627 628 if (rhsjacobianfunc) { 629 PetscBool missing; 630 ierr = PetscLogEventBegin(TS_JacobianEval,ts,U,A,B);CHKERRQ(ierr); 631 PetscStackPush("TS user Jacobian function"); 632 ierr = (*rhsjacobianfunc)(ts,t,U,A,B,ctx);CHKERRQ(ierr); 633 PetscStackPop; 634 ierr = PetscLogEventEnd(TS_JacobianEval,ts,U,A,B);CHKERRQ(ierr); 635 if (A) { 636 ierr = MatMissingDiagonal(A,&missing,NULL);CHKERRQ(ierr); 637 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"); 638 } 639 if (B && B != A) { 640 ierr = MatMissingDiagonal(B,&missing,NULL);CHKERRQ(ierr); 641 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"); 642 } 643 } else { 644 ierr = MatZeroEntries(A);CHKERRQ(ierr); 645 if (A != B) {ierr = MatZeroEntries(B);CHKERRQ(ierr);} 646 } 647 ts->rhsjacobian.time = t; 648 ierr = PetscObjectGetId((PetscObject)U,&ts->rhsjacobian.Xid);CHKERRQ(ierr); 649 ierr = PetscObjectStateGet((PetscObject)U,&ts->rhsjacobian.Xstate);CHKERRQ(ierr); 650 PetscFunctionReturn(0); 651 } 652 653 /*@ 654 TSComputeRHSFunction - Evaluates the right-hand-side function. 655 656 Collective on TS and Vec 657 658 Input Parameters: 659 + ts - the TS context 660 . t - current time 661 - U - state vector 662 663 Output Parameter: 664 . y - right hand side 665 666 Note: 667 Most users should not need to explicitly call this routine, as it 668 is used internally within the nonlinear solvers. 669 670 Level: developer 671 672 .keywords: TS, compute 673 674 .seealso: TSSetRHSFunction(), TSComputeIFunction() 675 @*/ 676 PetscErrorCode TSComputeRHSFunction(TS ts,PetscReal t,Vec U,Vec y) 677 { 678 PetscErrorCode ierr; 679 TSRHSFunction rhsfunction; 680 TSIFunction ifunction; 681 void *ctx; 682 DM dm; 683 684 PetscFunctionBegin; 685 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 686 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 687 PetscValidHeaderSpecific(y,VEC_CLASSID,4); 688 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 689 ierr = DMTSGetRHSFunction(dm,&rhsfunction,&ctx);CHKERRQ(ierr); 690 ierr = DMTSGetIFunction(dm,&ifunction,NULL);CHKERRQ(ierr); 691 692 if (!rhsfunction && !ifunction) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSFunction() and / or TSSetIFunction()"); 693 694 ierr = PetscLogEventBegin(TS_FunctionEval,ts,U,y,0);CHKERRQ(ierr); 695 if (rhsfunction) { 696 PetscStackPush("TS user right-hand-side function"); 697 ierr = (*rhsfunction)(ts,t,U,y,ctx);CHKERRQ(ierr); 698 PetscStackPop; 699 } else { 700 ierr = VecZeroEntries(y);CHKERRQ(ierr); 701 } 702 703 ierr = PetscLogEventEnd(TS_FunctionEval,ts,U,y,0);CHKERRQ(ierr); 704 PetscFunctionReturn(0); 705 } 706 707 /*@ 708 TSComputeSolutionFunction - Evaluates the solution function. 709 710 Collective on TS and Vec 711 712 Input Parameters: 713 + ts - the TS context 714 - t - current time 715 716 Output Parameter: 717 . U - the solution 718 719 Note: 720 Most users should not need to explicitly call this routine, as it 721 is used internally within the nonlinear solvers. 722 723 Level: developer 724 725 .keywords: TS, compute 726 727 .seealso: TSSetSolutionFunction(), TSSetRHSFunction(), TSComputeIFunction() 728 @*/ 729 PetscErrorCode TSComputeSolutionFunction(TS ts,PetscReal t,Vec U) 730 { 731 PetscErrorCode ierr; 732 TSSolutionFunction solutionfunction; 733 void *ctx; 734 DM dm; 735 736 PetscFunctionBegin; 737 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 738 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 739 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 740 ierr = DMTSGetSolutionFunction(dm,&solutionfunction,&ctx);CHKERRQ(ierr); 741 742 if (solutionfunction) { 743 PetscStackPush("TS user solution function"); 744 ierr = (*solutionfunction)(ts,t,U,ctx);CHKERRQ(ierr); 745 PetscStackPop; 746 } 747 PetscFunctionReturn(0); 748 } 749 /*@ 750 TSComputeForcingFunction - Evaluates the forcing function. 751 752 Collective on TS and Vec 753 754 Input Parameters: 755 + ts - the TS context 756 - t - current time 757 758 Output Parameter: 759 . U - the function value 760 761 Note: 762 Most users should not need to explicitly call this routine, as it 763 is used internally within the nonlinear solvers. 764 765 Level: developer 766 767 .keywords: TS, compute 768 769 .seealso: TSSetSolutionFunction(), TSSetRHSFunction(), TSComputeIFunction() 770 @*/ 771 PetscErrorCode TSComputeForcingFunction(TS ts,PetscReal t,Vec U) 772 { 773 PetscErrorCode ierr, (*forcing)(TS,PetscReal,Vec,void*); 774 void *ctx; 775 DM dm; 776 777 PetscFunctionBegin; 778 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 779 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 780 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 781 ierr = DMTSGetForcingFunction(dm,&forcing,&ctx);CHKERRQ(ierr); 782 783 if (forcing) { 784 PetscStackPush("TS user forcing function"); 785 ierr = (*forcing)(ts,t,U,ctx);CHKERRQ(ierr); 786 PetscStackPop; 787 } 788 PetscFunctionReturn(0); 789 } 790 791 static PetscErrorCode TSGetRHSVec_Private(TS ts,Vec *Frhs) 792 { 793 Vec F; 794 PetscErrorCode ierr; 795 796 PetscFunctionBegin; 797 *Frhs = NULL; 798 ierr = TSGetIFunction(ts,&F,NULL,NULL);CHKERRQ(ierr); 799 if (!ts->Frhs) { 800 ierr = VecDuplicate(F,&ts->Frhs);CHKERRQ(ierr); 801 } 802 *Frhs = ts->Frhs; 803 PetscFunctionReturn(0); 804 } 805 806 static PetscErrorCode TSGetRHSMats_Private(TS ts,Mat *Arhs,Mat *Brhs) 807 { 808 Mat A,B; 809 PetscErrorCode ierr; 810 TSIJacobian ijacobian; 811 812 PetscFunctionBegin; 813 if (Arhs) *Arhs = NULL; 814 if (Brhs) *Brhs = NULL; 815 ierr = TSGetIJacobian(ts,&A,&B,&ijacobian,NULL);CHKERRQ(ierr); 816 if (Arhs) { 817 if (!ts->Arhs) { 818 if (ijacobian) { 819 ierr = MatDuplicate(A,MAT_DO_NOT_COPY_VALUES,&ts->Arhs);CHKERRQ(ierr); 820 } else { 821 ts->Arhs = A; 822 ierr = PetscObjectReference((PetscObject)A);CHKERRQ(ierr); 823 } 824 } else { 825 PetscBool flg; 826 ierr = SNESGetUseMatrixFree(ts->snes,NULL,&flg);CHKERRQ(ierr); 827 /* Handle case where user provided only RHSJacobian and used -snes_mf_operator */ 828 if (flg && !ijacobian && ts->Arhs == ts->Brhs){ 829 ierr = PetscObjectDereference((PetscObject)ts->Arhs);CHKERRQ(ierr); 830 ts->Arhs = A; 831 ierr = PetscObjectReference((PetscObject)A);CHKERRQ(ierr); 832 } 833 } 834 *Arhs = ts->Arhs; 835 } 836 if (Brhs) { 837 if (!ts->Brhs) { 838 if (A != B) { 839 if (ijacobian) { 840 ierr = MatDuplicate(B,MAT_DO_NOT_COPY_VALUES,&ts->Brhs);CHKERRQ(ierr); 841 } else { 842 ts->Brhs = B; 843 ierr = PetscObjectReference((PetscObject)B);CHKERRQ(ierr); 844 } 845 } else { 846 ierr = PetscObjectReference((PetscObject)ts->Arhs);CHKERRQ(ierr); 847 ts->Brhs = ts->Arhs; 848 } 849 } 850 *Brhs = ts->Brhs; 851 } 852 PetscFunctionReturn(0); 853 } 854 855 /*@ 856 TSComputeIFunction - Evaluates the DAE residual written in implicit form F(t,U,Udot)=0 857 858 Collective on TS and Vec 859 860 Input Parameters: 861 + ts - the TS context 862 . t - current time 863 . U - state vector 864 . Udot - time derivative of state vector 865 - imex - flag indicates if the method is IMEX so that the RHSFunction should be kept separate 866 867 Output Parameter: 868 . Y - right hand side 869 870 Note: 871 Most users should not need to explicitly call this routine, as it 872 is used internally within the nonlinear solvers. 873 874 If the user did did not write their equations in implicit form, this 875 function recasts them in implicit form. 876 877 Level: developer 878 879 .keywords: TS, compute 880 881 .seealso: TSSetIFunction(), TSComputeRHSFunction() 882 @*/ 883 PetscErrorCode TSComputeIFunction(TS ts,PetscReal t,Vec U,Vec Udot,Vec Y,PetscBool imex) 884 { 885 PetscErrorCode ierr; 886 TSIFunction ifunction; 887 TSRHSFunction rhsfunction; 888 void *ctx; 889 DM dm; 890 891 PetscFunctionBegin; 892 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 893 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 894 PetscValidHeaderSpecific(Udot,VEC_CLASSID,4); 895 PetscValidHeaderSpecific(Y,VEC_CLASSID,5); 896 897 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 898 ierr = DMTSGetIFunction(dm,&ifunction,&ctx);CHKERRQ(ierr); 899 ierr = DMTSGetRHSFunction(dm,&rhsfunction,NULL);CHKERRQ(ierr); 900 901 if (!rhsfunction && !ifunction) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSFunction() and / or TSSetIFunction()"); 902 903 ierr = PetscLogEventBegin(TS_FunctionEval,ts,U,Udot,Y);CHKERRQ(ierr); 904 if (ifunction) { 905 PetscStackPush("TS user implicit function"); 906 ierr = (*ifunction)(ts,t,U,Udot,Y,ctx);CHKERRQ(ierr); 907 PetscStackPop; 908 } 909 if (imex) { 910 if (!ifunction) { 911 ierr = VecCopy(Udot,Y);CHKERRQ(ierr); 912 } 913 } else if (rhsfunction) { 914 if (ifunction) { 915 Vec Frhs; 916 ierr = TSGetRHSVec_Private(ts,&Frhs);CHKERRQ(ierr); 917 ierr = TSComputeRHSFunction(ts,t,U,Frhs);CHKERRQ(ierr); 918 ierr = VecAXPY(Y,-1,Frhs);CHKERRQ(ierr); 919 } else { 920 ierr = TSComputeRHSFunction(ts,t,U,Y);CHKERRQ(ierr); 921 ierr = VecAYPX(Y,-1,Udot);CHKERRQ(ierr); 922 } 923 } 924 ierr = PetscLogEventEnd(TS_FunctionEval,ts,U,Udot,Y);CHKERRQ(ierr); 925 PetscFunctionReturn(0); 926 } 927 928 /*@ 929 TSComputeIJacobian - Evaluates the Jacobian of the DAE 930 931 Collective on TS and Vec 932 933 Input 934 Input Parameters: 935 + ts - the TS context 936 . t - current timestep 937 . U - state vector 938 . Udot - time derivative of state vector 939 . shift - shift to apply, see note below 940 - imex - flag indicates if the method is IMEX so that the RHSJacobian should be kept separate 941 942 Output Parameters: 943 + A - Jacobian matrix 944 - B - matrix from which the preconditioner is constructed; often the same as A 945 946 Notes: 947 If F(t,U,Udot)=0 is the DAE, the required Jacobian is 948 949 dF/dU + shift*dF/dUdot 950 951 Most users should not need to explicitly call this routine, as it 952 is used internally within the nonlinear solvers. 953 954 Level: developer 955 956 .keywords: TS, compute, Jacobian, matrix 957 958 .seealso: TSSetIJacobian() 959 @*/ 960 PetscErrorCode TSComputeIJacobian(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat A,Mat B,PetscBool imex) 961 { 962 PetscErrorCode ierr; 963 TSIJacobian ijacobian; 964 TSRHSJacobian rhsjacobian; 965 DM dm; 966 void *ctx; 967 968 PetscFunctionBegin; 969 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 970 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 971 PetscValidHeaderSpecific(Udot,VEC_CLASSID,4); 972 PetscValidPointer(A,6); 973 PetscValidHeaderSpecific(A,MAT_CLASSID,6); 974 PetscValidPointer(B,7); 975 PetscValidHeaderSpecific(B,MAT_CLASSID,7); 976 977 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 978 ierr = DMTSGetIJacobian(dm,&ijacobian,&ctx);CHKERRQ(ierr); 979 ierr = DMTSGetRHSJacobian(dm,&rhsjacobian,NULL);CHKERRQ(ierr); 980 981 if (!rhsjacobian && !ijacobian) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSJacobian() and / or TSSetIJacobian()"); 982 983 ierr = PetscLogEventBegin(TS_JacobianEval,ts,U,A,B);CHKERRQ(ierr); 984 if (ijacobian) { 985 PetscBool missing; 986 PetscStackPush("TS user implicit Jacobian"); 987 ierr = (*ijacobian)(ts,t,U,Udot,shift,A,B,ctx);CHKERRQ(ierr); 988 PetscStackPop; 989 ierr = MatMissingDiagonal(A,&missing,NULL);CHKERRQ(ierr); 990 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"); 991 if (B != A) { 992 ierr = MatMissingDiagonal(B,&missing,NULL);CHKERRQ(ierr); 993 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"); 994 } 995 } 996 if (imex) { 997 if (!ijacobian) { /* system was written as Udot = G(t,U) */ 998 PetscBool assembled; 999 ierr = MatZeroEntries(A);CHKERRQ(ierr); 1000 ierr = MatAssembled(A,&assembled);CHKERRQ(ierr); 1001 if (!assembled) { 1002 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1003 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1004 } 1005 ierr = MatShift(A,shift);CHKERRQ(ierr); 1006 if (A != B) { 1007 ierr = MatZeroEntries(B);CHKERRQ(ierr); 1008 ierr = MatAssembled(B,&assembled);CHKERRQ(ierr); 1009 if (!assembled) { 1010 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1011 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1012 } 1013 ierr = MatShift(B,shift);CHKERRQ(ierr); 1014 } 1015 } 1016 } else { 1017 Mat Arhs = NULL,Brhs = NULL; 1018 if (rhsjacobian) { 1019 ierr = TSGetRHSMats_Private(ts,&Arhs,&Brhs);CHKERRQ(ierr); 1020 ierr = TSComputeRHSJacobian(ts,t,U,Arhs,Brhs);CHKERRQ(ierr); 1021 } 1022 if (Arhs == A) { /* No IJacobian, so we only have the RHS matrix */ 1023 PetscBool flg; 1024 ts->rhsjacobian.scale = -1; 1025 ts->rhsjacobian.shift = shift; 1026 ierr = SNESGetUseMatrixFree(ts->snes,NULL,&flg);CHKERRQ(ierr); 1027 /* since -snes_mf_operator uses the full SNES function it does not need to be shifted or scaled here */ 1028 if (!flg) { 1029 ierr = MatScale(A,-1);CHKERRQ(ierr); 1030 ierr = MatShift(A,shift);CHKERRQ(ierr); 1031 } 1032 if (A != B) { 1033 ierr = MatScale(B,-1);CHKERRQ(ierr); 1034 ierr = MatShift(B,shift);CHKERRQ(ierr); 1035 } 1036 } else if (Arhs) { /* Both IJacobian and RHSJacobian */ 1037 MatStructure axpy = DIFFERENT_NONZERO_PATTERN; 1038 if (!ijacobian) { /* No IJacobian provided, but we have a separate RHS matrix */ 1039 ierr = MatZeroEntries(A);CHKERRQ(ierr); 1040 ierr = MatShift(A,shift);CHKERRQ(ierr); 1041 if (A != B) { 1042 ierr = MatZeroEntries(B);CHKERRQ(ierr); 1043 ierr = MatShift(B,shift);CHKERRQ(ierr); 1044 } 1045 } 1046 ierr = MatAXPY(A,-1,Arhs,axpy);CHKERRQ(ierr); 1047 if (A != B) { 1048 ierr = MatAXPY(B,-1,Brhs,axpy);CHKERRQ(ierr); 1049 } 1050 } 1051 } 1052 ierr = PetscLogEventEnd(TS_JacobianEval,ts,U,A,B);CHKERRQ(ierr); 1053 PetscFunctionReturn(0); 1054 } 1055 1056 /*@C 1057 TSSetRHSFunction - Sets the routine for evaluating the function, 1058 where U_t = G(t,u). 1059 1060 Logically Collective on TS 1061 1062 Input Parameters: 1063 + ts - the TS context obtained from TSCreate() 1064 . r - vector to put the computed right hand side (or NULL to have it created) 1065 . f - routine for evaluating the right-hand-side function 1066 - ctx - [optional] user-defined context for private data for the 1067 function evaluation routine (may be NULL) 1068 1069 Calling sequence of func: 1070 $ func (TS ts,PetscReal t,Vec u,Vec F,void *ctx); 1071 1072 + t - current timestep 1073 . u - input vector 1074 . F - function vector 1075 - ctx - [optional] user-defined function context 1076 1077 Level: beginner 1078 1079 Notes: You must call this function or TSSetIFunction() to define your ODE. You cannot use this function when solving a DAE. 1080 1081 .keywords: TS, timestep, set, right-hand-side, function 1082 1083 .seealso: TSSetRHSJacobian(), TSSetIJacobian(), TSSetIFunction() 1084 @*/ 1085 PetscErrorCode TSSetRHSFunction(TS ts,Vec r,PetscErrorCode (*f)(TS,PetscReal,Vec,Vec,void*),void *ctx) 1086 { 1087 PetscErrorCode ierr; 1088 SNES snes; 1089 Vec ralloc = NULL; 1090 DM dm; 1091 1092 PetscFunctionBegin; 1093 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1094 if (r) PetscValidHeaderSpecific(r,VEC_CLASSID,2); 1095 1096 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1097 ierr = DMTSSetRHSFunction(dm,f,ctx);CHKERRQ(ierr); 1098 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1099 if (!r && !ts->dm && ts->vec_sol) { 1100 ierr = VecDuplicate(ts->vec_sol,&ralloc);CHKERRQ(ierr); 1101 r = ralloc; 1102 } 1103 ierr = SNESSetFunction(snes,r,SNESTSFormFunction,ts);CHKERRQ(ierr); 1104 ierr = VecDestroy(&ralloc);CHKERRQ(ierr); 1105 PetscFunctionReturn(0); 1106 } 1107 1108 /*@C 1109 TSSetSolutionFunction - Provide a function that computes the solution of the ODE or DAE 1110 1111 Logically Collective on TS 1112 1113 Input Parameters: 1114 + ts - the TS context obtained from TSCreate() 1115 . f - routine for evaluating the solution 1116 - ctx - [optional] user-defined context for private data for the 1117 function evaluation routine (may be NULL) 1118 1119 Calling sequence of func: 1120 $ func (TS ts,PetscReal t,Vec u,void *ctx); 1121 1122 + t - current timestep 1123 . u - output vector 1124 - ctx - [optional] user-defined function context 1125 1126 Notes: 1127 This routine is used for testing accuracy of time integration schemes when you already know the solution. 1128 If analytic solutions are not known for your system, consider using the Method of Manufactured Solutions to 1129 create closed-form solutions with non-physical forcing terms. 1130 1131 For low-dimensional problems solved in serial, such as small discrete systems, TSMonitorLGError() can be used to monitor the error history. 1132 1133 Level: beginner 1134 1135 .keywords: TS, timestep, set, right-hand-side, function 1136 1137 .seealso: TSSetRHSJacobian(), TSSetIJacobian(), TSComputeSolutionFunction(), TSSetForcingFunction() 1138 @*/ 1139 PetscErrorCode TSSetSolutionFunction(TS ts,PetscErrorCode (*f)(TS,PetscReal,Vec,void*),void *ctx) 1140 { 1141 PetscErrorCode ierr; 1142 DM dm; 1143 1144 PetscFunctionBegin; 1145 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1146 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1147 ierr = DMTSSetSolutionFunction(dm,f,ctx);CHKERRQ(ierr); 1148 PetscFunctionReturn(0); 1149 } 1150 1151 /*@C 1152 TSSetForcingFunction - Provide a function that computes a forcing term for a ODE or PDE 1153 1154 Logically Collective on TS 1155 1156 Input Parameters: 1157 + ts - the TS context obtained from TSCreate() 1158 . func - routine for evaluating the forcing function 1159 - ctx - [optional] user-defined context for private data for the 1160 function evaluation routine (may be NULL) 1161 1162 Calling sequence of func: 1163 $ func (TS ts,PetscReal t,Vec f,void *ctx); 1164 1165 + t - current timestep 1166 . f - output vector 1167 - ctx - [optional] user-defined function context 1168 1169 Notes: 1170 This routine is useful for testing accuracy of time integration schemes when using the Method of Manufactured Solutions to 1171 create closed-form solutions with a non-physical forcing term. It allows you to use the Method of Manufactored Solution without directly editing the 1172 definition of the problem you are solving and hence possibly introducing bugs. 1173 1174 This replaces the ODE F(u,u_t,t) = 0 the TS is solving with F(u,u_t,t) - func(t) = 0 1175 1176 This forcing function does not depend on the solution to the equations, it can only depend on spatial location, time, and possibly parameters, the 1177 parameters can be passed in the ctx variable. 1178 1179 For low-dimensional problems solved in serial, such as small discrete systems, TSMonitorLGError() can be used to monitor the error history. 1180 1181 Level: beginner 1182 1183 .keywords: TS, timestep, set, right-hand-side, function 1184 1185 .seealso: TSSetRHSJacobian(), TSSetIJacobian(), TSComputeSolutionFunction(), TSSetSolutionFunction() 1186 @*/ 1187 PetscErrorCode TSSetForcingFunction(TS ts,TSForcingFunction func,void *ctx) 1188 { 1189 PetscErrorCode ierr; 1190 DM dm; 1191 1192 PetscFunctionBegin; 1193 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1194 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1195 ierr = DMTSSetForcingFunction(dm,func,ctx);CHKERRQ(ierr); 1196 PetscFunctionReturn(0); 1197 } 1198 1199 /*@C 1200 TSSetRHSJacobian - Sets the function to compute the Jacobian of G, 1201 where U_t = G(U,t), as well as the location to store the matrix. 1202 1203 Logically Collective on TS 1204 1205 Input Parameters: 1206 + ts - the TS context obtained from TSCreate() 1207 . Amat - (approximate) Jacobian matrix 1208 . Pmat - matrix from which preconditioner is to be constructed (usually the same as Amat) 1209 . f - the Jacobian evaluation routine 1210 - ctx - [optional] user-defined context for private data for the 1211 Jacobian evaluation routine (may be NULL) 1212 1213 Calling sequence of f: 1214 $ func (TS ts,PetscReal t,Vec u,Mat A,Mat B,void *ctx); 1215 1216 + t - current timestep 1217 . u - input vector 1218 . Amat - (approximate) Jacobian matrix 1219 . Pmat - matrix from which preconditioner is to be constructed (usually the same as Amat) 1220 - ctx - [optional] user-defined context for matrix evaluation routine 1221 1222 Notes: 1223 You must set all the diagonal entries of the matrices, if they are zero you must still set them with a zero value 1224 1225 The TS solver may modify the nonzero structure and the entries of the matrices Amat and Pmat between the calls to f() 1226 You should not assume the values are the same in the next call to f() as you set them in the previous call. 1227 1228 Level: beginner 1229 1230 .keywords: TS, timestep, set, right-hand-side, Jacobian 1231 1232 .seealso: SNESComputeJacobianDefaultColor(), TSSetRHSFunction(), TSRHSJacobianSetReuse(), TSSetIJacobian() 1233 1234 @*/ 1235 PetscErrorCode TSSetRHSJacobian(TS ts,Mat Amat,Mat Pmat,TSRHSJacobian f,void *ctx) 1236 { 1237 PetscErrorCode ierr; 1238 SNES snes; 1239 DM dm; 1240 TSIJacobian ijacobian; 1241 1242 PetscFunctionBegin; 1243 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1244 if (Amat) PetscValidHeaderSpecific(Amat,MAT_CLASSID,2); 1245 if (Pmat) PetscValidHeaderSpecific(Pmat,MAT_CLASSID,3); 1246 if (Amat) PetscCheckSameComm(ts,1,Amat,2); 1247 if (Pmat) PetscCheckSameComm(ts,1,Pmat,3); 1248 1249 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1250 ierr = DMTSSetRHSJacobian(dm,f,ctx);CHKERRQ(ierr); 1251 if (f == TSComputeRHSJacobianConstant) { 1252 /* Handle this case automatically for the user; otherwise user should call themselves. */ 1253 ierr = TSRHSJacobianSetReuse(ts,PETSC_TRUE);CHKERRQ(ierr); 1254 } 1255 ierr = DMTSGetIJacobian(dm,&ijacobian,NULL);CHKERRQ(ierr); 1256 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1257 if (!ijacobian) { 1258 ierr = SNESSetJacobian(snes,Amat,Pmat,SNESTSFormJacobian,ts);CHKERRQ(ierr); 1259 } 1260 if (Amat) { 1261 ierr = PetscObjectReference((PetscObject)Amat);CHKERRQ(ierr); 1262 ierr = MatDestroy(&ts->Arhs);CHKERRQ(ierr); 1263 ts->Arhs = Amat; 1264 } 1265 if (Pmat) { 1266 ierr = PetscObjectReference((PetscObject)Pmat);CHKERRQ(ierr); 1267 ierr = MatDestroy(&ts->Brhs);CHKERRQ(ierr); 1268 ts->Brhs = Pmat; 1269 } 1270 PetscFunctionReturn(0); 1271 } 1272 1273 /*@C 1274 TSSetIFunction - Set the function to compute F(t,U,U_t) where F() = 0 is the DAE to be solved. 1275 1276 Logically Collective on TS 1277 1278 Input Parameters: 1279 + ts - the TS context obtained from TSCreate() 1280 . r - vector to hold the residual (or NULL to have it created internally) 1281 . f - the function evaluation routine 1282 - ctx - user-defined context for private data for the function evaluation routine (may be NULL) 1283 1284 Calling sequence of f: 1285 $ f(TS ts,PetscReal t,Vec u,Vec u_t,Vec F,ctx); 1286 1287 + t - time at step/stage being solved 1288 . u - state vector 1289 . u_t - time derivative of state vector 1290 . F - function vector 1291 - ctx - [optional] user-defined context for matrix evaluation routine 1292 1293 Important: 1294 The user MUST call either this routine or TSSetRHSFunction() to define the ODE. When solving DAEs you must use this function. 1295 1296 Level: beginner 1297 1298 .keywords: TS, timestep, set, DAE, Jacobian 1299 1300 .seealso: TSSetRHSJacobian(), TSSetRHSFunction(), TSSetIJacobian() 1301 @*/ 1302 PetscErrorCode TSSetIFunction(TS ts,Vec r,TSIFunction f,void *ctx) 1303 { 1304 PetscErrorCode ierr; 1305 SNES snes; 1306 Vec ralloc = NULL; 1307 DM dm; 1308 1309 PetscFunctionBegin; 1310 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1311 if (r) PetscValidHeaderSpecific(r,VEC_CLASSID,2); 1312 1313 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1314 ierr = DMTSSetIFunction(dm,f,ctx);CHKERRQ(ierr); 1315 1316 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1317 if (!r && !ts->dm && ts->vec_sol) { 1318 ierr = VecDuplicate(ts->vec_sol,&ralloc);CHKERRQ(ierr); 1319 r = ralloc; 1320 } 1321 ierr = SNESSetFunction(snes,r,SNESTSFormFunction,ts);CHKERRQ(ierr); 1322 ierr = VecDestroy(&ralloc);CHKERRQ(ierr); 1323 PetscFunctionReturn(0); 1324 } 1325 1326 /*@C 1327 TSGetIFunction - Returns the vector where the implicit residual is stored and the function/contex to compute it. 1328 1329 Not Collective 1330 1331 Input Parameter: 1332 . ts - the TS context 1333 1334 Output Parameter: 1335 + r - vector to hold residual (or NULL) 1336 . func - the function to compute residual (or NULL) 1337 - ctx - the function context (or NULL) 1338 1339 Level: advanced 1340 1341 .keywords: TS, nonlinear, get, function 1342 1343 .seealso: TSSetIFunction(), SNESGetFunction() 1344 @*/ 1345 PetscErrorCode TSGetIFunction(TS ts,Vec *r,TSIFunction *func,void **ctx) 1346 { 1347 PetscErrorCode ierr; 1348 SNES snes; 1349 DM dm; 1350 1351 PetscFunctionBegin; 1352 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1353 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1354 ierr = SNESGetFunction(snes,r,NULL,NULL);CHKERRQ(ierr); 1355 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1356 ierr = DMTSGetIFunction(dm,func,ctx);CHKERRQ(ierr); 1357 PetscFunctionReturn(0); 1358 } 1359 1360 /*@C 1361 TSGetRHSFunction - Returns the vector where the right hand side is stored and the function/context to compute it. 1362 1363 Not Collective 1364 1365 Input Parameter: 1366 . ts - the TS context 1367 1368 Output Parameter: 1369 + r - vector to hold computed right hand side (or NULL) 1370 . func - the function to compute right hand side (or NULL) 1371 - ctx - the function context (or NULL) 1372 1373 Level: advanced 1374 1375 .keywords: TS, nonlinear, get, function 1376 1377 .seealso: TSSetRHSFunction(), SNESGetFunction() 1378 @*/ 1379 PetscErrorCode TSGetRHSFunction(TS ts,Vec *r,TSRHSFunction *func,void **ctx) 1380 { 1381 PetscErrorCode ierr; 1382 SNES snes; 1383 DM dm; 1384 1385 PetscFunctionBegin; 1386 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1387 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1388 ierr = SNESGetFunction(snes,r,NULL,NULL);CHKERRQ(ierr); 1389 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1390 ierr = DMTSGetRHSFunction(dm,func,ctx);CHKERRQ(ierr); 1391 PetscFunctionReturn(0); 1392 } 1393 1394 /*@C 1395 TSSetIJacobian - Set the function to compute the matrix dF/dU + a*dF/dU_t where F(t,U,U_t) is the function 1396 provided with TSSetIFunction(). 1397 1398 Logically Collective on TS 1399 1400 Input Parameters: 1401 + ts - the TS context obtained from TSCreate() 1402 . Amat - (approximate) Jacobian matrix 1403 . Pmat - matrix used to compute preconditioner (usually the same as Amat) 1404 . f - the Jacobian evaluation routine 1405 - ctx - user-defined context for private data for the Jacobian evaluation routine (may be NULL) 1406 1407 Calling sequence of f: 1408 $ f(TS ts,PetscReal t,Vec U,Vec U_t,PetscReal a,Mat Amat,Mat Pmat,void *ctx); 1409 1410 + t - time at step/stage being solved 1411 . U - state vector 1412 . U_t - time derivative of state vector 1413 . a - shift 1414 . Amat - (approximate) Jacobian of F(t,U,W+a*U), equivalent to dF/dU + a*dF/dU_t 1415 . Pmat - matrix used for constructing preconditioner, usually the same as Amat 1416 - ctx - [optional] user-defined context for matrix evaluation routine 1417 1418 Notes: 1419 The matrices Amat and Pmat are exactly the matrices that are used by SNES for the nonlinear solve. 1420 1421 If you know the operator Amat has a null space you can use MatSetNullSpace() and MatSetTransposeNullSpace() to supply the null 1422 space to Amat and the KSP solvers will automatically use that null space as needed during the solution process. 1423 1424 The matrix dF/dU + a*dF/dU_t you provide turns out to be 1425 the Jacobian of F(t,U,W+a*U) where F(t,U,U_t) = 0 is the DAE to be solved. 1426 The time integrator internally approximates U_t by W+a*U where the positive "shift" 1427 a and vector W depend on the integration method, step size, and past states. For example with 1428 the backward Euler method a = 1/dt and W = -a*U(previous timestep) so 1429 W + a*U = a*(U - U(previous timestep)) = (U - U(previous timestep))/dt 1430 1431 You must set all the diagonal entries of the matrices, if they are zero you must still set them with a zero value 1432 1433 The TS solver may modify the nonzero structure and the entries of the matrices Amat and Pmat between the calls to f() 1434 You should not assume the values are the same in the next call to f() as you set them in the previous call. 1435 1436 Level: beginner 1437 1438 .keywords: TS, timestep, DAE, Jacobian 1439 1440 .seealso: TSSetIFunction(), TSSetRHSJacobian(), SNESComputeJacobianDefaultColor(), SNESComputeJacobianDefault(), TSSetRHSFunction() 1441 1442 @*/ 1443 PetscErrorCode TSSetIJacobian(TS ts,Mat Amat,Mat Pmat,TSIJacobian f,void *ctx) 1444 { 1445 PetscErrorCode ierr; 1446 SNES snes; 1447 DM dm; 1448 1449 PetscFunctionBegin; 1450 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1451 if (Amat) PetscValidHeaderSpecific(Amat,MAT_CLASSID,2); 1452 if (Pmat) PetscValidHeaderSpecific(Pmat,MAT_CLASSID,3); 1453 if (Amat) PetscCheckSameComm(ts,1,Amat,2); 1454 if (Pmat) PetscCheckSameComm(ts,1,Pmat,3); 1455 1456 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1457 ierr = DMTSSetIJacobian(dm,f,ctx);CHKERRQ(ierr); 1458 1459 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1460 ierr = SNESSetJacobian(snes,Amat,Pmat,SNESTSFormJacobian,ts);CHKERRQ(ierr); 1461 PetscFunctionReturn(0); 1462 } 1463 1464 /*@ 1465 TSRHSJacobianSetReuse - restore RHS Jacobian before re-evaluating. Without this flag, TS will change the sign and 1466 shift the RHS Jacobian for a finite-time-step implicit solve, in which case the user function will need to recompute 1467 the entire Jacobian. The reuse flag must be set if the evaluation function will assume that the matrix entries have 1468 not been changed by the TS. 1469 1470 Logically Collective 1471 1472 Input Arguments: 1473 + ts - TS context obtained from TSCreate() 1474 - reuse - PETSC_TRUE if the RHS Jacobian 1475 1476 Level: intermediate 1477 1478 .seealso: TSSetRHSJacobian(), TSComputeRHSJacobianConstant() 1479 @*/ 1480 PetscErrorCode TSRHSJacobianSetReuse(TS ts,PetscBool reuse) 1481 { 1482 PetscFunctionBegin; 1483 ts->rhsjacobian.reuse = reuse; 1484 PetscFunctionReturn(0); 1485 } 1486 1487 /*@C 1488 TSSetI2Function - Set the function to compute F(t,U,U_t,U_tt) where F = 0 is the DAE to be solved. 1489 1490 Logically Collective on TS 1491 1492 Input Parameters: 1493 + ts - the TS context obtained from TSCreate() 1494 . F - vector to hold the residual (or NULL to have it created internally) 1495 . fun - the function evaluation routine 1496 - ctx - user-defined context for private data for the function evaluation routine (may be NULL) 1497 1498 Calling sequence of fun: 1499 $ fun(TS ts,PetscReal t,Vec U,Vec U_t,Vec U_tt,Vec F,ctx); 1500 1501 + t - time at step/stage being solved 1502 . U - state vector 1503 . U_t - time derivative of state vector 1504 . U_tt - second time derivative of state vector 1505 . F - function vector 1506 - ctx - [optional] user-defined context for matrix evaluation routine (may be NULL) 1507 1508 Level: beginner 1509 1510 .keywords: TS, timestep, set, ODE, DAE, Function 1511 1512 .seealso: TSSetI2Jacobian() 1513 @*/ 1514 PetscErrorCode TSSetI2Function(TS ts,Vec F,TSI2Function fun,void *ctx) 1515 { 1516 DM dm; 1517 PetscErrorCode ierr; 1518 1519 PetscFunctionBegin; 1520 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1521 if (F) PetscValidHeaderSpecific(F,VEC_CLASSID,2); 1522 ierr = TSSetIFunction(ts,F,NULL,NULL);CHKERRQ(ierr); 1523 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1524 ierr = DMTSSetI2Function(dm,fun,ctx);CHKERRQ(ierr); 1525 PetscFunctionReturn(0); 1526 } 1527 1528 /*@C 1529 TSGetI2Function - Returns the vector where the implicit residual is stored and the function/contex to compute it. 1530 1531 Not Collective 1532 1533 Input Parameter: 1534 . ts - the TS context 1535 1536 Output Parameter: 1537 + r - vector to hold residual (or NULL) 1538 . fun - the function to compute residual (or NULL) 1539 - ctx - the function context (or NULL) 1540 1541 Level: advanced 1542 1543 .keywords: TS, nonlinear, get, function 1544 1545 .seealso: TSSetI2Function(), SNESGetFunction() 1546 @*/ 1547 PetscErrorCode TSGetI2Function(TS ts,Vec *r,TSI2Function *fun,void **ctx) 1548 { 1549 PetscErrorCode ierr; 1550 SNES snes; 1551 DM dm; 1552 1553 PetscFunctionBegin; 1554 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1555 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1556 ierr = SNESGetFunction(snes,r,NULL,NULL);CHKERRQ(ierr); 1557 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1558 ierr = DMTSGetI2Function(dm,fun,ctx);CHKERRQ(ierr); 1559 PetscFunctionReturn(0); 1560 } 1561 1562 /*@C 1563 TSSetI2Jacobian - Set the function to compute the matrix dF/dU + v*dF/dU_t + a*dF/dU_tt 1564 where F(t,U,U_t,U_tt) is the function you provided with TSSetI2Function(). 1565 1566 Logically Collective on TS 1567 1568 Input Parameters: 1569 + ts - the TS context obtained from TSCreate() 1570 . J - Jacobian matrix 1571 . P - preconditioning matrix for J (may be same as J) 1572 . jac - the Jacobian evaluation routine 1573 - ctx - user-defined context for private data for the Jacobian evaluation routine (may be NULL) 1574 1575 Calling sequence of jac: 1576 $ jac(TS ts,PetscReal t,Vec U,Vec U_t,Vec U_tt,PetscReal v,PetscReal a,Mat J,Mat P,void *ctx); 1577 1578 + t - time at step/stage being solved 1579 . U - state vector 1580 . U_t - time derivative of state vector 1581 . U_tt - second time derivative of state vector 1582 . v - shift for U_t 1583 . a - shift for U_tt 1584 . 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 1585 . P - preconditioning matrix for J, may be same as J 1586 - ctx - [optional] user-defined context for matrix evaluation routine 1587 1588 Notes: 1589 The matrices J and P are exactly the matrices that are used by SNES for the nonlinear solve. 1590 1591 The matrix dF/dU + v*dF/dU_t + a*dF/dU_tt you provide turns out to be 1592 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. 1593 The time integrator internally approximates U_t by W+v*U and U_tt by W'+a*U where the positive "shift" 1594 parameters 'v' and 'a' and vectors W, W' depend on the integration method, step size, and past states. 1595 1596 Level: beginner 1597 1598 .keywords: TS, timestep, set, ODE, DAE, Jacobian 1599 1600 .seealso: TSSetI2Function() 1601 @*/ 1602 PetscErrorCode TSSetI2Jacobian(TS ts,Mat J,Mat P,TSI2Jacobian jac,void *ctx) 1603 { 1604 DM dm; 1605 PetscErrorCode ierr; 1606 1607 PetscFunctionBegin; 1608 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1609 if (J) PetscValidHeaderSpecific(J,MAT_CLASSID,2); 1610 if (P) PetscValidHeaderSpecific(P,MAT_CLASSID,3); 1611 ierr = TSSetIJacobian(ts,J,P,NULL,NULL);CHKERRQ(ierr); 1612 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1613 ierr = DMTSSetI2Jacobian(dm,jac,ctx);CHKERRQ(ierr); 1614 PetscFunctionReturn(0); 1615 } 1616 1617 /*@C 1618 TSGetI2Jacobian - Returns the implicit Jacobian at the present timestep. 1619 1620 Not Collective, but parallel objects are returned if TS is parallel 1621 1622 Input Parameter: 1623 . ts - The TS context obtained from TSCreate() 1624 1625 Output Parameters: 1626 + J - The (approximate) Jacobian of F(t,U,U_t,U_tt) 1627 . P - The matrix from which the preconditioner is constructed, often the same as J 1628 . jac - The function to compute the Jacobian matrices 1629 - ctx - User-defined context for Jacobian evaluation routine 1630 1631 Notes: You can pass in NULL for any return argument you do not need. 1632 1633 Level: advanced 1634 1635 .seealso: TSGetTimeStep(), TSGetMatrices(), TSGetTime(), TSGetStepNumber() 1636 1637 .keywords: TS, timestep, get, matrix, Jacobian 1638 @*/ 1639 PetscErrorCode TSGetI2Jacobian(TS ts,Mat *J,Mat *P,TSI2Jacobian *jac,void **ctx) 1640 { 1641 PetscErrorCode ierr; 1642 SNES snes; 1643 DM dm; 1644 1645 PetscFunctionBegin; 1646 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1647 ierr = SNESSetUpMatrices(snes);CHKERRQ(ierr); 1648 ierr = SNESGetJacobian(snes,J,P,NULL,NULL);CHKERRQ(ierr); 1649 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1650 ierr = DMTSGetI2Jacobian(dm,jac,ctx);CHKERRQ(ierr); 1651 PetscFunctionReturn(0); 1652 } 1653 1654 /*@ 1655 TSComputeI2Function - Evaluates the DAE residual written in implicit form F(t,U,U_t,U_tt) = 0 1656 1657 Collective on TS and Vec 1658 1659 Input Parameters: 1660 + ts - the TS context 1661 . t - current time 1662 . U - state vector 1663 . V - time derivative of state vector (U_t) 1664 - A - second time derivative of state vector (U_tt) 1665 1666 Output Parameter: 1667 . F - the residual vector 1668 1669 Note: 1670 Most users should not need to explicitly call this routine, as it 1671 is used internally within the nonlinear solvers. 1672 1673 Level: developer 1674 1675 .keywords: TS, compute, function, vector 1676 1677 .seealso: TSSetI2Function() 1678 @*/ 1679 PetscErrorCode TSComputeI2Function(TS ts,PetscReal t,Vec U,Vec V,Vec A,Vec F) 1680 { 1681 DM dm; 1682 TSI2Function I2Function; 1683 void *ctx; 1684 TSRHSFunction rhsfunction; 1685 PetscErrorCode ierr; 1686 1687 PetscFunctionBegin; 1688 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1689 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 1690 PetscValidHeaderSpecific(V,VEC_CLASSID,4); 1691 PetscValidHeaderSpecific(A,VEC_CLASSID,5); 1692 PetscValidHeaderSpecific(F,VEC_CLASSID,6); 1693 1694 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1695 ierr = DMTSGetI2Function(dm,&I2Function,&ctx);CHKERRQ(ierr); 1696 ierr = DMTSGetRHSFunction(dm,&rhsfunction,NULL);CHKERRQ(ierr); 1697 1698 if (!I2Function) { 1699 ierr = TSComputeIFunction(ts,t,U,A,F,PETSC_FALSE);CHKERRQ(ierr); 1700 PetscFunctionReturn(0); 1701 } 1702 1703 ierr = PetscLogEventBegin(TS_FunctionEval,ts,U,V,F);CHKERRQ(ierr); 1704 1705 PetscStackPush("TS user implicit function"); 1706 ierr = I2Function(ts,t,U,V,A,F,ctx);CHKERRQ(ierr); 1707 PetscStackPop; 1708 1709 if (rhsfunction) { 1710 Vec Frhs; 1711 ierr = TSGetRHSVec_Private(ts,&Frhs);CHKERRQ(ierr); 1712 ierr = TSComputeRHSFunction(ts,t,U,Frhs);CHKERRQ(ierr); 1713 ierr = VecAXPY(F,-1,Frhs);CHKERRQ(ierr); 1714 } 1715 1716 ierr = PetscLogEventEnd(TS_FunctionEval,ts,U,V,F);CHKERRQ(ierr); 1717 PetscFunctionReturn(0); 1718 } 1719 1720 /*@ 1721 TSComputeI2Jacobian - Evaluates the Jacobian of the DAE 1722 1723 Collective on TS and Vec 1724 1725 Input Parameters: 1726 + ts - the TS context 1727 . t - current timestep 1728 . U - state vector 1729 . V - time derivative of state vector 1730 . A - second time derivative of state vector 1731 . shiftV - shift to apply, see note below 1732 - shiftA - shift to apply, see note below 1733 1734 Output Parameters: 1735 + J - Jacobian matrix 1736 - P - optional preconditioning matrix 1737 1738 Notes: 1739 If F(t,U,V,A)=0 is the DAE, the required Jacobian is 1740 1741 dF/dU + shiftV*dF/dV + shiftA*dF/dA 1742 1743 Most users should not need to explicitly call this routine, as it 1744 is used internally within the nonlinear solvers. 1745 1746 Level: developer 1747 1748 .keywords: TS, compute, Jacobian, matrix 1749 1750 .seealso: TSSetI2Jacobian() 1751 @*/ 1752 PetscErrorCode TSComputeI2Jacobian(TS ts,PetscReal t,Vec U,Vec V,Vec A,PetscReal shiftV,PetscReal shiftA,Mat J,Mat P) 1753 { 1754 DM dm; 1755 TSI2Jacobian I2Jacobian; 1756 void *ctx; 1757 TSRHSJacobian rhsjacobian; 1758 PetscErrorCode ierr; 1759 1760 PetscFunctionBegin; 1761 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1762 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 1763 PetscValidHeaderSpecific(V,VEC_CLASSID,4); 1764 PetscValidHeaderSpecific(A,VEC_CLASSID,5); 1765 PetscValidHeaderSpecific(J,MAT_CLASSID,8); 1766 PetscValidHeaderSpecific(P,MAT_CLASSID,9); 1767 1768 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1769 ierr = DMTSGetI2Jacobian(dm,&I2Jacobian,&ctx);CHKERRQ(ierr); 1770 ierr = DMTSGetRHSJacobian(dm,&rhsjacobian,NULL);CHKERRQ(ierr); 1771 1772 if (!I2Jacobian) { 1773 ierr = TSComputeIJacobian(ts,t,U,A,shiftA,J,P,PETSC_FALSE);CHKERRQ(ierr); 1774 PetscFunctionReturn(0); 1775 } 1776 1777 ierr = PetscLogEventBegin(TS_JacobianEval,ts,U,J,P);CHKERRQ(ierr); 1778 1779 PetscStackPush("TS user implicit Jacobian"); 1780 ierr = I2Jacobian(ts,t,U,V,A,shiftV,shiftA,J,P,ctx);CHKERRQ(ierr); 1781 PetscStackPop; 1782 1783 if (rhsjacobian) { 1784 Mat Jrhs,Prhs; MatStructure axpy = DIFFERENT_NONZERO_PATTERN; 1785 ierr = TSGetRHSMats_Private(ts,&Jrhs,&Prhs);CHKERRQ(ierr); 1786 ierr = TSComputeRHSJacobian(ts,t,U,Jrhs,Prhs);CHKERRQ(ierr); 1787 ierr = MatAXPY(J,-1,Jrhs,axpy);CHKERRQ(ierr); 1788 if (P != J) {ierr = MatAXPY(P,-1,Prhs,axpy);CHKERRQ(ierr);} 1789 } 1790 1791 ierr = PetscLogEventEnd(TS_JacobianEval,ts,U,J,P);CHKERRQ(ierr); 1792 PetscFunctionReturn(0); 1793 } 1794 1795 /*@ 1796 TS2SetSolution - Sets the initial solution and time derivative vectors 1797 for use by the TS routines handling second order equations. 1798 1799 Logically Collective on TS and Vec 1800 1801 Input Parameters: 1802 + ts - the TS context obtained from TSCreate() 1803 . u - the solution vector 1804 - v - the time derivative vector 1805 1806 Level: beginner 1807 1808 .keywords: TS, timestep, set, solution, initial conditions 1809 @*/ 1810 PetscErrorCode TS2SetSolution(TS ts,Vec u,Vec v) 1811 { 1812 PetscErrorCode ierr; 1813 1814 PetscFunctionBegin; 1815 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1816 PetscValidHeaderSpecific(u,VEC_CLASSID,2); 1817 PetscValidHeaderSpecific(v,VEC_CLASSID,3); 1818 ierr = TSSetSolution(ts,u);CHKERRQ(ierr); 1819 ierr = PetscObjectReference((PetscObject)v);CHKERRQ(ierr); 1820 ierr = VecDestroy(&ts->vec_dot);CHKERRQ(ierr); 1821 ts->vec_dot = v; 1822 PetscFunctionReturn(0); 1823 } 1824 1825 /*@ 1826 TS2GetSolution - Returns the solution and time derivative at the present timestep 1827 for second order equations. It is valid to call this routine inside the function 1828 that you are evaluating in order to move to the new timestep. This vector not 1829 changed until the solution at the next timestep has been calculated. 1830 1831 Not Collective, but Vec returned is parallel if TS is parallel 1832 1833 Input Parameter: 1834 . ts - the TS context obtained from TSCreate() 1835 1836 Output Parameter: 1837 + u - the vector containing the solution 1838 - v - the vector containing the time derivative 1839 1840 Level: intermediate 1841 1842 .seealso: TS2SetSolution(), TSGetTimeStep(), TSGetTime() 1843 1844 .keywords: TS, timestep, get, solution 1845 @*/ 1846 PetscErrorCode TS2GetSolution(TS ts,Vec *u,Vec *v) 1847 { 1848 PetscFunctionBegin; 1849 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1850 if (u) PetscValidPointer(u,2); 1851 if (v) PetscValidPointer(v,3); 1852 if (u) *u = ts->vec_sol; 1853 if (v) *v = ts->vec_dot; 1854 PetscFunctionReturn(0); 1855 } 1856 1857 /*@C 1858 TSLoad - Loads a KSP that has been stored in binary with KSPView(). 1859 1860 Collective on PetscViewer 1861 1862 Input Parameters: 1863 + newdm - the newly loaded TS, this needs to have been created with TSCreate() or 1864 some related function before a call to TSLoad(). 1865 - viewer - binary file viewer, obtained from PetscViewerBinaryOpen() 1866 1867 Level: intermediate 1868 1869 Notes: 1870 The type is determined by the data in the file, any type set into the TS before this call is ignored. 1871 1872 Notes for advanced users: 1873 Most users should not need to know the details of the binary storage 1874 format, since TSLoad() and TSView() completely hide these details. 1875 But for anyone who's interested, the standard binary matrix storage 1876 format is 1877 .vb 1878 has not yet been determined 1879 .ve 1880 1881 .seealso: PetscViewerBinaryOpen(), TSView(), MatLoad(), VecLoad() 1882 @*/ 1883 PetscErrorCode TSLoad(TS ts, PetscViewer viewer) 1884 { 1885 PetscErrorCode ierr; 1886 PetscBool isbinary; 1887 PetscInt classid; 1888 char type[256]; 1889 DMTS sdm; 1890 DM dm; 1891 1892 PetscFunctionBegin; 1893 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1894 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,2); 1895 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1896 if (!isbinary) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid viewer; open viewer with PetscViewerBinaryOpen()"); 1897 1898 ierr = PetscViewerBinaryRead(viewer,&classid,1,NULL,PETSC_INT);CHKERRQ(ierr); 1899 if (classid != TS_FILE_CLASSID) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Not TS next in file"); 1900 ierr = PetscViewerBinaryRead(viewer,type,256,NULL,PETSC_CHAR);CHKERRQ(ierr); 1901 ierr = TSSetType(ts, type);CHKERRQ(ierr); 1902 if (ts->ops->load) { 1903 ierr = (*ts->ops->load)(ts,viewer);CHKERRQ(ierr); 1904 } 1905 ierr = DMCreate(PetscObjectComm((PetscObject)ts),&dm);CHKERRQ(ierr); 1906 ierr = DMLoad(dm,viewer);CHKERRQ(ierr); 1907 ierr = TSSetDM(ts,dm);CHKERRQ(ierr); 1908 ierr = DMCreateGlobalVector(ts->dm,&ts->vec_sol);CHKERRQ(ierr); 1909 ierr = VecLoad(ts->vec_sol,viewer);CHKERRQ(ierr); 1910 ierr = DMGetDMTS(ts->dm,&sdm);CHKERRQ(ierr); 1911 ierr = DMTSLoad(sdm,viewer);CHKERRQ(ierr); 1912 PetscFunctionReturn(0); 1913 } 1914 1915 #include <petscdraw.h> 1916 #if defined(PETSC_HAVE_SAWS) 1917 #include <petscviewersaws.h> 1918 #endif 1919 /*@C 1920 TSView - Prints the TS data structure. 1921 1922 Collective on TS 1923 1924 Input Parameters: 1925 + ts - the TS context obtained from TSCreate() 1926 - viewer - visualization context 1927 1928 Options Database Key: 1929 . -ts_view - calls TSView() at end of TSStep() 1930 1931 Notes: 1932 The available visualization contexts include 1933 + PETSC_VIEWER_STDOUT_SELF - standard output (default) 1934 - PETSC_VIEWER_STDOUT_WORLD - synchronized standard 1935 output where only the first processor opens 1936 the file. All other processors send their 1937 data to the first processor to print. 1938 1939 The user can open an alternative visualization context with 1940 PetscViewerASCIIOpen() - output to a specified file. 1941 1942 Level: beginner 1943 1944 .keywords: TS, timestep, view 1945 1946 .seealso: PetscViewerASCIIOpen() 1947 @*/ 1948 PetscErrorCode TSView(TS ts,PetscViewer viewer) 1949 { 1950 PetscErrorCode ierr; 1951 TSType type; 1952 PetscBool iascii,isstring,isundials,isbinary,isdraw; 1953 DMTS sdm; 1954 #if defined(PETSC_HAVE_SAWS) 1955 PetscBool issaws; 1956 #endif 1957 1958 PetscFunctionBegin; 1959 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1960 if (!viewer) { 1961 ierr = PetscViewerASCIIGetStdout(PetscObjectComm((PetscObject)ts),&viewer);CHKERRQ(ierr); 1962 } 1963 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,2); 1964 PetscCheckSameComm(ts,1,viewer,2); 1965 1966 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1967 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSTRING,&isstring);CHKERRQ(ierr); 1968 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1969 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1970 #if defined(PETSC_HAVE_SAWS) 1971 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSAWS,&issaws);CHKERRQ(ierr); 1972 #endif 1973 if (iascii) { 1974 ierr = PetscObjectPrintClassNamePrefixType((PetscObject)ts,viewer);CHKERRQ(ierr); 1975 if (ts->ops->view) { 1976 ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr); 1977 ierr = (*ts->ops->view)(ts,viewer);CHKERRQ(ierr); 1978 ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr); 1979 } 1980 if (ts->max_steps < PETSC_MAX_INT) { 1981 ierr = PetscViewerASCIIPrintf(viewer," maximum steps=%D\n",ts->max_steps);CHKERRQ(ierr); 1982 } 1983 if (ts->max_time < PETSC_MAX_REAL) { 1984 ierr = PetscViewerASCIIPrintf(viewer," maximum time=%g\n",(double)ts->max_time);CHKERRQ(ierr); 1985 } 1986 if (ts->usessnes) { 1987 PetscBool lin; 1988 if (ts->problem_type == TS_NONLINEAR) { 1989 ierr = PetscViewerASCIIPrintf(viewer," total number of nonlinear solver iterations=%D\n",ts->snes_its);CHKERRQ(ierr); 1990 } 1991 ierr = PetscViewerASCIIPrintf(viewer," total number of linear solver iterations=%D\n",ts->ksp_its);CHKERRQ(ierr); 1992 ierr = PetscObjectTypeCompare((PetscObject)ts->snes,SNESKSPONLY,&lin);CHKERRQ(ierr); 1993 ierr = PetscViewerASCIIPrintf(viewer," total number of %slinear solve failures=%D\n",lin ? "" : "non",ts->num_snes_failures);CHKERRQ(ierr); 1994 } 1995 ierr = PetscViewerASCIIPrintf(viewer," total number of rejected steps=%D\n",ts->reject);CHKERRQ(ierr); 1996 if (ts->vrtol) { 1997 ierr = PetscViewerASCIIPrintf(viewer," using vector of relative error tolerances, ");CHKERRQ(ierr); 1998 } else { 1999 ierr = PetscViewerASCIIPrintf(viewer," using relative error tolerance of %g, ",(double)ts->rtol);CHKERRQ(ierr); 2000 } 2001 if (ts->vatol) { 2002 ierr = PetscViewerASCIIPrintf(viewer," using vector of absolute error tolerances\n");CHKERRQ(ierr); 2003 } else { 2004 ierr = PetscViewerASCIIPrintf(viewer," using absolute error tolerance of %g\n",(double)ts->atol);CHKERRQ(ierr); 2005 } 2006 ierr = TSAdaptView(ts->adapt,viewer);CHKERRQ(ierr); 2007 if (ts->snes && ts->usessnes) {ierr = SNESView(ts->snes,viewer);CHKERRQ(ierr);} 2008 ierr = DMGetDMTS(ts->dm,&sdm);CHKERRQ(ierr); 2009 ierr = DMTSView(sdm,viewer);CHKERRQ(ierr); 2010 } else if (isstring) { 2011 ierr = TSGetType(ts,&type);CHKERRQ(ierr); 2012 ierr = PetscViewerStringSPrintf(viewer," %-7.7s",type);CHKERRQ(ierr); 2013 } else if (isbinary) { 2014 PetscInt classid = TS_FILE_CLASSID; 2015 MPI_Comm comm; 2016 PetscMPIInt rank; 2017 char type[256]; 2018 2019 ierr = PetscObjectGetComm((PetscObject)ts,&comm);CHKERRQ(ierr); 2020 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2021 if (!rank) { 2022 ierr = PetscViewerBinaryWrite(viewer,&classid,1,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); 2023 ierr = PetscStrncpy(type,((PetscObject)ts)->type_name,256);CHKERRQ(ierr); 2024 ierr = PetscViewerBinaryWrite(viewer,type,256,PETSC_CHAR,PETSC_FALSE);CHKERRQ(ierr); 2025 } 2026 if (ts->ops->view) { 2027 ierr = (*ts->ops->view)(ts,viewer);CHKERRQ(ierr); 2028 } 2029 if (ts->adapt) {ierr = TSAdaptView(ts->adapt,viewer);CHKERRQ(ierr);} 2030 ierr = DMView(ts->dm,viewer);CHKERRQ(ierr); 2031 ierr = VecView(ts->vec_sol,viewer);CHKERRQ(ierr); 2032 ierr = DMGetDMTS(ts->dm,&sdm);CHKERRQ(ierr); 2033 ierr = DMTSView(sdm,viewer);CHKERRQ(ierr); 2034 } else if (isdraw) { 2035 PetscDraw draw; 2036 char str[36]; 2037 PetscReal x,y,bottom,h; 2038 2039 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 2040 ierr = PetscDrawGetCurrentPoint(draw,&x,&y);CHKERRQ(ierr); 2041 ierr = PetscStrcpy(str,"TS: ");CHKERRQ(ierr); 2042 ierr = PetscStrcat(str,((PetscObject)ts)->type_name);CHKERRQ(ierr); 2043 ierr = PetscDrawStringBoxed(draw,x,y,PETSC_DRAW_BLACK,PETSC_DRAW_BLACK,str,NULL,&h);CHKERRQ(ierr); 2044 bottom = y - h; 2045 ierr = PetscDrawPushCurrentPoint(draw,x,bottom);CHKERRQ(ierr); 2046 if (ts->ops->view) { 2047 ierr = (*ts->ops->view)(ts,viewer);CHKERRQ(ierr); 2048 } 2049 if (ts->adapt) {ierr = TSAdaptView(ts->adapt,viewer);CHKERRQ(ierr);} 2050 if (ts->snes) {ierr = SNESView(ts->snes,viewer);CHKERRQ(ierr);} 2051 ierr = PetscDrawPopCurrentPoint(draw);CHKERRQ(ierr); 2052 #if defined(PETSC_HAVE_SAWS) 2053 } else if (issaws) { 2054 PetscMPIInt rank; 2055 const char *name; 2056 2057 ierr = PetscObjectGetName((PetscObject)ts,&name);CHKERRQ(ierr); 2058 ierr = MPI_Comm_rank(PETSC_COMM_WORLD,&rank);CHKERRQ(ierr); 2059 if (!((PetscObject)ts)->amsmem && !rank) { 2060 char dir[1024]; 2061 2062 ierr = PetscObjectViewSAWs((PetscObject)ts,viewer);CHKERRQ(ierr); 2063 ierr = PetscSNPrintf(dir,1024,"/PETSc/Objects/%s/time_step",name);CHKERRQ(ierr); 2064 PetscStackCallSAWs(SAWs_Register,(dir,&ts->steps,1,SAWs_READ,SAWs_INT)); 2065 ierr = PetscSNPrintf(dir,1024,"/PETSc/Objects/%s/time",name);CHKERRQ(ierr); 2066 PetscStackCallSAWs(SAWs_Register,(dir,&ts->ptime,1,SAWs_READ,SAWs_DOUBLE)); 2067 } 2068 if (ts->ops->view) { 2069 ierr = (*ts->ops->view)(ts,viewer);CHKERRQ(ierr); 2070 } 2071 #endif 2072 } 2073 2074 ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr); 2075 ierr = PetscObjectTypeCompare((PetscObject)ts,TSSUNDIALS,&isundials);CHKERRQ(ierr); 2076 ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr); 2077 PetscFunctionReturn(0); 2078 } 2079 2080 /*@ 2081 TSSetApplicationContext - Sets an optional user-defined context for 2082 the timesteppers. 2083 2084 Logically Collective on TS 2085 2086 Input Parameters: 2087 + ts - the TS context obtained from TSCreate() 2088 - usrP - optional user context 2089 2090 Fortran Notes: To use this from Fortran you must write a Fortran interface definition for this 2091 function that tells Fortran the Fortran derived data type that you are passing in as the ctx argument. 2092 2093 Level: intermediate 2094 2095 .keywords: TS, timestep, set, application, context 2096 2097 .seealso: TSGetApplicationContext() 2098 @*/ 2099 PetscErrorCode TSSetApplicationContext(TS ts,void *usrP) 2100 { 2101 PetscFunctionBegin; 2102 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2103 ts->user = usrP; 2104 PetscFunctionReturn(0); 2105 } 2106 2107 /*@ 2108 TSGetApplicationContext - Gets the user-defined context for the 2109 timestepper. 2110 2111 Not Collective 2112 2113 Input Parameter: 2114 . ts - the TS context obtained from TSCreate() 2115 2116 Output Parameter: 2117 . usrP - user context 2118 2119 Fortran Notes: To use this from Fortran you must write a Fortran interface definition for this 2120 function that tells Fortran the Fortran derived data type that you are passing in as the ctx argument. 2121 2122 Level: intermediate 2123 2124 .keywords: TS, timestep, get, application, context 2125 2126 .seealso: TSSetApplicationContext() 2127 @*/ 2128 PetscErrorCode TSGetApplicationContext(TS ts,void *usrP) 2129 { 2130 PetscFunctionBegin; 2131 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2132 *(void**)usrP = ts->user; 2133 PetscFunctionReturn(0); 2134 } 2135 2136 /*@ 2137 TSGetStepNumber - Gets the number of steps completed. 2138 2139 Not Collective 2140 2141 Input Parameter: 2142 . ts - the TS context obtained from TSCreate() 2143 2144 Output Parameter: 2145 . steps - number of steps completed so far 2146 2147 Level: intermediate 2148 2149 .keywords: TS, timestep, get, iteration, number 2150 .seealso: TSGetTime(), TSGetTimeStep(), TSSetPreStep(), TSSetPreStage(), TSSetPostStage(), TSSetPostStep() 2151 @*/ 2152 PetscErrorCode TSGetStepNumber(TS ts,PetscInt *steps) 2153 { 2154 PetscFunctionBegin; 2155 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2156 PetscValidIntPointer(steps,2); 2157 *steps = ts->steps; 2158 PetscFunctionReturn(0); 2159 } 2160 2161 /*@ 2162 TSSetStepNumber - Sets the number of steps completed. 2163 2164 Logically Collective on TS 2165 2166 Input Parameters: 2167 + ts - the TS context 2168 - steps - number of steps completed so far 2169 2170 Notes: 2171 For most uses of the TS solvers the user need not explicitly call 2172 TSSetStepNumber(), as the step counter is appropriately updated in 2173 TSSolve()/TSStep()/TSRollBack(). Power users may call this routine to 2174 reinitialize timestepping by setting the step counter to zero (and time 2175 to the initial time) to solve a similar problem with different initial 2176 conditions or parameters. Other possible use case is to continue 2177 timestepping from a previously interrupted run in such a way that TS 2178 monitors will be called with a initial nonzero step counter. 2179 2180 Level: advanced 2181 2182 .keywords: TS, timestep, set, iteration, number 2183 .seealso: TSGetStepNumber(), TSSetTime(), TSSetTimeStep(), TSSetSolution() 2184 @*/ 2185 PetscErrorCode TSSetStepNumber(TS ts,PetscInt steps) 2186 { 2187 PetscFunctionBegin; 2188 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2189 PetscValidLogicalCollectiveInt(ts,steps,2); 2190 if (steps < 0) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Step number must be non-negative"); 2191 ts->steps = steps; 2192 PetscFunctionReturn(0); 2193 } 2194 2195 /*@ 2196 TSSetTimeStep - Allows one to reset the timestep at any time, 2197 useful for simple pseudo-timestepping codes. 2198 2199 Logically Collective on TS 2200 2201 Input Parameters: 2202 + ts - the TS context obtained from TSCreate() 2203 - time_step - the size of the timestep 2204 2205 Level: intermediate 2206 2207 .seealso: TSGetTimeStep(), TSSetTime() 2208 2209 .keywords: TS, set, timestep 2210 @*/ 2211 PetscErrorCode TSSetTimeStep(TS ts,PetscReal time_step) 2212 { 2213 PetscFunctionBegin; 2214 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2215 PetscValidLogicalCollectiveReal(ts,time_step,2); 2216 ts->time_step = time_step; 2217 PetscFunctionReturn(0); 2218 } 2219 2220 /*@ 2221 TSSetExactFinalTime - Determines whether to adapt the final time step to 2222 match the exact final time, interpolate solution to the exact final time, 2223 or just return at the final time TS computed. 2224 2225 Logically Collective on TS 2226 2227 Input Parameter: 2228 + ts - the time-step context 2229 - eftopt - exact final time option 2230 2231 $ TS_EXACTFINALTIME_STEPOVER - Don't do anything if final time is exceeded 2232 $ TS_EXACTFINALTIME_INTERPOLATE - Interpolate back to final time 2233 $ TS_EXACTFINALTIME_MATCHSTEP - Adapt final time step to match the final time 2234 2235 Options Database: 2236 . -ts_exact_final_time <stepover,interpolate,matchstep> - select the final step at runtime 2237 2238 Warning: If you use the option TS_EXACTFINALTIME_STEPOVER the solution may be at a very different time 2239 then the final time you selected. 2240 2241 Level: beginner 2242 2243 .seealso: TSExactFinalTimeOption, TSGetExactFinalTime() 2244 @*/ 2245 PetscErrorCode TSSetExactFinalTime(TS ts,TSExactFinalTimeOption eftopt) 2246 { 2247 PetscFunctionBegin; 2248 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2249 PetscValidLogicalCollectiveEnum(ts,eftopt,2); 2250 ts->exact_final_time = eftopt; 2251 PetscFunctionReturn(0); 2252 } 2253 2254 /*@ 2255 TSGetExactFinalTime - Gets the exact final time option. 2256 2257 Not Collective 2258 2259 Input Parameter: 2260 . ts - the TS context 2261 2262 Output Parameter: 2263 . eftopt - exact final time option 2264 2265 Level: beginner 2266 2267 .seealso: TSExactFinalTimeOption, TSSetExactFinalTime() 2268 @*/ 2269 PetscErrorCode TSGetExactFinalTime(TS ts,TSExactFinalTimeOption *eftopt) 2270 { 2271 PetscFunctionBegin; 2272 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2273 PetscValidPointer(eftopt,2); 2274 *eftopt = ts->exact_final_time; 2275 PetscFunctionReturn(0); 2276 } 2277 2278 /*@ 2279 TSGetTimeStep - Gets the current timestep size. 2280 2281 Not Collective 2282 2283 Input Parameter: 2284 . ts - the TS context obtained from TSCreate() 2285 2286 Output Parameter: 2287 . dt - the current timestep size 2288 2289 Level: intermediate 2290 2291 .seealso: TSSetTimeStep(), TSGetTime() 2292 2293 .keywords: TS, get, timestep 2294 @*/ 2295 PetscErrorCode TSGetTimeStep(TS ts,PetscReal *dt) 2296 { 2297 PetscFunctionBegin; 2298 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2299 PetscValidRealPointer(dt,2); 2300 *dt = ts->time_step; 2301 PetscFunctionReturn(0); 2302 } 2303 2304 /*@ 2305 TSGetSolution - Returns the solution at the present timestep. It 2306 is valid to call this routine inside the function that you are evaluating 2307 in order to move to the new timestep. This vector not changed until 2308 the solution at the next timestep has been calculated. 2309 2310 Not Collective, but Vec returned is parallel if TS is parallel 2311 2312 Input Parameter: 2313 . ts - the TS context obtained from TSCreate() 2314 2315 Output Parameter: 2316 . v - the vector containing the solution 2317 2318 Note: If you used TSSetExactFinalTime(ts,TS_EXACTFINALTIME_MATCHSTEP); this does not return the solution at the requested 2319 final time. It returns the solution at the next timestep. 2320 2321 Level: intermediate 2322 2323 .seealso: TSGetTimeStep(), TSGetTime(), TSGetSolveTime(), TSGetSolutionComponents() 2324 2325 .keywords: TS, timestep, get, solution 2326 @*/ 2327 PetscErrorCode TSGetSolution(TS ts,Vec *v) 2328 { 2329 PetscFunctionBegin; 2330 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2331 PetscValidPointer(v,2); 2332 *v = ts->vec_sol; 2333 PetscFunctionReturn(0); 2334 } 2335 2336 /*@ 2337 TSGetSolutionComponents - Returns any solution components at the present 2338 timestep, if available for the time integration method being used. 2339 Solution components are quantities that share the same size and 2340 structure as the solution vector. 2341 2342 Not Collective, but Vec returned is parallel if TS is parallel 2343 2344 Parameters : 2345 . ts - the TS context obtained from TSCreate() (input parameter). 2346 . n - If v is PETSC_NULL, then the number of solution components is 2347 returned through n, else the n-th solution component is 2348 returned in v. 2349 . v - the vector containing the n-th solution component 2350 (may be PETSC_NULL to use this function to find out 2351 the number of solutions components). 2352 2353 Level: advanced 2354 2355 .seealso: TSGetSolution() 2356 2357 .keywords: TS, timestep, get, solution 2358 @*/ 2359 PetscErrorCode TSGetSolutionComponents(TS ts,PetscInt *n,Vec *v) 2360 { 2361 PetscErrorCode ierr; 2362 2363 PetscFunctionBegin; 2364 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2365 if (!ts->ops->getsolutioncomponents) *n = 0; 2366 else { 2367 ierr = (*ts->ops->getsolutioncomponents)(ts,n,v);CHKERRQ(ierr); 2368 } 2369 PetscFunctionReturn(0); 2370 } 2371 2372 /*@ 2373 TSGetAuxSolution - Returns an auxiliary solution at the present 2374 timestep, if available for the time integration method being used. 2375 2376 Not Collective, but Vec returned is parallel if TS is parallel 2377 2378 Parameters : 2379 . ts - the TS context obtained from TSCreate() (input parameter). 2380 . v - the vector containing the auxiliary solution 2381 2382 Level: intermediate 2383 2384 .seealso: TSGetSolution() 2385 2386 .keywords: TS, timestep, get, solution 2387 @*/ 2388 PetscErrorCode TSGetAuxSolution(TS ts,Vec *v) 2389 { 2390 PetscErrorCode ierr; 2391 2392 PetscFunctionBegin; 2393 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2394 if (ts->ops->getauxsolution) { 2395 ierr = (*ts->ops->getauxsolution)(ts,v);CHKERRQ(ierr); 2396 } else { 2397 ierr = VecZeroEntries(*v); CHKERRQ(ierr); 2398 } 2399 PetscFunctionReturn(0); 2400 } 2401 2402 /*@ 2403 TSGetTimeError - Returns the estimated error vector, if the chosen 2404 TSType has an error estimation functionality. 2405 2406 Not Collective, but Vec returned is parallel if TS is parallel 2407 2408 Note: MUST call after TSSetUp() 2409 2410 Parameters : 2411 . ts - the TS context obtained from TSCreate() (input parameter). 2412 . n - current estimate (n=0) or previous one (n=-1) 2413 . v - the vector containing the error (same size as the solution). 2414 2415 Level: intermediate 2416 2417 .seealso: TSGetSolution(), TSSetTimeError() 2418 2419 .keywords: TS, timestep, get, error 2420 @*/ 2421 PetscErrorCode TSGetTimeError(TS ts,PetscInt n,Vec *v) 2422 { 2423 PetscErrorCode ierr; 2424 2425 PetscFunctionBegin; 2426 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2427 if (ts->ops->gettimeerror) { 2428 ierr = (*ts->ops->gettimeerror)(ts,n,v);CHKERRQ(ierr); 2429 } else { 2430 ierr = VecZeroEntries(*v);CHKERRQ(ierr); 2431 } 2432 PetscFunctionReturn(0); 2433 } 2434 2435 /*@ 2436 TSSetTimeError - Sets the estimated error vector, if the chosen 2437 TSType has an error estimation functionality. This can be used 2438 to restart such a time integrator with a given error vector. 2439 2440 Not Collective, but Vec returned is parallel if TS is parallel 2441 2442 Parameters : 2443 . ts - the TS context obtained from TSCreate() (input parameter). 2444 . v - the vector containing the error (same size as the solution). 2445 2446 Level: intermediate 2447 2448 .seealso: TSSetSolution(), TSGetTimeError) 2449 2450 .keywords: TS, timestep, get, error 2451 @*/ 2452 PetscErrorCode TSSetTimeError(TS ts,Vec v) 2453 { 2454 PetscErrorCode ierr; 2455 2456 PetscFunctionBegin; 2457 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2458 if (!ts->setupcalled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call TSSetUp() first"); 2459 if (ts->ops->settimeerror) { 2460 ierr = (*ts->ops->settimeerror)(ts,v);CHKERRQ(ierr); 2461 } 2462 PetscFunctionReturn(0); 2463 } 2464 2465 /*@ 2466 TSGetCostGradients - Returns the gradients from the TSAdjointSolve() 2467 2468 Not Collective, but Vec returned is parallel if TS is parallel 2469 2470 Input Parameter: 2471 . ts - the TS context obtained from TSCreate() 2472 2473 Output Parameter: 2474 + lambda - vectors containing the gradients of the cost functions with respect to the ODE/DAE solution variables 2475 - mu - vectors containing the gradients of the cost functions with respect to the problem parameters 2476 2477 Level: intermediate 2478 2479 .seealso: TSGetTimeStep() 2480 2481 .keywords: TS, timestep, get, sensitivity 2482 @*/ 2483 PetscErrorCode TSGetCostGradients(TS ts,PetscInt *numcost,Vec **lambda,Vec **mu) 2484 { 2485 PetscFunctionBegin; 2486 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2487 if (numcost) *numcost = ts->numcost; 2488 if (lambda) *lambda = ts->vecs_sensi; 2489 if (mu) *mu = ts->vecs_sensip; 2490 PetscFunctionReturn(0); 2491 } 2492 2493 /* ----- Routines to initialize and destroy a timestepper ---- */ 2494 /*@ 2495 TSSetProblemType - Sets the type of problem to be solved. 2496 2497 Not collective 2498 2499 Input Parameters: 2500 + ts - The TS 2501 - type - One of TS_LINEAR, TS_NONLINEAR where these types refer to problems of the forms 2502 .vb 2503 U_t - A U = 0 (linear) 2504 U_t - A(t) U = 0 (linear) 2505 F(t,U,U_t) = 0 (nonlinear) 2506 .ve 2507 2508 Level: beginner 2509 2510 .keywords: TS, problem type 2511 .seealso: TSSetUp(), TSProblemType, TS 2512 @*/ 2513 PetscErrorCode TSSetProblemType(TS ts, TSProblemType type) 2514 { 2515 PetscErrorCode ierr; 2516 2517 PetscFunctionBegin; 2518 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 2519 ts->problem_type = type; 2520 if (type == TS_LINEAR) { 2521 SNES snes; 2522 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 2523 ierr = SNESSetType(snes,SNESKSPONLY);CHKERRQ(ierr); 2524 } 2525 PetscFunctionReturn(0); 2526 } 2527 2528 /*@C 2529 TSGetProblemType - Gets the type of problem to be solved. 2530 2531 Not collective 2532 2533 Input Parameter: 2534 . ts - The TS 2535 2536 Output Parameter: 2537 . type - One of TS_LINEAR, TS_NONLINEAR where these types refer to problems of the forms 2538 .vb 2539 M U_t = A U 2540 M(t) U_t = A(t) U 2541 F(t,U,U_t) 2542 .ve 2543 2544 Level: beginner 2545 2546 .keywords: TS, problem type 2547 .seealso: TSSetUp(), TSProblemType, TS 2548 @*/ 2549 PetscErrorCode TSGetProblemType(TS ts, TSProblemType *type) 2550 { 2551 PetscFunctionBegin; 2552 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 2553 PetscValidIntPointer(type,2); 2554 *type = ts->problem_type; 2555 PetscFunctionReturn(0); 2556 } 2557 2558 /*@ 2559 TSSetUp - Sets up the internal data structures for the later use 2560 of a timestepper. 2561 2562 Collective on TS 2563 2564 Input Parameter: 2565 . ts - the TS context obtained from TSCreate() 2566 2567 Notes: 2568 For basic use of the TS solvers the user need not explicitly call 2569 TSSetUp(), since these actions will automatically occur during 2570 the call to TSStep() or TSSolve(). However, if one wishes to control this 2571 phase separately, TSSetUp() should be called after TSCreate() 2572 and optional routines of the form TSSetXXX(), but before TSStep() and TSSolve(). 2573 2574 Level: advanced 2575 2576 .keywords: TS, timestep, setup 2577 2578 .seealso: TSCreate(), TSStep(), TSDestroy(), TSSolve() 2579 @*/ 2580 PetscErrorCode TSSetUp(TS ts) 2581 { 2582 PetscErrorCode ierr; 2583 DM dm; 2584 PetscErrorCode (*func)(SNES,Vec,Vec,void*); 2585 PetscErrorCode (*jac)(SNES,Vec,Mat,Mat,void*); 2586 TSIFunction ifun; 2587 TSIJacobian ijac; 2588 TSI2Jacobian i2jac; 2589 TSRHSJacobian rhsjac; 2590 PetscBool isnone; 2591 2592 PetscFunctionBegin; 2593 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2594 if (ts->setupcalled) PetscFunctionReturn(0); 2595 2596 if (!((PetscObject)ts)->type_name) { 2597 ierr = TSGetIFunction(ts,NULL,&ifun,NULL);CHKERRQ(ierr); 2598 ierr = TSSetType(ts,ifun ? TSBEULER : TSEULER);CHKERRQ(ierr); 2599 } 2600 2601 if (!ts->vec_sol) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call TSSetSolution() first"); 2602 2603 if (ts->rhsjacobian.reuse) { 2604 Mat Amat,Pmat; 2605 SNES snes; 2606 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 2607 ierr = SNESGetJacobian(snes,&Amat,&Pmat,NULL,NULL);CHKERRQ(ierr); 2608 /* Matching matrices implies that an IJacobian is NOT set, because if it had been set, the IJacobian's matrix would 2609 * have displaced the RHS matrix */ 2610 if (Amat == ts->Arhs) { 2611 /* we need to copy the values of the matrix because for the constant Jacobian case the user will never set the numerical values in this new location */ 2612 ierr = MatDuplicate(ts->Arhs,MAT_COPY_VALUES,&Amat);CHKERRQ(ierr); 2613 ierr = SNESSetJacobian(snes,Amat,NULL,NULL,NULL);CHKERRQ(ierr); 2614 ierr = MatDestroy(&Amat);CHKERRQ(ierr); 2615 } 2616 if (Pmat == ts->Brhs) { 2617 ierr = MatDuplicate(ts->Brhs,MAT_COPY_VALUES,&Pmat);CHKERRQ(ierr); 2618 ierr = SNESSetJacobian(snes,NULL,Pmat,NULL,NULL);CHKERRQ(ierr); 2619 ierr = MatDestroy(&Pmat);CHKERRQ(ierr); 2620 } 2621 } 2622 2623 ierr = TSGetAdapt(ts,&ts->adapt);CHKERRQ(ierr); 2624 ierr = TSAdaptSetDefaultType(ts->adapt,ts->default_adapt_type);CHKERRQ(ierr); 2625 2626 if (ts->ops->setup) { 2627 ierr = (*ts->ops->setup)(ts);CHKERRQ(ierr); 2628 } 2629 2630 /* Attempt to check/preset a default value for the exact final time option */ 2631 ierr = PetscObjectTypeCompare((PetscObject)ts->adapt,TSADAPTNONE,&isnone);CHKERRQ(ierr); 2632 if (!isnone && ts->exact_final_time == TS_EXACTFINALTIME_UNSPECIFIED) 2633 ts->exact_final_time = TS_EXACTFINALTIME_MATCHSTEP; 2634 2635 /* In the case where we've set a DMTSFunction or what have you, we need the default SNESFunction 2636 to be set right but can't do it elsewhere due to the overreliance on ctx=ts. 2637 */ 2638 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 2639 ierr = DMSNESGetFunction(dm,&func,NULL);CHKERRQ(ierr); 2640 if (!func) { 2641 ierr = DMSNESSetFunction(dm,SNESTSFormFunction,ts);CHKERRQ(ierr); 2642 } 2643 /* If the SNES doesn't have a jacobian set and the TS has an ijacobian or rhsjacobian set, set the SNES to use it. 2644 Otherwise, the SNES will use coloring internally to form the Jacobian. 2645 */ 2646 ierr = DMSNESGetJacobian(dm,&jac,NULL);CHKERRQ(ierr); 2647 ierr = DMTSGetIJacobian(dm,&ijac,NULL);CHKERRQ(ierr); 2648 ierr = DMTSGetI2Jacobian(dm,&i2jac,NULL);CHKERRQ(ierr); 2649 ierr = DMTSGetRHSJacobian(dm,&rhsjac,NULL);CHKERRQ(ierr); 2650 if (!jac && (ijac || i2jac || rhsjac)) { 2651 ierr = DMSNESSetJacobian(dm,SNESTSFormJacobian,ts);CHKERRQ(ierr); 2652 } 2653 2654 /* if time integration scheme has a starting method, call it */ 2655 if (ts->ops->startingmethod) { 2656 ierr = (*ts->ops->startingmethod)(ts);CHKERRQ(ierr); 2657 } 2658 2659 ts->setupcalled = PETSC_TRUE; 2660 PetscFunctionReturn(0); 2661 } 2662 2663 /*@ 2664 TSAdjointSetUp - Sets up the internal data structures for the later use 2665 of an adjoint solver 2666 2667 Collective on TS 2668 2669 Input Parameter: 2670 . ts - the TS context obtained from TSCreate() 2671 2672 Level: advanced 2673 2674 .keywords: TS, timestep, setup 2675 2676 .seealso: TSCreate(), TSAdjointStep(), TSSetCostGradients() 2677 @*/ 2678 PetscErrorCode TSAdjointSetUp(TS ts) 2679 { 2680 PetscErrorCode ierr; 2681 2682 PetscFunctionBegin; 2683 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2684 if (ts->adjointsetupcalled) PetscFunctionReturn(0); 2685 if (!ts->vecs_sensi) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"Must call TSSetCostGradients() first"); 2686 if (ts->vecs_sensip && !ts->Jacp) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"Must call TSAdjointSetRHSJacobian() first"); 2687 2688 if (ts->vec_costintegral) { /* if there is integral in the cost function */ 2689 ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&ts->vecs_drdy);CHKERRQ(ierr); 2690 if (ts->vecs_sensip){ 2691 ierr = VecDuplicateVecs(ts->vecs_sensip[0],ts->numcost,&ts->vecs_drdp);CHKERRQ(ierr); 2692 } 2693 } 2694 2695 if (ts->ops->adjointsetup) { 2696 ierr = (*ts->ops->adjointsetup)(ts);CHKERRQ(ierr); 2697 } 2698 ts->adjointsetupcalled = PETSC_TRUE; 2699 PetscFunctionReturn(0); 2700 } 2701 2702 /*@ 2703 TSReset - Resets a TS context and removes any allocated Vecs and Mats. 2704 2705 Collective on TS 2706 2707 Input Parameter: 2708 . ts - the TS context obtained from TSCreate() 2709 2710 Level: beginner 2711 2712 .keywords: TS, timestep, reset 2713 2714 .seealso: TSCreate(), TSSetup(), TSDestroy() 2715 @*/ 2716 PetscErrorCode TSReset(TS ts) 2717 { 2718 PetscErrorCode ierr; 2719 2720 PetscFunctionBegin; 2721 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2722 2723 if (ts->ops->reset) { 2724 ierr = (*ts->ops->reset)(ts);CHKERRQ(ierr); 2725 } 2726 if (ts->snes) {ierr = SNESReset(ts->snes);CHKERRQ(ierr);} 2727 if (ts->adapt) {ierr = TSAdaptReset(ts->adapt);CHKERRQ(ierr);} 2728 2729 ierr = MatDestroy(&ts->Arhs);CHKERRQ(ierr); 2730 ierr = MatDestroy(&ts->Brhs);CHKERRQ(ierr); 2731 ierr = VecDestroy(&ts->Frhs);CHKERRQ(ierr); 2732 ierr = VecDestroy(&ts->vec_sol);CHKERRQ(ierr); 2733 ierr = VecDestroy(&ts->vec_dot);CHKERRQ(ierr); 2734 ierr = VecDestroy(&ts->vatol);CHKERRQ(ierr); 2735 ierr = VecDestroy(&ts->vrtol);CHKERRQ(ierr); 2736 ierr = VecDestroyVecs(ts->nwork,&ts->work);CHKERRQ(ierr); 2737 2738 ierr = VecDestroyVecs(ts->numcost,&ts->vecs_drdy);CHKERRQ(ierr); 2739 ierr = VecDestroyVecs(ts->numcost,&ts->vecs_drdp);CHKERRQ(ierr); 2740 2741 ierr = MatDestroy(&ts->Jacp);CHKERRQ(ierr); 2742 ierr = VecDestroy(&ts->vec_costintegral);CHKERRQ(ierr); 2743 ierr = VecDestroy(&ts->vec_costintegrand);CHKERRQ(ierr); 2744 2745 ierr = PetscFree(ts->vecs_fwdsensipacked);CHKERRQ(ierr); 2746 2747 ts->setupcalled = PETSC_FALSE; 2748 PetscFunctionReturn(0); 2749 } 2750 2751 /*@ 2752 TSDestroy - Destroys the timestepper context that was created 2753 with TSCreate(). 2754 2755 Collective on TS 2756 2757 Input Parameter: 2758 . ts - the TS context obtained from TSCreate() 2759 2760 Level: beginner 2761 2762 .keywords: TS, timestepper, destroy 2763 2764 .seealso: TSCreate(), TSSetUp(), TSSolve() 2765 @*/ 2766 PetscErrorCode TSDestroy(TS *ts) 2767 { 2768 PetscErrorCode ierr; 2769 2770 PetscFunctionBegin; 2771 if (!*ts) PetscFunctionReturn(0); 2772 PetscValidHeaderSpecific((*ts),TS_CLASSID,1); 2773 if (--((PetscObject)(*ts))->refct > 0) {*ts = 0; PetscFunctionReturn(0);} 2774 2775 ierr = TSReset((*ts));CHKERRQ(ierr); 2776 2777 /* if memory was published with SAWs then destroy it */ 2778 ierr = PetscObjectSAWsViewOff((PetscObject)*ts);CHKERRQ(ierr); 2779 if ((*ts)->ops->destroy) {ierr = (*(*ts)->ops->destroy)((*ts));CHKERRQ(ierr);} 2780 2781 ierr = TSTrajectoryDestroy(&(*ts)->trajectory);CHKERRQ(ierr); 2782 2783 ierr = TSAdaptDestroy(&(*ts)->adapt);CHKERRQ(ierr); 2784 ierr = TSEventDestroy(&(*ts)->event);CHKERRQ(ierr); 2785 2786 ierr = SNESDestroy(&(*ts)->snes);CHKERRQ(ierr); 2787 ierr = DMDestroy(&(*ts)->dm);CHKERRQ(ierr); 2788 ierr = TSMonitorCancel((*ts));CHKERRQ(ierr); 2789 ierr = TSAdjointMonitorCancel((*ts));CHKERRQ(ierr); 2790 2791 ierr = PetscHeaderDestroy(ts);CHKERRQ(ierr); 2792 PetscFunctionReturn(0); 2793 } 2794 2795 /*@ 2796 TSGetSNES - Returns the SNES (nonlinear solver) associated with 2797 a TS (timestepper) context. Valid only for nonlinear problems. 2798 2799 Not Collective, but SNES is parallel if TS is parallel 2800 2801 Input Parameter: 2802 . ts - the TS context obtained from TSCreate() 2803 2804 Output Parameter: 2805 . snes - the nonlinear solver context 2806 2807 Notes: 2808 The user can then directly manipulate the SNES context to set various 2809 options, etc. Likewise, the user can then extract and manipulate the 2810 KSP, KSP, and PC contexts as well. 2811 2812 TSGetSNES() does not work for integrators that do not use SNES; in 2813 this case TSGetSNES() returns NULL in snes. 2814 2815 Level: beginner 2816 2817 .keywords: timestep, get, SNES 2818 @*/ 2819 PetscErrorCode TSGetSNES(TS ts,SNES *snes) 2820 { 2821 PetscErrorCode ierr; 2822 2823 PetscFunctionBegin; 2824 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2825 PetscValidPointer(snes,2); 2826 if (!ts->snes) { 2827 ierr = SNESCreate(PetscObjectComm((PetscObject)ts),&ts->snes);CHKERRQ(ierr); 2828 ierr = SNESSetFunction(ts->snes,NULL,SNESTSFormFunction,ts);CHKERRQ(ierr); 2829 ierr = PetscLogObjectParent((PetscObject)ts,(PetscObject)ts->snes);CHKERRQ(ierr); 2830 ierr = PetscObjectIncrementTabLevel((PetscObject)ts->snes,(PetscObject)ts,1);CHKERRQ(ierr); 2831 if (ts->dm) {ierr = SNESSetDM(ts->snes,ts->dm);CHKERRQ(ierr);} 2832 if (ts->problem_type == TS_LINEAR) { 2833 ierr = SNESSetType(ts->snes,SNESKSPONLY);CHKERRQ(ierr); 2834 } 2835 } 2836 *snes = ts->snes; 2837 PetscFunctionReturn(0); 2838 } 2839 2840 /*@ 2841 TSSetSNES - Set the SNES (nonlinear solver) to be used by the timestepping context 2842 2843 Collective 2844 2845 Input Parameter: 2846 + ts - the TS context obtained from TSCreate() 2847 - snes - the nonlinear solver context 2848 2849 Notes: 2850 Most users should have the TS created by calling TSGetSNES() 2851 2852 Level: developer 2853 2854 .keywords: timestep, set, SNES 2855 @*/ 2856 PetscErrorCode TSSetSNES(TS ts,SNES snes) 2857 { 2858 PetscErrorCode ierr; 2859 PetscErrorCode (*func)(SNES,Vec,Mat,Mat,void*); 2860 2861 PetscFunctionBegin; 2862 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2863 PetscValidHeaderSpecific(snes,SNES_CLASSID,2); 2864 ierr = PetscObjectReference((PetscObject)snes);CHKERRQ(ierr); 2865 ierr = SNESDestroy(&ts->snes);CHKERRQ(ierr); 2866 2867 ts->snes = snes; 2868 2869 ierr = SNESSetFunction(ts->snes,NULL,SNESTSFormFunction,ts);CHKERRQ(ierr); 2870 ierr = SNESGetJacobian(ts->snes,NULL,NULL,&func,NULL);CHKERRQ(ierr); 2871 if (func == SNESTSFormJacobian) { 2872 ierr = SNESSetJacobian(ts->snes,NULL,NULL,SNESTSFormJacobian,ts);CHKERRQ(ierr); 2873 } 2874 PetscFunctionReturn(0); 2875 } 2876 2877 /*@ 2878 TSGetKSP - Returns the KSP (linear solver) associated with 2879 a TS (timestepper) context. 2880 2881 Not Collective, but KSP is parallel if TS is parallel 2882 2883 Input Parameter: 2884 . ts - the TS context obtained from TSCreate() 2885 2886 Output Parameter: 2887 . ksp - the nonlinear solver context 2888 2889 Notes: 2890 The user can then directly manipulate the KSP context to set various 2891 options, etc. Likewise, the user can then extract and manipulate the 2892 KSP and PC contexts as well. 2893 2894 TSGetKSP() does not work for integrators that do not use KSP; 2895 in this case TSGetKSP() returns NULL in ksp. 2896 2897 Level: beginner 2898 2899 .keywords: timestep, get, KSP 2900 @*/ 2901 PetscErrorCode TSGetKSP(TS ts,KSP *ksp) 2902 { 2903 PetscErrorCode ierr; 2904 SNES snes; 2905 2906 PetscFunctionBegin; 2907 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2908 PetscValidPointer(ksp,2); 2909 if (!((PetscObject)ts)->type_name) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_NULL,"KSP is not created yet. Call TSSetType() first"); 2910 if (ts->problem_type != TS_LINEAR) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Linear only; use TSGetSNES()"); 2911 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 2912 ierr = SNESGetKSP(snes,ksp);CHKERRQ(ierr); 2913 PetscFunctionReturn(0); 2914 } 2915 2916 /* ----------- Routines to set solver parameters ---------- */ 2917 2918 /*@ 2919 TSSetMaxSteps - Sets the maximum number of steps to use. 2920 2921 Logically Collective on TS 2922 2923 Input Parameters: 2924 + ts - the TS context obtained from TSCreate() 2925 - maxsteps - maximum number of steps to use 2926 2927 Options Database Keys: 2928 . -ts_max_steps <maxsteps> - Sets maxsteps 2929 2930 Notes: 2931 The default maximum number of steps is 5000 2932 2933 Level: intermediate 2934 2935 .keywords: TS, timestep, set, maximum, steps 2936 2937 .seealso: TSGetMaxSteps(), TSSetMaxTime(), TSSetExactFinalTime() 2938 @*/ 2939 PetscErrorCode TSSetMaxSteps(TS ts,PetscInt maxsteps) 2940 { 2941 PetscFunctionBegin; 2942 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2943 PetscValidLogicalCollectiveInt(ts,maxsteps,2); 2944 if (maxsteps < 0 ) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Maximum number of steps must be non-negative"); 2945 ts->max_steps = maxsteps; 2946 PetscFunctionReturn(0); 2947 } 2948 2949 /*@ 2950 TSGetMaxSteps - Gets the maximum number of steps to use. 2951 2952 Not Collective 2953 2954 Input Parameters: 2955 . ts - the TS context obtained from TSCreate() 2956 2957 Output Parameter: 2958 . maxsteps - maximum number of steps to use 2959 2960 Level: advanced 2961 2962 .keywords: TS, timestep, get, maximum, steps 2963 2964 .seealso: TSSetMaxSteps(), TSGetMaxTime(), TSSetMaxTime() 2965 @*/ 2966 PetscErrorCode TSGetMaxSteps(TS ts,PetscInt *maxsteps) 2967 { 2968 PetscFunctionBegin; 2969 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2970 PetscValidIntPointer(maxsteps,2); 2971 *maxsteps = ts->max_steps; 2972 PetscFunctionReturn(0); 2973 } 2974 2975 /*@ 2976 TSSetMaxTime - Sets the maximum (or final) time for timestepping. 2977 2978 Logically Collective on TS 2979 2980 Input Parameters: 2981 + ts - the TS context obtained from TSCreate() 2982 - maxtime - final time to step to 2983 2984 Options Database Keys: 2985 . -ts_max_time <maxtime> - Sets maxtime 2986 2987 Notes: 2988 The default maximum time is 5.0 2989 2990 Level: intermediate 2991 2992 .keywords: TS, timestep, set, maximum, time 2993 2994 .seealso: TSGetMaxTime(), TSSetMaxSteps(), TSSetExactFinalTime() 2995 @*/ 2996 PetscErrorCode TSSetMaxTime(TS ts,PetscReal maxtime) 2997 { 2998 PetscFunctionBegin; 2999 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3000 PetscValidLogicalCollectiveReal(ts,maxtime,2); 3001 ts->max_time = maxtime; 3002 PetscFunctionReturn(0); 3003 } 3004 3005 /*@ 3006 TSGetMaxTime - Gets the maximum (or final) time for timestepping. 3007 3008 Not Collective 3009 3010 Input Parameters: 3011 . ts - the TS context obtained from TSCreate() 3012 3013 Output Parameter: 3014 . maxtime - final time to step to 3015 3016 Level: advanced 3017 3018 .keywords: TS, timestep, get, maximum, time 3019 3020 .seealso: TSSetMaxTime(), TSGetMaxSteps(), TSSetMaxSteps() 3021 @*/ 3022 PetscErrorCode TSGetMaxTime(TS ts,PetscReal *maxtime) 3023 { 3024 PetscFunctionBegin; 3025 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3026 PetscValidRealPointer(maxtime,2); 3027 *maxtime = ts->max_time; 3028 PetscFunctionReturn(0); 3029 } 3030 3031 /*@ 3032 TSSetInitialTimeStep - Deprecated, use TSSetTime() and TSSetTimeStep(). 3033 3034 Level: deprecated 3035 3036 @*/ 3037 PetscErrorCode TSSetInitialTimeStep(TS ts,PetscReal initial_time,PetscReal time_step) 3038 { 3039 PetscErrorCode ierr; 3040 PetscFunctionBegin; 3041 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3042 ierr = TSSetTime(ts,initial_time);CHKERRQ(ierr); 3043 ierr = TSSetTimeStep(ts,time_step);CHKERRQ(ierr); 3044 PetscFunctionReturn(0); 3045 } 3046 3047 /*@ 3048 TSGetDuration - Deprecated, use TSGetMaxSteps() and TSGetMaxTime(). 3049 3050 Level: deprecated 3051 3052 @*/ 3053 PetscErrorCode TSGetDuration(TS ts, PetscInt *maxsteps, PetscReal *maxtime) 3054 { 3055 PetscFunctionBegin; 3056 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3057 if (maxsteps) { 3058 PetscValidIntPointer(maxsteps,2); 3059 *maxsteps = ts->max_steps; 3060 } 3061 if (maxtime) { 3062 PetscValidScalarPointer(maxtime,3); 3063 *maxtime = ts->max_time; 3064 } 3065 PetscFunctionReturn(0); 3066 } 3067 3068 /*@ 3069 TSSetDuration - Deprecated, use TSSetMaxSteps() and TSSetMaxTime(). 3070 3071 Level: deprecated 3072 3073 @*/ 3074 PetscErrorCode TSSetDuration(TS ts,PetscInt maxsteps,PetscReal maxtime) 3075 { 3076 PetscFunctionBegin; 3077 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3078 PetscValidLogicalCollectiveInt(ts,maxsteps,2); 3079 PetscValidLogicalCollectiveReal(ts,maxtime,2); 3080 if (maxsteps >= 0) ts->max_steps = maxsteps; 3081 if (maxtime != PETSC_DEFAULT) ts->max_time = maxtime; 3082 PetscFunctionReturn(0); 3083 } 3084 3085 /*@ 3086 TSGetTimeStepNumber - Deprecated, use TSGetStepNumber(). 3087 3088 Level: deprecated 3089 3090 @*/ 3091 PetscErrorCode TSGetTimeStepNumber(TS ts,PetscInt *steps) { return TSGetStepNumber(ts,steps); } 3092 3093 /*@ 3094 TSGetTotalSteps - Deprecated, use TSGetStepNumber(). 3095 3096 Level: deprecated 3097 3098 @*/ 3099 PetscErrorCode TSGetTotalSteps(TS ts,PetscInt *steps) { return TSGetStepNumber(ts,steps); } 3100 3101 /*@ 3102 TSSetSolution - Sets the initial solution vector 3103 for use by the TS routines. 3104 3105 Logically Collective on TS and Vec 3106 3107 Input Parameters: 3108 + ts - the TS context obtained from TSCreate() 3109 - u - the solution vector 3110 3111 Level: beginner 3112 3113 .keywords: TS, timestep, set, solution, initial values 3114 @*/ 3115 PetscErrorCode TSSetSolution(TS ts,Vec u) 3116 { 3117 PetscErrorCode ierr; 3118 DM dm; 3119 3120 PetscFunctionBegin; 3121 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3122 PetscValidHeaderSpecific(u,VEC_CLASSID,2); 3123 ierr = PetscObjectReference((PetscObject)u);CHKERRQ(ierr); 3124 ierr = VecDestroy(&ts->vec_sol);CHKERRQ(ierr); 3125 ts->vec_sol = u; 3126 3127 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 3128 ierr = DMShellSetGlobalVector(dm,u);CHKERRQ(ierr); 3129 PetscFunctionReturn(0); 3130 } 3131 3132 /*@ 3133 TSAdjointSetSteps - Sets the number of steps the adjoint solver should take backward in time 3134 3135 Logically Collective on TS 3136 3137 Input Parameters: 3138 + ts - the TS context obtained from TSCreate() 3139 . steps - number of steps to use 3140 3141 Level: intermediate 3142 3143 Notes: Normally one does not call this and TSAdjointSolve() integrates back to the original timestep. One can call this 3144 so as to integrate back to less than the original timestep 3145 3146 .keywords: TS, timestep, set, maximum, iterations 3147 3148 .seealso: TSSetExactFinalTime() 3149 @*/ 3150 PetscErrorCode TSAdjointSetSteps(TS ts,PetscInt steps) 3151 { 3152 PetscFunctionBegin; 3153 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3154 PetscValidLogicalCollectiveInt(ts,steps,2); 3155 if (steps < 0) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Cannot step back a negative number of steps"); 3156 if (steps > ts->steps) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Cannot step back more than the total number of forward steps"); 3157 ts->adjoint_max_steps = steps; 3158 PetscFunctionReturn(0); 3159 } 3160 3161 /*@ 3162 TSSetCostGradients - Sets the initial value of the gradients of the cost function w.r.t. initial values and w.r.t. the problem parameters 3163 for use by the TSAdjoint routines. 3164 3165 Logically Collective on TS and Vec 3166 3167 Input Parameters: 3168 + ts - the TS context obtained from TSCreate() 3169 . 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 3170 - mu - gradients with respect to the parameters, the number of entries in these vectors is the same as the number of parameters 3171 3172 Level: beginner 3173 3174 Notes: the entries in these vectors must be correctly initialized with the values lamda_i = df/dy|finaltime mu_i = df/dp|finaltime 3175 3176 After TSAdjointSolve() is called the lamba and the mu contain the computed sensitivities 3177 3178 .keywords: TS, timestep, set, sensitivity, initial values 3179 @*/ 3180 PetscErrorCode TSSetCostGradients(TS ts,PetscInt numcost,Vec *lambda,Vec *mu) 3181 { 3182 PetscFunctionBegin; 3183 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3184 PetscValidPointer(lambda,2); 3185 ts->vecs_sensi = lambda; 3186 ts->vecs_sensip = mu; 3187 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"); 3188 ts->numcost = numcost; 3189 PetscFunctionReturn(0); 3190 } 3191 3192 /*@C 3193 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. 3194 3195 Logically Collective on TS 3196 3197 Input Parameters: 3198 + ts - The TS context obtained from TSCreate() 3199 - func - The function 3200 3201 Calling sequence of func: 3202 $ func (TS ts,PetscReal t,Vec y,Mat A,void *ctx); 3203 + t - current timestep 3204 . y - input vector (current ODE solution) 3205 . A - output matrix 3206 - ctx - [optional] user-defined function context 3207 3208 Level: intermediate 3209 3210 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 3211 3212 .keywords: TS, sensitivity 3213 .seealso: 3214 @*/ 3215 PetscErrorCode TSAdjointSetRHSJacobian(TS ts,Mat Amat,PetscErrorCode (*func)(TS,PetscReal,Vec,Mat,void*),void *ctx) 3216 { 3217 PetscErrorCode ierr; 3218 3219 PetscFunctionBegin; 3220 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3221 PetscValidHeaderSpecific(Amat,MAT_CLASSID,2); 3222 3223 ts->rhsjacobianp = func; 3224 ts->rhsjacobianpctx = ctx; 3225 if(Amat) { 3226 ierr = PetscObjectReference((PetscObject)Amat);CHKERRQ(ierr); 3227 ierr = MatDestroy(&ts->Jacp);CHKERRQ(ierr); 3228 ts->Jacp = Amat; 3229 } 3230 PetscFunctionReturn(0); 3231 } 3232 3233 /*@C 3234 TSAdjointComputeRHSJacobian - Runs the user-defined Jacobian function. 3235 3236 Collective on TS 3237 3238 Input Parameters: 3239 . ts - The TS context obtained from TSCreate() 3240 3241 Level: developer 3242 3243 .keywords: TS, sensitivity 3244 .seealso: TSAdjointSetRHSJacobian() 3245 @*/ 3246 PetscErrorCode TSAdjointComputeRHSJacobian(TS ts,PetscReal t,Vec X,Mat Amat) 3247 { 3248 PetscErrorCode ierr; 3249 3250 PetscFunctionBegin; 3251 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3252 PetscValidHeaderSpecific(X,VEC_CLASSID,3); 3253 PetscValidPointer(Amat,4); 3254 3255 PetscStackPush("TS user JacobianP function for sensitivity analysis"); 3256 ierr = (*ts->rhsjacobianp)(ts,t,X,Amat,ts->rhsjacobianpctx); CHKERRQ(ierr); 3257 PetscStackPop; 3258 PetscFunctionReturn(0); 3259 } 3260 3261 /*@C 3262 TSSetCostIntegrand - Sets the routine for evaluating the integral term in one or more cost functions 3263 3264 Logically Collective on TS 3265 3266 Input Parameters: 3267 + ts - the TS context obtained from TSCreate() 3268 . numcost - number of gradients to be computed, this is the number of cost functions 3269 . costintegral - vector that stores the integral values 3270 . rf - routine for evaluating the integrand function 3271 . drdyf - function that computes the gradients of the r's with respect to y,NULL if not a function y 3272 . drdpf - function that computes the gradients of the r's with respect to p, NULL if not a function of p 3273 . fwd - flag indicating whether to evaluate cost integral in the forward run or the adjoint run 3274 - ctx - [optional] user-defined context for private data for the function evaluation routine (may be NULL) 3275 3276 Calling sequence of rf: 3277 $ PetscErrorCode rf(TS ts,PetscReal t,Vec y,Vec f,void *ctx); 3278 3279 Calling sequence of drdyf: 3280 $ PetscErroCode drdyf(TS ts,PetscReal t,Vec y,Vec *drdy,void *ctx); 3281 3282 Calling sequence of drdpf: 3283 $ PetscErroCode drdpf(TS ts,PetscReal t,Vec y,Vec *drdp,void *ctx); 3284 3285 Level: intermediate 3286 3287 Notes: For optimization there is usually a single cost function (numcost = 1). For sensitivities there may be multiple cost functions 3288 3289 .keywords: TS, sensitivity analysis, timestep, set, quadrature, function 3290 3291 .seealso: TSAdjointSetRHSJacobian(),TSGetCostGradients(), TSSetCostGradients() 3292 @*/ 3293 PetscErrorCode TSSetCostIntegrand(TS ts,PetscInt numcost,Vec costintegral,PetscErrorCode (*rf)(TS,PetscReal,Vec,Vec,void*), 3294 PetscErrorCode (*drdyf)(TS,PetscReal,Vec,Vec*,void*), 3295 PetscErrorCode (*drdpf)(TS,PetscReal,Vec,Vec*,void*), 3296 PetscBool fwd,void *ctx) 3297 { 3298 PetscErrorCode ierr; 3299 3300 PetscFunctionBegin; 3301 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3302 if (costintegral) PetscValidHeaderSpecific(costintegral,VEC_CLASSID,3); 3303 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() or TSForwardSetIntegralGradients()"); 3304 if (!ts->numcost) ts->numcost=numcost; 3305 3306 if (costintegral) { 3307 ierr = PetscObjectReference((PetscObject)costintegral);CHKERRQ(ierr); 3308 ierr = VecDestroy(&ts->vec_costintegral);CHKERRQ(ierr); 3309 ts->vec_costintegral = costintegral; 3310 } else { 3311 if (!ts->vec_costintegral) { /* Create a seq vec if user does not provide one */ 3312 ierr = VecCreateSeq(PETSC_COMM_SELF,numcost,&ts->vec_costintegral);CHKERRQ(ierr); 3313 } else { 3314 ierr = VecSet(ts->vec_costintegral,0.0);CHKERRQ(ierr); 3315 } 3316 } 3317 if (!ts->vec_costintegrand) { 3318 ierr = VecDuplicate(ts->vec_costintegral,&ts->vec_costintegrand);CHKERRQ(ierr); 3319 } else { 3320 ierr = VecSet(ts->vec_costintegrand,0.0);CHKERRQ(ierr); 3321 } 3322 ts->costintegralfwd = fwd; /* Evaluate the cost integral in forward run if fwd is true */ 3323 ts->costintegrand = rf; 3324 ts->costintegrandctx = ctx; 3325 ts->drdyfunction = drdyf; 3326 ts->drdpfunction = drdpf; 3327 PetscFunctionReturn(0); 3328 } 3329 3330 /*@ 3331 TSGetCostIntegral - Returns the values of the integral term in the cost functions. 3332 It is valid to call the routine after a backward run. 3333 3334 Not Collective 3335 3336 Input Parameter: 3337 . ts - the TS context obtained from TSCreate() 3338 3339 Output Parameter: 3340 . v - the vector containing the integrals for each cost function 3341 3342 Level: intermediate 3343 3344 .seealso: TSSetCostIntegrand() 3345 3346 .keywords: TS, sensitivity analysis 3347 @*/ 3348 PetscErrorCode TSGetCostIntegral(TS ts,Vec *v) 3349 { 3350 PetscFunctionBegin; 3351 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3352 PetscValidPointer(v,2); 3353 *v = ts->vec_costintegral; 3354 PetscFunctionReturn(0); 3355 } 3356 3357 /*@ 3358 TSComputeCostIntegrand - Evaluates the integral function in the cost functions. 3359 3360 Input Parameters: 3361 + ts - the TS context 3362 . t - current time 3363 - y - state vector, i.e. current solution 3364 3365 Output Parameter: 3366 . q - vector of size numcost to hold the outputs 3367 3368 Note: 3369 Most users should not need to explicitly call this routine, as it 3370 is used internally within the sensitivity analysis context. 3371 3372 Level: developer 3373 3374 .keywords: TS, compute 3375 3376 .seealso: TSSetCostIntegrand() 3377 @*/ 3378 PetscErrorCode TSComputeCostIntegrand(TS ts,PetscReal t,Vec y,Vec q) 3379 { 3380 PetscErrorCode ierr; 3381 3382 PetscFunctionBegin; 3383 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3384 PetscValidHeaderSpecific(y,VEC_CLASSID,3); 3385 PetscValidHeaderSpecific(q,VEC_CLASSID,4); 3386 3387 ierr = PetscLogEventBegin(TS_FunctionEval,ts,y,q,0);CHKERRQ(ierr); 3388 if (ts->costintegrand) { 3389 PetscStackPush("TS user integrand in the cost function"); 3390 ierr = (*ts->costintegrand)(ts,t,y,q,ts->costintegrandctx);CHKERRQ(ierr); 3391 PetscStackPop; 3392 } else { 3393 ierr = VecZeroEntries(q);CHKERRQ(ierr); 3394 } 3395 3396 ierr = PetscLogEventEnd(TS_FunctionEval,ts,y,q,0);CHKERRQ(ierr); 3397 PetscFunctionReturn(0); 3398 } 3399 3400 /*@ 3401 TSAdjointComputeDRDYFunction - Runs the user-defined DRDY function. 3402 3403 Collective on TS 3404 3405 Input Parameters: 3406 . ts - The TS context obtained from TSCreate() 3407 3408 Notes: 3409 TSAdjointComputeDRDYFunction() is typically used for sensitivity implementation, 3410 so most users would not generally call this routine themselves. 3411 3412 Level: developer 3413 3414 .keywords: TS, sensitivity 3415 .seealso: TSAdjointComputeDRDYFunction() 3416 @*/ 3417 PetscErrorCode TSAdjointComputeDRDYFunction(TS ts,PetscReal t,Vec y,Vec *drdy) 3418 { 3419 PetscErrorCode ierr; 3420 3421 PetscFunctionBegin; 3422 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3423 PetscValidHeaderSpecific(y,VEC_CLASSID,3); 3424 3425 PetscStackPush("TS user DRDY function for sensitivity analysis"); 3426 ierr = (*ts->drdyfunction)(ts,t,y,drdy,ts->costintegrandctx); CHKERRQ(ierr); 3427 PetscStackPop; 3428 PetscFunctionReturn(0); 3429 } 3430 3431 /*@ 3432 TSAdjointComputeDRDPFunction - Runs the user-defined DRDP function. 3433 3434 Collective on TS 3435 3436 Input Parameters: 3437 . ts - The TS context obtained from TSCreate() 3438 3439 Notes: 3440 TSDRDPFunction() is typically used for sensitivity implementation, 3441 so most users would not generally call this routine themselves. 3442 3443 Level: developer 3444 3445 .keywords: TS, sensitivity 3446 .seealso: TSAdjointSetDRDPFunction() 3447 @*/ 3448 PetscErrorCode TSAdjointComputeDRDPFunction(TS ts,PetscReal t,Vec y,Vec *drdp) 3449 { 3450 PetscErrorCode ierr; 3451 3452 PetscFunctionBegin; 3453 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3454 PetscValidHeaderSpecific(y,VEC_CLASSID,3); 3455 3456 PetscStackPush("TS user DRDP function for sensitivity analysis"); 3457 ierr = (*ts->drdpfunction)(ts,t,y,drdp,ts->costintegrandctx); CHKERRQ(ierr); 3458 PetscStackPop; 3459 PetscFunctionReturn(0); 3460 } 3461 3462 /*@C 3463 TSSetPreStep - Sets the general-purpose function 3464 called once at the beginning of each time step. 3465 3466 Logically Collective on TS 3467 3468 Input Parameters: 3469 + ts - The TS context obtained from TSCreate() 3470 - func - The function 3471 3472 Calling sequence of func: 3473 . func (TS ts); 3474 3475 Level: intermediate 3476 3477 .keywords: TS, timestep 3478 .seealso: TSSetPreStage(), TSSetPostStage(), TSSetPostStep(), TSStep(), TSRestartStep() 3479 @*/ 3480 PetscErrorCode TSSetPreStep(TS ts, PetscErrorCode (*func)(TS)) 3481 { 3482 PetscFunctionBegin; 3483 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3484 ts->prestep = func; 3485 PetscFunctionReturn(0); 3486 } 3487 3488 /*@ 3489 TSPreStep - Runs the user-defined pre-step function. 3490 3491 Collective on TS 3492 3493 Input Parameters: 3494 . ts - The TS context obtained from TSCreate() 3495 3496 Notes: 3497 TSPreStep() is typically used within time stepping implementations, 3498 so most users would not generally call this routine themselves. 3499 3500 Level: developer 3501 3502 .keywords: TS, timestep 3503 .seealso: TSSetPreStep(), TSPreStage(), TSPostStage(), TSPostStep() 3504 @*/ 3505 PetscErrorCode TSPreStep(TS ts) 3506 { 3507 PetscErrorCode ierr; 3508 3509 PetscFunctionBegin; 3510 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3511 if (ts->prestep) { 3512 Vec U; 3513 PetscObjectState sprev,spost; 3514 3515 ierr = TSGetSolution(ts,&U);CHKERRQ(ierr); 3516 ierr = PetscObjectStateGet((PetscObject)U,&sprev);CHKERRQ(ierr); 3517 PetscStackCallStandard((*ts->prestep),(ts)); 3518 ierr = PetscObjectStateGet((PetscObject)U,&spost);CHKERRQ(ierr); 3519 if (sprev != spost) {ierr = TSRestartStep(ts);CHKERRQ(ierr);} 3520 } 3521 PetscFunctionReturn(0); 3522 } 3523 3524 /*@C 3525 TSSetPreStage - Sets the general-purpose function 3526 called once at the beginning of each stage. 3527 3528 Logically Collective on TS 3529 3530 Input Parameters: 3531 + ts - The TS context obtained from TSCreate() 3532 - func - The function 3533 3534 Calling sequence of func: 3535 . PetscErrorCode func(TS ts, PetscReal stagetime); 3536 3537 Level: intermediate 3538 3539 Note: 3540 There may be several stages per time step. If the solve for a given stage fails, the step may be rejected and retried. 3541 The time step number being computed can be queried using TSGetStepNumber() and the total size of the step being 3542 attempted can be obtained using TSGetTimeStep(). The time at the start of the step is available via TSGetTime(). 3543 3544 .keywords: TS, timestep 3545 .seealso: TSSetPostStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext() 3546 @*/ 3547 PetscErrorCode TSSetPreStage(TS ts, PetscErrorCode (*func)(TS,PetscReal)) 3548 { 3549 PetscFunctionBegin; 3550 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3551 ts->prestage = func; 3552 PetscFunctionReturn(0); 3553 } 3554 3555 /*@C 3556 TSSetPostStage - Sets the general-purpose function 3557 called once at the end of each stage. 3558 3559 Logically Collective on TS 3560 3561 Input Parameters: 3562 + ts - The TS context obtained from TSCreate() 3563 - func - The function 3564 3565 Calling sequence of func: 3566 . PetscErrorCode func(TS ts, PetscReal stagetime, PetscInt stageindex, Vec* Y); 3567 3568 Level: intermediate 3569 3570 Note: 3571 There may be several stages per time step. If the solve for a given stage fails, the step may be rejected and retried. 3572 The time step number being computed can be queried using TSGetStepNumber() and the total size of the step being 3573 attempted can be obtained using TSGetTimeStep(). The time at the start of the step is available via TSGetTime(). 3574 3575 .keywords: TS, timestep 3576 .seealso: TSSetPreStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext() 3577 @*/ 3578 PetscErrorCode TSSetPostStage(TS ts, PetscErrorCode (*func)(TS,PetscReal,PetscInt,Vec*)) 3579 { 3580 PetscFunctionBegin; 3581 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3582 ts->poststage = func; 3583 PetscFunctionReturn(0); 3584 } 3585 3586 /*@C 3587 TSSetPostEvaluate - Sets the general-purpose function 3588 called once at the end of each step evaluation. 3589 3590 Logically Collective on TS 3591 3592 Input Parameters: 3593 + ts - The TS context obtained from TSCreate() 3594 - func - The function 3595 3596 Calling sequence of func: 3597 . PetscErrorCode func(TS ts); 3598 3599 Level: intermediate 3600 3601 Note: 3602 Semantically, TSSetPostEvaluate() differs from TSSetPostStep() since the function it sets is called before event-handling 3603 thus guaranteeing the same solution (computed by the time-stepper) will be passed to it. On the other hand, TSPostStep() 3604 may be passed a different solution, possibly changed by the event handler. TSPostEvaluate() is called after the next step 3605 solution is evaluated allowing to modify it, if need be. The solution can be obtained with TSGetSolution(), the time step 3606 with TSGetTimeStep(), and the time at the start of the step is available via TSGetTime() 3607 3608 .keywords: TS, timestep 3609 .seealso: TSSetPreStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext() 3610 @*/ 3611 PetscErrorCode TSSetPostEvaluate(TS ts, PetscErrorCode (*func)(TS)) 3612 { 3613 PetscFunctionBegin; 3614 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3615 ts->postevaluate = func; 3616 PetscFunctionReturn(0); 3617 } 3618 3619 /*@ 3620 TSPreStage - Runs the user-defined pre-stage function set using TSSetPreStage() 3621 3622 Collective on TS 3623 3624 Input Parameters: 3625 . ts - The TS context obtained from TSCreate() 3626 stagetime - The absolute time of the current stage 3627 3628 Notes: 3629 TSPreStage() is typically used within time stepping implementations, 3630 most users would not generally call this routine themselves. 3631 3632 Level: developer 3633 3634 .keywords: TS, timestep 3635 .seealso: TSPostStage(), TSSetPreStep(), TSPreStep(), TSPostStep() 3636 @*/ 3637 PetscErrorCode TSPreStage(TS ts, PetscReal stagetime) 3638 { 3639 PetscErrorCode ierr; 3640 3641 PetscFunctionBegin; 3642 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3643 if (ts->prestage) { 3644 PetscStackCallStandard((*ts->prestage),(ts,stagetime)); 3645 } 3646 PetscFunctionReturn(0); 3647 } 3648 3649 /*@ 3650 TSPostStage - Runs the user-defined post-stage function set using TSSetPostStage() 3651 3652 Collective on TS 3653 3654 Input Parameters: 3655 . ts - The TS context obtained from TSCreate() 3656 stagetime - The absolute time of the current stage 3657 stageindex - Stage number 3658 Y - Array of vectors (of size = total number 3659 of stages) with the stage solutions 3660 3661 Notes: 3662 TSPostStage() is typically used within time stepping implementations, 3663 most users would not generally call this routine themselves. 3664 3665 Level: developer 3666 3667 .keywords: TS, timestep 3668 .seealso: TSPreStage(), TSSetPreStep(), TSPreStep(), TSPostStep() 3669 @*/ 3670 PetscErrorCode TSPostStage(TS ts, PetscReal stagetime, PetscInt stageindex, Vec *Y) 3671 { 3672 PetscErrorCode ierr; 3673 3674 PetscFunctionBegin; 3675 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3676 if (ts->poststage) { 3677 PetscStackCallStandard((*ts->poststage),(ts,stagetime,stageindex,Y)); 3678 } 3679 PetscFunctionReturn(0); 3680 } 3681 3682 /*@ 3683 TSPostEvaluate - Runs the user-defined post-evaluate function set using TSSetPostEvaluate() 3684 3685 Collective on TS 3686 3687 Input Parameters: 3688 . ts - The TS context obtained from TSCreate() 3689 3690 Notes: 3691 TSPostEvaluate() is typically used within time stepping implementations, 3692 most users would not generally call this routine themselves. 3693 3694 Level: developer 3695 3696 .keywords: TS, timestep 3697 .seealso: TSSetPostEvaluate(), TSSetPreStep(), TSPreStep(), TSPostStep() 3698 @*/ 3699 PetscErrorCode TSPostEvaluate(TS ts) 3700 { 3701 PetscErrorCode ierr; 3702 3703 PetscFunctionBegin; 3704 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3705 if (ts->postevaluate) { 3706 Vec U; 3707 PetscObjectState sprev,spost; 3708 3709 ierr = TSGetSolution(ts,&U);CHKERRQ(ierr); 3710 ierr = PetscObjectStateGet((PetscObject)U,&sprev);CHKERRQ(ierr); 3711 PetscStackCallStandard((*ts->postevaluate),(ts)); 3712 ierr = PetscObjectStateGet((PetscObject)U,&spost);CHKERRQ(ierr); 3713 if (sprev != spost) {ierr = TSRestartStep(ts);CHKERRQ(ierr);} 3714 } 3715 PetscFunctionReturn(0); 3716 } 3717 3718 /*@C 3719 TSSetPostStep - Sets the general-purpose function 3720 called once at the end of each time step. 3721 3722 Logically Collective on TS 3723 3724 Input Parameters: 3725 + ts - The TS context obtained from TSCreate() 3726 - func - The function 3727 3728 Calling sequence of func: 3729 $ func (TS ts); 3730 3731 Notes: 3732 The function set by TSSetPostStep() is called after each successful step. The solution vector X 3733 obtained by TSGetSolution() may be different than that computed at the step end if the event handler 3734 locates an event and TSPostEvent() modifies it. Use TSSetPostEvaluate() if an unmodified solution is needed instead. 3735 3736 Level: intermediate 3737 3738 .keywords: TS, timestep 3739 .seealso: TSSetPreStep(), TSSetPreStage(), TSSetPostEvaluate(), TSGetTimeStep(), TSGetStepNumber(), TSGetTime(), TSRestartStep() 3740 @*/ 3741 PetscErrorCode TSSetPostStep(TS ts, PetscErrorCode (*func)(TS)) 3742 { 3743 PetscFunctionBegin; 3744 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3745 ts->poststep = func; 3746 PetscFunctionReturn(0); 3747 } 3748 3749 /*@ 3750 TSPostStep - Runs the user-defined post-step function. 3751 3752 Collective on TS 3753 3754 Input Parameters: 3755 . ts - The TS context obtained from TSCreate() 3756 3757 Notes: 3758 TSPostStep() is typically used within time stepping implementations, 3759 so most users would not generally call this routine themselves. 3760 3761 Level: developer 3762 3763 .keywords: TS, timestep 3764 @*/ 3765 PetscErrorCode TSPostStep(TS ts) 3766 { 3767 PetscErrorCode ierr; 3768 3769 PetscFunctionBegin; 3770 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3771 if (ts->poststep) { 3772 Vec U; 3773 PetscObjectState sprev,spost; 3774 3775 ierr = TSGetSolution(ts,&U);CHKERRQ(ierr); 3776 ierr = PetscObjectStateGet((PetscObject)U,&sprev);CHKERRQ(ierr); 3777 PetscStackCallStandard((*ts->poststep),(ts)); 3778 ierr = PetscObjectStateGet((PetscObject)U,&spost);CHKERRQ(ierr); 3779 if (sprev != spost) {ierr = TSRestartStep(ts);CHKERRQ(ierr);} 3780 } 3781 PetscFunctionReturn(0); 3782 } 3783 3784 /* ------------ Routines to set performance monitoring options ----------- */ 3785 3786 /*@C 3787 TSMonitorSet - Sets an ADDITIONAL function that is to be used at every 3788 timestep to display the iteration's progress. 3789 3790 Logically Collective on TS 3791 3792 Input Parameters: 3793 + ts - the TS context obtained from TSCreate() 3794 . monitor - monitoring routine 3795 . mctx - [optional] user-defined context for private data for the 3796 monitor routine (use NULL if no context is desired) 3797 - monitordestroy - [optional] routine that frees monitor context 3798 (may be NULL) 3799 3800 Calling sequence of monitor: 3801 $ PetscErrorCode monitor(TS ts,PetscInt steps,PetscReal time,Vec u,void *mctx) 3802 3803 + ts - the TS context 3804 . 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) 3805 . time - current time 3806 . u - current iterate 3807 - mctx - [optional] monitoring context 3808 3809 Notes: 3810 This routine adds an additional monitor to the list of monitors that 3811 already has been loaded. 3812 3813 Fortran notes: Only a single monitor function can be set for each TS object 3814 3815 Level: intermediate 3816 3817 .keywords: TS, timestep, set, monitor 3818 3819 .seealso: TSMonitorDefault(), TSMonitorCancel() 3820 @*/ 3821 PetscErrorCode TSMonitorSet(TS ts,PetscErrorCode (*monitor)(TS,PetscInt,PetscReal,Vec,void*),void *mctx,PetscErrorCode (*mdestroy)(void**)) 3822 { 3823 PetscErrorCode ierr; 3824 PetscInt i; 3825 PetscBool identical; 3826 3827 PetscFunctionBegin; 3828 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3829 for (i=0; i<ts->numbermonitors;i++) { 3830 ierr = PetscMonitorCompare((PetscErrorCode (*)(void))monitor,mctx,mdestroy,(PetscErrorCode (*)(void))ts->monitor[i],ts->monitorcontext[i],ts->monitordestroy[i],&identical);CHKERRQ(ierr); 3831 if (identical) PetscFunctionReturn(0); 3832 } 3833 if (ts->numbermonitors >= MAXTSMONITORS) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Too many monitors set"); 3834 ts->monitor[ts->numbermonitors] = monitor; 3835 ts->monitordestroy[ts->numbermonitors] = mdestroy; 3836 ts->monitorcontext[ts->numbermonitors++] = (void*)mctx; 3837 PetscFunctionReturn(0); 3838 } 3839 3840 /*@C 3841 TSMonitorCancel - Clears all the monitors that have been set on a time-step object. 3842 3843 Logically Collective on TS 3844 3845 Input Parameters: 3846 . ts - the TS context obtained from TSCreate() 3847 3848 Notes: 3849 There is no way to remove a single, specific monitor. 3850 3851 Level: intermediate 3852 3853 .keywords: TS, timestep, set, monitor 3854 3855 .seealso: TSMonitorDefault(), TSMonitorSet() 3856 @*/ 3857 PetscErrorCode TSMonitorCancel(TS ts) 3858 { 3859 PetscErrorCode ierr; 3860 PetscInt i; 3861 3862 PetscFunctionBegin; 3863 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3864 for (i=0; i<ts->numbermonitors; i++) { 3865 if (ts->monitordestroy[i]) { 3866 ierr = (*ts->monitordestroy[i])(&ts->monitorcontext[i]);CHKERRQ(ierr); 3867 } 3868 } 3869 ts->numbermonitors = 0; 3870 PetscFunctionReturn(0); 3871 } 3872 3873 /*@C 3874 TSMonitorDefault - The Default monitor, prints the timestep and time for each step 3875 3876 Level: intermediate 3877 3878 .keywords: TS, set, monitor 3879 3880 .seealso: TSMonitorSet() 3881 @*/ 3882 PetscErrorCode TSMonitorDefault(TS ts,PetscInt step,PetscReal ptime,Vec v,PetscViewerAndFormat *vf) 3883 { 3884 PetscErrorCode ierr; 3885 PetscViewer viewer = vf->viewer; 3886 PetscBool iascii,ibinary; 3887 3888 PetscFunctionBegin; 3889 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,4); 3890 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 3891 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&ibinary);CHKERRQ(ierr); 3892 ierr = PetscViewerPushFormat(viewer,vf->format);CHKERRQ(ierr); 3893 if (iascii) { 3894 ierr = PetscViewerASCIIAddTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 3895 if (step == -1){ /* this indicates it is an interpolated solution */ 3896 ierr = PetscViewerASCIIPrintf(viewer,"Interpolated solution at time %g between steps %D and %D\n",(double)ptime,ts->steps-1,ts->steps);CHKERRQ(ierr); 3897 } else { 3898 ierr = PetscViewerASCIIPrintf(viewer,"%D TS dt %g time %g%s",step,(double)ts->time_step,(double)ptime,ts->steprollback ? " (r)\n" : "\n");CHKERRQ(ierr); 3899 } 3900 ierr = PetscViewerASCIISubtractTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 3901 } else if (ibinary) { 3902 PetscMPIInt rank; 3903 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)viewer),&rank);CHKERRQ(ierr); 3904 if (!rank) { 3905 PetscBool skipHeader; 3906 PetscInt classid = REAL_FILE_CLASSID; 3907 3908 ierr = PetscViewerBinaryGetSkipHeader(viewer,&skipHeader);CHKERRQ(ierr); 3909 if (!skipHeader) { 3910 ierr = PetscViewerBinaryWrite(viewer,&classid,1,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); 3911 } 3912 ierr = PetscRealView(1,&ptime,viewer);CHKERRQ(ierr); 3913 } else { 3914 ierr = PetscRealView(0,&ptime,viewer);CHKERRQ(ierr); 3915 } 3916 } 3917 ierr = PetscViewerPopFormat(viewer);CHKERRQ(ierr); 3918 PetscFunctionReturn(0); 3919 } 3920 3921 /*@C 3922 TSAdjointMonitorSet - Sets an ADDITIONAL function that is to be used at every 3923 timestep to display the iteration's progress. 3924 3925 Logically Collective on TS 3926 3927 Input Parameters: 3928 + ts - the TS context obtained from TSCreate() 3929 . adjointmonitor - monitoring routine 3930 . adjointmctx - [optional] user-defined context for private data for the 3931 monitor routine (use NULL if no context is desired) 3932 - adjointmonitordestroy - [optional] routine that frees monitor context 3933 (may be NULL) 3934 3935 Calling sequence of monitor: 3936 $ int adjointmonitor(TS ts,PetscInt steps,PetscReal time,Vec u,PetscInt numcost,Vec *lambda, Vec *mu,void *adjointmctx) 3937 3938 + ts - the TS context 3939 . 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 3940 been interpolated to) 3941 . time - current time 3942 . u - current iterate 3943 . numcost - number of cost functionos 3944 . lambda - sensitivities to initial conditions 3945 . mu - sensitivities to parameters 3946 - adjointmctx - [optional] adjoint monitoring context 3947 3948 Notes: 3949 This routine adds an additional monitor to the list of monitors that 3950 already has been loaded. 3951 3952 Fortran notes: Only a single monitor function can be set for each TS object 3953 3954 Level: intermediate 3955 3956 .keywords: TS, timestep, set, adjoint, monitor 3957 3958 .seealso: TSAdjointMonitorCancel() 3959 @*/ 3960 PetscErrorCode TSAdjointMonitorSet(TS ts,PetscErrorCode (*adjointmonitor)(TS,PetscInt,PetscReal,Vec,PetscInt,Vec*,Vec*,void*),void *adjointmctx,PetscErrorCode (*adjointmdestroy)(void**)) 3961 { 3962 PetscErrorCode ierr; 3963 PetscInt i; 3964 PetscBool identical; 3965 3966 PetscFunctionBegin; 3967 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3968 for (i=0; i<ts->numbermonitors;i++) { 3969 ierr = PetscMonitorCompare((PetscErrorCode (*)(void))adjointmonitor,adjointmctx,adjointmdestroy,(PetscErrorCode (*)(void))ts->adjointmonitor[i],ts->adjointmonitorcontext[i],ts->adjointmonitordestroy[i],&identical);CHKERRQ(ierr); 3970 if (identical) PetscFunctionReturn(0); 3971 } 3972 if (ts->numberadjointmonitors >= MAXTSMONITORS) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Too many adjoint monitors set"); 3973 ts->adjointmonitor[ts->numberadjointmonitors] = adjointmonitor; 3974 ts->adjointmonitordestroy[ts->numberadjointmonitors] = adjointmdestroy; 3975 ts->adjointmonitorcontext[ts->numberadjointmonitors++] = (void*)adjointmctx; 3976 PetscFunctionReturn(0); 3977 } 3978 3979 /*@C 3980 TSAdjointMonitorCancel - Clears all the adjoint monitors that have been set on a time-step object. 3981 3982 Logically Collective on TS 3983 3984 Input Parameters: 3985 . ts - the TS context obtained from TSCreate() 3986 3987 Notes: 3988 There is no way to remove a single, specific monitor. 3989 3990 Level: intermediate 3991 3992 .keywords: TS, timestep, set, adjoint, monitor 3993 3994 .seealso: TSAdjointMonitorSet() 3995 @*/ 3996 PetscErrorCode TSAdjointMonitorCancel(TS ts) 3997 { 3998 PetscErrorCode ierr; 3999 PetscInt i; 4000 4001 PetscFunctionBegin; 4002 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4003 for (i=0; i<ts->numberadjointmonitors; i++) { 4004 if (ts->adjointmonitordestroy[i]) { 4005 ierr = (*ts->adjointmonitordestroy[i])(&ts->adjointmonitorcontext[i]);CHKERRQ(ierr); 4006 } 4007 } 4008 ts->numberadjointmonitors = 0; 4009 PetscFunctionReturn(0); 4010 } 4011 4012 /*@C 4013 TSAdjointMonitorDefault - the default monitor of adjoint computations 4014 4015 Level: intermediate 4016 4017 .keywords: TS, set, monitor 4018 4019 .seealso: TSAdjointMonitorSet() 4020 @*/ 4021 PetscErrorCode TSAdjointMonitorDefault(TS ts,PetscInt step,PetscReal ptime,Vec v,PetscInt numcost,Vec *lambda,Vec *mu,PetscViewerAndFormat *vf) 4022 { 4023 PetscErrorCode ierr; 4024 PetscViewer viewer = vf->viewer; 4025 4026 PetscFunctionBegin; 4027 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,4); 4028 ierr = PetscViewerPushFormat(viewer,vf->format);CHKERRQ(ierr); 4029 ierr = PetscViewerASCIIAddTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 4030 ierr = PetscViewerASCIIPrintf(viewer,"%D TS dt %g time %g%s",step,(double)ts->time_step,(double)ptime,ts->steprollback ? " (r)\n" : "\n");CHKERRQ(ierr); 4031 ierr = PetscViewerASCIISubtractTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 4032 ierr = PetscViewerPopFormat(viewer);CHKERRQ(ierr); 4033 PetscFunctionReturn(0); 4034 } 4035 4036 /*@ 4037 TSInterpolate - Interpolate the solution computed during the previous step to an arbitrary location in the interval 4038 4039 Collective on TS 4040 4041 Input Argument: 4042 + ts - time stepping context 4043 - t - time to interpolate to 4044 4045 Output Argument: 4046 . U - state at given time 4047 4048 Level: intermediate 4049 4050 Developer Notes: 4051 TSInterpolate() and the storing of previous steps/stages should be generalized to support delay differential equations and continuous adjoints. 4052 4053 .keywords: TS, set 4054 4055 .seealso: TSSetExactFinalTime(), TSSolve() 4056 @*/ 4057 PetscErrorCode TSInterpolate(TS ts,PetscReal t,Vec U) 4058 { 4059 PetscErrorCode ierr; 4060 4061 PetscFunctionBegin; 4062 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4063 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 4064 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); 4065 if (!ts->ops->interpolate) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"%s does not provide interpolation",((PetscObject)ts)->type_name); 4066 ierr = (*ts->ops->interpolate)(ts,t,U);CHKERRQ(ierr); 4067 PetscFunctionReturn(0); 4068 } 4069 4070 /*@ 4071 TSStep - Steps one time step 4072 4073 Collective on TS 4074 4075 Input Parameter: 4076 . ts - the TS context obtained from TSCreate() 4077 4078 Level: developer 4079 4080 Notes: 4081 The public interface for the ODE/DAE solvers is TSSolve(), you should almost for sure be using that routine and not this routine. 4082 4083 The hook set using TSSetPreStep() is called before each attempt to take the step. In general, the time step size may 4084 be changed due to adaptive error controller or solve failures. Note that steps may contain multiple stages. 4085 4086 This may over-step the final time provided in TSSetMaxTime() depending on the time-step used. TSSolve() interpolates to exactly the 4087 time provided in TSSetMaxTime(). One can use TSInterpolate() to determine an interpolated solution within the final timestep. 4088 4089 .keywords: TS, timestep, solve 4090 4091 .seealso: TSCreate(), TSSetUp(), TSDestroy(), TSSolve(), TSSetPreStep(), TSSetPreStage(), TSSetPostStage(), TSInterpolate() 4092 @*/ 4093 PetscErrorCode TSStep(TS ts) 4094 { 4095 PetscErrorCode ierr; 4096 static PetscBool cite = PETSC_FALSE; 4097 PetscReal ptime; 4098 4099 PetscFunctionBegin; 4100 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4101 ierr = PetscCitationsRegister("@techreport{tspaper,\n" 4102 " title = {{PETSc/TS}: A Modern Scalable {DAE/ODE} Solver Library},\n" 4103 " author = {Shrirang Abhyankar and Jed Brown and Emil Constantinescu and Debojyoti Ghosh and Barry F. Smith},\n" 4104 " type = {Preprint},\n" 4105 " number = {ANL/MCS-P5061-0114},\n" 4106 " institution = {Argonne National Laboratory},\n" 4107 " year = {2014}\n}\n",&cite);CHKERRQ(ierr); 4108 4109 ierr = TSSetUp(ts);CHKERRQ(ierr); 4110 ierr = TSTrajectorySetUp(ts->trajectory,ts);CHKERRQ(ierr); 4111 4112 if (ts->max_time >= PETSC_MAX_REAL && ts->max_steps == PETSC_MAX_INT) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"You must call TSSetMaxTime() or TSSetMaxSteps(), or use -ts_max_time <time> or -ts_max_steps <steps>"); 4113 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()"); 4114 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"); 4115 4116 if (!ts->steps) ts->ptime_prev = ts->ptime; 4117 ptime = ts->ptime; ts->ptime_prev_rollback = ts->ptime_prev; 4118 ts->reason = TS_CONVERGED_ITERATING; 4119 if (!ts->ops->step) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSStep not implemented for type '%s'",((PetscObject)ts)->type_name); 4120 ierr = PetscLogEventBegin(TS_Step,ts,0,0,0);CHKERRQ(ierr); 4121 ierr = (*ts->ops->step)(ts);CHKERRQ(ierr); 4122 ierr = PetscLogEventEnd(TS_Step,ts,0,0,0);CHKERRQ(ierr); 4123 ts->ptime_prev = ptime; 4124 ts->steps++; 4125 ts->steprollback = PETSC_FALSE; 4126 ts->steprestart = PETSC_FALSE; 4127 4128 if (ts->reason < 0) { 4129 if (ts->errorifstepfailed) { 4130 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]); 4131 else SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s",TSConvergedReasons[ts->reason]); 4132 } 4133 } else if (!ts->reason) { 4134 if (ts->steps >= ts->max_steps) ts->reason = TS_CONVERGED_ITS; 4135 else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME; 4136 } 4137 PetscFunctionReturn(0); 4138 } 4139 4140 /*@ 4141 TSAdjointStep - Steps one time step backward in the adjoint run 4142 4143 Collective on TS 4144 4145 Input Parameter: 4146 . ts - the TS context obtained from TSCreate() 4147 4148 Level: intermediate 4149 4150 .keywords: TS, adjoint, step 4151 4152 .seealso: TSAdjointSetUp(), TSAdjointSolve() 4153 @*/ 4154 PetscErrorCode TSAdjointStep(TS ts) 4155 { 4156 DM dm; 4157 PetscErrorCode ierr; 4158 4159 PetscFunctionBegin; 4160 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4161 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 4162 ierr = TSAdjointSetUp(ts);CHKERRQ(ierr); 4163 4164 ierr = VecViewFromOptions(ts->vec_sol,(PetscObject)ts,"-ts_view_solution");CHKERRQ(ierr); 4165 4166 ts->reason = TS_CONVERGED_ITERATING; 4167 ts->ptime_prev = ts->ptime; 4168 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); 4169 ierr = PetscLogEventBegin(TS_AdjointStep,ts,0,0,0);CHKERRQ(ierr); 4170 ierr = (*ts->ops->adjointstep)(ts);CHKERRQ(ierr); 4171 ierr = PetscLogEventEnd(TS_AdjointStep,ts,0,0,0);CHKERRQ(ierr); 4172 ts->adjoint_steps++; ts->steps--; 4173 4174 if (ts->reason < 0) { 4175 if (ts->errorifstepfailed) { 4176 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]); 4177 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]); 4178 else SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s",TSConvergedReasons[ts->reason]); 4179 } 4180 } else if (!ts->reason) { 4181 if (ts->adjoint_steps >= ts->adjoint_max_steps) ts->reason = TS_CONVERGED_ITS; 4182 } 4183 PetscFunctionReturn(0); 4184 } 4185 4186 /*@ 4187 TSEvaluateWLTE - Evaluate the weighted local truncation error norm 4188 at the end of a time step with a given order of accuracy. 4189 4190 Collective on TS 4191 4192 Input Arguments: 4193 + ts - time stepping context 4194 . wnormtype - norm type, either NORM_2 or NORM_INFINITY 4195 - order - optional, desired order for the error evaluation or PETSC_DECIDE 4196 4197 Output Arguments: 4198 + order - optional, the actual order of the error evaluation 4199 - wlte - the weighted local truncation error norm 4200 4201 Level: advanced 4202 4203 Notes: 4204 If the timestepper cannot evaluate the error in a particular step 4205 (eg. in the first step or restart steps after event handling), 4206 this routine returns wlte=-1.0 . 4207 4208 .seealso: TSStep(), TSAdapt, TSErrorWeightedNorm() 4209 @*/ 4210 PetscErrorCode TSEvaluateWLTE(TS ts,NormType wnormtype,PetscInt *order,PetscReal *wlte) 4211 { 4212 PetscErrorCode ierr; 4213 4214 PetscFunctionBegin; 4215 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4216 PetscValidType(ts,1); 4217 PetscValidLogicalCollectiveEnum(ts,wnormtype,4); 4218 if (order) PetscValidIntPointer(order,3); 4219 if (order) PetscValidLogicalCollectiveInt(ts,*order,3); 4220 PetscValidRealPointer(wlte,4); 4221 if (wnormtype != NORM_2 && wnormtype != NORM_INFINITY) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]); 4222 if (!ts->ops->evaluatewlte) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSEvaluateWLTE not implemented for type '%s'",((PetscObject)ts)->type_name); 4223 ierr = (*ts->ops->evaluatewlte)(ts,wnormtype,order,wlte);CHKERRQ(ierr); 4224 PetscFunctionReturn(0); 4225 } 4226 4227 /*@ 4228 TSEvaluateStep - Evaluate the solution at the end of a time step with a given order of accuracy. 4229 4230 Collective on TS 4231 4232 Input Arguments: 4233 + ts - time stepping context 4234 . order - desired order of accuracy 4235 - done - whether the step was evaluated at this order (pass NULL to generate an error if not available) 4236 4237 Output Arguments: 4238 . U - state at the end of the current step 4239 4240 Level: advanced 4241 4242 Notes: 4243 This function cannot be called until all stages have been evaluated. 4244 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. 4245 4246 .seealso: TSStep(), TSAdapt 4247 @*/ 4248 PetscErrorCode TSEvaluateStep(TS ts,PetscInt order,Vec U,PetscBool *done) 4249 { 4250 PetscErrorCode ierr; 4251 4252 PetscFunctionBegin; 4253 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4254 PetscValidType(ts,1); 4255 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 4256 if (!ts->ops->evaluatestep) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSEvaluateStep not implemented for type '%s'",((PetscObject)ts)->type_name); 4257 ierr = (*ts->ops->evaluatestep)(ts,order,U,done);CHKERRQ(ierr); 4258 PetscFunctionReturn(0); 4259 } 4260 4261 /*@ 4262 TSForwardCostIntegral - Evaluate the cost integral in the forward run. 4263 4264 Collective on TS 4265 4266 Input Arguments: 4267 . ts - time stepping context 4268 4269 Level: advanced 4270 4271 Notes: 4272 This function cannot be called until TSStep() has been completed. 4273 4274 .seealso: TSSolve(), TSAdjointCostIntegral() 4275 @*/ 4276 PetscErrorCode TSForwardCostIntegral(TS ts) 4277 { 4278 PetscErrorCode ierr; 4279 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4280 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); 4281 ierr = (*ts->ops->forwardintegral)(ts);CHKERRQ(ierr); 4282 PetscFunctionReturn(0); 4283 } 4284 4285 /*@ 4286 TSSolve - Steps the requested number of timesteps. 4287 4288 Collective on TS 4289 4290 Input Parameter: 4291 + ts - the TS context obtained from TSCreate() 4292 - u - the solution vector (can be null if TSSetSolution() was used and TSSetExactFinalTime(ts,TS_EXACTFINALTIME_MATCHSTEP) was not used, 4293 otherwise must contain the initial conditions and will contain the solution at the final requested time 4294 4295 Level: beginner 4296 4297 Notes: 4298 The final time returned by this function may be different from the time of the internally 4299 held state accessible by TSGetSolution() and TSGetTime() because the method may have 4300 stepped over the final time. 4301 4302 .keywords: TS, timestep, solve 4303 4304 .seealso: TSCreate(), TSSetSolution(), TSStep(), TSGetTime(), TSGetSolveTime() 4305 @*/ 4306 PetscErrorCode TSSolve(TS ts,Vec u) 4307 { 4308 Vec solution; 4309 PetscErrorCode ierr; 4310 4311 PetscFunctionBegin; 4312 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4313 if (u) PetscValidHeaderSpecific(u,VEC_CLASSID,2); 4314 4315 if (ts->exact_final_time == TS_EXACTFINALTIME_INTERPOLATE && u) { /* Need ts->vec_sol to be distinct so it is not overwritten when we interpolate at the end */ 4316 if (!ts->vec_sol || u == ts->vec_sol) { 4317 ierr = VecDuplicate(u,&solution);CHKERRQ(ierr); 4318 ierr = TSSetSolution(ts,solution);CHKERRQ(ierr); 4319 ierr = VecDestroy(&solution);CHKERRQ(ierr); /* grant ownership */ 4320 } 4321 ierr = VecCopy(u,ts->vec_sol);CHKERRQ(ierr); 4322 if (ts->forward_solve) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Sensitivity analysis does not support the mode TS_EXACTFINALTIME_INTERPOLATE"); 4323 } else if (u) { 4324 ierr = TSSetSolution(ts,u);CHKERRQ(ierr); 4325 } 4326 ierr = TSSetUp(ts);CHKERRQ(ierr); 4327 ierr = TSTrajectorySetUp(ts->trajectory,ts);CHKERRQ(ierr); 4328 4329 if (ts->max_time >= PETSC_MAX_REAL && ts->max_steps == PETSC_MAX_INT) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"You must call TSSetMaxTime() or TSSetMaxSteps(), or use -ts_max_time <time> or -ts_max_steps <steps>"); 4330 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()"); 4331 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"); 4332 4333 if (ts->forward_solve) { 4334 ierr = TSForwardSetUp(ts);CHKERRQ(ierr); 4335 } 4336 4337 /* reset number of steps only when the step is not restarted. ARKIMEX 4338 restarts the step after an event. Resetting these counters in such case causes 4339 TSTrajectory to incorrectly save the output files 4340 */ 4341 /* reset time step and iteration counters */ 4342 if (!ts->steps) { 4343 ts->ksp_its = 0; 4344 ts->snes_its = 0; 4345 ts->num_snes_failures = 0; 4346 ts->reject = 0; 4347 ts->steprestart = PETSC_TRUE; 4348 ts->steprollback = PETSC_FALSE; 4349 } 4350 if (ts->exact_final_time == TS_EXACTFINALTIME_MATCHSTEP && ts->ptime + ts->time_step > ts->max_time) ts->time_step = ts->max_time - ts->ptime; 4351 ts->reason = TS_CONVERGED_ITERATING; 4352 4353 ierr = TSViewFromOptions(ts,NULL,"-ts_view_pre");CHKERRQ(ierr); 4354 4355 if (ts->ops->solve) { /* This private interface is transitional and should be removed when all implementations are updated. */ 4356 ierr = (*ts->ops->solve)(ts);CHKERRQ(ierr); 4357 if (u) {ierr = VecCopy(ts->vec_sol,u);CHKERRQ(ierr);} 4358 ts->solvetime = ts->ptime; 4359 solution = ts->vec_sol; 4360 } else { /* Step the requested number of timesteps. */ 4361 if (ts->steps >= ts->max_steps) ts->reason = TS_CONVERGED_ITS; 4362 else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME; 4363 4364 if (!ts->steps) { 4365 ierr = TSTrajectorySet(ts->trajectory,ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 4366 ierr = TSEventInitialize(ts->event,ts,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 4367 } 4368 4369 while (!ts->reason) { 4370 ierr = TSMonitor(ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 4371 if (!ts->steprollback) { 4372 ierr = TSPreStep(ts);CHKERRQ(ierr); 4373 } 4374 ierr = TSStep(ts);CHKERRQ(ierr); 4375 if (ts->vec_costintegral && ts->costintegralfwd) { /* Must evaluate the cost integral before event is handled. The cost integral value can also be rolled back. */ 4376 ierr = TSForwardCostIntegral(ts);CHKERRQ(ierr); 4377 } 4378 if (ts->forward_solve) { /* compute forward sensitivities before event handling because postevent() may change RHS and jump conditions may have to be applied */ 4379 ierr = TSForwardStep(ts);CHKERRQ(ierr); 4380 } 4381 ierr = TSPostEvaluate(ts);CHKERRQ(ierr); 4382 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. */ 4383 if (ts->steprollback) { 4384 ierr = TSPostEvaluate(ts);CHKERRQ(ierr); 4385 } 4386 if (!ts->steprollback) { 4387 ierr = TSTrajectorySet(ts->trajectory,ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 4388 ierr = TSPostStep(ts);CHKERRQ(ierr); 4389 } 4390 } 4391 ierr = TSMonitor(ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 4392 4393 if (ts->exact_final_time == TS_EXACTFINALTIME_INTERPOLATE && ts->ptime > ts->max_time) { 4394 ierr = TSInterpolate(ts,ts->max_time,u);CHKERRQ(ierr); 4395 ts->solvetime = ts->max_time; 4396 solution = u; 4397 ierr = TSMonitor(ts,-1,ts->solvetime,solution);CHKERRQ(ierr); 4398 } else { 4399 if (u) {ierr = VecCopy(ts->vec_sol,u);CHKERRQ(ierr);} 4400 ts->solvetime = ts->ptime; 4401 solution = ts->vec_sol; 4402 } 4403 } 4404 4405 ierr = TSViewFromOptions(ts,NULL,"-ts_view");CHKERRQ(ierr); 4406 ierr = VecViewFromOptions(solution,NULL,"-ts_view_solution");CHKERRQ(ierr); 4407 ierr = PetscObjectSAWsBlock((PetscObject)ts);CHKERRQ(ierr); 4408 if (ts->adjoint_solve) { 4409 ierr = TSAdjointSolve(ts);CHKERRQ(ierr); 4410 } 4411 PetscFunctionReturn(0); 4412 } 4413 4414 /*@ 4415 TSAdjointCostIntegral - Evaluate the cost integral in the adjoint run. 4416 4417 Collective on TS 4418 4419 Input Arguments: 4420 . ts - time stepping context 4421 4422 Level: advanced 4423 4424 Notes: 4425 This function cannot be called until TSAdjointStep() has been completed. 4426 4427 .seealso: TSAdjointSolve(), TSAdjointStep 4428 @*/ 4429 PetscErrorCode TSAdjointCostIntegral(TS ts) 4430 { 4431 PetscErrorCode ierr; 4432 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4433 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); 4434 ierr = (*ts->ops->adjointintegral)(ts);CHKERRQ(ierr); 4435 PetscFunctionReturn(0); 4436 } 4437 4438 /*@ 4439 TSAdjointSolve - Solves the discrete ajoint problem for an ODE/DAE 4440 4441 Collective on TS 4442 4443 Input Parameter: 4444 . ts - the TS context obtained from TSCreate() 4445 4446 Options Database: 4447 . -ts_adjoint_view_solution <viewerinfo> - views the first gradient with respect to the initial values 4448 4449 Level: intermediate 4450 4451 Notes: 4452 This must be called after a call to TSSolve() that solves the forward problem 4453 4454 By default this will integrate back to the initial time, one can use TSAdjointSetSteps() to step back to a later time 4455 4456 .keywords: TS, timestep, solve 4457 4458 .seealso: TSCreate(), TSSetCostGradients(), TSSetSolution(), TSAdjointStep() 4459 @*/ 4460 PetscErrorCode TSAdjointSolve(TS ts) 4461 { 4462 PetscErrorCode ierr; 4463 4464 PetscFunctionBegin; 4465 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4466 ierr = TSAdjointSetUp(ts);CHKERRQ(ierr); 4467 4468 /* reset time step and iteration counters */ 4469 ts->adjoint_steps = 0; 4470 ts->ksp_its = 0; 4471 ts->snes_its = 0; 4472 ts->num_snes_failures = 0; 4473 ts->reject = 0; 4474 ts->reason = TS_CONVERGED_ITERATING; 4475 4476 if (!ts->adjoint_max_steps) ts->adjoint_max_steps = ts->steps; 4477 if (ts->adjoint_steps >= ts->adjoint_max_steps) ts->reason = TS_CONVERGED_ITS; 4478 4479 while (!ts->reason) { 4480 ierr = TSTrajectoryGet(ts->trajectory,ts,ts->steps,&ts->ptime);CHKERRQ(ierr); 4481 ierr = TSAdjointMonitor(ts,ts->steps,ts->ptime,ts->vec_sol,ts->numcost,ts->vecs_sensi,ts->vecs_sensip);CHKERRQ(ierr); 4482 ierr = TSAdjointEventHandler(ts);CHKERRQ(ierr); 4483 ierr = TSAdjointStep(ts);CHKERRQ(ierr); 4484 if (ts->vec_costintegral && !ts->costintegralfwd) { 4485 ierr = TSAdjointCostIntegral(ts);CHKERRQ(ierr); 4486 } 4487 } 4488 ierr = TSTrajectoryGet(ts->trajectory,ts,ts->steps,&ts->ptime);CHKERRQ(ierr); 4489 ierr = TSAdjointMonitor(ts,ts->steps,ts->ptime,ts->vec_sol,ts->numcost,ts->vecs_sensi,ts->vecs_sensip);CHKERRQ(ierr); 4490 ts->solvetime = ts->ptime; 4491 ierr = TSTrajectoryViewFromOptions(ts->trajectory,NULL,"-ts_trajectory_view");CHKERRQ(ierr); 4492 ierr = VecViewFromOptions(ts->vecs_sensi[0],(PetscObject) ts, "-ts_adjoint_view_solution");CHKERRQ(ierr); 4493 PetscFunctionReturn(0); 4494 } 4495 4496 /*@C 4497 TSMonitor - Runs all user-provided monitor routines set using TSMonitorSet() 4498 4499 Collective on TS 4500 4501 Input Parameters: 4502 + ts - time stepping context obtained from TSCreate() 4503 . step - step number that has just completed 4504 . ptime - model time of the state 4505 - u - state at the current model time 4506 4507 Notes: 4508 TSMonitor() is typically used automatically within the time stepping implementations. 4509 Users would almost never call this routine directly. 4510 4511 A step of -1 indicates that the monitor is being called on a solution obtained by interpolating from computed solutions 4512 4513 Level: developer 4514 4515 .keywords: TS, timestep 4516 @*/ 4517 PetscErrorCode TSMonitor(TS ts,PetscInt step,PetscReal ptime,Vec u) 4518 { 4519 DM dm; 4520 PetscInt i,n = ts->numbermonitors; 4521 PetscErrorCode ierr; 4522 4523 PetscFunctionBegin; 4524 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4525 PetscValidHeaderSpecific(u,VEC_CLASSID,4); 4526 4527 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 4528 ierr = DMSetOutputSequenceNumber(dm,step,ptime);CHKERRQ(ierr); 4529 4530 ierr = VecLockPush(u);CHKERRQ(ierr); 4531 for (i=0; i<n; i++) { 4532 ierr = (*ts->monitor[i])(ts,step,ptime,u,ts->monitorcontext[i]);CHKERRQ(ierr); 4533 } 4534 ierr = VecLockPop(u);CHKERRQ(ierr); 4535 PetscFunctionReturn(0); 4536 } 4537 4538 /*@C 4539 TSAdjointMonitor - Runs all user-provided adjoint monitor routines set using TSAdjointMonitorSet() 4540 4541 Collective on TS 4542 4543 Input Parameters: 4544 + ts - time stepping context obtained from TSCreate() 4545 . step - step number that has just completed 4546 . ptime - model time of the state 4547 . u - state at the current model time 4548 . numcost - number of cost functions (dimension of lambda or mu) 4549 . lambda - vectors containing the gradients of the cost functions with respect to the ODE/DAE solution variables 4550 - mu - vectors containing the gradients of the cost functions with respect to the problem parameters 4551 4552 Notes: 4553 TSAdjointMonitor() is typically used automatically within the time stepping implementations. 4554 Users would almost never call this routine directly. 4555 4556 Level: developer 4557 4558 .keywords: TS, timestep 4559 @*/ 4560 PetscErrorCode TSAdjointMonitor(TS ts,PetscInt step,PetscReal ptime,Vec u,PetscInt numcost,Vec *lambda, Vec *mu) 4561 { 4562 PetscErrorCode ierr; 4563 PetscInt i,n = ts->numberadjointmonitors; 4564 4565 PetscFunctionBegin; 4566 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4567 PetscValidHeaderSpecific(u,VEC_CLASSID,4); 4568 ierr = VecLockPush(u);CHKERRQ(ierr); 4569 for (i=0; i<n; i++) { 4570 ierr = (*ts->adjointmonitor[i])(ts,step,ptime,u,numcost,lambda,mu,ts->adjointmonitorcontext[i]);CHKERRQ(ierr); 4571 } 4572 ierr = VecLockPop(u);CHKERRQ(ierr); 4573 PetscFunctionReturn(0); 4574 } 4575 4576 /* ------------------------------------------------------------------------*/ 4577 /*@C 4578 TSMonitorLGCtxCreate - Creates a TSMonitorLGCtx context for use with 4579 TS to monitor the solution process graphically in various ways 4580 4581 Collective on TS 4582 4583 Input Parameters: 4584 + host - the X display to open, or null for the local machine 4585 . label - the title to put in the title bar 4586 . x, y - the screen coordinates of the upper left coordinate of the window 4587 . m, n - the screen width and height in pixels 4588 - howoften - if positive then determines the frequency of the plotting, if -1 then only at the final time 4589 4590 Output Parameter: 4591 . ctx - the context 4592 4593 Options Database Key: 4594 + -ts_monitor_lg_timestep - automatically sets line graph monitor 4595 + -ts_monitor_lg_timestep_log - automatically sets line graph monitor 4596 . -ts_monitor_lg_solution - monitor the solution (or certain values of the solution by calling TSMonitorLGSetDisplayVariables() or TSMonitorLGCtxSetDisplayVariables()) 4597 . -ts_monitor_lg_error - monitor the error 4598 . -ts_monitor_lg_ksp_iterations - monitor the number of KSP iterations needed for each timestep 4599 . -ts_monitor_lg_snes_iterations - monitor the number of SNES iterations needed for each timestep 4600 - -lg_use_markers <true,false> - mark the data points (at each time step) on the plot; default is true 4601 4602 Notes: 4603 Use TSMonitorLGCtxDestroy() to destroy. 4604 4605 One can provide a function that transforms the solution before plotting it with TSMonitorLGCtxSetTransform() or TSMonitorLGSetTransform() 4606 4607 Many of the functions that control the monitoring have two forms: TSMonitorLGSet/GetXXXX() and TSMonitorLGCtxSet/GetXXXX() the first take a TS object as the 4608 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 4609 as the first argument. 4610 4611 One can control the names displayed for each solution or error variable with TSMonitorLGCtxSetVariableNames() or TSMonitorLGSetVariableNames() 4612 4613 Level: intermediate 4614 4615 .keywords: TS, monitor, line graph, residual 4616 4617 .seealso: TSMonitorLGTimeStep(), TSMonitorSet(), TSMonitorLGSolution(), TSMonitorLGError(), TSMonitorDefault(), VecView(), 4618 TSMonitorLGCtxCreate(), TSMonitorLGCtxSetVariableNames(), TSMonitorLGCtxGetVariableNames(), 4619 TSMonitorLGSetVariableNames(), TSMonitorLGGetVariableNames(), TSMonitorLGSetDisplayVariables(), TSMonitorLGCtxSetDisplayVariables(), 4620 TSMonitorLGCtxSetTransform(), TSMonitorLGSetTransform(), TSMonitorLGError(), TSMonitorLGSNESIterations(), TSMonitorLGKSPIterations(), 4621 TSMonitorEnvelopeCtxCreate(), TSMonitorEnvelopeGetBounds(), TSMonitorEnvelopeCtxDestroy(), TSMonitorEnvelop() 4622 4623 @*/ 4624 PetscErrorCode TSMonitorLGCtxCreate(MPI_Comm comm,const char host[],const char label[],int x,int y,int m,int n,PetscInt howoften,TSMonitorLGCtx *ctx) 4625 { 4626 PetscDraw draw; 4627 PetscErrorCode ierr; 4628 4629 PetscFunctionBegin; 4630 ierr = PetscNew(ctx);CHKERRQ(ierr); 4631 ierr = PetscDrawCreate(comm,host,label,x,y,m,n,&draw);CHKERRQ(ierr); 4632 ierr = PetscDrawSetFromOptions(draw);CHKERRQ(ierr); 4633 ierr = PetscDrawLGCreate(draw,1,&(*ctx)->lg);CHKERRQ(ierr); 4634 ierr = PetscDrawLGSetFromOptions((*ctx)->lg);CHKERRQ(ierr); 4635 ierr = PetscDrawDestroy(&draw);CHKERRQ(ierr); 4636 (*ctx)->howoften = howoften; 4637 PetscFunctionReturn(0); 4638 } 4639 4640 PetscErrorCode TSMonitorLGTimeStep(TS ts,PetscInt step,PetscReal ptime,Vec v,void *monctx) 4641 { 4642 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 4643 PetscReal x = ptime,y; 4644 PetscErrorCode ierr; 4645 4646 PetscFunctionBegin; 4647 if (step < 0) PetscFunctionReturn(0); /* -1 indicates an interpolated solution */ 4648 if (!step) { 4649 PetscDrawAxis axis; 4650 const char *ylabel = ctx->semilogy ? "Log Time Step" : "Time Step"; 4651 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 4652 ierr = PetscDrawAxisSetLabels(axis,"Timestep as function of time","Time",ylabel);CHKERRQ(ierr); 4653 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 4654 } 4655 ierr = TSGetTimeStep(ts,&y);CHKERRQ(ierr); 4656 if (ctx->semilogy) y = PetscLog10Real(y); 4657 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 4658 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 4659 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 4660 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 4661 } 4662 PetscFunctionReturn(0); 4663 } 4664 4665 /*@C 4666 TSMonitorLGCtxDestroy - Destroys a line graph context that was created 4667 with TSMonitorLGCtxCreate(). 4668 4669 Collective on TSMonitorLGCtx 4670 4671 Input Parameter: 4672 . ctx - the monitor context 4673 4674 Level: intermediate 4675 4676 .keywords: TS, monitor, line graph, destroy 4677 4678 .seealso: TSMonitorLGCtxCreate(), TSMonitorSet(), TSMonitorLGTimeStep(); 4679 @*/ 4680 PetscErrorCode TSMonitorLGCtxDestroy(TSMonitorLGCtx *ctx) 4681 { 4682 PetscErrorCode ierr; 4683 4684 PetscFunctionBegin; 4685 if ((*ctx)->transformdestroy) { 4686 ierr = ((*ctx)->transformdestroy)((*ctx)->transformctx);CHKERRQ(ierr); 4687 } 4688 ierr = PetscDrawLGDestroy(&(*ctx)->lg);CHKERRQ(ierr); 4689 ierr = PetscStrArrayDestroy(&(*ctx)->names);CHKERRQ(ierr); 4690 ierr = PetscStrArrayDestroy(&(*ctx)->displaynames);CHKERRQ(ierr); 4691 ierr = PetscFree((*ctx)->displayvariables);CHKERRQ(ierr); 4692 ierr = PetscFree((*ctx)->displayvalues);CHKERRQ(ierr); 4693 ierr = PetscFree(*ctx);CHKERRQ(ierr); 4694 PetscFunctionReturn(0); 4695 } 4696 4697 /*@ 4698 TSGetTime - Gets the time of the most recently completed step. 4699 4700 Not Collective 4701 4702 Input Parameter: 4703 . ts - the TS context obtained from TSCreate() 4704 4705 Output Parameter: 4706 . t - the current time. This time may not corresponds to the final time set with TSSetMaxTime(), use TSGetSolveTime(). 4707 4708 Level: beginner 4709 4710 Note: 4711 When called during time step evaluation (e.g. during residual evaluation or via hooks set using TSSetPreStep(), 4712 TSSetPreStage(), TSSetPostStage(), or TSSetPostStep()), the time is the time at the start of the step being evaluated. 4713 4714 .seealso: TSGetSolveTime(), TSSetTime(), TSGetTimeStep() 4715 4716 .keywords: TS, get, time 4717 @*/ 4718 PetscErrorCode TSGetTime(TS ts,PetscReal *t) 4719 { 4720 PetscFunctionBegin; 4721 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4722 PetscValidRealPointer(t,2); 4723 *t = ts->ptime; 4724 PetscFunctionReturn(0); 4725 } 4726 4727 /*@ 4728 TSGetPrevTime - Gets the starting time of the previously completed step. 4729 4730 Not Collective 4731 4732 Input Parameter: 4733 . ts - the TS context obtained from TSCreate() 4734 4735 Output Parameter: 4736 . t - the previous time 4737 4738 Level: beginner 4739 4740 .seealso: TSGetTime(), TSGetSolveTime(), TSGetTimeStep() 4741 4742 .keywords: TS, get, time 4743 @*/ 4744 PetscErrorCode TSGetPrevTime(TS ts,PetscReal *t) 4745 { 4746 PetscFunctionBegin; 4747 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4748 PetscValidRealPointer(t,2); 4749 *t = ts->ptime_prev; 4750 PetscFunctionReturn(0); 4751 } 4752 4753 /*@ 4754 TSSetTime - Allows one to reset the time. 4755 4756 Logically Collective on TS 4757 4758 Input Parameters: 4759 + ts - the TS context obtained from TSCreate() 4760 - time - the time 4761 4762 Level: intermediate 4763 4764 .seealso: TSGetTime(), TSSetMaxSteps() 4765 4766 .keywords: TS, set, time 4767 @*/ 4768 PetscErrorCode TSSetTime(TS ts, PetscReal t) 4769 { 4770 PetscFunctionBegin; 4771 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4772 PetscValidLogicalCollectiveReal(ts,t,2); 4773 ts->ptime = t; 4774 PetscFunctionReturn(0); 4775 } 4776 4777 /*@C 4778 TSSetOptionsPrefix - Sets the prefix used for searching for all 4779 TS options in the database. 4780 4781 Logically Collective on TS 4782 4783 Input Parameter: 4784 + ts - The TS context 4785 - prefix - The prefix to prepend to all option names 4786 4787 Notes: 4788 A hyphen (-) must NOT be given at the beginning of the prefix name. 4789 The first character of all runtime options is AUTOMATICALLY the 4790 hyphen. 4791 4792 Level: advanced 4793 4794 .keywords: TS, set, options, prefix, database 4795 4796 .seealso: TSSetFromOptions() 4797 4798 @*/ 4799 PetscErrorCode TSSetOptionsPrefix(TS ts,const char prefix[]) 4800 { 4801 PetscErrorCode ierr; 4802 SNES snes; 4803 4804 PetscFunctionBegin; 4805 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4806 ierr = PetscObjectSetOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 4807 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4808 ierr = SNESSetOptionsPrefix(snes,prefix);CHKERRQ(ierr); 4809 PetscFunctionReturn(0); 4810 } 4811 4812 /*@C 4813 TSAppendOptionsPrefix - Appends to the prefix used for searching for all 4814 TS options in the database. 4815 4816 Logically Collective on TS 4817 4818 Input Parameter: 4819 + ts - The TS context 4820 - prefix - The prefix to prepend to all option names 4821 4822 Notes: 4823 A hyphen (-) must NOT be given at the beginning of the prefix name. 4824 The first character of all runtime options is AUTOMATICALLY the 4825 hyphen. 4826 4827 Level: advanced 4828 4829 .keywords: TS, append, options, prefix, database 4830 4831 .seealso: TSGetOptionsPrefix() 4832 4833 @*/ 4834 PetscErrorCode TSAppendOptionsPrefix(TS ts,const char prefix[]) 4835 { 4836 PetscErrorCode ierr; 4837 SNES snes; 4838 4839 PetscFunctionBegin; 4840 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4841 ierr = PetscObjectAppendOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 4842 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4843 ierr = SNESAppendOptionsPrefix(snes,prefix);CHKERRQ(ierr); 4844 PetscFunctionReturn(0); 4845 } 4846 4847 /*@C 4848 TSGetOptionsPrefix - Sets the prefix used for searching for all 4849 TS options in the database. 4850 4851 Not Collective 4852 4853 Input Parameter: 4854 . ts - The TS context 4855 4856 Output Parameter: 4857 . prefix - A pointer to the prefix string used 4858 4859 Notes: On the fortran side, the user should pass in a string 'prifix' of 4860 sufficient length to hold the prefix. 4861 4862 Level: intermediate 4863 4864 .keywords: TS, get, options, prefix, database 4865 4866 .seealso: TSAppendOptionsPrefix() 4867 @*/ 4868 PetscErrorCode TSGetOptionsPrefix(TS ts,const char *prefix[]) 4869 { 4870 PetscErrorCode ierr; 4871 4872 PetscFunctionBegin; 4873 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4874 PetscValidPointer(prefix,2); 4875 ierr = PetscObjectGetOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 4876 PetscFunctionReturn(0); 4877 } 4878 4879 /*@C 4880 TSGetRHSJacobian - Returns the Jacobian J at the present timestep. 4881 4882 Not Collective, but parallel objects are returned if TS is parallel 4883 4884 Input Parameter: 4885 . ts - The TS context obtained from TSCreate() 4886 4887 Output Parameters: 4888 + Amat - The (approximate) Jacobian J of G, where U_t = G(U,t) (or NULL) 4889 . Pmat - The matrix from which the preconditioner is constructed, usually the same as Amat (or NULL) 4890 . func - Function to compute the Jacobian of the RHS (or NULL) 4891 - ctx - User-defined context for Jacobian evaluation routine (or NULL) 4892 4893 Notes: You can pass in NULL for any return argument you do not need. 4894 4895 Level: intermediate 4896 4897 .seealso: TSGetTimeStep(), TSGetMatrices(), TSGetTime(), TSGetStepNumber() 4898 4899 .keywords: TS, timestep, get, matrix, Jacobian 4900 @*/ 4901 PetscErrorCode TSGetRHSJacobian(TS ts,Mat *Amat,Mat *Pmat,TSRHSJacobian *func,void **ctx) 4902 { 4903 PetscErrorCode ierr; 4904 DM dm; 4905 4906 PetscFunctionBegin; 4907 if (Amat || Pmat) { 4908 SNES snes; 4909 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4910 ierr = SNESSetUpMatrices(snes);CHKERRQ(ierr); 4911 ierr = SNESGetJacobian(snes,Amat,Pmat,NULL,NULL);CHKERRQ(ierr); 4912 } 4913 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 4914 ierr = DMTSGetRHSJacobian(dm,func,ctx);CHKERRQ(ierr); 4915 PetscFunctionReturn(0); 4916 } 4917 4918 /*@C 4919 TSGetIJacobian - Returns the implicit Jacobian at the present timestep. 4920 4921 Not Collective, but parallel objects are returned if TS is parallel 4922 4923 Input Parameter: 4924 . ts - The TS context obtained from TSCreate() 4925 4926 Output Parameters: 4927 + Amat - The (approximate) Jacobian of F(t,U,U_t) 4928 . Pmat - The matrix from which the preconditioner is constructed, often the same as Amat 4929 . f - The function to compute the matrices 4930 - ctx - User-defined context for Jacobian evaluation routine 4931 4932 Notes: You can pass in NULL for any return argument you do not need. 4933 4934 Level: advanced 4935 4936 .seealso: TSGetTimeStep(), TSGetRHSJacobian(), TSGetMatrices(), TSGetTime(), TSGetStepNumber() 4937 4938 .keywords: TS, timestep, get, matrix, Jacobian 4939 @*/ 4940 PetscErrorCode TSGetIJacobian(TS ts,Mat *Amat,Mat *Pmat,TSIJacobian *f,void **ctx) 4941 { 4942 PetscErrorCode ierr; 4943 DM dm; 4944 4945 PetscFunctionBegin; 4946 if (Amat || Pmat) { 4947 SNES snes; 4948 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4949 ierr = SNESSetUpMatrices(snes);CHKERRQ(ierr); 4950 ierr = SNESGetJacobian(snes,Amat,Pmat,NULL,NULL);CHKERRQ(ierr); 4951 } 4952 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 4953 ierr = DMTSGetIJacobian(dm,f,ctx);CHKERRQ(ierr); 4954 PetscFunctionReturn(0); 4955 } 4956 4957 /*@C 4958 TSMonitorDrawSolution - Monitors progress of the TS solvers by calling 4959 VecView() for the solution at each timestep 4960 4961 Collective on TS 4962 4963 Input Parameters: 4964 + ts - the TS context 4965 . step - current time-step 4966 . ptime - current time 4967 - dummy - either a viewer or NULL 4968 4969 Options Database: 4970 . -ts_monitor_draw_solution_initial - show initial solution as well as current solution 4971 4972 Notes: the initial solution and current solution are not display with a common axis scaling so generally the option -ts_monitor_draw_solution_initial 4973 will look bad 4974 4975 Level: intermediate 4976 4977 .keywords: TS, vector, monitor, view 4978 4979 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 4980 @*/ 4981 PetscErrorCode TSMonitorDrawSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 4982 { 4983 PetscErrorCode ierr; 4984 TSMonitorDrawCtx ictx = (TSMonitorDrawCtx)dummy; 4985 PetscDraw draw; 4986 4987 PetscFunctionBegin; 4988 if (!step && ictx->showinitial) { 4989 if (!ictx->initialsolution) { 4990 ierr = VecDuplicate(u,&ictx->initialsolution);CHKERRQ(ierr); 4991 } 4992 ierr = VecCopy(u,ictx->initialsolution);CHKERRQ(ierr); 4993 } 4994 if (!(((ictx->howoften > 0) && (!(step % ictx->howoften))) || ((ictx->howoften == -1) && ts->reason))) PetscFunctionReturn(0); 4995 4996 if (ictx->showinitial) { 4997 PetscReal pause; 4998 ierr = PetscViewerDrawGetPause(ictx->viewer,&pause);CHKERRQ(ierr); 4999 ierr = PetscViewerDrawSetPause(ictx->viewer,0.0);CHKERRQ(ierr); 5000 ierr = VecView(ictx->initialsolution,ictx->viewer);CHKERRQ(ierr); 5001 ierr = PetscViewerDrawSetPause(ictx->viewer,pause);CHKERRQ(ierr); 5002 ierr = PetscViewerDrawSetHold(ictx->viewer,PETSC_TRUE);CHKERRQ(ierr); 5003 } 5004 ierr = VecView(u,ictx->viewer);CHKERRQ(ierr); 5005 if (ictx->showtimestepandtime) { 5006 PetscReal xl,yl,xr,yr,h; 5007 char time[32]; 5008 5009 ierr = PetscViewerDrawGetDraw(ictx->viewer,0,&draw);CHKERRQ(ierr); 5010 ierr = PetscSNPrintf(time,32,"Timestep %d Time %g",(int)step,(double)ptime);CHKERRQ(ierr); 5011 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 5012 h = yl + .95*(yr - yl); 5013 ierr = PetscDrawStringCentered(draw,.5*(xl+xr),h,PETSC_DRAW_BLACK,time);CHKERRQ(ierr); 5014 ierr = PetscDrawFlush(draw);CHKERRQ(ierr); 5015 } 5016 5017 if (ictx->showinitial) { 5018 ierr = PetscViewerDrawSetHold(ictx->viewer,PETSC_FALSE);CHKERRQ(ierr); 5019 } 5020 PetscFunctionReturn(0); 5021 } 5022 5023 /*@C 5024 TSAdjointMonitorDrawSensi - Monitors progress of the adjoint TS solvers by calling 5025 VecView() for the sensitivities to initial states at each timestep 5026 5027 Collective on TS 5028 5029 Input Parameters: 5030 + ts - the TS context 5031 . step - current time-step 5032 . ptime - current time 5033 . u - current state 5034 . numcost - number of cost functions 5035 . lambda - sensitivities to initial conditions 5036 . mu - sensitivities to parameters 5037 - dummy - either a viewer or NULL 5038 5039 Level: intermediate 5040 5041 .keywords: TS, vector, adjoint, monitor, view 5042 5043 .seealso: TSAdjointMonitorSet(), TSAdjointMonitorDefault(), VecView() 5044 @*/ 5045 PetscErrorCode TSAdjointMonitorDrawSensi(TS ts,PetscInt step,PetscReal ptime,Vec u,PetscInt numcost,Vec *lambda,Vec *mu,void *dummy) 5046 { 5047 PetscErrorCode ierr; 5048 TSMonitorDrawCtx ictx = (TSMonitorDrawCtx)dummy; 5049 PetscDraw draw; 5050 PetscReal xl,yl,xr,yr,h; 5051 char time[32]; 5052 5053 PetscFunctionBegin; 5054 if (!(((ictx->howoften > 0) && (!(step % ictx->howoften))) || ((ictx->howoften == -1) && ts->reason))) PetscFunctionReturn(0); 5055 5056 ierr = VecView(lambda[0],ictx->viewer);CHKERRQ(ierr); 5057 ierr = PetscViewerDrawGetDraw(ictx->viewer,0,&draw);CHKERRQ(ierr); 5058 ierr = PetscSNPrintf(time,32,"Timestep %d Time %g",(int)step,(double)ptime);CHKERRQ(ierr); 5059 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 5060 h = yl + .95*(yr - yl); 5061 ierr = PetscDrawStringCentered(draw,.5*(xl+xr),h,PETSC_DRAW_BLACK,time);CHKERRQ(ierr); 5062 ierr = PetscDrawFlush(draw);CHKERRQ(ierr); 5063 PetscFunctionReturn(0); 5064 } 5065 5066 /*@C 5067 TSMonitorDrawSolutionPhase - Monitors progress of the TS solvers by plotting the solution as a phase diagram 5068 5069 Collective on TS 5070 5071 Input Parameters: 5072 + ts - the TS context 5073 . step - current time-step 5074 . ptime - current time 5075 - dummy - either a viewer or NULL 5076 5077 Level: intermediate 5078 5079 .keywords: TS, vector, monitor, view 5080 5081 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 5082 @*/ 5083 PetscErrorCode TSMonitorDrawSolutionPhase(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 5084 { 5085 PetscErrorCode ierr; 5086 TSMonitorDrawCtx ictx = (TSMonitorDrawCtx)dummy; 5087 PetscDraw draw; 5088 PetscDrawAxis axis; 5089 PetscInt n; 5090 PetscMPIInt size; 5091 PetscReal U0,U1,xl,yl,xr,yr,h; 5092 char time[32]; 5093 const PetscScalar *U; 5094 5095 PetscFunctionBegin; 5096 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)ts),&size);CHKERRQ(ierr); 5097 if (size != 1) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Only allowed for sequential runs"); 5098 ierr = VecGetSize(u,&n);CHKERRQ(ierr); 5099 if (n != 2) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Only for ODEs with two unknowns"); 5100 5101 ierr = PetscViewerDrawGetDraw(ictx->viewer,0,&draw);CHKERRQ(ierr); 5102 ierr = PetscViewerDrawGetDrawAxis(ictx->viewer,0,&axis);CHKERRQ(ierr); 5103 ierr = PetscDrawAxisGetLimits(axis,&xl,&xr,&yl,&yr);CHKERRQ(ierr); 5104 if (!step) { 5105 ierr = PetscDrawClear(draw);CHKERRQ(ierr); 5106 ierr = PetscDrawAxisDraw(axis);CHKERRQ(ierr); 5107 } 5108 5109 ierr = VecGetArrayRead(u,&U);CHKERRQ(ierr); 5110 U0 = PetscRealPart(U[0]); 5111 U1 = PetscRealPart(U[1]); 5112 ierr = VecRestoreArrayRead(u,&U);CHKERRQ(ierr); 5113 if ((U0 < xl) || (U1 < yl) || (U0 > xr) || (U1 > yr)) PetscFunctionReturn(0); 5114 5115 ierr = PetscDrawCollectiveBegin(draw);CHKERRQ(ierr); 5116 ierr = PetscDrawPoint(draw,U0,U1,PETSC_DRAW_BLACK);CHKERRQ(ierr); 5117 if (ictx->showtimestepandtime) { 5118 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 5119 ierr = PetscSNPrintf(time,32,"Timestep %d Time %g",(int)step,(double)ptime);CHKERRQ(ierr); 5120 h = yl + .95*(yr - yl); 5121 ierr = PetscDrawStringCentered(draw,.5*(xl+xr),h,PETSC_DRAW_BLACK,time);CHKERRQ(ierr); 5122 } 5123 ierr = PetscDrawCollectiveEnd(draw);CHKERRQ(ierr); 5124 ierr = PetscDrawFlush(draw);CHKERRQ(ierr); 5125 ierr = PetscDrawPause(draw);CHKERRQ(ierr); 5126 ierr = PetscDrawSave(draw);CHKERRQ(ierr); 5127 PetscFunctionReturn(0); 5128 } 5129 5130 /*@C 5131 TSMonitorDrawCtxDestroy - Destroys the monitor context for TSMonitorDrawSolution() 5132 5133 Collective on TS 5134 5135 Input Parameters: 5136 . ctx - the monitor context 5137 5138 Level: intermediate 5139 5140 .keywords: TS, vector, monitor, view 5141 5142 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorDrawSolution(), TSMonitorDrawError() 5143 @*/ 5144 PetscErrorCode TSMonitorDrawCtxDestroy(TSMonitorDrawCtx *ictx) 5145 { 5146 PetscErrorCode ierr; 5147 5148 PetscFunctionBegin; 5149 ierr = PetscViewerDestroy(&(*ictx)->viewer);CHKERRQ(ierr); 5150 ierr = VecDestroy(&(*ictx)->initialsolution);CHKERRQ(ierr); 5151 ierr = PetscFree(*ictx);CHKERRQ(ierr); 5152 PetscFunctionReturn(0); 5153 } 5154 5155 /*@C 5156 TSMonitorDrawCtxCreate - Creates the monitor context for TSMonitorDrawCtx 5157 5158 Collective on TS 5159 5160 Input Parameter: 5161 . ts - time-step context 5162 5163 Output Patameter: 5164 . ctx - the monitor context 5165 5166 Options Database: 5167 . -ts_monitor_draw_solution_initial - show initial solution as well as current solution 5168 5169 Level: intermediate 5170 5171 .keywords: TS, vector, monitor, view 5172 5173 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorDrawCtx() 5174 @*/ 5175 PetscErrorCode TSMonitorDrawCtxCreate(MPI_Comm comm,const char host[],const char label[],int x,int y,int m,int n,PetscInt howoften,TSMonitorDrawCtx *ctx) 5176 { 5177 PetscErrorCode ierr; 5178 5179 PetscFunctionBegin; 5180 ierr = PetscNew(ctx);CHKERRQ(ierr); 5181 ierr = PetscViewerDrawOpen(comm,host,label,x,y,m,n,&(*ctx)->viewer);CHKERRQ(ierr); 5182 ierr = PetscViewerSetFromOptions((*ctx)->viewer);CHKERRQ(ierr); 5183 5184 (*ctx)->howoften = howoften; 5185 (*ctx)->showinitial = PETSC_FALSE; 5186 ierr = PetscOptionsGetBool(NULL,NULL,"-ts_monitor_draw_solution_initial",&(*ctx)->showinitial,NULL);CHKERRQ(ierr); 5187 5188 (*ctx)->showtimestepandtime = PETSC_FALSE; 5189 ierr = PetscOptionsGetBool(NULL,NULL,"-ts_monitor_draw_solution_show_time",&(*ctx)->showtimestepandtime,NULL);CHKERRQ(ierr); 5190 PetscFunctionReturn(0); 5191 } 5192 5193 /*@C 5194 TSMonitorDrawError - Monitors progress of the TS solvers by calling 5195 VecView() for the error at each timestep 5196 5197 Collective on TS 5198 5199 Input Parameters: 5200 + ts - the TS context 5201 . step - current time-step 5202 . ptime - current time 5203 - dummy - either a viewer or NULL 5204 5205 Level: intermediate 5206 5207 .keywords: TS, vector, monitor, view 5208 5209 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 5210 @*/ 5211 PetscErrorCode TSMonitorDrawError(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 5212 { 5213 PetscErrorCode ierr; 5214 TSMonitorDrawCtx ctx = (TSMonitorDrawCtx)dummy; 5215 PetscViewer viewer = ctx->viewer; 5216 Vec work; 5217 5218 PetscFunctionBegin; 5219 if (!(((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason))) PetscFunctionReturn(0); 5220 ierr = VecDuplicate(u,&work);CHKERRQ(ierr); 5221 ierr = TSComputeSolutionFunction(ts,ptime,work);CHKERRQ(ierr); 5222 ierr = VecAXPY(work,-1.0,u);CHKERRQ(ierr); 5223 ierr = VecView(work,viewer);CHKERRQ(ierr); 5224 ierr = VecDestroy(&work);CHKERRQ(ierr); 5225 PetscFunctionReturn(0); 5226 } 5227 5228 #include <petsc/private/dmimpl.h> 5229 /*@ 5230 TSSetDM - Sets the DM that may be used by some nonlinear solvers or preconditioners under the TS 5231 5232 Logically Collective on TS and DM 5233 5234 Input Parameters: 5235 + ts - the ODE integrator object 5236 - dm - the dm, cannot be NULL 5237 5238 Level: intermediate 5239 5240 .seealso: TSGetDM(), SNESSetDM(), SNESGetDM() 5241 @*/ 5242 PetscErrorCode TSSetDM(TS ts,DM dm) 5243 { 5244 PetscErrorCode ierr; 5245 SNES snes; 5246 DMTS tsdm; 5247 5248 PetscFunctionBegin; 5249 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5250 PetscValidHeaderSpecific(dm,DM_CLASSID,2); 5251 ierr = PetscObjectReference((PetscObject)dm);CHKERRQ(ierr); 5252 if (ts->dm) { /* Move the DMTS context over to the new DM unless the new DM already has one */ 5253 if (ts->dm->dmts && !dm->dmts) { 5254 ierr = DMCopyDMTS(ts->dm,dm);CHKERRQ(ierr); 5255 ierr = DMGetDMTS(ts->dm,&tsdm);CHKERRQ(ierr); 5256 if (tsdm->originaldm == ts->dm) { /* Grant write privileges to the replacement DM */ 5257 tsdm->originaldm = dm; 5258 } 5259 } 5260 ierr = DMDestroy(&ts->dm);CHKERRQ(ierr); 5261 } 5262 ts->dm = dm; 5263 5264 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 5265 ierr = SNESSetDM(snes,dm);CHKERRQ(ierr); 5266 PetscFunctionReturn(0); 5267 } 5268 5269 /*@ 5270 TSGetDM - Gets the DM that may be used by some preconditioners 5271 5272 Not Collective 5273 5274 Input Parameter: 5275 . ts - the preconditioner context 5276 5277 Output Parameter: 5278 . dm - the dm 5279 5280 Level: intermediate 5281 5282 .seealso: TSSetDM(), SNESSetDM(), SNESGetDM() 5283 @*/ 5284 PetscErrorCode TSGetDM(TS ts,DM *dm) 5285 { 5286 PetscErrorCode ierr; 5287 5288 PetscFunctionBegin; 5289 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5290 if (!ts->dm) { 5291 ierr = DMShellCreate(PetscObjectComm((PetscObject)ts),&ts->dm);CHKERRQ(ierr); 5292 if (ts->snes) {ierr = SNESSetDM(ts->snes,ts->dm);CHKERRQ(ierr);} 5293 } 5294 *dm = ts->dm; 5295 PetscFunctionReturn(0); 5296 } 5297 5298 /*@ 5299 SNESTSFormFunction - Function to evaluate nonlinear residual 5300 5301 Logically Collective on SNES 5302 5303 Input Parameter: 5304 + snes - nonlinear solver 5305 . U - the current state at which to evaluate the residual 5306 - ctx - user context, must be a TS 5307 5308 Output Parameter: 5309 . F - the nonlinear residual 5310 5311 Notes: 5312 This function is not normally called by users and is automatically registered with the SNES used by TS. 5313 It is most frequently passed to MatFDColoringSetFunction(). 5314 5315 Level: advanced 5316 5317 .seealso: SNESSetFunction(), MatFDColoringSetFunction() 5318 @*/ 5319 PetscErrorCode SNESTSFormFunction(SNES snes,Vec U,Vec F,void *ctx) 5320 { 5321 TS ts = (TS)ctx; 5322 PetscErrorCode ierr; 5323 5324 PetscFunctionBegin; 5325 PetscValidHeaderSpecific(snes,SNES_CLASSID,1); 5326 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 5327 PetscValidHeaderSpecific(F,VEC_CLASSID,3); 5328 PetscValidHeaderSpecific(ts,TS_CLASSID,4); 5329 ierr = (ts->ops->snesfunction)(snes,U,F,ts);CHKERRQ(ierr); 5330 PetscFunctionReturn(0); 5331 } 5332 5333 /*@ 5334 SNESTSFormJacobian - Function to evaluate the Jacobian 5335 5336 Collective on SNES 5337 5338 Input Parameter: 5339 + snes - nonlinear solver 5340 . U - the current state at which to evaluate the residual 5341 - ctx - user context, must be a TS 5342 5343 Output Parameter: 5344 + A - the Jacobian 5345 . B - the preconditioning matrix (may be the same as A) 5346 - flag - indicates any structure change in the matrix 5347 5348 Notes: 5349 This function is not normally called by users and is automatically registered with the SNES used by TS. 5350 5351 Level: developer 5352 5353 .seealso: SNESSetJacobian() 5354 @*/ 5355 PetscErrorCode SNESTSFormJacobian(SNES snes,Vec U,Mat A,Mat B,void *ctx) 5356 { 5357 TS ts = (TS)ctx; 5358 PetscErrorCode ierr; 5359 5360 PetscFunctionBegin; 5361 PetscValidHeaderSpecific(snes,SNES_CLASSID,1); 5362 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 5363 PetscValidPointer(A,3); 5364 PetscValidHeaderSpecific(A,MAT_CLASSID,3); 5365 PetscValidPointer(B,4); 5366 PetscValidHeaderSpecific(B,MAT_CLASSID,4); 5367 PetscValidHeaderSpecific(ts,TS_CLASSID,6); 5368 ierr = (ts->ops->snesjacobian)(snes,U,A,B,ts);CHKERRQ(ierr); 5369 PetscFunctionReturn(0); 5370 } 5371 5372 /*@C 5373 TSComputeRHSFunctionLinear - Evaluate the right hand side via the user-provided Jacobian, for linear problems Udot = A U only 5374 5375 Collective on TS 5376 5377 Input Arguments: 5378 + ts - time stepping context 5379 . t - time at which to evaluate 5380 . U - state at which to evaluate 5381 - ctx - context 5382 5383 Output Arguments: 5384 . F - right hand side 5385 5386 Level: intermediate 5387 5388 Notes: 5389 This function is intended to be passed to TSSetRHSFunction() to evaluate the right hand side for linear problems. 5390 The matrix (and optionally the evaluation context) should be passed to TSSetRHSJacobian(). 5391 5392 .seealso: TSSetRHSFunction(), TSSetRHSJacobian(), TSComputeRHSJacobianConstant() 5393 @*/ 5394 PetscErrorCode TSComputeRHSFunctionLinear(TS ts,PetscReal t,Vec U,Vec F,void *ctx) 5395 { 5396 PetscErrorCode ierr; 5397 Mat Arhs,Brhs; 5398 5399 PetscFunctionBegin; 5400 ierr = TSGetRHSMats_Private(ts,&Arhs,&Brhs);CHKERRQ(ierr); 5401 ierr = TSComputeRHSJacobian(ts,t,U,Arhs,Brhs);CHKERRQ(ierr); 5402 ierr = MatMult(Arhs,U,F);CHKERRQ(ierr); 5403 PetscFunctionReturn(0); 5404 } 5405 5406 /*@C 5407 TSComputeRHSJacobianConstant - Reuses a Jacobian that is time-independent. 5408 5409 Collective on TS 5410 5411 Input Arguments: 5412 + ts - time stepping context 5413 . t - time at which to evaluate 5414 . U - state at which to evaluate 5415 - ctx - context 5416 5417 Output Arguments: 5418 + A - pointer to operator 5419 . B - pointer to preconditioning matrix 5420 - flg - matrix structure flag 5421 5422 Level: intermediate 5423 5424 Notes: 5425 This function is intended to be passed to TSSetRHSJacobian() to evaluate the Jacobian for linear time-independent problems. 5426 5427 .seealso: TSSetRHSFunction(), TSSetRHSJacobian(), TSComputeRHSFunctionLinear() 5428 @*/ 5429 PetscErrorCode TSComputeRHSJacobianConstant(TS ts,PetscReal t,Vec U,Mat A,Mat B,void *ctx) 5430 { 5431 PetscFunctionBegin; 5432 PetscFunctionReturn(0); 5433 } 5434 5435 /*@C 5436 TSComputeIFunctionLinear - Evaluate the left hand side via the user-provided Jacobian, for linear problems only 5437 5438 Collective on TS 5439 5440 Input Arguments: 5441 + ts - time stepping context 5442 . t - time at which to evaluate 5443 . U - state at which to evaluate 5444 . Udot - time derivative of state vector 5445 - ctx - context 5446 5447 Output Arguments: 5448 . F - left hand side 5449 5450 Level: intermediate 5451 5452 Notes: 5453 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 5454 user is required to write their own TSComputeIFunction. 5455 This function is intended to be passed to TSSetIFunction() to evaluate the left hand side for linear problems. 5456 The matrix (and optionally the evaluation context) should be passed to TSSetIJacobian(). 5457 5458 Note that using this function is NOT equivalent to using TSComputeRHSFunctionLinear() since that solves Udot = A U 5459 5460 .seealso: TSSetIFunction(), TSSetIJacobian(), TSComputeIJacobianConstant(), TSComputeRHSFunctionLinear() 5461 @*/ 5462 PetscErrorCode TSComputeIFunctionLinear(TS ts,PetscReal t,Vec U,Vec Udot,Vec F,void *ctx) 5463 { 5464 PetscErrorCode ierr; 5465 Mat A,B; 5466 5467 PetscFunctionBegin; 5468 ierr = TSGetIJacobian(ts,&A,&B,NULL,NULL);CHKERRQ(ierr); 5469 ierr = TSComputeIJacobian(ts,t,U,Udot,1.0,A,B,PETSC_TRUE);CHKERRQ(ierr); 5470 ierr = MatMult(A,Udot,F);CHKERRQ(ierr); 5471 PetscFunctionReturn(0); 5472 } 5473 5474 /*@C 5475 TSComputeIJacobianConstant - Reuses a time-independent for a semi-implicit DAE or ODE 5476 5477 Collective on TS 5478 5479 Input Arguments: 5480 + ts - time stepping context 5481 . t - time at which to evaluate 5482 . U - state at which to evaluate 5483 . Udot - time derivative of state vector 5484 . shift - shift to apply 5485 - ctx - context 5486 5487 Output Arguments: 5488 + A - pointer to operator 5489 . B - pointer to preconditioning matrix 5490 - flg - matrix structure flag 5491 5492 Level: advanced 5493 5494 Notes: 5495 This function is intended to be passed to TSSetIJacobian() to evaluate the Jacobian for linear time-independent problems. 5496 5497 It is only appropriate for problems of the form 5498 5499 $ M Udot = F(U,t) 5500 5501 where M is constant and F is non-stiff. The user must pass M to TSSetIJacobian(). The current implementation only 5502 works with IMEX time integration methods such as TSROSW and TSARKIMEX, since there is no support for de-constructing 5503 an implicit operator of the form 5504 5505 $ shift*M + J 5506 5507 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 5508 a copy of M or reassemble it when requested. 5509 5510 .seealso: TSSetIFunction(), TSSetIJacobian(), TSComputeIFunctionLinear() 5511 @*/ 5512 PetscErrorCode TSComputeIJacobianConstant(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat A,Mat B,void *ctx) 5513 { 5514 PetscErrorCode ierr; 5515 5516 PetscFunctionBegin; 5517 ierr = MatScale(A, shift / ts->ijacobian.shift);CHKERRQ(ierr); 5518 ts->ijacobian.shift = shift; 5519 PetscFunctionReturn(0); 5520 } 5521 5522 /*@ 5523 TSGetEquationType - Gets the type of the equation that TS is solving. 5524 5525 Not Collective 5526 5527 Input Parameter: 5528 . ts - the TS context 5529 5530 Output Parameter: 5531 . equation_type - see TSEquationType 5532 5533 Level: beginner 5534 5535 .keywords: TS, equation type 5536 5537 .seealso: TSSetEquationType(), TSEquationType 5538 @*/ 5539 PetscErrorCode TSGetEquationType(TS ts,TSEquationType *equation_type) 5540 { 5541 PetscFunctionBegin; 5542 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5543 PetscValidPointer(equation_type,2); 5544 *equation_type = ts->equation_type; 5545 PetscFunctionReturn(0); 5546 } 5547 5548 /*@ 5549 TSSetEquationType - Sets the type of the equation that TS is solving. 5550 5551 Not Collective 5552 5553 Input Parameter: 5554 + ts - the TS context 5555 - equation_type - see TSEquationType 5556 5557 Level: advanced 5558 5559 .keywords: TS, equation type 5560 5561 .seealso: TSGetEquationType(), TSEquationType 5562 @*/ 5563 PetscErrorCode TSSetEquationType(TS ts,TSEquationType equation_type) 5564 { 5565 PetscFunctionBegin; 5566 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5567 ts->equation_type = equation_type; 5568 PetscFunctionReturn(0); 5569 } 5570 5571 /*@ 5572 TSGetConvergedReason - Gets the reason the TS iteration was stopped. 5573 5574 Not Collective 5575 5576 Input Parameter: 5577 . ts - the TS context 5578 5579 Output Parameter: 5580 . reason - negative value indicates diverged, positive value converged, see TSConvergedReason or the 5581 manual pages for the individual convergence tests for complete lists 5582 5583 Level: beginner 5584 5585 Notes: 5586 Can only be called after the call to TSSolve() is complete. 5587 5588 .keywords: TS, nonlinear, set, convergence, test 5589 5590 .seealso: TSSetConvergenceTest(), TSConvergedReason 5591 @*/ 5592 PetscErrorCode TSGetConvergedReason(TS ts,TSConvergedReason *reason) 5593 { 5594 PetscFunctionBegin; 5595 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5596 PetscValidPointer(reason,2); 5597 *reason = ts->reason; 5598 PetscFunctionReturn(0); 5599 } 5600 5601 /*@ 5602 TSSetConvergedReason - Sets the reason for handling the convergence of TSSolve. 5603 5604 Not Collective 5605 5606 Input Parameter: 5607 + ts - the TS context 5608 . reason - negative value indicates diverged, positive value converged, see TSConvergedReason or the 5609 manual pages for the individual convergence tests for complete lists 5610 5611 Level: advanced 5612 5613 Notes: 5614 Can only be called during TSSolve() is active. 5615 5616 .keywords: TS, nonlinear, set, convergence, test 5617 5618 .seealso: TSConvergedReason 5619 @*/ 5620 PetscErrorCode TSSetConvergedReason(TS ts,TSConvergedReason reason) 5621 { 5622 PetscFunctionBegin; 5623 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5624 ts->reason = reason; 5625 PetscFunctionReturn(0); 5626 } 5627 5628 /*@ 5629 TSGetSolveTime - Gets the time after a call to TSSolve() 5630 5631 Not Collective 5632 5633 Input Parameter: 5634 . ts - the TS context 5635 5636 Output Parameter: 5637 . ftime - the final time. This time corresponds to the final time set with TSSetMaxTime() 5638 5639 Level: beginner 5640 5641 Notes: 5642 Can only be called after the call to TSSolve() is complete. 5643 5644 .keywords: TS, nonlinear, set, convergence, test 5645 5646 .seealso: TSSetConvergenceTest(), TSConvergedReason 5647 @*/ 5648 PetscErrorCode TSGetSolveTime(TS ts,PetscReal *ftime) 5649 { 5650 PetscFunctionBegin; 5651 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5652 PetscValidPointer(ftime,2); 5653 *ftime = ts->solvetime; 5654 PetscFunctionReturn(0); 5655 } 5656 5657 /*@ 5658 TSGetSNESIterations - Gets the total number of nonlinear iterations 5659 used by the time integrator. 5660 5661 Not Collective 5662 5663 Input Parameter: 5664 . ts - TS context 5665 5666 Output Parameter: 5667 . nits - number of nonlinear iterations 5668 5669 Notes: 5670 This counter is reset to zero for each successive call to TSSolve(). 5671 5672 Level: intermediate 5673 5674 .keywords: TS, get, number, nonlinear, iterations 5675 5676 .seealso: TSGetKSPIterations() 5677 @*/ 5678 PetscErrorCode TSGetSNESIterations(TS ts,PetscInt *nits) 5679 { 5680 PetscFunctionBegin; 5681 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5682 PetscValidIntPointer(nits,2); 5683 *nits = ts->snes_its; 5684 PetscFunctionReturn(0); 5685 } 5686 5687 /*@ 5688 TSGetKSPIterations - Gets the total number of linear iterations 5689 used by the time integrator. 5690 5691 Not Collective 5692 5693 Input Parameter: 5694 . ts - TS context 5695 5696 Output Parameter: 5697 . lits - number of linear iterations 5698 5699 Notes: 5700 This counter is reset to zero for each successive call to TSSolve(). 5701 5702 Level: intermediate 5703 5704 .keywords: TS, get, number, linear, iterations 5705 5706 .seealso: TSGetSNESIterations(), SNESGetKSPIterations() 5707 @*/ 5708 PetscErrorCode TSGetKSPIterations(TS ts,PetscInt *lits) 5709 { 5710 PetscFunctionBegin; 5711 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5712 PetscValidIntPointer(lits,2); 5713 *lits = ts->ksp_its; 5714 PetscFunctionReturn(0); 5715 } 5716 5717 /*@ 5718 TSGetStepRejections - Gets the total number of rejected steps. 5719 5720 Not Collective 5721 5722 Input Parameter: 5723 . ts - TS context 5724 5725 Output Parameter: 5726 . rejects - number of steps rejected 5727 5728 Notes: 5729 This counter is reset to zero for each successive call to TSSolve(). 5730 5731 Level: intermediate 5732 5733 .keywords: TS, get, number 5734 5735 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetSNESFailures(), TSSetMaxSNESFailures(), TSSetErrorIfStepFails() 5736 @*/ 5737 PetscErrorCode TSGetStepRejections(TS ts,PetscInt *rejects) 5738 { 5739 PetscFunctionBegin; 5740 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5741 PetscValidIntPointer(rejects,2); 5742 *rejects = ts->reject; 5743 PetscFunctionReturn(0); 5744 } 5745 5746 /*@ 5747 TSGetSNESFailures - Gets the total number of failed SNES solves 5748 5749 Not Collective 5750 5751 Input Parameter: 5752 . ts - TS context 5753 5754 Output Parameter: 5755 . fails - number of failed nonlinear solves 5756 5757 Notes: 5758 This counter is reset to zero for each successive call to TSSolve(). 5759 5760 Level: intermediate 5761 5762 .keywords: TS, get, number 5763 5764 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSSetMaxSNESFailures() 5765 @*/ 5766 PetscErrorCode TSGetSNESFailures(TS ts,PetscInt *fails) 5767 { 5768 PetscFunctionBegin; 5769 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5770 PetscValidIntPointer(fails,2); 5771 *fails = ts->num_snes_failures; 5772 PetscFunctionReturn(0); 5773 } 5774 5775 /*@ 5776 TSSetMaxStepRejections - Sets the maximum number of step rejections before a step fails 5777 5778 Not Collective 5779 5780 Input Parameter: 5781 + ts - TS context 5782 - rejects - maximum number of rejected steps, pass -1 for unlimited 5783 5784 Notes: 5785 The counter is reset to zero for each step 5786 5787 Options Database Key: 5788 . -ts_max_reject - Maximum number of step rejections before a step fails 5789 5790 Level: intermediate 5791 5792 .keywords: TS, set, maximum, number 5793 5794 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxSNESFailures(), TSGetStepRejections(), TSGetSNESFailures(), TSSetErrorIfStepFails(), TSGetConvergedReason() 5795 @*/ 5796 PetscErrorCode TSSetMaxStepRejections(TS ts,PetscInt rejects) 5797 { 5798 PetscFunctionBegin; 5799 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5800 ts->max_reject = rejects; 5801 PetscFunctionReturn(0); 5802 } 5803 5804 /*@ 5805 TSSetMaxSNESFailures - Sets the maximum number of failed SNES solves 5806 5807 Not Collective 5808 5809 Input Parameter: 5810 + ts - TS context 5811 - fails - maximum number of failed nonlinear solves, pass -1 for unlimited 5812 5813 Notes: 5814 The counter is reset to zero for each successive call to TSSolve(). 5815 5816 Options Database Key: 5817 . -ts_max_snes_failures - Maximum number of nonlinear solve failures 5818 5819 Level: intermediate 5820 5821 .keywords: TS, set, maximum, number 5822 5823 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSGetSNESFailures(), SNESGetConvergedReason(), TSGetConvergedReason() 5824 @*/ 5825 PetscErrorCode TSSetMaxSNESFailures(TS ts,PetscInt fails) 5826 { 5827 PetscFunctionBegin; 5828 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5829 ts->max_snes_failures = fails; 5830 PetscFunctionReturn(0); 5831 } 5832 5833 /*@ 5834 TSSetErrorIfStepFails - Error if no step succeeds 5835 5836 Not Collective 5837 5838 Input Parameter: 5839 + ts - TS context 5840 - err - PETSC_TRUE to error if no step succeeds, PETSC_FALSE to return without failure 5841 5842 Options Database Key: 5843 . -ts_error_if_step_fails - Error if no step succeeds 5844 5845 Level: intermediate 5846 5847 .keywords: TS, set, error 5848 5849 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSGetSNESFailures(), TSSetErrorIfStepFails(), TSGetConvergedReason() 5850 @*/ 5851 PetscErrorCode TSSetErrorIfStepFails(TS ts,PetscBool err) 5852 { 5853 PetscFunctionBegin; 5854 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5855 ts->errorifstepfailed = err; 5856 PetscFunctionReturn(0); 5857 } 5858 5859 /*@C 5860 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 5861 5862 Collective on TS 5863 5864 Input Parameters: 5865 + ts - the TS context 5866 . step - current time-step 5867 . ptime - current time 5868 . u - current state 5869 - vf - viewer and its format 5870 5871 Level: intermediate 5872 5873 .keywords: TS, vector, monitor, view 5874 5875 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 5876 @*/ 5877 PetscErrorCode TSMonitorSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,PetscViewerAndFormat *vf) 5878 { 5879 PetscErrorCode ierr; 5880 5881 PetscFunctionBegin; 5882 ierr = PetscViewerPushFormat(vf->viewer,vf->format);CHKERRQ(ierr); 5883 ierr = VecView(u,vf->viewer);CHKERRQ(ierr); 5884 ierr = PetscViewerPopFormat(vf->viewer);CHKERRQ(ierr); 5885 PetscFunctionReturn(0); 5886 } 5887 5888 /*@C 5889 TSMonitorSolutionVTK - Monitors progress of the TS solvers by VecView() for the solution at each timestep. 5890 5891 Collective on TS 5892 5893 Input Parameters: 5894 + ts - the TS context 5895 . step - current time-step 5896 . ptime - current time 5897 . u - current state 5898 - filenametemplate - string containing a format specifier for the integer time step (e.g. %03D) 5899 5900 Level: intermediate 5901 5902 Notes: 5903 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. 5904 These are named according to the file name template. 5905 5906 This function is normally passed as an argument to TSMonitorSet() along with TSMonitorSolutionVTKDestroy(). 5907 5908 .keywords: TS, vector, monitor, view 5909 5910 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 5911 @*/ 5912 PetscErrorCode TSMonitorSolutionVTK(TS ts,PetscInt step,PetscReal ptime,Vec u,void *filenametemplate) 5913 { 5914 PetscErrorCode ierr; 5915 char filename[PETSC_MAX_PATH_LEN]; 5916 PetscViewer viewer; 5917 5918 PetscFunctionBegin; 5919 if (step < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */ 5920 ierr = PetscSNPrintf(filename,sizeof(filename),(const char*)filenametemplate,step);CHKERRQ(ierr); 5921 ierr = PetscViewerVTKOpen(PetscObjectComm((PetscObject)ts),filename,FILE_MODE_WRITE,&viewer);CHKERRQ(ierr); 5922 ierr = VecView(u,viewer);CHKERRQ(ierr); 5923 ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr); 5924 PetscFunctionReturn(0); 5925 } 5926 5927 /*@C 5928 TSMonitorSolutionVTKDestroy - Destroy context for monitoring 5929 5930 Collective on TS 5931 5932 Input Parameters: 5933 . filenametemplate - string containing a format specifier for the integer time step (e.g. %03D) 5934 5935 Level: intermediate 5936 5937 Note: 5938 This function is normally passed to TSMonitorSet() along with TSMonitorSolutionVTK(). 5939 5940 .keywords: TS, vector, monitor, view 5941 5942 .seealso: TSMonitorSet(), TSMonitorSolutionVTK() 5943 @*/ 5944 PetscErrorCode TSMonitorSolutionVTKDestroy(void *filenametemplate) 5945 { 5946 PetscErrorCode ierr; 5947 5948 PetscFunctionBegin; 5949 ierr = PetscFree(*(char**)filenametemplate);CHKERRQ(ierr); 5950 PetscFunctionReturn(0); 5951 } 5952 5953 /*@ 5954 TSGetAdapt - Get the adaptive controller context for the current method 5955 5956 Collective on TS if controller has not been created yet 5957 5958 Input Arguments: 5959 . ts - time stepping context 5960 5961 Output Arguments: 5962 . adapt - adaptive controller 5963 5964 Level: intermediate 5965 5966 .seealso: TSAdapt, TSAdaptSetType(), TSAdaptChoose() 5967 @*/ 5968 PetscErrorCode TSGetAdapt(TS ts,TSAdapt *adapt) 5969 { 5970 PetscErrorCode ierr; 5971 5972 PetscFunctionBegin; 5973 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5974 PetscValidPointer(adapt,2); 5975 if (!ts->adapt) { 5976 ierr = TSAdaptCreate(PetscObjectComm((PetscObject)ts),&ts->adapt);CHKERRQ(ierr); 5977 ierr = PetscLogObjectParent((PetscObject)ts,(PetscObject)ts->adapt);CHKERRQ(ierr); 5978 ierr = PetscObjectIncrementTabLevel((PetscObject)ts->adapt,(PetscObject)ts,1);CHKERRQ(ierr); 5979 } 5980 *adapt = ts->adapt; 5981 PetscFunctionReturn(0); 5982 } 5983 5984 /*@ 5985 TSSetTolerances - Set tolerances for local truncation error when using adaptive controller 5986 5987 Logically Collective 5988 5989 Input Arguments: 5990 + ts - time integration context 5991 . atol - scalar absolute tolerances, PETSC_DECIDE to leave current value 5992 . vatol - vector of absolute tolerances or NULL, used in preference to atol if present 5993 . rtol - scalar relative tolerances, PETSC_DECIDE to leave current value 5994 - vrtol - vector of relative tolerances or NULL, used in preference to atol if present 5995 5996 Options Database keys: 5997 + -ts_rtol <rtol> - relative tolerance for local truncation error 5998 - -ts_atol <atol> Absolute tolerance for local truncation error 5999 6000 Notes: 6001 With PETSc's implicit schemes for DAE problems, the calculation of the local truncation error 6002 (LTE) includes both the differential and the algebraic variables. If one wants the LTE to be 6003 computed only for the differential or the algebraic part then this can be done using the vector of 6004 tolerances vatol. For example, by setting the tolerance vector with the desired tolerance for the 6005 differential part and infinity for the algebraic part, the LTE calculation will include only the 6006 differential variables. 6007 6008 Level: beginner 6009 6010 .seealso: TS, TSAdapt, TSVecNormWRMS(), TSGetTolerances() 6011 @*/ 6012 PetscErrorCode TSSetTolerances(TS ts,PetscReal atol,Vec vatol,PetscReal rtol,Vec vrtol) 6013 { 6014 PetscErrorCode ierr; 6015 6016 PetscFunctionBegin; 6017 if (atol != PETSC_DECIDE && atol != PETSC_DEFAULT) ts->atol = atol; 6018 if (vatol) { 6019 ierr = PetscObjectReference((PetscObject)vatol);CHKERRQ(ierr); 6020 ierr = VecDestroy(&ts->vatol);CHKERRQ(ierr); 6021 ts->vatol = vatol; 6022 } 6023 if (rtol != PETSC_DECIDE && rtol != PETSC_DEFAULT) ts->rtol = rtol; 6024 if (vrtol) { 6025 ierr = PetscObjectReference((PetscObject)vrtol);CHKERRQ(ierr); 6026 ierr = VecDestroy(&ts->vrtol);CHKERRQ(ierr); 6027 ts->vrtol = vrtol; 6028 } 6029 PetscFunctionReturn(0); 6030 } 6031 6032 /*@ 6033 TSGetTolerances - Get tolerances for local truncation error when using adaptive controller 6034 6035 Logically Collective 6036 6037 Input Arguments: 6038 . ts - time integration context 6039 6040 Output Arguments: 6041 + atol - scalar absolute tolerances, NULL to ignore 6042 . vatol - vector of absolute tolerances, NULL to ignore 6043 . rtol - scalar relative tolerances, NULL to ignore 6044 - vrtol - vector of relative tolerances, NULL to ignore 6045 6046 Level: beginner 6047 6048 .seealso: TS, TSAdapt, TSVecNormWRMS(), TSSetTolerances() 6049 @*/ 6050 PetscErrorCode TSGetTolerances(TS ts,PetscReal *atol,Vec *vatol,PetscReal *rtol,Vec *vrtol) 6051 { 6052 PetscFunctionBegin; 6053 if (atol) *atol = ts->atol; 6054 if (vatol) *vatol = ts->vatol; 6055 if (rtol) *rtol = ts->rtol; 6056 if (vrtol) *vrtol = ts->vrtol; 6057 PetscFunctionReturn(0); 6058 } 6059 6060 /*@ 6061 TSErrorWeightedNorm2 - compute a weighted 2-norm of the difference between two state vectors 6062 6063 Collective on TS 6064 6065 Input Arguments: 6066 + ts - time stepping context 6067 . U - state vector, usually ts->vec_sol 6068 - Y - state vector to be compared to U 6069 6070 Output Arguments: 6071 . norm - weighted norm, a value of 1.0 means that the error matches the tolerances 6072 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 6073 . normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 6074 6075 Level: developer 6076 6077 .seealso: TSErrorWeightedNorm(), TSErrorWeightedNormInfinity() 6078 @*/ 6079 PetscErrorCode TSErrorWeightedNorm2(TS ts,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6080 { 6081 PetscErrorCode ierr; 6082 PetscInt i,n,N,rstart; 6083 PetscInt n_loc,na_loc,nr_loc; 6084 PetscReal n_glb,na_glb,nr_glb; 6085 const PetscScalar *u,*y; 6086 PetscReal sum,suma,sumr,gsum,gsuma,gsumr,diff; 6087 PetscReal tol,tola,tolr; 6088 PetscReal err_loc[6],err_glb[6]; 6089 6090 PetscFunctionBegin; 6091 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6092 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 6093 PetscValidHeaderSpecific(Y,VEC_CLASSID,3); 6094 PetscValidType(U,2); 6095 PetscValidType(Y,3); 6096 PetscCheckSameComm(U,2,Y,3); 6097 PetscValidPointer(norm,4); 6098 PetscValidPointer(norma,5); 6099 PetscValidPointer(normr,6); 6100 if (U == Y) SETERRQ(PetscObjectComm((PetscObject)U),PETSC_ERR_ARG_IDN,"U and Y cannot be the same vector"); 6101 6102 ierr = VecGetSize(U,&N);CHKERRQ(ierr); 6103 ierr = VecGetLocalSize(U,&n);CHKERRQ(ierr); 6104 ierr = VecGetOwnershipRange(U,&rstart,NULL);CHKERRQ(ierr); 6105 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 6106 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 6107 sum = 0.; n_loc = 0; 6108 suma = 0.; na_loc = 0; 6109 sumr = 0.; nr_loc = 0; 6110 if (ts->vatol && ts->vrtol) { 6111 const PetscScalar *atol,*rtol; 6112 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6113 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6114 for (i=0; i<n; i++) { 6115 diff = PetscAbsScalar(y[i] - u[i]); 6116 tola = PetscRealPart(atol[i]); 6117 if(tola>0.){ 6118 suma += PetscSqr(diff/tola); 6119 na_loc++; 6120 } 6121 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6122 if(tolr>0.){ 6123 sumr += PetscSqr(diff/tolr); 6124 nr_loc++; 6125 } 6126 tol=tola+tolr; 6127 if(tol>0.){ 6128 sum += PetscSqr(diff/tol); 6129 n_loc++; 6130 } 6131 } 6132 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6133 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6134 } else if (ts->vatol) { /* vector atol, scalar rtol */ 6135 const PetscScalar *atol; 6136 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6137 for (i=0; i<n; i++) { 6138 diff = PetscAbsScalar(y[i] - u[i]); 6139 tola = PetscRealPart(atol[i]); 6140 if(tola>0.){ 6141 suma += PetscSqr(diff/tola); 6142 na_loc++; 6143 } 6144 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6145 if(tolr>0.){ 6146 sumr += PetscSqr(diff/tolr); 6147 nr_loc++; 6148 } 6149 tol=tola+tolr; 6150 if(tol>0.){ 6151 sum += PetscSqr(diff/tol); 6152 n_loc++; 6153 } 6154 } 6155 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6156 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 6157 const PetscScalar *rtol; 6158 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6159 for (i=0; i<n; i++) { 6160 diff = PetscAbsScalar(y[i] - u[i]); 6161 tola = ts->atol; 6162 if(tola>0.){ 6163 suma += PetscSqr(diff/tola); 6164 na_loc++; 6165 } 6166 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6167 if(tolr>0.){ 6168 sumr += PetscSqr(diff/tolr); 6169 nr_loc++; 6170 } 6171 tol=tola+tolr; 6172 if(tol>0.){ 6173 sum += PetscSqr(diff/tol); 6174 n_loc++; 6175 } 6176 } 6177 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6178 } else { /* scalar atol, scalar rtol */ 6179 for (i=0; i<n; i++) { 6180 diff = PetscAbsScalar(y[i] - u[i]); 6181 tola = ts->atol; 6182 if(tola>0.){ 6183 suma += PetscSqr(diff/tola); 6184 na_loc++; 6185 } 6186 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6187 if(tolr>0.){ 6188 sumr += PetscSqr(diff/tolr); 6189 nr_loc++; 6190 } 6191 tol=tola+tolr; 6192 if(tol>0.){ 6193 sum += PetscSqr(diff/tol); 6194 n_loc++; 6195 } 6196 } 6197 } 6198 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 6199 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 6200 6201 err_loc[0] = sum; 6202 err_loc[1] = suma; 6203 err_loc[2] = sumr; 6204 err_loc[3] = (PetscReal)n_loc; 6205 err_loc[4] = (PetscReal)na_loc; 6206 err_loc[5] = (PetscReal)nr_loc; 6207 6208 ierr = MPIU_Allreduce(err_loc,err_glb,6,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6209 6210 gsum = err_glb[0]; 6211 gsuma = err_glb[1]; 6212 gsumr = err_glb[2]; 6213 n_glb = err_glb[3]; 6214 na_glb = err_glb[4]; 6215 nr_glb = err_glb[5]; 6216 6217 *norm = 0.; 6218 if(n_glb>0. ){*norm = PetscSqrtReal(gsum / n_glb );} 6219 *norma = 0.; 6220 if(na_glb>0.){*norma = PetscSqrtReal(gsuma / na_glb);} 6221 *normr = 0.; 6222 if(nr_glb>0.){*normr = PetscSqrtReal(gsumr / nr_glb);} 6223 6224 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 6225 if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 6226 if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 6227 PetscFunctionReturn(0); 6228 } 6229 6230 /*@ 6231 TSErrorWeightedNormInfinity - compute a weighted infinity-norm of the difference between two state vectors 6232 6233 Collective on TS 6234 6235 Input Arguments: 6236 + ts - time stepping context 6237 . U - state vector, usually ts->vec_sol 6238 - Y - state vector to be compared to U 6239 6240 Output Arguments: 6241 . norm - weighted norm, a value of 1.0 means that the error matches the tolerances 6242 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 6243 . normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 6244 6245 Level: developer 6246 6247 .seealso: TSErrorWeightedNorm(), TSErrorWeightedNorm2() 6248 @*/ 6249 PetscErrorCode TSErrorWeightedNormInfinity(TS ts,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6250 { 6251 PetscErrorCode ierr; 6252 PetscInt i,n,N,rstart; 6253 const PetscScalar *u,*y; 6254 PetscReal max,gmax,maxa,gmaxa,maxr,gmaxr; 6255 PetscReal tol,tola,tolr,diff; 6256 PetscReal err_loc[3],err_glb[3]; 6257 6258 PetscFunctionBegin; 6259 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6260 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 6261 PetscValidHeaderSpecific(Y,VEC_CLASSID,3); 6262 PetscValidType(U,2); 6263 PetscValidType(Y,3); 6264 PetscCheckSameComm(U,2,Y,3); 6265 PetscValidPointer(norm,4); 6266 PetscValidPointer(norma,5); 6267 PetscValidPointer(normr,6); 6268 if (U == Y) SETERRQ(PetscObjectComm((PetscObject)U),PETSC_ERR_ARG_IDN,"U and Y cannot be the same vector"); 6269 6270 ierr = VecGetSize(U,&N);CHKERRQ(ierr); 6271 ierr = VecGetLocalSize(U,&n);CHKERRQ(ierr); 6272 ierr = VecGetOwnershipRange(U,&rstart,NULL);CHKERRQ(ierr); 6273 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 6274 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 6275 6276 max=0.; 6277 maxa=0.; 6278 maxr=0.; 6279 6280 if (ts->vatol && ts->vrtol) { /* vector atol, vector rtol */ 6281 const PetscScalar *atol,*rtol; 6282 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6283 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6284 6285 for (i=0; i<n; i++) { 6286 diff = PetscAbsScalar(y[i] - u[i]); 6287 tola = PetscRealPart(atol[i]); 6288 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6289 tol = tola+tolr; 6290 if(tola>0.){ 6291 maxa = PetscMax(maxa,diff / tola); 6292 } 6293 if(tolr>0.){ 6294 maxr = PetscMax(maxr,diff / tolr); 6295 } 6296 if(tol>0.){ 6297 max = PetscMax(max,diff / tol); 6298 } 6299 } 6300 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6301 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6302 } else if (ts->vatol) { /* vector atol, scalar rtol */ 6303 const PetscScalar *atol; 6304 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6305 for (i=0; i<n; i++) { 6306 diff = PetscAbsScalar(y[i] - u[i]); 6307 tola = PetscRealPart(atol[i]); 6308 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6309 tol = tola+tolr; 6310 if(tola>0.){ 6311 maxa = PetscMax(maxa,diff / tola); 6312 } 6313 if(tolr>0.){ 6314 maxr = PetscMax(maxr,diff / tolr); 6315 } 6316 if(tol>0.){ 6317 max = PetscMax(max,diff / tol); 6318 } 6319 } 6320 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6321 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 6322 const PetscScalar *rtol; 6323 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6324 6325 for (i=0; i<n; i++) { 6326 diff = PetscAbsScalar(y[i] - u[i]); 6327 tola = ts->atol; 6328 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6329 tol = tola+tolr; 6330 if(tola>0.){ 6331 maxa = PetscMax(maxa,diff / tola); 6332 } 6333 if(tolr>0.){ 6334 maxr = PetscMax(maxr,diff / tolr); 6335 } 6336 if(tol>0.){ 6337 max = PetscMax(max,diff / tol); 6338 } 6339 } 6340 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6341 } else { /* scalar atol, scalar rtol */ 6342 6343 for (i=0; i<n; i++) { 6344 diff = PetscAbsScalar(y[i] - u[i]); 6345 tola = ts->atol; 6346 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6347 tol = tola+tolr; 6348 if(tola>0.){ 6349 maxa = PetscMax(maxa,diff / tola); 6350 } 6351 if(tolr>0.){ 6352 maxr = PetscMax(maxr,diff / tolr); 6353 } 6354 if(tol>0.){ 6355 max = PetscMax(max,diff / tol); 6356 } 6357 } 6358 } 6359 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 6360 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 6361 err_loc[0] = max; 6362 err_loc[1] = maxa; 6363 err_loc[2] = maxr; 6364 ierr = MPIU_Allreduce(err_loc,err_glb,3,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6365 gmax = err_glb[0]; 6366 gmaxa = err_glb[1]; 6367 gmaxr = err_glb[2]; 6368 6369 *norm = gmax; 6370 *norma = gmaxa; 6371 *normr = gmaxr; 6372 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 6373 if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 6374 if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 6375 PetscFunctionReturn(0); 6376 } 6377 6378 /*@ 6379 TSErrorWeightedNorm - compute a weighted norm of the difference between two state vectors based on supplied absolute and relative tolerances 6380 6381 Collective on TS 6382 6383 Input Arguments: 6384 + ts - time stepping context 6385 . U - state vector, usually ts->vec_sol 6386 . Y - state vector to be compared to U 6387 - wnormtype - norm type, either NORM_2 or NORM_INFINITY 6388 6389 Output Arguments: 6390 . norm - weighted norm, a value of 1.0 achieves a balance between absolute and relative tolerances 6391 . norma - weighted norm, a value of 1.0 means that the error meets the absolute tolerance set by the user 6392 . normr - weighted norm, a value of 1.0 means that the error meets the relative tolerance set by the user 6393 6394 Options Database Keys: 6395 . -ts_adapt_wnormtype <wnormtype> - 2, INFINITY 6396 6397 Level: developer 6398 6399 .seealso: TSErrorWeightedNormInfinity(), TSErrorWeightedNorm2(), TSErrorWeightedENorm 6400 @*/ 6401 PetscErrorCode TSErrorWeightedNorm(TS ts,Vec U,Vec Y,NormType wnormtype,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6402 { 6403 PetscErrorCode ierr; 6404 6405 PetscFunctionBegin; 6406 if (wnormtype == NORM_2) { 6407 ierr = TSErrorWeightedNorm2(ts,U,Y,norm,norma,normr);CHKERRQ(ierr); 6408 } else if(wnormtype == NORM_INFINITY) { 6409 ierr = TSErrorWeightedNormInfinity(ts,U,Y,norm,norma,normr);CHKERRQ(ierr); 6410 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]); 6411 PetscFunctionReturn(0); 6412 } 6413 6414 6415 /*@ 6416 TSErrorWeightedENorm2 - compute a weighted 2 error norm based on supplied absolute and relative tolerances 6417 6418 Collective on TS 6419 6420 Input Arguments: 6421 + ts - time stepping context 6422 . E - error vector 6423 . U - state vector, usually ts->vec_sol 6424 - Y - state vector, previous time step 6425 6426 Output Arguments: 6427 . norm - weighted norm, a value of 1.0 means that the error matches the tolerances 6428 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 6429 . normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 6430 6431 Level: developer 6432 6433 .seealso: TSErrorWeightedENorm(), TSErrorWeightedENormInfinity() 6434 @*/ 6435 PetscErrorCode TSErrorWeightedENorm2(TS ts,Vec E,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6436 { 6437 PetscErrorCode ierr; 6438 PetscInt i,n,N,rstart; 6439 PetscInt n_loc,na_loc,nr_loc; 6440 PetscReal n_glb,na_glb,nr_glb; 6441 const PetscScalar *e,*u,*y; 6442 PetscReal err,sum,suma,sumr,gsum,gsuma,gsumr; 6443 PetscReal tol,tola,tolr; 6444 PetscReal err_loc[6],err_glb[6]; 6445 6446 PetscFunctionBegin; 6447 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6448 PetscValidHeaderSpecific(E,VEC_CLASSID,2); 6449 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 6450 PetscValidHeaderSpecific(Y,VEC_CLASSID,4); 6451 PetscValidType(E,2); 6452 PetscValidType(U,3); 6453 PetscValidType(Y,4); 6454 PetscCheckSameComm(E,2,U,3); 6455 PetscCheckSameComm(U,2,Y,3); 6456 PetscValidPointer(norm,5); 6457 PetscValidPointer(norma,6); 6458 PetscValidPointer(normr,7); 6459 6460 ierr = VecGetSize(E,&N);CHKERRQ(ierr); 6461 ierr = VecGetLocalSize(E,&n);CHKERRQ(ierr); 6462 ierr = VecGetOwnershipRange(E,&rstart,NULL);CHKERRQ(ierr); 6463 ierr = VecGetArrayRead(E,&e);CHKERRQ(ierr); 6464 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 6465 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 6466 sum = 0.; n_loc = 0; 6467 suma = 0.; na_loc = 0; 6468 sumr = 0.; nr_loc = 0; 6469 if (ts->vatol && ts->vrtol) { 6470 const PetscScalar *atol,*rtol; 6471 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6472 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6473 for (i=0; i<n; i++) { 6474 err = PetscAbsScalar(e[i]); 6475 tola = PetscRealPart(atol[i]); 6476 if(tola>0.){ 6477 suma += PetscSqr(err/tola); 6478 na_loc++; 6479 } 6480 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6481 if(tolr>0.){ 6482 sumr += PetscSqr(err/tolr); 6483 nr_loc++; 6484 } 6485 tol=tola+tolr; 6486 if(tol>0.){ 6487 sum += PetscSqr(err/tol); 6488 n_loc++; 6489 } 6490 } 6491 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6492 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6493 } else if (ts->vatol) { /* vector atol, scalar rtol */ 6494 const PetscScalar *atol; 6495 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6496 for (i=0; i<n; i++) { 6497 err = PetscAbsScalar(e[i]); 6498 tola = PetscRealPart(atol[i]); 6499 if(tola>0.){ 6500 suma += PetscSqr(err/tola); 6501 na_loc++; 6502 } 6503 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6504 if(tolr>0.){ 6505 sumr += PetscSqr(err/tolr); 6506 nr_loc++; 6507 } 6508 tol=tola+tolr; 6509 if(tol>0.){ 6510 sum += PetscSqr(err/tol); 6511 n_loc++; 6512 } 6513 } 6514 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6515 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 6516 const PetscScalar *rtol; 6517 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6518 for (i=0; i<n; i++) { 6519 err = PetscAbsScalar(e[i]); 6520 tola = ts->atol; 6521 if(tola>0.){ 6522 suma += PetscSqr(err/tola); 6523 na_loc++; 6524 } 6525 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6526 if(tolr>0.){ 6527 sumr += PetscSqr(err/tolr); 6528 nr_loc++; 6529 } 6530 tol=tola+tolr; 6531 if(tol>0.){ 6532 sum += PetscSqr(err/tol); 6533 n_loc++; 6534 } 6535 } 6536 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6537 } else { /* scalar atol, scalar rtol */ 6538 for (i=0; i<n; i++) { 6539 err = PetscAbsScalar(e[i]); 6540 tola = ts->atol; 6541 if(tola>0.){ 6542 suma += PetscSqr(err/tola); 6543 na_loc++; 6544 } 6545 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6546 if(tolr>0.){ 6547 sumr += PetscSqr(err/tolr); 6548 nr_loc++; 6549 } 6550 tol=tola+tolr; 6551 if(tol>0.){ 6552 sum += PetscSqr(err/tol); 6553 n_loc++; 6554 } 6555 } 6556 } 6557 ierr = VecRestoreArrayRead(E,&e);CHKERRQ(ierr); 6558 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 6559 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 6560 6561 err_loc[0] = sum; 6562 err_loc[1] = suma; 6563 err_loc[2] = sumr; 6564 err_loc[3] = (PetscReal)n_loc; 6565 err_loc[4] = (PetscReal)na_loc; 6566 err_loc[5] = (PetscReal)nr_loc; 6567 6568 ierr = MPIU_Allreduce(err_loc,err_glb,6,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6569 6570 gsum = err_glb[0]; 6571 gsuma = err_glb[1]; 6572 gsumr = err_glb[2]; 6573 n_glb = err_glb[3]; 6574 na_glb = err_glb[4]; 6575 nr_glb = err_glb[5]; 6576 6577 *norm = 0.; 6578 if(n_glb>0. ){*norm = PetscSqrtReal(gsum / n_glb );} 6579 *norma = 0.; 6580 if(na_glb>0.){*norma = PetscSqrtReal(gsuma / na_glb);} 6581 *normr = 0.; 6582 if(nr_glb>0.){*normr = PetscSqrtReal(gsumr / nr_glb);} 6583 6584 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 6585 if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 6586 if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 6587 PetscFunctionReturn(0); 6588 } 6589 6590 /*@ 6591 TSErrorWeightedENormInfinity - compute a weighted infinity error norm based on supplied absolute and relative tolerances 6592 Collective on TS 6593 6594 Input Arguments: 6595 + ts - time stepping context 6596 . E - error vector 6597 . U - state vector, usually ts->vec_sol 6598 - Y - state vector, previous time step 6599 6600 Output Arguments: 6601 . norm - weighted norm, a value of 1.0 means that the error matches the tolerances 6602 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 6603 . normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 6604 6605 Level: developer 6606 6607 .seealso: TSErrorWeightedENorm(), TSErrorWeightedENorm2() 6608 @*/ 6609 PetscErrorCode TSErrorWeightedENormInfinity(TS ts,Vec E,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6610 { 6611 PetscErrorCode ierr; 6612 PetscInt i,n,N,rstart; 6613 const PetscScalar *e,*u,*y; 6614 PetscReal err,max,gmax,maxa,gmaxa,maxr,gmaxr; 6615 PetscReal tol,tola,tolr; 6616 PetscReal err_loc[3],err_glb[3]; 6617 6618 PetscFunctionBegin; 6619 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6620 PetscValidHeaderSpecific(E,VEC_CLASSID,2); 6621 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 6622 PetscValidHeaderSpecific(Y,VEC_CLASSID,4); 6623 PetscValidType(E,2); 6624 PetscValidType(U,3); 6625 PetscValidType(Y,4); 6626 PetscCheckSameComm(E,2,U,3); 6627 PetscCheckSameComm(U,2,Y,3); 6628 PetscValidPointer(norm,5); 6629 PetscValidPointer(norma,6); 6630 PetscValidPointer(normr,7); 6631 6632 ierr = VecGetSize(E,&N);CHKERRQ(ierr); 6633 ierr = VecGetLocalSize(E,&n);CHKERRQ(ierr); 6634 ierr = VecGetOwnershipRange(E,&rstart,NULL);CHKERRQ(ierr); 6635 ierr = VecGetArrayRead(E,&e);CHKERRQ(ierr); 6636 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 6637 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 6638 6639 max=0.; 6640 maxa=0.; 6641 maxr=0.; 6642 6643 if (ts->vatol && ts->vrtol) { /* vector atol, vector rtol */ 6644 const PetscScalar *atol,*rtol; 6645 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6646 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6647 6648 for (i=0; i<n; i++) { 6649 err = PetscAbsScalar(e[i]); 6650 tola = PetscRealPart(atol[i]); 6651 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6652 tol = tola+tolr; 6653 if(tola>0.){ 6654 maxa = PetscMax(maxa,err / tola); 6655 } 6656 if(tolr>0.){ 6657 maxr = PetscMax(maxr,err / tolr); 6658 } 6659 if(tol>0.){ 6660 max = PetscMax(max,err / tol); 6661 } 6662 } 6663 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6664 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6665 } else if (ts->vatol) { /* vector atol, scalar rtol */ 6666 const PetscScalar *atol; 6667 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6668 for (i=0; i<n; i++) { 6669 err = PetscAbsScalar(e[i]); 6670 tola = PetscRealPart(atol[i]); 6671 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6672 tol = tola+tolr; 6673 if(tola>0.){ 6674 maxa = PetscMax(maxa,err / tola); 6675 } 6676 if(tolr>0.){ 6677 maxr = PetscMax(maxr,err / tolr); 6678 } 6679 if(tol>0.){ 6680 max = PetscMax(max,err / tol); 6681 } 6682 } 6683 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6684 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 6685 const PetscScalar *rtol; 6686 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6687 6688 for (i=0; i<n; i++) { 6689 err = PetscAbsScalar(e[i]); 6690 tola = ts->atol; 6691 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6692 tol = tola+tolr; 6693 if(tola>0.){ 6694 maxa = PetscMax(maxa,err / tola); 6695 } 6696 if(tolr>0.){ 6697 maxr = PetscMax(maxr,err / tolr); 6698 } 6699 if(tol>0.){ 6700 max = PetscMax(max,err / tol); 6701 } 6702 } 6703 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6704 } else { /* scalar atol, scalar rtol */ 6705 6706 for (i=0; i<n; i++) { 6707 err = PetscAbsScalar(e[i]); 6708 tola = ts->atol; 6709 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6710 tol = tola+tolr; 6711 if(tola>0.){ 6712 maxa = PetscMax(maxa,err / tola); 6713 } 6714 if(tolr>0.){ 6715 maxr = PetscMax(maxr,err / tolr); 6716 } 6717 if(tol>0.){ 6718 max = PetscMax(max,err / tol); 6719 } 6720 } 6721 } 6722 ierr = VecRestoreArrayRead(E,&e);CHKERRQ(ierr); 6723 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 6724 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 6725 err_loc[0] = max; 6726 err_loc[1] = maxa; 6727 err_loc[2] = maxr; 6728 ierr = MPIU_Allreduce(err_loc,err_glb,3,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6729 gmax = err_glb[0]; 6730 gmaxa = err_glb[1]; 6731 gmaxr = err_glb[2]; 6732 6733 *norm = gmax; 6734 *norma = gmaxa; 6735 *normr = gmaxr; 6736 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 6737 if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 6738 if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 6739 PetscFunctionReturn(0); 6740 } 6741 6742 /*@ 6743 TSErrorWeightedENorm - compute a weighted error norm based on supplied absolute and relative tolerances 6744 6745 Collective on TS 6746 6747 Input Arguments: 6748 + ts - time stepping context 6749 . E - error vector 6750 . U - state vector, usually ts->vec_sol 6751 . Y - state vector, previous time step 6752 - wnormtype - norm type, either NORM_2 or NORM_INFINITY 6753 6754 Output Arguments: 6755 . norm - weighted norm, a value of 1.0 achieves a balance between absolute and relative tolerances 6756 . norma - weighted norm, a value of 1.0 means that the error meets the absolute tolerance set by the user 6757 . normr - weighted norm, a value of 1.0 means that the error meets the relative tolerance set by the user 6758 6759 Options Database Keys: 6760 . -ts_adapt_wnormtype <wnormtype> - 2, INFINITY 6761 6762 Level: developer 6763 6764 .seealso: TSErrorWeightedENormInfinity(), TSErrorWeightedENorm2(), TSErrorWeightedNormInfinity(), TSErrorWeightedNorm2() 6765 @*/ 6766 PetscErrorCode TSErrorWeightedENorm(TS ts,Vec E,Vec U,Vec Y,NormType wnormtype,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6767 { 6768 PetscErrorCode ierr; 6769 6770 PetscFunctionBegin; 6771 if (wnormtype == NORM_2) { 6772 ierr = TSErrorWeightedENorm2(ts,E,U,Y,norm,norma,normr);CHKERRQ(ierr); 6773 } else if(wnormtype == NORM_INFINITY) { 6774 ierr = TSErrorWeightedENormInfinity(ts,E,U,Y,norm,norma,normr);CHKERRQ(ierr); 6775 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]); 6776 PetscFunctionReturn(0); 6777 } 6778 6779 6780 /*@ 6781 TSSetCFLTimeLocal - Set the local CFL constraint relative to forward Euler 6782 6783 Logically Collective on TS 6784 6785 Input Arguments: 6786 + ts - time stepping context 6787 - cfltime - maximum stable time step if using forward Euler (value can be different on each process) 6788 6789 Note: 6790 After calling this function, the global CFL time can be obtained by calling TSGetCFLTime() 6791 6792 Level: intermediate 6793 6794 .seealso: TSGetCFLTime(), TSADAPTCFL 6795 @*/ 6796 PetscErrorCode TSSetCFLTimeLocal(TS ts,PetscReal cfltime) 6797 { 6798 PetscFunctionBegin; 6799 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6800 ts->cfltime_local = cfltime; 6801 ts->cfltime = -1.; 6802 PetscFunctionReturn(0); 6803 } 6804 6805 /*@ 6806 TSGetCFLTime - Get the maximum stable time step according to CFL criteria applied to forward Euler 6807 6808 Collective on TS 6809 6810 Input Arguments: 6811 . ts - time stepping context 6812 6813 Output Arguments: 6814 . cfltime - maximum stable time step for forward Euler 6815 6816 Level: advanced 6817 6818 .seealso: TSSetCFLTimeLocal() 6819 @*/ 6820 PetscErrorCode TSGetCFLTime(TS ts,PetscReal *cfltime) 6821 { 6822 PetscErrorCode ierr; 6823 6824 PetscFunctionBegin; 6825 if (ts->cfltime < 0) { 6826 ierr = MPIU_Allreduce(&ts->cfltime_local,&ts->cfltime,1,MPIU_REAL,MPIU_MIN,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6827 } 6828 *cfltime = ts->cfltime; 6829 PetscFunctionReturn(0); 6830 } 6831 6832 /*@ 6833 TSVISetVariableBounds - Sets the lower and upper bounds for the solution vector. xl <= x <= xu 6834 6835 Input Parameters: 6836 . ts - the TS context. 6837 . xl - lower bound. 6838 . xu - upper bound. 6839 6840 Notes: 6841 If this routine is not called then the lower and upper bounds are set to 6842 PETSC_NINFINITY and PETSC_INFINITY respectively during SNESSetUp(). 6843 6844 Level: advanced 6845 6846 @*/ 6847 PetscErrorCode TSVISetVariableBounds(TS ts, Vec xl, Vec xu) 6848 { 6849 PetscErrorCode ierr; 6850 SNES snes; 6851 6852 PetscFunctionBegin; 6853 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 6854 ierr = SNESVISetVariableBounds(snes,xl,xu);CHKERRQ(ierr); 6855 PetscFunctionReturn(0); 6856 } 6857 6858 #if defined(PETSC_HAVE_MATLAB_ENGINE) 6859 #include <mex.h> 6860 6861 typedef struct {char *funcname; mxArray *ctx;} TSMatlabContext; 6862 6863 /* 6864 TSComputeFunction_Matlab - Calls the function that has been set with 6865 TSSetFunctionMatlab(). 6866 6867 Collective on TS 6868 6869 Input Parameters: 6870 + snes - the TS context 6871 - u - input vector 6872 6873 Output Parameter: 6874 . y - function vector, as set by TSSetFunction() 6875 6876 Notes: 6877 TSComputeFunction() is typically used within nonlinear solvers 6878 implementations, so most users would not generally call this routine 6879 themselves. 6880 6881 Level: developer 6882 6883 .keywords: TS, nonlinear, compute, function 6884 6885 .seealso: TSSetFunction(), TSGetFunction() 6886 */ 6887 PetscErrorCode TSComputeFunction_Matlab(TS snes,PetscReal time,Vec u,Vec udot,Vec y, void *ctx) 6888 { 6889 PetscErrorCode ierr; 6890 TSMatlabContext *sctx = (TSMatlabContext*)ctx; 6891 int nlhs = 1,nrhs = 7; 6892 mxArray *plhs[1],*prhs[7]; 6893 long long int lx = 0,lxdot = 0,ly = 0,ls = 0; 6894 6895 PetscFunctionBegin; 6896 PetscValidHeaderSpecific(snes,TS_CLASSID,1); 6897 PetscValidHeaderSpecific(u,VEC_CLASSID,3); 6898 PetscValidHeaderSpecific(udot,VEC_CLASSID,4); 6899 PetscValidHeaderSpecific(y,VEC_CLASSID,5); 6900 PetscCheckSameComm(snes,1,u,3); 6901 PetscCheckSameComm(snes,1,y,5); 6902 6903 ierr = PetscMemcpy(&ls,&snes,sizeof(snes));CHKERRQ(ierr); 6904 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 6905 ierr = PetscMemcpy(&lxdot,&udot,sizeof(udot));CHKERRQ(ierr); 6906 ierr = PetscMemcpy(&ly,&y,sizeof(u));CHKERRQ(ierr); 6907 6908 prhs[0] = mxCreateDoubleScalar((double)ls); 6909 prhs[1] = mxCreateDoubleScalar(time); 6910 prhs[2] = mxCreateDoubleScalar((double)lx); 6911 prhs[3] = mxCreateDoubleScalar((double)lxdot); 6912 prhs[4] = mxCreateDoubleScalar((double)ly); 6913 prhs[5] = mxCreateString(sctx->funcname); 6914 prhs[6] = sctx->ctx; 6915 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSComputeFunctionInternal");CHKERRQ(ierr); 6916 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 6917 mxDestroyArray(prhs[0]); 6918 mxDestroyArray(prhs[1]); 6919 mxDestroyArray(prhs[2]); 6920 mxDestroyArray(prhs[3]); 6921 mxDestroyArray(prhs[4]); 6922 mxDestroyArray(prhs[5]); 6923 mxDestroyArray(plhs[0]); 6924 PetscFunctionReturn(0); 6925 } 6926 6927 /* 6928 TSSetFunctionMatlab - Sets the function evaluation routine and function 6929 vector for use by the TS routines in solving ODEs 6930 equations from MATLAB. Here the function is a string containing the name of a MATLAB function 6931 6932 Logically Collective on TS 6933 6934 Input Parameters: 6935 + ts - the TS context 6936 - func - function evaluation routine 6937 6938 Calling sequence of func: 6939 $ func (TS ts,PetscReal time,Vec u,Vec udot,Vec f,void *ctx); 6940 6941 Level: beginner 6942 6943 .keywords: TS, nonlinear, set, function 6944 6945 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 6946 */ 6947 PetscErrorCode TSSetFunctionMatlab(TS ts,const char *func,mxArray *ctx) 6948 { 6949 PetscErrorCode ierr; 6950 TSMatlabContext *sctx; 6951 6952 PetscFunctionBegin; 6953 /* currently sctx is memory bleed */ 6954 ierr = PetscNew(&sctx);CHKERRQ(ierr); 6955 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 6956 /* 6957 This should work, but it doesn't 6958 sctx->ctx = ctx; 6959 mexMakeArrayPersistent(sctx->ctx); 6960 */ 6961 sctx->ctx = mxDuplicateArray(ctx); 6962 6963 ierr = TSSetIFunction(ts,NULL,TSComputeFunction_Matlab,sctx);CHKERRQ(ierr); 6964 PetscFunctionReturn(0); 6965 } 6966 6967 /* 6968 TSComputeJacobian_Matlab - Calls the function that has been set with 6969 TSSetJacobianMatlab(). 6970 6971 Collective on TS 6972 6973 Input Parameters: 6974 + ts - the TS context 6975 . u - input vector 6976 . A, B - the matrices 6977 - ctx - user context 6978 6979 Level: developer 6980 6981 .keywords: TS, nonlinear, compute, function 6982 6983 .seealso: TSSetFunction(), TSGetFunction() 6984 @*/ 6985 PetscErrorCode TSComputeJacobian_Matlab(TS ts,PetscReal time,Vec u,Vec udot,PetscReal shift,Mat A,Mat B,void *ctx) 6986 { 6987 PetscErrorCode ierr; 6988 TSMatlabContext *sctx = (TSMatlabContext*)ctx; 6989 int nlhs = 2,nrhs = 9; 6990 mxArray *plhs[2],*prhs[9]; 6991 long long int lx = 0,lxdot = 0,lA = 0,ls = 0, lB = 0; 6992 6993 PetscFunctionBegin; 6994 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6995 PetscValidHeaderSpecific(u,VEC_CLASSID,3); 6996 6997 /* call Matlab function in ctx with arguments u and y */ 6998 6999 ierr = PetscMemcpy(&ls,&ts,sizeof(ts));CHKERRQ(ierr); 7000 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 7001 ierr = PetscMemcpy(&lxdot,&udot,sizeof(u));CHKERRQ(ierr); 7002 ierr = PetscMemcpy(&lA,A,sizeof(u));CHKERRQ(ierr); 7003 ierr = PetscMemcpy(&lB,B,sizeof(u));CHKERRQ(ierr); 7004 7005 prhs[0] = mxCreateDoubleScalar((double)ls); 7006 prhs[1] = mxCreateDoubleScalar((double)time); 7007 prhs[2] = mxCreateDoubleScalar((double)lx); 7008 prhs[3] = mxCreateDoubleScalar((double)lxdot); 7009 prhs[4] = mxCreateDoubleScalar((double)shift); 7010 prhs[5] = mxCreateDoubleScalar((double)lA); 7011 prhs[6] = mxCreateDoubleScalar((double)lB); 7012 prhs[7] = mxCreateString(sctx->funcname); 7013 prhs[8] = sctx->ctx; 7014 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSComputeJacobianInternal");CHKERRQ(ierr); 7015 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 7016 mxDestroyArray(prhs[0]); 7017 mxDestroyArray(prhs[1]); 7018 mxDestroyArray(prhs[2]); 7019 mxDestroyArray(prhs[3]); 7020 mxDestroyArray(prhs[4]); 7021 mxDestroyArray(prhs[5]); 7022 mxDestroyArray(prhs[6]); 7023 mxDestroyArray(prhs[7]); 7024 mxDestroyArray(plhs[0]); 7025 mxDestroyArray(plhs[1]); 7026 PetscFunctionReturn(0); 7027 } 7028 7029 /* 7030 TSSetJacobianMatlab - Sets the Jacobian function evaluation routine and two empty Jacobian matrices 7031 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 7032 7033 Logically Collective on TS 7034 7035 Input Parameters: 7036 + ts - the TS context 7037 . A,B - Jacobian matrices 7038 . func - function evaluation routine 7039 - ctx - user context 7040 7041 Calling sequence of func: 7042 $ flag = func (TS ts,PetscReal time,Vec u,Vec udot,Mat A,Mat B,void *ctx); 7043 7044 Level: developer 7045 7046 .keywords: TS, nonlinear, set, function 7047 7048 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 7049 */ 7050 PetscErrorCode TSSetJacobianMatlab(TS ts,Mat A,Mat B,const char *func,mxArray *ctx) 7051 { 7052 PetscErrorCode ierr; 7053 TSMatlabContext *sctx; 7054 7055 PetscFunctionBegin; 7056 /* currently sctx is memory bleed */ 7057 ierr = PetscNew(&sctx);CHKERRQ(ierr); 7058 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 7059 /* 7060 This should work, but it doesn't 7061 sctx->ctx = ctx; 7062 mexMakeArrayPersistent(sctx->ctx); 7063 */ 7064 sctx->ctx = mxDuplicateArray(ctx); 7065 7066 ierr = TSSetIJacobian(ts,A,B,TSComputeJacobian_Matlab,sctx);CHKERRQ(ierr); 7067 PetscFunctionReturn(0); 7068 } 7069 7070 /* 7071 TSMonitor_Matlab - Calls the function that has been set with TSMonitorSetMatlab(). 7072 7073 Collective on TS 7074 7075 .seealso: TSSetFunction(), TSGetFunction() 7076 @*/ 7077 PetscErrorCode TSMonitor_Matlab(TS ts,PetscInt it, PetscReal time,Vec u, void *ctx) 7078 { 7079 PetscErrorCode ierr; 7080 TSMatlabContext *sctx = (TSMatlabContext*)ctx; 7081 int nlhs = 1,nrhs = 6; 7082 mxArray *plhs[1],*prhs[6]; 7083 long long int lx = 0,ls = 0; 7084 7085 PetscFunctionBegin; 7086 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 7087 PetscValidHeaderSpecific(u,VEC_CLASSID,4); 7088 7089 ierr = PetscMemcpy(&ls,&ts,sizeof(ts));CHKERRQ(ierr); 7090 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 7091 7092 prhs[0] = mxCreateDoubleScalar((double)ls); 7093 prhs[1] = mxCreateDoubleScalar((double)it); 7094 prhs[2] = mxCreateDoubleScalar((double)time); 7095 prhs[3] = mxCreateDoubleScalar((double)lx); 7096 prhs[4] = mxCreateString(sctx->funcname); 7097 prhs[5] = sctx->ctx; 7098 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSMonitorInternal");CHKERRQ(ierr); 7099 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 7100 mxDestroyArray(prhs[0]); 7101 mxDestroyArray(prhs[1]); 7102 mxDestroyArray(prhs[2]); 7103 mxDestroyArray(prhs[3]); 7104 mxDestroyArray(prhs[4]); 7105 mxDestroyArray(plhs[0]); 7106 PetscFunctionReturn(0); 7107 } 7108 7109 /* 7110 TSMonitorSetMatlab - Sets the monitor function from Matlab 7111 7112 Level: developer 7113 7114 .keywords: TS, nonlinear, set, function 7115 7116 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 7117 */ 7118 PetscErrorCode TSMonitorSetMatlab(TS ts,const char *func,mxArray *ctx) 7119 { 7120 PetscErrorCode ierr; 7121 TSMatlabContext *sctx; 7122 7123 PetscFunctionBegin; 7124 /* currently sctx is memory bleed */ 7125 ierr = PetscNew(&sctx);CHKERRQ(ierr); 7126 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 7127 /* 7128 This should work, but it doesn't 7129 sctx->ctx = ctx; 7130 mexMakeArrayPersistent(sctx->ctx); 7131 */ 7132 sctx->ctx = mxDuplicateArray(ctx); 7133 7134 ierr = TSMonitorSet(ts,TSMonitor_Matlab,sctx,NULL);CHKERRQ(ierr); 7135 PetscFunctionReturn(0); 7136 } 7137 #endif 7138 7139 /*@C 7140 TSMonitorLGSolution - Monitors progress of the TS solvers by plotting each component of the solution vector 7141 in a time based line graph 7142 7143 Collective on TS 7144 7145 Input Parameters: 7146 + ts - the TS context 7147 . step - current time-step 7148 . ptime - current time 7149 . u - current solution 7150 - dctx - the TSMonitorLGCtx object that contains all the options for the monitoring, this is created with TSMonitorLGCtxCreate() 7151 7152 Options Database: 7153 . -ts_monitor_lg_solution_variables 7154 7155 Level: intermediate 7156 7157 Notes: Each process in a parallel run displays its component solutions in a separate window 7158 7159 .keywords: TS, vector, monitor, view 7160 7161 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGCtxCreate(), TSMonitorLGCtxSetVariableNames(), TSMonitorLGCtxGetVariableNames(), 7162 TSMonitorLGSetVariableNames(), TSMonitorLGGetVariableNames(), TSMonitorLGSetDisplayVariables(), TSMonitorLGCtxSetDisplayVariables(), 7163 TSMonitorLGCtxSetTransform(), TSMonitorLGSetTransform(), TSMonitorLGError(), TSMonitorLGSNESIterations(), TSMonitorLGKSPIterations(), 7164 TSMonitorEnvelopeCtxCreate(), TSMonitorEnvelopeGetBounds(), TSMonitorEnvelopeCtxDestroy(), TSMonitorEnvelop() 7165 @*/ 7166 PetscErrorCode TSMonitorLGSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dctx) 7167 { 7168 PetscErrorCode ierr; 7169 TSMonitorLGCtx ctx = (TSMonitorLGCtx)dctx; 7170 const PetscScalar *yy; 7171 Vec v; 7172 7173 PetscFunctionBegin; 7174 if (step < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */ 7175 if (!step) { 7176 PetscDrawAxis axis; 7177 PetscInt dim; 7178 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 7179 ierr = PetscDrawAxisSetLabels(axis,"Solution as function of time","Time","Solution");CHKERRQ(ierr); 7180 if (!ctx->names) { 7181 PetscBool flg; 7182 /* user provides names of variables to plot but no names has been set so assume names are integer values */ 7183 ierr = PetscOptionsHasName(((PetscObject)ts)->options,((PetscObject)ts)->prefix,"-ts_monitor_lg_solution_variables",&flg);CHKERRQ(ierr); 7184 if (flg) { 7185 PetscInt i,n; 7186 char **names; 7187 ierr = VecGetSize(u,&n);CHKERRQ(ierr); 7188 ierr = PetscMalloc1(n+1,&names);CHKERRQ(ierr); 7189 for (i=0; i<n; i++) { 7190 ierr = PetscMalloc1(5,&names[i]);CHKERRQ(ierr); 7191 ierr = PetscSNPrintf(names[i],5,"%D",i);CHKERRQ(ierr); 7192 } 7193 names[n] = NULL; 7194 ctx->names = names; 7195 } 7196 } 7197 if (ctx->names && !ctx->displaynames) { 7198 char **displaynames; 7199 PetscBool flg; 7200 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 7201 ierr = PetscMalloc1(dim+1,&displaynames);CHKERRQ(ierr); 7202 ierr = PetscMemzero(displaynames,(dim+1)*sizeof(char*));CHKERRQ(ierr); 7203 ierr = PetscOptionsGetStringArray(((PetscObject)ts)->options,((PetscObject)ts)->prefix,"-ts_monitor_lg_solution_variables",displaynames,&dim,&flg);CHKERRQ(ierr); 7204 if (flg) { 7205 ierr = TSMonitorLGCtxSetDisplayVariables(ctx,(const char *const *)displaynames);CHKERRQ(ierr); 7206 } 7207 ierr = PetscStrArrayDestroy(&displaynames);CHKERRQ(ierr); 7208 } 7209 if (ctx->displaynames) { 7210 ierr = PetscDrawLGSetDimension(ctx->lg,ctx->ndisplayvariables);CHKERRQ(ierr); 7211 ierr = PetscDrawLGSetLegend(ctx->lg,(const char *const *)ctx->displaynames);CHKERRQ(ierr); 7212 } else if (ctx->names) { 7213 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 7214 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 7215 ierr = PetscDrawLGSetLegend(ctx->lg,(const char *const *)ctx->names);CHKERRQ(ierr); 7216 } else { 7217 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 7218 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 7219 } 7220 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 7221 } 7222 7223 if (!ctx->transform) v = u; 7224 else {ierr = (*ctx->transform)(ctx->transformctx,u,&v);CHKERRQ(ierr);} 7225 ierr = VecGetArrayRead(v,&yy);CHKERRQ(ierr); 7226 if (ctx->displaynames) { 7227 PetscInt i; 7228 for (i=0; i<ctx->ndisplayvariables; i++) 7229 ctx->displayvalues[i] = PetscRealPart(yy[ctx->displayvariables[i]]); 7230 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,ctx->displayvalues);CHKERRQ(ierr); 7231 } else { 7232 #if defined(PETSC_USE_COMPLEX) 7233 PetscInt i,n; 7234 PetscReal *yreal; 7235 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 7236 ierr = PetscMalloc1(n,&yreal);CHKERRQ(ierr); 7237 for (i=0; i<n; i++) yreal[i] = PetscRealPart(yy[i]); 7238 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yreal);CHKERRQ(ierr); 7239 ierr = PetscFree(yreal);CHKERRQ(ierr); 7240 #else 7241 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yy);CHKERRQ(ierr); 7242 #endif 7243 } 7244 ierr = VecRestoreArrayRead(v,&yy);CHKERRQ(ierr); 7245 if (ctx->transform) {ierr = VecDestroy(&v);CHKERRQ(ierr);} 7246 7247 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 7248 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 7249 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 7250 } 7251 PetscFunctionReturn(0); 7252 } 7253 7254 /*@C 7255 TSMonitorLGSetVariableNames - Sets the name of each component in the solution vector so that it may be displayed in the plot 7256 7257 Collective on TS 7258 7259 Input Parameters: 7260 + ts - the TS context 7261 - names - the names of the components, final string must be NULL 7262 7263 Level: intermediate 7264 7265 Notes: If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored 7266 7267 .keywords: TS, vector, monitor, view 7268 7269 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables(), TSMonitorLGCtxSetVariableNames() 7270 @*/ 7271 PetscErrorCode TSMonitorLGSetVariableNames(TS ts,const char * const *names) 7272 { 7273 PetscErrorCode ierr; 7274 PetscInt i; 7275 7276 PetscFunctionBegin; 7277 for (i=0; i<ts->numbermonitors; i++) { 7278 if (ts->monitor[i] == TSMonitorLGSolution) { 7279 ierr = TSMonitorLGCtxSetVariableNames((TSMonitorLGCtx)ts->monitorcontext[i],names);CHKERRQ(ierr); 7280 break; 7281 } 7282 } 7283 PetscFunctionReturn(0); 7284 } 7285 7286 /*@C 7287 TSMonitorLGCtxSetVariableNames - Sets the name of each component in the solution vector so that it may be displayed in the plot 7288 7289 Collective on TS 7290 7291 Input Parameters: 7292 + ts - the TS context 7293 - names - the names of the components, final string must be NULL 7294 7295 Level: intermediate 7296 7297 .keywords: TS, vector, monitor, view 7298 7299 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables(), TSMonitorLGSetVariableNames() 7300 @*/ 7301 PetscErrorCode TSMonitorLGCtxSetVariableNames(TSMonitorLGCtx ctx,const char * const *names) 7302 { 7303 PetscErrorCode ierr; 7304 7305 PetscFunctionBegin; 7306 ierr = PetscStrArrayDestroy(&ctx->names);CHKERRQ(ierr); 7307 ierr = PetscStrArrayallocpy(names,&ctx->names);CHKERRQ(ierr); 7308 PetscFunctionReturn(0); 7309 } 7310 7311 /*@C 7312 TSMonitorLGGetVariableNames - Gets the name of each component in the solution vector so that it may be displayed in the plot 7313 7314 Collective on TS 7315 7316 Input Parameter: 7317 . ts - the TS context 7318 7319 Output Parameter: 7320 . names - the names of the components, final string must be NULL 7321 7322 Level: intermediate 7323 7324 Notes: If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored 7325 7326 .keywords: TS, vector, monitor, view 7327 7328 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables() 7329 @*/ 7330 PetscErrorCode TSMonitorLGGetVariableNames(TS ts,const char *const **names) 7331 { 7332 PetscInt i; 7333 7334 PetscFunctionBegin; 7335 *names = NULL; 7336 for (i=0; i<ts->numbermonitors; i++) { 7337 if (ts->monitor[i] == TSMonitorLGSolution) { 7338 TSMonitorLGCtx ctx = (TSMonitorLGCtx) ts->monitorcontext[i]; 7339 *names = (const char *const *)ctx->names; 7340 break; 7341 } 7342 } 7343 PetscFunctionReturn(0); 7344 } 7345 7346 /*@C 7347 TSMonitorLGCtxSetDisplayVariables - Sets the variables that are to be display in the monitor 7348 7349 Collective on TS 7350 7351 Input Parameters: 7352 + ctx - the TSMonitorLG context 7353 . displaynames - the names of the components, final string must be NULL 7354 7355 Level: intermediate 7356 7357 .keywords: TS, vector, monitor, view 7358 7359 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames() 7360 @*/ 7361 PetscErrorCode TSMonitorLGCtxSetDisplayVariables(TSMonitorLGCtx ctx,const char * const *displaynames) 7362 { 7363 PetscInt j = 0,k; 7364 PetscErrorCode ierr; 7365 7366 PetscFunctionBegin; 7367 if (!ctx->names) PetscFunctionReturn(0); 7368 ierr = PetscStrArrayDestroy(&ctx->displaynames);CHKERRQ(ierr); 7369 ierr = PetscStrArrayallocpy(displaynames,&ctx->displaynames);CHKERRQ(ierr); 7370 while (displaynames[j]) j++; 7371 ctx->ndisplayvariables = j; 7372 ierr = PetscMalloc1(ctx->ndisplayvariables,&ctx->displayvariables);CHKERRQ(ierr); 7373 ierr = PetscMalloc1(ctx->ndisplayvariables,&ctx->displayvalues);CHKERRQ(ierr); 7374 j = 0; 7375 while (displaynames[j]) { 7376 k = 0; 7377 while (ctx->names[k]) { 7378 PetscBool flg; 7379 ierr = PetscStrcmp(displaynames[j],ctx->names[k],&flg);CHKERRQ(ierr); 7380 if (flg) { 7381 ctx->displayvariables[j] = k; 7382 break; 7383 } 7384 k++; 7385 } 7386 j++; 7387 } 7388 PetscFunctionReturn(0); 7389 } 7390 7391 /*@C 7392 TSMonitorLGSetDisplayVariables - Sets the variables that are to be display in the monitor 7393 7394 Collective on TS 7395 7396 Input Parameters: 7397 + ts - the TS context 7398 . displaynames - the names of the components, final string must be NULL 7399 7400 Notes: If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored 7401 7402 Level: intermediate 7403 7404 .keywords: TS, vector, monitor, view 7405 7406 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames() 7407 @*/ 7408 PetscErrorCode TSMonitorLGSetDisplayVariables(TS ts,const char * const *displaynames) 7409 { 7410 PetscInt i; 7411 PetscErrorCode ierr; 7412 7413 PetscFunctionBegin; 7414 for (i=0; i<ts->numbermonitors; i++) { 7415 if (ts->monitor[i] == TSMonitorLGSolution) { 7416 ierr = TSMonitorLGCtxSetDisplayVariables((TSMonitorLGCtx)ts->monitorcontext[i],displaynames);CHKERRQ(ierr); 7417 break; 7418 } 7419 } 7420 PetscFunctionReturn(0); 7421 } 7422 7423 /*@C 7424 TSMonitorLGSetTransform - Solution vector will be transformed by provided function before being displayed 7425 7426 Collective on TS 7427 7428 Input Parameters: 7429 + ts - the TS context 7430 . transform - the transform function 7431 . destroy - function to destroy the optional context 7432 - ctx - optional context used by transform function 7433 7434 Notes: If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored 7435 7436 Level: intermediate 7437 7438 .keywords: TS, vector, monitor, view 7439 7440 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames(), TSMonitorLGCtxSetTransform() 7441 @*/ 7442 PetscErrorCode TSMonitorLGSetTransform(TS ts,PetscErrorCode (*transform)(void*,Vec,Vec*),PetscErrorCode (*destroy)(void*),void *tctx) 7443 { 7444 PetscInt i; 7445 PetscErrorCode ierr; 7446 7447 PetscFunctionBegin; 7448 for (i=0; i<ts->numbermonitors; i++) { 7449 if (ts->monitor[i] == TSMonitorLGSolution) { 7450 ierr = TSMonitorLGCtxSetTransform((TSMonitorLGCtx)ts->monitorcontext[i],transform,destroy,tctx);CHKERRQ(ierr); 7451 } 7452 } 7453 PetscFunctionReturn(0); 7454 } 7455 7456 /*@C 7457 TSMonitorLGCtxSetTransform - Solution vector will be transformed by provided function before being displayed 7458 7459 Collective on TSLGCtx 7460 7461 Input Parameters: 7462 + ts - the TS context 7463 . transform - the transform function 7464 . destroy - function to destroy the optional context 7465 - ctx - optional context used by transform function 7466 7467 Level: intermediate 7468 7469 .keywords: TS, vector, monitor, view 7470 7471 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames(), TSMonitorLGSetTransform() 7472 @*/ 7473 PetscErrorCode TSMonitorLGCtxSetTransform(TSMonitorLGCtx ctx,PetscErrorCode (*transform)(void*,Vec,Vec*),PetscErrorCode (*destroy)(void*),void *tctx) 7474 { 7475 PetscFunctionBegin; 7476 ctx->transform = transform; 7477 ctx->transformdestroy = destroy; 7478 ctx->transformctx = tctx; 7479 PetscFunctionReturn(0); 7480 } 7481 7482 /*@C 7483 TSMonitorLGError - Monitors progress of the TS solvers by plotting each component of the error 7484 in a time based line graph 7485 7486 Collective on TS 7487 7488 Input Parameters: 7489 + ts - the TS context 7490 . step - current time-step 7491 . ptime - current time 7492 . u - current solution 7493 - dctx - TSMonitorLGCtx object created with TSMonitorLGCtxCreate() 7494 7495 Level: intermediate 7496 7497 Notes: Each process in a parallel run displays its component errors in a separate window 7498 7499 The user must provide the solution using TSSetSolutionFunction() to use this monitor. 7500 7501 Options Database Keys: 7502 . -ts_monitor_lg_error - create a graphical monitor of error history 7503 7504 .keywords: TS, vector, monitor, view 7505 7506 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSSetSolutionFunction() 7507 @*/ 7508 PetscErrorCode TSMonitorLGError(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 7509 { 7510 PetscErrorCode ierr; 7511 TSMonitorLGCtx ctx = (TSMonitorLGCtx)dummy; 7512 const PetscScalar *yy; 7513 Vec y; 7514 7515 PetscFunctionBegin; 7516 if (!step) { 7517 PetscDrawAxis axis; 7518 PetscInt dim; 7519 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 7520 ierr = PetscDrawAxisSetLabels(axis,"Error in solution as function of time","Time","Error");CHKERRQ(ierr); 7521 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 7522 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 7523 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 7524 } 7525 ierr = VecDuplicate(u,&y);CHKERRQ(ierr); 7526 ierr = TSComputeSolutionFunction(ts,ptime,y);CHKERRQ(ierr); 7527 ierr = VecAXPY(y,-1.0,u);CHKERRQ(ierr); 7528 ierr = VecGetArrayRead(y,&yy);CHKERRQ(ierr); 7529 #if defined(PETSC_USE_COMPLEX) 7530 { 7531 PetscReal *yreal; 7532 PetscInt i,n; 7533 ierr = VecGetLocalSize(y,&n);CHKERRQ(ierr); 7534 ierr = PetscMalloc1(n,&yreal);CHKERRQ(ierr); 7535 for (i=0; i<n; i++) yreal[i] = PetscRealPart(yy[i]); 7536 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yreal);CHKERRQ(ierr); 7537 ierr = PetscFree(yreal);CHKERRQ(ierr); 7538 } 7539 #else 7540 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yy);CHKERRQ(ierr); 7541 #endif 7542 ierr = VecRestoreArrayRead(y,&yy);CHKERRQ(ierr); 7543 ierr = VecDestroy(&y);CHKERRQ(ierr); 7544 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 7545 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 7546 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 7547 } 7548 PetscFunctionReturn(0); 7549 } 7550 7551 PetscErrorCode TSMonitorLGSNESIterations(TS ts,PetscInt n,PetscReal ptime,Vec v,void *monctx) 7552 { 7553 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 7554 PetscReal x = ptime,y; 7555 PetscErrorCode ierr; 7556 PetscInt its; 7557 7558 PetscFunctionBegin; 7559 if (n < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */ 7560 if (!n) { 7561 PetscDrawAxis axis; 7562 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 7563 ierr = PetscDrawAxisSetLabels(axis,"Nonlinear iterations as function of time","Time","SNES Iterations");CHKERRQ(ierr); 7564 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 7565 ctx->snes_its = 0; 7566 } 7567 ierr = TSGetSNESIterations(ts,&its);CHKERRQ(ierr); 7568 y = its - ctx->snes_its; 7569 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 7570 if (((ctx->howoften > 0) && (!(n % ctx->howoften)) && (n > -1)) || ((ctx->howoften == -1) && (n == -1))) { 7571 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 7572 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 7573 } 7574 ctx->snes_its = its; 7575 PetscFunctionReturn(0); 7576 } 7577 7578 PetscErrorCode TSMonitorLGKSPIterations(TS ts,PetscInt n,PetscReal ptime,Vec v,void *monctx) 7579 { 7580 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 7581 PetscReal x = ptime,y; 7582 PetscErrorCode ierr; 7583 PetscInt its; 7584 7585 PetscFunctionBegin; 7586 if (n < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */ 7587 if (!n) { 7588 PetscDrawAxis axis; 7589 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 7590 ierr = PetscDrawAxisSetLabels(axis,"Linear iterations as function of time","Time","KSP Iterations");CHKERRQ(ierr); 7591 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 7592 ctx->ksp_its = 0; 7593 } 7594 ierr = TSGetKSPIterations(ts,&its);CHKERRQ(ierr); 7595 y = its - ctx->ksp_its; 7596 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 7597 if (((ctx->howoften > 0) && (!(n % ctx->howoften)) && (n > -1)) || ((ctx->howoften == -1) && (n == -1))) { 7598 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 7599 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 7600 } 7601 ctx->ksp_its = its; 7602 PetscFunctionReturn(0); 7603 } 7604 7605 /*@ 7606 TSComputeLinearStability - computes the linear stability function at a point 7607 7608 Collective on TS and Vec 7609 7610 Input Parameters: 7611 + ts - the TS context 7612 - xr,xi - real and imaginary part of input arguments 7613 7614 Output Parameters: 7615 . yr,yi - real and imaginary part of function value 7616 7617 Level: developer 7618 7619 .keywords: TS, compute 7620 7621 .seealso: TSSetRHSFunction(), TSComputeIFunction() 7622 @*/ 7623 PetscErrorCode TSComputeLinearStability(TS ts,PetscReal xr,PetscReal xi,PetscReal *yr,PetscReal *yi) 7624 { 7625 PetscErrorCode ierr; 7626 7627 PetscFunctionBegin; 7628 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 7629 if (!ts->ops->linearstability) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Linearized stability function not provided for this method"); 7630 ierr = (*ts->ops->linearstability)(ts,xr,xi,yr,yi);CHKERRQ(ierr); 7631 PetscFunctionReturn(0); 7632 } 7633 7634 /* ------------------------------------------------------------------------*/ 7635 /*@C 7636 TSMonitorEnvelopeCtxCreate - Creates a context for use with TSMonitorEnvelope() 7637 7638 Collective on TS 7639 7640 Input Parameters: 7641 . ts - the ODE solver object 7642 7643 Output Parameter: 7644 . ctx - the context 7645 7646 Level: intermediate 7647 7648 .keywords: TS, monitor, line graph, residual, seealso 7649 7650 .seealso: TSMonitorLGTimeStep(), TSMonitorSet(), TSMonitorLGSolution(), TSMonitorLGError() 7651 7652 @*/ 7653 PetscErrorCode TSMonitorEnvelopeCtxCreate(TS ts,TSMonitorEnvelopeCtx *ctx) 7654 { 7655 PetscErrorCode ierr; 7656 7657 PetscFunctionBegin; 7658 ierr = PetscNew(ctx);CHKERRQ(ierr); 7659 PetscFunctionReturn(0); 7660 } 7661 7662 /*@C 7663 TSMonitorEnvelope - Monitors the maximum and minimum value of each component of the solution 7664 7665 Collective on TS 7666 7667 Input Parameters: 7668 + ts - the TS context 7669 . step - current time-step 7670 . ptime - current time 7671 . u - current solution 7672 - dctx - the envelope context 7673 7674 Options Database: 7675 . -ts_monitor_envelope 7676 7677 Level: intermediate 7678 7679 Notes: after a solve you can use TSMonitorEnvelopeGetBounds() to access the envelope 7680 7681 .keywords: TS, vector, monitor, view 7682 7683 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorEnvelopeGetBounds(), TSMonitorEnvelopeCtxCreate() 7684 @*/ 7685 PetscErrorCode TSMonitorEnvelope(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dctx) 7686 { 7687 PetscErrorCode ierr; 7688 TSMonitorEnvelopeCtx ctx = (TSMonitorEnvelopeCtx)dctx; 7689 7690 PetscFunctionBegin; 7691 if (!ctx->max) { 7692 ierr = VecDuplicate(u,&ctx->max);CHKERRQ(ierr); 7693 ierr = VecDuplicate(u,&ctx->min);CHKERRQ(ierr); 7694 ierr = VecCopy(u,ctx->max);CHKERRQ(ierr); 7695 ierr = VecCopy(u,ctx->min);CHKERRQ(ierr); 7696 } else { 7697 ierr = VecPointwiseMax(ctx->max,u,ctx->max);CHKERRQ(ierr); 7698 ierr = VecPointwiseMin(ctx->min,u,ctx->min);CHKERRQ(ierr); 7699 } 7700 PetscFunctionReturn(0); 7701 } 7702 7703 /*@C 7704 TSMonitorEnvelopeGetBounds - Gets the bounds for the components of the solution 7705 7706 Collective on TS 7707 7708 Input Parameter: 7709 . ts - the TS context 7710 7711 Output Parameter: 7712 + max - the maximum values 7713 - min - the minimum values 7714 7715 Notes: If the TS does not have a TSMonitorEnvelopeCtx associated with it then this function is ignored 7716 7717 Level: intermediate 7718 7719 .keywords: TS, vector, monitor, view 7720 7721 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables() 7722 @*/ 7723 PetscErrorCode TSMonitorEnvelopeGetBounds(TS ts,Vec *max,Vec *min) 7724 { 7725 PetscInt i; 7726 7727 PetscFunctionBegin; 7728 if (max) *max = NULL; 7729 if (min) *min = NULL; 7730 for (i=0; i<ts->numbermonitors; i++) { 7731 if (ts->monitor[i] == TSMonitorEnvelope) { 7732 TSMonitorEnvelopeCtx ctx = (TSMonitorEnvelopeCtx) ts->monitorcontext[i]; 7733 if (max) *max = ctx->max; 7734 if (min) *min = ctx->min; 7735 break; 7736 } 7737 } 7738 PetscFunctionReturn(0); 7739 } 7740 7741 /*@C 7742 TSMonitorEnvelopeCtxDestroy - Destroys a context that was created with TSMonitorEnvelopeCtxCreate(). 7743 7744 Collective on TSMonitorEnvelopeCtx 7745 7746 Input Parameter: 7747 . ctx - the monitor context 7748 7749 Level: intermediate 7750 7751 .keywords: TS, monitor, line graph, destroy 7752 7753 .seealso: TSMonitorLGCtxCreate(), TSMonitorSet(), TSMonitorLGTimeStep() 7754 @*/ 7755 PetscErrorCode TSMonitorEnvelopeCtxDestroy(TSMonitorEnvelopeCtx *ctx) 7756 { 7757 PetscErrorCode ierr; 7758 7759 PetscFunctionBegin; 7760 ierr = VecDestroy(&(*ctx)->min);CHKERRQ(ierr); 7761 ierr = VecDestroy(&(*ctx)->max);CHKERRQ(ierr); 7762 ierr = PetscFree(*ctx);CHKERRQ(ierr); 7763 PetscFunctionReturn(0); 7764 } 7765 7766 /*@ 7767 TSRestartStep - Flags the solver to restart the next step 7768 7769 Collective on TS 7770 7771 Input Parameter: 7772 . ts - the TS context obtained from TSCreate() 7773 7774 Level: advanced 7775 7776 Notes: 7777 Multistep methods like BDF or Runge-Kutta methods with FSAL property require restarting the solver in the event of 7778 discontinuities. These discontinuities may be introduced as a consequence of explicitly modifications to the solution 7779 vector (which PETSc attempts to detect and handle) or problem coefficients (which PETSc is not able to detect). For 7780 the sake of correctness and maximum safety, users are expected to call TSRestart() whenever they introduce 7781 discontinuities in callback routines (e.g. prestep and poststep routines, or implicit/rhs function routines with 7782 discontinuous source terms). 7783 7784 .keywords: TS, timestep, restart 7785 7786 .seealso: TSSolve(), TSSetPreStep(), TSSetPostStep() 7787 @*/ 7788 PetscErrorCode TSRestartStep(TS ts) 7789 { 7790 PetscFunctionBegin; 7791 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 7792 ts->steprestart = PETSC_TRUE; 7793 PetscFunctionReturn(0); 7794 } 7795 7796 /*@ 7797 TSRollBack - Rolls back one time step 7798 7799 Collective on TS 7800 7801 Input Parameter: 7802 . ts - the TS context obtained from TSCreate() 7803 7804 Level: advanced 7805 7806 .keywords: TS, timestep, rollback 7807 7808 .seealso: TSCreate(), TSSetUp(), TSDestroy(), TSSolve(), TSSetPreStep(), TSSetPreStage(), TSInterpolate() 7809 @*/ 7810 PetscErrorCode TSRollBack(TS ts) 7811 { 7812 PetscErrorCode ierr; 7813 7814 PetscFunctionBegin; 7815 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 7816 if (ts->steprollback) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"TSRollBack already called"); 7817 if (!ts->ops->rollback) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSRollBack not implemented for type '%s'",((PetscObject)ts)->type_name); 7818 ierr = (*ts->ops->rollback)(ts);CHKERRQ(ierr); 7819 ts->time_step = ts->ptime - ts->ptime_prev; 7820 ts->ptime = ts->ptime_prev; 7821 ts->ptime_prev = ts->ptime_prev_rollback; 7822 ts->steps--; 7823 ts->steprollback = PETSC_TRUE; 7824 PetscFunctionReturn(0); 7825 } 7826 7827 /*@ 7828 TSGetStages - Get the number of stages and stage values 7829 7830 Input Parameter: 7831 . ts - the TS context obtained from TSCreate() 7832 7833 Level: advanced 7834 7835 .keywords: TS, getstages 7836 7837 .seealso: TSCreate() 7838 @*/ 7839 PetscErrorCode TSGetStages(TS ts,PetscInt *ns,Vec **Y) 7840 { 7841 PetscErrorCode ierr; 7842 7843 PetscFunctionBegin; 7844 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 7845 PetscValidPointer(ns,2); 7846 7847 if (!ts->ops->getstages) *ns=0; 7848 else { 7849 ierr = (*ts->ops->getstages)(ts,ns,Y);CHKERRQ(ierr); 7850 } 7851 PetscFunctionReturn(0); 7852 } 7853 7854 /*@C 7855 TSComputeIJacobianDefaultColor - Computes the Jacobian using finite differences and coloring to exploit matrix sparsity. 7856 7857 Collective on SNES 7858 7859 Input Parameters: 7860 + ts - the TS context 7861 . t - current timestep 7862 . U - state vector 7863 . Udot - time derivative of state vector 7864 . shift - shift to apply, see note below 7865 - ctx - an optional user context 7866 7867 Output Parameters: 7868 + J - Jacobian matrix (not altered in this routine) 7869 - B - newly computed Jacobian matrix to use with preconditioner (generally the same as J) 7870 7871 Level: intermediate 7872 7873 Notes: 7874 If F(t,U,Udot)=0 is the DAE, the required Jacobian is 7875 7876 dF/dU + shift*dF/dUdot 7877 7878 Most users should not need to explicitly call this routine, as it 7879 is used internally within the nonlinear solvers. 7880 7881 This will first try to get the coloring from the DM. If the DM type has no coloring 7882 routine, then it will try to get the coloring from the matrix. This requires that the 7883 matrix have nonzero entries precomputed. 7884 7885 .keywords: TS, finite differences, Jacobian, coloring, sparse 7886 .seealso: TSSetIJacobian(), MatFDColoringCreate(), MatFDColoringSetFunction() 7887 @*/ 7888 PetscErrorCode TSComputeIJacobianDefaultColor(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat J,Mat B,void *ctx) 7889 { 7890 SNES snes; 7891 MatFDColoring color; 7892 PetscBool hascolor, matcolor = PETSC_FALSE; 7893 PetscErrorCode ierr; 7894 7895 PetscFunctionBegin; 7896 ierr = PetscOptionsGetBool(((PetscObject)ts)->options,((PetscObject) ts)->prefix, "-ts_fd_color_use_mat", &matcolor, NULL);CHKERRQ(ierr); 7897 ierr = PetscObjectQuery((PetscObject) B, "TSMatFDColoring", (PetscObject *) &color);CHKERRQ(ierr); 7898 if (!color) { 7899 DM dm; 7900 ISColoring iscoloring; 7901 7902 ierr = TSGetDM(ts, &dm);CHKERRQ(ierr); 7903 ierr = DMHasColoring(dm, &hascolor);CHKERRQ(ierr); 7904 if (hascolor && !matcolor) { 7905 ierr = DMCreateColoring(dm, IS_COLORING_GLOBAL, &iscoloring);CHKERRQ(ierr); 7906 ierr = MatFDColoringCreate(B, iscoloring, &color);CHKERRQ(ierr); 7907 ierr = MatFDColoringSetFunction(color, (PetscErrorCode (*)(void)) SNESTSFormFunction, (void *) ts);CHKERRQ(ierr); 7908 ierr = MatFDColoringSetFromOptions(color);CHKERRQ(ierr); 7909 ierr = MatFDColoringSetUp(B, iscoloring, color);CHKERRQ(ierr); 7910 ierr = ISColoringDestroy(&iscoloring);CHKERRQ(ierr); 7911 } else { 7912 MatColoring mc; 7913 7914 ierr = MatColoringCreate(B, &mc);CHKERRQ(ierr); 7915 ierr = MatColoringSetDistance(mc, 2);CHKERRQ(ierr); 7916 ierr = MatColoringSetType(mc, MATCOLORINGSL);CHKERRQ(ierr); 7917 ierr = MatColoringSetFromOptions(mc);CHKERRQ(ierr); 7918 ierr = MatColoringApply(mc, &iscoloring);CHKERRQ(ierr); 7919 ierr = MatColoringDestroy(&mc);CHKERRQ(ierr); 7920 ierr = MatFDColoringCreate(B, iscoloring, &color);CHKERRQ(ierr); 7921 ierr = MatFDColoringSetFunction(color, (PetscErrorCode (*)(void)) SNESTSFormFunction, (void *) ts);CHKERRQ(ierr); 7922 ierr = MatFDColoringSetFromOptions(color);CHKERRQ(ierr); 7923 ierr = MatFDColoringSetUp(B, iscoloring, color);CHKERRQ(ierr); 7924 ierr = ISColoringDestroy(&iscoloring);CHKERRQ(ierr); 7925 } 7926 ierr = PetscObjectCompose((PetscObject) B, "TSMatFDColoring", (PetscObject) color);CHKERRQ(ierr); 7927 ierr = PetscObjectDereference((PetscObject) color);CHKERRQ(ierr); 7928 } 7929 ierr = TSGetSNES(ts, &snes);CHKERRQ(ierr); 7930 ierr = MatFDColoringApply(B, color, U, snes);CHKERRQ(ierr); 7931 if (J != B) { 7932 ierr = MatAssemblyBegin(J, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 7933 ierr = MatAssemblyEnd(J, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 7934 } 7935 PetscFunctionReturn(0); 7936 } 7937 7938 /*@ 7939 TSSetFunctionDomainError - Set the function testing if the current state vector is valid 7940 7941 Input Parameters: 7942 ts - the TS context 7943 func - function called within TSFunctionDomainError 7944 7945 Level: intermediate 7946 7947 .keywords: TS, state, domain 7948 .seealso: TSAdaptCheckStage(), TSFunctionDomainError() 7949 @*/ 7950 7951 PetscErrorCode TSSetFunctionDomainError(TS ts, PetscErrorCode (*func)(TS,PetscReal,Vec,PetscBool*)) 7952 { 7953 PetscFunctionBegin; 7954 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 7955 ts->functiondomainerror = func; 7956 PetscFunctionReturn(0); 7957 } 7958 7959 /*@ 7960 TSFunctionDomainError - Check if the current state is valid 7961 7962 Input Parameters: 7963 ts - the TS context 7964 stagetime - time of the simulation 7965 Y - state vector to check. 7966 7967 Output Parameter: 7968 accept - Set to PETSC_FALSE if the current state vector is valid. 7969 7970 Note: 7971 This function should be used to ensure the state is in a valid part of the space. 7972 For example, one can ensure here all values are positive. 7973 7974 Level: advanced 7975 @*/ 7976 PetscErrorCode TSFunctionDomainError(TS ts,PetscReal stagetime,Vec Y,PetscBool* accept) 7977 { 7978 PetscErrorCode ierr; 7979 7980 PetscFunctionBegin; 7981 7982 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 7983 *accept = PETSC_TRUE; 7984 if (ts->functiondomainerror) { 7985 PetscStackCallStandard((*ts->functiondomainerror),(ts,stagetime,Y,accept)); 7986 } 7987 PetscFunctionReturn(0); 7988 } 7989 7990 /*@C 7991 TSClone - This function clones a time step object. 7992 7993 Collective on MPI_Comm 7994 7995 Input Parameter: 7996 . tsin - The input TS 7997 7998 Output Parameter: 7999 . tsout - The output TS (cloned) 8000 8001 Notes: 8002 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. 8003 8004 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); 8005 8006 Level: developer 8007 8008 .keywords: TS, clone 8009 .seealso: TSCreate(), TSSetType(), TSSetUp(), TSDestroy(), TSSetProblemType() 8010 @*/ 8011 PetscErrorCode TSClone(TS tsin, TS *tsout) 8012 { 8013 TS t; 8014 PetscErrorCode ierr; 8015 SNES snes_start; 8016 DM dm; 8017 TSType type; 8018 8019 PetscFunctionBegin; 8020 PetscValidPointer(tsin,1); 8021 *tsout = NULL; 8022 8023 ierr = PetscHeaderCreate(t, TS_CLASSID, "TS", "Time stepping", "TS", PetscObjectComm((PetscObject)tsin), TSDestroy, TSView);CHKERRQ(ierr); 8024 8025 /* General TS description */ 8026 t->numbermonitors = 0; 8027 t->setupcalled = 0; 8028 t->ksp_its = 0; 8029 t->snes_its = 0; 8030 t->nwork = 0; 8031 t->rhsjacobian.time = -1e20; 8032 t->rhsjacobian.scale = 1.; 8033 t->ijacobian.shift = 1.; 8034 8035 ierr = TSGetSNES(tsin,&snes_start);CHKERRQ(ierr); 8036 ierr = TSSetSNES(t,snes_start);CHKERRQ(ierr); 8037 8038 ierr = TSGetDM(tsin,&dm);CHKERRQ(ierr); 8039 ierr = TSSetDM(t,dm);CHKERRQ(ierr); 8040 8041 t->adapt = tsin->adapt; 8042 ierr = PetscObjectReference((PetscObject)t->adapt);CHKERRQ(ierr); 8043 8044 t->trajectory = tsin->trajectory; 8045 ierr = PetscObjectReference((PetscObject)t->trajectory);CHKERRQ(ierr); 8046 8047 t->event = tsin->event; 8048 if (t->event) t->event->refct++; 8049 8050 t->problem_type = tsin->problem_type; 8051 t->ptime = tsin->ptime; 8052 t->ptime_prev = tsin->ptime_prev; 8053 t->time_step = tsin->time_step; 8054 t->max_time = tsin->max_time; 8055 t->steps = tsin->steps; 8056 t->max_steps = tsin->max_steps; 8057 t->equation_type = tsin->equation_type; 8058 t->atol = tsin->atol; 8059 t->rtol = tsin->rtol; 8060 t->max_snes_failures = tsin->max_snes_failures; 8061 t->max_reject = tsin->max_reject; 8062 t->errorifstepfailed = tsin->errorifstepfailed; 8063 8064 ierr = TSGetType(tsin,&type);CHKERRQ(ierr); 8065 ierr = TSSetType(t,type);CHKERRQ(ierr); 8066 8067 t->vec_sol = NULL; 8068 8069 t->cfltime = tsin->cfltime; 8070 t->cfltime_local = tsin->cfltime_local; 8071 t->exact_final_time = tsin->exact_final_time; 8072 8073 ierr = PetscMemcpy(t->ops,tsin->ops,sizeof(struct _TSOps));CHKERRQ(ierr); 8074 8075 if (((PetscObject)tsin)->fortran_func_pointers) { 8076 PetscInt i; 8077 ierr = PetscMalloc((10)*sizeof(void(*)(void)),&((PetscObject)t)->fortran_func_pointers);CHKERRQ(ierr); 8078 for (i=0; i<10; i++) { 8079 ((PetscObject)t)->fortran_func_pointers[i] = ((PetscObject)tsin)->fortran_func_pointers[i]; 8080 } 8081 } 8082 *tsout = t; 8083 PetscFunctionReturn(0); 8084 } 8085