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