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() 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) ts->steprestart = PETSC_TRUE; 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 PetscStackCallStandard((*ts->postevaluate),(ts)); 3706 } 3707 PetscFunctionReturn(0); 3708 } 3709 3710 /*@C 3711 TSSetPostStep - Sets the general-purpose function 3712 called once at the end of each time step. 3713 3714 Logically Collective on TS 3715 3716 Input Parameters: 3717 + ts - The TS context obtained from TSCreate() 3718 - func - The function 3719 3720 Calling sequence of func: 3721 $ func (TS ts); 3722 3723 Notes: 3724 The function set by TSSetPostStep() is called after each successful step. The solution vector X 3725 obtained by TSGetSolution() may be different than that computed at the step end if the event handler 3726 locates an event and TSPostEvent() modifies it. Use TSSetPostEvaluate() if an unmodified solution is needed instead. 3727 3728 Level: intermediate 3729 3730 .keywords: TS, timestep 3731 .seealso: TSSetPreStep(), TSSetPreStage(), TSSetPostEvaluate(), TSGetTimeStep(), TSGetStepNumber(), TSGetTime() 3732 @*/ 3733 PetscErrorCode TSSetPostStep(TS ts, PetscErrorCode (*func)(TS)) 3734 { 3735 PetscFunctionBegin; 3736 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3737 ts->poststep = func; 3738 PetscFunctionReturn(0); 3739 } 3740 3741 /*@ 3742 TSPostStep - Runs the user-defined post-step function. 3743 3744 Collective on TS 3745 3746 Input Parameters: 3747 . ts - The TS context obtained from TSCreate() 3748 3749 Notes: 3750 TSPostStep() is typically used within time stepping implementations, 3751 so most users would not generally call this routine themselves. 3752 3753 Level: developer 3754 3755 .keywords: TS, timestep 3756 @*/ 3757 PetscErrorCode TSPostStep(TS ts) 3758 { 3759 PetscErrorCode ierr; 3760 3761 PetscFunctionBegin; 3762 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3763 if (ts->poststep) { 3764 Vec U; 3765 PetscObjectState sprev,spost; 3766 3767 ierr = TSGetSolution(ts,&U);CHKERRQ(ierr); 3768 ierr = PetscObjectStateGet((PetscObject)U,&sprev);CHKERRQ(ierr); 3769 PetscStackCallStandard((*ts->poststep),(ts)); 3770 ierr = PetscObjectStateGet((PetscObject)U,&spost);CHKERRQ(ierr); 3771 if (sprev != spost) ts->steprestart = PETSC_TRUE; 3772 } 3773 PetscFunctionReturn(0); 3774 } 3775 3776 /* ------------ Routines to set performance monitoring options ----------- */ 3777 3778 /*@C 3779 TSMonitorSet - Sets an ADDITIONAL function that is to be used at every 3780 timestep to display the iteration's progress. 3781 3782 Logically Collective on TS 3783 3784 Input Parameters: 3785 + ts - the TS context obtained from TSCreate() 3786 . monitor - monitoring routine 3787 . mctx - [optional] user-defined context for private data for the 3788 monitor routine (use NULL if no context is desired) 3789 - monitordestroy - [optional] routine that frees monitor context 3790 (may be NULL) 3791 3792 Calling sequence of monitor: 3793 $ int monitor(TS ts,PetscInt steps,PetscReal time,Vec u,void *mctx) 3794 3795 + ts - the TS context 3796 . 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) 3797 . time - current time 3798 . u - current iterate 3799 - mctx - [optional] monitoring context 3800 3801 Notes: 3802 This routine adds an additional monitor to the list of monitors that 3803 already has been loaded. 3804 3805 Fortran notes: Only a single monitor function can be set for each TS object 3806 3807 Level: intermediate 3808 3809 .keywords: TS, timestep, set, monitor 3810 3811 .seealso: TSMonitorDefault(), TSMonitorCancel() 3812 @*/ 3813 PetscErrorCode TSMonitorSet(TS ts,PetscErrorCode (*monitor)(TS,PetscInt,PetscReal,Vec,void*),void *mctx,PetscErrorCode (*mdestroy)(void**)) 3814 { 3815 PetscErrorCode ierr; 3816 PetscInt i; 3817 PetscBool identical; 3818 3819 PetscFunctionBegin; 3820 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3821 for (i=0; i<ts->numbermonitors;i++) { 3822 ierr = PetscMonitorCompare((PetscErrorCode (*)(void))monitor,mctx,mdestroy,(PetscErrorCode (*)(void))ts->monitor[i],ts->monitorcontext[i],ts->monitordestroy[i],&identical);CHKERRQ(ierr); 3823 if (identical) PetscFunctionReturn(0); 3824 } 3825 if (ts->numbermonitors >= MAXTSMONITORS) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Too many monitors set"); 3826 ts->monitor[ts->numbermonitors] = monitor; 3827 ts->monitordestroy[ts->numbermonitors] = mdestroy; 3828 ts->monitorcontext[ts->numbermonitors++] = (void*)mctx; 3829 PetscFunctionReturn(0); 3830 } 3831 3832 /*@C 3833 TSMonitorCancel - Clears all the monitors that have been set on a time-step object. 3834 3835 Logically Collective on TS 3836 3837 Input Parameters: 3838 . ts - the TS context obtained from TSCreate() 3839 3840 Notes: 3841 There is no way to remove a single, specific monitor. 3842 3843 Level: intermediate 3844 3845 .keywords: TS, timestep, set, monitor 3846 3847 .seealso: TSMonitorDefault(), TSMonitorSet() 3848 @*/ 3849 PetscErrorCode TSMonitorCancel(TS ts) 3850 { 3851 PetscErrorCode ierr; 3852 PetscInt i; 3853 3854 PetscFunctionBegin; 3855 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3856 for (i=0; i<ts->numbermonitors; i++) { 3857 if (ts->monitordestroy[i]) { 3858 ierr = (*ts->monitordestroy[i])(&ts->monitorcontext[i]);CHKERRQ(ierr); 3859 } 3860 } 3861 ts->numbermonitors = 0; 3862 PetscFunctionReturn(0); 3863 } 3864 3865 /*@C 3866 TSMonitorDefault - The Default monitor, prints the timestep and time for each step 3867 3868 Level: intermediate 3869 3870 .keywords: TS, set, monitor 3871 3872 .seealso: TSMonitorSet() 3873 @*/ 3874 PetscErrorCode TSMonitorDefault(TS ts,PetscInt step,PetscReal ptime,Vec v,PetscViewerAndFormat *vf) 3875 { 3876 PetscErrorCode ierr; 3877 PetscViewer viewer = vf->viewer; 3878 PetscBool iascii,ibinary; 3879 3880 PetscFunctionBegin; 3881 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,4); 3882 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 3883 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&ibinary);CHKERRQ(ierr); 3884 ierr = PetscViewerPushFormat(viewer,vf->format);CHKERRQ(ierr); 3885 if (iascii) { 3886 ierr = PetscViewerASCIIAddTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 3887 if (step == -1){ /* this indicates it is an interpolated solution */ 3888 ierr = PetscViewerASCIIPrintf(viewer,"Interpolated solution at time %g between steps %D and %D\n",(double)ptime,ts->steps-1,ts->steps);CHKERRQ(ierr); 3889 } else { 3890 ierr = PetscViewerASCIIPrintf(viewer,"%D TS dt %g time %g%s",step,(double)ts->time_step,(double)ptime,ts->steprollback ? " (r)\n" : "\n");CHKERRQ(ierr); 3891 } 3892 ierr = PetscViewerASCIISubtractTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 3893 } else if (ibinary) { 3894 PetscMPIInt rank; 3895 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)viewer),&rank);CHKERRQ(ierr); 3896 if (!rank) { 3897 PetscBool skipHeader; 3898 PetscInt classid = REAL_FILE_CLASSID; 3899 3900 ierr = PetscViewerBinaryGetSkipHeader(viewer,&skipHeader);CHKERRQ(ierr); 3901 if (!skipHeader) { 3902 ierr = PetscViewerBinaryWrite(viewer,&classid,1,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); 3903 } 3904 ierr = PetscRealView(1,&ptime,viewer);CHKERRQ(ierr); 3905 } else { 3906 ierr = PetscRealView(0,&ptime,viewer);CHKERRQ(ierr); 3907 } 3908 } 3909 ierr = PetscViewerPopFormat(viewer);CHKERRQ(ierr); 3910 PetscFunctionReturn(0); 3911 } 3912 3913 /*@C 3914 TSAdjointMonitorSet - Sets an ADDITIONAL function that is to be used at every 3915 timestep to display the iteration's progress. 3916 3917 Logically Collective on TS 3918 3919 Input Parameters: 3920 + ts - the TS context obtained from TSCreate() 3921 . adjointmonitor - monitoring routine 3922 . adjointmctx - [optional] user-defined context for private data for the 3923 monitor routine (use NULL if no context is desired) 3924 - adjointmonitordestroy - [optional] routine that frees monitor context 3925 (may be NULL) 3926 3927 Calling sequence of monitor: 3928 $ int adjointmonitor(TS ts,PetscInt steps,PetscReal time,Vec u,PetscInt numcost,Vec *lambda, Vec *mu,void *adjointmctx) 3929 3930 + ts - the TS context 3931 . 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 3932 been interpolated to) 3933 . time - current time 3934 . u - current iterate 3935 . numcost - number of cost functionos 3936 . lambda - sensitivities to initial conditions 3937 . mu - sensitivities to parameters 3938 - adjointmctx - [optional] adjoint monitoring context 3939 3940 Notes: 3941 This routine adds an additional monitor to the list of monitors that 3942 already has been loaded. 3943 3944 Fortran notes: Only a single monitor function can be set for each TS object 3945 3946 Level: intermediate 3947 3948 .keywords: TS, timestep, set, adjoint, monitor 3949 3950 .seealso: TSAdjointMonitorCancel() 3951 @*/ 3952 PetscErrorCode TSAdjointMonitorSet(TS ts,PetscErrorCode (*adjointmonitor)(TS,PetscInt,PetscReal,Vec,PetscInt,Vec*,Vec*,void*),void *adjointmctx,PetscErrorCode (*adjointmdestroy)(void**)) 3953 { 3954 PetscErrorCode ierr; 3955 PetscInt i; 3956 PetscBool identical; 3957 3958 PetscFunctionBegin; 3959 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3960 for (i=0; i<ts->numbermonitors;i++) { 3961 ierr = PetscMonitorCompare((PetscErrorCode (*)(void))adjointmonitor,adjointmctx,adjointmdestroy,(PetscErrorCode (*)(void))ts->adjointmonitor[i],ts->adjointmonitorcontext[i],ts->adjointmonitordestroy[i],&identical);CHKERRQ(ierr); 3962 if (identical) PetscFunctionReturn(0); 3963 } 3964 if (ts->numberadjointmonitors >= MAXTSMONITORS) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Too many adjoint monitors set"); 3965 ts->adjointmonitor[ts->numberadjointmonitors] = adjointmonitor; 3966 ts->adjointmonitordestroy[ts->numberadjointmonitors] = adjointmdestroy; 3967 ts->adjointmonitorcontext[ts->numberadjointmonitors++] = (void*)adjointmctx; 3968 PetscFunctionReturn(0); 3969 } 3970 3971 /*@C 3972 TSAdjointMonitorCancel - Clears all the adjoint monitors that have been set on a time-step object. 3973 3974 Logically Collective on TS 3975 3976 Input Parameters: 3977 . ts - the TS context obtained from TSCreate() 3978 3979 Notes: 3980 There is no way to remove a single, specific monitor. 3981 3982 Level: intermediate 3983 3984 .keywords: TS, timestep, set, adjoint, monitor 3985 3986 .seealso: TSAdjointMonitorSet() 3987 @*/ 3988 PetscErrorCode TSAdjointMonitorCancel(TS ts) 3989 { 3990 PetscErrorCode ierr; 3991 PetscInt i; 3992 3993 PetscFunctionBegin; 3994 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3995 for (i=0; i<ts->numberadjointmonitors; i++) { 3996 if (ts->adjointmonitordestroy[i]) { 3997 ierr = (*ts->adjointmonitordestroy[i])(&ts->adjointmonitorcontext[i]);CHKERRQ(ierr); 3998 } 3999 } 4000 ts->numberadjointmonitors = 0; 4001 PetscFunctionReturn(0); 4002 } 4003 4004 /*@C 4005 TSAdjointMonitorDefault - the default monitor of adjoint computations 4006 4007 Level: intermediate 4008 4009 .keywords: TS, set, monitor 4010 4011 .seealso: TSAdjointMonitorSet() 4012 @*/ 4013 PetscErrorCode TSAdjointMonitorDefault(TS ts,PetscInt step,PetscReal ptime,Vec v,PetscInt numcost,Vec *lambda,Vec *mu,PetscViewerAndFormat *vf) 4014 { 4015 PetscErrorCode ierr; 4016 PetscViewer viewer = vf->viewer; 4017 4018 PetscFunctionBegin; 4019 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,4); 4020 ierr = PetscViewerPushFormat(viewer,vf->format);CHKERRQ(ierr); 4021 ierr = PetscViewerASCIIAddTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 4022 ierr = PetscViewerASCIIPrintf(viewer,"%D TS dt %g time %g%s",step,(double)ts->time_step,(double)ptime,ts->steprollback ? " (r)\n" : "\n");CHKERRQ(ierr); 4023 ierr = PetscViewerASCIISubtractTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 4024 ierr = PetscViewerPopFormat(viewer);CHKERRQ(ierr); 4025 PetscFunctionReturn(0); 4026 } 4027 4028 /*@ 4029 TSInterpolate - Interpolate the solution computed during the previous step to an arbitrary location in the interval 4030 4031 Collective on TS 4032 4033 Input Argument: 4034 + ts - time stepping context 4035 - t - time to interpolate to 4036 4037 Output Argument: 4038 . U - state at given time 4039 4040 Level: intermediate 4041 4042 Developer Notes: 4043 TSInterpolate() and the storing of previous steps/stages should be generalized to support delay differential equations and continuous adjoints. 4044 4045 .keywords: TS, set 4046 4047 .seealso: TSSetExactFinalTime(), TSSolve() 4048 @*/ 4049 PetscErrorCode TSInterpolate(TS ts,PetscReal t,Vec U) 4050 { 4051 PetscErrorCode ierr; 4052 4053 PetscFunctionBegin; 4054 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4055 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 4056 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); 4057 if (!ts->ops->interpolate) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"%s does not provide interpolation",((PetscObject)ts)->type_name); 4058 ierr = (*ts->ops->interpolate)(ts,t,U);CHKERRQ(ierr); 4059 PetscFunctionReturn(0); 4060 } 4061 4062 /*@ 4063 TSStep - Steps one time step 4064 4065 Collective on TS 4066 4067 Input Parameter: 4068 . ts - the TS context obtained from TSCreate() 4069 4070 Level: developer 4071 4072 Notes: 4073 The public interface for the ODE/DAE solvers is TSSolve(), you should almost for sure be using that routine and not this routine. 4074 4075 The hook set using TSSetPreStep() is called before each attempt to take the step. In general, the time step size may 4076 be changed due to adaptive error controller or solve failures. Note that steps may contain multiple stages. 4077 4078 This may over-step the final time provided in TSSetMaxTime() depending on the time-step used. TSSolve() interpolates to exactly the 4079 time provided in TSSetMaxTime(). One can use TSInterpolate() to determine an interpolated solution within the final timestep. 4080 4081 .keywords: TS, timestep, solve 4082 4083 .seealso: TSCreate(), TSSetUp(), TSDestroy(), TSSolve(), TSSetPreStep(), TSSetPreStage(), TSSetPostStage(), TSInterpolate() 4084 @*/ 4085 PetscErrorCode TSStep(TS ts) 4086 { 4087 PetscErrorCode ierr; 4088 static PetscBool cite = PETSC_FALSE; 4089 PetscReal ptime; 4090 4091 PetscFunctionBegin; 4092 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4093 ierr = PetscCitationsRegister("@techreport{tspaper,\n" 4094 " title = {{PETSc/TS}: A Modern Scalable {DAE/ODE} Solver Library},\n" 4095 " author = {Shrirang Abhyankar and Jed Brown and Emil Constantinescu and Debojyoti Ghosh and Barry F. Smith},\n" 4096 " type = {Preprint},\n" 4097 " number = {ANL/MCS-P5061-0114},\n" 4098 " institution = {Argonne National Laboratory},\n" 4099 " year = {2014}\n}\n",&cite);CHKERRQ(ierr); 4100 4101 ierr = TSSetUp(ts);CHKERRQ(ierr); 4102 ierr = TSTrajectorySetUp(ts->trajectory,ts);CHKERRQ(ierr); 4103 4104 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>"); 4105 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()"); 4106 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"); 4107 4108 if (!ts->steps) ts->ptime_prev = ts->ptime; 4109 ptime = ts->ptime; ts->ptime_prev_rollback = ts->ptime_prev; 4110 ts->reason = TS_CONVERGED_ITERATING; 4111 if (!ts->ops->step) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSStep not implemented for type '%s'",((PetscObject)ts)->type_name); 4112 ierr = PetscLogEventBegin(TS_Step,ts,0,0,0);CHKERRQ(ierr); 4113 ierr = (*ts->ops->step)(ts);CHKERRQ(ierr); 4114 ierr = PetscLogEventEnd(TS_Step,ts,0,0,0);CHKERRQ(ierr); 4115 ts->ptime_prev = ptime; 4116 ts->steps++; 4117 ts->steprollback = PETSC_FALSE; 4118 ts->steprestart = PETSC_FALSE; 4119 4120 if (ts->reason < 0) { 4121 if (ts->errorifstepfailed) { 4122 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]); 4123 else SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s",TSConvergedReasons[ts->reason]); 4124 } 4125 } else if (!ts->reason) { 4126 if (ts->steps >= ts->max_steps) ts->reason = TS_CONVERGED_ITS; 4127 else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME; 4128 } 4129 PetscFunctionReturn(0); 4130 } 4131 4132 /*@ 4133 TSAdjointStep - Steps one time step backward in the adjoint run 4134 4135 Collective on TS 4136 4137 Input Parameter: 4138 . ts - the TS context obtained from TSCreate() 4139 4140 Level: intermediate 4141 4142 .keywords: TS, adjoint, step 4143 4144 .seealso: TSAdjointSetUp(), TSAdjointSolve() 4145 @*/ 4146 PetscErrorCode TSAdjointStep(TS ts) 4147 { 4148 DM dm; 4149 PetscErrorCode ierr; 4150 4151 PetscFunctionBegin; 4152 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4153 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 4154 ierr = TSAdjointSetUp(ts);CHKERRQ(ierr); 4155 4156 ierr = VecViewFromOptions(ts->vec_sol,(PetscObject)ts,"-ts_view_solution");CHKERRQ(ierr); 4157 4158 ts->reason = TS_CONVERGED_ITERATING; 4159 ts->ptime_prev = ts->ptime; 4160 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); 4161 ierr = PetscLogEventBegin(TS_AdjointStep,ts,0,0,0);CHKERRQ(ierr); 4162 ierr = (*ts->ops->adjointstep)(ts);CHKERRQ(ierr); 4163 ierr = PetscLogEventEnd(TS_AdjointStep,ts,0,0,0);CHKERRQ(ierr); 4164 ts->adjoint_steps++; ts->steps--; 4165 4166 if (ts->reason < 0) { 4167 if (ts->errorifstepfailed) { 4168 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]); 4169 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]); 4170 else SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s",TSConvergedReasons[ts->reason]); 4171 } 4172 } else if (!ts->reason) { 4173 if (ts->adjoint_steps >= ts->adjoint_max_steps) ts->reason = TS_CONVERGED_ITS; 4174 } 4175 PetscFunctionReturn(0); 4176 } 4177 4178 /*@ 4179 TSEvaluateWLTE - Evaluate the weighted local truncation error norm 4180 at the end of a time step with a given order of accuracy. 4181 4182 Collective on TS 4183 4184 Input Arguments: 4185 + ts - time stepping context 4186 . wnormtype - norm type, either NORM_2 or NORM_INFINITY 4187 - order - optional, desired order for the error evaluation or PETSC_DECIDE 4188 4189 Output Arguments: 4190 + order - optional, the actual order of the error evaluation 4191 - wlte - the weighted local truncation error norm 4192 4193 Level: advanced 4194 4195 Notes: 4196 If the timestepper cannot evaluate the error in a particular step 4197 (eg. in the first step or restart steps after event handling), 4198 this routine returns wlte=-1.0 . 4199 4200 .seealso: TSStep(), TSAdapt, TSErrorWeightedNorm() 4201 @*/ 4202 PetscErrorCode TSEvaluateWLTE(TS ts,NormType wnormtype,PetscInt *order,PetscReal *wlte) 4203 { 4204 PetscErrorCode ierr; 4205 4206 PetscFunctionBegin; 4207 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4208 PetscValidType(ts,1); 4209 PetscValidLogicalCollectiveEnum(ts,wnormtype,4); 4210 if (order) PetscValidIntPointer(order,3); 4211 if (order) PetscValidLogicalCollectiveInt(ts,*order,3); 4212 PetscValidRealPointer(wlte,4); 4213 if (wnormtype != NORM_2 && wnormtype != NORM_INFINITY) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]); 4214 if (!ts->ops->evaluatewlte) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSEvaluateWLTE not implemented for type '%s'",((PetscObject)ts)->type_name); 4215 ierr = (*ts->ops->evaluatewlte)(ts,wnormtype,order,wlte);CHKERRQ(ierr); 4216 PetscFunctionReturn(0); 4217 } 4218 4219 /*@ 4220 TSEvaluateStep - Evaluate the solution at the end of a time step with a given order of accuracy. 4221 4222 Collective on TS 4223 4224 Input Arguments: 4225 + ts - time stepping context 4226 . order - desired order of accuracy 4227 - done - whether the step was evaluated at this order (pass NULL to generate an error if not available) 4228 4229 Output Arguments: 4230 . U - state at the end of the current step 4231 4232 Level: advanced 4233 4234 Notes: 4235 This function cannot be called until all stages have been evaluated. 4236 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. 4237 4238 .seealso: TSStep(), TSAdapt 4239 @*/ 4240 PetscErrorCode TSEvaluateStep(TS ts,PetscInt order,Vec U,PetscBool *done) 4241 { 4242 PetscErrorCode ierr; 4243 4244 PetscFunctionBegin; 4245 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4246 PetscValidType(ts,1); 4247 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 4248 if (!ts->ops->evaluatestep) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSEvaluateStep not implemented for type '%s'",((PetscObject)ts)->type_name); 4249 ierr = (*ts->ops->evaluatestep)(ts,order,U,done);CHKERRQ(ierr); 4250 PetscFunctionReturn(0); 4251 } 4252 4253 /*@ 4254 TSForwardCostIntegral - Evaluate the cost integral in the forward run. 4255 4256 Collective on TS 4257 4258 Input Arguments: 4259 . ts - time stepping context 4260 4261 Level: advanced 4262 4263 Notes: 4264 This function cannot be called until TSStep() has been completed. 4265 4266 .seealso: TSSolve(), TSAdjointCostIntegral() 4267 @*/ 4268 PetscErrorCode TSForwardCostIntegral(TS ts) 4269 { 4270 PetscErrorCode ierr; 4271 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4272 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); 4273 ierr = (*ts->ops->forwardintegral)(ts);CHKERRQ(ierr); 4274 PetscFunctionReturn(0); 4275 } 4276 4277 /*@ 4278 TSSolve - Steps the requested number of timesteps. 4279 4280 Collective on TS 4281 4282 Input Parameter: 4283 + ts - the TS context obtained from TSCreate() 4284 - u - the solution vector (can be null if TSSetSolution() was used and TSSetExactFinalTime(ts,TS_EXACTFINALTIME_MATCHSTEP) was not used, 4285 otherwise must contain the initial conditions and will contain the solution at the final requested time 4286 4287 Level: beginner 4288 4289 Notes: 4290 The final time returned by this function may be different from the time of the internally 4291 held state accessible by TSGetSolution() and TSGetTime() because the method may have 4292 stepped over the final time. 4293 4294 .keywords: TS, timestep, solve 4295 4296 .seealso: TSCreate(), TSSetSolution(), TSStep(), TSGetTime(), TSGetSolveTime() 4297 @*/ 4298 PetscErrorCode TSSolve(TS ts,Vec u) 4299 { 4300 Vec solution; 4301 PetscErrorCode ierr; 4302 4303 PetscFunctionBegin; 4304 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4305 if (u) PetscValidHeaderSpecific(u,VEC_CLASSID,2); 4306 4307 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 */ 4308 PetscValidHeaderSpecific(u,VEC_CLASSID,2); 4309 if (!ts->vec_sol || u == ts->vec_sol) { 4310 ierr = VecDuplicate(u,&solution);CHKERRQ(ierr); 4311 ierr = TSSetSolution(ts,solution);CHKERRQ(ierr); 4312 ierr = VecDestroy(&solution);CHKERRQ(ierr); /* grant ownership */ 4313 } 4314 ierr = VecCopy(u,ts->vec_sol);CHKERRQ(ierr); 4315 if (ts->forward_solve) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Sensitivity analysis does not support the mode TS_EXACTFINALTIME_INTERPOLATE"); 4316 } else if (u) { 4317 ierr = TSSetSolution(ts,u);CHKERRQ(ierr); 4318 } 4319 ierr = TSSetUp(ts);CHKERRQ(ierr); 4320 ierr = TSTrajectorySetUp(ts->trajectory,ts);CHKERRQ(ierr); 4321 4322 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>"); 4323 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()"); 4324 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"); 4325 4326 if (ts->forward_solve) { 4327 ierr = TSForwardSetUp(ts);CHKERRQ(ierr); 4328 } 4329 4330 /* reset number of steps only when the step is not restarted. ARKIMEX 4331 restarts the step after an event. Resetting these counters in such case causes 4332 TSTrajectory to incorrectly save the output files 4333 */ 4334 /* reset time step and iteration counters */ 4335 4336 if (!ts->steps) { 4337 ts->ksp_its = 0; 4338 ts->snes_its = 0; 4339 ts->num_snes_failures = 0; 4340 ts->reject = 0; 4341 ts->steprestart = PETSC_TRUE; 4342 ts->steprollback = PETSC_FALSE; 4343 } 4344 ts->reason = TS_CONVERGED_ITERATING; 4345 4346 ierr = TSViewFromOptions(ts,NULL,"-ts_view_pre");CHKERRQ(ierr); 4347 4348 if (ts->ops->solve) { /* This private interface is transitional and should be removed when all implementations are updated. */ 4349 ierr = (*ts->ops->solve)(ts);CHKERRQ(ierr); 4350 if (u) {ierr = VecCopy(ts->vec_sol,u);CHKERRQ(ierr);} 4351 ts->solvetime = ts->ptime; 4352 solution = ts->vec_sol; 4353 } else { /* Step the requested number of timesteps. */ 4354 if (ts->steps >= ts->max_steps) ts->reason = TS_CONVERGED_ITS; 4355 else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME; 4356 4357 if (!ts->steps) { 4358 ierr = TSTrajectorySet(ts->trajectory,ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 4359 ierr = TSEventInitialize(ts->event,ts,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 4360 } 4361 4362 while (!ts->reason) { 4363 ierr = TSMonitor(ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 4364 if (!ts->steprollback) { 4365 ierr = TSPreStep(ts);CHKERRQ(ierr); 4366 } 4367 ierr = TSStep(ts);CHKERRQ(ierr); 4368 if (ts->vec_costintegral && ts->costintegralfwd) { /* Must evaluate the cost integral before event is handled. The cost integral value can also be rolled back. */ 4369 ierr = TSForwardCostIntegral(ts);CHKERRQ(ierr); 4370 } 4371 if (ts->forward_solve) { /* compute forward sensitivities before event handling because postevent() may change RHS and jump conditions may have to be applied */ 4372 ierr = TSForwardStep(ts);CHKERRQ(ierr); 4373 } 4374 ierr = TSPostEvaluate(ts);CHKERRQ(ierr); 4375 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. */ 4376 if (ts->steprollback) { 4377 ierr = TSPostEvaluate(ts);CHKERRQ(ierr); 4378 } 4379 if (!ts->steprollback) { 4380 ierr = TSTrajectorySet(ts->trajectory,ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 4381 ierr = TSPostStep(ts);CHKERRQ(ierr); 4382 } 4383 } 4384 ierr = TSMonitor(ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 4385 4386 if (ts->exact_final_time == TS_EXACTFINALTIME_INTERPOLATE && ts->ptime > ts->max_time) { 4387 ierr = TSInterpolate(ts,ts->max_time,u);CHKERRQ(ierr); 4388 ts->solvetime = ts->max_time; 4389 solution = u; 4390 ierr = TSMonitor(ts,-1,ts->solvetime,solution);CHKERRQ(ierr); 4391 } else { 4392 if (u) {ierr = VecCopy(ts->vec_sol,u);CHKERRQ(ierr);} 4393 ts->solvetime = ts->ptime; 4394 solution = ts->vec_sol; 4395 } 4396 } 4397 4398 ierr = TSViewFromOptions(ts,NULL,"-ts_view");CHKERRQ(ierr); 4399 ierr = VecViewFromOptions(solution,NULL,"-ts_view_solution");CHKERRQ(ierr); 4400 ierr = PetscObjectSAWsBlock((PetscObject)ts);CHKERRQ(ierr); 4401 if (ts->adjoint_solve) { 4402 ierr = TSAdjointSolve(ts);CHKERRQ(ierr); 4403 } 4404 PetscFunctionReturn(0); 4405 } 4406 4407 /*@ 4408 TSAdjointCostIntegral - Evaluate the cost integral in the adjoint run. 4409 4410 Collective on TS 4411 4412 Input Arguments: 4413 . ts - time stepping context 4414 4415 Level: advanced 4416 4417 Notes: 4418 This function cannot be called until TSAdjointStep() has been completed. 4419 4420 .seealso: TSAdjointSolve(), TSAdjointStep 4421 @*/ 4422 PetscErrorCode TSAdjointCostIntegral(TS ts) 4423 { 4424 PetscErrorCode ierr; 4425 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4426 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); 4427 ierr = (*ts->ops->adjointintegral)(ts);CHKERRQ(ierr); 4428 PetscFunctionReturn(0); 4429 } 4430 4431 /*@ 4432 TSAdjointSolve - Solves the discrete ajoint problem for an ODE/DAE 4433 4434 Collective on TS 4435 4436 Input Parameter: 4437 . ts - the TS context obtained from TSCreate() 4438 4439 Options Database: 4440 . -ts_adjoint_view_solution <viewerinfo> - views the first gradient with respect to the initial values 4441 4442 Level: intermediate 4443 4444 Notes: 4445 This must be called after a call to TSSolve() that solves the forward problem 4446 4447 By default this will integrate back to the initial time, one can use TSAdjointSetSteps() to step back to a later time 4448 4449 .keywords: TS, timestep, solve 4450 4451 .seealso: TSCreate(), TSSetCostGradients(), TSSetSolution(), TSAdjointStep() 4452 @*/ 4453 PetscErrorCode TSAdjointSolve(TS ts) 4454 { 4455 PetscErrorCode ierr; 4456 4457 PetscFunctionBegin; 4458 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4459 ierr = TSAdjointSetUp(ts);CHKERRQ(ierr); 4460 4461 /* reset time step and iteration counters */ 4462 ts->adjoint_steps = 0; 4463 ts->ksp_its = 0; 4464 ts->snes_its = 0; 4465 ts->num_snes_failures = 0; 4466 ts->reject = 0; 4467 ts->reason = TS_CONVERGED_ITERATING; 4468 4469 if (!ts->adjoint_max_steps) ts->adjoint_max_steps = ts->steps; 4470 if (ts->adjoint_steps >= ts->adjoint_max_steps) ts->reason = TS_CONVERGED_ITS; 4471 4472 while (!ts->reason) { 4473 ierr = TSTrajectoryGet(ts->trajectory,ts,ts->steps,&ts->ptime);CHKERRQ(ierr); 4474 ierr = TSAdjointMonitor(ts,ts->steps,ts->ptime,ts->vec_sol,ts->numcost,ts->vecs_sensi,ts->vecs_sensip);CHKERRQ(ierr); 4475 ierr = TSAdjointEventHandler(ts);CHKERRQ(ierr); 4476 ierr = TSAdjointStep(ts);CHKERRQ(ierr); 4477 if (ts->vec_costintegral && !ts->costintegralfwd) { 4478 ierr = TSAdjointCostIntegral(ts);CHKERRQ(ierr); 4479 } 4480 } 4481 ierr = TSTrajectoryGet(ts->trajectory,ts,ts->steps,&ts->ptime);CHKERRQ(ierr); 4482 ierr = TSAdjointMonitor(ts,ts->steps,ts->ptime,ts->vec_sol,ts->numcost,ts->vecs_sensi,ts->vecs_sensip);CHKERRQ(ierr); 4483 ts->solvetime = ts->ptime; 4484 ierr = TSTrajectoryViewFromOptions(ts->trajectory,NULL,"-ts_trajectory_view");CHKERRQ(ierr); 4485 ierr = VecViewFromOptions(ts->vecs_sensi[0],(PetscObject) ts, "-ts_adjoint_view_solution");CHKERRQ(ierr); 4486 PetscFunctionReturn(0); 4487 } 4488 4489 /*@C 4490 TSMonitor - Runs all user-provided monitor routines set using TSMonitorSet() 4491 4492 Collective on TS 4493 4494 Input Parameters: 4495 + ts - time stepping context obtained from TSCreate() 4496 . step - step number that has just completed 4497 . ptime - model time of the state 4498 - u - state at the current model time 4499 4500 Notes: 4501 TSMonitor() is typically used automatically within the time stepping implementations. 4502 Users would almost never call this routine directly. 4503 4504 A step of -1 indicates that the monitor is being called on a solution obtained by interpolating from computed solutions 4505 4506 Level: developer 4507 4508 .keywords: TS, timestep 4509 @*/ 4510 PetscErrorCode TSMonitor(TS ts,PetscInt step,PetscReal ptime,Vec u) 4511 { 4512 DM dm; 4513 PetscInt i,n = ts->numbermonitors; 4514 PetscErrorCode ierr; 4515 4516 PetscFunctionBegin; 4517 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4518 PetscValidHeaderSpecific(u,VEC_CLASSID,4); 4519 4520 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 4521 ierr = DMSetOutputSequenceNumber(dm,step,ptime);CHKERRQ(ierr); 4522 4523 ierr = VecLockPush(u);CHKERRQ(ierr); 4524 for (i=0; i<n; i++) { 4525 ierr = (*ts->monitor[i])(ts,step,ptime,u,ts->monitorcontext[i]);CHKERRQ(ierr); 4526 } 4527 ierr = VecLockPop(u);CHKERRQ(ierr); 4528 PetscFunctionReturn(0); 4529 } 4530 4531 /*@C 4532 TSAdjointMonitor - Runs all user-provided adjoint monitor routines set using TSAdjointMonitorSet() 4533 4534 Collective on TS 4535 4536 Input Parameters: 4537 + ts - time stepping context obtained from TSCreate() 4538 . step - step number that has just completed 4539 . ptime - model time of the state 4540 . u - state at the current model time 4541 . numcost - number of cost functions (dimension of lambda or mu) 4542 . lambda - vectors containing the gradients of the cost functions with respect to the ODE/DAE solution variables 4543 - mu - vectors containing the gradients of the cost functions with respect to the problem parameters 4544 4545 Notes: 4546 TSAdjointMonitor() is typically used automatically within the time stepping implementations. 4547 Users would almost never call this routine directly. 4548 4549 Level: developer 4550 4551 .keywords: TS, timestep 4552 @*/ 4553 PetscErrorCode TSAdjointMonitor(TS ts,PetscInt step,PetscReal ptime,Vec u,PetscInt numcost,Vec *lambda, Vec *mu) 4554 { 4555 PetscErrorCode ierr; 4556 PetscInt i,n = ts->numberadjointmonitors; 4557 4558 PetscFunctionBegin; 4559 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4560 PetscValidHeaderSpecific(u,VEC_CLASSID,4); 4561 ierr = VecLockPush(u);CHKERRQ(ierr); 4562 for (i=0; i<n; i++) { 4563 ierr = (*ts->adjointmonitor[i])(ts,step,ptime,u,numcost,lambda,mu,ts->adjointmonitorcontext[i]);CHKERRQ(ierr); 4564 } 4565 ierr = VecLockPop(u);CHKERRQ(ierr); 4566 PetscFunctionReturn(0); 4567 } 4568 4569 /* ------------------------------------------------------------------------*/ 4570 /*@C 4571 TSMonitorLGCtxCreate - Creates a TSMonitorLGCtx context for use with 4572 TS to monitor the solution process graphically in various ways 4573 4574 Collective on TS 4575 4576 Input Parameters: 4577 + host - the X display to open, or null for the local machine 4578 . label - the title to put in the title bar 4579 . x, y - the screen coordinates of the upper left coordinate of the window 4580 . m, n - the screen width and height in pixels 4581 - howoften - if positive then determines the frequency of the plotting, if -1 then only at the final time 4582 4583 Output Parameter: 4584 . ctx - the context 4585 4586 Options Database Key: 4587 + -ts_monitor_lg_timestep - automatically sets line graph monitor 4588 + -ts_monitor_lg_timestep_log - automatically sets line graph monitor 4589 . -ts_monitor_lg_solution - monitor the solution (or certain values of the solution by calling TSMonitorLGSetDisplayVariables() or TSMonitorLGCtxSetDisplayVariables()) 4590 . -ts_monitor_lg_error - monitor the error 4591 . -ts_monitor_lg_ksp_iterations - monitor the number of KSP iterations needed for each timestep 4592 . -ts_monitor_lg_snes_iterations - monitor the number of SNES iterations needed for each timestep 4593 - -lg_use_markers <true,false> - mark the data points (at each time step) on the plot; default is true 4594 4595 Notes: 4596 Use TSMonitorLGCtxDestroy() to destroy. 4597 4598 One can provide a function that transforms the solution before plotting it with TSMonitorLGCtxSetTransform() or TSMonitorLGSetTransform() 4599 4600 Many of the functions that control the monitoring have two forms: TSMonitorLGSet/GetXXXX() and TSMonitorLGCtxSet/GetXXXX() the first take a TS object as the 4601 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 4602 as the first argument. 4603 4604 One can control the names displayed for each solution or error variable with TSMonitorLGCtxSetVariableNames() or TSMonitorLGSetVariableNames() 4605 4606 Level: intermediate 4607 4608 .keywords: TS, monitor, line graph, residual 4609 4610 .seealso: TSMonitorLGTimeStep(), TSMonitorSet(), TSMonitorLGSolution(), TSMonitorLGError(), TSMonitorDefault(), VecView(), 4611 TSMonitorLGCtxCreate(), TSMonitorLGCtxSetVariableNames(), TSMonitorLGCtxGetVariableNames(), 4612 TSMonitorLGSetVariableNames(), TSMonitorLGGetVariableNames(), TSMonitorLGSetDisplayVariables(), TSMonitorLGCtxSetDisplayVariables(), 4613 TSMonitorLGCtxSetTransform(), TSMonitorLGSetTransform(), TSMonitorLGError(), TSMonitorLGSNESIterations(), TSMonitorLGKSPIterations(), 4614 TSMonitorEnvelopeCtxCreate(), TSMonitorEnvelopeGetBounds(), TSMonitorEnvelopeCtxDestroy(), TSMonitorEnvelop() 4615 4616 @*/ 4617 PetscErrorCode TSMonitorLGCtxCreate(MPI_Comm comm,const char host[],const char label[],int x,int y,int m,int n,PetscInt howoften,TSMonitorLGCtx *ctx) 4618 { 4619 PetscDraw draw; 4620 PetscErrorCode ierr; 4621 4622 PetscFunctionBegin; 4623 ierr = PetscNew(ctx);CHKERRQ(ierr); 4624 ierr = PetscDrawCreate(comm,host,label,x,y,m,n,&draw);CHKERRQ(ierr); 4625 ierr = PetscDrawSetFromOptions(draw);CHKERRQ(ierr); 4626 ierr = PetscDrawLGCreate(draw,1,&(*ctx)->lg);CHKERRQ(ierr); 4627 ierr = PetscDrawLGSetFromOptions((*ctx)->lg);CHKERRQ(ierr); 4628 ierr = PetscDrawDestroy(&draw);CHKERRQ(ierr); 4629 (*ctx)->howoften = howoften; 4630 PetscFunctionReturn(0); 4631 } 4632 4633 PetscErrorCode TSMonitorLGTimeStep(TS ts,PetscInt step,PetscReal ptime,Vec v,void *monctx) 4634 { 4635 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 4636 PetscReal x = ptime,y; 4637 PetscErrorCode ierr; 4638 4639 PetscFunctionBegin; 4640 if (step < 0) PetscFunctionReturn(0); /* -1 indicates an interpolated solution */ 4641 if (!step) { 4642 PetscDrawAxis axis; 4643 const char *ylabel = ctx->semilogy ? "Log Time Step" : "Time Step"; 4644 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 4645 ierr = PetscDrawAxisSetLabels(axis,"Timestep as function of time","Time",ylabel);CHKERRQ(ierr); 4646 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 4647 } 4648 ierr = TSGetTimeStep(ts,&y);CHKERRQ(ierr); 4649 if (ctx->semilogy) y = PetscLog10Real(y); 4650 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 4651 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 4652 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 4653 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 4654 } 4655 PetscFunctionReturn(0); 4656 } 4657 4658 /*@C 4659 TSMonitorLGCtxDestroy - Destroys a line graph context that was created 4660 with TSMonitorLGCtxCreate(). 4661 4662 Collective on TSMonitorLGCtx 4663 4664 Input Parameter: 4665 . ctx - the monitor context 4666 4667 Level: intermediate 4668 4669 .keywords: TS, monitor, line graph, destroy 4670 4671 .seealso: TSMonitorLGCtxCreate(), TSMonitorSet(), TSMonitorLGTimeStep(); 4672 @*/ 4673 PetscErrorCode TSMonitorLGCtxDestroy(TSMonitorLGCtx *ctx) 4674 { 4675 PetscErrorCode ierr; 4676 4677 PetscFunctionBegin; 4678 if ((*ctx)->transformdestroy) { 4679 ierr = ((*ctx)->transformdestroy)((*ctx)->transformctx);CHKERRQ(ierr); 4680 } 4681 ierr = PetscDrawLGDestroy(&(*ctx)->lg);CHKERRQ(ierr); 4682 ierr = PetscStrArrayDestroy(&(*ctx)->names);CHKERRQ(ierr); 4683 ierr = PetscStrArrayDestroy(&(*ctx)->displaynames);CHKERRQ(ierr); 4684 ierr = PetscFree((*ctx)->displayvariables);CHKERRQ(ierr); 4685 ierr = PetscFree((*ctx)->displayvalues);CHKERRQ(ierr); 4686 ierr = PetscFree(*ctx);CHKERRQ(ierr); 4687 PetscFunctionReturn(0); 4688 } 4689 4690 /*@ 4691 TSGetTime - Gets the time of the most recently completed step. 4692 4693 Not Collective 4694 4695 Input Parameter: 4696 . ts - the TS context obtained from TSCreate() 4697 4698 Output Parameter: 4699 . t - the current time. This time may not corresponds to the final time set with TSSetMaxTime(), use TSGetSolveTime(). 4700 4701 Level: beginner 4702 4703 Note: 4704 When called during time step evaluation (e.g. during residual evaluation or via hooks set using TSSetPreStep(), 4705 TSSetPreStage(), TSSetPostStage(), or TSSetPostStep()), the time is the time at the start of the step being evaluated. 4706 4707 .seealso: TSGetSolveTime(), TSSetTime(), TSGetTimeStep() 4708 4709 .keywords: TS, get, time 4710 @*/ 4711 PetscErrorCode TSGetTime(TS ts,PetscReal *t) 4712 { 4713 PetscFunctionBegin; 4714 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4715 PetscValidRealPointer(t,2); 4716 *t = ts->ptime; 4717 PetscFunctionReturn(0); 4718 } 4719 4720 /*@ 4721 TSGetPrevTime - Gets the starting time of the previously completed step. 4722 4723 Not Collective 4724 4725 Input Parameter: 4726 . ts - the TS context obtained from TSCreate() 4727 4728 Output Parameter: 4729 . t - the previous time 4730 4731 Level: beginner 4732 4733 .seealso: TSGetTime(), TSGetSolveTime(), TSGetTimeStep() 4734 4735 .keywords: TS, get, time 4736 @*/ 4737 PetscErrorCode TSGetPrevTime(TS ts,PetscReal *t) 4738 { 4739 PetscFunctionBegin; 4740 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4741 PetscValidRealPointer(t,2); 4742 *t = ts->ptime_prev; 4743 PetscFunctionReturn(0); 4744 } 4745 4746 /*@ 4747 TSSetTime - Allows one to reset the time. 4748 4749 Logically Collective on TS 4750 4751 Input Parameters: 4752 + ts - the TS context obtained from TSCreate() 4753 - time - the time 4754 4755 Level: intermediate 4756 4757 .seealso: TSGetTime(), TSSetMaxSteps() 4758 4759 .keywords: TS, set, time 4760 @*/ 4761 PetscErrorCode TSSetTime(TS ts, PetscReal t) 4762 { 4763 PetscFunctionBegin; 4764 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4765 PetscValidLogicalCollectiveReal(ts,t,2); 4766 ts->ptime = t; 4767 PetscFunctionReturn(0); 4768 } 4769 4770 /*@C 4771 TSSetOptionsPrefix - Sets the prefix used for searching for all 4772 TS options in the database. 4773 4774 Logically Collective on TS 4775 4776 Input Parameter: 4777 + ts - The TS context 4778 - prefix - The prefix to prepend to all option names 4779 4780 Notes: 4781 A hyphen (-) must NOT be given at the beginning of the prefix name. 4782 The first character of all runtime options is AUTOMATICALLY the 4783 hyphen. 4784 4785 Level: advanced 4786 4787 .keywords: TS, set, options, prefix, database 4788 4789 .seealso: TSSetFromOptions() 4790 4791 @*/ 4792 PetscErrorCode TSSetOptionsPrefix(TS ts,const char prefix[]) 4793 { 4794 PetscErrorCode ierr; 4795 SNES snes; 4796 4797 PetscFunctionBegin; 4798 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4799 ierr = PetscObjectSetOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 4800 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4801 ierr = SNESSetOptionsPrefix(snes,prefix);CHKERRQ(ierr); 4802 PetscFunctionReturn(0); 4803 } 4804 4805 /*@C 4806 TSAppendOptionsPrefix - Appends to the prefix used for searching for all 4807 TS options in the database. 4808 4809 Logically Collective on TS 4810 4811 Input Parameter: 4812 + ts - The TS context 4813 - prefix - The prefix to prepend to all option names 4814 4815 Notes: 4816 A hyphen (-) must NOT be given at the beginning of the prefix name. 4817 The first character of all runtime options is AUTOMATICALLY the 4818 hyphen. 4819 4820 Level: advanced 4821 4822 .keywords: TS, append, options, prefix, database 4823 4824 .seealso: TSGetOptionsPrefix() 4825 4826 @*/ 4827 PetscErrorCode TSAppendOptionsPrefix(TS ts,const char prefix[]) 4828 { 4829 PetscErrorCode ierr; 4830 SNES snes; 4831 4832 PetscFunctionBegin; 4833 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4834 ierr = PetscObjectAppendOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 4835 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4836 ierr = SNESAppendOptionsPrefix(snes,prefix);CHKERRQ(ierr); 4837 PetscFunctionReturn(0); 4838 } 4839 4840 /*@C 4841 TSGetOptionsPrefix - Sets the prefix used for searching for all 4842 TS options in the database. 4843 4844 Not Collective 4845 4846 Input Parameter: 4847 . ts - The TS context 4848 4849 Output Parameter: 4850 . prefix - A pointer to the prefix string used 4851 4852 Notes: On the fortran side, the user should pass in a string 'prifix' of 4853 sufficient length to hold the prefix. 4854 4855 Level: intermediate 4856 4857 .keywords: TS, get, options, prefix, database 4858 4859 .seealso: TSAppendOptionsPrefix() 4860 @*/ 4861 PetscErrorCode TSGetOptionsPrefix(TS ts,const char *prefix[]) 4862 { 4863 PetscErrorCode ierr; 4864 4865 PetscFunctionBegin; 4866 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4867 PetscValidPointer(prefix,2); 4868 ierr = PetscObjectGetOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 4869 PetscFunctionReturn(0); 4870 } 4871 4872 /*@C 4873 TSGetRHSJacobian - Returns the Jacobian J at the present timestep. 4874 4875 Not Collective, but parallel objects are returned if TS is parallel 4876 4877 Input Parameter: 4878 . ts - The TS context obtained from TSCreate() 4879 4880 Output Parameters: 4881 + Amat - The (approximate) Jacobian J of G, where U_t = G(U,t) (or NULL) 4882 . Pmat - The matrix from which the preconditioner is constructed, usually the same as Amat (or NULL) 4883 . func - Function to compute the Jacobian of the RHS (or NULL) 4884 - ctx - User-defined context for Jacobian evaluation routine (or NULL) 4885 4886 Notes: You can pass in NULL for any return argument you do not need. 4887 4888 Level: intermediate 4889 4890 .seealso: TSGetTimeStep(), TSGetMatrices(), TSGetTime(), TSGetStepNumber() 4891 4892 .keywords: TS, timestep, get, matrix, Jacobian 4893 @*/ 4894 PetscErrorCode TSGetRHSJacobian(TS ts,Mat *Amat,Mat *Pmat,TSRHSJacobian *func,void **ctx) 4895 { 4896 PetscErrorCode ierr; 4897 DM dm; 4898 4899 PetscFunctionBegin; 4900 if (Amat || Pmat) { 4901 SNES snes; 4902 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4903 ierr = SNESSetUpMatrices(snes);CHKERRQ(ierr); 4904 ierr = SNESGetJacobian(snes,Amat,Pmat,NULL,NULL);CHKERRQ(ierr); 4905 } 4906 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 4907 ierr = DMTSGetRHSJacobian(dm,func,ctx);CHKERRQ(ierr); 4908 PetscFunctionReturn(0); 4909 } 4910 4911 /*@C 4912 TSGetIJacobian - Returns the implicit Jacobian at the present timestep. 4913 4914 Not Collective, but parallel objects are returned if TS is parallel 4915 4916 Input Parameter: 4917 . ts - The TS context obtained from TSCreate() 4918 4919 Output Parameters: 4920 + Amat - The (approximate) Jacobian of F(t,U,U_t) 4921 . Pmat - The matrix from which the preconditioner is constructed, often the same as Amat 4922 . f - The function to compute the matrices 4923 - ctx - User-defined context for Jacobian evaluation routine 4924 4925 Notes: You can pass in NULL for any return argument you do not need. 4926 4927 Level: advanced 4928 4929 .seealso: TSGetTimeStep(), TSGetRHSJacobian(), TSGetMatrices(), TSGetTime(), TSGetStepNumber() 4930 4931 .keywords: TS, timestep, get, matrix, Jacobian 4932 @*/ 4933 PetscErrorCode TSGetIJacobian(TS ts,Mat *Amat,Mat *Pmat,TSIJacobian *f,void **ctx) 4934 { 4935 PetscErrorCode ierr; 4936 DM dm; 4937 4938 PetscFunctionBegin; 4939 if (Amat || Pmat) { 4940 SNES snes; 4941 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4942 ierr = SNESSetUpMatrices(snes);CHKERRQ(ierr); 4943 ierr = SNESGetJacobian(snes,Amat,Pmat,NULL,NULL);CHKERRQ(ierr); 4944 } 4945 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 4946 ierr = DMTSGetIJacobian(dm,f,ctx);CHKERRQ(ierr); 4947 PetscFunctionReturn(0); 4948 } 4949 4950 /*@C 4951 TSMonitorDrawSolution - Monitors progress of the TS solvers by calling 4952 VecView() for the solution at each timestep 4953 4954 Collective on TS 4955 4956 Input Parameters: 4957 + ts - the TS context 4958 . step - current time-step 4959 . ptime - current time 4960 - dummy - either a viewer or NULL 4961 4962 Options Database: 4963 . -ts_monitor_draw_solution_initial - show initial solution as well as current solution 4964 4965 Notes: the initial solution and current solution are not display with a common axis scaling so generally the option -ts_monitor_draw_solution_initial 4966 will look bad 4967 4968 Level: intermediate 4969 4970 .keywords: TS, vector, monitor, view 4971 4972 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 4973 @*/ 4974 PetscErrorCode TSMonitorDrawSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 4975 { 4976 PetscErrorCode ierr; 4977 TSMonitorDrawCtx ictx = (TSMonitorDrawCtx)dummy; 4978 PetscDraw draw; 4979 4980 PetscFunctionBegin; 4981 if (!step && ictx->showinitial) { 4982 if (!ictx->initialsolution) { 4983 ierr = VecDuplicate(u,&ictx->initialsolution);CHKERRQ(ierr); 4984 } 4985 ierr = VecCopy(u,ictx->initialsolution);CHKERRQ(ierr); 4986 } 4987 if (!(((ictx->howoften > 0) && (!(step % ictx->howoften))) || ((ictx->howoften == -1) && ts->reason))) PetscFunctionReturn(0); 4988 4989 if (ictx->showinitial) { 4990 PetscReal pause; 4991 ierr = PetscViewerDrawGetPause(ictx->viewer,&pause);CHKERRQ(ierr); 4992 ierr = PetscViewerDrawSetPause(ictx->viewer,0.0);CHKERRQ(ierr); 4993 ierr = VecView(ictx->initialsolution,ictx->viewer);CHKERRQ(ierr); 4994 ierr = PetscViewerDrawSetPause(ictx->viewer,pause);CHKERRQ(ierr); 4995 ierr = PetscViewerDrawSetHold(ictx->viewer,PETSC_TRUE);CHKERRQ(ierr); 4996 } 4997 ierr = VecView(u,ictx->viewer);CHKERRQ(ierr); 4998 if (ictx->showtimestepandtime) { 4999 PetscReal xl,yl,xr,yr,h; 5000 char time[32]; 5001 5002 ierr = PetscViewerDrawGetDraw(ictx->viewer,0,&draw);CHKERRQ(ierr); 5003 ierr = PetscSNPrintf(time,32,"Timestep %d Time %g",(int)step,(double)ptime);CHKERRQ(ierr); 5004 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 5005 h = yl + .95*(yr - yl); 5006 ierr = PetscDrawStringCentered(draw,.5*(xl+xr),h,PETSC_DRAW_BLACK,time);CHKERRQ(ierr); 5007 ierr = PetscDrawFlush(draw);CHKERRQ(ierr); 5008 } 5009 5010 if (ictx->showinitial) { 5011 ierr = PetscViewerDrawSetHold(ictx->viewer,PETSC_FALSE);CHKERRQ(ierr); 5012 } 5013 PetscFunctionReturn(0); 5014 } 5015 5016 /*@C 5017 TSAdjointMonitorDrawSensi - Monitors progress of the adjoint TS solvers by calling 5018 VecView() for the sensitivities to initial states at each timestep 5019 5020 Collective on TS 5021 5022 Input Parameters: 5023 + ts - the TS context 5024 . step - current time-step 5025 . ptime - current time 5026 . u - current state 5027 . numcost - number of cost functions 5028 . lambda - sensitivities to initial conditions 5029 . mu - sensitivities to parameters 5030 - dummy - either a viewer or NULL 5031 5032 Level: intermediate 5033 5034 .keywords: TS, vector, adjoint, monitor, view 5035 5036 .seealso: TSAdjointMonitorSet(), TSAdjointMonitorDefault(), VecView() 5037 @*/ 5038 PetscErrorCode TSAdjointMonitorDrawSensi(TS ts,PetscInt step,PetscReal ptime,Vec u,PetscInt numcost,Vec *lambda,Vec *mu,void *dummy) 5039 { 5040 PetscErrorCode ierr; 5041 TSMonitorDrawCtx ictx = (TSMonitorDrawCtx)dummy; 5042 PetscDraw draw; 5043 PetscReal xl,yl,xr,yr,h; 5044 char time[32]; 5045 5046 PetscFunctionBegin; 5047 if (!(((ictx->howoften > 0) && (!(step % ictx->howoften))) || ((ictx->howoften == -1) && ts->reason))) PetscFunctionReturn(0); 5048 5049 ierr = VecView(lambda[0],ictx->viewer);CHKERRQ(ierr); 5050 ierr = PetscViewerDrawGetDraw(ictx->viewer,0,&draw);CHKERRQ(ierr); 5051 ierr = PetscSNPrintf(time,32,"Timestep %d Time %g",(int)step,(double)ptime);CHKERRQ(ierr); 5052 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 5053 h = yl + .95*(yr - yl); 5054 ierr = PetscDrawStringCentered(draw,.5*(xl+xr),h,PETSC_DRAW_BLACK,time);CHKERRQ(ierr); 5055 ierr = PetscDrawFlush(draw);CHKERRQ(ierr); 5056 PetscFunctionReturn(0); 5057 } 5058 5059 /*@C 5060 TSMonitorDrawSolutionPhase - Monitors progress of the TS solvers by plotting the solution as a phase diagram 5061 5062 Collective on TS 5063 5064 Input Parameters: 5065 + ts - the TS context 5066 . step - current time-step 5067 . ptime - current time 5068 - dummy - either a viewer or NULL 5069 5070 Level: intermediate 5071 5072 .keywords: TS, vector, monitor, view 5073 5074 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 5075 @*/ 5076 PetscErrorCode TSMonitorDrawSolutionPhase(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 5077 { 5078 PetscErrorCode ierr; 5079 TSMonitorDrawCtx ictx = (TSMonitorDrawCtx)dummy; 5080 PetscDraw draw; 5081 PetscDrawAxis axis; 5082 PetscInt n; 5083 PetscMPIInt size; 5084 PetscReal U0,U1,xl,yl,xr,yr,h; 5085 char time[32]; 5086 const PetscScalar *U; 5087 5088 PetscFunctionBegin; 5089 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)ts),&size);CHKERRQ(ierr); 5090 if (size != 1) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Only allowed for sequential runs"); 5091 ierr = VecGetSize(u,&n);CHKERRQ(ierr); 5092 if (n != 2) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Only for ODEs with two unknowns"); 5093 5094 ierr = PetscViewerDrawGetDraw(ictx->viewer,0,&draw);CHKERRQ(ierr); 5095 ierr = PetscViewerDrawGetDrawAxis(ictx->viewer,0,&axis);CHKERRQ(ierr); 5096 ierr = PetscDrawAxisGetLimits(axis,&xl,&xr,&yl,&yr);CHKERRQ(ierr); 5097 if (!step) { 5098 ierr = PetscDrawClear(draw);CHKERRQ(ierr); 5099 ierr = PetscDrawAxisDraw(axis);CHKERRQ(ierr); 5100 } 5101 5102 ierr = VecGetArrayRead(u,&U);CHKERRQ(ierr); 5103 U0 = PetscRealPart(U[0]); 5104 U1 = PetscRealPart(U[1]); 5105 ierr = VecRestoreArrayRead(u,&U);CHKERRQ(ierr); 5106 if ((U0 < xl) || (U1 < yl) || (U0 > xr) || (U1 > yr)) PetscFunctionReturn(0); 5107 5108 ierr = PetscDrawCollectiveBegin(draw);CHKERRQ(ierr); 5109 ierr = PetscDrawPoint(draw,U0,U1,PETSC_DRAW_BLACK);CHKERRQ(ierr); 5110 if (ictx->showtimestepandtime) { 5111 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 5112 ierr = PetscSNPrintf(time,32,"Timestep %d Time %g",(int)step,(double)ptime);CHKERRQ(ierr); 5113 h = yl + .95*(yr - yl); 5114 ierr = PetscDrawStringCentered(draw,.5*(xl+xr),h,PETSC_DRAW_BLACK,time);CHKERRQ(ierr); 5115 } 5116 ierr = PetscDrawCollectiveEnd(draw);CHKERRQ(ierr); 5117 ierr = PetscDrawFlush(draw);CHKERRQ(ierr); 5118 ierr = PetscDrawPause(draw);CHKERRQ(ierr); 5119 ierr = PetscDrawSave(draw);CHKERRQ(ierr); 5120 PetscFunctionReturn(0); 5121 } 5122 5123 /*@C 5124 TSMonitorDrawCtxDestroy - Destroys the monitor context for TSMonitorDrawSolution() 5125 5126 Collective on TS 5127 5128 Input Parameters: 5129 . ctx - the monitor context 5130 5131 Level: intermediate 5132 5133 .keywords: TS, vector, monitor, view 5134 5135 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorDrawSolution(), TSMonitorDrawError() 5136 @*/ 5137 PetscErrorCode TSMonitorDrawCtxDestroy(TSMonitorDrawCtx *ictx) 5138 { 5139 PetscErrorCode ierr; 5140 5141 PetscFunctionBegin; 5142 ierr = PetscViewerDestroy(&(*ictx)->viewer);CHKERRQ(ierr); 5143 ierr = VecDestroy(&(*ictx)->initialsolution);CHKERRQ(ierr); 5144 ierr = PetscFree(*ictx);CHKERRQ(ierr); 5145 PetscFunctionReturn(0); 5146 } 5147 5148 /*@C 5149 TSMonitorDrawCtxCreate - Creates the monitor context for TSMonitorDrawCtx 5150 5151 Collective on TS 5152 5153 Input Parameter: 5154 . ts - time-step context 5155 5156 Output Patameter: 5157 . ctx - the monitor context 5158 5159 Options Database: 5160 . -ts_monitor_draw_solution_initial - show initial solution as well as current solution 5161 5162 Level: intermediate 5163 5164 .keywords: TS, vector, monitor, view 5165 5166 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorDrawCtx() 5167 @*/ 5168 PetscErrorCode TSMonitorDrawCtxCreate(MPI_Comm comm,const char host[],const char label[],int x,int y,int m,int n,PetscInt howoften,TSMonitorDrawCtx *ctx) 5169 { 5170 PetscErrorCode ierr; 5171 5172 PetscFunctionBegin; 5173 ierr = PetscNew(ctx);CHKERRQ(ierr); 5174 ierr = PetscViewerDrawOpen(comm,host,label,x,y,m,n,&(*ctx)->viewer);CHKERRQ(ierr); 5175 ierr = PetscViewerSetFromOptions((*ctx)->viewer);CHKERRQ(ierr); 5176 5177 (*ctx)->howoften = howoften; 5178 (*ctx)->showinitial = PETSC_FALSE; 5179 ierr = PetscOptionsGetBool(NULL,NULL,"-ts_monitor_draw_solution_initial",&(*ctx)->showinitial,NULL);CHKERRQ(ierr); 5180 5181 (*ctx)->showtimestepandtime = PETSC_FALSE; 5182 ierr = PetscOptionsGetBool(NULL,NULL,"-ts_monitor_draw_solution_show_time",&(*ctx)->showtimestepandtime,NULL);CHKERRQ(ierr); 5183 PetscFunctionReturn(0); 5184 } 5185 5186 /*@C 5187 TSMonitorDrawError - Monitors progress of the TS solvers by calling 5188 VecView() for the error at each timestep 5189 5190 Collective on TS 5191 5192 Input Parameters: 5193 + ts - the TS context 5194 . step - current time-step 5195 . ptime - current time 5196 - dummy - either a viewer or NULL 5197 5198 Level: intermediate 5199 5200 .keywords: TS, vector, monitor, view 5201 5202 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 5203 @*/ 5204 PetscErrorCode TSMonitorDrawError(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 5205 { 5206 PetscErrorCode ierr; 5207 TSMonitorDrawCtx ctx = (TSMonitorDrawCtx)dummy; 5208 PetscViewer viewer = ctx->viewer; 5209 Vec work; 5210 5211 PetscFunctionBegin; 5212 if (!(((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason))) PetscFunctionReturn(0); 5213 ierr = VecDuplicate(u,&work);CHKERRQ(ierr); 5214 ierr = TSComputeSolutionFunction(ts,ptime,work);CHKERRQ(ierr); 5215 ierr = VecAXPY(work,-1.0,u);CHKERRQ(ierr); 5216 ierr = VecView(work,viewer);CHKERRQ(ierr); 5217 ierr = VecDestroy(&work);CHKERRQ(ierr); 5218 PetscFunctionReturn(0); 5219 } 5220 5221 #include <petsc/private/dmimpl.h> 5222 /*@ 5223 TSSetDM - Sets the DM that may be used by some nonlinear solvers or preconditioners under the TS 5224 5225 Logically Collective on TS and DM 5226 5227 Input Parameters: 5228 + ts - the ODE integrator object 5229 - dm - the dm, cannot be NULL 5230 5231 Level: intermediate 5232 5233 .seealso: TSGetDM(), SNESSetDM(), SNESGetDM() 5234 @*/ 5235 PetscErrorCode TSSetDM(TS ts,DM dm) 5236 { 5237 PetscErrorCode ierr; 5238 SNES snes; 5239 DMTS tsdm; 5240 5241 PetscFunctionBegin; 5242 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5243 PetscValidHeaderSpecific(dm,DM_CLASSID,2); 5244 ierr = PetscObjectReference((PetscObject)dm);CHKERRQ(ierr); 5245 if (ts->dm) { /* Move the DMTS context over to the new DM unless the new DM already has one */ 5246 if (ts->dm->dmts && !dm->dmts) { 5247 ierr = DMCopyDMTS(ts->dm,dm);CHKERRQ(ierr); 5248 ierr = DMGetDMTS(ts->dm,&tsdm);CHKERRQ(ierr); 5249 if (tsdm->originaldm == ts->dm) { /* Grant write privileges to the replacement DM */ 5250 tsdm->originaldm = dm; 5251 } 5252 } 5253 ierr = DMDestroy(&ts->dm);CHKERRQ(ierr); 5254 } 5255 ts->dm = dm; 5256 5257 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 5258 ierr = SNESSetDM(snes,dm);CHKERRQ(ierr); 5259 PetscFunctionReturn(0); 5260 } 5261 5262 /*@ 5263 TSGetDM - Gets the DM that may be used by some preconditioners 5264 5265 Not Collective 5266 5267 Input Parameter: 5268 . ts - the preconditioner context 5269 5270 Output Parameter: 5271 . dm - the dm 5272 5273 Level: intermediate 5274 5275 .seealso: TSSetDM(), SNESSetDM(), SNESGetDM() 5276 @*/ 5277 PetscErrorCode TSGetDM(TS ts,DM *dm) 5278 { 5279 PetscErrorCode ierr; 5280 5281 PetscFunctionBegin; 5282 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5283 if (!ts->dm) { 5284 ierr = DMShellCreate(PetscObjectComm((PetscObject)ts),&ts->dm);CHKERRQ(ierr); 5285 if (ts->snes) {ierr = SNESSetDM(ts->snes,ts->dm);CHKERRQ(ierr);} 5286 } 5287 *dm = ts->dm; 5288 PetscFunctionReturn(0); 5289 } 5290 5291 /*@ 5292 SNESTSFormFunction - Function to evaluate nonlinear residual 5293 5294 Logically Collective on SNES 5295 5296 Input Parameter: 5297 + snes - nonlinear solver 5298 . U - the current state at which to evaluate the residual 5299 - ctx - user context, must be a TS 5300 5301 Output Parameter: 5302 . F - the nonlinear residual 5303 5304 Notes: 5305 This function is not normally called by users and is automatically registered with the SNES used by TS. 5306 It is most frequently passed to MatFDColoringSetFunction(). 5307 5308 Level: advanced 5309 5310 .seealso: SNESSetFunction(), MatFDColoringSetFunction() 5311 @*/ 5312 PetscErrorCode SNESTSFormFunction(SNES snes,Vec U,Vec F,void *ctx) 5313 { 5314 TS ts = (TS)ctx; 5315 PetscErrorCode ierr; 5316 5317 PetscFunctionBegin; 5318 PetscValidHeaderSpecific(snes,SNES_CLASSID,1); 5319 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 5320 PetscValidHeaderSpecific(F,VEC_CLASSID,3); 5321 PetscValidHeaderSpecific(ts,TS_CLASSID,4); 5322 ierr = (ts->ops->snesfunction)(snes,U,F,ts);CHKERRQ(ierr); 5323 PetscFunctionReturn(0); 5324 } 5325 5326 /*@ 5327 SNESTSFormJacobian - Function to evaluate the Jacobian 5328 5329 Collective on SNES 5330 5331 Input Parameter: 5332 + snes - nonlinear solver 5333 . U - the current state at which to evaluate the residual 5334 - ctx - user context, must be a TS 5335 5336 Output Parameter: 5337 + A - the Jacobian 5338 . B - the preconditioning matrix (may be the same as A) 5339 - flag - indicates any structure change in the matrix 5340 5341 Notes: 5342 This function is not normally called by users and is automatically registered with the SNES used by TS. 5343 5344 Level: developer 5345 5346 .seealso: SNESSetJacobian() 5347 @*/ 5348 PetscErrorCode SNESTSFormJacobian(SNES snes,Vec U,Mat A,Mat B,void *ctx) 5349 { 5350 TS ts = (TS)ctx; 5351 PetscErrorCode ierr; 5352 5353 PetscFunctionBegin; 5354 PetscValidHeaderSpecific(snes,SNES_CLASSID,1); 5355 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 5356 PetscValidPointer(A,3); 5357 PetscValidHeaderSpecific(A,MAT_CLASSID,3); 5358 PetscValidPointer(B,4); 5359 PetscValidHeaderSpecific(B,MAT_CLASSID,4); 5360 PetscValidHeaderSpecific(ts,TS_CLASSID,6); 5361 ierr = (ts->ops->snesjacobian)(snes,U,A,B,ts);CHKERRQ(ierr); 5362 PetscFunctionReturn(0); 5363 } 5364 5365 /*@C 5366 TSComputeRHSFunctionLinear - Evaluate the right hand side via the user-provided Jacobian, for linear problems Udot = A U only 5367 5368 Collective on TS 5369 5370 Input Arguments: 5371 + ts - time stepping context 5372 . t - time at which to evaluate 5373 . U - state at which to evaluate 5374 - ctx - context 5375 5376 Output Arguments: 5377 . F - right hand side 5378 5379 Level: intermediate 5380 5381 Notes: 5382 This function is intended to be passed to TSSetRHSFunction() to evaluate the right hand side for linear problems. 5383 The matrix (and optionally the evaluation context) should be passed to TSSetRHSJacobian(). 5384 5385 .seealso: TSSetRHSFunction(), TSSetRHSJacobian(), TSComputeRHSJacobianConstant() 5386 @*/ 5387 PetscErrorCode TSComputeRHSFunctionLinear(TS ts,PetscReal t,Vec U,Vec F,void *ctx) 5388 { 5389 PetscErrorCode ierr; 5390 Mat Arhs,Brhs; 5391 5392 PetscFunctionBegin; 5393 ierr = TSGetRHSMats_Private(ts,&Arhs,&Brhs);CHKERRQ(ierr); 5394 ierr = TSComputeRHSJacobian(ts,t,U,Arhs,Brhs);CHKERRQ(ierr); 5395 ierr = MatMult(Arhs,U,F);CHKERRQ(ierr); 5396 PetscFunctionReturn(0); 5397 } 5398 5399 /*@C 5400 TSComputeRHSJacobianConstant - Reuses a Jacobian that is time-independent. 5401 5402 Collective on TS 5403 5404 Input Arguments: 5405 + ts - time stepping context 5406 . t - time at which to evaluate 5407 . U - state at which to evaluate 5408 - ctx - context 5409 5410 Output Arguments: 5411 + A - pointer to operator 5412 . B - pointer to preconditioning matrix 5413 - flg - matrix structure flag 5414 5415 Level: intermediate 5416 5417 Notes: 5418 This function is intended to be passed to TSSetRHSJacobian() to evaluate the Jacobian for linear time-independent problems. 5419 5420 .seealso: TSSetRHSFunction(), TSSetRHSJacobian(), TSComputeRHSFunctionLinear() 5421 @*/ 5422 PetscErrorCode TSComputeRHSJacobianConstant(TS ts,PetscReal t,Vec U,Mat A,Mat B,void *ctx) 5423 { 5424 PetscFunctionBegin; 5425 PetscFunctionReturn(0); 5426 } 5427 5428 /*@C 5429 TSComputeIFunctionLinear - Evaluate the left hand side via the user-provided Jacobian, for linear problems only 5430 5431 Collective on TS 5432 5433 Input Arguments: 5434 + ts - time stepping context 5435 . t - time at which to evaluate 5436 . U - state at which to evaluate 5437 . Udot - time derivative of state vector 5438 - ctx - context 5439 5440 Output Arguments: 5441 . F - left hand side 5442 5443 Level: intermediate 5444 5445 Notes: 5446 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 5447 user is required to write their own TSComputeIFunction. 5448 This function is intended to be passed to TSSetIFunction() to evaluate the left hand side for linear problems. 5449 The matrix (and optionally the evaluation context) should be passed to TSSetIJacobian(). 5450 5451 Note that using this function is NOT equivalent to using TSComputeRHSFunctionLinear() since that solves Udot = A U 5452 5453 .seealso: TSSetIFunction(), TSSetIJacobian(), TSComputeIJacobianConstant(), TSComputeRHSFunctionLinear() 5454 @*/ 5455 PetscErrorCode TSComputeIFunctionLinear(TS ts,PetscReal t,Vec U,Vec Udot,Vec F,void *ctx) 5456 { 5457 PetscErrorCode ierr; 5458 Mat A,B; 5459 5460 PetscFunctionBegin; 5461 ierr = TSGetIJacobian(ts,&A,&B,NULL,NULL);CHKERRQ(ierr); 5462 ierr = TSComputeIJacobian(ts,t,U,Udot,1.0,A,B,PETSC_TRUE);CHKERRQ(ierr); 5463 ierr = MatMult(A,Udot,F);CHKERRQ(ierr); 5464 PetscFunctionReturn(0); 5465 } 5466 5467 /*@C 5468 TSComputeIJacobianConstant - Reuses a time-independent for a semi-implicit DAE or ODE 5469 5470 Collective on TS 5471 5472 Input Arguments: 5473 + ts - time stepping context 5474 . t - time at which to evaluate 5475 . U - state at which to evaluate 5476 . Udot - time derivative of state vector 5477 . shift - shift to apply 5478 - ctx - context 5479 5480 Output Arguments: 5481 + A - pointer to operator 5482 . B - pointer to preconditioning matrix 5483 - flg - matrix structure flag 5484 5485 Level: advanced 5486 5487 Notes: 5488 This function is intended to be passed to TSSetIJacobian() to evaluate the Jacobian for linear time-independent problems. 5489 5490 It is only appropriate for problems of the form 5491 5492 $ M Udot = F(U,t) 5493 5494 where M is constant and F is non-stiff. The user must pass M to TSSetIJacobian(). The current implementation only 5495 works with IMEX time integration methods such as TSROSW and TSARKIMEX, since there is no support for de-constructing 5496 an implicit operator of the form 5497 5498 $ shift*M + J 5499 5500 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 5501 a copy of M or reassemble it when requested. 5502 5503 .seealso: TSSetIFunction(), TSSetIJacobian(), TSComputeIFunctionLinear() 5504 @*/ 5505 PetscErrorCode TSComputeIJacobianConstant(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat A,Mat B,void *ctx) 5506 { 5507 PetscErrorCode ierr; 5508 5509 PetscFunctionBegin; 5510 ierr = MatScale(A, shift / ts->ijacobian.shift);CHKERRQ(ierr); 5511 ts->ijacobian.shift = shift; 5512 PetscFunctionReturn(0); 5513 } 5514 5515 /*@ 5516 TSGetEquationType - Gets the type of the equation that TS is solving. 5517 5518 Not Collective 5519 5520 Input Parameter: 5521 . ts - the TS context 5522 5523 Output Parameter: 5524 . equation_type - see TSEquationType 5525 5526 Level: beginner 5527 5528 .keywords: TS, equation type 5529 5530 .seealso: TSSetEquationType(), TSEquationType 5531 @*/ 5532 PetscErrorCode TSGetEquationType(TS ts,TSEquationType *equation_type) 5533 { 5534 PetscFunctionBegin; 5535 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5536 PetscValidPointer(equation_type,2); 5537 *equation_type = ts->equation_type; 5538 PetscFunctionReturn(0); 5539 } 5540 5541 /*@ 5542 TSSetEquationType - Sets the type of the equation that TS is solving. 5543 5544 Not Collective 5545 5546 Input Parameter: 5547 + ts - the TS context 5548 - equation_type - see TSEquationType 5549 5550 Level: advanced 5551 5552 .keywords: TS, equation type 5553 5554 .seealso: TSGetEquationType(), TSEquationType 5555 @*/ 5556 PetscErrorCode TSSetEquationType(TS ts,TSEquationType equation_type) 5557 { 5558 PetscFunctionBegin; 5559 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5560 ts->equation_type = equation_type; 5561 PetscFunctionReturn(0); 5562 } 5563 5564 /*@ 5565 TSGetConvergedReason - Gets the reason the TS iteration was stopped. 5566 5567 Not Collective 5568 5569 Input Parameter: 5570 . ts - the TS context 5571 5572 Output Parameter: 5573 . reason - negative value indicates diverged, positive value converged, see TSConvergedReason or the 5574 manual pages for the individual convergence tests for complete lists 5575 5576 Level: beginner 5577 5578 Notes: 5579 Can only be called after the call to TSSolve() is complete. 5580 5581 .keywords: TS, nonlinear, set, convergence, test 5582 5583 .seealso: TSSetConvergenceTest(), TSConvergedReason 5584 @*/ 5585 PetscErrorCode TSGetConvergedReason(TS ts,TSConvergedReason *reason) 5586 { 5587 PetscFunctionBegin; 5588 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5589 PetscValidPointer(reason,2); 5590 *reason = ts->reason; 5591 PetscFunctionReturn(0); 5592 } 5593 5594 /*@ 5595 TSSetConvergedReason - Sets the reason for handling the convergence of TSSolve. 5596 5597 Not Collective 5598 5599 Input Parameter: 5600 + ts - the TS context 5601 . reason - negative value indicates diverged, positive value converged, see TSConvergedReason or the 5602 manual pages for the individual convergence tests for complete lists 5603 5604 Level: advanced 5605 5606 Notes: 5607 Can only be called during TSSolve() is active. 5608 5609 .keywords: TS, nonlinear, set, convergence, test 5610 5611 .seealso: TSConvergedReason 5612 @*/ 5613 PetscErrorCode TSSetConvergedReason(TS ts,TSConvergedReason reason) 5614 { 5615 PetscFunctionBegin; 5616 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5617 ts->reason = reason; 5618 PetscFunctionReturn(0); 5619 } 5620 5621 /*@ 5622 TSGetSolveTime - Gets the time after a call to TSSolve() 5623 5624 Not Collective 5625 5626 Input Parameter: 5627 . ts - the TS context 5628 5629 Output Parameter: 5630 . ftime - the final time. This time corresponds to the final time set with TSSetMaxTime() 5631 5632 Level: beginner 5633 5634 Notes: 5635 Can only be called after the call to TSSolve() is complete. 5636 5637 .keywords: TS, nonlinear, set, convergence, test 5638 5639 .seealso: TSSetConvergenceTest(), TSConvergedReason 5640 @*/ 5641 PetscErrorCode TSGetSolveTime(TS ts,PetscReal *ftime) 5642 { 5643 PetscFunctionBegin; 5644 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5645 PetscValidPointer(ftime,2); 5646 *ftime = ts->solvetime; 5647 PetscFunctionReturn(0); 5648 } 5649 5650 /*@ 5651 TSGetSNESIterations - Gets the total number of nonlinear iterations 5652 used by the time integrator. 5653 5654 Not Collective 5655 5656 Input Parameter: 5657 . ts - TS context 5658 5659 Output Parameter: 5660 . nits - number of nonlinear iterations 5661 5662 Notes: 5663 This counter is reset to zero for each successive call to TSSolve(). 5664 5665 Level: intermediate 5666 5667 .keywords: TS, get, number, nonlinear, iterations 5668 5669 .seealso: TSGetKSPIterations() 5670 @*/ 5671 PetscErrorCode TSGetSNESIterations(TS ts,PetscInt *nits) 5672 { 5673 PetscFunctionBegin; 5674 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5675 PetscValidIntPointer(nits,2); 5676 *nits = ts->snes_its; 5677 PetscFunctionReturn(0); 5678 } 5679 5680 /*@ 5681 TSGetKSPIterations - Gets the total number of linear iterations 5682 used by the time integrator. 5683 5684 Not Collective 5685 5686 Input Parameter: 5687 . ts - TS context 5688 5689 Output Parameter: 5690 . lits - number of linear iterations 5691 5692 Notes: 5693 This counter is reset to zero for each successive call to TSSolve(). 5694 5695 Level: intermediate 5696 5697 .keywords: TS, get, number, linear, iterations 5698 5699 .seealso: TSGetSNESIterations(), SNESGetKSPIterations() 5700 @*/ 5701 PetscErrorCode TSGetKSPIterations(TS ts,PetscInt *lits) 5702 { 5703 PetscFunctionBegin; 5704 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5705 PetscValidIntPointer(lits,2); 5706 *lits = ts->ksp_its; 5707 PetscFunctionReturn(0); 5708 } 5709 5710 /*@ 5711 TSGetStepRejections - Gets the total number of rejected steps. 5712 5713 Not Collective 5714 5715 Input Parameter: 5716 . ts - TS context 5717 5718 Output Parameter: 5719 . rejects - number of steps rejected 5720 5721 Notes: 5722 This counter is reset to zero for each successive call to TSSolve(). 5723 5724 Level: intermediate 5725 5726 .keywords: TS, get, number 5727 5728 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetSNESFailures(), TSSetMaxSNESFailures(), TSSetErrorIfStepFails() 5729 @*/ 5730 PetscErrorCode TSGetStepRejections(TS ts,PetscInt *rejects) 5731 { 5732 PetscFunctionBegin; 5733 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5734 PetscValidIntPointer(rejects,2); 5735 *rejects = ts->reject; 5736 PetscFunctionReturn(0); 5737 } 5738 5739 /*@ 5740 TSGetSNESFailures - Gets the total number of failed SNES solves 5741 5742 Not Collective 5743 5744 Input Parameter: 5745 . ts - TS context 5746 5747 Output Parameter: 5748 . fails - number of failed nonlinear solves 5749 5750 Notes: 5751 This counter is reset to zero for each successive call to TSSolve(). 5752 5753 Level: intermediate 5754 5755 .keywords: TS, get, number 5756 5757 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSSetMaxSNESFailures() 5758 @*/ 5759 PetscErrorCode TSGetSNESFailures(TS ts,PetscInt *fails) 5760 { 5761 PetscFunctionBegin; 5762 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5763 PetscValidIntPointer(fails,2); 5764 *fails = ts->num_snes_failures; 5765 PetscFunctionReturn(0); 5766 } 5767 5768 /*@ 5769 TSSetMaxStepRejections - Sets the maximum number of step rejections before a step fails 5770 5771 Not Collective 5772 5773 Input Parameter: 5774 + ts - TS context 5775 - rejects - maximum number of rejected steps, pass -1 for unlimited 5776 5777 Notes: 5778 The counter is reset to zero for each step 5779 5780 Options Database Key: 5781 . -ts_max_reject - Maximum number of step rejections before a step fails 5782 5783 Level: intermediate 5784 5785 .keywords: TS, set, maximum, number 5786 5787 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxSNESFailures(), TSGetStepRejections(), TSGetSNESFailures(), TSSetErrorIfStepFails(), TSGetConvergedReason() 5788 @*/ 5789 PetscErrorCode TSSetMaxStepRejections(TS ts,PetscInt rejects) 5790 { 5791 PetscFunctionBegin; 5792 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5793 ts->max_reject = rejects; 5794 PetscFunctionReturn(0); 5795 } 5796 5797 /*@ 5798 TSSetMaxSNESFailures - Sets the maximum number of failed SNES solves 5799 5800 Not Collective 5801 5802 Input Parameter: 5803 + ts - TS context 5804 - fails - maximum number of failed nonlinear solves, pass -1 for unlimited 5805 5806 Notes: 5807 The counter is reset to zero for each successive call to TSSolve(). 5808 5809 Options Database Key: 5810 . -ts_max_snes_failures - Maximum number of nonlinear solve failures 5811 5812 Level: intermediate 5813 5814 .keywords: TS, set, maximum, number 5815 5816 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSGetSNESFailures(), SNESGetConvergedReason(), TSGetConvergedReason() 5817 @*/ 5818 PetscErrorCode TSSetMaxSNESFailures(TS ts,PetscInt fails) 5819 { 5820 PetscFunctionBegin; 5821 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5822 ts->max_snes_failures = fails; 5823 PetscFunctionReturn(0); 5824 } 5825 5826 /*@ 5827 TSSetErrorIfStepFails - Error if no step succeeds 5828 5829 Not Collective 5830 5831 Input Parameter: 5832 + ts - TS context 5833 - err - PETSC_TRUE to error if no step succeeds, PETSC_FALSE to return without failure 5834 5835 Options Database Key: 5836 . -ts_error_if_step_fails - Error if no step succeeds 5837 5838 Level: intermediate 5839 5840 .keywords: TS, set, error 5841 5842 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSGetSNESFailures(), TSSetErrorIfStepFails(), TSGetConvergedReason() 5843 @*/ 5844 PetscErrorCode TSSetErrorIfStepFails(TS ts,PetscBool err) 5845 { 5846 PetscFunctionBegin; 5847 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5848 ts->errorifstepfailed = err; 5849 PetscFunctionReturn(0); 5850 } 5851 5852 /*@C 5853 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 5854 5855 Collective on TS 5856 5857 Input Parameters: 5858 + ts - the TS context 5859 . step - current time-step 5860 . ptime - current time 5861 . u - current state 5862 - vf - viewer and its format 5863 5864 Level: intermediate 5865 5866 .keywords: TS, vector, monitor, view 5867 5868 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 5869 @*/ 5870 PetscErrorCode TSMonitorSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,PetscViewerAndFormat *vf) 5871 { 5872 PetscErrorCode ierr; 5873 5874 PetscFunctionBegin; 5875 ierr = PetscViewerPushFormat(vf->viewer,vf->format);CHKERRQ(ierr); 5876 ierr = VecView(u,vf->viewer);CHKERRQ(ierr); 5877 ierr = PetscViewerPopFormat(vf->viewer);CHKERRQ(ierr); 5878 PetscFunctionReturn(0); 5879 } 5880 5881 /*@C 5882 TSMonitorSolutionVTK - Monitors progress of the TS solvers by VecView() for the solution at each timestep. 5883 5884 Collective on TS 5885 5886 Input Parameters: 5887 + ts - the TS context 5888 . step - current time-step 5889 . ptime - current time 5890 . u - current state 5891 - filenametemplate - string containing a format specifier for the integer time step (e.g. %03D) 5892 5893 Level: intermediate 5894 5895 Notes: 5896 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. 5897 These are named according to the file name template. 5898 5899 This function is normally passed as an argument to TSMonitorSet() along with TSMonitorSolutionVTKDestroy(). 5900 5901 .keywords: TS, vector, monitor, view 5902 5903 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 5904 @*/ 5905 PetscErrorCode TSMonitorSolutionVTK(TS ts,PetscInt step,PetscReal ptime,Vec u,void *filenametemplate) 5906 { 5907 PetscErrorCode ierr; 5908 char filename[PETSC_MAX_PATH_LEN]; 5909 PetscViewer viewer; 5910 5911 PetscFunctionBegin; 5912 if (step < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */ 5913 ierr = PetscSNPrintf(filename,sizeof(filename),(const char*)filenametemplate,step);CHKERRQ(ierr); 5914 ierr = PetscViewerVTKOpen(PetscObjectComm((PetscObject)ts),filename,FILE_MODE_WRITE,&viewer);CHKERRQ(ierr); 5915 ierr = VecView(u,viewer);CHKERRQ(ierr); 5916 ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr); 5917 PetscFunctionReturn(0); 5918 } 5919 5920 /*@C 5921 TSMonitorSolutionVTKDestroy - Destroy context for monitoring 5922 5923 Collective on TS 5924 5925 Input Parameters: 5926 . filenametemplate - string containing a format specifier for the integer time step (e.g. %03D) 5927 5928 Level: intermediate 5929 5930 Note: 5931 This function is normally passed to TSMonitorSet() along with TSMonitorSolutionVTK(). 5932 5933 .keywords: TS, vector, monitor, view 5934 5935 .seealso: TSMonitorSet(), TSMonitorSolutionVTK() 5936 @*/ 5937 PetscErrorCode TSMonitorSolutionVTKDestroy(void *filenametemplate) 5938 { 5939 PetscErrorCode ierr; 5940 5941 PetscFunctionBegin; 5942 ierr = PetscFree(*(char**)filenametemplate);CHKERRQ(ierr); 5943 PetscFunctionReturn(0); 5944 } 5945 5946 /*@ 5947 TSGetAdapt - Get the adaptive controller context for the current method 5948 5949 Collective on TS if controller has not been created yet 5950 5951 Input Arguments: 5952 . ts - time stepping context 5953 5954 Output Arguments: 5955 . adapt - adaptive controller 5956 5957 Level: intermediate 5958 5959 .seealso: TSAdapt, TSAdaptSetType(), TSAdaptChoose() 5960 @*/ 5961 PetscErrorCode TSGetAdapt(TS ts,TSAdapt *adapt) 5962 { 5963 PetscErrorCode ierr; 5964 5965 PetscFunctionBegin; 5966 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5967 PetscValidPointer(adapt,2); 5968 if (!ts->adapt) { 5969 ierr = TSAdaptCreate(PetscObjectComm((PetscObject)ts),&ts->adapt);CHKERRQ(ierr); 5970 ierr = PetscLogObjectParent((PetscObject)ts,(PetscObject)ts->adapt);CHKERRQ(ierr); 5971 ierr = PetscObjectIncrementTabLevel((PetscObject)ts->adapt,(PetscObject)ts,1);CHKERRQ(ierr); 5972 } 5973 *adapt = ts->adapt; 5974 PetscFunctionReturn(0); 5975 } 5976 5977 /*@ 5978 TSSetTolerances - Set tolerances for local truncation error when using adaptive controller 5979 5980 Logically Collective 5981 5982 Input Arguments: 5983 + ts - time integration context 5984 . atol - scalar absolute tolerances, PETSC_DECIDE to leave current value 5985 . vatol - vector of absolute tolerances or NULL, used in preference to atol if present 5986 . rtol - scalar relative tolerances, PETSC_DECIDE to leave current value 5987 - vrtol - vector of relative tolerances or NULL, used in preference to atol if present 5988 5989 Options Database keys: 5990 + -ts_rtol <rtol> - relative tolerance for local truncation error 5991 - -ts_atol <atol> Absolute tolerance for local truncation error 5992 5993 Notes: 5994 With PETSc's implicit schemes for DAE problems, the calculation of the local truncation error 5995 (LTE) includes both the differential and the algebraic variables. If one wants the LTE to be 5996 computed only for the differential or the algebraic part then this can be done using the vector of 5997 tolerances vatol. For example, by setting the tolerance vector with the desired tolerance for the 5998 differential part and infinity for the algebraic part, the LTE calculation will include only the 5999 differential variables. 6000 6001 Level: beginner 6002 6003 .seealso: TS, TSAdapt, TSVecNormWRMS(), TSGetTolerances() 6004 @*/ 6005 PetscErrorCode TSSetTolerances(TS ts,PetscReal atol,Vec vatol,PetscReal rtol,Vec vrtol) 6006 { 6007 PetscErrorCode ierr; 6008 6009 PetscFunctionBegin; 6010 if (atol != PETSC_DECIDE && atol != PETSC_DEFAULT) ts->atol = atol; 6011 if (vatol) { 6012 ierr = PetscObjectReference((PetscObject)vatol);CHKERRQ(ierr); 6013 ierr = VecDestroy(&ts->vatol);CHKERRQ(ierr); 6014 ts->vatol = vatol; 6015 } 6016 if (rtol != PETSC_DECIDE && rtol != PETSC_DEFAULT) ts->rtol = rtol; 6017 if (vrtol) { 6018 ierr = PetscObjectReference((PetscObject)vrtol);CHKERRQ(ierr); 6019 ierr = VecDestroy(&ts->vrtol);CHKERRQ(ierr); 6020 ts->vrtol = vrtol; 6021 } 6022 PetscFunctionReturn(0); 6023 } 6024 6025 /*@ 6026 TSGetTolerances - Get tolerances for local truncation error when using adaptive controller 6027 6028 Logically Collective 6029 6030 Input Arguments: 6031 . ts - time integration context 6032 6033 Output Arguments: 6034 + atol - scalar absolute tolerances, NULL to ignore 6035 . vatol - vector of absolute tolerances, NULL to ignore 6036 . rtol - scalar relative tolerances, NULL to ignore 6037 - vrtol - vector of relative tolerances, NULL to ignore 6038 6039 Level: beginner 6040 6041 .seealso: TS, TSAdapt, TSVecNormWRMS(), TSSetTolerances() 6042 @*/ 6043 PetscErrorCode TSGetTolerances(TS ts,PetscReal *atol,Vec *vatol,PetscReal *rtol,Vec *vrtol) 6044 { 6045 PetscFunctionBegin; 6046 if (atol) *atol = ts->atol; 6047 if (vatol) *vatol = ts->vatol; 6048 if (rtol) *rtol = ts->rtol; 6049 if (vrtol) *vrtol = ts->vrtol; 6050 PetscFunctionReturn(0); 6051 } 6052 6053 /*@ 6054 TSErrorWeightedNorm2 - compute a weighted 2-norm of the difference between two state vectors 6055 6056 Collective on TS 6057 6058 Input Arguments: 6059 + ts - time stepping context 6060 . U - state vector, usually ts->vec_sol 6061 - Y - state vector to be compared to U 6062 6063 Output Arguments: 6064 . norm - weighted norm, a value of 1.0 means that the error matches the tolerances 6065 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 6066 . normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 6067 6068 Level: developer 6069 6070 .seealso: TSErrorWeightedNorm(), TSErrorWeightedNormInfinity() 6071 @*/ 6072 PetscErrorCode TSErrorWeightedNorm2(TS ts,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6073 { 6074 PetscErrorCode ierr; 6075 PetscInt i,n,N,rstart; 6076 PetscInt n_loc,na_loc,nr_loc; 6077 PetscReal n_glb,na_glb,nr_glb; 6078 const PetscScalar *u,*y; 6079 PetscReal sum,suma,sumr,gsum,gsuma,gsumr,diff; 6080 PetscReal tol,tola,tolr; 6081 PetscReal err_loc[6],err_glb[6]; 6082 6083 PetscFunctionBegin; 6084 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6085 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 6086 PetscValidHeaderSpecific(Y,VEC_CLASSID,3); 6087 PetscValidType(U,2); 6088 PetscValidType(Y,3); 6089 PetscCheckSameComm(U,2,Y,3); 6090 PetscValidPointer(norm,4); 6091 PetscValidPointer(norma,5); 6092 PetscValidPointer(normr,6); 6093 if (U == Y) SETERRQ(PetscObjectComm((PetscObject)U),PETSC_ERR_ARG_IDN,"U and Y cannot be the same vector"); 6094 6095 ierr = VecGetSize(U,&N);CHKERRQ(ierr); 6096 ierr = VecGetLocalSize(U,&n);CHKERRQ(ierr); 6097 ierr = VecGetOwnershipRange(U,&rstart,NULL);CHKERRQ(ierr); 6098 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 6099 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 6100 sum = 0.; n_loc = 0; 6101 suma = 0.; na_loc = 0; 6102 sumr = 0.; nr_loc = 0; 6103 if (ts->vatol && ts->vrtol) { 6104 const PetscScalar *atol,*rtol; 6105 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6106 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6107 for (i=0; i<n; i++) { 6108 diff = PetscAbsScalar(y[i] - u[i]); 6109 tola = PetscRealPart(atol[i]); 6110 if(tola>0.){ 6111 suma += PetscSqr(diff/tola); 6112 na_loc++; 6113 } 6114 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6115 if(tolr>0.){ 6116 sumr += PetscSqr(diff/tolr); 6117 nr_loc++; 6118 } 6119 tol=tola+tolr; 6120 if(tol>0.){ 6121 sum += PetscSqr(diff/tol); 6122 n_loc++; 6123 } 6124 } 6125 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6126 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6127 } else if (ts->vatol) { /* vector atol, scalar rtol */ 6128 const PetscScalar *atol; 6129 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6130 for (i=0; i<n; i++) { 6131 diff = PetscAbsScalar(y[i] - u[i]); 6132 tola = PetscRealPart(atol[i]); 6133 if(tola>0.){ 6134 suma += PetscSqr(diff/tola); 6135 na_loc++; 6136 } 6137 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6138 if(tolr>0.){ 6139 sumr += PetscSqr(diff/tolr); 6140 nr_loc++; 6141 } 6142 tol=tola+tolr; 6143 if(tol>0.){ 6144 sum += PetscSqr(diff/tol); 6145 n_loc++; 6146 } 6147 } 6148 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6149 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 6150 const PetscScalar *rtol; 6151 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6152 for (i=0; i<n; i++) { 6153 diff = PetscAbsScalar(y[i] - u[i]); 6154 tola = ts->atol; 6155 if(tola>0.){ 6156 suma += PetscSqr(diff/tola); 6157 na_loc++; 6158 } 6159 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6160 if(tolr>0.){ 6161 sumr += PetscSqr(diff/tolr); 6162 nr_loc++; 6163 } 6164 tol=tola+tolr; 6165 if(tol>0.){ 6166 sum += PetscSqr(diff/tol); 6167 n_loc++; 6168 } 6169 } 6170 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6171 } else { /* scalar atol, scalar rtol */ 6172 for (i=0; i<n; i++) { 6173 diff = PetscAbsScalar(y[i] - u[i]); 6174 tola = ts->atol; 6175 if(tola>0.){ 6176 suma += PetscSqr(diff/tola); 6177 na_loc++; 6178 } 6179 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6180 if(tolr>0.){ 6181 sumr += PetscSqr(diff/tolr); 6182 nr_loc++; 6183 } 6184 tol=tola+tolr; 6185 if(tol>0.){ 6186 sum += PetscSqr(diff/tol); 6187 n_loc++; 6188 } 6189 } 6190 } 6191 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 6192 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 6193 6194 err_loc[0] = sum; 6195 err_loc[1] = suma; 6196 err_loc[2] = sumr; 6197 err_loc[3] = (PetscReal)n_loc; 6198 err_loc[4] = (PetscReal)na_loc; 6199 err_loc[5] = (PetscReal)nr_loc; 6200 6201 ierr = MPIU_Allreduce(err_loc,err_glb,6,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6202 6203 gsum = err_glb[0]; 6204 gsuma = err_glb[1]; 6205 gsumr = err_glb[2]; 6206 n_glb = err_glb[3]; 6207 na_glb = err_glb[4]; 6208 nr_glb = err_glb[5]; 6209 6210 *norm = 0.; 6211 if(n_glb>0. ){*norm = PetscSqrtReal(gsum / n_glb );} 6212 *norma = 0.; 6213 if(na_glb>0.){*norma = PetscSqrtReal(gsuma / na_glb);} 6214 *normr = 0.; 6215 if(nr_glb>0.){*normr = PetscSqrtReal(gsumr / nr_glb);} 6216 6217 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 6218 if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 6219 if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 6220 PetscFunctionReturn(0); 6221 } 6222 6223 /*@ 6224 TSErrorWeightedNormInfinity - compute a weighted infinity-norm of the difference between two state vectors 6225 6226 Collective on TS 6227 6228 Input Arguments: 6229 + ts - time stepping context 6230 . U - state vector, usually ts->vec_sol 6231 - Y - state vector to be compared to U 6232 6233 Output Arguments: 6234 . norm - weighted norm, a value of 1.0 means that the error matches the tolerances 6235 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 6236 . normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 6237 6238 Level: developer 6239 6240 .seealso: TSErrorWeightedNorm(), TSErrorWeightedNorm2() 6241 @*/ 6242 PetscErrorCode TSErrorWeightedNormInfinity(TS ts,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6243 { 6244 PetscErrorCode ierr; 6245 PetscInt i,n,N,rstart; 6246 const PetscScalar *u,*y; 6247 PetscReal max,gmax,maxa,gmaxa,maxr,gmaxr; 6248 PetscReal tol,tola,tolr,diff; 6249 PetscReal err_loc[3],err_glb[3]; 6250 6251 PetscFunctionBegin; 6252 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6253 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 6254 PetscValidHeaderSpecific(Y,VEC_CLASSID,3); 6255 PetscValidType(U,2); 6256 PetscValidType(Y,3); 6257 PetscCheckSameComm(U,2,Y,3); 6258 PetscValidPointer(norm,4); 6259 PetscValidPointer(norma,5); 6260 PetscValidPointer(normr,6); 6261 if (U == Y) SETERRQ(PetscObjectComm((PetscObject)U),PETSC_ERR_ARG_IDN,"U and Y cannot be the same vector"); 6262 6263 ierr = VecGetSize(U,&N);CHKERRQ(ierr); 6264 ierr = VecGetLocalSize(U,&n);CHKERRQ(ierr); 6265 ierr = VecGetOwnershipRange(U,&rstart,NULL);CHKERRQ(ierr); 6266 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 6267 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 6268 6269 max=0.; 6270 maxa=0.; 6271 maxr=0.; 6272 6273 if (ts->vatol && ts->vrtol) { /* vector atol, vector rtol */ 6274 const PetscScalar *atol,*rtol; 6275 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6276 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6277 6278 for (i=0; i<n; i++) { 6279 diff = PetscAbsScalar(y[i] - u[i]); 6280 tola = PetscRealPart(atol[i]); 6281 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6282 tol = tola+tolr; 6283 if(tola>0.){ 6284 maxa = PetscMax(maxa,diff / tola); 6285 } 6286 if(tolr>0.){ 6287 maxr = PetscMax(maxr,diff / tolr); 6288 } 6289 if(tol>0.){ 6290 max = PetscMax(max,diff / tol); 6291 } 6292 } 6293 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6294 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6295 } else if (ts->vatol) { /* vector atol, scalar rtol */ 6296 const PetscScalar *atol; 6297 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6298 for (i=0; i<n; i++) { 6299 diff = PetscAbsScalar(y[i] - u[i]); 6300 tola = PetscRealPart(atol[i]); 6301 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6302 tol = tola+tolr; 6303 if(tola>0.){ 6304 maxa = PetscMax(maxa,diff / tola); 6305 } 6306 if(tolr>0.){ 6307 maxr = PetscMax(maxr,diff / tolr); 6308 } 6309 if(tol>0.){ 6310 max = PetscMax(max,diff / tol); 6311 } 6312 } 6313 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6314 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 6315 const PetscScalar *rtol; 6316 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6317 6318 for (i=0; i<n; i++) { 6319 diff = PetscAbsScalar(y[i] - u[i]); 6320 tola = ts->atol; 6321 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6322 tol = tola+tolr; 6323 if(tola>0.){ 6324 maxa = PetscMax(maxa,diff / tola); 6325 } 6326 if(tolr>0.){ 6327 maxr = PetscMax(maxr,diff / tolr); 6328 } 6329 if(tol>0.){ 6330 max = PetscMax(max,diff / tol); 6331 } 6332 } 6333 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6334 } else { /* scalar atol, scalar rtol */ 6335 6336 for (i=0; i<n; i++) { 6337 diff = PetscAbsScalar(y[i] - u[i]); 6338 tola = ts->atol; 6339 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6340 tol = tola+tolr; 6341 if(tola>0.){ 6342 maxa = PetscMax(maxa,diff / tola); 6343 } 6344 if(tolr>0.){ 6345 maxr = PetscMax(maxr,diff / tolr); 6346 } 6347 if(tol>0.){ 6348 max = PetscMax(max,diff / tol); 6349 } 6350 } 6351 } 6352 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 6353 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 6354 err_loc[0] = max; 6355 err_loc[1] = maxa; 6356 err_loc[2] = maxr; 6357 ierr = MPIU_Allreduce(err_loc,err_glb,3,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6358 gmax = err_glb[0]; 6359 gmaxa = err_glb[1]; 6360 gmaxr = err_glb[2]; 6361 6362 *norm = gmax; 6363 *norma = gmaxa; 6364 *normr = gmaxr; 6365 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 6366 if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 6367 if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 6368 PetscFunctionReturn(0); 6369 } 6370 6371 /*@ 6372 TSErrorWeightedNorm - compute a weighted norm of the difference between two state vectors based on supplied absolute and relative tolerances 6373 6374 Collective on TS 6375 6376 Input Arguments: 6377 + ts - time stepping context 6378 . U - state vector, usually ts->vec_sol 6379 . Y - state vector to be compared to U 6380 - wnormtype - norm type, either NORM_2 or NORM_INFINITY 6381 6382 Output Arguments: 6383 . norm - weighted norm, a value of 1.0 achieves a balance between absolute and relative tolerances 6384 . norma - weighted norm, a value of 1.0 means that the error meets the absolute tolerance set by the user 6385 . normr - weighted norm, a value of 1.0 means that the error meets the relative tolerance set by the user 6386 6387 Options Database Keys: 6388 . -ts_adapt_wnormtype <wnormtype> - 2, INFINITY 6389 6390 Level: developer 6391 6392 .seealso: TSErrorWeightedNormInfinity(), TSErrorWeightedNorm2(), TSErrorWeightedENorm 6393 @*/ 6394 PetscErrorCode TSErrorWeightedNorm(TS ts,Vec U,Vec Y,NormType wnormtype,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6395 { 6396 PetscErrorCode ierr; 6397 6398 PetscFunctionBegin; 6399 if (wnormtype == NORM_2) { 6400 ierr = TSErrorWeightedNorm2(ts,U,Y,norm,norma,normr);CHKERRQ(ierr); 6401 } else if(wnormtype == NORM_INFINITY) { 6402 ierr = TSErrorWeightedNormInfinity(ts,U,Y,norm,norma,normr);CHKERRQ(ierr); 6403 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]); 6404 PetscFunctionReturn(0); 6405 } 6406 6407 6408 /*@ 6409 TSErrorWeightedENorm2 - compute a weighted 2 error norm based on supplied absolute and relative tolerances 6410 6411 Collective on TS 6412 6413 Input Arguments: 6414 + ts - time stepping context 6415 . E - error vector 6416 . U - state vector, usually ts->vec_sol 6417 - Y - state vector, previous time step 6418 6419 Output Arguments: 6420 . norm - weighted norm, a value of 1.0 means that the error matches the tolerances 6421 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 6422 . normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 6423 6424 Level: developer 6425 6426 .seealso: TSErrorWeightedENorm(), TSErrorWeightedENormInfinity() 6427 @*/ 6428 PetscErrorCode TSErrorWeightedENorm2(TS ts,Vec E,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6429 { 6430 PetscErrorCode ierr; 6431 PetscInt i,n,N,rstart; 6432 PetscInt n_loc,na_loc,nr_loc; 6433 PetscReal n_glb,na_glb,nr_glb; 6434 const PetscScalar *e,*u,*y; 6435 PetscReal err,sum,suma,sumr,gsum,gsuma,gsumr; 6436 PetscReal tol,tola,tolr; 6437 PetscReal err_loc[6],err_glb[6]; 6438 6439 PetscFunctionBegin; 6440 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6441 PetscValidHeaderSpecific(E,VEC_CLASSID,2); 6442 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 6443 PetscValidHeaderSpecific(Y,VEC_CLASSID,4); 6444 PetscValidType(E,2); 6445 PetscValidType(U,3); 6446 PetscValidType(Y,4); 6447 PetscCheckSameComm(E,2,U,3); 6448 PetscCheckSameComm(U,2,Y,3); 6449 PetscValidPointer(norm,5); 6450 PetscValidPointer(norma,6); 6451 PetscValidPointer(normr,7); 6452 6453 ierr = VecGetSize(E,&N);CHKERRQ(ierr); 6454 ierr = VecGetLocalSize(E,&n);CHKERRQ(ierr); 6455 ierr = VecGetOwnershipRange(E,&rstart,NULL);CHKERRQ(ierr); 6456 ierr = VecGetArrayRead(E,&e);CHKERRQ(ierr); 6457 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 6458 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 6459 sum = 0.; n_loc = 0; 6460 suma = 0.; na_loc = 0; 6461 sumr = 0.; nr_loc = 0; 6462 if (ts->vatol && ts->vrtol) { 6463 const PetscScalar *atol,*rtol; 6464 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6465 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6466 for (i=0; i<n; i++) { 6467 err = PetscAbsScalar(e[i]); 6468 tola = PetscRealPart(atol[i]); 6469 if(tola>0.){ 6470 suma += PetscSqr(err/tola); 6471 na_loc++; 6472 } 6473 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6474 if(tolr>0.){ 6475 sumr += PetscSqr(err/tolr); 6476 nr_loc++; 6477 } 6478 tol=tola+tolr; 6479 if(tol>0.){ 6480 sum += PetscSqr(err/tol); 6481 n_loc++; 6482 } 6483 } 6484 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6485 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6486 } else if (ts->vatol) { /* vector atol, scalar rtol */ 6487 const PetscScalar *atol; 6488 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6489 for (i=0; i<n; i++) { 6490 err = PetscAbsScalar(e[i]); 6491 tola = PetscRealPart(atol[i]); 6492 if(tola>0.){ 6493 suma += PetscSqr(err/tola); 6494 na_loc++; 6495 } 6496 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6497 if(tolr>0.){ 6498 sumr += PetscSqr(err/tolr); 6499 nr_loc++; 6500 } 6501 tol=tola+tolr; 6502 if(tol>0.){ 6503 sum += PetscSqr(err/tol); 6504 n_loc++; 6505 } 6506 } 6507 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6508 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 6509 const PetscScalar *rtol; 6510 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6511 for (i=0; i<n; i++) { 6512 err = PetscAbsScalar(e[i]); 6513 tola = ts->atol; 6514 if(tola>0.){ 6515 suma += PetscSqr(err/tola); 6516 na_loc++; 6517 } 6518 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6519 if(tolr>0.){ 6520 sumr += PetscSqr(err/tolr); 6521 nr_loc++; 6522 } 6523 tol=tola+tolr; 6524 if(tol>0.){ 6525 sum += PetscSqr(err/tol); 6526 n_loc++; 6527 } 6528 } 6529 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6530 } else { /* scalar atol, scalar rtol */ 6531 for (i=0; i<n; i++) { 6532 err = PetscAbsScalar(e[i]); 6533 tola = ts->atol; 6534 if(tola>0.){ 6535 suma += PetscSqr(err/tola); 6536 na_loc++; 6537 } 6538 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6539 if(tolr>0.){ 6540 sumr += PetscSqr(err/tolr); 6541 nr_loc++; 6542 } 6543 tol=tola+tolr; 6544 if(tol>0.){ 6545 sum += PetscSqr(err/tol); 6546 n_loc++; 6547 } 6548 } 6549 } 6550 ierr = VecRestoreArrayRead(E,&e);CHKERRQ(ierr); 6551 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 6552 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 6553 6554 err_loc[0] = sum; 6555 err_loc[1] = suma; 6556 err_loc[2] = sumr; 6557 err_loc[3] = (PetscReal)n_loc; 6558 err_loc[4] = (PetscReal)na_loc; 6559 err_loc[5] = (PetscReal)nr_loc; 6560 6561 ierr = MPIU_Allreduce(err_loc,err_glb,6,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6562 6563 gsum = err_glb[0]; 6564 gsuma = err_glb[1]; 6565 gsumr = err_glb[2]; 6566 n_glb = err_glb[3]; 6567 na_glb = err_glb[4]; 6568 nr_glb = err_glb[5]; 6569 6570 *norm = 0.; 6571 if(n_glb>0. ){*norm = PetscSqrtReal(gsum / n_glb );} 6572 *norma = 0.; 6573 if(na_glb>0.){*norma = PetscSqrtReal(gsuma / na_glb);} 6574 *normr = 0.; 6575 if(nr_glb>0.){*normr = PetscSqrtReal(gsumr / nr_glb);} 6576 6577 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 6578 if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 6579 if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 6580 PetscFunctionReturn(0); 6581 } 6582 6583 /*@ 6584 TSErrorWeightedENormInfinity - compute a weighted infinity error norm based on supplied absolute and relative tolerances 6585 Collective on TS 6586 6587 Input Arguments: 6588 + ts - time stepping context 6589 . E - error vector 6590 . U - state vector, usually ts->vec_sol 6591 - Y - state vector, previous time step 6592 6593 Output Arguments: 6594 . norm - weighted norm, a value of 1.0 means that the error matches the tolerances 6595 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 6596 . normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 6597 6598 Level: developer 6599 6600 .seealso: TSErrorWeightedENorm(), TSErrorWeightedENorm2() 6601 @*/ 6602 PetscErrorCode TSErrorWeightedENormInfinity(TS ts,Vec E,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6603 { 6604 PetscErrorCode ierr; 6605 PetscInt i,n,N,rstart; 6606 const PetscScalar *e,*u,*y; 6607 PetscReal err,max,gmax,maxa,gmaxa,maxr,gmaxr; 6608 PetscReal tol,tola,tolr; 6609 PetscReal err_loc[3],err_glb[3]; 6610 6611 PetscFunctionBegin; 6612 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6613 PetscValidHeaderSpecific(E,VEC_CLASSID,2); 6614 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 6615 PetscValidHeaderSpecific(Y,VEC_CLASSID,4); 6616 PetscValidType(E,2); 6617 PetscValidType(U,3); 6618 PetscValidType(Y,4); 6619 PetscCheckSameComm(E,2,U,3); 6620 PetscCheckSameComm(U,2,Y,3); 6621 PetscValidPointer(norm,5); 6622 PetscValidPointer(norma,6); 6623 PetscValidPointer(normr,7); 6624 6625 ierr = VecGetSize(E,&N);CHKERRQ(ierr); 6626 ierr = VecGetLocalSize(E,&n);CHKERRQ(ierr); 6627 ierr = VecGetOwnershipRange(E,&rstart,NULL);CHKERRQ(ierr); 6628 ierr = VecGetArrayRead(E,&e);CHKERRQ(ierr); 6629 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 6630 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 6631 6632 max=0.; 6633 maxa=0.; 6634 maxr=0.; 6635 6636 if (ts->vatol && ts->vrtol) { /* vector atol, vector rtol */ 6637 const PetscScalar *atol,*rtol; 6638 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6639 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6640 6641 for (i=0; i<n; i++) { 6642 err = PetscAbsScalar(e[i]); 6643 tola = PetscRealPart(atol[i]); 6644 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6645 tol = tola+tolr; 6646 if(tola>0.){ 6647 maxa = PetscMax(maxa,err / tola); 6648 } 6649 if(tolr>0.){ 6650 maxr = PetscMax(maxr,err / tolr); 6651 } 6652 if(tol>0.){ 6653 max = PetscMax(max,err / tol); 6654 } 6655 } 6656 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6657 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6658 } else if (ts->vatol) { /* vector atol, scalar rtol */ 6659 const PetscScalar *atol; 6660 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6661 for (i=0; i<n; i++) { 6662 err = PetscAbsScalar(e[i]); 6663 tola = PetscRealPart(atol[i]); 6664 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6665 tol = tola+tolr; 6666 if(tola>0.){ 6667 maxa = PetscMax(maxa,err / tola); 6668 } 6669 if(tolr>0.){ 6670 maxr = PetscMax(maxr,err / tolr); 6671 } 6672 if(tol>0.){ 6673 max = PetscMax(max,err / tol); 6674 } 6675 } 6676 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6677 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 6678 const PetscScalar *rtol; 6679 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6680 6681 for (i=0; i<n; i++) { 6682 err = PetscAbsScalar(e[i]); 6683 tola = ts->atol; 6684 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6685 tol = tola+tolr; 6686 if(tola>0.){ 6687 maxa = PetscMax(maxa,err / tola); 6688 } 6689 if(tolr>0.){ 6690 maxr = PetscMax(maxr,err / tolr); 6691 } 6692 if(tol>0.){ 6693 max = PetscMax(max,err / tol); 6694 } 6695 } 6696 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6697 } else { /* scalar atol, scalar rtol */ 6698 6699 for (i=0; i<n; i++) { 6700 err = PetscAbsScalar(e[i]); 6701 tola = ts->atol; 6702 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6703 tol = tola+tolr; 6704 if(tola>0.){ 6705 maxa = PetscMax(maxa,err / tola); 6706 } 6707 if(tolr>0.){ 6708 maxr = PetscMax(maxr,err / tolr); 6709 } 6710 if(tol>0.){ 6711 max = PetscMax(max,err / tol); 6712 } 6713 } 6714 } 6715 ierr = VecRestoreArrayRead(E,&e);CHKERRQ(ierr); 6716 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 6717 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 6718 err_loc[0] = max; 6719 err_loc[1] = maxa; 6720 err_loc[2] = maxr; 6721 ierr = MPIU_Allreduce(err_loc,err_glb,3,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6722 gmax = err_glb[0]; 6723 gmaxa = err_glb[1]; 6724 gmaxr = err_glb[2]; 6725 6726 *norm = gmax; 6727 *norma = gmaxa; 6728 *normr = gmaxr; 6729 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 6730 if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 6731 if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 6732 PetscFunctionReturn(0); 6733 } 6734 6735 /*@ 6736 TSErrorWeightedENorm - compute a weighted error norm based on supplied absolute and relative tolerances 6737 6738 Collective on TS 6739 6740 Input Arguments: 6741 + ts - time stepping context 6742 . E - error vector 6743 . U - state vector, usually ts->vec_sol 6744 . Y - state vector, previous time step 6745 - wnormtype - norm type, either NORM_2 or NORM_INFINITY 6746 6747 Output Arguments: 6748 . norm - weighted norm, a value of 1.0 achieves a balance between absolute and relative tolerances 6749 . norma - weighted norm, a value of 1.0 means that the error meets the absolute tolerance set by the user 6750 . normr - weighted norm, a value of 1.0 means that the error meets the relative tolerance set by the user 6751 6752 Options Database Keys: 6753 . -ts_adapt_wnormtype <wnormtype> - 2, INFINITY 6754 6755 Level: developer 6756 6757 .seealso: TSErrorWeightedENormInfinity(), TSErrorWeightedENorm2(), TSErrorWeightedNormInfinity(), TSErrorWeightedNorm2() 6758 @*/ 6759 PetscErrorCode TSErrorWeightedENorm(TS ts,Vec E,Vec U,Vec Y,NormType wnormtype,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6760 { 6761 PetscErrorCode ierr; 6762 6763 PetscFunctionBegin; 6764 if (wnormtype == NORM_2) { 6765 ierr = TSErrorWeightedENorm2(ts,E,U,Y,norm,norma,normr);CHKERRQ(ierr); 6766 } else if(wnormtype == NORM_INFINITY) { 6767 ierr = TSErrorWeightedENormInfinity(ts,E,U,Y,norm,norma,normr);CHKERRQ(ierr); 6768 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]); 6769 PetscFunctionReturn(0); 6770 } 6771 6772 6773 /*@ 6774 TSSetCFLTimeLocal - Set the local CFL constraint relative to forward Euler 6775 6776 Logically Collective on TS 6777 6778 Input Arguments: 6779 + ts - time stepping context 6780 - cfltime - maximum stable time step if using forward Euler (value can be different on each process) 6781 6782 Note: 6783 After calling this function, the global CFL time can be obtained by calling TSGetCFLTime() 6784 6785 Level: intermediate 6786 6787 .seealso: TSGetCFLTime(), TSADAPTCFL 6788 @*/ 6789 PetscErrorCode TSSetCFLTimeLocal(TS ts,PetscReal cfltime) 6790 { 6791 PetscFunctionBegin; 6792 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6793 ts->cfltime_local = cfltime; 6794 ts->cfltime = -1.; 6795 PetscFunctionReturn(0); 6796 } 6797 6798 /*@ 6799 TSGetCFLTime - Get the maximum stable time step according to CFL criteria applied to forward Euler 6800 6801 Collective on TS 6802 6803 Input Arguments: 6804 . ts - time stepping context 6805 6806 Output Arguments: 6807 . cfltime - maximum stable time step for forward Euler 6808 6809 Level: advanced 6810 6811 .seealso: TSSetCFLTimeLocal() 6812 @*/ 6813 PetscErrorCode TSGetCFLTime(TS ts,PetscReal *cfltime) 6814 { 6815 PetscErrorCode ierr; 6816 6817 PetscFunctionBegin; 6818 if (ts->cfltime < 0) { 6819 ierr = MPIU_Allreduce(&ts->cfltime_local,&ts->cfltime,1,MPIU_REAL,MPIU_MIN,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6820 } 6821 *cfltime = ts->cfltime; 6822 PetscFunctionReturn(0); 6823 } 6824 6825 /*@ 6826 TSVISetVariableBounds - Sets the lower and upper bounds for the solution vector. xl <= x <= xu 6827 6828 Input Parameters: 6829 . ts - the TS context. 6830 . xl - lower bound. 6831 . xu - upper bound. 6832 6833 Notes: 6834 If this routine is not called then the lower and upper bounds are set to 6835 PETSC_NINFINITY and PETSC_INFINITY respectively during SNESSetUp(). 6836 6837 Level: advanced 6838 6839 @*/ 6840 PetscErrorCode TSVISetVariableBounds(TS ts, Vec xl, Vec xu) 6841 { 6842 PetscErrorCode ierr; 6843 SNES snes; 6844 6845 PetscFunctionBegin; 6846 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 6847 ierr = SNESVISetVariableBounds(snes,xl,xu);CHKERRQ(ierr); 6848 PetscFunctionReturn(0); 6849 } 6850 6851 #if defined(PETSC_HAVE_MATLAB_ENGINE) 6852 #include <mex.h> 6853 6854 typedef struct {char *funcname; mxArray *ctx;} TSMatlabContext; 6855 6856 /* 6857 TSComputeFunction_Matlab - Calls the function that has been set with 6858 TSSetFunctionMatlab(). 6859 6860 Collective on TS 6861 6862 Input Parameters: 6863 + snes - the TS context 6864 - u - input vector 6865 6866 Output Parameter: 6867 . y - function vector, as set by TSSetFunction() 6868 6869 Notes: 6870 TSComputeFunction() is typically used within nonlinear solvers 6871 implementations, so most users would not generally call this routine 6872 themselves. 6873 6874 Level: developer 6875 6876 .keywords: TS, nonlinear, compute, function 6877 6878 .seealso: TSSetFunction(), TSGetFunction() 6879 */ 6880 PetscErrorCode TSComputeFunction_Matlab(TS snes,PetscReal time,Vec u,Vec udot,Vec y, void *ctx) 6881 { 6882 PetscErrorCode ierr; 6883 TSMatlabContext *sctx = (TSMatlabContext*)ctx; 6884 int nlhs = 1,nrhs = 7; 6885 mxArray *plhs[1],*prhs[7]; 6886 long long int lx = 0,lxdot = 0,ly = 0,ls = 0; 6887 6888 PetscFunctionBegin; 6889 PetscValidHeaderSpecific(snes,TS_CLASSID,1); 6890 PetscValidHeaderSpecific(u,VEC_CLASSID,3); 6891 PetscValidHeaderSpecific(udot,VEC_CLASSID,4); 6892 PetscValidHeaderSpecific(y,VEC_CLASSID,5); 6893 PetscCheckSameComm(snes,1,u,3); 6894 PetscCheckSameComm(snes,1,y,5); 6895 6896 ierr = PetscMemcpy(&ls,&snes,sizeof(snes));CHKERRQ(ierr); 6897 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 6898 ierr = PetscMemcpy(&lxdot,&udot,sizeof(udot));CHKERRQ(ierr); 6899 ierr = PetscMemcpy(&ly,&y,sizeof(u));CHKERRQ(ierr); 6900 6901 prhs[0] = mxCreateDoubleScalar((double)ls); 6902 prhs[1] = mxCreateDoubleScalar(time); 6903 prhs[2] = mxCreateDoubleScalar((double)lx); 6904 prhs[3] = mxCreateDoubleScalar((double)lxdot); 6905 prhs[4] = mxCreateDoubleScalar((double)ly); 6906 prhs[5] = mxCreateString(sctx->funcname); 6907 prhs[6] = sctx->ctx; 6908 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSComputeFunctionInternal");CHKERRQ(ierr); 6909 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 6910 mxDestroyArray(prhs[0]); 6911 mxDestroyArray(prhs[1]); 6912 mxDestroyArray(prhs[2]); 6913 mxDestroyArray(prhs[3]); 6914 mxDestroyArray(prhs[4]); 6915 mxDestroyArray(prhs[5]); 6916 mxDestroyArray(plhs[0]); 6917 PetscFunctionReturn(0); 6918 } 6919 6920 /* 6921 TSSetFunctionMatlab - Sets the function evaluation routine and function 6922 vector for use by the TS routines in solving ODEs 6923 equations from MATLAB. Here the function is a string containing the name of a MATLAB function 6924 6925 Logically Collective on TS 6926 6927 Input Parameters: 6928 + ts - the TS context 6929 - func - function evaluation routine 6930 6931 Calling sequence of func: 6932 $ func (TS ts,PetscReal time,Vec u,Vec udot,Vec f,void *ctx); 6933 6934 Level: beginner 6935 6936 .keywords: TS, nonlinear, set, function 6937 6938 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 6939 */ 6940 PetscErrorCode TSSetFunctionMatlab(TS ts,const char *func,mxArray *ctx) 6941 { 6942 PetscErrorCode ierr; 6943 TSMatlabContext *sctx; 6944 6945 PetscFunctionBegin; 6946 /* currently sctx is memory bleed */ 6947 ierr = PetscNew(&sctx);CHKERRQ(ierr); 6948 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 6949 /* 6950 This should work, but it doesn't 6951 sctx->ctx = ctx; 6952 mexMakeArrayPersistent(sctx->ctx); 6953 */ 6954 sctx->ctx = mxDuplicateArray(ctx); 6955 6956 ierr = TSSetIFunction(ts,NULL,TSComputeFunction_Matlab,sctx);CHKERRQ(ierr); 6957 PetscFunctionReturn(0); 6958 } 6959 6960 /* 6961 TSComputeJacobian_Matlab - Calls the function that has been set with 6962 TSSetJacobianMatlab(). 6963 6964 Collective on TS 6965 6966 Input Parameters: 6967 + ts - the TS context 6968 . u - input vector 6969 . A, B - the matrices 6970 - ctx - user context 6971 6972 Level: developer 6973 6974 .keywords: TS, nonlinear, compute, function 6975 6976 .seealso: TSSetFunction(), TSGetFunction() 6977 @*/ 6978 PetscErrorCode TSComputeJacobian_Matlab(TS ts,PetscReal time,Vec u,Vec udot,PetscReal shift,Mat A,Mat B,void *ctx) 6979 { 6980 PetscErrorCode ierr; 6981 TSMatlabContext *sctx = (TSMatlabContext*)ctx; 6982 int nlhs = 2,nrhs = 9; 6983 mxArray *plhs[2],*prhs[9]; 6984 long long int lx = 0,lxdot = 0,lA = 0,ls = 0, lB = 0; 6985 6986 PetscFunctionBegin; 6987 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6988 PetscValidHeaderSpecific(u,VEC_CLASSID,3); 6989 6990 /* call Matlab function in ctx with arguments u and y */ 6991 6992 ierr = PetscMemcpy(&ls,&ts,sizeof(ts));CHKERRQ(ierr); 6993 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 6994 ierr = PetscMemcpy(&lxdot,&udot,sizeof(u));CHKERRQ(ierr); 6995 ierr = PetscMemcpy(&lA,A,sizeof(u));CHKERRQ(ierr); 6996 ierr = PetscMemcpy(&lB,B,sizeof(u));CHKERRQ(ierr); 6997 6998 prhs[0] = mxCreateDoubleScalar((double)ls); 6999 prhs[1] = mxCreateDoubleScalar((double)time); 7000 prhs[2] = mxCreateDoubleScalar((double)lx); 7001 prhs[3] = mxCreateDoubleScalar((double)lxdot); 7002 prhs[4] = mxCreateDoubleScalar((double)shift); 7003 prhs[5] = mxCreateDoubleScalar((double)lA); 7004 prhs[6] = mxCreateDoubleScalar((double)lB); 7005 prhs[7] = mxCreateString(sctx->funcname); 7006 prhs[8] = sctx->ctx; 7007 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSComputeJacobianInternal");CHKERRQ(ierr); 7008 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 7009 mxDestroyArray(prhs[0]); 7010 mxDestroyArray(prhs[1]); 7011 mxDestroyArray(prhs[2]); 7012 mxDestroyArray(prhs[3]); 7013 mxDestroyArray(prhs[4]); 7014 mxDestroyArray(prhs[5]); 7015 mxDestroyArray(prhs[6]); 7016 mxDestroyArray(prhs[7]); 7017 mxDestroyArray(plhs[0]); 7018 mxDestroyArray(plhs[1]); 7019 PetscFunctionReturn(0); 7020 } 7021 7022 /* 7023 TSSetJacobianMatlab - Sets the Jacobian function evaluation routine and two empty Jacobian matrices 7024 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 7025 7026 Logically Collective on TS 7027 7028 Input Parameters: 7029 + ts - the TS context 7030 . A,B - Jacobian matrices 7031 . func - function evaluation routine 7032 - ctx - user context 7033 7034 Calling sequence of func: 7035 $ flag = func (TS ts,PetscReal time,Vec u,Vec udot,Mat A,Mat B,void *ctx); 7036 7037 Level: developer 7038 7039 .keywords: TS, nonlinear, set, function 7040 7041 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 7042 */ 7043 PetscErrorCode TSSetJacobianMatlab(TS ts,Mat A,Mat B,const char *func,mxArray *ctx) 7044 { 7045 PetscErrorCode ierr; 7046 TSMatlabContext *sctx; 7047 7048 PetscFunctionBegin; 7049 /* currently sctx is memory bleed */ 7050 ierr = PetscNew(&sctx);CHKERRQ(ierr); 7051 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 7052 /* 7053 This should work, but it doesn't 7054 sctx->ctx = ctx; 7055 mexMakeArrayPersistent(sctx->ctx); 7056 */ 7057 sctx->ctx = mxDuplicateArray(ctx); 7058 7059 ierr = TSSetIJacobian(ts,A,B,TSComputeJacobian_Matlab,sctx);CHKERRQ(ierr); 7060 PetscFunctionReturn(0); 7061 } 7062 7063 /* 7064 TSMonitor_Matlab - Calls the function that has been set with TSMonitorSetMatlab(). 7065 7066 Collective on TS 7067 7068 .seealso: TSSetFunction(), TSGetFunction() 7069 @*/ 7070 PetscErrorCode TSMonitor_Matlab(TS ts,PetscInt it, PetscReal time,Vec u, void *ctx) 7071 { 7072 PetscErrorCode ierr; 7073 TSMatlabContext *sctx = (TSMatlabContext*)ctx; 7074 int nlhs = 1,nrhs = 6; 7075 mxArray *plhs[1],*prhs[6]; 7076 long long int lx = 0,ls = 0; 7077 7078 PetscFunctionBegin; 7079 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 7080 PetscValidHeaderSpecific(u,VEC_CLASSID,4); 7081 7082 ierr = PetscMemcpy(&ls,&ts,sizeof(ts));CHKERRQ(ierr); 7083 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 7084 7085 prhs[0] = mxCreateDoubleScalar((double)ls); 7086 prhs[1] = mxCreateDoubleScalar((double)it); 7087 prhs[2] = mxCreateDoubleScalar((double)time); 7088 prhs[3] = mxCreateDoubleScalar((double)lx); 7089 prhs[4] = mxCreateString(sctx->funcname); 7090 prhs[5] = sctx->ctx; 7091 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSMonitorInternal");CHKERRQ(ierr); 7092 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 7093 mxDestroyArray(prhs[0]); 7094 mxDestroyArray(prhs[1]); 7095 mxDestroyArray(prhs[2]); 7096 mxDestroyArray(prhs[3]); 7097 mxDestroyArray(prhs[4]); 7098 mxDestroyArray(plhs[0]); 7099 PetscFunctionReturn(0); 7100 } 7101 7102 /* 7103 TSMonitorSetMatlab - Sets the monitor function from Matlab 7104 7105 Level: developer 7106 7107 .keywords: TS, nonlinear, set, function 7108 7109 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 7110 */ 7111 PetscErrorCode TSMonitorSetMatlab(TS ts,const char *func,mxArray *ctx) 7112 { 7113 PetscErrorCode ierr; 7114 TSMatlabContext *sctx; 7115 7116 PetscFunctionBegin; 7117 /* currently sctx is memory bleed */ 7118 ierr = PetscNew(&sctx);CHKERRQ(ierr); 7119 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 7120 /* 7121 This should work, but it doesn't 7122 sctx->ctx = ctx; 7123 mexMakeArrayPersistent(sctx->ctx); 7124 */ 7125 sctx->ctx = mxDuplicateArray(ctx); 7126 7127 ierr = TSMonitorSet(ts,TSMonitor_Matlab,sctx,NULL);CHKERRQ(ierr); 7128 PetscFunctionReturn(0); 7129 } 7130 #endif 7131 7132 /*@C 7133 TSMonitorLGSolution - Monitors progress of the TS solvers by plotting each component of the solution vector 7134 in a time based line graph 7135 7136 Collective on TS 7137 7138 Input Parameters: 7139 + ts - the TS context 7140 . step - current time-step 7141 . ptime - current time 7142 . u - current solution 7143 - dctx - the TSMonitorLGCtx object that contains all the options for the monitoring, this is created with TSMonitorLGCtxCreate() 7144 7145 Options Database: 7146 . -ts_monitor_lg_solution_variables 7147 7148 Level: intermediate 7149 7150 Notes: Each process in a parallel run displays its component solutions in a separate window 7151 7152 .keywords: TS, vector, monitor, view 7153 7154 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGCtxCreate(), TSMonitorLGCtxSetVariableNames(), TSMonitorLGCtxGetVariableNames(), 7155 TSMonitorLGSetVariableNames(), TSMonitorLGGetVariableNames(), TSMonitorLGSetDisplayVariables(), TSMonitorLGCtxSetDisplayVariables(), 7156 TSMonitorLGCtxSetTransform(), TSMonitorLGSetTransform(), TSMonitorLGError(), TSMonitorLGSNESIterations(), TSMonitorLGKSPIterations(), 7157 TSMonitorEnvelopeCtxCreate(), TSMonitorEnvelopeGetBounds(), TSMonitorEnvelopeCtxDestroy(), TSMonitorEnvelop() 7158 @*/ 7159 PetscErrorCode TSMonitorLGSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dctx) 7160 { 7161 PetscErrorCode ierr; 7162 TSMonitorLGCtx ctx = (TSMonitorLGCtx)dctx; 7163 const PetscScalar *yy; 7164 Vec v; 7165 7166 PetscFunctionBegin; 7167 if (step < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */ 7168 if (!step) { 7169 PetscDrawAxis axis; 7170 PetscInt dim; 7171 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 7172 ierr = PetscDrawAxisSetLabels(axis,"Solution as function of time","Time","Solution");CHKERRQ(ierr); 7173 if (!ctx->names) { 7174 PetscBool flg; 7175 /* user provides names of variables to plot but no names has been set so assume names are integer values */ 7176 ierr = PetscOptionsHasName(((PetscObject)ts)->options,((PetscObject)ts)->prefix,"-ts_monitor_lg_solution_variables",&flg);CHKERRQ(ierr); 7177 if (flg) { 7178 PetscInt i,n; 7179 char **names; 7180 ierr = VecGetSize(u,&n);CHKERRQ(ierr); 7181 ierr = PetscMalloc1(n+1,&names);CHKERRQ(ierr); 7182 for (i=0; i<n; i++) { 7183 ierr = PetscMalloc1(5,&names[i]);CHKERRQ(ierr); 7184 ierr = PetscSNPrintf(names[i],5,"%D",i);CHKERRQ(ierr); 7185 } 7186 names[n] = NULL; 7187 ctx->names = names; 7188 } 7189 } 7190 if (ctx->names && !ctx->displaynames) { 7191 char **displaynames; 7192 PetscBool flg; 7193 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 7194 ierr = PetscMalloc1(dim+1,&displaynames);CHKERRQ(ierr); 7195 ierr = PetscMemzero(displaynames,(dim+1)*sizeof(char*));CHKERRQ(ierr); 7196 ierr = PetscOptionsGetStringArray(((PetscObject)ts)->options,((PetscObject)ts)->prefix,"-ts_monitor_lg_solution_variables",displaynames,&dim,&flg);CHKERRQ(ierr); 7197 if (flg) { 7198 ierr = TSMonitorLGCtxSetDisplayVariables(ctx,(const char *const *)displaynames);CHKERRQ(ierr); 7199 } 7200 ierr = PetscStrArrayDestroy(&displaynames);CHKERRQ(ierr); 7201 } 7202 if (ctx->displaynames) { 7203 ierr = PetscDrawLGSetDimension(ctx->lg,ctx->ndisplayvariables);CHKERRQ(ierr); 7204 ierr = PetscDrawLGSetLegend(ctx->lg,(const char *const *)ctx->displaynames);CHKERRQ(ierr); 7205 } else if (ctx->names) { 7206 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 7207 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 7208 ierr = PetscDrawLGSetLegend(ctx->lg,(const char *const *)ctx->names);CHKERRQ(ierr); 7209 } else { 7210 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 7211 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 7212 } 7213 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 7214 } 7215 7216 if (!ctx->transform) v = u; 7217 else {ierr = (*ctx->transform)(ctx->transformctx,u,&v);CHKERRQ(ierr);} 7218 ierr = VecGetArrayRead(v,&yy);CHKERRQ(ierr); 7219 if (ctx->displaynames) { 7220 PetscInt i; 7221 for (i=0; i<ctx->ndisplayvariables; i++) 7222 ctx->displayvalues[i] = PetscRealPart(yy[ctx->displayvariables[i]]); 7223 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,ctx->displayvalues);CHKERRQ(ierr); 7224 } else { 7225 #if defined(PETSC_USE_COMPLEX) 7226 PetscInt i,n; 7227 PetscReal *yreal; 7228 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 7229 ierr = PetscMalloc1(n,&yreal);CHKERRQ(ierr); 7230 for (i=0; i<n; i++) yreal[i] = PetscRealPart(yy[i]); 7231 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yreal);CHKERRQ(ierr); 7232 ierr = PetscFree(yreal);CHKERRQ(ierr); 7233 #else 7234 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yy);CHKERRQ(ierr); 7235 #endif 7236 } 7237 ierr = VecRestoreArrayRead(v,&yy);CHKERRQ(ierr); 7238 if (ctx->transform) {ierr = VecDestroy(&v);CHKERRQ(ierr);} 7239 7240 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 7241 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 7242 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 7243 } 7244 PetscFunctionReturn(0); 7245 } 7246 7247 /*@C 7248 TSMonitorLGSetVariableNames - Sets the name of each component in the solution vector so that it may be displayed in the plot 7249 7250 Collective on TS 7251 7252 Input Parameters: 7253 + ts - the TS context 7254 - names - the names of the components, final string must be NULL 7255 7256 Level: intermediate 7257 7258 Notes: If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored 7259 7260 .keywords: TS, vector, monitor, view 7261 7262 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables(), TSMonitorLGCtxSetVariableNames() 7263 @*/ 7264 PetscErrorCode TSMonitorLGSetVariableNames(TS ts,const char * const *names) 7265 { 7266 PetscErrorCode ierr; 7267 PetscInt i; 7268 7269 PetscFunctionBegin; 7270 for (i=0; i<ts->numbermonitors; i++) { 7271 if (ts->monitor[i] == TSMonitorLGSolution) { 7272 ierr = TSMonitorLGCtxSetVariableNames((TSMonitorLGCtx)ts->monitorcontext[i],names);CHKERRQ(ierr); 7273 break; 7274 } 7275 } 7276 PetscFunctionReturn(0); 7277 } 7278 7279 /*@C 7280 TSMonitorLGCtxSetVariableNames - Sets the name of each component in the solution vector so that it may be displayed in the plot 7281 7282 Collective on TS 7283 7284 Input Parameters: 7285 + ts - the TS context 7286 - names - the names of the components, final string must be NULL 7287 7288 Level: intermediate 7289 7290 .keywords: TS, vector, monitor, view 7291 7292 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables(), TSMonitorLGSetVariableNames() 7293 @*/ 7294 PetscErrorCode TSMonitorLGCtxSetVariableNames(TSMonitorLGCtx ctx,const char * const *names) 7295 { 7296 PetscErrorCode ierr; 7297 7298 PetscFunctionBegin; 7299 ierr = PetscStrArrayDestroy(&ctx->names);CHKERRQ(ierr); 7300 ierr = PetscStrArrayallocpy(names,&ctx->names);CHKERRQ(ierr); 7301 PetscFunctionReturn(0); 7302 } 7303 7304 /*@C 7305 TSMonitorLGGetVariableNames - Gets the name of each component in the solution vector so that it may be displayed in the plot 7306 7307 Collective on TS 7308 7309 Input Parameter: 7310 . ts - the TS context 7311 7312 Output Parameter: 7313 . names - the names of the components, final string must be NULL 7314 7315 Level: intermediate 7316 7317 Notes: If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored 7318 7319 .keywords: TS, vector, monitor, view 7320 7321 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables() 7322 @*/ 7323 PetscErrorCode TSMonitorLGGetVariableNames(TS ts,const char *const **names) 7324 { 7325 PetscInt i; 7326 7327 PetscFunctionBegin; 7328 *names = NULL; 7329 for (i=0; i<ts->numbermonitors; i++) { 7330 if (ts->monitor[i] == TSMonitorLGSolution) { 7331 TSMonitorLGCtx ctx = (TSMonitorLGCtx) ts->monitorcontext[i]; 7332 *names = (const char *const *)ctx->names; 7333 break; 7334 } 7335 } 7336 PetscFunctionReturn(0); 7337 } 7338 7339 /*@C 7340 TSMonitorLGCtxSetDisplayVariables - Sets the variables that are to be display in the monitor 7341 7342 Collective on TS 7343 7344 Input Parameters: 7345 + ctx - the TSMonitorLG context 7346 . displaynames - the names of the components, final string must be NULL 7347 7348 Level: intermediate 7349 7350 .keywords: TS, vector, monitor, view 7351 7352 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames() 7353 @*/ 7354 PetscErrorCode TSMonitorLGCtxSetDisplayVariables(TSMonitorLGCtx ctx,const char * const *displaynames) 7355 { 7356 PetscInt j = 0,k; 7357 PetscErrorCode ierr; 7358 7359 PetscFunctionBegin; 7360 if (!ctx->names) PetscFunctionReturn(0); 7361 ierr = PetscStrArrayDestroy(&ctx->displaynames);CHKERRQ(ierr); 7362 ierr = PetscStrArrayallocpy(displaynames,&ctx->displaynames);CHKERRQ(ierr); 7363 while (displaynames[j]) j++; 7364 ctx->ndisplayvariables = j; 7365 ierr = PetscMalloc1(ctx->ndisplayvariables,&ctx->displayvariables);CHKERRQ(ierr); 7366 ierr = PetscMalloc1(ctx->ndisplayvariables,&ctx->displayvalues);CHKERRQ(ierr); 7367 j = 0; 7368 while (displaynames[j]) { 7369 k = 0; 7370 while (ctx->names[k]) { 7371 PetscBool flg; 7372 ierr = PetscStrcmp(displaynames[j],ctx->names[k],&flg);CHKERRQ(ierr); 7373 if (flg) { 7374 ctx->displayvariables[j] = k; 7375 break; 7376 } 7377 k++; 7378 } 7379 j++; 7380 } 7381 PetscFunctionReturn(0); 7382 } 7383 7384 /*@C 7385 TSMonitorLGSetDisplayVariables - Sets the variables that are to be display in the monitor 7386 7387 Collective on TS 7388 7389 Input Parameters: 7390 + ts - the TS context 7391 . displaynames - the names of the components, final string must be NULL 7392 7393 Notes: If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored 7394 7395 Level: intermediate 7396 7397 .keywords: TS, vector, monitor, view 7398 7399 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames() 7400 @*/ 7401 PetscErrorCode TSMonitorLGSetDisplayVariables(TS ts,const char * const *displaynames) 7402 { 7403 PetscInt i; 7404 PetscErrorCode ierr; 7405 7406 PetscFunctionBegin; 7407 for (i=0; i<ts->numbermonitors; i++) { 7408 if (ts->monitor[i] == TSMonitorLGSolution) { 7409 ierr = TSMonitorLGCtxSetDisplayVariables((TSMonitorLGCtx)ts->monitorcontext[i],displaynames);CHKERRQ(ierr); 7410 break; 7411 } 7412 } 7413 PetscFunctionReturn(0); 7414 } 7415 7416 /*@C 7417 TSMonitorLGSetTransform - Solution vector will be transformed by provided function before being displayed 7418 7419 Collective on TS 7420 7421 Input Parameters: 7422 + ts - the TS context 7423 . transform - the transform function 7424 . destroy - function to destroy the optional context 7425 - ctx - optional context used by transform function 7426 7427 Notes: If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored 7428 7429 Level: intermediate 7430 7431 .keywords: TS, vector, monitor, view 7432 7433 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames(), TSMonitorLGCtxSetTransform() 7434 @*/ 7435 PetscErrorCode TSMonitorLGSetTransform(TS ts,PetscErrorCode (*transform)(void*,Vec,Vec*),PetscErrorCode (*destroy)(void*),void *tctx) 7436 { 7437 PetscInt i; 7438 PetscErrorCode ierr; 7439 7440 PetscFunctionBegin; 7441 for (i=0; i<ts->numbermonitors; i++) { 7442 if (ts->monitor[i] == TSMonitorLGSolution) { 7443 ierr = TSMonitorLGCtxSetTransform((TSMonitorLGCtx)ts->monitorcontext[i],transform,destroy,tctx);CHKERRQ(ierr); 7444 } 7445 } 7446 PetscFunctionReturn(0); 7447 } 7448 7449 /*@C 7450 TSMonitorLGCtxSetTransform - Solution vector will be transformed by provided function before being displayed 7451 7452 Collective on TSLGCtx 7453 7454 Input Parameters: 7455 + ts - the TS context 7456 . transform - the transform function 7457 . destroy - function to destroy the optional context 7458 - ctx - optional context used by transform function 7459 7460 Level: intermediate 7461 7462 .keywords: TS, vector, monitor, view 7463 7464 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames(), TSMonitorLGSetTransform() 7465 @*/ 7466 PetscErrorCode TSMonitorLGCtxSetTransform(TSMonitorLGCtx ctx,PetscErrorCode (*transform)(void*,Vec,Vec*),PetscErrorCode (*destroy)(void*),void *tctx) 7467 { 7468 PetscFunctionBegin; 7469 ctx->transform = transform; 7470 ctx->transformdestroy = destroy; 7471 ctx->transformctx = tctx; 7472 PetscFunctionReturn(0); 7473 } 7474 7475 /*@C 7476 TSMonitorLGError - Monitors progress of the TS solvers by plotting each component of the error 7477 in a time based line graph 7478 7479 Collective on TS 7480 7481 Input Parameters: 7482 + ts - the TS context 7483 . step - current time-step 7484 . ptime - current time 7485 . u - current solution 7486 - dctx - TSMonitorLGCtx object created with TSMonitorLGCtxCreate() 7487 7488 Level: intermediate 7489 7490 Notes: Each process in a parallel run displays its component errors in a separate window 7491 7492 The user must provide the solution using TSSetSolutionFunction() to use this monitor. 7493 7494 Options Database Keys: 7495 . -ts_monitor_lg_error - create a graphical monitor of error history 7496 7497 .keywords: TS, vector, monitor, view 7498 7499 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSSetSolutionFunction() 7500 @*/ 7501 PetscErrorCode TSMonitorLGError(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 7502 { 7503 PetscErrorCode ierr; 7504 TSMonitorLGCtx ctx = (TSMonitorLGCtx)dummy; 7505 const PetscScalar *yy; 7506 Vec y; 7507 7508 PetscFunctionBegin; 7509 if (!step) { 7510 PetscDrawAxis axis; 7511 PetscInt dim; 7512 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 7513 ierr = PetscDrawAxisSetLabels(axis,"Error in solution as function of time","Time","Error");CHKERRQ(ierr); 7514 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 7515 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 7516 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 7517 } 7518 ierr = VecDuplicate(u,&y);CHKERRQ(ierr); 7519 ierr = TSComputeSolutionFunction(ts,ptime,y);CHKERRQ(ierr); 7520 ierr = VecAXPY(y,-1.0,u);CHKERRQ(ierr); 7521 ierr = VecGetArrayRead(y,&yy);CHKERRQ(ierr); 7522 #if defined(PETSC_USE_COMPLEX) 7523 { 7524 PetscReal *yreal; 7525 PetscInt i,n; 7526 ierr = VecGetLocalSize(y,&n);CHKERRQ(ierr); 7527 ierr = PetscMalloc1(n,&yreal);CHKERRQ(ierr); 7528 for (i=0; i<n; i++) yreal[i] = PetscRealPart(yy[i]); 7529 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yreal);CHKERRQ(ierr); 7530 ierr = PetscFree(yreal);CHKERRQ(ierr); 7531 } 7532 #else 7533 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yy);CHKERRQ(ierr); 7534 #endif 7535 ierr = VecRestoreArrayRead(y,&yy);CHKERRQ(ierr); 7536 ierr = VecDestroy(&y);CHKERRQ(ierr); 7537 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 7538 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 7539 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 7540 } 7541 PetscFunctionReturn(0); 7542 } 7543 7544 PetscErrorCode TSMonitorLGSNESIterations(TS ts,PetscInt n,PetscReal ptime,Vec v,void *monctx) 7545 { 7546 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 7547 PetscReal x = ptime,y; 7548 PetscErrorCode ierr; 7549 PetscInt its; 7550 7551 PetscFunctionBegin; 7552 if (n < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */ 7553 if (!n) { 7554 PetscDrawAxis axis; 7555 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 7556 ierr = PetscDrawAxisSetLabels(axis,"Nonlinear iterations as function of time","Time","SNES Iterations");CHKERRQ(ierr); 7557 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 7558 ctx->snes_its = 0; 7559 } 7560 ierr = TSGetSNESIterations(ts,&its);CHKERRQ(ierr); 7561 y = its - ctx->snes_its; 7562 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 7563 if (((ctx->howoften > 0) && (!(n % ctx->howoften)) && (n > -1)) || ((ctx->howoften == -1) && (n == -1))) { 7564 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 7565 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 7566 } 7567 ctx->snes_its = its; 7568 PetscFunctionReturn(0); 7569 } 7570 7571 PetscErrorCode TSMonitorLGKSPIterations(TS ts,PetscInt n,PetscReal ptime,Vec v,void *monctx) 7572 { 7573 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 7574 PetscReal x = ptime,y; 7575 PetscErrorCode ierr; 7576 PetscInt its; 7577 7578 PetscFunctionBegin; 7579 if (n < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */ 7580 if (!n) { 7581 PetscDrawAxis axis; 7582 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 7583 ierr = PetscDrawAxisSetLabels(axis,"Linear iterations as function of time","Time","KSP Iterations");CHKERRQ(ierr); 7584 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 7585 ctx->ksp_its = 0; 7586 } 7587 ierr = TSGetKSPIterations(ts,&its);CHKERRQ(ierr); 7588 y = its - ctx->ksp_its; 7589 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 7590 if (((ctx->howoften > 0) && (!(n % ctx->howoften)) && (n > -1)) || ((ctx->howoften == -1) && (n == -1))) { 7591 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 7592 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 7593 } 7594 ctx->ksp_its = its; 7595 PetscFunctionReturn(0); 7596 } 7597 7598 /*@ 7599 TSComputeLinearStability - computes the linear stability function at a point 7600 7601 Collective on TS and Vec 7602 7603 Input Parameters: 7604 + ts - the TS context 7605 - xr,xi - real and imaginary part of input arguments 7606 7607 Output Parameters: 7608 . yr,yi - real and imaginary part of function value 7609 7610 Level: developer 7611 7612 .keywords: TS, compute 7613 7614 .seealso: TSSetRHSFunction(), TSComputeIFunction() 7615 @*/ 7616 PetscErrorCode TSComputeLinearStability(TS ts,PetscReal xr,PetscReal xi,PetscReal *yr,PetscReal *yi) 7617 { 7618 PetscErrorCode ierr; 7619 7620 PetscFunctionBegin; 7621 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 7622 if (!ts->ops->linearstability) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Linearized stability function not provided for this method"); 7623 ierr = (*ts->ops->linearstability)(ts,xr,xi,yr,yi);CHKERRQ(ierr); 7624 PetscFunctionReturn(0); 7625 } 7626 7627 /* ------------------------------------------------------------------------*/ 7628 /*@C 7629 TSMonitorEnvelopeCtxCreate - Creates a context for use with TSMonitorEnvelope() 7630 7631 Collective on TS 7632 7633 Input Parameters: 7634 . ts - the ODE solver object 7635 7636 Output Parameter: 7637 . ctx - the context 7638 7639 Level: intermediate 7640 7641 .keywords: TS, monitor, line graph, residual, seealso 7642 7643 .seealso: TSMonitorLGTimeStep(), TSMonitorSet(), TSMonitorLGSolution(), TSMonitorLGError() 7644 7645 @*/ 7646 PetscErrorCode TSMonitorEnvelopeCtxCreate(TS ts,TSMonitorEnvelopeCtx *ctx) 7647 { 7648 PetscErrorCode ierr; 7649 7650 PetscFunctionBegin; 7651 ierr = PetscNew(ctx);CHKERRQ(ierr); 7652 PetscFunctionReturn(0); 7653 } 7654 7655 /*@C 7656 TSMonitorEnvelope - Monitors the maximum and minimum value of each component of the solution 7657 7658 Collective on TS 7659 7660 Input Parameters: 7661 + ts - the TS context 7662 . step - current time-step 7663 . ptime - current time 7664 . u - current solution 7665 - dctx - the envelope context 7666 7667 Options Database: 7668 . -ts_monitor_envelope 7669 7670 Level: intermediate 7671 7672 Notes: after a solve you can use TSMonitorEnvelopeGetBounds() to access the envelope 7673 7674 .keywords: TS, vector, monitor, view 7675 7676 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorEnvelopeGetBounds(), TSMonitorEnvelopeCtxCreate() 7677 @*/ 7678 PetscErrorCode TSMonitorEnvelope(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dctx) 7679 { 7680 PetscErrorCode ierr; 7681 TSMonitorEnvelopeCtx ctx = (TSMonitorEnvelopeCtx)dctx; 7682 7683 PetscFunctionBegin; 7684 if (!ctx->max) { 7685 ierr = VecDuplicate(u,&ctx->max);CHKERRQ(ierr); 7686 ierr = VecDuplicate(u,&ctx->min);CHKERRQ(ierr); 7687 ierr = VecCopy(u,ctx->max);CHKERRQ(ierr); 7688 ierr = VecCopy(u,ctx->min);CHKERRQ(ierr); 7689 } else { 7690 ierr = VecPointwiseMax(ctx->max,u,ctx->max);CHKERRQ(ierr); 7691 ierr = VecPointwiseMin(ctx->min,u,ctx->min);CHKERRQ(ierr); 7692 } 7693 PetscFunctionReturn(0); 7694 } 7695 7696 /*@C 7697 TSMonitorEnvelopeGetBounds - Gets the bounds for the components of the solution 7698 7699 Collective on TS 7700 7701 Input Parameter: 7702 . ts - the TS context 7703 7704 Output Parameter: 7705 + max - the maximum values 7706 - min - the minimum values 7707 7708 Notes: If the TS does not have a TSMonitorEnvelopeCtx associated with it then this function is ignored 7709 7710 Level: intermediate 7711 7712 .keywords: TS, vector, monitor, view 7713 7714 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables() 7715 @*/ 7716 PetscErrorCode TSMonitorEnvelopeGetBounds(TS ts,Vec *max,Vec *min) 7717 { 7718 PetscInt i; 7719 7720 PetscFunctionBegin; 7721 if (max) *max = NULL; 7722 if (min) *min = NULL; 7723 for (i=0; i<ts->numbermonitors; i++) { 7724 if (ts->monitor[i] == TSMonitorEnvelope) { 7725 TSMonitorEnvelopeCtx ctx = (TSMonitorEnvelopeCtx) ts->monitorcontext[i]; 7726 if (max) *max = ctx->max; 7727 if (min) *min = ctx->min; 7728 break; 7729 } 7730 } 7731 PetscFunctionReturn(0); 7732 } 7733 7734 /*@C 7735 TSMonitorEnvelopeCtxDestroy - Destroys a context that was created with TSMonitorEnvelopeCtxCreate(). 7736 7737 Collective on TSMonitorEnvelopeCtx 7738 7739 Input Parameter: 7740 . ctx - the monitor context 7741 7742 Level: intermediate 7743 7744 .keywords: TS, monitor, line graph, destroy 7745 7746 .seealso: TSMonitorLGCtxCreate(), TSMonitorSet(), TSMonitorLGTimeStep() 7747 @*/ 7748 PetscErrorCode TSMonitorEnvelopeCtxDestroy(TSMonitorEnvelopeCtx *ctx) 7749 { 7750 PetscErrorCode ierr; 7751 7752 PetscFunctionBegin; 7753 ierr = VecDestroy(&(*ctx)->min);CHKERRQ(ierr); 7754 ierr = VecDestroy(&(*ctx)->max);CHKERRQ(ierr); 7755 ierr = PetscFree(*ctx);CHKERRQ(ierr); 7756 PetscFunctionReturn(0); 7757 } 7758 7759 /*@ 7760 TSRollBack - Rolls back one time step 7761 7762 Collective on TS 7763 7764 Input Parameter: 7765 . ts - the TS context obtained from TSCreate() 7766 7767 Level: advanced 7768 7769 .keywords: TS, timestep, rollback 7770 7771 .seealso: TSCreate(), TSSetUp(), TSDestroy(), TSSolve(), TSSetPreStep(), TSSetPreStage(), TSInterpolate() 7772 @*/ 7773 PetscErrorCode TSRollBack(TS ts) 7774 { 7775 PetscErrorCode ierr; 7776 7777 PetscFunctionBegin; 7778 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 7779 if (ts->steprollback) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"TSRollBack already called"); 7780 if (!ts->ops->rollback) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSRollBack not implemented for type '%s'",((PetscObject)ts)->type_name); 7781 ierr = (*ts->ops->rollback)(ts);CHKERRQ(ierr); 7782 ts->time_step = ts->ptime - ts->ptime_prev; 7783 ts->ptime = ts->ptime_prev; 7784 ts->ptime_prev = ts->ptime_prev_rollback; 7785 ts->steps--; 7786 ts->steprollback = PETSC_TRUE; 7787 PetscFunctionReturn(0); 7788 } 7789 7790 /*@ 7791 TSGetStages - Get the number of stages and stage values 7792 7793 Input Parameter: 7794 . ts - the TS context obtained from TSCreate() 7795 7796 Level: advanced 7797 7798 .keywords: TS, getstages 7799 7800 .seealso: TSCreate() 7801 @*/ 7802 PetscErrorCode TSGetStages(TS ts,PetscInt *ns,Vec **Y) 7803 { 7804 PetscErrorCode ierr; 7805 7806 PetscFunctionBegin; 7807 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 7808 PetscValidPointer(ns,2); 7809 7810 if (!ts->ops->getstages) *ns=0; 7811 else { 7812 ierr = (*ts->ops->getstages)(ts,ns,Y);CHKERRQ(ierr); 7813 } 7814 PetscFunctionReturn(0); 7815 } 7816 7817 /*@C 7818 TSComputeIJacobianDefaultColor - Computes the Jacobian using finite differences and coloring to exploit matrix sparsity. 7819 7820 Collective on SNES 7821 7822 Input Parameters: 7823 + ts - the TS context 7824 . t - current timestep 7825 . U - state vector 7826 . Udot - time derivative of state vector 7827 . shift - shift to apply, see note below 7828 - ctx - an optional user context 7829 7830 Output Parameters: 7831 + J - Jacobian matrix (not altered in this routine) 7832 - B - newly computed Jacobian matrix to use with preconditioner (generally the same as J) 7833 7834 Level: intermediate 7835 7836 Notes: 7837 If F(t,U,Udot)=0 is the DAE, the required Jacobian is 7838 7839 dF/dU + shift*dF/dUdot 7840 7841 Most users should not need to explicitly call this routine, as it 7842 is used internally within the nonlinear solvers. 7843 7844 This will first try to get the coloring from the DM. If the DM type has no coloring 7845 routine, then it will try to get the coloring from the matrix. This requires that the 7846 matrix have nonzero entries precomputed. 7847 7848 .keywords: TS, finite differences, Jacobian, coloring, sparse 7849 .seealso: TSSetIJacobian(), MatFDColoringCreate(), MatFDColoringSetFunction() 7850 @*/ 7851 PetscErrorCode TSComputeIJacobianDefaultColor(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat J,Mat B,void *ctx) 7852 { 7853 SNES snes; 7854 MatFDColoring color; 7855 PetscBool hascolor, matcolor = PETSC_FALSE; 7856 PetscErrorCode ierr; 7857 7858 PetscFunctionBegin; 7859 ierr = PetscOptionsGetBool(((PetscObject)ts)->options,((PetscObject) ts)->prefix, "-ts_fd_color_use_mat", &matcolor, NULL);CHKERRQ(ierr); 7860 ierr = PetscObjectQuery((PetscObject) B, "TSMatFDColoring", (PetscObject *) &color);CHKERRQ(ierr); 7861 if (!color) { 7862 DM dm; 7863 ISColoring iscoloring; 7864 7865 ierr = TSGetDM(ts, &dm);CHKERRQ(ierr); 7866 ierr = DMHasColoring(dm, &hascolor);CHKERRQ(ierr); 7867 if (hascolor && !matcolor) { 7868 ierr = DMCreateColoring(dm, IS_COLORING_GLOBAL, &iscoloring);CHKERRQ(ierr); 7869 ierr = MatFDColoringCreate(B, iscoloring, &color);CHKERRQ(ierr); 7870 ierr = MatFDColoringSetFunction(color, (PetscErrorCode (*)(void)) SNESTSFormFunction, (void *) ts);CHKERRQ(ierr); 7871 ierr = MatFDColoringSetFromOptions(color);CHKERRQ(ierr); 7872 ierr = MatFDColoringSetUp(B, iscoloring, color);CHKERRQ(ierr); 7873 ierr = ISColoringDestroy(&iscoloring);CHKERRQ(ierr); 7874 } else { 7875 MatColoring mc; 7876 7877 ierr = MatColoringCreate(B, &mc);CHKERRQ(ierr); 7878 ierr = MatColoringSetDistance(mc, 2);CHKERRQ(ierr); 7879 ierr = MatColoringSetType(mc, MATCOLORINGSL);CHKERRQ(ierr); 7880 ierr = MatColoringSetFromOptions(mc);CHKERRQ(ierr); 7881 ierr = MatColoringApply(mc, &iscoloring);CHKERRQ(ierr); 7882 ierr = MatColoringDestroy(&mc);CHKERRQ(ierr); 7883 ierr = MatFDColoringCreate(B, iscoloring, &color);CHKERRQ(ierr); 7884 ierr = MatFDColoringSetFunction(color, (PetscErrorCode (*)(void)) SNESTSFormFunction, (void *) ts);CHKERRQ(ierr); 7885 ierr = MatFDColoringSetFromOptions(color);CHKERRQ(ierr); 7886 ierr = MatFDColoringSetUp(B, iscoloring, color);CHKERRQ(ierr); 7887 ierr = ISColoringDestroy(&iscoloring);CHKERRQ(ierr); 7888 } 7889 ierr = PetscObjectCompose((PetscObject) B, "TSMatFDColoring", (PetscObject) color);CHKERRQ(ierr); 7890 ierr = PetscObjectDereference((PetscObject) color);CHKERRQ(ierr); 7891 } 7892 ierr = TSGetSNES(ts, &snes);CHKERRQ(ierr); 7893 ierr = MatFDColoringApply(B, color, U, snes);CHKERRQ(ierr); 7894 if (J != B) { 7895 ierr = MatAssemblyBegin(J, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 7896 ierr = MatAssemblyEnd(J, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 7897 } 7898 PetscFunctionReturn(0); 7899 } 7900 7901 /*@ 7902 TSSetFunctionDomainError - Set the function testing if the current state vector is valid 7903 7904 Input Parameters: 7905 ts - the TS context 7906 func - function called within TSFunctionDomainError 7907 7908 Level: intermediate 7909 7910 .keywords: TS, state, domain 7911 .seealso: TSAdaptCheckStage(), TSFunctionDomainError() 7912 @*/ 7913 7914 PetscErrorCode TSSetFunctionDomainError(TS ts, PetscErrorCode (*func)(TS,PetscReal,Vec,PetscBool*)) 7915 { 7916 PetscFunctionBegin; 7917 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 7918 ts->functiondomainerror = func; 7919 PetscFunctionReturn(0); 7920 } 7921 7922 /*@ 7923 TSFunctionDomainError - Check if the current state is valid 7924 7925 Input Parameters: 7926 ts - the TS context 7927 stagetime - time of the simulation 7928 Y - state vector to check. 7929 7930 Output Parameter: 7931 accept - Set to PETSC_FALSE if the current state vector is valid. 7932 7933 Note: 7934 This function should be used to ensure the state is in a valid part of the space. 7935 For example, one can ensure here all values are positive. 7936 7937 Level: advanced 7938 @*/ 7939 PetscErrorCode TSFunctionDomainError(TS ts,PetscReal stagetime,Vec Y,PetscBool* accept) 7940 { 7941 PetscErrorCode ierr; 7942 7943 PetscFunctionBegin; 7944 7945 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 7946 *accept = PETSC_TRUE; 7947 if (ts->functiondomainerror) { 7948 PetscStackCallStandard((*ts->functiondomainerror),(ts,stagetime,Y,accept)); 7949 } 7950 PetscFunctionReturn(0); 7951 } 7952 7953 /*@C 7954 TSClone - This function clones a time step object. 7955 7956 Collective on MPI_Comm 7957 7958 Input Parameter: 7959 . tsin - The input TS 7960 7961 Output Parameter: 7962 . tsout - The output TS (cloned) 7963 7964 Notes: 7965 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. 7966 7967 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); 7968 7969 Level: developer 7970 7971 .keywords: TS, clone 7972 .seealso: TSCreate(), TSSetType(), TSSetUp(), TSDestroy(), TSSetProblemType() 7973 @*/ 7974 PetscErrorCode TSClone(TS tsin, TS *tsout) 7975 { 7976 TS t; 7977 PetscErrorCode ierr; 7978 SNES snes_start; 7979 DM dm; 7980 TSType type; 7981 7982 PetscFunctionBegin; 7983 PetscValidPointer(tsin,1); 7984 *tsout = NULL; 7985 7986 ierr = PetscHeaderCreate(t, TS_CLASSID, "TS", "Time stepping", "TS", PetscObjectComm((PetscObject)tsin), TSDestroy, TSView);CHKERRQ(ierr); 7987 7988 /* General TS description */ 7989 t->numbermonitors = 0; 7990 t->setupcalled = 0; 7991 t->ksp_its = 0; 7992 t->snes_its = 0; 7993 t->nwork = 0; 7994 t->rhsjacobian.time = -1e20; 7995 t->rhsjacobian.scale = 1.; 7996 t->ijacobian.shift = 1.; 7997 7998 ierr = TSGetSNES(tsin,&snes_start);CHKERRQ(ierr); 7999 ierr = TSSetSNES(t,snes_start);CHKERRQ(ierr); 8000 8001 ierr = TSGetDM(tsin,&dm);CHKERRQ(ierr); 8002 ierr = TSSetDM(t,dm);CHKERRQ(ierr); 8003 8004 t->adapt = tsin->adapt; 8005 ierr = PetscObjectReference((PetscObject)t->adapt);CHKERRQ(ierr); 8006 8007 t->trajectory = tsin->trajectory; 8008 ierr = PetscObjectReference((PetscObject)t->trajectory);CHKERRQ(ierr); 8009 8010 t->event = tsin->event; 8011 if (t->event) t->event->refct++; 8012 8013 t->problem_type = tsin->problem_type; 8014 t->ptime = tsin->ptime; 8015 t->ptime_prev = tsin->ptime_prev; 8016 t->time_step = tsin->time_step; 8017 t->max_time = tsin->max_time; 8018 t->steps = tsin->steps; 8019 t->max_steps = tsin->max_steps; 8020 t->equation_type = tsin->equation_type; 8021 t->atol = tsin->atol; 8022 t->rtol = tsin->rtol; 8023 t->max_snes_failures = tsin->max_snes_failures; 8024 t->max_reject = tsin->max_reject; 8025 t->errorifstepfailed = tsin->errorifstepfailed; 8026 8027 ierr = TSGetType(tsin,&type);CHKERRQ(ierr); 8028 ierr = TSSetType(t,type);CHKERRQ(ierr); 8029 8030 t->vec_sol = NULL; 8031 8032 t->cfltime = tsin->cfltime; 8033 t->cfltime_local = tsin->cfltime_local; 8034 t->exact_final_time = tsin->exact_final_time; 8035 8036 ierr = PetscMemcpy(t->ops,tsin->ops,sizeof(struct _TSOps));CHKERRQ(ierr); 8037 8038 if (((PetscObject)tsin)->fortran_func_pointers) { 8039 PetscInt i; 8040 ierr = PetscMalloc((10)*sizeof(void(*)(void)),&((PetscObject)t)->fortran_func_pointers);CHKERRQ(ierr); 8041 for (i=0; i<10; i++) { 8042 ((PetscObject)t)->fortran_func_pointers[i] = ((PetscObject)tsin)->fortran_func_pointers[i]; 8043 } 8044 } 8045 *tsout = t; 8046 PetscFunctionReturn(0); 8047 } 8048