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 (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(). 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(). 2573 2574 Level: advanced 2575 2576 .keywords: TS, timestep, setup 2577 2578 .seealso: TSCreate(), TSStep(), TSDestroy() 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 .keywords: TS, timestep, set, sensitivity, initial values 3177 @*/ 3178 PetscErrorCode TSSetCostGradients(TS ts,PetscInt numcost,Vec *lambda,Vec *mu) 3179 { 3180 PetscFunctionBegin; 3181 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3182 PetscValidPointer(lambda,2); 3183 ts->vecs_sensi = lambda; 3184 ts->vecs_sensip = mu; 3185 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"); 3186 ts->numcost = numcost; 3187 PetscFunctionReturn(0); 3188 } 3189 3190 /*@C 3191 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. 3192 3193 Logically Collective on TS 3194 3195 Input Parameters: 3196 + ts - The TS context obtained from TSCreate() 3197 - func - The function 3198 3199 Calling sequence of func: 3200 $ func (TS ts,PetscReal t,Vec y,Mat A,void *ctx); 3201 + t - current timestep 3202 . y - input vector (current ODE solution) 3203 . A - output matrix 3204 - ctx - [optional] user-defined function context 3205 3206 Level: intermediate 3207 3208 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 3209 3210 .keywords: TS, sensitivity 3211 .seealso: 3212 @*/ 3213 PetscErrorCode TSAdjointSetRHSJacobian(TS ts,Mat Amat,PetscErrorCode (*func)(TS,PetscReal,Vec,Mat,void*),void *ctx) 3214 { 3215 PetscErrorCode ierr; 3216 3217 PetscFunctionBegin; 3218 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3219 PetscValidHeaderSpecific(Amat,MAT_CLASSID,2); 3220 3221 ts->rhsjacobianp = func; 3222 ts->rhsjacobianpctx = ctx; 3223 if(Amat) { 3224 ierr = PetscObjectReference((PetscObject)Amat);CHKERRQ(ierr); 3225 ierr = MatDestroy(&ts->Jacp);CHKERRQ(ierr); 3226 ts->Jacp = Amat; 3227 } 3228 PetscFunctionReturn(0); 3229 } 3230 3231 /*@C 3232 TSAdjointComputeRHSJacobian - Runs the user-defined Jacobian function. 3233 3234 Collective on TS 3235 3236 Input Parameters: 3237 . ts - The TS context obtained from TSCreate() 3238 3239 Level: developer 3240 3241 .keywords: TS, sensitivity 3242 .seealso: TSAdjointSetRHSJacobian() 3243 @*/ 3244 PetscErrorCode TSAdjointComputeRHSJacobian(TS ts,PetscReal t,Vec X,Mat Amat) 3245 { 3246 PetscErrorCode ierr; 3247 3248 PetscFunctionBegin; 3249 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3250 PetscValidHeaderSpecific(X,VEC_CLASSID,3); 3251 PetscValidPointer(Amat,4); 3252 3253 PetscStackPush("TS user JacobianP function for sensitivity analysis"); 3254 ierr = (*ts->rhsjacobianp)(ts,t,X,Amat,ts->rhsjacobianpctx); CHKERRQ(ierr); 3255 PetscStackPop; 3256 PetscFunctionReturn(0); 3257 } 3258 3259 /*@C 3260 TSSetCostIntegrand - Sets the routine for evaluating the integral term in one or more cost functions 3261 3262 Logically Collective on TS 3263 3264 Input Parameters: 3265 + ts - the TS context obtained from TSCreate() 3266 . numcost - number of gradients to be computed, this is the number of cost functions 3267 . costintegral - vector that stores the integral values 3268 . rf - routine for evaluating the integrand function 3269 . drdyf - function that computes the gradients of the r's with respect to y,NULL if not a function y 3270 . drdpf - function that computes the gradients of the r's with respect to p, NULL if not a function of p 3271 . fwd - flag indicating whether to evaluate cost integral in the forward run or the adjoint run 3272 - ctx - [optional] user-defined context for private data for the function evaluation routine (may be NULL) 3273 3274 Calling sequence of rf: 3275 $ PetscErrorCode rf(TS ts,PetscReal t,Vec y,Vec f,void *ctx); 3276 3277 Calling sequence of drdyf: 3278 $ PetscErroCode drdyf(TS ts,PetscReal t,Vec y,Vec *drdy,void *ctx); 3279 3280 Calling sequence of drdpf: 3281 $ PetscErroCode drdpf(TS ts,PetscReal t,Vec y,Vec *drdp,void *ctx); 3282 3283 Level: intermediate 3284 3285 Notes: For optimization there is usually a single cost function (numcost = 1). For sensitivities there may be multiple cost functions 3286 3287 .keywords: TS, sensitivity analysis, timestep, set, quadrature, function 3288 3289 .seealso: TSAdjointSetRHSJacobian(),TSGetCostGradients(), TSSetCostGradients() 3290 @*/ 3291 PetscErrorCode TSSetCostIntegrand(TS ts,PetscInt numcost,Vec costintegral,PetscErrorCode (*rf)(TS,PetscReal,Vec,Vec,void*), 3292 PetscErrorCode (*drdyf)(TS,PetscReal,Vec,Vec*,void*), 3293 PetscErrorCode (*drdpf)(TS,PetscReal,Vec,Vec*,void*), 3294 PetscBool fwd,void *ctx) 3295 { 3296 PetscErrorCode ierr; 3297 3298 PetscFunctionBegin; 3299 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3300 if (costintegral) PetscValidHeaderSpecific(costintegral,VEC_CLASSID,3); 3301 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()"); 3302 if (!ts->numcost) ts->numcost=numcost; 3303 3304 if (costintegral) { 3305 ierr = PetscObjectReference((PetscObject)costintegral);CHKERRQ(ierr); 3306 ierr = VecDestroy(&ts->vec_costintegral);CHKERRQ(ierr); 3307 ts->vec_costintegral = costintegral; 3308 } else { 3309 if (!ts->vec_costintegral) { /* Create a seq vec if user does not provide one */ 3310 ierr = VecCreateSeq(PETSC_COMM_SELF,numcost,&ts->vec_costintegral);CHKERRQ(ierr); 3311 } else { 3312 ierr = VecSet(ts->vec_costintegral,0.0);CHKERRQ(ierr); 3313 } 3314 } 3315 if (!ts->vec_costintegrand) { 3316 ierr = VecDuplicate(ts->vec_costintegral,&ts->vec_costintegrand);CHKERRQ(ierr); 3317 } else { 3318 ierr = VecSet(ts->vec_costintegrand,0.0);CHKERRQ(ierr); 3319 } 3320 ts->costintegralfwd = fwd; /* Evaluate the cost integral in forward run if fwd is true */ 3321 ts->costintegrand = rf; 3322 ts->costintegrandctx = ctx; 3323 ts->drdyfunction = drdyf; 3324 ts->drdpfunction = drdpf; 3325 PetscFunctionReturn(0); 3326 } 3327 3328 /*@ 3329 TSGetCostIntegral - Returns the values of the integral term in the cost functions. 3330 It is valid to call the routine after a backward run. 3331 3332 Not Collective 3333 3334 Input Parameter: 3335 . ts - the TS context obtained from TSCreate() 3336 3337 Output Parameter: 3338 . v - the vector containing the integrals for each cost function 3339 3340 Level: intermediate 3341 3342 .seealso: TSSetCostIntegrand() 3343 3344 .keywords: TS, sensitivity analysis 3345 @*/ 3346 PetscErrorCode TSGetCostIntegral(TS ts,Vec *v) 3347 { 3348 PetscFunctionBegin; 3349 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3350 PetscValidPointer(v,2); 3351 *v = ts->vec_costintegral; 3352 PetscFunctionReturn(0); 3353 } 3354 3355 /*@ 3356 TSComputeCostIntegrand - Evaluates the integral function in the cost functions. 3357 3358 Input Parameters: 3359 + ts - the TS context 3360 . t - current time 3361 - y - state vector, i.e. current solution 3362 3363 Output Parameter: 3364 . q - vector of size numcost to hold the outputs 3365 3366 Note: 3367 Most users should not need to explicitly call this routine, as it 3368 is used internally within the sensitivity analysis context. 3369 3370 Level: developer 3371 3372 .keywords: TS, compute 3373 3374 .seealso: TSSetCostIntegrand() 3375 @*/ 3376 PetscErrorCode TSComputeCostIntegrand(TS ts,PetscReal t,Vec y,Vec q) 3377 { 3378 PetscErrorCode ierr; 3379 3380 PetscFunctionBegin; 3381 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3382 PetscValidHeaderSpecific(y,VEC_CLASSID,3); 3383 PetscValidHeaderSpecific(q,VEC_CLASSID,4); 3384 3385 ierr = PetscLogEventBegin(TS_FunctionEval,ts,y,q,0);CHKERRQ(ierr); 3386 if (ts->costintegrand) { 3387 PetscStackPush("TS user integrand in the cost function"); 3388 ierr = (*ts->costintegrand)(ts,t,y,q,ts->costintegrandctx);CHKERRQ(ierr); 3389 PetscStackPop; 3390 } else { 3391 ierr = VecZeroEntries(q);CHKERRQ(ierr); 3392 } 3393 3394 ierr = PetscLogEventEnd(TS_FunctionEval,ts,y,q,0);CHKERRQ(ierr); 3395 PetscFunctionReturn(0); 3396 } 3397 3398 /*@ 3399 TSAdjointComputeDRDYFunction - Runs the user-defined DRDY function. 3400 3401 Collective on TS 3402 3403 Input Parameters: 3404 . ts - The TS context obtained from TSCreate() 3405 3406 Notes: 3407 TSAdjointComputeDRDYFunction() is typically used for sensitivity implementation, 3408 so most users would not generally call this routine themselves. 3409 3410 Level: developer 3411 3412 .keywords: TS, sensitivity 3413 .seealso: TSAdjointComputeDRDYFunction() 3414 @*/ 3415 PetscErrorCode TSAdjointComputeDRDYFunction(TS ts,PetscReal t,Vec y,Vec *drdy) 3416 { 3417 PetscErrorCode ierr; 3418 3419 PetscFunctionBegin; 3420 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3421 PetscValidHeaderSpecific(y,VEC_CLASSID,3); 3422 3423 PetscStackPush("TS user DRDY function for sensitivity analysis"); 3424 ierr = (*ts->drdyfunction)(ts,t,y,drdy,ts->costintegrandctx); CHKERRQ(ierr); 3425 PetscStackPop; 3426 PetscFunctionReturn(0); 3427 } 3428 3429 /*@ 3430 TSAdjointComputeDRDPFunction - Runs the user-defined DRDP function. 3431 3432 Collective on TS 3433 3434 Input Parameters: 3435 . ts - The TS context obtained from TSCreate() 3436 3437 Notes: 3438 TSDRDPFunction() is typically used for sensitivity implementation, 3439 so most users would not generally call this routine themselves. 3440 3441 Level: developer 3442 3443 .keywords: TS, sensitivity 3444 .seealso: TSAdjointSetDRDPFunction() 3445 @*/ 3446 PetscErrorCode TSAdjointComputeDRDPFunction(TS ts,PetscReal t,Vec y,Vec *drdp) 3447 { 3448 PetscErrorCode ierr; 3449 3450 PetscFunctionBegin; 3451 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3452 PetscValidHeaderSpecific(y,VEC_CLASSID,3); 3453 3454 PetscStackPush("TS user DRDP function for sensitivity analysis"); 3455 ierr = (*ts->drdpfunction)(ts,t,y,drdp,ts->costintegrandctx); CHKERRQ(ierr); 3456 PetscStackPop; 3457 PetscFunctionReturn(0); 3458 } 3459 3460 /*@C 3461 TSSetPreStep - Sets the general-purpose function 3462 called once at the beginning of each time step. 3463 3464 Logically Collective on TS 3465 3466 Input Parameters: 3467 + ts - The TS context obtained from TSCreate() 3468 - func - The function 3469 3470 Calling sequence of func: 3471 . func (TS ts); 3472 3473 Level: intermediate 3474 3475 .keywords: TS, timestep 3476 .seealso: TSSetPreStage(), TSSetPostStage(), TSSetPostStep(), TSStep(), TSRestartStep() 3477 @*/ 3478 PetscErrorCode TSSetPreStep(TS ts, PetscErrorCode (*func)(TS)) 3479 { 3480 PetscFunctionBegin; 3481 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3482 ts->prestep = func; 3483 PetscFunctionReturn(0); 3484 } 3485 3486 /*@ 3487 TSPreStep - Runs the user-defined pre-step function. 3488 3489 Collective on TS 3490 3491 Input Parameters: 3492 . ts - The TS context obtained from TSCreate() 3493 3494 Notes: 3495 TSPreStep() is typically used within time stepping implementations, 3496 so most users would not generally call this routine themselves. 3497 3498 Level: developer 3499 3500 .keywords: TS, timestep 3501 .seealso: TSSetPreStep(), TSPreStage(), TSPostStage(), TSPostStep() 3502 @*/ 3503 PetscErrorCode TSPreStep(TS ts) 3504 { 3505 PetscErrorCode ierr; 3506 3507 PetscFunctionBegin; 3508 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3509 if (ts->prestep) { 3510 Vec U; 3511 PetscObjectState sprev,spost; 3512 3513 ierr = TSGetSolution(ts,&U);CHKERRQ(ierr); 3514 ierr = PetscObjectStateGet((PetscObject)U,&sprev);CHKERRQ(ierr); 3515 PetscStackCallStandard((*ts->prestep),(ts)); 3516 ierr = PetscObjectStateGet((PetscObject)U,&spost);CHKERRQ(ierr); 3517 if (sprev != spost) {ierr = TSRestartStep(ts);CHKERRQ(ierr);} 3518 } 3519 PetscFunctionReturn(0); 3520 } 3521 3522 /*@C 3523 TSSetPreStage - Sets the general-purpose function 3524 called once at the beginning of each stage. 3525 3526 Logically Collective on TS 3527 3528 Input Parameters: 3529 + ts - The TS context obtained from TSCreate() 3530 - func - The function 3531 3532 Calling sequence of func: 3533 . PetscErrorCode func(TS ts, PetscReal stagetime); 3534 3535 Level: intermediate 3536 3537 Note: 3538 There may be several stages per time step. If the solve for a given stage fails, the step may be rejected and retried. 3539 The time step number being computed can be queried using TSGetStepNumber() and the total size of the step being 3540 attempted can be obtained using TSGetTimeStep(). The time at the start of the step is available via TSGetTime(). 3541 3542 .keywords: TS, timestep 3543 .seealso: TSSetPostStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext() 3544 @*/ 3545 PetscErrorCode TSSetPreStage(TS ts, PetscErrorCode (*func)(TS,PetscReal)) 3546 { 3547 PetscFunctionBegin; 3548 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3549 ts->prestage = func; 3550 PetscFunctionReturn(0); 3551 } 3552 3553 /*@C 3554 TSSetPostStage - Sets the general-purpose function 3555 called once at the end of each stage. 3556 3557 Logically Collective on TS 3558 3559 Input Parameters: 3560 + ts - The TS context obtained from TSCreate() 3561 - func - The function 3562 3563 Calling sequence of func: 3564 . PetscErrorCode func(TS ts, PetscReal stagetime, PetscInt stageindex, Vec* Y); 3565 3566 Level: intermediate 3567 3568 Note: 3569 There may be several stages per time step. If the solve for a given stage fails, the step may be rejected and retried. 3570 The time step number being computed can be queried using TSGetStepNumber() and the total size of the step being 3571 attempted can be obtained using TSGetTimeStep(). The time at the start of the step is available via TSGetTime(). 3572 3573 .keywords: TS, timestep 3574 .seealso: TSSetPreStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext() 3575 @*/ 3576 PetscErrorCode TSSetPostStage(TS ts, PetscErrorCode (*func)(TS,PetscReal,PetscInt,Vec*)) 3577 { 3578 PetscFunctionBegin; 3579 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3580 ts->poststage = func; 3581 PetscFunctionReturn(0); 3582 } 3583 3584 /*@C 3585 TSSetPostEvaluate - Sets the general-purpose function 3586 called once at the end of each step evaluation. 3587 3588 Logically Collective on TS 3589 3590 Input Parameters: 3591 + ts - The TS context obtained from TSCreate() 3592 - func - The function 3593 3594 Calling sequence of func: 3595 . PetscErrorCode func(TS ts); 3596 3597 Level: intermediate 3598 3599 Note: 3600 Semantically, TSSetPostEvaluate() differs from TSSetPostStep() since the function it sets is called before event-handling 3601 thus guaranteeing the same solution (computed by the time-stepper) will be passed to it. On the other hand, TSPostStep() 3602 may be passed a different solution, possibly changed by the event handler. TSPostEvaluate() is called after the next step 3603 solution is evaluated allowing to modify it, if need be. The solution can be obtained with TSGetSolution(), the time step 3604 with TSGetTimeStep(), and the time at the start of the step is available via TSGetTime() 3605 3606 .keywords: TS, timestep 3607 .seealso: TSSetPreStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext() 3608 @*/ 3609 PetscErrorCode TSSetPostEvaluate(TS ts, PetscErrorCode (*func)(TS)) 3610 { 3611 PetscFunctionBegin; 3612 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3613 ts->postevaluate = func; 3614 PetscFunctionReturn(0); 3615 } 3616 3617 /*@ 3618 TSPreStage - Runs the user-defined pre-stage function set using TSSetPreStage() 3619 3620 Collective on TS 3621 3622 Input Parameters: 3623 . ts - The TS context obtained from TSCreate() 3624 stagetime - The absolute time of the current stage 3625 3626 Notes: 3627 TSPreStage() is typically used within time stepping implementations, 3628 most users would not generally call this routine themselves. 3629 3630 Level: developer 3631 3632 .keywords: TS, timestep 3633 .seealso: TSPostStage(), TSSetPreStep(), TSPreStep(), TSPostStep() 3634 @*/ 3635 PetscErrorCode TSPreStage(TS ts, PetscReal stagetime) 3636 { 3637 PetscErrorCode ierr; 3638 3639 PetscFunctionBegin; 3640 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3641 if (ts->prestage) { 3642 PetscStackCallStandard((*ts->prestage),(ts,stagetime)); 3643 } 3644 PetscFunctionReturn(0); 3645 } 3646 3647 /*@ 3648 TSPostStage - Runs the user-defined post-stage function set using TSSetPostStage() 3649 3650 Collective on TS 3651 3652 Input Parameters: 3653 . ts - The TS context obtained from TSCreate() 3654 stagetime - The absolute time of the current stage 3655 stageindex - Stage number 3656 Y - Array of vectors (of size = total number 3657 of stages) with the stage solutions 3658 3659 Notes: 3660 TSPostStage() is typically used within time stepping implementations, 3661 most users would not generally call this routine themselves. 3662 3663 Level: developer 3664 3665 .keywords: TS, timestep 3666 .seealso: TSPreStage(), TSSetPreStep(), TSPreStep(), TSPostStep() 3667 @*/ 3668 PetscErrorCode TSPostStage(TS ts, PetscReal stagetime, PetscInt stageindex, Vec *Y) 3669 { 3670 PetscErrorCode ierr; 3671 3672 PetscFunctionBegin; 3673 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3674 if (ts->poststage) { 3675 PetscStackCallStandard((*ts->poststage),(ts,stagetime,stageindex,Y)); 3676 } 3677 PetscFunctionReturn(0); 3678 } 3679 3680 /*@ 3681 TSPostEvaluate - Runs the user-defined post-evaluate function set using TSSetPostEvaluate() 3682 3683 Collective on TS 3684 3685 Input Parameters: 3686 . ts - The TS context obtained from TSCreate() 3687 3688 Notes: 3689 TSPostEvaluate() is typically used within time stepping implementations, 3690 most users would not generally call this routine themselves. 3691 3692 Level: developer 3693 3694 .keywords: TS, timestep 3695 .seealso: TSSetPostEvaluate(), TSSetPreStep(), TSPreStep(), TSPostStep() 3696 @*/ 3697 PetscErrorCode TSPostEvaluate(TS ts) 3698 { 3699 PetscErrorCode ierr; 3700 3701 PetscFunctionBegin; 3702 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3703 if (ts->postevaluate) { 3704 Vec U; 3705 PetscObjectState sprev,spost; 3706 3707 ierr = TSGetSolution(ts,&U);CHKERRQ(ierr); 3708 ierr = PetscObjectStateGet((PetscObject)U,&sprev);CHKERRQ(ierr); 3709 PetscStackCallStandard((*ts->postevaluate),(ts)); 3710 ierr = PetscObjectStateGet((PetscObject)U,&spost);CHKERRQ(ierr); 3711 if (sprev != spost) {ierr = TSRestartStep(ts);CHKERRQ(ierr);} 3712 } 3713 PetscFunctionReturn(0); 3714 } 3715 3716 /*@C 3717 TSSetPostStep - Sets the general-purpose function 3718 called once at the end of each time step. 3719 3720 Logically Collective on TS 3721 3722 Input Parameters: 3723 + ts - The TS context obtained from TSCreate() 3724 - func - The function 3725 3726 Calling sequence of func: 3727 $ func (TS ts); 3728 3729 Notes: 3730 The function set by TSSetPostStep() is called after each successful step. The solution vector X 3731 obtained by TSGetSolution() may be different than that computed at the step end if the event handler 3732 locates an event and TSPostEvent() modifies it. Use TSSetPostEvaluate() if an unmodified solution is needed instead. 3733 3734 Level: intermediate 3735 3736 .keywords: TS, timestep 3737 .seealso: TSSetPreStep(), TSSetPreStage(), TSSetPostEvaluate(), TSGetTimeStep(), TSGetStepNumber(), TSGetTime(), TSRestartStep() 3738 @*/ 3739 PetscErrorCode TSSetPostStep(TS ts, PetscErrorCode (*func)(TS)) 3740 { 3741 PetscFunctionBegin; 3742 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3743 ts->poststep = func; 3744 PetscFunctionReturn(0); 3745 } 3746 3747 /*@ 3748 TSPostStep - Runs the user-defined post-step function. 3749 3750 Collective on TS 3751 3752 Input Parameters: 3753 . ts - The TS context obtained from TSCreate() 3754 3755 Notes: 3756 TSPostStep() is typically used within time stepping implementations, 3757 so most users would not generally call this routine themselves. 3758 3759 Level: developer 3760 3761 .keywords: TS, timestep 3762 @*/ 3763 PetscErrorCode TSPostStep(TS ts) 3764 { 3765 PetscErrorCode ierr; 3766 3767 PetscFunctionBegin; 3768 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3769 if (ts->poststep) { 3770 Vec U; 3771 PetscObjectState sprev,spost; 3772 3773 ierr = TSGetSolution(ts,&U);CHKERRQ(ierr); 3774 ierr = PetscObjectStateGet((PetscObject)U,&sprev);CHKERRQ(ierr); 3775 PetscStackCallStandard((*ts->poststep),(ts)); 3776 ierr = PetscObjectStateGet((PetscObject)U,&spost);CHKERRQ(ierr); 3777 if (sprev != spost) {ierr = TSRestartStep(ts);CHKERRQ(ierr);} 3778 } 3779 PetscFunctionReturn(0); 3780 } 3781 3782 /* ------------ Routines to set performance monitoring options ----------- */ 3783 3784 /*@C 3785 TSMonitorSet - Sets an ADDITIONAL function that is to be used at every 3786 timestep to display the iteration's progress. 3787 3788 Logically Collective on TS 3789 3790 Input Parameters: 3791 + ts - the TS context obtained from TSCreate() 3792 . monitor - monitoring routine 3793 . mctx - [optional] user-defined context for private data for the 3794 monitor routine (use NULL if no context is desired) 3795 - monitordestroy - [optional] routine that frees monitor context 3796 (may be NULL) 3797 3798 Calling sequence of monitor: 3799 $ PetscErrorCode monitor(TS ts,PetscInt steps,PetscReal time,Vec u,void *mctx) 3800 3801 + ts - the TS context 3802 . 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) 3803 . time - current time 3804 . u - current iterate 3805 - mctx - [optional] monitoring context 3806 3807 Notes: 3808 This routine adds an additional monitor to the list of monitors that 3809 already has been loaded. 3810 3811 Fortran notes: Only a single monitor function can be set for each TS object 3812 3813 Level: intermediate 3814 3815 .keywords: TS, timestep, set, monitor 3816 3817 .seealso: TSMonitorDefault(), TSMonitorCancel() 3818 @*/ 3819 PetscErrorCode TSMonitorSet(TS ts,PetscErrorCode (*monitor)(TS,PetscInt,PetscReal,Vec,void*),void *mctx,PetscErrorCode (*mdestroy)(void**)) 3820 { 3821 PetscErrorCode ierr; 3822 PetscInt i; 3823 PetscBool identical; 3824 3825 PetscFunctionBegin; 3826 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3827 for (i=0; i<ts->numbermonitors;i++) { 3828 ierr = PetscMonitorCompare((PetscErrorCode (*)(void))monitor,mctx,mdestroy,(PetscErrorCode (*)(void))ts->monitor[i],ts->monitorcontext[i],ts->monitordestroy[i],&identical);CHKERRQ(ierr); 3829 if (identical) PetscFunctionReturn(0); 3830 } 3831 if (ts->numbermonitors >= MAXTSMONITORS) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Too many monitors set"); 3832 ts->monitor[ts->numbermonitors] = monitor; 3833 ts->monitordestroy[ts->numbermonitors] = mdestroy; 3834 ts->monitorcontext[ts->numbermonitors++] = (void*)mctx; 3835 PetscFunctionReturn(0); 3836 } 3837 3838 /*@C 3839 TSMonitorCancel - Clears all the monitors that have been set on a time-step object. 3840 3841 Logically Collective on TS 3842 3843 Input Parameters: 3844 . ts - the TS context obtained from TSCreate() 3845 3846 Notes: 3847 There is no way to remove a single, specific monitor. 3848 3849 Level: intermediate 3850 3851 .keywords: TS, timestep, set, monitor 3852 3853 .seealso: TSMonitorDefault(), TSMonitorSet() 3854 @*/ 3855 PetscErrorCode TSMonitorCancel(TS ts) 3856 { 3857 PetscErrorCode ierr; 3858 PetscInt i; 3859 3860 PetscFunctionBegin; 3861 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3862 for (i=0; i<ts->numbermonitors; i++) { 3863 if (ts->monitordestroy[i]) { 3864 ierr = (*ts->monitordestroy[i])(&ts->monitorcontext[i]);CHKERRQ(ierr); 3865 } 3866 } 3867 ts->numbermonitors = 0; 3868 PetscFunctionReturn(0); 3869 } 3870 3871 /*@C 3872 TSMonitorDefault - The Default monitor, prints the timestep and time for each step 3873 3874 Level: intermediate 3875 3876 .keywords: TS, set, monitor 3877 3878 .seealso: TSMonitorSet() 3879 @*/ 3880 PetscErrorCode TSMonitorDefault(TS ts,PetscInt step,PetscReal ptime,Vec v,PetscViewerAndFormat *vf) 3881 { 3882 PetscErrorCode ierr; 3883 PetscViewer viewer = vf->viewer; 3884 PetscBool iascii,ibinary; 3885 3886 PetscFunctionBegin; 3887 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,4); 3888 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 3889 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&ibinary);CHKERRQ(ierr); 3890 ierr = PetscViewerPushFormat(viewer,vf->format);CHKERRQ(ierr); 3891 if (iascii) { 3892 ierr = PetscViewerASCIIAddTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 3893 if (step == -1){ /* this indicates it is an interpolated solution */ 3894 ierr = PetscViewerASCIIPrintf(viewer,"Interpolated solution at time %g between steps %D and %D\n",(double)ptime,ts->steps-1,ts->steps);CHKERRQ(ierr); 3895 } else { 3896 ierr = PetscViewerASCIIPrintf(viewer,"%D TS dt %g time %g%s",step,(double)ts->time_step,(double)ptime,ts->steprollback ? " (r)\n" : "\n");CHKERRQ(ierr); 3897 } 3898 ierr = PetscViewerASCIISubtractTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 3899 } else if (ibinary) { 3900 PetscMPIInt rank; 3901 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)viewer),&rank);CHKERRQ(ierr); 3902 if (!rank) { 3903 PetscBool skipHeader; 3904 PetscInt classid = REAL_FILE_CLASSID; 3905 3906 ierr = PetscViewerBinaryGetSkipHeader(viewer,&skipHeader);CHKERRQ(ierr); 3907 if (!skipHeader) { 3908 ierr = PetscViewerBinaryWrite(viewer,&classid,1,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); 3909 } 3910 ierr = PetscRealView(1,&ptime,viewer);CHKERRQ(ierr); 3911 } else { 3912 ierr = PetscRealView(0,&ptime,viewer);CHKERRQ(ierr); 3913 } 3914 } 3915 ierr = PetscViewerPopFormat(viewer);CHKERRQ(ierr); 3916 PetscFunctionReturn(0); 3917 } 3918 3919 /*@C 3920 TSAdjointMonitorSet - Sets an ADDITIONAL function that is to be used at every 3921 timestep to display the iteration's progress. 3922 3923 Logically Collective on TS 3924 3925 Input Parameters: 3926 + ts - the TS context obtained from TSCreate() 3927 . adjointmonitor - monitoring routine 3928 . adjointmctx - [optional] user-defined context for private data for the 3929 monitor routine (use NULL if no context is desired) 3930 - adjointmonitordestroy - [optional] routine that frees monitor context 3931 (may be NULL) 3932 3933 Calling sequence of monitor: 3934 $ int adjointmonitor(TS ts,PetscInt steps,PetscReal time,Vec u,PetscInt numcost,Vec *lambda, Vec *mu,void *adjointmctx) 3935 3936 + ts - the TS context 3937 . 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 3938 been interpolated to) 3939 . time - current time 3940 . u - current iterate 3941 . numcost - number of cost functionos 3942 . lambda - sensitivities to initial conditions 3943 . mu - sensitivities to parameters 3944 - adjointmctx - [optional] adjoint monitoring context 3945 3946 Notes: 3947 This routine adds an additional monitor to the list of monitors that 3948 already has been loaded. 3949 3950 Fortran notes: Only a single monitor function can be set for each TS object 3951 3952 Level: intermediate 3953 3954 .keywords: TS, timestep, set, adjoint, monitor 3955 3956 .seealso: TSAdjointMonitorCancel() 3957 @*/ 3958 PetscErrorCode TSAdjointMonitorSet(TS ts,PetscErrorCode (*adjointmonitor)(TS,PetscInt,PetscReal,Vec,PetscInt,Vec*,Vec*,void*),void *adjointmctx,PetscErrorCode (*adjointmdestroy)(void**)) 3959 { 3960 PetscErrorCode ierr; 3961 PetscInt i; 3962 PetscBool identical; 3963 3964 PetscFunctionBegin; 3965 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3966 for (i=0; i<ts->numbermonitors;i++) { 3967 ierr = PetscMonitorCompare((PetscErrorCode (*)(void))adjointmonitor,adjointmctx,adjointmdestroy,(PetscErrorCode (*)(void))ts->adjointmonitor[i],ts->adjointmonitorcontext[i],ts->adjointmonitordestroy[i],&identical);CHKERRQ(ierr); 3968 if (identical) PetscFunctionReturn(0); 3969 } 3970 if (ts->numberadjointmonitors >= MAXTSMONITORS) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Too many adjoint monitors set"); 3971 ts->adjointmonitor[ts->numberadjointmonitors] = adjointmonitor; 3972 ts->adjointmonitordestroy[ts->numberadjointmonitors] = adjointmdestroy; 3973 ts->adjointmonitorcontext[ts->numberadjointmonitors++] = (void*)adjointmctx; 3974 PetscFunctionReturn(0); 3975 } 3976 3977 /*@C 3978 TSAdjointMonitorCancel - Clears all the adjoint monitors that have been set on a time-step object. 3979 3980 Logically Collective on TS 3981 3982 Input Parameters: 3983 . ts - the TS context obtained from TSCreate() 3984 3985 Notes: 3986 There is no way to remove a single, specific monitor. 3987 3988 Level: intermediate 3989 3990 .keywords: TS, timestep, set, adjoint, monitor 3991 3992 .seealso: TSAdjointMonitorSet() 3993 @*/ 3994 PetscErrorCode TSAdjointMonitorCancel(TS ts) 3995 { 3996 PetscErrorCode ierr; 3997 PetscInt i; 3998 3999 PetscFunctionBegin; 4000 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4001 for (i=0; i<ts->numberadjointmonitors; i++) { 4002 if (ts->adjointmonitordestroy[i]) { 4003 ierr = (*ts->adjointmonitordestroy[i])(&ts->adjointmonitorcontext[i]);CHKERRQ(ierr); 4004 } 4005 } 4006 ts->numberadjointmonitors = 0; 4007 PetscFunctionReturn(0); 4008 } 4009 4010 /*@C 4011 TSAdjointMonitorDefault - the default monitor of adjoint computations 4012 4013 Level: intermediate 4014 4015 .keywords: TS, set, monitor 4016 4017 .seealso: TSAdjointMonitorSet() 4018 @*/ 4019 PetscErrorCode TSAdjointMonitorDefault(TS ts,PetscInt step,PetscReal ptime,Vec v,PetscInt numcost,Vec *lambda,Vec *mu,PetscViewerAndFormat *vf) 4020 { 4021 PetscErrorCode ierr; 4022 PetscViewer viewer = vf->viewer; 4023 4024 PetscFunctionBegin; 4025 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,4); 4026 ierr = PetscViewerPushFormat(viewer,vf->format);CHKERRQ(ierr); 4027 ierr = PetscViewerASCIIAddTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 4028 ierr = PetscViewerASCIIPrintf(viewer,"%D TS dt %g time %g%s",step,(double)ts->time_step,(double)ptime,ts->steprollback ? " (r)\n" : "\n");CHKERRQ(ierr); 4029 ierr = PetscViewerASCIISubtractTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 4030 ierr = PetscViewerPopFormat(viewer);CHKERRQ(ierr); 4031 PetscFunctionReturn(0); 4032 } 4033 4034 /*@ 4035 TSInterpolate - Interpolate the solution computed during the previous step to an arbitrary location in the interval 4036 4037 Collective on TS 4038 4039 Input Argument: 4040 + ts - time stepping context 4041 - t - time to interpolate to 4042 4043 Output Argument: 4044 . U - state at given time 4045 4046 Level: intermediate 4047 4048 Developer Notes: 4049 TSInterpolate() and the storing of previous steps/stages should be generalized to support delay differential equations and continuous adjoints. 4050 4051 .keywords: TS, set 4052 4053 .seealso: TSSetExactFinalTime(), TSSolve() 4054 @*/ 4055 PetscErrorCode TSInterpolate(TS ts,PetscReal t,Vec U) 4056 { 4057 PetscErrorCode ierr; 4058 4059 PetscFunctionBegin; 4060 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4061 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 4062 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); 4063 if (!ts->ops->interpolate) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"%s does not provide interpolation",((PetscObject)ts)->type_name); 4064 ierr = (*ts->ops->interpolate)(ts,t,U);CHKERRQ(ierr); 4065 PetscFunctionReturn(0); 4066 } 4067 4068 /*@ 4069 TSStep - Steps one time step 4070 4071 Collective on TS 4072 4073 Input Parameter: 4074 . ts - the TS context obtained from TSCreate() 4075 4076 Level: developer 4077 4078 Notes: 4079 The public interface for the ODE/DAE solvers is TSSolve(), you should almost for sure be using that routine and not this routine. 4080 4081 The hook set using TSSetPreStep() is called before each attempt to take the step. In general, the time step size may 4082 be changed due to adaptive error controller or solve failures. Note that steps may contain multiple stages. 4083 4084 This may over-step the final time provided in TSSetMaxTime() depending on the time-step used. TSSolve() interpolates to exactly the 4085 time provided in TSSetMaxTime(). One can use TSInterpolate() to determine an interpolated solution within the final timestep. 4086 4087 .keywords: TS, timestep, solve 4088 4089 .seealso: TSCreate(), TSSetUp(), TSDestroy(), TSSolve(), TSSetPreStep(), TSSetPreStage(), TSSetPostStage(), TSInterpolate() 4090 @*/ 4091 PetscErrorCode TSStep(TS ts) 4092 { 4093 PetscErrorCode ierr; 4094 static PetscBool cite = PETSC_FALSE; 4095 PetscReal ptime; 4096 4097 PetscFunctionBegin; 4098 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4099 ierr = PetscCitationsRegister("@techreport{tspaper,\n" 4100 " title = {{PETSc/TS}: A Modern Scalable {DAE/ODE} Solver Library},\n" 4101 " author = {Shrirang Abhyankar and Jed Brown and Emil Constantinescu and Debojyoti Ghosh and Barry F. Smith},\n" 4102 " type = {Preprint},\n" 4103 " number = {ANL/MCS-P5061-0114},\n" 4104 " institution = {Argonne National Laboratory},\n" 4105 " year = {2014}\n}\n",&cite);CHKERRQ(ierr); 4106 4107 ierr = TSSetUp(ts);CHKERRQ(ierr); 4108 ierr = TSTrajectorySetUp(ts->trajectory,ts);CHKERRQ(ierr); 4109 4110 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>"); 4111 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()"); 4112 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"); 4113 4114 if (!ts->steps) ts->ptime_prev = ts->ptime; 4115 ptime = ts->ptime; ts->ptime_prev_rollback = ts->ptime_prev; 4116 ts->reason = TS_CONVERGED_ITERATING; 4117 if (!ts->ops->step) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSStep not implemented for type '%s'",((PetscObject)ts)->type_name); 4118 ierr = PetscLogEventBegin(TS_Step,ts,0,0,0);CHKERRQ(ierr); 4119 ierr = (*ts->ops->step)(ts);CHKERRQ(ierr); 4120 ierr = PetscLogEventEnd(TS_Step,ts,0,0,0);CHKERRQ(ierr); 4121 ts->ptime_prev = ptime; 4122 ts->steps++; 4123 ts->steprollback = PETSC_FALSE; 4124 ts->steprestart = PETSC_FALSE; 4125 4126 if (ts->reason < 0) { 4127 if (ts->errorifstepfailed) { 4128 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]); 4129 else SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s",TSConvergedReasons[ts->reason]); 4130 } 4131 } else if (!ts->reason) { 4132 if (ts->steps >= ts->max_steps) ts->reason = TS_CONVERGED_ITS; 4133 else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME; 4134 } 4135 PetscFunctionReturn(0); 4136 } 4137 4138 /*@ 4139 TSAdjointStep - Steps one time step backward in the adjoint run 4140 4141 Collective on TS 4142 4143 Input Parameter: 4144 . ts - the TS context obtained from TSCreate() 4145 4146 Level: intermediate 4147 4148 .keywords: TS, adjoint, step 4149 4150 .seealso: TSAdjointSetUp(), TSAdjointSolve() 4151 @*/ 4152 PetscErrorCode TSAdjointStep(TS ts) 4153 { 4154 DM dm; 4155 PetscErrorCode ierr; 4156 4157 PetscFunctionBegin; 4158 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4159 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 4160 ierr = TSAdjointSetUp(ts);CHKERRQ(ierr); 4161 4162 ierr = VecViewFromOptions(ts->vec_sol,(PetscObject)ts,"-ts_view_solution");CHKERRQ(ierr); 4163 4164 ts->reason = TS_CONVERGED_ITERATING; 4165 ts->ptime_prev = ts->ptime; 4166 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); 4167 ierr = PetscLogEventBegin(TS_AdjointStep,ts,0,0,0);CHKERRQ(ierr); 4168 ierr = (*ts->ops->adjointstep)(ts);CHKERRQ(ierr); 4169 ierr = PetscLogEventEnd(TS_AdjointStep,ts,0,0,0);CHKERRQ(ierr); 4170 ts->adjoint_steps++; ts->steps--; 4171 4172 if (ts->reason < 0) { 4173 if (ts->errorifstepfailed) { 4174 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]); 4175 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]); 4176 else SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s",TSConvergedReasons[ts->reason]); 4177 } 4178 } else if (!ts->reason) { 4179 if (ts->adjoint_steps >= ts->adjoint_max_steps) ts->reason = TS_CONVERGED_ITS; 4180 } 4181 PetscFunctionReturn(0); 4182 } 4183 4184 /*@ 4185 TSEvaluateWLTE - Evaluate the weighted local truncation error norm 4186 at the end of a time step with a given order of accuracy. 4187 4188 Collective on TS 4189 4190 Input Arguments: 4191 + ts - time stepping context 4192 . wnormtype - norm type, either NORM_2 or NORM_INFINITY 4193 - order - optional, desired order for the error evaluation or PETSC_DECIDE 4194 4195 Output Arguments: 4196 + order - optional, the actual order of the error evaluation 4197 - wlte - the weighted local truncation error norm 4198 4199 Level: advanced 4200 4201 Notes: 4202 If the timestepper cannot evaluate the error in a particular step 4203 (eg. in the first step or restart steps after event handling), 4204 this routine returns wlte=-1.0 . 4205 4206 .seealso: TSStep(), TSAdapt, TSErrorWeightedNorm() 4207 @*/ 4208 PetscErrorCode TSEvaluateWLTE(TS ts,NormType wnormtype,PetscInt *order,PetscReal *wlte) 4209 { 4210 PetscErrorCode ierr; 4211 4212 PetscFunctionBegin; 4213 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4214 PetscValidType(ts,1); 4215 PetscValidLogicalCollectiveEnum(ts,wnormtype,4); 4216 if (order) PetscValidIntPointer(order,3); 4217 if (order) PetscValidLogicalCollectiveInt(ts,*order,3); 4218 PetscValidRealPointer(wlte,4); 4219 if (wnormtype != NORM_2 && wnormtype != NORM_INFINITY) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]); 4220 if (!ts->ops->evaluatewlte) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSEvaluateWLTE not implemented for type '%s'",((PetscObject)ts)->type_name); 4221 ierr = (*ts->ops->evaluatewlte)(ts,wnormtype,order,wlte);CHKERRQ(ierr); 4222 PetscFunctionReturn(0); 4223 } 4224 4225 /*@ 4226 TSEvaluateStep - Evaluate the solution at the end of a time step with a given order of accuracy. 4227 4228 Collective on TS 4229 4230 Input Arguments: 4231 + ts - time stepping context 4232 . order - desired order of accuracy 4233 - done - whether the step was evaluated at this order (pass NULL to generate an error if not available) 4234 4235 Output Arguments: 4236 . U - state at the end of the current step 4237 4238 Level: advanced 4239 4240 Notes: 4241 This function cannot be called until all stages have been evaluated. 4242 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. 4243 4244 .seealso: TSStep(), TSAdapt 4245 @*/ 4246 PetscErrorCode TSEvaluateStep(TS ts,PetscInt order,Vec U,PetscBool *done) 4247 { 4248 PetscErrorCode ierr; 4249 4250 PetscFunctionBegin; 4251 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4252 PetscValidType(ts,1); 4253 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 4254 if (!ts->ops->evaluatestep) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSEvaluateStep not implemented for type '%s'",((PetscObject)ts)->type_name); 4255 ierr = (*ts->ops->evaluatestep)(ts,order,U,done);CHKERRQ(ierr); 4256 PetscFunctionReturn(0); 4257 } 4258 4259 /*@ 4260 TSForwardCostIntegral - Evaluate the cost integral in the forward run. 4261 4262 Collective on TS 4263 4264 Input Arguments: 4265 . ts - time stepping context 4266 4267 Level: advanced 4268 4269 Notes: 4270 This function cannot be called until TSStep() has been completed. 4271 4272 .seealso: TSSolve(), TSAdjointCostIntegral() 4273 @*/ 4274 PetscErrorCode TSForwardCostIntegral(TS ts) 4275 { 4276 PetscErrorCode ierr; 4277 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4278 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); 4279 ierr = (*ts->ops->forwardintegral)(ts);CHKERRQ(ierr); 4280 PetscFunctionReturn(0); 4281 } 4282 4283 /*@ 4284 TSSolve - Steps the requested number of timesteps. 4285 4286 Collective on TS 4287 4288 Input Parameter: 4289 + ts - the TS context obtained from TSCreate() 4290 - u - the solution vector (can be null if TSSetSolution() was used and TSSetExactFinalTime(ts,TS_EXACTFINALTIME_MATCHSTEP) was not used, 4291 otherwise must contain the initial conditions and will contain the solution at the final requested time 4292 4293 Level: beginner 4294 4295 Notes: 4296 The final time returned by this function may be different from the time of the internally 4297 held state accessible by TSGetSolution() and TSGetTime() because the method may have 4298 stepped over the final time. 4299 4300 .keywords: TS, timestep, solve 4301 4302 .seealso: TSCreate(), TSSetSolution(), TSStep(), TSGetTime(), TSGetSolveTime() 4303 @*/ 4304 PetscErrorCode TSSolve(TS ts,Vec u) 4305 { 4306 Vec solution; 4307 PetscErrorCode ierr; 4308 4309 PetscFunctionBegin; 4310 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4311 if (u) PetscValidHeaderSpecific(u,VEC_CLASSID,2); 4312 4313 if (ts->exact_final_time == TS_EXACTFINALTIME_INTERPOLATE) { /* Need ts->vec_sol to be distinct so it is not overwritten when we interpolate at the end */ 4314 PetscValidHeaderSpecific(u,VEC_CLASSID,2); 4315 if (!ts->vec_sol || u == ts->vec_sol) { 4316 ierr = VecDuplicate(u,&solution);CHKERRQ(ierr); 4317 ierr = TSSetSolution(ts,solution);CHKERRQ(ierr); 4318 ierr = VecDestroy(&solution);CHKERRQ(ierr); /* grant ownership */ 4319 } 4320 ierr = VecCopy(u,ts->vec_sol);CHKERRQ(ierr); 4321 if (ts->forward_solve) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Sensitivity analysis does not support the mode TS_EXACTFINALTIME_INTERPOLATE"); 4322 } else if (u) { 4323 ierr = TSSetSolution(ts,u);CHKERRQ(ierr); 4324 } 4325 ierr = TSSetUp(ts);CHKERRQ(ierr); 4326 ierr = TSTrajectorySetUp(ts->trajectory,ts);CHKERRQ(ierr); 4327 4328 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>"); 4329 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()"); 4330 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"); 4331 4332 if (ts->forward_solve) { 4333 ierr = TSForwardSetUp(ts);CHKERRQ(ierr); 4334 } 4335 4336 /* reset number of steps only when the step is not restarted. ARKIMEX 4337 restarts the step after an event. Resetting these counters in such case causes 4338 TSTrajectory to incorrectly save the output files 4339 */ 4340 /* reset time step and iteration counters */ 4341 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 ts->reason = TS_CONVERGED_ITERATING; 4351 4352 ierr = TSViewFromOptions(ts,NULL,"-ts_view_pre");CHKERRQ(ierr); 4353 4354 if (ts->ops->solve) { /* This private interface is transitional and should be removed when all implementations are updated. */ 4355 ierr = (*ts->ops->solve)(ts);CHKERRQ(ierr); 4356 if (u) {ierr = VecCopy(ts->vec_sol,u);CHKERRQ(ierr);} 4357 ts->solvetime = ts->ptime; 4358 solution = ts->vec_sol; 4359 } else { /* Step the requested number of timesteps. */ 4360 if (ts->steps >= ts->max_steps) ts->reason = TS_CONVERGED_ITS; 4361 else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME; 4362 4363 if (!ts->steps) { 4364 ierr = TSTrajectorySet(ts->trajectory,ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 4365 ierr = TSEventInitialize(ts->event,ts,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 4366 } 4367 4368 while (!ts->reason) { 4369 ierr = TSMonitor(ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 4370 if (!ts->steprollback) { 4371 ierr = TSPreStep(ts);CHKERRQ(ierr); 4372 } 4373 ierr = TSStep(ts);CHKERRQ(ierr); 4374 if (ts->vec_costintegral && ts->costintegralfwd) { /* Must evaluate the cost integral before event is handled. The cost integral value can also be rolled back. */ 4375 ierr = TSForwardCostIntegral(ts);CHKERRQ(ierr); 4376 } 4377 if (ts->forward_solve) { /* compute forward sensitivities before event handling because postevent() may change RHS and jump conditions may have to be applied */ 4378 ierr = TSForwardStep(ts);CHKERRQ(ierr); 4379 } 4380 ierr = TSPostEvaluate(ts);CHKERRQ(ierr); 4381 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. */ 4382 if (ts->steprollback) { 4383 ierr = TSPostEvaluate(ts);CHKERRQ(ierr); 4384 } 4385 if (!ts->steprollback) { 4386 ierr = TSTrajectorySet(ts->trajectory,ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 4387 ierr = TSPostStep(ts);CHKERRQ(ierr); 4388 } 4389 } 4390 ierr = TSMonitor(ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 4391 4392 if (ts->exact_final_time == TS_EXACTFINALTIME_INTERPOLATE && ts->ptime > ts->max_time) { 4393 ierr = TSInterpolate(ts,ts->max_time,u);CHKERRQ(ierr); 4394 ts->solvetime = ts->max_time; 4395 solution = u; 4396 ierr = TSMonitor(ts,-1,ts->solvetime,solution);CHKERRQ(ierr); 4397 } else { 4398 if (u) {ierr = VecCopy(ts->vec_sol,u);CHKERRQ(ierr);} 4399 ts->solvetime = ts->ptime; 4400 solution = ts->vec_sol; 4401 } 4402 } 4403 4404 ierr = TSViewFromOptions(ts,NULL,"-ts_view");CHKERRQ(ierr); 4405 ierr = VecViewFromOptions(solution,NULL,"-ts_view_solution");CHKERRQ(ierr); 4406 ierr = PetscObjectSAWsBlock((PetscObject)ts);CHKERRQ(ierr); 4407 if (ts->adjoint_solve) { 4408 ierr = TSAdjointSolve(ts);CHKERRQ(ierr); 4409 } 4410 PetscFunctionReturn(0); 4411 } 4412 4413 /*@ 4414 TSAdjointCostIntegral - Evaluate the cost integral in the adjoint run. 4415 4416 Collective on TS 4417 4418 Input Arguments: 4419 . ts - time stepping context 4420 4421 Level: advanced 4422 4423 Notes: 4424 This function cannot be called until TSAdjointStep() has been completed. 4425 4426 .seealso: TSAdjointSolve(), TSAdjointStep 4427 @*/ 4428 PetscErrorCode TSAdjointCostIntegral(TS ts) 4429 { 4430 PetscErrorCode ierr; 4431 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4432 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); 4433 ierr = (*ts->ops->adjointintegral)(ts);CHKERRQ(ierr); 4434 PetscFunctionReturn(0); 4435 } 4436 4437 /*@ 4438 TSAdjointSolve - Solves the discrete ajoint problem for an ODE/DAE 4439 4440 Collective on TS 4441 4442 Input Parameter: 4443 . ts - the TS context obtained from TSCreate() 4444 4445 Options Database: 4446 . -ts_adjoint_view_solution <viewerinfo> - views the first gradient with respect to the initial values 4447 4448 Level: intermediate 4449 4450 Notes: 4451 This must be called after a call to TSSolve() that solves the forward problem 4452 4453 By default this will integrate back to the initial time, one can use TSAdjointSetSteps() to step back to a later time 4454 4455 .keywords: TS, timestep, solve 4456 4457 .seealso: TSCreate(), TSSetCostGradients(), TSSetSolution(), TSAdjointStep() 4458 @*/ 4459 PetscErrorCode TSAdjointSolve(TS ts) 4460 { 4461 PetscErrorCode ierr; 4462 4463 PetscFunctionBegin; 4464 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4465 ierr = TSAdjointSetUp(ts);CHKERRQ(ierr); 4466 4467 /* reset time step and iteration counters */ 4468 ts->adjoint_steps = 0; 4469 ts->ksp_its = 0; 4470 ts->snes_its = 0; 4471 ts->num_snes_failures = 0; 4472 ts->reject = 0; 4473 ts->reason = TS_CONVERGED_ITERATING; 4474 4475 if (!ts->adjoint_max_steps) ts->adjoint_max_steps = ts->steps; 4476 if (ts->adjoint_steps >= ts->adjoint_max_steps) ts->reason = TS_CONVERGED_ITS; 4477 4478 while (!ts->reason) { 4479 ierr = TSTrajectoryGet(ts->trajectory,ts,ts->steps,&ts->ptime);CHKERRQ(ierr); 4480 ierr = TSAdjointMonitor(ts,ts->steps,ts->ptime,ts->vec_sol,ts->numcost,ts->vecs_sensi,ts->vecs_sensip);CHKERRQ(ierr); 4481 ierr = TSAdjointEventHandler(ts);CHKERRQ(ierr); 4482 ierr = TSAdjointStep(ts);CHKERRQ(ierr); 4483 if (ts->vec_costintegral && !ts->costintegralfwd) { 4484 ierr = TSAdjointCostIntegral(ts);CHKERRQ(ierr); 4485 } 4486 } 4487 ierr = TSTrajectoryGet(ts->trajectory,ts,ts->steps,&ts->ptime);CHKERRQ(ierr); 4488 ierr = TSAdjointMonitor(ts,ts->steps,ts->ptime,ts->vec_sol,ts->numcost,ts->vecs_sensi,ts->vecs_sensip);CHKERRQ(ierr); 4489 ts->solvetime = ts->ptime; 4490 ierr = TSTrajectoryViewFromOptions(ts->trajectory,NULL,"-ts_trajectory_view");CHKERRQ(ierr); 4491 ierr = VecViewFromOptions(ts->vecs_sensi[0],(PetscObject) ts, "-ts_adjoint_view_solution");CHKERRQ(ierr); 4492 PetscFunctionReturn(0); 4493 } 4494 4495 /*@C 4496 TSMonitor - Runs all user-provided monitor routines set using TSMonitorSet() 4497 4498 Collective on TS 4499 4500 Input Parameters: 4501 + ts - time stepping context obtained from TSCreate() 4502 . step - step number that has just completed 4503 . ptime - model time of the state 4504 - u - state at the current model time 4505 4506 Notes: 4507 TSMonitor() is typically used automatically within the time stepping implementations. 4508 Users would almost never call this routine directly. 4509 4510 A step of -1 indicates that the monitor is being called on a solution obtained by interpolating from computed solutions 4511 4512 Level: developer 4513 4514 .keywords: TS, timestep 4515 @*/ 4516 PetscErrorCode TSMonitor(TS ts,PetscInt step,PetscReal ptime,Vec u) 4517 { 4518 DM dm; 4519 PetscInt i,n = ts->numbermonitors; 4520 PetscErrorCode ierr; 4521 4522 PetscFunctionBegin; 4523 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4524 PetscValidHeaderSpecific(u,VEC_CLASSID,4); 4525 4526 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 4527 ierr = DMSetOutputSequenceNumber(dm,step,ptime);CHKERRQ(ierr); 4528 4529 ierr = VecLockPush(u);CHKERRQ(ierr); 4530 for (i=0; i<n; i++) { 4531 ierr = (*ts->monitor[i])(ts,step,ptime,u,ts->monitorcontext[i]);CHKERRQ(ierr); 4532 } 4533 ierr = VecLockPop(u);CHKERRQ(ierr); 4534 PetscFunctionReturn(0); 4535 } 4536 4537 /*@C 4538 TSAdjointMonitor - Runs all user-provided adjoint monitor routines set using TSAdjointMonitorSet() 4539 4540 Collective on TS 4541 4542 Input Parameters: 4543 + ts - time stepping context obtained from TSCreate() 4544 . step - step number that has just completed 4545 . ptime - model time of the state 4546 . u - state at the current model time 4547 . numcost - number of cost functions (dimension of lambda or mu) 4548 . lambda - vectors containing the gradients of the cost functions with respect to the ODE/DAE solution variables 4549 - mu - vectors containing the gradients of the cost functions with respect to the problem parameters 4550 4551 Notes: 4552 TSAdjointMonitor() is typically used automatically within the time stepping implementations. 4553 Users would almost never call this routine directly. 4554 4555 Level: developer 4556 4557 .keywords: TS, timestep 4558 @*/ 4559 PetscErrorCode TSAdjointMonitor(TS ts,PetscInt step,PetscReal ptime,Vec u,PetscInt numcost,Vec *lambda, Vec *mu) 4560 { 4561 PetscErrorCode ierr; 4562 PetscInt i,n = ts->numberadjointmonitors; 4563 4564 PetscFunctionBegin; 4565 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4566 PetscValidHeaderSpecific(u,VEC_CLASSID,4); 4567 ierr = VecLockPush(u);CHKERRQ(ierr); 4568 for (i=0; i<n; i++) { 4569 ierr = (*ts->adjointmonitor[i])(ts,step,ptime,u,numcost,lambda,mu,ts->adjointmonitorcontext[i]);CHKERRQ(ierr); 4570 } 4571 ierr = VecLockPop(u);CHKERRQ(ierr); 4572 PetscFunctionReturn(0); 4573 } 4574 4575 /* ------------------------------------------------------------------------*/ 4576 /*@C 4577 TSMonitorLGCtxCreate - Creates a TSMonitorLGCtx context for use with 4578 TS to monitor the solution process graphically in various ways 4579 4580 Collective on TS 4581 4582 Input Parameters: 4583 + host - the X display to open, or null for the local machine 4584 . label - the title to put in the title bar 4585 . x, y - the screen coordinates of the upper left coordinate of the window 4586 . m, n - the screen width and height in pixels 4587 - howoften - if positive then determines the frequency of the plotting, if -1 then only at the final time 4588 4589 Output Parameter: 4590 . ctx - the context 4591 4592 Options Database Key: 4593 + -ts_monitor_lg_timestep - automatically sets line graph monitor 4594 + -ts_monitor_lg_timestep_log - automatically sets line graph monitor 4595 . -ts_monitor_lg_solution - monitor the solution (or certain values of the solution by calling TSMonitorLGSetDisplayVariables() or TSMonitorLGCtxSetDisplayVariables()) 4596 . -ts_monitor_lg_error - monitor the error 4597 . -ts_monitor_lg_ksp_iterations - monitor the number of KSP iterations needed for each timestep 4598 . -ts_monitor_lg_snes_iterations - monitor the number of SNES iterations needed for each timestep 4599 - -lg_use_markers <true,false> - mark the data points (at each time step) on the plot; default is true 4600 4601 Notes: 4602 Use TSMonitorLGCtxDestroy() to destroy. 4603 4604 One can provide a function that transforms the solution before plotting it with TSMonitorLGCtxSetTransform() or TSMonitorLGSetTransform() 4605 4606 Many of the functions that control the monitoring have two forms: TSMonitorLGSet/GetXXXX() and TSMonitorLGCtxSet/GetXXXX() the first take a TS object as the 4607 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 4608 as the first argument. 4609 4610 One can control the names displayed for each solution or error variable with TSMonitorLGCtxSetVariableNames() or TSMonitorLGSetVariableNames() 4611 4612 Level: intermediate 4613 4614 .keywords: TS, monitor, line graph, residual 4615 4616 .seealso: TSMonitorLGTimeStep(), TSMonitorSet(), TSMonitorLGSolution(), TSMonitorLGError(), TSMonitorDefault(), VecView(), 4617 TSMonitorLGCtxCreate(), TSMonitorLGCtxSetVariableNames(), TSMonitorLGCtxGetVariableNames(), 4618 TSMonitorLGSetVariableNames(), TSMonitorLGGetVariableNames(), TSMonitorLGSetDisplayVariables(), TSMonitorLGCtxSetDisplayVariables(), 4619 TSMonitorLGCtxSetTransform(), TSMonitorLGSetTransform(), TSMonitorLGError(), TSMonitorLGSNESIterations(), TSMonitorLGKSPIterations(), 4620 TSMonitorEnvelopeCtxCreate(), TSMonitorEnvelopeGetBounds(), TSMonitorEnvelopeCtxDestroy(), TSMonitorEnvelop() 4621 4622 @*/ 4623 PetscErrorCode TSMonitorLGCtxCreate(MPI_Comm comm,const char host[],const char label[],int x,int y,int m,int n,PetscInt howoften,TSMonitorLGCtx *ctx) 4624 { 4625 PetscDraw draw; 4626 PetscErrorCode ierr; 4627 4628 PetscFunctionBegin; 4629 ierr = PetscNew(ctx);CHKERRQ(ierr); 4630 ierr = PetscDrawCreate(comm,host,label,x,y,m,n,&draw);CHKERRQ(ierr); 4631 ierr = PetscDrawSetFromOptions(draw);CHKERRQ(ierr); 4632 ierr = PetscDrawLGCreate(draw,1,&(*ctx)->lg);CHKERRQ(ierr); 4633 ierr = PetscDrawLGSetFromOptions((*ctx)->lg);CHKERRQ(ierr); 4634 ierr = PetscDrawDestroy(&draw);CHKERRQ(ierr); 4635 (*ctx)->howoften = howoften; 4636 PetscFunctionReturn(0); 4637 } 4638 4639 PetscErrorCode TSMonitorLGTimeStep(TS ts,PetscInt step,PetscReal ptime,Vec v,void *monctx) 4640 { 4641 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 4642 PetscReal x = ptime,y; 4643 PetscErrorCode ierr; 4644 4645 PetscFunctionBegin; 4646 if (step < 0) PetscFunctionReturn(0); /* -1 indicates an interpolated solution */ 4647 if (!step) { 4648 PetscDrawAxis axis; 4649 const char *ylabel = ctx->semilogy ? "Log Time Step" : "Time Step"; 4650 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 4651 ierr = PetscDrawAxisSetLabels(axis,"Timestep as function of time","Time",ylabel);CHKERRQ(ierr); 4652 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 4653 } 4654 ierr = TSGetTimeStep(ts,&y);CHKERRQ(ierr); 4655 if (ctx->semilogy) y = PetscLog10Real(y); 4656 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 4657 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 4658 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 4659 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 4660 } 4661 PetscFunctionReturn(0); 4662 } 4663 4664 /*@C 4665 TSMonitorLGCtxDestroy - Destroys a line graph context that was created 4666 with TSMonitorLGCtxCreate(). 4667 4668 Collective on TSMonitorLGCtx 4669 4670 Input Parameter: 4671 . ctx - the monitor context 4672 4673 Level: intermediate 4674 4675 .keywords: TS, monitor, line graph, destroy 4676 4677 .seealso: TSMonitorLGCtxCreate(), TSMonitorSet(), TSMonitorLGTimeStep(); 4678 @*/ 4679 PetscErrorCode TSMonitorLGCtxDestroy(TSMonitorLGCtx *ctx) 4680 { 4681 PetscErrorCode ierr; 4682 4683 PetscFunctionBegin; 4684 if ((*ctx)->transformdestroy) { 4685 ierr = ((*ctx)->transformdestroy)((*ctx)->transformctx);CHKERRQ(ierr); 4686 } 4687 ierr = PetscDrawLGDestroy(&(*ctx)->lg);CHKERRQ(ierr); 4688 ierr = PetscStrArrayDestroy(&(*ctx)->names);CHKERRQ(ierr); 4689 ierr = PetscStrArrayDestroy(&(*ctx)->displaynames);CHKERRQ(ierr); 4690 ierr = PetscFree((*ctx)->displayvariables);CHKERRQ(ierr); 4691 ierr = PetscFree((*ctx)->displayvalues);CHKERRQ(ierr); 4692 ierr = PetscFree(*ctx);CHKERRQ(ierr); 4693 PetscFunctionReturn(0); 4694 } 4695 4696 /*@ 4697 TSGetTime - Gets the time of the most recently completed step. 4698 4699 Not Collective 4700 4701 Input Parameter: 4702 . ts - the TS context obtained from TSCreate() 4703 4704 Output Parameter: 4705 . t - the current time. This time may not corresponds to the final time set with TSSetMaxTime(), use TSGetSolveTime(). 4706 4707 Level: beginner 4708 4709 Note: 4710 When called during time step evaluation (e.g. during residual evaluation or via hooks set using TSSetPreStep(), 4711 TSSetPreStage(), TSSetPostStage(), or TSSetPostStep()), the time is the time at the start of the step being evaluated. 4712 4713 .seealso: TSGetSolveTime(), TSSetTime(), TSGetTimeStep() 4714 4715 .keywords: TS, get, time 4716 @*/ 4717 PetscErrorCode TSGetTime(TS ts,PetscReal *t) 4718 { 4719 PetscFunctionBegin; 4720 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4721 PetscValidRealPointer(t,2); 4722 *t = ts->ptime; 4723 PetscFunctionReturn(0); 4724 } 4725 4726 /*@ 4727 TSGetPrevTime - Gets the starting time of the previously completed step. 4728 4729 Not Collective 4730 4731 Input Parameter: 4732 . ts - the TS context obtained from TSCreate() 4733 4734 Output Parameter: 4735 . t - the previous time 4736 4737 Level: beginner 4738 4739 .seealso: TSGetTime(), TSGetSolveTime(), TSGetTimeStep() 4740 4741 .keywords: TS, get, time 4742 @*/ 4743 PetscErrorCode TSGetPrevTime(TS ts,PetscReal *t) 4744 { 4745 PetscFunctionBegin; 4746 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4747 PetscValidRealPointer(t,2); 4748 *t = ts->ptime_prev; 4749 PetscFunctionReturn(0); 4750 } 4751 4752 /*@ 4753 TSSetTime - Allows one to reset the time. 4754 4755 Logically Collective on TS 4756 4757 Input Parameters: 4758 + ts - the TS context obtained from TSCreate() 4759 - time - the time 4760 4761 Level: intermediate 4762 4763 .seealso: TSGetTime(), TSSetMaxSteps() 4764 4765 .keywords: TS, set, time 4766 @*/ 4767 PetscErrorCode TSSetTime(TS ts, PetscReal t) 4768 { 4769 PetscFunctionBegin; 4770 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4771 PetscValidLogicalCollectiveReal(ts,t,2); 4772 ts->ptime = t; 4773 PetscFunctionReturn(0); 4774 } 4775 4776 /*@C 4777 TSSetOptionsPrefix - Sets the prefix used for searching for all 4778 TS options in the database. 4779 4780 Logically Collective on TS 4781 4782 Input Parameter: 4783 + ts - The TS context 4784 - prefix - The prefix to prepend to all option names 4785 4786 Notes: 4787 A hyphen (-) must NOT be given at the beginning of the prefix name. 4788 The first character of all runtime options is AUTOMATICALLY the 4789 hyphen. 4790 4791 Level: advanced 4792 4793 .keywords: TS, set, options, prefix, database 4794 4795 .seealso: TSSetFromOptions() 4796 4797 @*/ 4798 PetscErrorCode TSSetOptionsPrefix(TS ts,const char prefix[]) 4799 { 4800 PetscErrorCode ierr; 4801 SNES snes; 4802 4803 PetscFunctionBegin; 4804 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4805 ierr = PetscObjectSetOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 4806 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4807 ierr = SNESSetOptionsPrefix(snes,prefix);CHKERRQ(ierr); 4808 PetscFunctionReturn(0); 4809 } 4810 4811 /*@C 4812 TSAppendOptionsPrefix - Appends to the prefix used for searching for all 4813 TS options in the database. 4814 4815 Logically Collective on TS 4816 4817 Input Parameter: 4818 + ts - The TS context 4819 - prefix - The prefix to prepend to all option names 4820 4821 Notes: 4822 A hyphen (-) must NOT be given at the beginning of the prefix name. 4823 The first character of all runtime options is AUTOMATICALLY the 4824 hyphen. 4825 4826 Level: advanced 4827 4828 .keywords: TS, append, options, prefix, database 4829 4830 .seealso: TSGetOptionsPrefix() 4831 4832 @*/ 4833 PetscErrorCode TSAppendOptionsPrefix(TS ts,const char prefix[]) 4834 { 4835 PetscErrorCode ierr; 4836 SNES snes; 4837 4838 PetscFunctionBegin; 4839 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4840 ierr = PetscObjectAppendOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 4841 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4842 ierr = SNESAppendOptionsPrefix(snes,prefix);CHKERRQ(ierr); 4843 PetscFunctionReturn(0); 4844 } 4845 4846 /*@C 4847 TSGetOptionsPrefix - Sets the prefix used for searching for all 4848 TS options in the database. 4849 4850 Not Collective 4851 4852 Input Parameter: 4853 . ts - The TS context 4854 4855 Output Parameter: 4856 . prefix - A pointer to the prefix string used 4857 4858 Notes: On the fortran side, the user should pass in a string 'prifix' of 4859 sufficient length to hold the prefix. 4860 4861 Level: intermediate 4862 4863 .keywords: TS, get, options, prefix, database 4864 4865 .seealso: TSAppendOptionsPrefix() 4866 @*/ 4867 PetscErrorCode TSGetOptionsPrefix(TS ts,const char *prefix[]) 4868 { 4869 PetscErrorCode ierr; 4870 4871 PetscFunctionBegin; 4872 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4873 PetscValidPointer(prefix,2); 4874 ierr = PetscObjectGetOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 4875 PetscFunctionReturn(0); 4876 } 4877 4878 /*@C 4879 TSGetRHSJacobian - Returns the Jacobian J at the present timestep. 4880 4881 Not Collective, but parallel objects are returned if TS is parallel 4882 4883 Input Parameter: 4884 . ts - The TS context obtained from TSCreate() 4885 4886 Output Parameters: 4887 + Amat - The (approximate) Jacobian J of G, where U_t = G(U,t) (or NULL) 4888 . Pmat - The matrix from which the preconditioner is constructed, usually the same as Amat (or NULL) 4889 . func - Function to compute the Jacobian of the RHS (or NULL) 4890 - ctx - User-defined context for Jacobian evaluation routine (or NULL) 4891 4892 Notes: You can pass in NULL for any return argument you do not need. 4893 4894 Level: intermediate 4895 4896 .seealso: TSGetTimeStep(), TSGetMatrices(), TSGetTime(), TSGetStepNumber() 4897 4898 .keywords: TS, timestep, get, matrix, Jacobian 4899 @*/ 4900 PetscErrorCode TSGetRHSJacobian(TS ts,Mat *Amat,Mat *Pmat,TSRHSJacobian *func,void **ctx) 4901 { 4902 PetscErrorCode ierr; 4903 DM dm; 4904 4905 PetscFunctionBegin; 4906 if (Amat || Pmat) { 4907 SNES snes; 4908 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4909 ierr = SNESSetUpMatrices(snes);CHKERRQ(ierr); 4910 ierr = SNESGetJacobian(snes,Amat,Pmat,NULL,NULL);CHKERRQ(ierr); 4911 } 4912 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 4913 ierr = DMTSGetRHSJacobian(dm,func,ctx);CHKERRQ(ierr); 4914 PetscFunctionReturn(0); 4915 } 4916 4917 /*@C 4918 TSGetIJacobian - Returns the implicit Jacobian at the present timestep. 4919 4920 Not Collective, but parallel objects are returned if TS is parallel 4921 4922 Input Parameter: 4923 . ts - The TS context obtained from TSCreate() 4924 4925 Output Parameters: 4926 + Amat - The (approximate) Jacobian of F(t,U,U_t) 4927 . Pmat - The matrix from which the preconditioner is constructed, often the same as Amat 4928 . f - The function to compute the matrices 4929 - ctx - User-defined context for Jacobian evaluation routine 4930 4931 Notes: You can pass in NULL for any return argument you do not need. 4932 4933 Level: advanced 4934 4935 .seealso: TSGetTimeStep(), TSGetRHSJacobian(), TSGetMatrices(), TSGetTime(), TSGetStepNumber() 4936 4937 .keywords: TS, timestep, get, matrix, Jacobian 4938 @*/ 4939 PetscErrorCode TSGetIJacobian(TS ts,Mat *Amat,Mat *Pmat,TSIJacobian *f,void **ctx) 4940 { 4941 PetscErrorCode ierr; 4942 DM dm; 4943 4944 PetscFunctionBegin; 4945 if (Amat || Pmat) { 4946 SNES snes; 4947 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4948 ierr = SNESSetUpMatrices(snes);CHKERRQ(ierr); 4949 ierr = SNESGetJacobian(snes,Amat,Pmat,NULL,NULL);CHKERRQ(ierr); 4950 } 4951 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 4952 ierr = DMTSGetIJacobian(dm,f,ctx);CHKERRQ(ierr); 4953 PetscFunctionReturn(0); 4954 } 4955 4956 /*@C 4957 TSMonitorDrawSolution - Monitors progress of the TS solvers by calling 4958 VecView() for the solution at each timestep 4959 4960 Collective on TS 4961 4962 Input Parameters: 4963 + ts - the TS context 4964 . step - current time-step 4965 . ptime - current time 4966 - dummy - either a viewer or NULL 4967 4968 Options Database: 4969 . -ts_monitor_draw_solution_initial - show initial solution as well as current solution 4970 4971 Notes: the initial solution and current solution are not display with a common axis scaling so generally the option -ts_monitor_draw_solution_initial 4972 will look bad 4973 4974 Level: intermediate 4975 4976 .keywords: TS, vector, monitor, view 4977 4978 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 4979 @*/ 4980 PetscErrorCode TSMonitorDrawSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 4981 { 4982 PetscErrorCode ierr; 4983 TSMonitorDrawCtx ictx = (TSMonitorDrawCtx)dummy; 4984 PetscDraw draw; 4985 4986 PetscFunctionBegin; 4987 if (!step && ictx->showinitial) { 4988 if (!ictx->initialsolution) { 4989 ierr = VecDuplicate(u,&ictx->initialsolution);CHKERRQ(ierr); 4990 } 4991 ierr = VecCopy(u,ictx->initialsolution);CHKERRQ(ierr); 4992 } 4993 if (!(((ictx->howoften > 0) && (!(step % ictx->howoften))) || ((ictx->howoften == -1) && ts->reason))) PetscFunctionReturn(0); 4994 4995 if (ictx->showinitial) { 4996 PetscReal pause; 4997 ierr = PetscViewerDrawGetPause(ictx->viewer,&pause);CHKERRQ(ierr); 4998 ierr = PetscViewerDrawSetPause(ictx->viewer,0.0);CHKERRQ(ierr); 4999 ierr = VecView(ictx->initialsolution,ictx->viewer);CHKERRQ(ierr); 5000 ierr = PetscViewerDrawSetPause(ictx->viewer,pause);CHKERRQ(ierr); 5001 ierr = PetscViewerDrawSetHold(ictx->viewer,PETSC_TRUE);CHKERRQ(ierr); 5002 } 5003 ierr = VecView(u,ictx->viewer);CHKERRQ(ierr); 5004 if (ictx->showtimestepandtime) { 5005 PetscReal xl,yl,xr,yr,h; 5006 char time[32]; 5007 5008 ierr = PetscViewerDrawGetDraw(ictx->viewer,0,&draw);CHKERRQ(ierr); 5009 ierr = PetscSNPrintf(time,32,"Timestep %d Time %g",(int)step,(double)ptime);CHKERRQ(ierr); 5010 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 5011 h = yl + .95*(yr - yl); 5012 ierr = PetscDrawStringCentered(draw,.5*(xl+xr),h,PETSC_DRAW_BLACK,time);CHKERRQ(ierr); 5013 ierr = PetscDrawFlush(draw);CHKERRQ(ierr); 5014 } 5015 5016 if (ictx->showinitial) { 5017 ierr = PetscViewerDrawSetHold(ictx->viewer,PETSC_FALSE);CHKERRQ(ierr); 5018 } 5019 PetscFunctionReturn(0); 5020 } 5021 5022 /*@C 5023 TSAdjointMonitorDrawSensi - Monitors progress of the adjoint TS solvers by calling 5024 VecView() for the sensitivities to initial states at each timestep 5025 5026 Collective on TS 5027 5028 Input Parameters: 5029 + ts - the TS context 5030 . step - current time-step 5031 . ptime - current time 5032 . u - current state 5033 . numcost - number of cost functions 5034 . lambda - sensitivities to initial conditions 5035 . mu - sensitivities to parameters 5036 - dummy - either a viewer or NULL 5037 5038 Level: intermediate 5039 5040 .keywords: TS, vector, adjoint, monitor, view 5041 5042 .seealso: TSAdjointMonitorSet(), TSAdjointMonitorDefault(), VecView() 5043 @*/ 5044 PetscErrorCode TSAdjointMonitorDrawSensi(TS ts,PetscInt step,PetscReal ptime,Vec u,PetscInt numcost,Vec *lambda,Vec *mu,void *dummy) 5045 { 5046 PetscErrorCode ierr; 5047 TSMonitorDrawCtx ictx = (TSMonitorDrawCtx)dummy; 5048 PetscDraw draw; 5049 PetscReal xl,yl,xr,yr,h; 5050 char time[32]; 5051 5052 PetscFunctionBegin; 5053 if (!(((ictx->howoften > 0) && (!(step % ictx->howoften))) || ((ictx->howoften == -1) && ts->reason))) PetscFunctionReturn(0); 5054 5055 ierr = VecView(lambda[0],ictx->viewer);CHKERRQ(ierr); 5056 ierr = PetscViewerDrawGetDraw(ictx->viewer,0,&draw);CHKERRQ(ierr); 5057 ierr = PetscSNPrintf(time,32,"Timestep %d Time %g",(int)step,(double)ptime);CHKERRQ(ierr); 5058 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 5059 h = yl + .95*(yr - yl); 5060 ierr = PetscDrawStringCentered(draw,.5*(xl+xr),h,PETSC_DRAW_BLACK,time);CHKERRQ(ierr); 5061 ierr = PetscDrawFlush(draw);CHKERRQ(ierr); 5062 PetscFunctionReturn(0); 5063 } 5064 5065 /*@C 5066 TSMonitorDrawSolutionPhase - Monitors progress of the TS solvers by plotting the solution as a phase diagram 5067 5068 Collective on TS 5069 5070 Input Parameters: 5071 + ts - the TS context 5072 . step - current time-step 5073 . ptime - current time 5074 - dummy - either a viewer or NULL 5075 5076 Level: intermediate 5077 5078 .keywords: TS, vector, monitor, view 5079 5080 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 5081 @*/ 5082 PetscErrorCode TSMonitorDrawSolutionPhase(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 5083 { 5084 PetscErrorCode ierr; 5085 TSMonitorDrawCtx ictx = (TSMonitorDrawCtx)dummy; 5086 PetscDraw draw; 5087 PetscDrawAxis axis; 5088 PetscInt n; 5089 PetscMPIInt size; 5090 PetscReal U0,U1,xl,yl,xr,yr,h; 5091 char time[32]; 5092 const PetscScalar *U; 5093 5094 PetscFunctionBegin; 5095 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)ts),&size);CHKERRQ(ierr); 5096 if (size != 1) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Only allowed for sequential runs"); 5097 ierr = VecGetSize(u,&n);CHKERRQ(ierr); 5098 if (n != 2) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Only for ODEs with two unknowns"); 5099 5100 ierr = PetscViewerDrawGetDraw(ictx->viewer,0,&draw);CHKERRQ(ierr); 5101 ierr = PetscViewerDrawGetDrawAxis(ictx->viewer,0,&axis);CHKERRQ(ierr); 5102 ierr = PetscDrawAxisGetLimits(axis,&xl,&xr,&yl,&yr);CHKERRQ(ierr); 5103 if (!step) { 5104 ierr = PetscDrawClear(draw);CHKERRQ(ierr); 5105 ierr = PetscDrawAxisDraw(axis);CHKERRQ(ierr); 5106 } 5107 5108 ierr = VecGetArrayRead(u,&U);CHKERRQ(ierr); 5109 U0 = PetscRealPart(U[0]); 5110 U1 = PetscRealPart(U[1]); 5111 ierr = VecRestoreArrayRead(u,&U);CHKERRQ(ierr); 5112 if ((U0 < xl) || (U1 < yl) || (U0 > xr) || (U1 > yr)) PetscFunctionReturn(0); 5113 5114 ierr = PetscDrawCollectiveBegin(draw);CHKERRQ(ierr); 5115 ierr = PetscDrawPoint(draw,U0,U1,PETSC_DRAW_BLACK);CHKERRQ(ierr); 5116 if (ictx->showtimestepandtime) { 5117 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 5118 ierr = PetscSNPrintf(time,32,"Timestep %d Time %g",(int)step,(double)ptime);CHKERRQ(ierr); 5119 h = yl + .95*(yr - yl); 5120 ierr = PetscDrawStringCentered(draw,.5*(xl+xr),h,PETSC_DRAW_BLACK,time);CHKERRQ(ierr); 5121 } 5122 ierr = PetscDrawCollectiveEnd(draw);CHKERRQ(ierr); 5123 ierr = PetscDrawFlush(draw);CHKERRQ(ierr); 5124 ierr = PetscDrawPause(draw);CHKERRQ(ierr); 5125 ierr = PetscDrawSave(draw);CHKERRQ(ierr); 5126 PetscFunctionReturn(0); 5127 } 5128 5129 /*@C 5130 TSMonitorDrawCtxDestroy - Destroys the monitor context for TSMonitorDrawSolution() 5131 5132 Collective on TS 5133 5134 Input Parameters: 5135 . ctx - the monitor context 5136 5137 Level: intermediate 5138 5139 .keywords: TS, vector, monitor, view 5140 5141 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorDrawSolution(), TSMonitorDrawError() 5142 @*/ 5143 PetscErrorCode TSMonitorDrawCtxDestroy(TSMonitorDrawCtx *ictx) 5144 { 5145 PetscErrorCode ierr; 5146 5147 PetscFunctionBegin; 5148 ierr = PetscViewerDestroy(&(*ictx)->viewer);CHKERRQ(ierr); 5149 ierr = VecDestroy(&(*ictx)->initialsolution);CHKERRQ(ierr); 5150 ierr = PetscFree(*ictx);CHKERRQ(ierr); 5151 PetscFunctionReturn(0); 5152 } 5153 5154 /*@C 5155 TSMonitorDrawCtxCreate - Creates the monitor context for TSMonitorDrawCtx 5156 5157 Collective on TS 5158 5159 Input Parameter: 5160 . ts - time-step context 5161 5162 Output Patameter: 5163 . ctx - the monitor context 5164 5165 Options Database: 5166 . -ts_monitor_draw_solution_initial - show initial solution as well as current solution 5167 5168 Level: intermediate 5169 5170 .keywords: TS, vector, monitor, view 5171 5172 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorDrawCtx() 5173 @*/ 5174 PetscErrorCode TSMonitorDrawCtxCreate(MPI_Comm comm,const char host[],const char label[],int x,int y,int m,int n,PetscInt howoften,TSMonitorDrawCtx *ctx) 5175 { 5176 PetscErrorCode ierr; 5177 5178 PetscFunctionBegin; 5179 ierr = PetscNew(ctx);CHKERRQ(ierr); 5180 ierr = PetscViewerDrawOpen(comm,host,label,x,y,m,n,&(*ctx)->viewer);CHKERRQ(ierr); 5181 ierr = PetscViewerSetFromOptions((*ctx)->viewer);CHKERRQ(ierr); 5182 5183 (*ctx)->howoften = howoften; 5184 (*ctx)->showinitial = PETSC_FALSE; 5185 ierr = PetscOptionsGetBool(NULL,NULL,"-ts_monitor_draw_solution_initial",&(*ctx)->showinitial,NULL);CHKERRQ(ierr); 5186 5187 (*ctx)->showtimestepandtime = PETSC_FALSE; 5188 ierr = PetscOptionsGetBool(NULL,NULL,"-ts_monitor_draw_solution_show_time",&(*ctx)->showtimestepandtime,NULL);CHKERRQ(ierr); 5189 PetscFunctionReturn(0); 5190 } 5191 5192 /*@C 5193 TSMonitorDrawError - Monitors progress of the TS solvers by calling 5194 VecView() for the error at each timestep 5195 5196 Collective on TS 5197 5198 Input Parameters: 5199 + ts - the TS context 5200 . step - current time-step 5201 . ptime - current time 5202 - dummy - either a viewer or NULL 5203 5204 Level: intermediate 5205 5206 .keywords: TS, vector, monitor, view 5207 5208 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 5209 @*/ 5210 PetscErrorCode TSMonitorDrawError(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 5211 { 5212 PetscErrorCode ierr; 5213 TSMonitorDrawCtx ctx = (TSMonitorDrawCtx)dummy; 5214 PetscViewer viewer = ctx->viewer; 5215 Vec work; 5216 5217 PetscFunctionBegin; 5218 if (!(((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason))) PetscFunctionReturn(0); 5219 ierr = VecDuplicate(u,&work);CHKERRQ(ierr); 5220 ierr = TSComputeSolutionFunction(ts,ptime,work);CHKERRQ(ierr); 5221 ierr = VecAXPY(work,-1.0,u);CHKERRQ(ierr); 5222 ierr = VecView(work,viewer);CHKERRQ(ierr); 5223 ierr = VecDestroy(&work);CHKERRQ(ierr); 5224 PetscFunctionReturn(0); 5225 } 5226 5227 #include <petsc/private/dmimpl.h> 5228 /*@ 5229 TSSetDM - Sets the DM that may be used by some nonlinear solvers or preconditioners under the TS 5230 5231 Logically Collective on TS and DM 5232 5233 Input Parameters: 5234 + ts - the ODE integrator object 5235 - dm - the dm, cannot be NULL 5236 5237 Level: intermediate 5238 5239 .seealso: TSGetDM(), SNESSetDM(), SNESGetDM() 5240 @*/ 5241 PetscErrorCode TSSetDM(TS ts,DM dm) 5242 { 5243 PetscErrorCode ierr; 5244 SNES snes; 5245 DMTS tsdm; 5246 5247 PetscFunctionBegin; 5248 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5249 PetscValidHeaderSpecific(dm,DM_CLASSID,2); 5250 ierr = PetscObjectReference((PetscObject)dm);CHKERRQ(ierr); 5251 if (ts->dm) { /* Move the DMTS context over to the new DM unless the new DM already has one */ 5252 if (ts->dm->dmts && !dm->dmts) { 5253 ierr = DMCopyDMTS(ts->dm,dm);CHKERRQ(ierr); 5254 ierr = DMGetDMTS(ts->dm,&tsdm);CHKERRQ(ierr); 5255 if (tsdm->originaldm == ts->dm) { /* Grant write privileges to the replacement DM */ 5256 tsdm->originaldm = dm; 5257 } 5258 } 5259 ierr = DMDestroy(&ts->dm);CHKERRQ(ierr); 5260 } 5261 ts->dm = dm; 5262 5263 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 5264 ierr = SNESSetDM(snes,dm);CHKERRQ(ierr); 5265 PetscFunctionReturn(0); 5266 } 5267 5268 /*@ 5269 TSGetDM - Gets the DM that may be used by some preconditioners 5270 5271 Not Collective 5272 5273 Input Parameter: 5274 . ts - the preconditioner context 5275 5276 Output Parameter: 5277 . dm - the dm 5278 5279 Level: intermediate 5280 5281 .seealso: TSSetDM(), SNESSetDM(), SNESGetDM() 5282 @*/ 5283 PetscErrorCode TSGetDM(TS ts,DM *dm) 5284 { 5285 PetscErrorCode ierr; 5286 5287 PetscFunctionBegin; 5288 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5289 if (!ts->dm) { 5290 ierr = DMShellCreate(PetscObjectComm((PetscObject)ts),&ts->dm);CHKERRQ(ierr); 5291 if (ts->snes) {ierr = SNESSetDM(ts->snes,ts->dm);CHKERRQ(ierr);} 5292 } 5293 *dm = ts->dm; 5294 PetscFunctionReturn(0); 5295 } 5296 5297 /*@ 5298 SNESTSFormFunction - Function to evaluate nonlinear residual 5299 5300 Logically Collective on SNES 5301 5302 Input Parameter: 5303 + snes - nonlinear solver 5304 . U - the current state at which to evaluate the residual 5305 - ctx - user context, must be a TS 5306 5307 Output Parameter: 5308 . F - the nonlinear residual 5309 5310 Notes: 5311 This function is not normally called by users and is automatically registered with the SNES used by TS. 5312 It is most frequently passed to MatFDColoringSetFunction(). 5313 5314 Level: advanced 5315 5316 .seealso: SNESSetFunction(), MatFDColoringSetFunction() 5317 @*/ 5318 PetscErrorCode SNESTSFormFunction(SNES snes,Vec U,Vec F,void *ctx) 5319 { 5320 TS ts = (TS)ctx; 5321 PetscErrorCode ierr; 5322 5323 PetscFunctionBegin; 5324 PetscValidHeaderSpecific(snes,SNES_CLASSID,1); 5325 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 5326 PetscValidHeaderSpecific(F,VEC_CLASSID,3); 5327 PetscValidHeaderSpecific(ts,TS_CLASSID,4); 5328 ierr = (ts->ops->snesfunction)(snes,U,F,ts);CHKERRQ(ierr); 5329 PetscFunctionReturn(0); 5330 } 5331 5332 /*@ 5333 SNESTSFormJacobian - Function to evaluate the Jacobian 5334 5335 Collective on SNES 5336 5337 Input Parameter: 5338 + snes - nonlinear solver 5339 . U - the current state at which to evaluate the residual 5340 - ctx - user context, must be a TS 5341 5342 Output Parameter: 5343 + A - the Jacobian 5344 . B - the preconditioning matrix (may be the same as A) 5345 - flag - indicates any structure change in the matrix 5346 5347 Notes: 5348 This function is not normally called by users and is automatically registered with the SNES used by TS. 5349 5350 Level: developer 5351 5352 .seealso: SNESSetJacobian() 5353 @*/ 5354 PetscErrorCode SNESTSFormJacobian(SNES snes,Vec U,Mat A,Mat B,void *ctx) 5355 { 5356 TS ts = (TS)ctx; 5357 PetscErrorCode ierr; 5358 5359 PetscFunctionBegin; 5360 PetscValidHeaderSpecific(snes,SNES_CLASSID,1); 5361 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 5362 PetscValidPointer(A,3); 5363 PetscValidHeaderSpecific(A,MAT_CLASSID,3); 5364 PetscValidPointer(B,4); 5365 PetscValidHeaderSpecific(B,MAT_CLASSID,4); 5366 PetscValidHeaderSpecific(ts,TS_CLASSID,6); 5367 ierr = (ts->ops->snesjacobian)(snes,U,A,B,ts);CHKERRQ(ierr); 5368 PetscFunctionReturn(0); 5369 } 5370 5371 /*@C 5372 TSComputeRHSFunctionLinear - Evaluate the right hand side via the user-provided Jacobian, for linear problems Udot = A U only 5373 5374 Collective on TS 5375 5376 Input Arguments: 5377 + ts - time stepping context 5378 . t - time at which to evaluate 5379 . U - state at which to evaluate 5380 - ctx - context 5381 5382 Output Arguments: 5383 . F - right hand side 5384 5385 Level: intermediate 5386 5387 Notes: 5388 This function is intended to be passed to TSSetRHSFunction() to evaluate the right hand side for linear problems. 5389 The matrix (and optionally the evaluation context) should be passed to TSSetRHSJacobian(). 5390 5391 .seealso: TSSetRHSFunction(), TSSetRHSJacobian(), TSComputeRHSJacobianConstant() 5392 @*/ 5393 PetscErrorCode TSComputeRHSFunctionLinear(TS ts,PetscReal t,Vec U,Vec F,void *ctx) 5394 { 5395 PetscErrorCode ierr; 5396 Mat Arhs,Brhs; 5397 5398 PetscFunctionBegin; 5399 ierr = TSGetRHSMats_Private(ts,&Arhs,&Brhs);CHKERRQ(ierr); 5400 ierr = TSComputeRHSJacobian(ts,t,U,Arhs,Brhs);CHKERRQ(ierr); 5401 ierr = MatMult(Arhs,U,F);CHKERRQ(ierr); 5402 PetscFunctionReturn(0); 5403 } 5404 5405 /*@C 5406 TSComputeRHSJacobianConstant - Reuses a Jacobian that is time-independent. 5407 5408 Collective on TS 5409 5410 Input Arguments: 5411 + ts - time stepping context 5412 . t - time at which to evaluate 5413 . U - state at which to evaluate 5414 - ctx - context 5415 5416 Output Arguments: 5417 + A - pointer to operator 5418 . B - pointer to preconditioning matrix 5419 - flg - matrix structure flag 5420 5421 Level: intermediate 5422 5423 Notes: 5424 This function is intended to be passed to TSSetRHSJacobian() to evaluate the Jacobian for linear time-independent problems. 5425 5426 .seealso: TSSetRHSFunction(), TSSetRHSJacobian(), TSComputeRHSFunctionLinear() 5427 @*/ 5428 PetscErrorCode TSComputeRHSJacobianConstant(TS ts,PetscReal t,Vec U,Mat A,Mat B,void *ctx) 5429 { 5430 PetscFunctionBegin; 5431 PetscFunctionReturn(0); 5432 } 5433 5434 /*@C 5435 TSComputeIFunctionLinear - Evaluate the left hand side via the user-provided Jacobian, for linear problems only 5436 5437 Collective on TS 5438 5439 Input Arguments: 5440 + ts - time stepping context 5441 . t - time at which to evaluate 5442 . U - state at which to evaluate 5443 . Udot - time derivative of state vector 5444 - ctx - context 5445 5446 Output Arguments: 5447 . F - left hand side 5448 5449 Level: intermediate 5450 5451 Notes: 5452 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 5453 user is required to write their own TSComputeIFunction. 5454 This function is intended to be passed to TSSetIFunction() to evaluate the left hand side for linear problems. 5455 The matrix (and optionally the evaluation context) should be passed to TSSetIJacobian(). 5456 5457 Note that using this function is NOT equivalent to using TSComputeRHSFunctionLinear() since that solves Udot = A U 5458 5459 .seealso: TSSetIFunction(), TSSetIJacobian(), TSComputeIJacobianConstant(), TSComputeRHSFunctionLinear() 5460 @*/ 5461 PetscErrorCode TSComputeIFunctionLinear(TS ts,PetscReal t,Vec U,Vec Udot,Vec F,void *ctx) 5462 { 5463 PetscErrorCode ierr; 5464 Mat A,B; 5465 5466 PetscFunctionBegin; 5467 ierr = TSGetIJacobian(ts,&A,&B,NULL,NULL);CHKERRQ(ierr); 5468 ierr = TSComputeIJacobian(ts,t,U,Udot,1.0,A,B,PETSC_TRUE);CHKERRQ(ierr); 5469 ierr = MatMult(A,Udot,F);CHKERRQ(ierr); 5470 PetscFunctionReturn(0); 5471 } 5472 5473 /*@C 5474 TSComputeIJacobianConstant - Reuses a time-independent for a semi-implicit DAE or ODE 5475 5476 Collective on TS 5477 5478 Input Arguments: 5479 + ts - time stepping context 5480 . t - time at which to evaluate 5481 . U - state at which to evaluate 5482 . Udot - time derivative of state vector 5483 . shift - shift to apply 5484 - ctx - context 5485 5486 Output Arguments: 5487 + A - pointer to operator 5488 . B - pointer to preconditioning matrix 5489 - flg - matrix structure flag 5490 5491 Level: advanced 5492 5493 Notes: 5494 This function is intended to be passed to TSSetIJacobian() to evaluate the Jacobian for linear time-independent problems. 5495 5496 It is only appropriate for problems of the form 5497 5498 $ M Udot = F(U,t) 5499 5500 where M is constant and F is non-stiff. The user must pass M to TSSetIJacobian(). The current implementation only 5501 works with IMEX time integration methods such as TSROSW and TSARKIMEX, since there is no support for de-constructing 5502 an implicit operator of the form 5503 5504 $ shift*M + J 5505 5506 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 5507 a copy of M or reassemble it when requested. 5508 5509 .seealso: TSSetIFunction(), TSSetIJacobian(), TSComputeIFunctionLinear() 5510 @*/ 5511 PetscErrorCode TSComputeIJacobianConstant(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat A,Mat B,void *ctx) 5512 { 5513 PetscErrorCode ierr; 5514 5515 PetscFunctionBegin; 5516 ierr = MatScale(A, shift / ts->ijacobian.shift);CHKERRQ(ierr); 5517 ts->ijacobian.shift = shift; 5518 PetscFunctionReturn(0); 5519 } 5520 5521 /*@ 5522 TSGetEquationType - Gets the type of the equation that TS is solving. 5523 5524 Not Collective 5525 5526 Input Parameter: 5527 . ts - the TS context 5528 5529 Output Parameter: 5530 . equation_type - see TSEquationType 5531 5532 Level: beginner 5533 5534 .keywords: TS, equation type 5535 5536 .seealso: TSSetEquationType(), TSEquationType 5537 @*/ 5538 PetscErrorCode TSGetEquationType(TS ts,TSEquationType *equation_type) 5539 { 5540 PetscFunctionBegin; 5541 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5542 PetscValidPointer(equation_type,2); 5543 *equation_type = ts->equation_type; 5544 PetscFunctionReturn(0); 5545 } 5546 5547 /*@ 5548 TSSetEquationType - Sets the type of the equation that TS is solving. 5549 5550 Not Collective 5551 5552 Input Parameter: 5553 + ts - the TS context 5554 - equation_type - see TSEquationType 5555 5556 Level: advanced 5557 5558 .keywords: TS, equation type 5559 5560 .seealso: TSGetEquationType(), TSEquationType 5561 @*/ 5562 PetscErrorCode TSSetEquationType(TS ts,TSEquationType equation_type) 5563 { 5564 PetscFunctionBegin; 5565 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5566 ts->equation_type = equation_type; 5567 PetscFunctionReturn(0); 5568 } 5569 5570 /*@ 5571 TSGetConvergedReason - Gets the reason the TS iteration was stopped. 5572 5573 Not Collective 5574 5575 Input Parameter: 5576 . ts - the TS context 5577 5578 Output Parameter: 5579 . reason - negative value indicates diverged, positive value converged, see TSConvergedReason or the 5580 manual pages for the individual convergence tests for complete lists 5581 5582 Level: beginner 5583 5584 Notes: 5585 Can only be called after the call to TSSolve() is complete. 5586 5587 .keywords: TS, nonlinear, set, convergence, test 5588 5589 .seealso: TSSetConvergenceTest(), TSConvergedReason 5590 @*/ 5591 PetscErrorCode TSGetConvergedReason(TS ts,TSConvergedReason *reason) 5592 { 5593 PetscFunctionBegin; 5594 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5595 PetscValidPointer(reason,2); 5596 *reason = ts->reason; 5597 PetscFunctionReturn(0); 5598 } 5599 5600 /*@ 5601 TSSetConvergedReason - Sets the reason for handling the convergence of TSSolve. 5602 5603 Not Collective 5604 5605 Input Parameter: 5606 + ts - the TS context 5607 . reason - negative value indicates diverged, positive value converged, see TSConvergedReason or the 5608 manual pages for the individual convergence tests for complete lists 5609 5610 Level: advanced 5611 5612 Notes: 5613 Can only be called during TSSolve() is active. 5614 5615 .keywords: TS, nonlinear, set, convergence, test 5616 5617 .seealso: TSConvergedReason 5618 @*/ 5619 PetscErrorCode TSSetConvergedReason(TS ts,TSConvergedReason reason) 5620 { 5621 PetscFunctionBegin; 5622 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5623 ts->reason = reason; 5624 PetscFunctionReturn(0); 5625 } 5626 5627 /*@ 5628 TSGetSolveTime - Gets the time after a call to TSSolve() 5629 5630 Not Collective 5631 5632 Input Parameter: 5633 . ts - the TS context 5634 5635 Output Parameter: 5636 . ftime - the final time. This time corresponds to the final time set with TSSetMaxTime() 5637 5638 Level: beginner 5639 5640 Notes: 5641 Can only be called after the call to TSSolve() is complete. 5642 5643 .keywords: TS, nonlinear, set, convergence, test 5644 5645 .seealso: TSSetConvergenceTest(), TSConvergedReason 5646 @*/ 5647 PetscErrorCode TSGetSolveTime(TS ts,PetscReal *ftime) 5648 { 5649 PetscFunctionBegin; 5650 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5651 PetscValidPointer(ftime,2); 5652 *ftime = ts->solvetime; 5653 PetscFunctionReturn(0); 5654 } 5655 5656 /*@ 5657 TSGetSNESIterations - Gets the total number of nonlinear iterations 5658 used by the time integrator. 5659 5660 Not Collective 5661 5662 Input Parameter: 5663 . ts - TS context 5664 5665 Output Parameter: 5666 . nits - number of nonlinear iterations 5667 5668 Notes: 5669 This counter is reset to zero for each successive call to TSSolve(). 5670 5671 Level: intermediate 5672 5673 .keywords: TS, get, number, nonlinear, iterations 5674 5675 .seealso: TSGetKSPIterations() 5676 @*/ 5677 PetscErrorCode TSGetSNESIterations(TS ts,PetscInt *nits) 5678 { 5679 PetscFunctionBegin; 5680 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5681 PetscValidIntPointer(nits,2); 5682 *nits = ts->snes_its; 5683 PetscFunctionReturn(0); 5684 } 5685 5686 /*@ 5687 TSGetKSPIterations - Gets the total number of linear iterations 5688 used by the time integrator. 5689 5690 Not Collective 5691 5692 Input Parameter: 5693 . ts - TS context 5694 5695 Output Parameter: 5696 . lits - number of linear iterations 5697 5698 Notes: 5699 This counter is reset to zero for each successive call to TSSolve(). 5700 5701 Level: intermediate 5702 5703 .keywords: TS, get, number, linear, iterations 5704 5705 .seealso: TSGetSNESIterations(), SNESGetKSPIterations() 5706 @*/ 5707 PetscErrorCode TSGetKSPIterations(TS ts,PetscInt *lits) 5708 { 5709 PetscFunctionBegin; 5710 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5711 PetscValidIntPointer(lits,2); 5712 *lits = ts->ksp_its; 5713 PetscFunctionReturn(0); 5714 } 5715 5716 /*@ 5717 TSGetStepRejections - Gets the total number of rejected steps. 5718 5719 Not Collective 5720 5721 Input Parameter: 5722 . ts - TS context 5723 5724 Output Parameter: 5725 . rejects - number of steps rejected 5726 5727 Notes: 5728 This counter is reset to zero for each successive call to TSSolve(). 5729 5730 Level: intermediate 5731 5732 .keywords: TS, get, number 5733 5734 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetSNESFailures(), TSSetMaxSNESFailures(), TSSetErrorIfStepFails() 5735 @*/ 5736 PetscErrorCode TSGetStepRejections(TS ts,PetscInt *rejects) 5737 { 5738 PetscFunctionBegin; 5739 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5740 PetscValidIntPointer(rejects,2); 5741 *rejects = ts->reject; 5742 PetscFunctionReturn(0); 5743 } 5744 5745 /*@ 5746 TSGetSNESFailures - Gets the total number of failed SNES solves 5747 5748 Not Collective 5749 5750 Input Parameter: 5751 . ts - TS context 5752 5753 Output Parameter: 5754 . fails - number of failed nonlinear solves 5755 5756 Notes: 5757 This counter is reset to zero for each successive call to TSSolve(). 5758 5759 Level: intermediate 5760 5761 .keywords: TS, get, number 5762 5763 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSSetMaxSNESFailures() 5764 @*/ 5765 PetscErrorCode TSGetSNESFailures(TS ts,PetscInt *fails) 5766 { 5767 PetscFunctionBegin; 5768 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5769 PetscValidIntPointer(fails,2); 5770 *fails = ts->num_snes_failures; 5771 PetscFunctionReturn(0); 5772 } 5773 5774 /*@ 5775 TSSetMaxStepRejections - Sets the maximum number of step rejections before a step fails 5776 5777 Not Collective 5778 5779 Input Parameter: 5780 + ts - TS context 5781 - rejects - maximum number of rejected steps, pass -1 for unlimited 5782 5783 Notes: 5784 The counter is reset to zero for each step 5785 5786 Options Database Key: 5787 . -ts_max_reject - Maximum number of step rejections before a step fails 5788 5789 Level: intermediate 5790 5791 .keywords: TS, set, maximum, number 5792 5793 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxSNESFailures(), TSGetStepRejections(), TSGetSNESFailures(), TSSetErrorIfStepFails(), TSGetConvergedReason() 5794 @*/ 5795 PetscErrorCode TSSetMaxStepRejections(TS ts,PetscInt rejects) 5796 { 5797 PetscFunctionBegin; 5798 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5799 ts->max_reject = rejects; 5800 PetscFunctionReturn(0); 5801 } 5802 5803 /*@ 5804 TSSetMaxSNESFailures - Sets the maximum number of failed SNES solves 5805 5806 Not Collective 5807 5808 Input Parameter: 5809 + ts - TS context 5810 - fails - maximum number of failed nonlinear solves, pass -1 for unlimited 5811 5812 Notes: 5813 The counter is reset to zero for each successive call to TSSolve(). 5814 5815 Options Database Key: 5816 . -ts_max_snes_failures - Maximum number of nonlinear solve failures 5817 5818 Level: intermediate 5819 5820 .keywords: TS, set, maximum, number 5821 5822 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSGetSNESFailures(), SNESGetConvergedReason(), TSGetConvergedReason() 5823 @*/ 5824 PetscErrorCode TSSetMaxSNESFailures(TS ts,PetscInt fails) 5825 { 5826 PetscFunctionBegin; 5827 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5828 ts->max_snes_failures = fails; 5829 PetscFunctionReturn(0); 5830 } 5831 5832 /*@ 5833 TSSetErrorIfStepFails - Error if no step succeeds 5834 5835 Not Collective 5836 5837 Input Parameter: 5838 + ts - TS context 5839 - err - PETSC_TRUE to error if no step succeeds, PETSC_FALSE to return without failure 5840 5841 Options Database Key: 5842 . -ts_error_if_step_fails - Error if no step succeeds 5843 5844 Level: intermediate 5845 5846 .keywords: TS, set, error 5847 5848 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSGetSNESFailures(), TSSetErrorIfStepFails(), TSGetConvergedReason() 5849 @*/ 5850 PetscErrorCode TSSetErrorIfStepFails(TS ts,PetscBool err) 5851 { 5852 PetscFunctionBegin; 5853 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5854 ts->errorifstepfailed = err; 5855 PetscFunctionReturn(0); 5856 } 5857 5858 /*@C 5859 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 5860 5861 Collective on TS 5862 5863 Input Parameters: 5864 + ts - the TS context 5865 . step - current time-step 5866 . ptime - current time 5867 . u - current state 5868 - vf - viewer and its format 5869 5870 Level: intermediate 5871 5872 .keywords: TS, vector, monitor, view 5873 5874 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 5875 @*/ 5876 PetscErrorCode TSMonitorSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,PetscViewerAndFormat *vf) 5877 { 5878 PetscErrorCode ierr; 5879 5880 PetscFunctionBegin; 5881 ierr = PetscViewerPushFormat(vf->viewer,vf->format);CHKERRQ(ierr); 5882 ierr = VecView(u,vf->viewer);CHKERRQ(ierr); 5883 ierr = PetscViewerPopFormat(vf->viewer);CHKERRQ(ierr); 5884 PetscFunctionReturn(0); 5885 } 5886 5887 /*@C 5888 TSMonitorSolutionVTK - Monitors progress of the TS solvers by VecView() for the solution at each timestep. 5889 5890 Collective on TS 5891 5892 Input Parameters: 5893 + ts - the TS context 5894 . step - current time-step 5895 . ptime - current time 5896 . u - current state 5897 - filenametemplate - string containing a format specifier for the integer time step (e.g. %03D) 5898 5899 Level: intermediate 5900 5901 Notes: 5902 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. 5903 These are named according to the file name template. 5904 5905 This function is normally passed as an argument to TSMonitorSet() along with TSMonitorSolutionVTKDestroy(). 5906 5907 .keywords: TS, vector, monitor, view 5908 5909 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 5910 @*/ 5911 PetscErrorCode TSMonitorSolutionVTK(TS ts,PetscInt step,PetscReal ptime,Vec u,void *filenametemplate) 5912 { 5913 PetscErrorCode ierr; 5914 char filename[PETSC_MAX_PATH_LEN]; 5915 PetscViewer viewer; 5916 5917 PetscFunctionBegin; 5918 if (step < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */ 5919 ierr = PetscSNPrintf(filename,sizeof(filename),(const char*)filenametemplate,step);CHKERRQ(ierr); 5920 ierr = PetscViewerVTKOpen(PetscObjectComm((PetscObject)ts),filename,FILE_MODE_WRITE,&viewer);CHKERRQ(ierr); 5921 ierr = VecView(u,viewer);CHKERRQ(ierr); 5922 ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr); 5923 PetscFunctionReturn(0); 5924 } 5925 5926 /*@C 5927 TSMonitorSolutionVTKDestroy - Destroy context for monitoring 5928 5929 Collective on TS 5930 5931 Input Parameters: 5932 . filenametemplate - string containing a format specifier for the integer time step (e.g. %03D) 5933 5934 Level: intermediate 5935 5936 Note: 5937 This function is normally passed to TSMonitorSet() along with TSMonitorSolutionVTK(). 5938 5939 .keywords: TS, vector, monitor, view 5940 5941 .seealso: TSMonitorSet(), TSMonitorSolutionVTK() 5942 @*/ 5943 PetscErrorCode TSMonitorSolutionVTKDestroy(void *filenametemplate) 5944 { 5945 PetscErrorCode ierr; 5946 5947 PetscFunctionBegin; 5948 ierr = PetscFree(*(char**)filenametemplate);CHKERRQ(ierr); 5949 PetscFunctionReturn(0); 5950 } 5951 5952 /*@ 5953 TSGetAdapt - Get the adaptive controller context for the current method 5954 5955 Collective on TS if controller has not been created yet 5956 5957 Input Arguments: 5958 . ts - time stepping context 5959 5960 Output Arguments: 5961 . adapt - adaptive controller 5962 5963 Level: intermediate 5964 5965 .seealso: TSAdapt, TSAdaptSetType(), TSAdaptChoose() 5966 @*/ 5967 PetscErrorCode TSGetAdapt(TS ts,TSAdapt *adapt) 5968 { 5969 PetscErrorCode ierr; 5970 5971 PetscFunctionBegin; 5972 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5973 PetscValidPointer(adapt,2); 5974 if (!ts->adapt) { 5975 ierr = TSAdaptCreate(PetscObjectComm((PetscObject)ts),&ts->adapt);CHKERRQ(ierr); 5976 ierr = PetscLogObjectParent((PetscObject)ts,(PetscObject)ts->adapt);CHKERRQ(ierr); 5977 ierr = PetscObjectIncrementTabLevel((PetscObject)ts->adapt,(PetscObject)ts,1);CHKERRQ(ierr); 5978 } 5979 *adapt = ts->adapt; 5980 PetscFunctionReturn(0); 5981 } 5982 5983 /*@ 5984 TSSetTolerances - Set tolerances for local truncation error when using adaptive controller 5985 5986 Logically Collective 5987 5988 Input Arguments: 5989 + ts - time integration context 5990 . atol - scalar absolute tolerances, PETSC_DECIDE to leave current value 5991 . vatol - vector of absolute tolerances or NULL, used in preference to atol if present 5992 . rtol - scalar relative tolerances, PETSC_DECIDE to leave current value 5993 - vrtol - vector of relative tolerances or NULL, used in preference to atol if present 5994 5995 Options Database keys: 5996 + -ts_rtol <rtol> - relative tolerance for local truncation error 5997 - -ts_atol <atol> Absolute tolerance for local truncation error 5998 5999 Notes: 6000 With PETSc's implicit schemes for DAE problems, the calculation of the local truncation error 6001 (LTE) includes both the differential and the algebraic variables. If one wants the LTE to be 6002 computed only for the differential or the algebraic part then this can be done using the vector of 6003 tolerances vatol. For example, by setting the tolerance vector with the desired tolerance for the 6004 differential part and infinity for the algebraic part, the LTE calculation will include only the 6005 differential variables. 6006 6007 Level: beginner 6008 6009 .seealso: TS, TSAdapt, TSVecNormWRMS(), TSGetTolerances() 6010 @*/ 6011 PetscErrorCode TSSetTolerances(TS ts,PetscReal atol,Vec vatol,PetscReal rtol,Vec vrtol) 6012 { 6013 PetscErrorCode ierr; 6014 6015 PetscFunctionBegin; 6016 if (atol != PETSC_DECIDE && atol != PETSC_DEFAULT) ts->atol = atol; 6017 if (vatol) { 6018 ierr = PetscObjectReference((PetscObject)vatol);CHKERRQ(ierr); 6019 ierr = VecDestroy(&ts->vatol);CHKERRQ(ierr); 6020 ts->vatol = vatol; 6021 } 6022 if (rtol != PETSC_DECIDE && rtol != PETSC_DEFAULT) ts->rtol = rtol; 6023 if (vrtol) { 6024 ierr = PetscObjectReference((PetscObject)vrtol);CHKERRQ(ierr); 6025 ierr = VecDestroy(&ts->vrtol);CHKERRQ(ierr); 6026 ts->vrtol = vrtol; 6027 } 6028 PetscFunctionReturn(0); 6029 } 6030 6031 /*@ 6032 TSGetTolerances - Get tolerances for local truncation error when using adaptive controller 6033 6034 Logically Collective 6035 6036 Input Arguments: 6037 . ts - time integration context 6038 6039 Output Arguments: 6040 + atol - scalar absolute tolerances, NULL to ignore 6041 . vatol - vector of absolute tolerances, NULL to ignore 6042 . rtol - scalar relative tolerances, NULL to ignore 6043 - vrtol - vector of relative tolerances, NULL to ignore 6044 6045 Level: beginner 6046 6047 .seealso: TS, TSAdapt, TSVecNormWRMS(), TSSetTolerances() 6048 @*/ 6049 PetscErrorCode TSGetTolerances(TS ts,PetscReal *atol,Vec *vatol,PetscReal *rtol,Vec *vrtol) 6050 { 6051 PetscFunctionBegin; 6052 if (atol) *atol = ts->atol; 6053 if (vatol) *vatol = ts->vatol; 6054 if (rtol) *rtol = ts->rtol; 6055 if (vrtol) *vrtol = ts->vrtol; 6056 PetscFunctionReturn(0); 6057 } 6058 6059 /*@ 6060 TSErrorWeightedNorm2 - compute a weighted 2-norm of the difference between two state vectors 6061 6062 Collective on TS 6063 6064 Input Arguments: 6065 + ts - time stepping context 6066 . U - state vector, usually ts->vec_sol 6067 - Y - state vector to be compared to U 6068 6069 Output Arguments: 6070 . norm - weighted norm, a value of 1.0 means that the error matches the tolerances 6071 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 6072 . normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 6073 6074 Level: developer 6075 6076 .seealso: TSErrorWeightedNorm(), TSErrorWeightedNormInfinity() 6077 @*/ 6078 PetscErrorCode TSErrorWeightedNorm2(TS ts,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6079 { 6080 PetscErrorCode ierr; 6081 PetscInt i,n,N,rstart; 6082 PetscInt n_loc,na_loc,nr_loc; 6083 PetscReal n_glb,na_glb,nr_glb; 6084 const PetscScalar *u,*y; 6085 PetscReal sum,suma,sumr,gsum,gsuma,gsumr,diff; 6086 PetscReal tol,tola,tolr; 6087 PetscReal err_loc[6],err_glb[6]; 6088 6089 PetscFunctionBegin; 6090 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6091 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 6092 PetscValidHeaderSpecific(Y,VEC_CLASSID,3); 6093 PetscValidType(U,2); 6094 PetscValidType(Y,3); 6095 PetscCheckSameComm(U,2,Y,3); 6096 PetscValidPointer(norm,4); 6097 PetscValidPointer(norma,5); 6098 PetscValidPointer(normr,6); 6099 if (U == Y) SETERRQ(PetscObjectComm((PetscObject)U),PETSC_ERR_ARG_IDN,"U and Y cannot be the same vector"); 6100 6101 ierr = VecGetSize(U,&N);CHKERRQ(ierr); 6102 ierr = VecGetLocalSize(U,&n);CHKERRQ(ierr); 6103 ierr = VecGetOwnershipRange(U,&rstart,NULL);CHKERRQ(ierr); 6104 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 6105 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 6106 sum = 0.; n_loc = 0; 6107 suma = 0.; na_loc = 0; 6108 sumr = 0.; nr_loc = 0; 6109 if (ts->vatol && ts->vrtol) { 6110 const PetscScalar *atol,*rtol; 6111 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6112 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6113 for (i=0; i<n; i++) { 6114 diff = PetscAbsScalar(y[i] - u[i]); 6115 tola = PetscRealPart(atol[i]); 6116 if(tola>0.){ 6117 suma += PetscSqr(diff/tola); 6118 na_loc++; 6119 } 6120 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6121 if(tolr>0.){ 6122 sumr += PetscSqr(diff/tolr); 6123 nr_loc++; 6124 } 6125 tol=tola+tolr; 6126 if(tol>0.){ 6127 sum += PetscSqr(diff/tol); 6128 n_loc++; 6129 } 6130 } 6131 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6132 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6133 } else if (ts->vatol) { /* vector atol, scalar rtol */ 6134 const PetscScalar *atol; 6135 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6136 for (i=0; i<n; i++) { 6137 diff = PetscAbsScalar(y[i] - u[i]); 6138 tola = PetscRealPart(atol[i]); 6139 if(tola>0.){ 6140 suma += PetscSqr(diff/tola); 6141 na_loc++; 6142 } 6143 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6144 if(tolr>0.){ 6145 sumr += PetscSqr(diff/tolr); 6146 nr_loc++; 6147 } 6148 tol=tola+tolr; 6149 if(tol>0.){ 6150 sum += PetscSqr(diff/tol); 6151 n_loc++; 6152 } 6153 } 6154 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6155 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 6156 const PetscScalar *rtol; 6157 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6158 for (i=0; i<n; i++) { 6159 diff = PetscAbsScalar(y[i] - u[i]); 6160 tola = ts->atol; 6161 if(tola>0.){ 6162 suma += PetscSqr(diff/tola); 6163 na_loc++; 6164 } 6165 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6166 if(tolr>0.){ 6167 sumr += PetscSqr(diff/tolr); 6168 nr_loc++; 6169 } 6170 tol=tola+tolr; 6171 if(tol>0.){ 6172 sum += PetscSqr(diff/tol); 6173 n_loc++; 6174 } 6175 } 6176 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6177 } else { /* scalar atol, scalar rtol */ 6178 for (i=0; i<n; i++) { 6179 diff = PetscAbsScalar(y[i] - u[i]); 6180 tola = ts->atol; 6181 if(tola>0.){ 6182 suma += PetscSqr(diff/tola); 6183 na_loc++; 6184 } 6185 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6186 if(tolr>0.){ 6187 sumr += PetscSqr(diff/tolr); 6188 nr_loc++; 6189 } 6190 tol=tola+tolr; 6191 if(tol>0.){ 6192 sum += PetscSqr(diff/tol); 6193 n_loc++; 6194 } 6195 } 6196 } 6197 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 6198 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 6199 6200 err_loc[0] = sum; 6201 err_loc[1] = suma; 6202 err_loc[2] = sumr; 6203 err_loc[3] = (PetscReal)n_loc; 6204 err_loc[4] = (PetscReal)na_loc; 6205 err_loc[5] = (PetscReal)nr_loc; 6206 6207 ierr = MPIU_Allreduce(err_loc,err_glb,6,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6208 6209 gsum = err_glb[0]; 6210 gsuma = err_glb[1]; 6211 gsumr = err_glb[2]; 6212 n_glb = err_glb[3]; 6213 na_glb = err_glb[4]; 6214 nr_glb = err_glb[5]; 6215 6216 *norm = 0.; 6217 if(n_glb>0. ){*norm = PetscSqrtReal(gsum / n_glb );} 6218 *norma = 0.; 6219 if(na_glb>0.){*norma = PetscSqrtReal(gsuma / na_glb);} 6220 *normr = 0.; 6221 if(nr_glb>0.){*normr = PetscSqrtReal(gsumr / nr_glb);} 6222 6223 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 6224 if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 6225 if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 6226 PetscFunctionReturn(0); 6227 } 6228 6229 /*@ 6230 TSErrorWeightedNormInfinity - compute a weighted infinity-norm of the difference between two state vectors 6231 6232 Collective on TS 6233 6234 Input Arguments: 6235 + ts - time stepping context 6236 . U - state vector, usually ts->vec_sol 6237 - Y - state vector to be compared to U 6238 6239 Output Arguments: 6240 . norm - weighted norm, a value of 1.0 means that the error matches the tolerances 6241 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 6242 . normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 6243 6244 Level: developer 6245 6246 .seealso: TSErrorWeightedNorm(), TSErrorWeightedNorm2() 6247 @*/ 6248 PetscErrorCode TSErrorWeightedNormInfinity(TS ts,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6249 { 6250 PetscErrorCode ierr; 6251 PetscInt i,n,N,rstart; 6252 const PetscScalar *u,*y; 6253 PetscReal max,gmax,maxa,gmaxa,maxr,gmaxr; 6254 PetscReal tol,tola,tolr,diff; 6255 PetscReal err_loc[3],err_glb[3]; 6256 6257 PetscFunctionBegin; 6258 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6259 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 6260 PetscValidHeaderSpecific(Y,VEC_CLASSID,3); 6261 PetscValidType(U,2); 6262 PetscValidType(Y,3); 6263 PetscCheckSameComm(U,2,Y,3); 6264 PetscValidPointer(norm,4); 6265 PetscValidPointer(norma,5); 6266 PetscValidPointer(normr,6); 6267 if (U == Y) SETERRQ(PetscObjectComm((PetscObject)U),PETSC_ERR_ARG_IDN,"U and Y cannot be the same vector"); 6268 6269 ierr = VecGetSize(U,&N);CHKERRQ(ierr); 6270 ierr = VecGetLocalSize(U,&n);CHKERRQ(ierr); 6271 ierr = VecGetOwnershipRange(U,&rstart,NULL);CHKERRQ(ierr); 6272 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 6273 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 6274 6275 max=0.; 6276 maxa=0.; 6277 maxr=0.; 6278 6279 if (ts->vatol && ts->vrtol) { /* vector atol, vector rtol */ 6280 const PetscScalar *atol,*rtol; 6281 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6282 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6283 6284 for (i=0; i<n; i++) { 6285 diff = PetscAbsScalar(y[i] - u[i]); 6286 tola = PetscRealPart(atol[i]); 6287 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6288 tol = tola+tolr; 6289 if(tola>0.){ 6290 maxa = PetscMax(maxa,diff / tola); 6291 } 6292 if(tolr>0.){ 6293 maxr = PetscMax(maxr,diff / tolr); 6294 } 6295 if(tol>0.){ 6296 max = PetscMax(max,diff / tol); 6297 } 6298 } 6299 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6300 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6301 } else if (ts->vatol) { /* vector atol, scalar rtol */ 6302 const PetscScalar *atol; 6303 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6304 for (i=0; i<n; i++) { 6305 diff = PetscAbsScalar(y[i] - u[i]); 6306 tola = PetscRealPart(atol[i]); 6307 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6308 tol = tola+tolr; 6309 if(tola>0.){ 6310 maxa = PetscMax(maxa,diff / tola); 6311 } 6312 if(tolr>0.){ 6313 maxr = PetscMax(maxr,diff / tolr); 6314 } 6315 if(tol>0.){ 6316 max = PetscMax(max,diff / tol); 6317 } 6318 } 6319 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6320 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 6321 const PetscScalar *rtol; 6322 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6323 6324 for (i=0; i<n; i++) { 6325 diff = PetscAbsScalar(y[i] - u[i]); 6326 tola = ts->atol; 6327 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6328 tol = tola+tolr; 6329 if(tola>0.){ 6330 maxa = PetscMax(maxa,diff / tola); 6331 } 6332 if(tolr>0.){ 6333 maxr = PetscMax(maxr,diff / tolr); 6334 } 6335 if(tol>0.){ 6336 max = PetscMax(max,diff / tol); 6337 } 6338 } 6339 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6340 } else { /* scalar atol, scalar rtol */ 6341 6342 for (i=0; i<n; i++) { 6343 diff = PetscAbsScalar(y[i] - u[i]); 6344 tola = ts->atol; 6345 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6346 tol = tola+tolr; 6347 if(tola>0.){ 6348 maxa = PetscMax(maxa,diff / tola); 6349 } 6350 if(tolr>0.){ 6351 maxr = PetscMax(maxr,diff / tolr); 6352 } 6353 if(tol>0.){ 6354 max = PetscMax(max,diff / tol); 6355 } 6356 } 6357 } 6358 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 6359 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 6360 err_loc[0] = max; 6361 err_loc[1] = maxa; 6362 err_loc[2] = maxr; 6363 ierr = MPIU_Allreduce(err_loc,err_glb,3,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6364 gmax = err_glb[0]; 6365 gmaxa = err_glb[1]; 6366 gmaxr = err_glb[2]; 6367 6368 *norm = gmax; 6369 *norma = gmaxa; 6370 *normr = gmaxr; 6371 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 6372 if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 6373 if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 6374 PetscFunctionReturn(0); 6375 } 6376 6377 /*@ 6378 TSErrorWeightedNorm - compute a weighted norm of the difference between two state vectors based on supplied absolute and relative tolerances 6379 6380 Collective on TS 6381 6382 Input Arguments: 6383 + ts - time stepping context 6384 . U - state vector, usually ts->vec_sol 6385 . Y - state vector to be compared to U 6386 - wnormtype - norm type, either NORM_2 or NORM_INFINITY 6387 6388 Output Arguments: 6389 . norm - weighted norm, a value of 1.0 achieves a balance between absolute and relative tolerances 6390 . norma - weighted norm, a value of 1.0 means that the error meets the absolute tolerance set by the user 6391 . normr - weighted norm, a value of 1.0 means that the error meets the relative tolerance set by the user 6392 6393 Options Database Keys: 6394 . -ts_adapt_wnormtype <wnormtype> - 2, INFINITY 6395 6396 Level: developer 6397 6398 .seealso: TSErrorWeightedNormInfinity(), TSErrorWeightedNorm2(), TSErrorWeightedENorm 6399 @*/ 6400 PetscErrorCode TSErrorWeightedNorm(TS ts,Vec U,Vec Y,NormType wnormtype,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6401 { 6402 PetscErrorCode ierr; 6403 6404 PetscFunctionBegin; 6405 if (wnormtype == NORM_2) { 6406 ierr = TSErrorWeightedNorm2(ts,U,Y,norm,norma,normr);CHKERRQ(ierr); 6407 } else if(wnormtype == NORM_INFINITY) { 6408 ierr = TSErrorWeightedNormInfinity(ts,U,Y,norm,norma,normr);CHKERRQ(ierr); 6409 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]); 6410 PetscFunctionReturn(0); 6411 } 6412 6413 6414 /*@ 6415 TSErrorWeightedENorm2 - compute a weighted 2 error norm based on supplied absolute and relative tolerances 6416 6417 Collective on TS 6418 6419 Input Arguments: 6420 + ts - time stepping context 6421 . E - error vector 6422 . U - state vector, usually ts->vec_sol 6423 - Y - state vector, previous time step 6424 6425 Output Arguments: 6426 . norm - weighted norm, a value of 1.0 means that the error matches the tolerances 6427 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 6428 . normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 6429 6430 Level: developer 6431 6432 .seealso: TSErrorWeightedENorm(), TSErrorWeightedENormInfinity() 6433 @*/ 6434 PetscErrorCode TSErrorWeightedENorm2(TS ts,Vec E,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6435 { 6436 PetscErrorCode ierr; 6437 PetscInt i,n,N,rstart; 6438 PetscInt n_loc,na_loc,nr_loc; 6439 PetscReal n_glb,na_glb,nr_glb; 6440 const PetscScalar *e,*u,*y; 6441 PetscReal err,sum,suma,sumr,gsum,gsuma,gsumr; 6442 PetscReal tol,tola,tolr; 6443 PetscReal err_loc[6],err_glb[6]; 6444 6445 PetscFunctionBegin; 6446 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6447 PetscValidHeaderSpecific(E,VEC_CLASSID,2); 6448 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 6449 PetscValidHeaderSpecific(Y,VEC_CLASSID,4); 6450 PetscValidType(E,2); 6451 PetscValidType(U,3); 6452 PetscValidType(Y,4); 6453 PetscCheckSameComm(E,2,U,3); 6454 PetscCheckSameComm(U,2,Y,3); 6455 PetscValidPointer(norm,5); 6456 PetscValidPointer(norma,6); 6457 PetscValidPointer(normr,7); 6458 6459 ierr = VecGetSize(E,&N);CHKERRQ(ierr); 6460 ierr = VecGetLocalSize(E,&n);CHKERRQ(ierr); 6461 ierr = VecGetOwnershipRange(E,&rstart,NULL);CHKERRQ(ierr); 6462 ierr = VecGetArrayRead(E,&e);CHKERRQ(ierr); 6463 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 6464 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 6465 sum = 0.; n_loc = 0; 6466 suma = 0.; na_loc = 0; 6467 sumr = 0.; nr_loc = 0; 6468 if (ts->vatol && ts->vrtol) { 6469 const PetscScalar *atol,*rtol; 6470 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6471 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6472 for (i=0; i<n; i++) { 6473 err = PetscAbsScalar(e[i]); 6474 tola = PetscRealPart(atol[i]); 6475 if(tola>0.){ 6476 suma += PetscSqr(err/tola); 6477 na_loc++; 6478 } 6479 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6480 if(tolr>0.){ 6481 sumr += PetscSqr(err/tolr); 6482 nr_loc++; 6483 } 6484 tol=tola+tolr; 6485 if(tol>0.){ 6486 sum += PetscSqr(err/tol); 6487 n_loc++; 6488 } 6489 } 6490 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6491 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6492 } else if (ts->vatol) { /* vector atol, scalar rtol */ 6493 const PetscScalar *atol; 6494 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6495 for (i=0; i<n; i++) { 6496 err = PetscAbsScalar(e[i]); 6497 tola = PetscRealPart(atol[i]); 6498 if(tola>0.){ 6499 suma += PetscSqr(err/tola); 6500 na_loc++; 6501 } 6502 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6503 if(tolr>0.){ 6504 sumr += PetscSqr(err/tolr); 6505 nr_loc++; 6506 } 6507 tol=tola+tolr; 6508 if(tol>0.){ 6509 sum += PetscSqr(err/tol); 6510 n_loc++; 6511 } 6512 } 6513 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6514 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 6515 const PetscScalar *rtol; 6516 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6517 for (i=0; i<n; i++) { 6518 err = PetscAbsScalar(e[i]); 6519 tola = ts->atol; 6520 if(tola>0.){ 6521 suma += PetscSqr(err/tola); 6522 na_loc++; 6523 } 6524 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6525 if(tolr>0.){ 6526 sumr += PetscSqr(err/tolr); 6527 nr_loc++; 6528 } 6529 tol=tola+tolr; 6530 if(tol>0.){ 6531 sum += PetscSqr(err/tol); 6532 n_loc++; 6533 } 6534 } 6535 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6536 } else { /* scalar atol, scalar rtol */ 6537 for (i=0; i<n; i++) { 6538 err = PetscAbsScalar(e[i]); 6539 tola = ts->atol; 6540 if(tola>0.){ 6541 suma += PetscSqr(err/tola); 6542 na_loc++; 6543 } 6544 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6545 if(tolr>0.){ 6546 sumr += PetscSqr(err/tolr); 6547 nr_loc++; 6548 } 6549 tol=tola+tolr; 6550 if(tol>0.){ 6551 sum += PetscSqr(err/tol); 6552 n_loc++; 6553 } 6554 } 6555 } 6556 ierr = VecRestoreArrayRead(E,&e);CHKERRQ(ierr); 6557 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 6558 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 6559 6560 err_loc[0] = sum; 6561 err_loc[1] = suma; 6562 err_loc[2] = sumr; 6563 err_loc[3] = (PetscReal)n_loc; 6564 err_loc[4] = (PetscReal)na_loc; 6565 err_loc[5] = (PetscReal)nr_loc; 6566 6567 ierr = MPIU_Allreduce(err_loc,err_glb,6,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6568 6569 gsum = err_glb[0]; 6570 gsuma = err_glb[1]; 6571 gsumr = err_glb[2]; 6572 n_glb = err_glb[3]; 6573 na_glb = err_glb[4]; 6574 nr_glb = err_glb[5]; 6575 6576 *norm = 0.; 6577 if(n_glb>0. ){*norm = PetscSqrtReal(gsum / n_glb );} 6578 *norma = 0.; 6579 if(na_glb>0.){*norma = PetscSqrtReal(gsuma / na_glb);} 6580 *normr = 0.; 6581 if(nr_glb>0.){*normr = PetscSqrtReal(gsumr / nr_glb);} 6582 6583 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 6584 if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 6585 if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 6586 PetscFunctionReturn(0); 6587 } 6588 6589 /*@ 6590 TSErrorWeightedENormInfinity - compute a weighted infinity error norm based on supplied absolute and relative tolerances 6591 Collective on TS 6592 6593 Input Arguments: 6594 + ts - time stepping context 6595 . E - error vector 6596 . U - state vector, usually ts->vec_sol 6597 - Y - state vector, previous time step 6598 6599 Output Arguments: 6600 . norm - weighted norm, a value of 1.0 means that the error matches the tolerances 6601 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 6602 . normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 6603 6604 Level: developer 6605 6606 .seealso: TSErrorWeightedENorm(), TSErrorWeightedENorm2() 6607 @*/ 6608 PetscErrorCode TSErrorWeightedENormInfinity(TS ts,Vec E,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6609 { 6610 PetscErrorCode ierr; 6611 PetscInt i,n,N,rstart; 6612 const PetscScalar *e,*u,*y; 6613 PetscReal err,max,gmax,maxa,gmaxa,maxr,gmaxr; 6614 PetscReal tol,tola,tolr; 6615 PetscReal err_loc[3],err_glb[3]; 6616 6617 PetscFunctionBegin; 6618 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6619 PetscValidHeaderSpecific(E,VEC_CLASSID,2); 6620 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 6621 PetscValidHeaderSpecific(Y,VEC_CLASSID,4); 6622 PetscValidType(E,2); 6623 PetscValidType(U,3); 6624 PetscValidType(Y,4); 6625 PetscCheckSameComm(E,2,U,3); 6626 PetscCheckSameComm(U,2,Y,3); 6627 PetscValidPointer(norm,5); 6628 PetscValidPointer(norma,6); 6629 PetscValidPointer(normr,7); 6630 6631 ierr = VecGetSize(E,&N);CHKERRQ(ierr); 6632 ierr = VecGetLocalSize(E,&n);CHKERRQ(ierr); 6633 ierr = VecGetOwnershipRange(E,&rstart,NULL);CHKERRQ(ierr); 6634 ierr = VecGetArrayRead(E,&e);CHKERRQ(ierr); 6635 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 6636 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 6637 6638 max=0.; 6639 maxa=0.; 6640 maxr=0.; 6641 6642 if (ts->vatol && ts->vrtol) { /* vector atol, vector rtol */ 6643 const PetscScalar *atol,*rtol; 6644 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6645 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6646 6647 for (i=0; i<n; i++) { 6648 err = PetscAbsScalar(e[i]); 6649 tola = PetscRealPart(atol[i]); 6650 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6651 tol = tola+tolr; 6652 if(tola>0.){ 6653 maxa = PetscMax(maxa,err / tola); 6654 } 6655 if(tolr>0.){ 6656 maxr = PetscMax(maxr,err / tolr); 6657 } 6658 if(tol>0.){ 6659 max = PetscMax(max,err / tol); 6660 } 6661 } 6662 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6663 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6664 } else if (ts->vatol) { /* vector atol, scalar rtol */ 6665 const PetscScalar *atol; 6666 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6667 for (i=0; i<n; i++) { 6668 err = PetscAbsScalar(e[i]); 6669 tola = PetscRealPart(atol[i]); 6670 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6671 tol = tola+tolr; 6672 if(tola>0.){ 6673 maxa = PetscMax(maxa,err / tola); 6674 } 6675 if(tolr>0.){ 6676 maxr = PetscMax(maxr,err / tolr); 6677 } 6678 if(tol>0.){ 6679 max = PetscMax(max,err / tol); 6680 } 6681 } 6682 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6683 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 6684 const PetscScalar *rtol; 6685 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6686 6687 for (i=0; i<n; i++) { 6688 err = PetscAbsScalar(e[i]); 6689 tola = ts->atol; 6690 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6691 tol = tola+tolr; 6692 if(tola>0.){ 6693 maxa = PetscMax(maxa,err / tola); 6694 } 6695 if(tolr>0.){ 6696 maxr = PetscMax(maxr,err / tolr); 6697 } 6698 if(tol>0.){ 6699 max = PetscMax(max,err / tol); 6700 } 6701 } 6702 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6703 } else { /* scalar atol, scalar rtol */ 6704 6705 for (i=0; i<n; i++) { 6706 err = PetscAbsScalar(e[i]); 6707 tola = ts->atol; 6708 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6709 tol = tola+tolr; 6710 if(tola>0.){ 6711 maxa = PetscMax(maxa,err / tola); 6712 } 6713 if(tolr>0.){ 6714 maxr = PetscMax(maxr,err / tolr); 6715 } 6716 if(tol>0.){ 6717 max = PetscMax(max,err / tol); 6718 } 6719 } 6720 } 6721 ierr = VecRestoreArrayRead(E,&e);CHKERRQ(ierr); 6722 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 6723 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 6724 err_loc[0] = max; 6725 err_loc[1] = maxa; 6726 err_loc[2] = maxr; 6727 ierr = MPIU_Allreduce(err_loc,err_glb,3,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6728 gmax = err_glb[0]; 6729 gmaxa = err_glb[1]; 6730 gmaxr = err_glb[2]; 6731 6732 *norm = gmax; 6733 *norma = gmaxa; 6734 *normr = gmaxr; 6735 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 6736 if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 6737 if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 6738 PetscFunctionReturn(0); 6739 } 6740 6741 /*@ 6742 TSErrorWeightedENorm - compute a weighted error norm based on supplied absolute and relative tolerances 6743 6744 Collective on TS 6745 6746 Input Arguments: 6747 + ts - time stepping context 6748 . E - error vector 6749 . U - state vector, usually ts->vec_sol 6750 . Y - state vector, previous time step 6751 - wnormtype - norm type, either NORM_2 or NORM_INFINITY 6752 6753 Output Arguments: 6754 . norm - weighted norm, a value of 1.0 achieves a balance between absolute and relative tolerances 6755 . norma - weighted norm, a value of 1.0 means that the error meets the absolute tolerance set by the user 6756 . normr - weighted norm, a value of 1.0 means that the error meets the relative tolerance set by the user 6757 6758 Options Database Keys: 6759 . -ts_adapt_wnormtype <wnormtype> - 2, INFINITY 6760 6761 Level: developer 6762 6763 .seealso: TSErrorWeightedENormInfinity(), TSErrorWeightedENorm2(), TSErrorWeightedNormInfinity(), TSErrorWeightedNorm2() 6764 @*/ 6765 PetscErrorCode TSErrorWeightedENorm(TS ts,Vec E,Vec U,Vec Y,NormType wnormtype,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6766 { 6767 PetscErrorCode ierr; 6768 6769 PetscFunctionBegin; 6770 if (wnormtype == NORM_2) { 6771 ierr = TSErrorWeightedENorm2(ts,E,U,Y,norm,norma,normr);CHKERRQ(ierr); 6772 } else if(wnormtype == NORM_INFINITY) { 6773 ierr = TSErrorWeightedENormInfinity(ts,E,U,Y,norm,norma,normr);CHKERRQ(ierr); 6774 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]); 6775 PetscFunctionReturn(0); 6776 } 6777 6778 6779 /*@ 6780 TSSetCFLTimeLocal - Set the local CFL constraint relative to forward Euler 6781 6782 Logically Collective on TS 6783 6784 Input Arguments: 6785 + ts - time stepping context 6786 - cfltime - maximum stable time step if using forward Euler (value can be different on each process) 6787 6788 Note: 6789 After calling this function, the global CFL time can be obtained by calling TSGetCFLTime() 6790 6791 Level: intermediate 6792 6793 .seealso: TSGetCFLTime(), TSADAPTCFL 6794 @*/ 6795 PetscErrorCode TSSetCFLTimeLocal(TS ts,PetscReal cfltime) 6796 { 6797 PetscFunctionBegin; 6798 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6799 ts->cfltime_local = cfltime; 6800 ts->cfltime = -1.; 6801 PetscFunctionReturn(0); 6802 } 6803 6804 /*@ 6805 TSGetCFLTime - Get the maximum stable time step according to CFL criteria applied to forward Euler 6806 6807 Collective on TS 6808 6809 Input Arguments: 6810 . ts - time stepping context 6811 6812 Output Arguments: 6813 . cfltime - maximum stable time step for forward Euler 6814 6815 Level: advanced 6816 6817 .seealso: TSSetCFLTimeLocal() 6818 @*/ 6819 PetscErrorCode TSGetCFLTime(TS ts,PetscReal *cfltime) 6820 { 6821 PetscErrorCode ierr; 6822 6823 PetscFunctionBegin; 6824 if (ts->cfltime < 0) { 6825 ierr = MPIU_Allreduce(&ts->cfltime_local,&ts->cfltime,1,MPIU_REAL,MPIU_MIN,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6826 } 6827 *cfltime = ts->cfltime; 6828 PetscFunctionReturn(0); 6829 } 6830 6831 /*@ 6832 TSVISetVariableBounds - Sets the lower and upper bounds for the solution vector. xl <= x <= xu 6833 6834 Input Parameters: 6835 . ts - the TS context. 6836 . xl - lower bound. 6837 . xu - upper bound. 6838 6839 Notes: 6840 If this routine is not called then the lower and upper bounds are set to 6841 PETSC_NINFINITY and PETSC_INFINITY respectively during SNESSetUp(). 6842 6843 Level: advanced 6844 6845 @*/ 6846 PetscErrorCode TSVISetVariableBounds(TS ts, Vec xl, Vec xu) 6847 { 6848 PetscErrorCode ierr; 6849 SNES snes; 6850 6851 PetscFunctionBegin; 6852 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 6853 ierr = SNESVISetVariableBounds(snes,xl,xu);CHKERRQ(ierr); 6854 PetscFunctionReturn(0); 6855 } 6856 6857 #if defined(PETSC_HAVE_MATLAB_ENGINE) 6858 #include <mex.h> 6859 6860 typedef struct {char *funcname; mxArray *ctx;} TSMatlabContext; 6861 6862 /* 6863 TSComputeFunction_Matlab - Calls the function that has been set with 6864 TSSetFunctionMatlab(). 6865 6866 Collective on TS 6867 6868 Input Parameters: 6869 + snes - the TS context 6870 - u - input vector 6871 6872 Output Parameter: 6873 . y - function vector, as set by TSSetFunction() 6874 6875 Notes: 6876 TSComputeFunction() is typically used within nonlinear solvers 6877 implementations, so most users would not generally call this routine 6878 themselves. 6879 6880 Level: developer 6881 6882 .keywords: TS, nonlinear, compute, function 6883 6884 .seealso: TSSetFunction(), TSGetFunction() 6885 */ 6886 PetscErrorCode TSComputeFunction_Matlab(TS snes,PetscReal time,Vec u,Vec udot,Vec y, void *ctx) 6887 { 6888 PetscErrorCode ierr; 6889 TSMatlabContext *sctx = (TSMatlabContext*)ctx; 6890 int nlhs = 1,nrhs = 7; 6891 mxArray *plhs[1],*prhs[7]; 6892 long long int lx = 0,lxdot = 0,ly = 0,ls = 0; 6893 6894 PetscFunctionBegin; 6895 PetscValidHeaderSpecific(snes,TS_CLASSID,1); 6896 PetscValidHeaderSpecific(u,VEC_CLASSID,3); 6897 PetscValidHeaderSpecific(udot,VEC_CLASSID,4); 6898 PetscValidHeaderSpecific(y,VEC_CLASSID,5); 6899 PetscCheckSameComm(snes,1,u,3); 6900 PetscCheckSameComm(snes,1,y,5); 6901 6902 ierr = PetscMemcpy(&ls,&snes,sizeof(snes));CHKERRQ(ierr); 6903 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 6904 ierr = PetscMemcpy(&lxdot,&udot,sizeof(udot));CHKERRQ(ierr); 6905 ierr = PetscMemcpy(&ly,&y,sizeof(u));CHKERRQ(ierr); 6906 6907 prhs[0] = mxCreateDoubleScalar((double)ls); 6908 prhs[1] = mxCreateDoubleScalar(time); 6909 prhs[2] = mxCreateDoubleScalar((double)lx); 6910 prhs[3] = mxCreateDoubleScalar((double)lxdot); 6911 prhs[4] = mxCreateDoubleScalar((double)ly); 6912 prhs[5] = mxCreateString(sctx->funcname); 6913 prhs[6] = sctx->ctx; 6914 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSComputeFunctionInternal");CHKERRQ(ierr); 6915 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 6916 mxDestroyArray(prhs[0]); 6917 mxDestroyArray(prhs[1]); 6918 mxDestroyArray(prhs[2]); 6919 mxDestroyArray(prhs[3]); 6920 mxDestroyArray(prhs[4]); 6921 mxDestroyArray(prhs[5]); 6922 mxDestroyArray(plhs[0]); 6923 PetscFunctionReturn(0); 6924 } 6925 6926 /* 6927 TSSetFunctionMatlab - Sets the function evaluation routine and function 6928 vector for use by the TS routines in solving ODEs 6929 equations from MATLAB. Here the function is a string containing the name of a MATLAB function 6930 6931 Logically Collective on TS 6932 6933 Input Parameters: 6934 + ts - the TS context 6935 - func - function evaluation routine 6936 6937 Calling sequence of func: 6938 $ func (TS ts,PetscReal time,Vec u,Vec udot,Vec f,void *ctx); 6939 6940 Level: beginner 6941 6942 .keywords: TS, nonlinear, set, function 6943 6944 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 6945 */ 6946 PetscErrorCode TSSetFunctionMatlab(TS ts,const char *func,mxArray *ctx) 6947 { 6948 PetscErrorCode ierr; 6949 TSMatlabContext *sctx; 6950 6951 PetscFunctionBegin; 6952 /* currently sctx is memory bleed */ 6953 ierr = PetscNew(&sctx);CHKERRQ(ierr); 6954 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 6955 /* 6956 This should work, but it doesn't 6957 sctx->ctx = ctx; 6958 mexMakeArrayPersistent(sctx->ctx); 6959 */ 6960 sctx->ctx = mxDuplicateArray(ctx); 6961 6962 ierr = TSSetIFunction(ts,NULL,TSComputeFunction_Matlab,sctx);CHKERRQ(ierr); 6963 PetscFunctionReturn(0); 6964 } 6965 6966 /* 6967 TSComputeJacobian_Matlab - Calls the function that has been set with 6968 TSSetJacobianMatlab(). 6969 6970 Collective on TS 6971 6972 Input Parameters: 6973 + ts - the TS context 6974 . u - input vector 6975 . A, B - the matrices 6976 - ctx - user context 6977 6978 Level: developer 6979 6980 .keywords: TS, nonlinear, compute, function 6981 6982 .seealso: TSSetFunction(), TSGetFunction() 6983 @*/ 6984 PetscErrorCode TSComputeJacobian_Matlab(TS ts,PetscReal time,Vec u,Vec udot,PetscReal shift,Mat A,Mat B,void *ctx) 6985 { 6986 PetscErrorCode ierr; 6987 TSMatlabContext *sctx = (TSMatlabContext*)ctx; 6988 int nlhs = 2,nrhs = 9; 6989 mxArray *plhs[2],*prhs[9]; 6990 long long int lx = 0,lxdot = 0,lA = 0,ls = 0, lB = 0; 6991 6992 PetscFunctionBegin; 6993 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6994 PetscValidHeaderSpecific(u,VEC_CLASSID,3); 6995 6996 /* call Matlab function in ctx with arguments u and y */ 6997 6998 ierr = PetscMemcpy(&ls,&ts,sizeof(ts));CHKERRQ(ierr); 6999 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 7000 ierr = PetscMemcpy(&lxdot,&udot,sizeof(u));CHKERRQ(ierr); 7001 ierr = PetscMemcpy(&lA,A,sizeof(u));CHKERRQ(ierr); 7002 ierr = PetscMemcpy(&lB,B,sizeof(u));CHKERRQ(ierr); 7003 7004 prhs[0] = mxCreateDoubleScalar((double)ls); 7005 prhs[1] = mxCreateDoubleScalar((double)time); 7006 prhs[2] = mxCreateDoubleScalar((double)lx); 7007 prhs[3] = mxCreateDoubleScalar((double)lxdot); 7008 prhs[4] = mxCreateDoubleScalar((double)shift); 7009 prhs[5] = mxCreateDoubleScalar((double)lA); 7010 prhs[6] = mxCreateDoubleScalar((double)lB); 7011 prhs[7] = mxCreateString(sctx->funcname); 7012 prhs[8] = sctx->ctx; 7013 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSComputeJacobianInternal");CHKERRQ(ierr); 7014 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 7015 mxDestroyArray(prhs[0]); 7016 mxDestroyArray(prhs[1]); 7017 mxDestroyArray(prhs[2]); 7018 mxDestroyArray(prhs[3]); 7019 mxDestroyArray(prhs[4]); 7020 mxDestroyArray(prhs[5]); 7021 mxDestroyArray(prhs[6]); 7022 mxDestroyArray(prhs[7]); 7023 mxDestroyArray(plhs[0]); 7024 mxDestroyArray(plhs[1]); 7025 PetscFunctionReturn(0); 7026 } 7027 7028 /* 7029 TSSetJacobianMatlab - Sets the Jacobian function evaluation routine and two empty Jacobian matrices 7030 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 7031 7032 Logically Collective on TS 7033 7034 Input Parameters: 7035 + ts - the TS context 7036 . A,B - Jacobian matrices 7037 . func - function evaluation routine 7038 - ctx - user context 7039 7040 Calling sequence of func: 7041 $ flag = func (TS ts,PetscReal time,Vec u,Vec udot,Mat A,Mat B,void *ctx); 7042 7043 Level: developer 7044 7045 .keywords: TS, nonlinear, set, function 7046 7047 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 7048 */ 7049 PetscErrorCode TSSetJacobianMatlab(TS ts,Mat A,Mat B,const char *func,mxArray *ctx) 7050 { 7051 PetscErrorCode ierr; 7052 TSMatlabContext *sctx; 7053 7054 PetscFunctionBegin; 7055 /* currently sctx is memory bleed */ 7056 ierr = PetscNew(&sctx);CHKERRQ(ierr); 7057 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 7058 /* 7059 This should work, but it doesn't 7060 sctx->ctx = ctx; 7061 mexMakeArrayPersistent(sctx->ctx); 7062 */ 7063 sctx->ctx = mxDuplicateArray(ctx); 7064 7065 ierr = TSSetIJacobian(ts,A,B,TSComputeJacobian_Matlab,sctx);CHKERRQ(ierr); 7066 PetscFunctionReturn(0); 7067 } 7068 7069 /* 7070 TSMonitor_Matlab - Calls the function that has been set with TSMonitorSetMatlab(). 7071 7072 Collective on TS 7073 7074 .seealso: TSSetFunction(), TSGetFunction() 7075 @*/ 7076 PetscErrorCode TSMonitor_Matlab(TS ts,PetscInt it, PetscReal time,Vec u, void *ctx) 7077 { 7078 PetscErrorCode ierr; 7079 TSMatlabContext *sctx = (TSMatlabContext*)ctx; 7080 int nlhs = 1,nrhs = 6; 7081 mxArray *plhs[1],*prhs[6]; 7082 long long int lx = 0,ls = 0; 7083 7084 PetscFunctionBegin; 7085 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 7086 PetscValidHeaderSpecific(u,VEC_CLASSID,4); 7087 7088 ierr = PetscMemcpy(&ls,&ts,sizeof(ts));CHKERRQ(ierr); 7089 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 7090 7091 prhs[0] = mxCreateDoubleScalar((double)ls); 7092 prhs[1] = mxCreateDoubleScalar((double)it); 7093 prhs[2] = mxCreateDoubleScalar((double)time); 7094 prhs[3] = mxCreateDoubleScalar((double)lx); 7095 prhs[4] = mxCreateString(sctx->funcname); 7096 prhs[5] = sctx->ctx; 7097 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSMonitorInternal");CHKERRQ(ierr); 7098 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 7099 mxDestroyArray(prhs[0]); 7100 mxDestroyArray(prhs[1]); 7101 mxDestroyArray(prhs[2]); 7102 mxDestroyArray(prhs[3]); 7103 mxDestroyArray(prhs[4]); 7104 mxDestroyArray(plhs[0]); 7105 PetscFunctionReturn(0); 7106 } 7107 7108 /* 7109 TSMonitorSetMatlab - Sets the monitor function from Matlab 7110 7111 Level: developer 7112 7113 .keywords: TS, nonlinear, set, function 7114 7115 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 7116 */ 7117 PetscErrorCode TSMonitorSetMatlab(TS ts,const char *func,mxArray *ctx) 7118 { 7119 PetscErrorCode ierr; 7120 TSMatlabContext *sctx; 7121 7122 PetscFunctionBegin; 7123 /* currently sctx is memory bleed */ 7124 ierr = PetscNew(&sctx);CHKERRQ(ierr); 7125 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 7126 /* 7127 This should work, but it doesn't 7128 sctx->ctx = ctx; 7129 mexMakeArrayPersistent(sctx->ctx); 7130 */ 7131 sctx->ctx = mxDuplicateArray(ctx); 7132 7133 ierr = TSMonitorSet(ts,TSMonitor_Matlab,sctx,NULL);CHKERRQ(ierr); 7134 PetscFunctionReturn(0); 7135 } 7136 #endif 7137 7138 /*@C 7139 TSMonitorLGSolution - Monitors progress of the TS solvers by plotting each component of the solution vector 7140 in a time based line graph 7141 7142 Collective on TS 7143 7144 Input Parameters: 7145 + ts - the TS context 7146 . step - current time-step 7147 . ptime - current time 7148 . u - current solution 7149 - dctx - the TSMonitorLGCtx object that contains all the options for the monitoring, this is created with TSMonitorLGCtxCreate() 7150 7151 Options Database: 7152 . -ts_monitor_lg_solution_variables 7153 7154 Level: intermediate 7155 7156 Notes: Each process in a parallel run displays its component solutions in a separate window 7157 7158 .keywords: TS, vector, monitor, view 7159 7160 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGCtxCreate(), TSMonitorLGCtxSetVariableNames(), TSMonitorLGCtxGetVariableNames(), 7161 TSMonitorLGSetVariableNames(), TSMonitorLGGetVariableNames(), TSMonitorLGSetDisplayVariables(), TSMonitorLGCtxSetDisplayVariables(), 7162 TSMonitorLGCtxSetTransform(), TSMonitorLGSetTransform(), TSMonitorLGError(), TSMonitorLGSNESIterations(), TSMonitorLGKSPIterations(), 7163 TSMonitorEnvelopeCtxCreate(), TSMonitorEnvelopeGetBounds(), TSMonitorEnvelopeCtxDestroy(), TSMonitorEnvelop() 7164 @*/ 7165 PetscErrorCode TSMonitorLGSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dctx) 7166 { 7167 PetscErrorCode ierr; 7168 TSMonitorLGCtx ctx = (TSMonitorLGCtx)dctx; 7169 const PetscScalar *yy; 7170 Vec v; 7171 7172 PetscFunctionBegin; 7173 if (step < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */ 7174 if (!step) { 7175 PetscDrawAxis axis; 7176 PetscInt dim; 7177 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 7178 ierr = PetscDrawAxisSetLabels(axis,"Solution as function of time","Time","Solution");CHKERRQ(ierr); 7179 if (!ctx->names) { 7180 PetscBool flg; 7181 /* user provides names of variables to plot but no names has been set so assume names are integer values */ 7182 ierr = PetscOptionsHasName(((PetscObject)ts)->options,((PetscObject)ts)->prefix,"-ts_monitor_lg_solution_variables",&flg);CHKERRQ(ierr); 7183 if (flg) { 7184 PetscInt i,n; 7185 char **names; 7186 ierr = VecGetSize(u,&n);CHKERRQ(ierr); 7187 ierr = PetscMalloc1(n+1,&names);CHKERRQ(ierr); 7188 for (i=0; i<n; i++) { 7189 ierr = PetscMalloc1(5,&names[i]);CHKERRQ(ierr); 7190 ierr = PetscSNPrintf(names[i],5,"%D",i);CHKERRQ(ierr); 7191 } 7192 names[n] = NULL; 7193 ctx->names = names; 7194 } 7195 } 7196 if (ctx->names && !ctx->displaynames) { 7197 char **displaynames; 7198 PetscBool flg; 7199 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 7200 ierr = PetscMalloc1(dim+1,&displaynames);CHKERRQ(ierr); 7201 ierr = PetscMemzero(displaynames,(dim+1)*sizeof(char*));CHKERRQ(ierr); 7202 ierr = PetscOptionsGetStringArray(((PetscObject)ts)->options,((PetscObject)ts)->prefix,"-ts_monitor_lg_solution_variables",displaynames,&dim,&flg);CHKERRQ(ierr); 7203 if (flg) { 7204 ierr = TSMonitorLGCtxSetDisplayVariables(ctx,(const char *const *)displaynames);CHKERRQ(ierr); 7205 } 7206 ierr = PetscStrArrayDestroy(&displaynames);CHKERRQ(ierr); 7207 } 7208 if (ctx->displaynames) { 7209 ierr = PetscDrawLGSetDimension(ctx->lg,ctx->ndisplayvariables);CHKERRQ(ierr); 7210 ierr = PetscDrawLGSetLegend(ctx->lg,(const char *const *)ctx->displaynames);CHKERRQ(ierr); 7211 } else if (ctx->names) { 7212 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 7213 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 7214 ierr = PetscDrawLGSetLegend(ctx->lg,(const char *const *)ctx->names);CHKERRQ(ierr); 7215 } else { 7216 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 7217 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 7218 } 7219 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 7220 } 7221 7222 if (!ctx->transform) v = u; 7223 else {ierr = (*ctx->transform)(ctx->transformctx,u,&v);CHKERRQ(ierr);} 7224 ierr = VecGetArrayRead(v,&yy);CHKERRQ(ierr); 7225 if (ctx->displaynames) { 7226 PetscInt i; 7227 for (i=0; i<ctx->ndisplayvariables; i++) 7228 ctx->displayvalues[i] = PetscRealPart(yy[ctx->displayvariables[i]]); 7229 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,ctx->displayvalues);CHKERRQ(ierr); 7230 } else { 7231 #if defined(PETSC_USE_COMPLEX) 7232 PetscInt i,n; 7233 PetscReal *yreal; 7234 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 7235 ierr = PetscMalloc1(n,&yreal);CHKERRQ(ierr); 7236 for (i=0; i<n; i++) yreal[i] = PetscRealPart(yy[i]); 7237 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yreal);CHKERRQ(ierr); 7238 ierr = PetscFree(yreal);CHKERRQ(ierr); 7239 #else 7240 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yy);CHKERRQ(ierr); 7241 #endif 7242 } 7243 ierr = VecRestoreArrayRead(v,&yy);CHKERRQ(ierr); 7244 if (ctx->transform) {ierr = VecDestroy(&v);CHKERRQ(ierr);} 7245 7246 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 7247 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 7248 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 7249 } 7250 PetscFunctionReturn(0); 7251 } 7252 7253 /*@C 7254 TSMonitorLGSetVariableNames - Sets the name of each component in the solution vector so that it may be displayed in the plot 7255 7256 Collective on TS 7257 7258 Input Parameters: 7259 + ts - the TS context 7260 - names - the names of the components, final string must be NULL 7261 7262 Level: intermediate 7263 7264 Notes: If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored 7265 7266 .keywords: TS, vector, monitor, view 7267 7268 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables(), TSMonitorLGCtxSetVariableNames() 7269 @*/ 7270 PetscErrorCode TSMonitorLGSetVariableNames(TS ts,const char * const *names) 7271 { 7272 PetscErrorCode ierr; 7273 PetscInt i; 7274 7275 PetscFunctionBegin; 7276 for (i=0; i<ts->numbermonitors; i++) { 7277 if (ts->monitor[i] == TSMonitorLGSolution) { 7278 ierr = TSMonitorLGCtxSetVariableNames((TSMonitorLGCtx)ts->monitorcontext[i],names);CHKERRQ(ierr); 7279 break; 7280 } 7281 } 7282 PetscFunctionReturn(0); 7283 } 7284 7285 /*@C 7286 TSMonitorLGCtxSetVariableNames - Sets the name of each component in the solution vector so that it may be displayed in the plot 7287 7288 Collective on TS 7289 7290 Input Parameters: 7291 + ts - the TS context 7292 - names - the names of the components, final string must be NULL 7293 7294 Level: intermediate 7295 7296 .keywords: TS, vector, monitor, view 7297 7298 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables(), TSMonitorLGSetVariableNames() 7299 @*/ 7300 PetscErrorCode TSMonitorLGCtxSetVariableNames(TSMonitorLGCtx ctx,const char * const *names) 7301 { 7302 PetscErrorCode ierr; 7303 7304 PetscFunctionBegin; 7305 ierr = PetscStrArrayDestroy(&ctx->names);CHKERRQ(ierr); 7306 ierr = PetscStrArrayallocpy(names,&ctx->names);CHKERRQ(ierr); 7307 PetscFunctionReturn(0); 7308 } 7309 7310 /*@C 7311 TSMonitorLGGetVariableNames - Gets the name of each component in the solution vector so that it may be displayed in the plot 7312 7313 Collective on TS 7314 7315 Input Parameter: 7316 . ts - the TS context 7317 7318 Output Parameter: 7319 . names - the names of the components, final string must be NULL 7320 7321 Level: intermediate 7322 7323 Notes: If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored 7324 7325 .keywords: TS, vector, monitor, view 7326 7327 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables() 7328 @*/ 7329 PetscErrorCode TSMonitorLGGetVariableNames(TS ts,const char *const **names) 7330 { 7331 PetscInt i; 7332 7333 PetscFunctionBegin; 7334 *names = NULL; 7335 for (i=0; i<ts->numbermonitors; i++) { 7336 if (ts->monitor[i] == TSMonitorLGSolution) { 7337 TSMonitorLGCtx ctx = (TSMonitorLGCtx) ts->monitorcontext[i]; 7338 *names = (const char *const *)ctx->names; 7339 break; 7340 } 7341 } 7342 PetscFunctionReturn(0); 7343 } 7344 7345 /*@C 7346 TSMonitorLGCtxSetDisplayVariables - Sets the variables that are to be display in the monitor 7347 7348 Collective on TS 7349 7350 Input Parameters: 7351 + ctx - the TSMonitorLG context 7352 . displaynames - the names of the components, final string must be NULL 7353 7354 Level: intermediate 7355 7356 .keywords: TS, vector, monitor, view 7357 7358 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames() 7359 @*/ 7360 PetscErrorCode TSMonitorLGCtxSetDisplayVariables(TSMonitorLGCtx ctx,const char * const *displaynames) 7361 { 7362 PetscInt j = 0,k; 7363 PetscErrorCode ierr; 7364 7365 PetscFunctionBegin; 7366 if (!ctx->names) PetscFunctionReturn(0); 7367 ierr = PetscStrArrayDestroy(&ctx->displaynames);CHKERRQ(ierr); 7368 ierr = PetscStrArrayallocpy(displaynames,&ctx->displaynames);CHKERRQ(ierr); 7369 while (displaynames[j]) j++; 7370 ctx->ndisplayvariables = j; 7371 ierr = PetscMalloc1(ctx->ndisplayvariables,&ctx->displayvariables);CHKERRQ(ierr); 7372 ierr = PetscMalloc1(ctx->ndisplayvariables,&ctx->displayvalues);CHKERRQ(ierr); 7373 j = 0; 7374 while (displaynames[j]) { 7375 k = 0; 7376 while (ctx->names[k]) { 7377 PetscBool flg; 7378 ierr = PetscStrcmp(displaynames[j],ctx->names[k],&flg);CHKERRQ(ierr); 7379 if (flg) { 7380 ctx->displayvariables[j] = k; 7381 break; 7382 } 7383 k++; 7384 } 7385 j++; 7386 } 7387 PetscFunctionReturn(0); 7388 } 7389 7390 /*@C 7391 TSMonitorLGSetDisplayVariables - Sets the variables that are to be display in the monitor 7392 7393 Collective on TS 7394 7395 Input Parameters: 7396 + ts - the TS context 7397 . displaynames - the names of the components, final string must be NULL 7398 7399 Notes: If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored 7400 7401 Level: intermediate 7402 7403 .keywords: TS, vector, monitor, view 7404 7405 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames() 7406 @*/ 7407 PetscErrorCode TSMonitorLGSetDisplayVariables(TS ts,const char * const *displaynames) 7408 { 7409 PetscInt i; 7410 PetscErrorCode ierr; 7411 7412 PetscFunctionBegin; 7413 for (i=0; i<ts->numbermonitors; i++) { 7414 if (ts->monitor[i] == TSMonitorLGSolution) { 7415 ierr = TSMonitorLGCtxSetDisplayVariables((TSMonitorLGCtx)ts->monitorcontext[i],displaynames);CHKERRQ(ierr); 7416 break; 7417 } 7418 } 7419 PetscFunctionReturn(0); 7420 } 7421 7422 /*@C 7423 TSMonitorLGSetTransform - Solution vector will be transformed by provided function before being displayed 7424 7425 Collective on TS 7426 7427 Input Parameters: 7428 + ts - the TS context 7429 . transform - the transform function 7430 . destroy - function to destroy the optional context 7431 - ctx - optional context used by transform function 7432 7433 Notes: If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored 7434 7435 Level: intermediate 7436 7437 .keywords: TS, vector, monitor, view 7438 7439 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames(), TSMonitorLGCtxSetTransform() 7440 @*/ 7441 PetscErrorCode TSMonitorLGSetTransform(TS ts,PetscErrorCode (*transform)(void*,Vec,Vec*),PetscErrorCode (*destroy)(void*),void *tctx) 7442 { 7443 PetscInt i; 7444 PetscErrorCode ierr; 7445 7446 PetscFunctionBegin; 7447 for (i=0; i<ts->numbermonitors; i++) { 7448 if (ts->monitor[i] == TSMonitorLGSolution) { 7449 ierr = TSMonitorLGCtxSetTransform((TSMonitorLGCtx)ts->monitorcontext[i],transform,destroy,tctx);CHKERRQ(ierr); 7450 } 7451 } 7452 PetscFunctionReturn(0); 7453 } 7454 7455 /*@C 7456 TSMonitorLGCtxSetTransform - Solution vector will be transformed by provided function before being displayed 7457 7458 Collective on TSLGCtx 7459 7460 Input Parameters: 7461 + ts - the TS context 7462 . transform - the transform function 7463 . destroy - function to destroy the optional context 7464 - ctx - optional context used by transform function 7465 7466 Level: intermediate 7467 7468 .keywords: TS, vector, monitor, view 7469 7470 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames(), TSMonitorLGSetTransform() 7471 @*/ 7472 PetscErrorCode TSMonitorLGCtxSetTransform(TSMonitorLGCtx ctx,PetscErrorCode (*transform)(void*,Vec,Vec*),PetscErrorCode (*destroy)(void*),void *tctx) 7473 { 7474 PetscFunctionBegin; 7475 ctx->transform = transform; 7476 ctx->transformdestroy = destroy; 7477 ctx->transformctx = tctx; 7478 PetscFunctionReturn(0); 7479 } 7480 7481 /*@C 7482 TSMonitorLGError - Monitors progress of the TS solvers by plotting each component of the error 7483 in a time based line graph 7484 7485 Collective on TS 7486 7487 Input Parameters: 7488 + ts - the TS context 7489 . step - current time-step 7490 . ptime - current time 7491 . u - current solution 7492 - dctx - TSMonitorLGCtx object created with TSMonitorLGCtxCreate() 7493 7494 Level: intermediate 7495 7496 Notes: Each process in a parallel run displays its component errors in a separate window 7497 7498 The user must provide the solution using TSSetSolutionFunction() to use this monitor. 7499 7500 Options Database Keys: 7501 . -ts_monitor_lg_error - create a graphical monitor of error history 7502 7503 .keywords: TS, vector, monitor, view 7504 7505 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSSetSolutionFunction() 7506 @*/ 7507 PetscErrorCode TSMonitorLGError(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 7508 { 7509 PetscErrorCode ierr; 7510 TSMonitorLGCtx ctx = (TSMonitorLGCtx)dummy; 7511 const PetscScalar *yy; 7512 Vec y; 7513 7514 PetscFunctionBegin; 7515 if (!step) { 7516 PetscDrawAxis axis; 7517 PetscInt dim; 7518 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 7519 ierr = PetscDrawAxisSetLabels(axis,"Error in solution as function of time","Time","Error");CHKERRQ(ierr); 7520 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 7521 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 7522 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 7523 } 7524 ierr = VecDuplicate(u,&y);CHKERRQ(ierr); 7525 ierr = TSComputeSolutionFunction(ts,ptime,y);CHKERRQ(ierr); 7526 ierr = VecAXPY(y,-1.0,u);CHKERRQ(ierr); 7527 ierr = VecGetArrayRead(y,&yy);CHKERRQ(ierr); 7528 #if defined(PETSC_USE_COMPLEX) 7529 { 7530 PetscReal *yreal; 7531 PetscInt i,n; 7532 ierr = VecGetLocalSize(y,&n);CHKERRQ(ierr); 7533 ierr = PetscMalloc1(n,&yreal);CHKERRQ(ierr); 7534 for (i=0; i<n; i++) yreal[i] = PetscRealPart(yy[i]); 7535 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yreal);CHKERRQ(ierr); 7536 ierr = PetscFree(yreal);CHKERRQ(ierr); 7537 } 7538 #else 7539 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yy);CHKERRQ(ierr); 7540 #endif 7541 ierr = VecRestoreArrayRead(y,&yy);CHKERRQ(ierr); 7542 ierr = VecDestroy(&y);CHKERRQ(ierr); 7543 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 7544 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 7545 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 7546 } 7547 PetscFunctionReturn(0); 7548 } 7549 7550 PetscErrorCode TSMonitorLGSNESIterations(TS ts,PetscInt n,PetscReal ptime,Vec v,void *monctx) 7551 { 7552 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 7553 PetscReal x = ptime,y; 7554 PetscErrorCode ierr; 7555 PetscInt its; 7556 7557 PetscFunctionBegin; 7558 if (n < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */ 7559 if (!n) { 7560 PetscDrawAxis axis; 7561 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 7562 ierr = PetscDrawAxisSetLabels(axis,"Nonlinear iterations as function of time","Time","SNES Iterations");CHKERRQ(ierr); 7563 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 7564 ctx->snes_its = 0; 7565 } 7566 ierr = TSGetSNESIterations(ts,&its);CHKERRQ(ierr); 7567 y = its - ctx->snes_its; 7568 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 7569 if (((ctx->howoften > 0) && (!(n % ctx->howoften)) && (n > -1)) || ((ctx->howoften == -1) && (n == -1))) { 7570 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 7571 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 7572 } 7573 ctx->snes_its = its; 7574 PetscFunctionReturn(0); 7575 } 7576 7577 PetscErrorCode TSMonitorLGKSPIterations(TS ts,PetscInt n,PetscReal ptime,Vec v,void *monctx) 7578 { 7579 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 7580 PetscReal x = ptime,y; 7581 PetscErrorCode ierr; 7582 PetscInt its; 7583 7584 PetscFunctionBegin; 7585 if (n < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */ 7586 if (!n) { 7587 PetscDrawAxis axis; 7588 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 7589 ierr = PetscDrawAxisSetLabels(axis,"Linear iterations as function of time","Time","KSP Iterations");CHKERRQ(ierr); 7590 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 7591 ctx->ksp_its = 0; 7592 } 7593 ierr = TSGetKSPIterations(ts,&its);CHKERRQ(ierr); 7594 y = its - ctx->ksp_its; 7595 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 7596 if (((ctx->howoften > 0) && (!(n % ctx->howoften)) && (n > -1)) || ((ctx->howoften == -1) && (n == -1))) { 7597 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 7598 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 7599 } 7600 ctx->ksp_its = its; 7601 PetscFunctionReturn(0); 7602 } 7603 7604 /*@ 7605 TSComputeLinearStability - computes the linear stability function at a point 7606 7607 Collective on TS and Vec 7608 7609 Input Parameters: 7610 + ts - the TS context 7611 - xr,xi - real and imaginary part of input arguments 7612 7613 Output Parameters: 7614 . yr,yi - real and imaginary part of function value 7615 7616 Level: developer 7617 7618 .keywords: TS, compute 7619 7620 .seealso: TSSetRHSFunction(), TSComputeIFunction() 7621 @*/ 7622 PetscErrorCode TSComputeLinearStability(TS ts,PetscReal xr,PetscReal xi,PetscReal *yr,PetscReal *yi) 7623 { 7624 PetscErrorCode ierr; 7625 7626 PetscFunctionBegin; 7627 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 7628 if (!ts->ops->linearstability) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Linearized stability function not provided for this method"); 7629 ierr = (*ts->ops->linearstability)(ts,xr,xi,yr,yi);CHKERRQ(ierr); 7630 PetscFunctionReturn(0); 7631 } 7632 7633 /* ------------------------------------------------------------------------*/ 7634 /*@C 7635 TSMonitorEnvelopeCtxCreate - Creates a context for use with TSMonitorEnvelope() 7636 7637 Collective on TS 7638 7639 Input Parameters: 7640 . ts - the ODE solver object 7641 7642 Output Parameter: 7643 . ctx - the context 7644 7645 Level: intermediate 7646 7647 .keywords: TS, monitor, line graph, residual, seealso 7648 7649 .seealso: TSMonitorLGTimeStep(), TSMonitorSet(), TSMonitorLGSolution(), TSMonitorLGError() 7650 7651 @*/ 7652 PetscErrorCode TSMonitorEnvelopeCtxCreate(TS ts,TSMonitorEnvelopeCtx *ctx) 7653 { 7654 PetscErrorCode ierr; 7655 7656 PetscFunctionBegin; 7657 ierr = PetscNew(ctx);CHKERRQ(ierr); 7658 PetscFunctionReturn(0); 7659 } 7660 7661 /*@C 7662 TSMonitorEnvelope - Monitors the maximum and minimum value of each component of the solution 7663 7664 Collective on TS 7665 7666 Input Parameters: 7667 + ts - the TS context 7668 . step - current time-step 7669 . ptime - current time 7670 . u - current solution 7671 - dctx - the envelope context 7672 7673 Options Database: 7674 . -ts_monitor_envelope 7675 7676 Level: intermediate 7677 7678 Notes: after a solve you can use TSMonitorEnvelopeGetBounds() to access the envelope 7679 7680 .keywords: TS, vector, monitor, view 7681 7682 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorEnvelopeGetBounds(), TSMonitorEnvelopeCtxCreate() 7683 @*/ 7684 PetscErrorCode TSMonitorEnvelope(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dctx) 7685 { 7686 PetscErrorCode ierr; 7687 TSMonitorEnvelopeCtx ctx = (TSMonitorEnvelopeCtx)dctx; 7688 7689 PetscFunctionBegin; 7690 if (!ctx->max) { 7691 ierr = VecDuplicate(u,&ctx->max);CHKERRQ(ierr); 7692 ierr = VecDuplicate(u,&ctx->min);CHKERRQ(ierr); 7693 ierr = VecCopy(u,ctx->max);CHKERRQ(ierr); 7694 ierr = VecCopy(u,ctx->min);CHKERRQ(ierr); 7695 } else { 7696 ierr = VecPointwiseMax(ctx->max,u,ctx->max);CHKERRQ(ierr); 7697 ierr = VecPointwiseMin(ctx->min,u,ctx->min);CHKERRQ(ierr); 7698 } 7699 PetscFunctionReturn(0); 7700 } 7701 7702 /*@C 7703 TSMonitorEnvelopeGetBounds - Gets the bounds for the components of the solution 7704 7705 Collective on TS 7706 7707 Input Parameter: 7708 . ts - the TS context 7709 7710 Output Parameter: 7711 + max - the maximum values 7712 - min - the minimum values 7713 7714 Notes: If the TS does not have a TSMonitorEnvelopeCtx associated with it then this function is ignored 7715 7716 Level: intermediate 7717 7718 .keywords: TS, vector, monitor, view 7719 7720 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables() 7721 @*/ 7722 PetscErrorCode TSMonitorEnvelopeGetBounds(TS ts,Vec *max,Vec *min) 7723 { 7724 PetscInt i; 7725 7726 PetscFunctionBegin; 7727 if (max) *max = NULL; 7728 if (min) *min = NULL; 7729 for (i=0; i<ts->numbermonitors; i++) { 7730 if (ts->monitor[i] == TSMonitorEnvelope) { 7731 TSMonitorEnvelopeCtx ctx = (TSMonitorEnvelopeCtx) ts->monitorcontext[i]; 7732 if (max) *max = ctx->max; 7733 if (min) *min = ctx->min; 7734 break; 7735 } 7736 } 7737 PetscFunctionReturn(0); 7738 } 7739 7740 /*@C 7741 TSMonitorEnvelopeCtxDestroy - Destroys a context that was created with TSMonitorEnvelopeCtxCreate(). 7742 7743 Collective on TSMonitorEnvelopeCtx 7744 7745 Input Parameter: 7746 . ctx - the monitor context 7747 7748 Level: intermediate 7749 7750 .keywords: TS, monitor, line graph, destroy 7751 7752 .seealso: TSMonitorLGCtxCreate(), TSMonitorSet(), TSMonitorLGTimeStep() 7753 @*/ 7754 PetscErrorCode TSMonitorEnvelopeCtxDestroy(TSMonitorEnvelopeCtx *ctx) 7755 { 7756 PetscErrorCode ierr; 7757 7758 PetscFunctionBegin; 7759 ierr = VecDestroy(&(*ctx)->min);CHKERRQ(ierr); 7760 ierr = VecDestroy(&(*ctx)->max);CHKERRQ(ierr); 7761 ierr = PetscFree(*ctx);CHKERRQ(ierr); 7762 PetscFunctionReturn(0); 7763 } 7764 7765 /*@ 7766 TSRestartStep - Flags the solver to restart the next step 7767 7768 Collective on TS 7769 7770 Input Parameter: 7771 . ts - the TS context obtained from TSCreate() 7772 7773 Level: advanced 7774 7775 Notes: 7776 Multistep methods like BDF or Runge-Kutta methods with FSAL property require restarting the solver in the event of 7777 discontinuities. These discontinuities may be introduced as a consequence of explicitly modifications to the solution 7778 vector (which PETSc attempts to detect and handle) or problem coefficients (which PETSc is not able to detect). For 7779 the sake of correctness and maximum safety, users are expected to call TSRestart() whenever they introduce 7780 discontinuities in callback routines (e.g. prestep and poststep routines, or implicit/rhs function routines with 7781 discontinuous source terms). 7782 7783 .keywords: TS, timestep, restart 7784 7785 .seealso: TSSolve(), TSSetPreStep(), TSSetPostStep() 7786 @*/ 7787 PetscErrorCode TSRestartStep(TS ts) 7788 { 7789 PetscFunctionBegin; 7790 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 7791 ts->steprestart = PETSC_TRUE; 7792 PetscFunctionReturn(0); 7793 } 7794 7795 /*@ 7796 TSRollBack - Rolls back one time step 7797 7798 Collective on TS 7799 7800 Input Parameter: 7801 . ts - the TS context obtained from TSCreate() 7802 7803 Level: advanced 7804 7805 .keywords: TS, timestep, rollback 7806 7807 .seealso: TSCreate(), TSSetUp(), TSDestroy(), TSSolve(), TSSetPreStep(), TSSetPreStage(), TSInterpolate() 7808 @*/ 7809 PetscErrorCode TSRollBack(TS ts) 7810 { 7811 PetscErrorCode ierr; 7812 7813 PetscFunctionBegin; 7814 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 7815 if (ts->steprollback) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"TSRollBack already called"); 7816 if (!ts->ops->rollback) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSRollBack not implemented for type '%s'",((PetscObject)ts)->type_name); 7817 ierr = (*ts->ops->rollback)(ts);CHKERRQ(ierr); 7818 ts->time_step = ts->ptime - ts->ptime_prev; 7819 ts->ptime = ts->ptime_prev; 7820 ts->ptime_prev = ts->ptime_prev_rollback; 7821 ts->steps--; 7822 ts->steprollback = PETSC_TRUE; 7823 PetscFunctionReturn(0); 7824 } 7825 7826 /*@ 7827 TSGetStages - Get the number of stages and stage values 7828 7829 Input Parameter: 7830 . ts - the TS context obtained from TSCreate() 7831 7832 Level: advanced 7833 7834 .keywords: TS, getstages 7835 7836 .seealso: TSCreate() 7837 @*/ 7838 PetscErrorCode TSGetStages(TS ts,PetscInt *ns,Vec **Y) 7839 { 7840 PetscErrorCode ierr; 7841 7842 PetscFunctionBegin; 7843 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 7844 PetscValidPointer(ns,2); 7845 7846 if (!ts->ops->getstages) *ns=0; 7847 else { 7848 ierr = (*ts->ops->getstages)(ts,ns,Y);CHKERRQ(ierr); 7849 } 7850 PetscFunctionReturn(0); 7851 } 7852 7853 /*@C 7854 TSComputeIJacobianDefaultColor - Computes the Jacobian using finite differences and coloring to exploit matrix sparsity. 7855 7856 Collective on SNES 7857 7858 Input Parameters: 7859 + ts - the TS context 7860 . t - current timestep 7861 . U - state vector 7862 . Udot - time derivative of state vector 7863 . shift - shift to apply, see note below 7864 - ctx - an optional user context 7865 7866 Output Parameters: 7867 + J - Jacobian matrix (not altered in this routine) 7868 - B - newly computed Jacobian matrix to use with preconditioner (generally the same as J) 7869 7870 Level: intermediate 7871 7872 Notes: 7873 If F(t,U,Udot)=0 is the DAE, the required Jacobian is 7874 7875 dF/dU + shift*dF/dUdot 7876 7877 Most users should not need to explicitly call this routine, as it 7878 is used internally within the nonlinear solvers. 7879 7880 This will first try to get the coloring from the DM. If the DM type has no coloring 7881 routine, then it will try to get the coloring from the matrix. This requires that the 7882 matrix have nonzero entries precomputed. 7883 7884 .keywords: TS, finite differences, Jacobian, coloring, sparse 7885 .seealso: TSSetIJacobian(), MatFDColoringCreate(), MatFDColoringSetFunction() 7886 @*/ 7887 PetscErrorCode TSComputeIJacobianDefaultColor(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat J,Mat B,void *ctx) 7888 { 7889 SNES snes; 7890 MatFDColoring color; 7891 PetscBool hascolor, matcolor = PETSC_FALSE; 7892 PetscErrorCode ierr; 7893 7894 PetscFunctionBegin; 7895 ierr = PetscOptionsGetBool(((PetscObject)ts)->options,((PetscObject) ts)->prefix, "-ts_fd_color_use_mat", &matcolor, NULL);CHKERRQ(ierr); 7896 ierr = PetscObjectQuery((PetscObject) B, "TSMatFDColoring", (PetscObject *) &color);CHKERRQ(ierr); 7897 if (!color) { 7898 DM dm; 7899 ISColoring iscoloring; 7900 7901 ierr = TSGetDM(ts, &dm);CHKERRQ(ierr); 7902 ierr = DMHasColoring(dm, &hascolor);CHKERRQ(ierr); 7903 if (hascolor && !matcolor) { 7904 ierr = DMCreateColoring(dm, IS_COLORING_GLOBAL, &iscoloring);CHKERRQ(ierr); 7905 ierr = MatFDColoringCreate(B, iscoloring, &color);CHKERRQ(ierr); 7906 ierr = MatFDColoringSetFunction(color, (PetscErrorCode (*)(void)) SNESTSFormFunction, (void *) ts);CHKERRQ(ierr); 7907 ierr = MatFDColoringSetFromOptions(color);CHKERRQ(ierr); 7908 ierr = MatFDColoringSetUp(B, iscoloring, color);CHKERRQ(ierr); 7909 ierr = ISColoringDestroy(&iscoloring);CHKERRQ(ierr); 7910 } else { 7911 MatColoring mc; 7912 7913 ierr = MatColoringCreate(B, &mc);CHKERRQ(ierr); 7914 ierr = MatColoringSetDistance(mc, 2);CHKERRQ(ierr); 7915 ierr = MatColoringSetType(mc, MATCOLORINGSL);CHKERRQ(ierr); 7916 ierr = MatColoringSetFromOptions(mc);CHKERRQ(ierr); 7917 ierr = MatColoringApply(mc, &iscoloring);CHKERRQ(ierr); 7918 ierr = MatColoringDestroy(&mc);CHKERRQ(ierr); 7919 ierr = MatFDColoringCreate(B, iscoloring, &color);CHKERRQ(ierr); 7920 ierr = MatFDColoringSetFunction(color, (PetscErrorCode (*)(void)) SNESTSFormFunction, (void *) ts);CHKERRQ(ierr); 7921 ierr = MatFDColoringSetFromOptions(color);CHKERRQ(ierr); 7922 ierr = MatFDColoringSetUp(B, iscoloring, color);CHKERRQ(ierr); 7923 ierr = ISColoringDestroy(&iscoloring);CHKERRQ(ierr); 7924 } 7925 ierr = PetscObjectCompose((PetscObject) B, "TSMatFDColoring", (PetscObject) color);CHKERRQ(ierr); 7926 ierr = PetscObjectDereference((PetscObject) color);CHKERRQ(ierr); 7927 } 7928 ierr = TSGetSNES(ts, &snes);CHKERRQ(ierr); 7929 ierr = MatFDColoringApply(B, color, U, snes);CHKERRQ(ierr); 7930 if (J != B) { 7931 ierr = MatAssemblyBegin(J, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 7932 ierr = MatAssemblyEnd(J, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 7933 } 7934 PetscFunctionReturn(0); 7935 } 7936 7937 /*@ 7938 TSSetFunctionDomainError - Set the function testing if the current state vector is valid 7939 7940 Input Parameters: 7941 ts - the TS context 7942 func - function called within TSFunctionDomainError 7943 7944 Level: intermediate 7945 7946 .keywords: TS, state, domain 7947 .seealso: TSAdaptCheckStage(), TSFunctionDomainError() 7948 @*/ 7949 7950 PetscErrorCode TSSetFunctionDomainError(TS ts, PetscErrorCode (*func)(TS,PetscReal,Vec,PetscBool*)) 7951 { 7952 PetscFunctionBegin; 7953 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 7954 ts->functiondomainerror = func; 7955 PetscFunctionReturn(0); 7956 } 7957 7958 /*@ 7959 TSFunctionDomainError - Check if the current state is valid 7960 7961 Input Parameters: 7962 ts - the TS context 7963 stagetime - time of the simulation 7964 Y - state vector to check. 7965 7966 Output Parameter: 7967 accept - Set to PETSC_FALSE if the current state vector is valid. 7968 7969 Note: 7970 This function should be used to ensure the state is in a valid part of the space. 7971 For example, one can ensure here all values are positive. 7972 7973 Level: advanced 7974 @*/ 7975 PetscErrorCode TSFunctionDomainError(TS ts,PetscReal stagetime,Vec Y,PetscBool* accept) 7976 { 7977 PetscErrorCode ierr; 7978 7979 PetscFunctionBegin; 7980 7981 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 7982 *accept = PETSC_TRUE; 7983 if (ts->functiondomainerror) { 7984 PetscStackCallStandard((*ts->functiondomainerror),(ts,stagetime,Y,accept)); 7985 } 7986 PetscFunctionReturn(0); 7987 } 7988 7989 /*@C 7990 TSClone - This function clones a time step object. 7991 7992 Collective on MPI_Comm 7993 7994 Input Parameter: 7995 . tsin - The input TS 7996 7997 Output Parameter: 7998 . tsout - The output TS (cloned) 7999 8000 Notes: 8001 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. 8002 8003 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); 8004 8005 Level: developer 8006 8007 .keywords: TS, clone 8008 .seealso: TSCreate(), TSSetType(), TSSetUp(), TSDestroy(), TSSetProblemType() 8009 @*/ 8010 PetscErrorCode TSClone(TS tsin, TS *tsout) 8011 { 8012 TS t; 8013 PetscErrorCode ierr; 8014 SNES snes_start; 8015 DM dm; 8016 TSType type; 8017 8018 PetscFunctionBegin; 8019 PetscValidPointer(tsin,1); 8020 *tsout = NULL; 8021 8022 ierr = PetscHeaderCreate(t, TS_CLASSID, "TS", "Time stepping", "TS", PetscObjectComm((PetscObject)tsin), TSDestroy, TSView);CHKERRQ(ierr); 8023 8024 /* General TS description */ 8025 t->numbermonitors = 0; 8026 t->setupcalled = 0; 8027 t->ksp_its = 0; 8028 t->snes_its = 0; 8029 t->nwork = 0; 8030 t->rhsjacobian.time = -1e20; 8031 t->rhsjacobian.scale = 1.; 8032 t->ijacobian.shift = 1.; 8033 8034 ierr = TSGetSNES(tsin,&snes_start);CHKERRQ(ierr); 8035 ierr = TSSetSNES(t,snes_start);CHKERRQ(ierr); 8036 8037 ierr = TSGetDM(tsin,&dm);CHKERRQ(ierr); 8038 ierr = TSSetDM(t,dm);CHKERRQ(ierr); 8039 8040 t->adapt = tsin->adapt; 8041 ierr = PetscObjectReference((PetscObject)t->adapt);CHKERRQ(ierr); 8042 8043 t->trajectory = tsin->trajectory; 8044 ierr = PetscObjectReference((PetscObject)t->trajectory);CHKERRQ(ierr); 8045 8046 t->event = tsin->event; 8047 if (t->event) t->event->refct++; 8048 8049 t->problem_type = tsin->problem_type; 8050 t->ptime = tsin->ptime; 8051 t->ptime_prev = tsin->ptime_prev; 8052 t->time_step = tsin->time_step; 8053 t->max_time = tsin->max_time; 8054 t->steps = tsin->steps; 8055 t->max_steps = tsin->max_steps; 8056 t->equation_type = tsin->equation_type; 8057 t->atol = tsin->atol; 8058 t->rtol = tsin->rtol; 8059 t->max_snes_failures = tsin->max_snes_failures; 8060 t->max_reject = tsin->max_reject; 8061 t->errorifstepfailed = tsin->errorifstepfailed; 8062 8063 ierr = TSGetType(tsin,&type);CHKERRQ(ierr); 8064 ierr = TSSetType(t,type);CHKERRQ(ierr); 8065 8066 t->vec_sol = NULL; 8067 8068 t->cfltime = tsin->cfltime; 8069 t->cfltime_local = tsin->cfltime_local; 8070 t->exact_final_time = tsin->exact_final_time; 8071 8072 ierr = PetscMemcpy(t->ops,tsin->ops,sizeof(struct _TSOps));CHKERRQ(ierr); 8073 8074 if (((PetscObject)tsin)->fortran_func_pointers) { 8075 PetscInt i; 8076 ierr = PetscMalloc((10)*sizeof(void(*)(void)),&((PetscObject)t)->fortran_func_pointers);CHKERRQ(ierr); 8077 for (i=0; i<10; i++) { 8078 ((PetscObject)t)->fortran_func_pointers[i] = ((PetscObject)tsin)->fortran_func_pointers[i]; 8079 } 8080 } 8081 *tsout = t; 8082 PetscFunctionReturn(0); 8083 } 8084