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 PetscErrorCode TSSetInitialTimeStep(TS ts,PetscReal initial_time,PetscReal time_step) 3036 { 3037 PetscErrorCode ierr; 3038 PetscFunctionBegin; 3039 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3040 ierr = TSSetTime(ts,initial_time);CHKERRQ(ierr); 3041 ierr = TSSetTimeStep(ts,time_step);CHKERRQ(ierr); 3042 PetscFunctionReturn(0); 3043 } 3044 3045 /*@ 3046 TSGetDuration - Deprecated, use TSGetMaxSteps() and TSGetMaxTime(). 3047 @*/ 3048 PetscErrorCode TSGetDuration(TS ts, PetscInt *maxsteps, PetscReal *maxtime) 3049 { 3050 PetscFunctionBegin; 3051 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3052 if (maxsteps) { 3053 PetscValidIntPointer(maxsteps,2); 3054 *maxsteps = ts->max_steps; 3055 } 3056 if (maxtime) { 3057 PetscValidScalarPointer(maxtime,3); 3058 *maxtime = ts->max_time; 3059 } 3060 PetscFunctionReturn(0); 3061 } 3062 3063 /*@ 3064 TSSetDuration - Deprecated, use TSSetMaxSteps() and TSSetMaxTime(). 3065 @*/ 3066 PetscErrorCode TSSetDuration(TS ts,PetscInt maxsteps,PetscReal maxtime) 3067 { 3068 PetscFunctionBegin; 3069 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3070 PetscValidLogicalCollectiveInt(ts,maxsteps,2); 3071 PetscValidLogicalCollectiveReal(ts,maxtime,2); 3072 if (maxsteps >= 0) ts->max_steps = maxsteps; 3073 if (maxtime != PETSC_DEFAULT) ts->max_time = maxtime; 3074 PetscFunctionReturn(0); 3075 } 3076 3077 /*@ 3078 TSGetTimeStepNumber - Deprecated, use TSGetStepNumber(). 3079 @*/ 3080 PetscErrorCode TSGetTimeStepNumber(TS ts,PetscInt *steps) { return TSGetStepNumber(ts,steps); } 3081 3082 /*@ 3083 TSGetTotalSteps - Deprecated, use TSGetStepNumber(). 3084 @*/ 3085 PetscErrorCode TSGetTotalSteps(TS ts,PetscInt *steps) { return TSGetStepNumber(ts,steps); } 3086 3087 /*@ 3088 TSSetSolution - Sets the initial solution vector 3089 for use by the TS routines. 3090 3091 Logically Collective on TS and Vec 3092 3093 Input Parameters: 3094 + ts - the TS context obtained from TSCreate() 3095 - u - the solution vector 3096 3097 Level: beginner 3098 3099 .keywords: TS, timestep, set, solution, initial values 3100 @*/ 3101 PetscErrorCode TSSetSolution(TS ts,Vec u) 3102 { 3103 PetscErrorCode ierr; 3104 DM dm; 3105 3106 PetscFunctionBegin; 3107 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3108 PetscValidHeaderSpecific(u,VEC_CLASSID,2); 3109 ierr = PetscObjectReference((PetscObject)u);CHKERRQ(ierr); 3110 ierr = VecDestroy(&ts->vec_sol);CHKERRQ(ierr); 3111 ts->vec_sol = u; 3112 3113 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 3114 ierr = DMShellSetGlobalVector(dm,u);CHKERRQ(ierr); 3115 PetscFunctionReturn(0); 3116 } 3117 3118 /*@ 3119 TSAdjointSetSteps - Sets the number of steps the adjoint solver should take backward in time 3120 3121 Logically Collective on TS 3122 3123 Input Parameters: 3124 + ts - the TS context obtained from TSCreate() 3125 . steps - number of steps to use 3126 3127 Level: intermediate 3128 3129 Notes: Normally one does not call this and TSAdjointSolve() integrates back to the original timestep. One can call this 3130 so as to integrate back to less than the original timestep 3131 3132 .keywords: TS, timestep, set, maximum, iterations 3133 3134 .seealso: TSSetExactFinalTime() 3135 @*/ 3136 PetscErrorCode TSAdjointSetSteps(TS ts,PetscInt steps) 3137 { 3138 PetscFunctionBegin; 3139 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3140 PetscValidLogicalCollectiveInt(ts,steps,2); 3141 if (steps < 0) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Cannot step back a negative number of steps"); 3142 if (steps > ts->steps) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Cannot step back more than the total number of forward steps"); 3143 ts->adjoint_max_steps = steps; 3144 PetscFunctionReturn(0); 3145 } 3146 3147 /*@ 3148 TSSetCostGradients - Sets the initial value of the gradients of the cost function w.r.t. initial values and w.r.t. the problem parameters 3149 for use by the TSAdjoint routines. 3150 3151 Logically Collective on TS and Vec 3152 3153 Input Parameters: 3154 + ts - the TS context obtained from TSCreate() 3155 . 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 3156 - mu - gradients with respect to the parameters, the number of entries in these vectors is the same as the number of parameters 3157 3158 Level: beginner 3159 3160 Notes: the entries in these vectors must be correctly initialized with the values lamda_i = df/dy|finaltime mu_i = df/dp|finaltime 3161 3162 .keywords: TS, timestep, set, sensitivity, initial values 3163 @*/ 3164 PetscErrorCode TSSetCostGradients(TS ts,PetscInt numcost,Vec *lambda,Vec *mu) 3165 { 3166 PetscFunctionBegin; 3167 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3168 PetscValidPointer(lambda,2); 3169 ts->vecs_sensi = lambda; 3170 ts->vecs_sensip = mu; 3171 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"); 3172 ts->numcost = numcost; 3173 PetscFunctionReturn(0); 3174 } 3175 3176 /*@C 3177 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. 3178 3179 Logically Collective on TS 3180 3181 Input Parameters: 3182 + ts - The TS context obtained from TSCreate() 3183 - func - The function 3184 3185 Calling sequence of func: 3186 $ func (TS ts,PetscReal t,Vec y,Mat A,void *ctx); 3187 + t - current timestep 3188 . y - input vector (current ODE solution) 3189 . A - output matrix 3190 - ctx - [optional] user-defined function context 3191 3192 Level: intermediate 3193 3194 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 3195 3196 .keywords: TS, sensitivity 3197 .seealso: 3198 @*/ 3199 PetscErrorCode TSAdjointSetRHSJacobian(TS ts,Mat Amat,PetscErrorCode (*func)(TS,PetscReal,Vec,Mat,void*),void *ctx) 3200 { 3201 PetscErrorCode ierr; 3202 3203 PetscFunctionBegin; 3204 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3205 PetscValidHeaderSpecific(Amat,MAT_CLASSID,2); 3206 3207 ts->rhsjacobianp = func; 3208 ts->rhsjacobianpctx = ctx; 3209 if(Amat) { 3210 ierr = PetscObjectReference((PetscObject)Amat);CHKERRQ(ierr); 3211 ierr = MatDestroy(&ts->Jacp);CHKERRQ(ierr); 3212 ts->Jacp = Amat; 3213 } 3214 PetscFunctionReturn(0); 3215 } 3216 3217 /*@C 3218 TSAdjointComputeRHSJacobian - Runs the user-defined Jacobian function. 3219 3220 Collective on TS 3221 3222 Input Parameters: 3223 . ts - The TS context obtained from TSCreate() 3224 3225 Level: developer 3226 3227 .keywords: TS, sensitivity 3228 .seealso: TSAdjointSetRHSJacobian() 3229 @*/ 3230 PetscErrorCode TSAdjointComputeRHSJacobian(TS ts,PetscReal t,Vec X,Mat Amat) 3231 { 3232 PetscErrorCode ierr; 3233 3234 PetscFunctionBegin; 3235 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3236 PetscValidHeaderSpecific(X,VEC_CLASSID,3); 3237 PetscValidPointer(Amat,4); 3238 3239 PetscStackPush("TS user JacobianP function for sensitivity analysis"); 3240 ierr = (*ts->rhsjacobianp)(ts,t,X,Amat,ts->rhsjacobianpctx); CHKERRQ(ierr); 3241 PetscStackPop; 3242 PetscFunctionReturn(0); 3243 } 3244 3245 /*@C 3246 TSSetCostIntegrand - Sets the routine for evaluating the integral term in one or more cost functions 3247 3248 Logically Collective on TS 3249 3250 Input Parameters: 3251 + ts - the TS context obtained from TSCreate() 3252 . numcost - number of gradients to be computed, this is the number of cost functions 3253 . costintegral - vector that stores the integral values 3254 . rf - routine for evaluating the integrand function 3255 . drdyf - function that computes the gradients of the r's with respect to y,NULL if not a function y 3256 . drdpf - function that computes the gradients of the r's with respect to p, NULL if not a function of p 3257 . fwd - flag indicating whether to evaluate cost integral in the forward run or the adjoint run 3258 - ctx - [optional] user-defined context for private data for the function evaluation routine (may be NULL) 3259 3260 Calling sequence of rf: 3261 $ PetscErrorCode rf(TS ts,PetscReal t,Vec y,Vec f,void *ctx); 3262 3263 Calling sequence of drdyf: 3264 $ PetscErroCode drdyf(TS ts,PetscReal t,Vec y,Vec *drdy,void *ctx); 3265 3266 Calling sequence of drdpf: 3267 $ PetscErroCode drdpf(TS ts,PetscReal t,Vec y,Vec *drdp,void *ctx); 3268 3269 Level: intermediate 3270 3271 Notes: For optimization there is usually a single cost function (numcost = 1). For sensitivities there may be multiple cost functions 3272 3273 .keywords: TS, sensitivity analysis, timestep, set, quadrature, function 3274 3275 .seealso: TSAdjointSetRHSJacobian(),TSGetCostGradients(), TSSetCostGradients() 3276 @*/ 3277 PetscErrorCode TSSetCostIntegrand(TS ts,PetscInt numcost,Vec costintegral,PetscErrorCode (*rf)(TS,PetscReal,Vec,Vec,void*), 3278 PetscErrorCode (*drdyf)(TS,PetscReal,Vec,Vec*,void*), 3279 PetscErrorCode (*drdpf)(TS,PetscReal,Vec,Vec*,void*), 3280 PetscBool fwd,void *ctx) 3281 { 3282 PetscErrorCode ierr; 3283 3284 PetscFunctionBegin; 3285 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3286 if (costintegral) PetscValidHeaderSpecific(costintegral,VEC_CLASSID,3); 3287 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()"); 3288 if (!ts->numcost) ts->numcost=numcost; 3289 3290 if (costintegral) { 3291 ierr = PetscObjectReference((PetscObject)costintegral);CHKERRQ(ierr); 3292 ierr = VecDestroy(&ts->vec_costintegral);CHKERRQ(ierr); 3293 ts->vec_costintegral = costintegral; 3294 } else { 3295 if (!ts->vec_costintegral) { /* Create a seq vec if user does not provide one */ 3296 ierr = VecCreateSeq(PETSC_COMM_SELF,numcost,&ts->vec_costintegral);CHKERRQ(ierr); 3297 } else { 3298 ierr = VecSet(ts->vec_costintegral,0.0);CHKERRQ(ierr); 3299 } 3300 } 3301 if (!ts->vec_costintegrand) { 3302 ierr = VecDuplicate(ts->vec_costintegral,&ts->vec_costintegrand);CHKERRQ(ierr); 3303 } else { 3304 ierr = VecSet(ts->vec_costintegrand,0.0);CHKERRQ(ierr); 3305 } 3306 ts->costintegralfwd = fwd; /* Evaluate the cost integral in forward run if fwd is true */ 3307 ts->costintegrand = rf; 3308 ts->costintegrandctx = ctx; 3309 ts->drdyfunction = drdyf; 3310 ts->drdpfunction = drdpf; 3311 PetscFunctionReturn(0); 3312 } 3313 3314 /*@ 3315 TSGetCostIntegral - Returns the values of the integral term in the cost functions. 3316 It is valid to call the routine after a backward run. 3317 3318 Not Collective 3319 3320 Input Parameter: 3321 . ts - the TS context obtained from TSCreate() 3322 3323 Output Parameter: 3324 . v - the vector containing the integrals for each cost function 3325 3326 Level: intermediate 3327 3328 .seealso: TSSetCostIntegrand() 3329 3330 .keywords: TS, sensitivity analysis 3331 @*/ 3332 PetscErrorCode TSGetCostIntegral(TS ts,Vec *v) 3333 { 3334 PetscFunctionBegin; 3335 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3336 PetscValidPointer(v,2); 3337 *v = ts->vec_costintegral; 3338 PetscFunctionReturn(0); 3339 } 3340 3341 /*@ 3342 TSComputeCostIntegrand - Evaluates the integral function in the cost functions. 3343 3344 Input Parameters: 3345 + ts - the TS context 3346 . t - current time 3347 - y - state vector, i.e. current solution 3348 3349 Output Parameter: 3350 . q - vector of size numcost to hold the outputs 3351 3352 Note: 3353 Most users should not need to explicitly call this routine, as it 3354 is used internally within the sensitivity analysis context. 3355 3356 Level: developer 3357 3358 .keywords: TS, compute 3359 3360 .seealso: TSSetCostIntegrand() 3361 @*/ 3362 PetscErrorCode TSComputeCostIntegrand(TS ts,PetscReal t,Vec y,Vec q) 3363 { 3364 PetscErrorCode ierr; 3365 3366 PetscFunctionBegin; 3367 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3368 PetscValidHeaderSpecific(y,VEC_CLASSID,3); 3369 PetscValidHeaderSpecific(q,VEC_CLASSID,4); 3370 3371 ierr = PetscLogEventBegin(TS_FunctionEval,ts,y,q,0);CHKERRQ(ierr); 3372 if (ts->costintegrand) { 3373 PetscStackPush("TS user integrand in the cost function"); 3374 ierr = (*ts->costintegrand)(ts,t,y,q,ts->costintegrandctx);CHKERRQ(ierr); 3375 PetscStackPop; 3376 } else { 3377 ierr = VecZeroEntries(q);CHKERRQ(ierr); 3378 } 3379 3380 ierr = PetscLogEventEnd(TS_FunctionEval,ts,y,q,0);CHKERRQ(ierr); 3381 PetscFunctionReturn(0); 3382 } 3383 3384 /*@ 3385 TSAdjointComputeDRDYFunction - Runs the user-defined DRDY function. 3386 3387 Collective on TS 3388 3389 Input Parameters: 3390 . ts - The TS context obtained from TSCreate() 3391 3392 Notes: 3393 TSAdjointComputeDRDYFunction() is typically used for sensitivity implementation, 3394 so most users would not generally call this routine themselves. 3395 3396 Level: developer 3397 3398 .keywords: TS, sensitivity 3399 .seealso: TSAdjointComputeDRDYFunction() 3400 @*/ 3401 PetscErrorCode TSAdjointComputeDRDYFunction(TS ts,PetscReal t,Vec y,Vec *drdy) 3402 { 3403 PetscErrorCode ierr; 3404 3405 PetscFunctionBegin; 3406 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3407 PetscValidHeaderSpecific(y,VEC_CLASSID,3); 3408 3409 PetscStackPush("TS user DRDY function for sensitivity analysis"); 3410 ierr = (*ts->drdyfunction)(ts,t,y,drdy,ts->costintegrandctx); CHKERRQ(ierr); 3411 PetscStackPop; 3412 PetscFunctionReturn(0); 3413 } 3414 3415 /*@ 3416 TSAdjointComputeDRDPFunction - Runs the user-defined DRDP function. 3417 3418 Collective on TS 3419 3420 Input Parameters: 3421 . ts - The TS context obtained from TSCreate() 3422 3423 Notes: 3424 TSDRDPFunction() is typically used for sensitivity implementation, 3425 so most users would not generally call this routine themselves. 3426 3427 Level: developer 3428 3429 .keywords: TS, sensitivity 3430 .seealso: TSAdjointSetDRDPFunction() 3431 @*/ 3432 PetscErrorCode TSAdjointComputeDRDPFunction(TS ts,PetscReal t,Vec y,Vec *drdp) 3433 { 3434 PetscErrorCode ierr; 3435 3436 PetscFunctionBegin; 3437 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3438 PetscValidHeaderSpecific(y,VEC_CLASSID,3); 3439 3440 PetscStackPush("TS user DRDP function for sensitivity analysis"); 3441 ierr = (*ts->drdpfunction)(ts,t,y,drdp,ts->costintegrandctx); CHKERRQ(ierr); 3442 PetscStackPop; 3443 PetscFunctionReturn(0); 3444 } 3445 3446 /*@C 3447 TSSetPreStep - Sets the general-purpose function 3448 called once at the beginning of each time step. 3449 3450 Logically Collective on TS 3451 3452 Input Parameters: 3453 + ts - The TS context obtained from TSCreate() 3454 - func - The function 3455 3456 Calling sequence of func: 3457 . func (TS ts); 3458 3459 Level: intermediate 3460 3461 .keywords: TS, timestep 3462 .seealso: TSSetPreStage(), TSSetPostStage(), TSSetPostStep(), TSStep() 3463 @*/ 3464 PetscErrorCode TSSetPreStep(TS ts, PetscErrorCode (*func)(TS)) 3465 { 3466 PetscFunctionBegin; 3467 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3468 ts->prestep = func; 3469 PetscFunctionReturn(0); 3470 } 3471 3472 /*@ 3473 TSPreStep - Runs the user-defined pre-step function. 3474 3475 Collective on TS 3476 3477 Input Parameters: 3478 . ts - The TS context obtained from TSCreate() 3479 3480 Notes: 3481 TSPreStep() is typically used within time stepping implementations, 3482 so most users would not generally call this routine themselves. 3483 3484 Level: developer 3485 3486 .keywords: TS, timestep 3487 .seealso: TSSetPreStep(), TSPreStage(), TSPostStage(), TSPostStep() 3488 @*/ 3489 PetscErrorCode TSPreStep(TS ts) 3490 { 3491 PetscErrorCode ierr; 3492 3493 PetscFunctionBegin; 3494 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3495 if (ts->prestep) { 3496 PetscStackCallStandard((*ts->prestep),(ts)); 3497 } 3498 PetscFunctionReturn(0); 3499 } 3500 3501 /*@C 3502 TSSetPreStage - Sets the general-purpose function 3503 called once at the beginning of each stage. 3504 3505 Logically Collective on TS 3506 3507 Input Parameters: 3508 + ts - The TS context obtained from TSCreate() 3509 - func - The function 3510 3511 Calling sequence of func: 3512 . PetscErrorCode func(TS ts, PetscReal stagetime); 3513 3514 Level: intermediate 3515 3516 Note: 3517 There may be several stages per time step. If the solve for a given stage fails, the step may be rejected and retried. 3518 The time step number being computed can be queried using TSGetStepNumber() and the total size of the step being 3519 attempted can be obtained using TSGetTimeStep(). The time at the start of the step is available via TSGetTime(). 3520 3521 .keywords: TS, timestep 3522 .seealso: TSSetPostStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext() 3523 @*/ 3524 PetscErrorCode TSSetPreStage(TS ts, PetscErrorCode (*func)(TS,PetscReal)) 3525 { 3526 PetscFunctionBegin; 3527 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3528 ts->prestage = func; 3529 PetscFunctionReturn(0); 3530 } 3531 3532 /*@C 3533 TSSetPostStage - Sets the general-purpose function 3534 called once at the end of each stage. 3535 3536 Logically Collective on TS 3537 3538 Input Parameters: 3539 + ts - The TS context obtained from TSCreate() 3540 - func - The function 3541 3542 Calling sequence of func: 3543 . PetscErrorCode func(TS ts, PetscReal stagetime, PetscInt stageindex, Vec* Y); 3544 3545 Level: intermediate 3546 3547 Note: 3548 There may be several stages per time step. If the solve for a given stage fails, the step may be rejected and retried. 3549 The time step number being computed can be queried using TSGetStepNumber() and the total size of the step being 3550 attempted can be obtained using TSGetTimeStep(). The time at the start of the step is available via TSGetTime(). 3551 3552 .keywords: TS, timestep 3553 .seealso: TSSetPreStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext() 3554 @*/ 3555 PetscErrorCode TSSetPostStage(TS ts, PetscErrorCode (*func)(TS,PetscReal,PetscInt,Vec*)) 3556 { 3557 PetscFunctionBegin; 3558 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3559 ts->poststage = func; 3560 PetscFunctionReturn(0); 3561 } 3562 3563 /*@C 3564 TSSetPostEvaluate - Sets the general-purpose function 3565 called once at the end of each step evaluation. 3566 3567 Logically Collective on TS 3568 3569 Input Parameters: 3570 + ts - The TS context obtained from TSCreate() 3571 - func - The function 3572 3573 Calling sequence of func: 3574 . PetscErrorCode func(TS ts); 3575 3576 Level: intermediate 3577 3578 Note: 3579 Semantically, TSSetPostEvaluate() differs from TSSetPostStep() since the function it sets is called before event-handling 3580 thus guaranteeing the same solution (computed by the time-stepper) will be passed to it. On the other hand, TSPostStep() 3581 may be passed a different solution, possibly changed by the event handler. TSPostEvaluate() is called after the next step 3582 solution is evaluated allowing to modify it, if need be. The solution can be obtained with TSGetSolution(), the time step 3583 with TSGetTimeStep(), and the time at the start of the step is available via TSGetTime() 3584 3585 .keywords: TS, timestep 3586 .seealso: TSSetPreStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext() 3587 @*/ 3588 PetscErrorCode TSSetPostEvaluate(TS ts, PetscErrorCode (*func)(TS)) 3589 { 3590 PetscFunctionBegin; 3591 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3592 ts->postevaluate = func; 3593 PetscFunctionReturn(0); 3594 } 3595 3596 /*@ 3597 TSPreStage - Runs the user-defined pre-stage function set using TSSetPreStage() 3598 3599 Collective on TS 3600 3601 Input Parameters: 3602 . ts - The TS context obtained from TSCreate() 3603 stagetime - The absolute time of the current stage 3604 3605 Notes: 3606 TSPreStage() is typically used within time stepping implementations, 3607 most users would not generally call this routine themselves. 3608 3609 Level: developer 3610 3611 .keywords: TS, timestep 3612 .seealso: TSPostStage(), TSSetPreStep(), TSPreStep(), TSPostStep() 3613 @*/ 3614 PetscErrorCode TSPreStage(TS ts, PetscReal stagetime) 3615 { 3616 PetscErrorCode ierr; 3617 3618 PetscFunctionBegin; 3619 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3620 if (ts->prestage) { 3621 PetscStackCallStandard((*ts->prestage),(ts,stagetime)); 3622 } 3623 PetscFunctionReturn(0); 3624 } 3625 3626 /*@ 3627 TSPostStage - Runs the user-defined post-stage function set using TSSetPostStage() 3628 3629 Collective on TS 3630 3631 Input Parameters: 3632 . ts - The TS context obtained from TSCreate() 3633 stagetime - The absolute time of the current stage 3634 stageindex - Stage number 3635 Y - Array of vectors (of size = total number 3636 of stages) with the stage solutions 3637 3638 Notes: 3639 TSPostStage() is typically used within time stepping implementations, 3640 most users would not generally call this routine themselves. 3641 3642 Level: developer 3643 3644 .keywords: TS, timestep 3645 .seealso: TSPreStage(), TSSetPreStep(), TSPreStep(), TSPostStep() 3646 @*/ 3647 PetscErrorCode TSPostStage(TS ts, PetscReal stagetime, PetscInt stageindex, Vec *Y) 3648 { 3649 PetscErrorCode ierr; 3650 3651 PetscFunctionBegin; 3652 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3653 if (ts->poststage) { 3654 PetscStackCallStandard((*ts->poststage),(ts,stagetime,stageindex,Y)); 3655 } 3656 PetscFunctionReturn(0); 3657 } 3658 3659 /*@ 3660 TSPostEvaluate - Runs the user-defined post-evaluate function set using TSSetPostEvaluate() 3661 3662 Collective on TS 3663 3664 Input Parameters: 3665 . ts - The TS context obtained from TSCreate() 3666 3667 Notes: 3668 TSPostEvaluate() is typically used within time stepping implementations, 3669 most users would not generally call this routine themselves. 3670 3671 Level: developer 3672 3673 .keywords: TS, timestep 3674 .seealso: TSSetPostEvaluate(), TSSetPreStep(), TSPreStep(), TSPostStep() 3675 @*/ 3676 PetscErrorCode TSPostEvaluate(TS ts) 3677 { 3678 PetscErrorCode ierr; 3679 3680 PetscFunctionBegin; 3681 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3682 if (ts->postevaluate) { 3683 PetscStackCallStandard((*ts->postevaluate),(ts)); 3684 } 3685 PetscFunctionReturn(0); 3686 } 3687 3688 /*@C 3689 TSSetPostStep - Sets the general-purpose function 3690 called once at the end of each time step. 3691 3692 Logically Collective on TS 3693 3694 Input Parameters: 3695 + ts - The TS context obtained from TSCreate() 3696 - func - The function 3697 3698 Calling sequence of func: 3699 $ func (TS ts); 3700 3701 Notes: 3702 The function set by TSSetPostStep() is called after each successful step. The solution vector X 3703 obtained by TSGetSolution() may be different than that computed at the step end if the event handler 3704 locates an event and TSPostEvent() modifies it. Use TSSetPostEvaluate() if an unmodified solution is needed instead. 3705 3706 Level: intermediate 3707 3708 .keywords: TS, timestep 3709 .seealso: TSSetPreStep(), TSSetPreStage(), TSSetPostEvaluate(), TSGetTimeStep(), TSGetStepNumber(), TSGetTime() 3710 @*/ 3711 PetscErrorCode TSSetPostStep(TS ts, PetscErrorCode (*func)(TS)) 3712 { 3713 PetscFunctionBegin; 3714 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3715 ts->poststep = func; 3716 PetscFunctionReturn(0); 3717 } 3718 3719 /*@ 3720 TSPostStep - Runs the user-defined post-step function. 3721 3722 Collective on TS 3723 3724 Input Parameters: 3725 . ts - The TS context obtained from TSCreate() 3726 3727 Notes: 3728 TSPostStep() is typically used within time stepping implementations, 3729 so most users would not generally call this routine themselves. 3730 3731 Level: developer 3732 3733 .keywords: TS, timestep 3734 @*/ 3735 PetscErrorCode TSPostStep(TS ts) 3736 { 3737 PetscErrorCode ierr; 3738 3739 PetscFunctionBegin; 3740 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3741 if (ts->poststep) { 3742 PetscStackCallStandard((*ts->poststep),(ts)); 3743 } 3744 PetscFunctionReturn(0); 3745 } 3746 3747 /* ------------ Routines to set performance monitoring options ----------- */ 3748 3749 /*@C 3750 TSMonitorSet - Sets an ADDITIONAL function that is to be used at every 3751 timestep to display the iteration's progress. 3752 3753 Logically Collective on TS 3754 3755 Input Parameters: 3756 + ts - the TS context obtained from TSCreate() 3757 . monitor - monitoring routine 3758 . mctx - [optional] user-defined context for private data for the 3759 monitor routine (use NULL if no context is desired) 3760 - monitordestroy - [optional] routine that frees monitor context 3761 (may be NULL) 3762 3763 Calling sequence of monitor: 3764 $ int monitor(TS ts,PetscInt steps,PetscReal time,Vec u,void *mctx) 3765 3766 + ts - the TS context 3767 . 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) 3768 . time - current time 3769 . u - current iterate 3770 - mctx - [optional] monitoring context 3771 3772 Notes: 3773 This routine adds an additional monitor to the list of monitors that 3774 already has been loaded. 3775 3776 Fortran notes: Only a single monitor function can be set for each TS object 3777 3778 Level: intermediate 3779 3780 .keywords: TS, timestep, set, monitor 3781 3782 .seealso: TSMonitorDefault(), TSMonitorCancel() 3783 @*/ 3784 PetscErrorCode TSMonitorSet(TS ts,PetscErrorCode (*monitor)(TS,PetscInt,PetscReal,Vec,void*),void *mctx,PetscErrorCode (*mdestroy)(void**)) 3785 { 3786 PetscErrorCode ierr; 3787 PetscInt i; 3788 PetscBool identical; 3789 3790 PetscFunctionBegin; 3791 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3792 for (i=0; i<ts->numbermonitors;i++) { 3793 ierr = PetscMonitorCompare((PetscErrorCode (*)(void))monitor,mctx,mdestroy,(PetscErrorCode (*)(void))ts->monitor[i],ts->monitorcontext[i],ts->monitordestroy[i],&identical);CHKERRQ(ierr); 3794 if (identical) PetscFunctionReturn(0); 3795 } 3796 if (ts->numbermonitors >= MAXTSMONITORS) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Too many monitors set"); 3797 ts->monitor[ts->numbermonitors] = monitor; 3798 ts->monitordestroy[ts->numbermonitors] = mdestroy; 3799 ts->monitorcontext[ts->numbermonitors++] = (void*)mctx; 3800 PetscFunctionReturn(0); 3801 } 3802 3803 /*@C 3804 TSMonitorCancel - Clears all the monitors that have been set on a time-step object. 3805 3806 Logically Collective on TS 3807 3808 Input Parameters: 3809 . ts - the TS context obtained from TSCreate() 3810 3811 Notes: 3812 There is no way to remove a single, specific monitor. 3813 3814 Level: intermediate 3815 3816 .keywords: TS, timestep, set, monitor 3817 3818 .seealso: TSMonitorDefault(), TSMonitorSet() 3819 @*/ 3820 PetscErrorCode TSMonitorCancel(TS ts) 3821 { 3822 PetscErrorCode ierr; 3823 PetscInt i; 3824 3825 PetscFunctionBegin; 3826 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3827 for (i=0; i<ts->numbermonitors; i++) { 3828 if (ts->monitordestroy[i]) { 3829 ierr = (*ts->monitordestroy[i])(&ts->monitorcontext[i]);CHKERRQ(ierr); 3830 } 3831 } 3832 ts->numbermonitors = 0; 3833 PetscFunctionReturn(0); 3834 } 3835 3836 /*@C 3837 TSMonitorDefault - The Default monitor, prints the timestep and time for each step 3838 3839 Level: intermediate 3840 3841 .keywords: TS, set, monitor 3842 3843 .seealso: TSMonitorSet() 3844 @*/ 3845 PetscErrorCode TSMonitorDefault(TS ts,PetscInt step,PetscReal ptime,Vec v,PetscViewerAndFormat *vf) 3846 { 3847 PetscErrorCode ierr; 3848 PetscViewer viewer = vf->viewer; 3849 PetscBool iascii,ibinary; 3850 3851 PetscFunctionBegin; 3852 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,4); 3853 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 3854 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&ibinary);CHKERRQ(ierr); 3855 ierr = PetscViewerPushFormat(viewer,vf->format);CHKERRQ(ierr); 3856 if (iascii) { 3857 ierr = PetscViewerASCIIAddTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 3858 if (step == -1){ /* this indicates it is an interpolated solution */ 3859 ierr = PetscViewerASCIIPrintf(viewer,"Interpolated solution at time %g between steps %D and %D\n",(double)ptime,ts->steps-1,ts->steps);CHKERRQ(ierr); 3860 } else { 3861 ierr = PetscViewerASCIIPrintf(viewer,"%D TS dt %g time %g%s",step,(double)ts->time_step,(double)ptime,ts->steprollback ? " (r)\n" : "\n");CHKERRQ(ierr); 3862 } 3863 ierr = PetscViewerASCIISubtractTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 3864 } else if (ibinary) { 3865 PetscMPIInt rank; 3866 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)viewer),&rank);CHKERRQ(ierr); 3867 if (!rank) { 3868 PetscBool skipHeader; 3869 PetscInt classid = REAL_FILE_CLASSID; 3870 3871 ierr = PetscViewerBinaryGetSkipHeader(viewer,&skipHeader);CHKERRQ(ierr); 3872 if (!skipHeader) { 3873 ierr = PetscViewerBinaryWrite(viewer,&classid,1,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); 3874 } 3875 ierr = PetscRealView(1,&ptime,viewer);CHKERRQ(ierr); 3876 } else { 3877 ierr = PetscRealView(0,&ptime,viewer);CHKERRQ(ierr); 3878 } 3879 } 3880 ierr = PetscViewerPopFormat(viewer);CHKERRQ(ierr); 3881 PetscFunctionReturn(0); 3882 } 3883 3884 /*@C 3885 TSAdjointMonitorSet - Sets an ADDITIONAL function that is to be used at every 3886 timestep to display the iteration's progress. 3887 3888 Logically Collective on TS 3889 3890 Input Parameters: 3891 + ts - the TS context obtained from TSCreate() 3892 . adjointmonitor - monitoring routine 3893 . adjointmctx - [optional] user-defined context for private data for the 3894 monitor routine (use NULL if no context is desired) 3895 - adjointmonitordestroy - [optional] routine that frees monitor context 3896 (may be NULL) 3897 3898 Calling sequence of monitor: 3899 $ int adjointmonitor(TS ts,PetscInt steps,PetscReal time,Vec u,PetscInt numcost,Vec *lambda, Vec *mu,void *adjointmctx) 3900 3901 + ts - the TS context 3902 . 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 3903 been interpolated to) 3904 . time - current time 3905 . u - current iterate 3906 . numcost - number of cost functionos 3907 . lambda - sensitivities to initial conditions 3908 . mu - sensitivities to parameters 3909 - adjointmctx - [optional] adjoint monitoring context 3910 3911 Notes: 3912 This routine adds an additional monitor to the list of monitors that 3913 already has been loaded. 3914 3915 Fortran notes: Only a single monitor function can be set for each TS object 3916 3917 Level: intermediate 3918 3919 .keywords: TS, timestep, set, adjoint, monitor 3920 3921 .seealso: TSAdjointMonitorCancel() 3922 @*/ 3923 PetscErrorCode TSAdjointMonitorSet(TS ts,PetscErrorCode (*adjointmonitor)(TS,PetscInt,PetscReal,Vec,PetscInt,Vec*,Vec*,void*),void *adjointmctx,PetscErrorCode (*adjointmdestroy)(void**)) 3924 { 3925 PetscErrorCode ierr; 3926 PetscInt i; 3927 PetscBool identical; 3928 3929 PetscFunctionBegin; 3930 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3931 for (i=0; i<ts->numbermonitors;i++) { 3932 ierr = PetscMonitorCompare((PetscErrorCode (*)(void))adjointmonitor,adjointmctx,adjointmdestroy,(PetscErrorCode (*)(void))ts->adjointmonitor[i],ts->adjointmonitorcontext[i],ts->adjointmonitordestroy[i],&identical);CHKERRQ(ierr); 3933 if (identical) PetscFunctionReturn(0); 3934 } 3935 if (ts->numberadjointmonitors >= MAXTSMONITORS) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Too many adjoint monitors set"); 3936 ts->adjointmonitor[ts->numberadjointmonitors] = adjointmonitor; 3937 ts->adjointmonitordestroy[ts->numberadjointmonitors] = adjointmdestroy; 3938 ts->adjointmonitorcontext[ts->numberadjointmonitors++] = (void*)adjointmctx; 3939 PetscFunctionReturn(0); 3940 } 3941 3942 /*@C 3943 TSAdjointMonitorCancel - Clears all the adjoint monitors that have been set on a time-step object. 3944 3945 Logically Collective on TS 3946 3947 Input Parameters: 3948 . ts - the TS context obtained from TSCreate() 3949 3950 Notes: 3951 There is no way to remove a single, specific monitor. 3952 3953 Level: intermediate 3954 3955 .keywords: TS, timestep, set, adjoint, monitor 3956 3957 .seealso: TSAdjointMonitorSet() 3958 @*/ 3959 PetscErrorCode TSAdjointMonitorCancel(TS ts) 3960 { 3961 PetscErrorCode ierr; 3962 PetscInt i; 3963 3964 PetscFunctionBegin; 3965 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3966 for (i=0; i<ts->numberadjointmonitors; i++) { 3967 if (ts->adjointmonitordestroy[i]) { 3968 ierr = (*ts->adjointmonitordestroy[i])(&ts->adjointmonitorcontext[i]);CHKERRQ(ierr); 3969 } 3970 } 3971 ts->numberadjointmonitors = 0; 3972 PetscFunctionReturn(0); 3973 } 3974 3975 /*@C 3976 TSAdjointMonitorDefault - the default monitor of adjoint computations 3977 3978 Level: intermediate 3979 3980 .keywords: TS, set, monitor 3981 3982 .seealso: TSAdjointMonitorSet() 3983 @*/ 3984 PetscErrorCode TSAdjointMonitorDefault(TS ts,PetscInt step,PetscReal ptime,Vec v,PetscInt numcost,Vec *lambda,Vec *mu,PetscViewerAndFormat *vf) 3985 { 3986 PetscErrorCode ierr; 3987 PetscViewer viewer = vf->viewer; 3988 3989 PetscFunctionBegin; 3990 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,4); 3991 ierr = PetscViewerPushFormat(viewer,vf->format);CHKERRQ(ierr); 3992 ierr = PetscViewerASCIIAddTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 3993 ierr = PetscViewerASCIIPrintf(viewer,"%D TS dt %g time %g%s",step,(double)ts->time_step,(double)ptime,ts->steprollback ? " (r)\n" : "\n");CHKERRQ(ierr); 3994 ierr = PetscViewerASCIISubtractTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 3995 ierr = PetscViewerPopFormat(viewer);CHKERRQ(ierr); 3996 PetscFunctionReturn(0); 3997 } 3998 3999 /*@ 4000 TSInterpolate - Interpolate the solution computed during the previous step to an arbitrary location in the interval 4001 4002 Collective on TS 4003 4004 Input Argument: 4005 + ts - time stepping context 4006 - t - time to interpolate to 4007 4008 Output Argument: 4009 . U - state at given time 4010 4011 Level: intermediate 4012 4013 Developer Notes: 4014 TSInterpolate() and the storing of previous steps/stages should be generalized to support delay differential equations and continuous adjoints. 4015 4016 .keywords: TS, set 4017 4018 .seealso: TSSetExactFinalTime(), TSSolve() 4019 @*/ 4020 PetscErrorCode TSInterpolate(TS ts,PetscReal t,Vec U) 4021 { 4022 PetscErrorCode ierr; 4023 4024 PetscFunctionBegin; 4025 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4026 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 4027 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); 4028 if (!ts->ops->interpolate) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"%s does not provide interpolation",((PetscObject)ts)->type_name); 4029 ierr = (*ts->ops->interpolate)(ts,t,U);CHKERRQ(ierr); 4030 PetscFunctionReturn(0); 4031 } 4032 4033 /*@ 4034 TSStep - Steps one time step 4035 4036 Collective on TS 4037 4038 Input Parameter: 4039 . ts - the TS context obtained from TSCreate() 4040 4041 Level: developer 4042 4043 Notes: 4044 The public interface for the ODE/DAE solvers is TSSolve(), you should almost for sure be using that routine and not this routine. 4045 4046 The hook set using TSSetPreStep() is called before each attempt to take the step. In general, the time step size may 4047 be changed due to adaptive error controller or solve failures. Note that steps may contain multiple stages. 4048 4049 This may over-step the final time provided in TSSetMaxTime() depending on the time-step used. TSSolve() interpolates to exactly the 4050 time provided in TSSetMaxTime(). One can use TSInterpolate() to determine an interpolated solution within the final timestep. 4051 4052 .keywords: TS, timestep, solve 4053 4054 .seealso: TSCreate(), TSSetUp(), TSDestroy(), TSSolve(), TSSetPreStep(), TSSetPreStage(), TSSetPostStage(), TSInterpolate() 4055 @*/ 4056 PetscErrorCode TSStep(TS ts) 4057 { 4058 PetscErrorCode ierr; 4059 static PetscBool cite = PETSC_FALSE; 4060 PetscReal ptime; 4061 4062 PetscFunctionBegin; 4063 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4064 ierr = PetscCitationsRegister("@techreport{tspaper,\n" 4065 " title = {{PETSc/TS}: A Modern Scalable {DAE/ODE} Solver Library},\n" 4066 " author = {Shrirang Abhyankar and Jed Brown and Emil Constantinescu and Debojyoti Ghosh and Barry F. Smith},\n" 4067 " type = {Preprint},\n" 4068 " number = {ANL/MCS-P5061-0114},\n" 4069 " institution = {Argonne National Laboratory},\n" 4070 " year = {2014}\n}\n",&cite);CHKERRQ(ierr); 4071 4072 ierr = TSSetUp(ts);CHKERRQ(ierr); 4073 ierr = TSTrajectorySetUp(ts->trajectory,ts);CHKERRQ(ierr); 4074 4075 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>"); 4076 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()"); 4077 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"); 4078 4079 if (!ts->steps) ts->ptime_prev = ts->ptime; 4080 ptime = ts->ptime; ts->ptime_prev_rollback = ts->ptime_prev; 4081 ts->reason = TS_CONVERGED_ITERATING; 4082 if (!ts->ops->step) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSStep not implemented for type '%s'",((PetscObject)ts)->type_name); 4083 ierr = PetscLogEventBegin(TS_Step,ts,0,0,0);CHKERRQ(ierr); 4084 ierr = (*ts->ops->step)(ts);CHKERRQ(ierr); 4085 ierr = PetscLogEventEnd(TS_Step,ts,0,0,0);CHKERRQ(ierr); 4086 ts->ptime_prev = ptime; 4087 ts->steps++; 4088 ts->steprollback = PETSC_FALSE; 4089 ts->steprestart = PETSC_FALSE; 4090 4091 if (ts->reason < 0) { 4092 if (ts->errorifstepfailed) { 4093 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]); 4094 else SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s",TSConvergedReasons[ts->reason]); 4095 } 4096 } else if (!ts->reason) { 4097 if (ts->steps >= ts->max_steps) ts->reason = TS_CONVERGED_ITS; 4098 else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME; 4099 } 4100 PetscFunctionReturn(0); 4101 } 4102 4103 /*@ 4104 TSAdjointStep - Steps one time step backward in the adjoint run 4105 4106 Collective on TS 4107 4108 Input Parameter: 4109 . ts - the TS context obtained from TSCreate() 4110 4111 Level: intermediate 4112 4113 .keywords: TS, adjoint, step 4114 4115 .seealso: TSAdjointSetUp(), TSAdjointSolve() 4116 @*/ 4117 PetscErrorCode TSAdjointStep(TS ts) 4118 { 4119 DM dm; 4120 PetscErrorCode ierr; 4121 4122 PetscFunctionBegin; 4123 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4124 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 4125 ierr = TSAdjointSetUp(ts);CHKERRQ(ierr); 4126 4127 ierr = VecViewFromOptions(ts->vec_sol,(PetscObject)ts,"-ts_view_solution");CHKERRQ(ierr); 4128 4129 ts->reason = TS_CONVERGED_ITERATING; 4130 ts->ptime_prev = ts->ptime; 4131 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); 4132 ierr = PetscLogEventBegin(TS_AdjointStep,ts,0,0,0);CHKERRQ(ierr); 4133 ierr = (*ts->ops->adjointstep)(ts);CHKERRQ(ierr); 4134 ierr = PetscLogEventEnd(TS_AdjointStep,ts,0,0,0);CHKERRQ(ierr); 4135 ts->adjoint_steps++; ts->steps--; 4136 4137 if (ts->reason < 0) { 4138 if (ts->errorifstepfailed) { 4139 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]); 4140 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]); 4141 else SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s",TSConvergedReasons[ts->reason]); 4142 } 4143 } else if (!ts->reason) { 4144 if (ts->adjoint_steps >= ts->adjoint_max_steps) ts->reason = TS_CONVERGED_ITS; 4145 } 4146 PetscFunctionReturn(0); 4147 } 4148 4149 /*@ 4150 TSEvaluateWLTE - Evaluate the weighted local truncation error norm 4151 at the end of a time step with a given order of accuracy. 4152 4153 Collective on TS 4154 4155 Input Arguments: 4156 + ts - time stepping context 4157 . wnormtype - norm type, either NORM_2 or NORM_INFINITY 4158 - order - optional, desired order for the error evaluation or PETSC_DECIDE 4159 4160 Output Arguments: 4161 + order - optional, the actual order of the error evaluation 4162 - wlte - the weighted local truncation error norm 4163 4164 Level: advanced 4165 4166 Notes: 4167 If the timestepper cannot evaluate the error in a particular step 4168 (eg. in the first step or restart steps after event handling), 4169 this routine returns wlte=-1.0 . 4170 4171 .seealso: TSStep(), TSAdapt, TSErrorWeightedNorm() 4172 @*/ 4173 PetscErrorCode TSEvaluateWLTE(TS ts,NormType wnormtype,PetscInt *order,PetscReal *wlte) 4174 { 4175 PetscErrorCode ierr; 4176 4177 PetscFunctionBegin; 4178 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4179 PetscValidType(ts,1); 4180 PetscValidLogicalCollectiveEnum(ts,wnormtype,4); 4181 if (order) PetscValidIntPointer(order,3); 4182 if (order) PetscValidLogicalCollectiveInt(ts,*order,3); 4183 PetscValidRealPointer(wlte,4); 4184 if (wnormtype != NORM_2 && wnormtype != NORM_INFINITY) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]); 4185 if (!ts->ops->evaluatewlte) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSEvaluateWLTE not implemented for type '%s'",((PetscObject)ts)->type_name); 4186 ierr = (*ts->ops->evaluatewlte)(ts,wnormtype,order,wlte);CHKERRQ(ierr); 4187 PetscFunctionReturn(0); 4188 } 4189 4190 /*@ 4191 TSEvaluateStep - Evaluate the solution at the end of a time step with a given order of accuracy. 4192 4193 Collective on TS 4194 4195 Input Arguments: 4196 + ts - time stepping context 4197 . order - desired order of accuracy 4198 - done - whether the step was evaluated at this order (pass NULL to generate an error if not available) 4199 4200 Output Arguments: 4201 . U - state at the end of the current step 4202 4203 Level: advanced 4204 4205 Notes: 4206 This function cannot be called until all stages have been evaluated. 4207 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. 4208 4209 .seealso: TSStep(), TSAdapt 4210 @*/ 4211 PetscErrorCode TSEvaluateStep(TS ts,PetscInt order,Vec U,PetscBool *done) 4212 { 4213 PetscErrorCode ierr; 4214 4215 PetscFunctionBegin; 4216 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4217 PetscValidType(ts,1); 4218 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 4219 if (!ts->ops->evaluatestep) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSEvaluateStep not implemented for type '%s'",((PetscObject)ts)->type_name); 4220 ierr = (*ts->ops->evaluatestep)(ts,order,U,done);CHKERRQ(ierr); 4221 PetscFunctionReturn(0); 4222 } 4223 4224 /*@ 4225 TSForwardCostIntegral - Evaluate the cost integral in the forward run. 4226 4227 Collective on TS 4228 4229 Input Arguments: 4230 . ts - time stepping context 4231 4232 Level: advanced 4233 4234 Notes: 4235 This function cannot be called until TSStep() has been completed. 4236 4237 .seealso: TSSolve(), TSAdjointCostIntegral() 4238 @*/ 4239 PetscErrorCode TSForwardCostIntegral(TS ts) 4240 { 4241 PetscErrorCode ierr; 4242 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4243 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); 4244 ierr = (*ts->ops->forwardintegral)(ts);CHKERRQ(ierr); 4245 PetscFunctionReturn(0); 4246 } 4247 4248 /*@ 4249 TSSolve - Steps the requested number of timesteps. 4250 4251 Collective on TS 4252 4253 Input Parameter: 4254 + ts - the TS context obtained from TSCreate() 4255 - u - the solution vector (can be null if TSSetSolution() was used and TSSetExactFinalTime(ts,TS_EXACTFINALTIME_MATCHSTEP) was not used, 4256 otherwise must contain the initial conditions and will contain the solution at the final requested time 4257 4258 Level: beginner 4259 4260 Notes: 4261 The final time returned by this function may be different from the time of the internally 4262 held state accessible by TSGetSolution() and TSGetTime() because the method may have 4263 stepped over the final time. 4264 4265 .keywords: TS, timestep, solve 4266 4267 .seealso: TSCreate(), TSSetSolution(), TSStep(), TSGetTime(), TSGetSolveTime() 4268 @*/ 4269 PetscErrorCode TSSolve(TS ts,Vec u) 4270 { 4271 Vec solution; 4272 PetscErrorCode ierr; 4273 4274 PetscFunctionBegin; 4275 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4276 if (u) PetscValidHeaderSpecific(u,VEC_CLASSID,2); 4277 4278 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 */ 4279 PetscValidHeaderSpecific(u,VEC_CLASSID,2); 4280 if (!ts->vec_sol || u == ts->vec_sol) { 4281 ierr = VecDuplicate(u,&solution);CHKERRQ(ierr); 4282 ierr = TSSetSolution(ts,solution);CHKERRQ(ierr); 4283 ierr = VecDestroy(&solution);CHKERRQ(ierr); /* grant ownership */ 4284 } 4285 ierr = VecCopy(u,ts->vec_sol);CHKERRQ(ierr); 4286 if (ts->forward_solve) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Sensitivity analysis does not support the mode TS_EXACTFINALTIME_INTERPOLATE"); 4287 } else if (u) { 4288 ierr = TSSetSolution(ts,u);CHKERRQ(ierr); 4289 } 4290 ierr = TSSetUp(ts);CHKERRQ(ierr); 4291 ierr = TSTrajectorySetUp(ts->trajectory,ts);CHKERRQ(ierr); 4292 4293 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>"); 4294 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()"); 4295 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"); 4296 4297 if (ts->forward_solve) { 4298 ierr = TSForwardSetUp(ts);CHKERRQ(ierr); 4299 } 4300 4301 /* reset number of steps only when the step is not restarted. ARKIMEX 4302 restarts the step after an event. Resetting these counters in such case causes 4303 TSTrajectory to incorrectly save the output files 4304 */ 4305 /* reset time step and iteration counters */ 4306 4307 if (!ts->steps) { 4308 ts->ksp_its = 0; 4309 ts->snes_its = 0; 4310 ts->num_snes_failures = 0; 4311 ts->reject = 0; 4312 ts->steprestart = PETSC_TRUE; 4313 ts->steprollback = PETSC_FALSE; 4314 } 4315 ts->reason = TS_CONVERGED_ITERATING; 4316 4317 ierr = TSViewFromOptions(ts,NULL,"-ts_view_pre");CHKERRQ(ierr); 4318 4319 if (ts->ops->solve) { /* This private interface is transitional and should be removed when all implementations are updated. */ 4320 ierr = (*ts->ops->solve)(ts);CHKERRQ(ierr); 4321 if (u) {ierr = VecCopy(ts->vec_sol,u);CHKERRQ(ierr);} 4322 ts->solvetime = ts->ptime; 4323 solution = ts->vec_sol; 4324 } else { /* Step the requested number of timesteps. */ 4325 if (ts->steps >= ts->max_steps) ts->reason = TS_CONVERGED_ITS; 4326 else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME; 4327 4328 if (!ts->steps) { 4329 ierr = TSTrajectorySet(ts->trajectory,ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 4330 ierr = TSEventInitialize(ts->event,ts,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 4331 } 4332 4333 while (!ts->reason) { 4334 ierr = TSMonitor(ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 4335 if (!ts->steprollback) { 4336 ierr = TSPreStep(ts);CHKERRQ(ierr); 4337 } 4338 ierr = TSStep(ts);CHKERRQ(ierr); 4339 if (ts->vec_costintegral && ts->costintegralfwd) { /* Must evaluate the cost integral before event is handled. The cost integral value can also be rolled back. */ 4340 ierr = TSForwardCostIntegral(ts);CHKERRQ(ierr); 4341 } 4342 if (!ts->steprollback && ts->forward_solve) { /* compute forward sensitivities before event handling because postevent() may change RHS and jump conditions may have to be applied */ 4343 ierr = TSForwardStep(ts);CHKERRQ(ierr); 4344 } 4345 ierr = TSPostEvaluate(ts);CHKERRQ(ierr); 4346 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. */ 4347 if (!ts->steprollback) { 4348 ierr = TSTrajectorySet(ts->trajectory,ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 4349 ierr = TSPostStep(ts);CHKERRQ(ierr); 4350 } 4351 } 4352 ierr = TSMonitor(ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 4353 4354 if (ts->exact_final_time == TS_EXACTFINALTIME_INTERPOLATE && ts->ptime > ts->max_time) { 4355 ierr = TSInterpolate(ts,ts->max_time,u);CHKERRQ(ierr); 4356 ts->solvetime = ts->max_time; 4357 solution = u; 4358 ierr = TSMonitor(ts,-1,ts->solvetime,solution);CHKERRQ(ierr); 4359 } else { 4360 if (u) {ierr = VecCopy(ts->vec_sol,u);CHKERRQ(ierr);} 4361 ts->solvetime = ts->ptime; 4362 solution = ts->vec_sol; 4363 } 4364 } 4365 4366 ierr = TSViewFromOptions(ts,NULL,"-ts_view");CHKERRQ(ierr); 4367 ierr = VecViewFromOptions(solution,NULL,"-ts_view_solution");CHKERRQ(ierr); 4368 ierr = PetscObjectSAWsBlock((PetscObject)ts);CHKERRQ(ierr); 4369 if (ts->adjoint_solve) { 4370 ierr = TSAdjointSolve(ts);CHKERRQ(ierr); 4371 } 4372 PetscFunctionReturn(0); 4373 } 4374 4375 /*@ 4376 TSAdjointCostIntegral - Evaluate the cost integral in the adjoint run. 4377 4378 Collective on TS 4379 4380 Input Arguments: 4381 . ts - time stepping context 4382 4383 Level: advanced 4384 4385 Notes: 4386 This function cannot be called until TSAdjointStep() has been completed. 4387 4388 .seealso: TSAdjointSolve(), TSAdjointStep 4389 @*/ 4390 PetscErrorCode TSAdjointCostIntegral(TS ts) 4391 { 4392 PetscErrorCode ierr; 4393 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4394 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); 4395 ierr = (*ts->ops->adjointintegral)(ts);CHKERRQ(ierr); 4396 PetscFunctionReturn(0); 4397 } 4398 4399 /*@ 4400 TSAdjointSolve - Solves the discrete ajoint problem for an ODE/DAE 4401 4402 Collective on TS 4403 4404 Input Parameter: 4405 . ts - the TS context obtained from TSCreate() 4406 4407 Options Database: 4408 . -ts_adjoint_view_solution <viewerinfo> - views the first gradient with respect to the initial values 4409 4410 Level: intermediate 4411 4412 Notes: 4413 This must be called after a call to TSSolve() that solves the forward problem 4414 4415 By default this will integrate back to the initial time, one can use TSAdjointSetSteps() to step back to a later time 4416 4417 .keywords: TS, timestep, solve 4418 4419 .seealso: TSCreate(), TSSetCostGradients(), TSSetSolution(), TSAdjointStep() 4420 @*/ 4421 PetscErrorCode TSAdjointSolve(TS ts) 4422 { 4423 PetscErrorCode ierr; 4424 4425 PetscFunctionBegin; 4426 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4427 ierr = TSAdjointSetUp(ts);CHKERRQ(ierr); 4428 4429 /* reset time step and iteration counters */ 4430 ts->adjoint_steps = 0; 4431 ts->ksp_its = 0; 4432 ts->snes_its = 0; 4433 ts->num_snes_failures = 0; 4434 ts->reject = 0; 4435 ts->reason = TS_CONVERGED_ITERATING; 4436 4437 if (!ts->adjoint_max_steps) ts->adjoint_max_steps = ts->steps; 4438 if (ts->adjoint_steps >= ts->adjoint_max_steps) ts->reason = TS_CONVERGED_ITS; 4439 4440 while (!ts->reason) { 4441 ierr = TSTrajectoryGet(ts->trajectory,ts,ts->steps,&ts->ptime);CHKERRQ(ierr); 4442 ierr = TSAdjointMonitor(ts,ts->steps,ts->ptime,ts->vec_sol,ts->numcost,ts->vecs_sensi,ts->vecs_sensip);CHKERRQ(ierr); 4443 ierr = TSAdjointEventHandler(ts);CHKERRQ(ierr); 4444 ierr = TSAdjointStep(ts);CHKERRQ(ierr); 4445 if (ts->vec_costintegral && !ts->costintegralfwd) { 4446 ierr = TSAdjointCostIntegral(ts);CHKERRQ(ierr); 4447 } 4448 } 4449 ierr = TSTrajectoryGet(ts->trajectory,ts,ts->steps,&ts->ptime);CHKERRQ(ierr); 4450 ierr = TSAdjointMonitor(ts,ts->steps,ts->ptime,ts->vec_sol,ts->numcost,ts->vecs_sensi,ts->vecs_sensip);CHKERRQ(ierr); 4451 ts->solvetime = ts->ptime; 4452 ierr = TSTrajectoryViewFromOptions(ts->trajectory,NULL,"-ts_trajectory_view");CHKERRQ(ierr); 4453 ierr = VecViewFromOptions(ts->vecs_sensi[0],(PetscObject) ts, "-ts_adjoint_view_solution");CHKERRQ(ierr); 4454 PetscFunctionReturn(0); 4455 } 4456 4457 /*@C 4458 TSMonitor - Runs all user-provided monitor routines set using TSMonitorSet() 4459 4460 Collective on TS 4461 4462 Input Parameters: 4463 + ts - time stepping context obtained from TSCreate() 4464 . step - step number that has just completed 4465 . ptime - model time of the state 4466 - u - state at the current model time 4467 4468 Notes: 4469 TSMonitor() is typically used automatically within the time stepping implementations. 4470 Users would almost never call this routine directly. 4471 4472 A step of -1 indicates that the monitor is being called on a solution obtained by interpolating from computed solutions 4473 4474 Level: developer 4475 4476 .keywords: TS, timestep 4477 @*/ 4478 PetscErrorCode TSMonitor(TS ts,PetscInt step,PetscReal ptime,Vec u) 4479 { 4480 DM dm; 4481 PetscInt i,n = ts->numbermonitors; 4482 PetscErrorCode ierr; 4483 4484 PetscFunctionBegin; 4485 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4486 PetscValidHeaderSpecific(u,VEC_CLASSID,4); 4487 4488 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 4489 ierr = DMSetOutputSequenceNumber(dm,step,ptime);CHKERRQ(ierr); 4490 4491 ierr = VecLockPush(u);CHKERRQ(ierr); 4492 for (i=0; i<n; i++) { 4493 ierr = (*ts->monitor[i])(ts,step,ptime,u,ts->monitorcontext[i]);CHKERRQ(ierr); 4494 } 4495 ierr = VecLockPop(u);CHKERRQ(ierr); 4496 PetscFunctionReturn(0); 4497 } 4498 4499 /*@C 4500 TSAdjointMonitor - Runs all user-provided adjoint monitor routines set using TSAdjointMonitorSet() 4501 4502 Collective on TS 4503 4504 Input Parameters: 4505 + ts - time stepping context obtained from TSCreate() 4506 . step - step number that has just completed 4507 . ptime - model time of the state 4508 . u - state at the current model time 4509 . numcost - number of cost functions (dimension of lambda or mu) 4510 . lambda - vectors containing the gradients of the cost functions with respect to the ODE/DAE solution variables 4511 - mu - vectors containing the gradients of the cost functions with respect to the problem parameters 4512 4513 Notes: 4514 TSAdjointMonitor() is typically used automatically within the time stepping implementations. 4515 Users would almost never call this routine directly. 4516 4517 Level: developer 4518 4519 .keywords: TS, timestep 4520 @*/ 4521 PetscErrorCode TSAdjointMonitor(TS ts,PetscInt step,PetscReal ptime,Vec u,PetscInt numcost,Vec *lambda, Vec *mu) 4522 { 4523 PetscErrorCode ierr; 4524 PetscInt i,n = ts->numberadjointmonitors; 4525 4526 PetscFunctionBegin; 4527 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4528 PetscValidHeaderSpecific(u,VEC_CLASSID,4); 4529 ierr = VecLockPush(u);CHKERRQ(ierr); 4530 for (i=0; i<n; i++) { 4531 ierr = (*ts->adjointmonitor[i])(ts,step,ptime,u,numcost,lambda,mu,ts->adjointmonitorcontext[i]);CHKERRQ(ierr); 4532 } 4533 ierr = VecLockPop(u);CHKERRQ(ierr); 4534 PetscFunctionReturn(0); 4535 } 4536 4537 /* ------------------------------------------------------------------------*/ 4538 /*@C 4539 TSMonitorLGCtxCreate - Creates a TSMonitorLGCtx context for use with 4540 TS to monitor the solution process graphically in various ways 4541 4542 Collective on TS 4543 4544 Input Parameters: 4545 + host - the X display to open, or null for the local machine 4546 . label - the title to put in the title bar 4547 . x, y - the screen coordinates of the upper left coordinate of the window 4548 . m, n - the screen width and height in pixels 4549 - howoften - if positive then determines the frequency of the plotting, if -1 then only at the final time 4550 4551 Output Parameter: 4552 . ctx - the context 4553 4554 Options Database Key: 4555 + -ts_monitor_lg_timestep - automatically sets line graph monitor 4556 + -ts_monitor_lg_timestep_log - automatically sets line graph monitor 4557 . -ts_monitor_lg_solution - monitor the solution (or certain values of the solution by calling TSMonitorLGSetDisplayVariables() or TSMonitorLGCtxSetDisplayVariables()) 4558 . -ts_monitor_lg_error - monitor the error 4559 . -ts_monitor_lg_ksp_iterations - monitor the number of KSP iterations needed for each timestep 4560 . -ts_monitor_lg_snes_iterations - monitor the number of SNES iterations needed for each timestep 4561 - -lg_use_markers <true,false> - mark the data points (at each time step) on the plot; default is true 4562 4563 Notes: 4564 Use TSMonitorLGCtxDestroy() to destroy. 4565 4566 One can provide a function that transforms the solution before plotting it with TSMonitorLGCtxSetTransform() or TSMonitorLGSetTransform() 4567 4568 Many of the functions that control the monitoring have two forms: TSMonitorLGSet/GetXXXX() and TSMonitorLGCtxSet/GetXXXX() the first take a TS object as the 4569 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 4570 as the first argument. 4571 4572 One can control the names displayed for each solution or error variable with TSMonitorLGCtxSetVariableNames() or TSMonitorLGSetVariableNames() 4573 4574 Level: intermediate 4575 4576 .keywords: TS, monitor, line graph, residual 4577 4578 .seealso: TSMonitorLGTimeStep(), TSMonitorSet(), TSMonitorLGSolution(), TSMonitorLGError(), TSMonitorDefault(), VecView(), 4579 TSMonitorLGCtxCreate(), TSMonitorLGCtxSetVariableNames(), TSMonitorLGCtxGetVariableNames(), 4580 TSMonitorLGSetVariableNames(), TSMonitorLGGetVariableNames(), TSMonitorLGSetDisplayVariables(), TSMonitorLGCtxSetDisplayVariables(), 4581 TSMonitorLGCtxSetTransform(), TSMonitorLGSetTransform(), TSMonitorLGError(), TSMonitorLGSNESIterations(), TSMonitorLGKSPIterations(), 4582 TSMonitorEnvelopeCtxCreate(), TSMonitorEnvelopeGetBounds(), TSMonitorEnvelopeCtxDestroy(), TSMonitorEnvelop() 4583 4584 @*/ 4585 PetscErrorCode TSMonitorLGCtxCreate(MPI_Comm comm,const char host[],const char label[],int x,int y,int m,int n,PetscInt howoften,TSMonitorLGCtx *ctx) 4586 { 4587 PetscDraw draw; 4588 PetscErrorCode ierr; 4589 4590 PetscFunctionBegin; 4591 ierr = PetscNew(ctx);CHKERRQ(ierr); 4592 ierr = PetscDrawCreate(comm,host,label,x,y,m,n,&draw);CHKERRQ(ierr); 4593 ierr = PetscDrawSetFromOptions(draw);CHKERRQ(ierr); 4594 ierr = PetscDrawLGCreate(draw,1,&(*ctx)->lg);CHKERRQ(ierr); 4595 ierr = PetscDrawLGSetFromOptions((*ctx)->lg);CHKERRQ(ierr); 4596 ierr = PetscDrawDestroy(&draw);CHKERRQ(ierr); 4597 (*ctx)->howoften = howoften; 4598 PetscFunctionReturn(0); 4599 } 4600 4601 PetscErrorCode TSMonitorLGTimeStep(TS ts,PetscInt step,PetscReal ptime,Vec v,void *monctx) 4602 { 4603 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 4604 PetscReal x = ptime,y; 4605 PetscErrorCode ierr; 4606 4607 PetscFunctionBegin; 4608 if (step < 0) PetscFunctionReturn(0); /* -1 indicates an interpolated solution */ 4609 if (!step) { 4610 PetscDrawAxis axis; 4611 const char *ylabel = ctx->semilogy ? "Log Time Step" : "Time Step"; 4612 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 4613 ierr = PetscDrawAxisSetLabels(axis,"Timestep as function of time","Time",ylabel);CHKERRQ(ierr); 4614 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 4615 } 4616 ierr = TSGetTimeStep(ts,&y);CHKERRQ(ierr); 4617 if (ctx->semilogy) y = PetscLog10Real(y); 4618 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 4619 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 4620 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 4621 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 4622 } 4623 PetscFunctionReturn(0); 4624 } 4625 4626 /*@C 4627 TSMonitorLGCtxDestroy - Destroys a line graph context that was created 4628 with TSMonitorLGCtxCreate(). 4629 4630 Collective on TSMonitorLGCtx 4631 4632 Input Parameter: 4633 . ctx - the monitor context 4634 4635 Level: intermediate 4636 4637 .keywords: TS, monitor, line graph, destroy 4638 4639 .seealso: TSMonitorLGCtxCreate(), TSMonitorSet(), TSMonitorLGTimeStep(); 4640 @*/ 4641 PetscErrorCode TSMonitorLGCtxDestroy(TSMonitorLGCtx *ctx) 4642 { 4643 PetscErrorCode ierr; 4644 4645 PetscFunctionBegin; 4646 if ((*ctx)->transformdestroy) { 4647 ierr = ((*ctx)->transformdestroy)((*ctx)->transformctx);CHKERRQ(ierr); 4648 } 4649 ierr = PetscDrawLGDestroy(&(*ctx)->lg);CHKERRQ(ierr); 4650 ierr = PetscStrArrayDestroy(&(*ctx)->names);CHKERRQ(ierr); 4651 ierr = PetscStrArrayDestroy(&(*ctx)->displaynames);CHKERRQ(ierr); 4652 ierr = PetscFree((*ctx)->displayvariables);CHKERRQ(ierr); 4653 ierr = PetscFree((*ctx)->displayvalues);CHKERRQ(ierr); 4654 ierr = PetscFree(*ctx);CHKERRQ(ierr); 4655 PetscFunctionReturn(0); 4656 } 4657 4658 /*@ 4659 TSGetTime - Gets the time of the most recently completed step. 4660 4661 Not Collective 4662 4663 Input Parameter: 4664 . ts - the TS context obtained from TSCreate() 4665 4666 Output Parameter: 4667 . t - the current time. This time may not corresponds to the final time set with TSSetMaxTime(), use TSGetSolveTime(). 4668 4669 Level: beginner 4670 4671 Note: 4672 When called during time step evaluation (e.g. during residual evaluation or via hooks set using TSSetPreStep(), 4673 TSSetPreStage(), TSSetPostStage(), or TSSetPostStep()), the time is the time at the start of the step being evaluated. 4674 4675 .seealso: TSGetSolveTime(), TSSetTime(), TSGetTimeStep() 4676 4677 .keywords: TS, get, time 4678 @*/ 4679 PetscErrorCode TSGetTime(TS ts,PetscReal *t) 4680 { 4681 PetscFunctionBegin; 4682 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4683 PetscValidRealPointer(t,2); 4684 *t = ts->ptime; 4685 PetscFunctionReturn(0); 4686 } 4687 4688 /*@ 4689 TSGetPrevTime - Gets the starting time of the previously completed step. 4690 4691 Not Collective 4692 4693 Input Parameter: 4694 . ts - the TS context obtained from TSCreate() 4695 4696 Output Parameter: 4697 . t - the previous time 4698 4699 Level: beginner 4700 4701 .seealso: TSGetTime(), TSGetSolveTime(), TSGetTimeStep() 4702 4703 .keywords: TS, get, time 4704 @*/ 4705 PetscErrorCode TSGetPrevTime(TS ts,PetscReal *t) 4706 { 4707 PetscFunctionBegin; 4708 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4709 PetscValidRealPointer(t,2); 4710 *t = ts->ptime_prev; 4711 PetscFunctionReturn(0); 4712 } 4713 4714 /*@ 4715 TSSetTime - Allows one to reset the time. 4716 4717 Logically Collective on TS 4718 4719 Input Parameters: 4720 + ts - the TS context obtained from TSCreate() 4721 - time - the time 4722 4723 Level: intermediate 4724 4725 .seealso: TSGetTime(), TSSetMaxSteps() 4726 4727 .keywords: TS, set, time 4728 @*/ 4729 PetscErrorCode TSSetTime(TS ts, PetscReal t) 4730 { 4731 PetscFunctionBegin; 4732 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4733 PetscValidLogicalCollectiveReal(ts,t,2); 4734 ts->ptime = t; 4735 PetscFunctionReturn(0); 4736 } 4737 4738 /*@C 4739 TSSetOptionsPrefix - Sets the prefix used for searching for all 4740 TS options in the database. 4741 4742 Logically Collective on TS 4743 4744 Input Parameter: 4745 + ts - The TS context 4746 - prefix - The prefix to prepend to all option names 4747 4748 Notes: 4749 A hyphen (-) must NOT be given at the beginning of the prefix name. 4750 The first character of all runtime options is AUTOMATICALLY the 4751 hyphen. 4752 4753 Level: advanced 4754 4755 .keywords: TS, set, options, prefix, database 4756 4757 .seealso: TSSetFromOptions() 4758 4759 @*/ 4760 PetscErrorCode TSSetOptionsPrefix(TS ts,const char prefix[]) 4761 { 4762 PetscErrorCode ierr; 4763 SNES snes; 4764 4765 PetscFunctionBegin; 4766 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4767 ierr = PetscObjectSetOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 4768 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4769 ierr = SNESSetOptionsPrefix(snes,prefix);CHKERRQ(ierr); 4770 PetscFunctionReturn(0); 4771 } 4772 4773 /*@C 4774 TSAppendOptionsPrefix - Appends to the prefix used for searching for all 4775 TS options in the database. 4776 4777 Logically Collective on TS 4778 4779 Input Parameter: 4780 + ts - The TS context 4781 - prefix - The prefix to prepend to all option names 4782 4783 Notes: 4784 A hyphen (-) must NOT be given at the beginning of the prefix name. 4785 The first character of all runtime options is AUTOMATICALLY the 4786 hyphen. 4787 4788 Level: advanced 4789 4790 .keywords: TS, append, options, prefix, database 4791 4792 .seealso: TSGetOptionsPrefix() 4793 4794 @*/ 4795 PetscErrorCode TSAppendOptionsPrefix(TS ts,const char prefix[]) 4796 { 4797 PetscErrorCode ierr; 4798 SNES snes; 4799 4800 PetscFunctionBegin; 4801 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4802 ierr = PetscObjectAppendOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 4803 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4804 ierr = SNESAppendOptionsPrefix(snes,prefix);CHKERRQ(ierr); 4805 PetscFunctionReturn(0); 4806 } 4807 4808 /*@C 4809 TSGetOptionsPrefix - Sets the prefix used for searching for all 4810 TS options in the database. 4811 4812 Not Collective 4813 4814 Input Parameter: 4815 . ts - The TS context 4816 4817 Output Parameter: 4818 . prefix - A pointer to the prefix string used 4819 4820 Notes: On the fortran side, the user should pass in a string 'prifix' of 4821 sufficient length to hold the prefix. 4822 4823 Level: intermediate 4824 4825 .keywords: TS, get, options, prefix, database 4826 4827 .seealso: TSAppendOptionsPrefix() 4828 @*/ 4829 PetscErrorCode TSGetOptionsPrefix(TS ts,const char *prefix[]) 4830 { 4831 PetscErrorCode ierr; 4832 4833 PetscFunctionBegin; 4834 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4835 PetscValidPointer(prefix,2); 4836 ierr = PetscObjectGetOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 4837 PetscFunctionReturn(0); 4838 } 4839 4840 /*@C 4841 TSGetRHSJacobian - Returns the Jacobian J at the present timestep. 4842 4843 Not Collective, but parallel objects are returned if TS is parallel 4844 4845 Input Parameter: 4846 . ts - The TS context obtained from TSCreate() 4847 4848 Output Parameters: 4849 + Amat - The (approximate) Jacobian J of G, where U_t = G(U,t) (or NULL) 4850 . Pmat - The matrix from which the preconditioner is constructed, usually the same as Amat (or NULL) 4851 . func - Function to compute the Jacobian of the RHS (or NULL) 4852 - ctx - User-defined context for Jacobian evaluation routine (or NULL) 4853 4854 Notes: You can pass in NULL for any return argument you do not need. 4855 4856 Level: intermediate 4857 4858 .seealso: TSGetTimeStep(), TSGetMatrices(), TSGetTime(), TSGetStepNumber() 4859 4860 .keywords: TS, timestep, get, matrix, Jacobian 4861 @*/ 4862 PetscErrorCode TSGetRHSJacobian(TS ts,Mat *Amat,Mat *Pmat,TSRHSJacobian *func,void **ctx) 4863 { 4864 PetscErrorCode ierr; 4865 DM dm; 4866 4867 PetscFunctionBegin; 4868 if (Amat || Pmat) { 4869 SNES snes; 4870 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4871 ierr = SNESSetUpMatrices(snes);CHKERRQ(ierr); 4872 ierr = SNESGetJacobian(snes,Amat,Pmat,NULL,NULL);CHKERRQ(ierr); 4873 } 4874 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 4875 ierr = DMTSGetRHSJacobian(dm,func,ctx);CHKERRQ(ierr); 4876 PetscFunctionReturn(0); 4877 } 4878 4879 /*@C 4880 TSGetIJacobian - Returns the implicit Jacobian at the present timestep. 4881 4882 Not Collective, but parallel objects are returned if TS is parallel 4883 4884 Input Parameter: 4885 . ts - The TS context obtained from TSCreate() 4886 4887 Output Parameters: 4888 + Amat - The (approximate) Jacobian of F(t,U,U_t) 4889 . Pmat - The matrix from which the preconditioner is constructed, often the same as Amat 4890 . f - The function to compute the matrices 4891 - ctx - User-defined context for Jacobian evaluation routine 4892 4893 Notes: You can pass in NULL for any return argument you do not need. 4894 4895 Level: advanced 4896 4897 .seealso: TSGetTimeStep(), TSGetRHSJacobian(), TSGetMatrices(), TSGetTime(), TSGetStepNumber() 4898 4899 .keywords: TS, timestep, get, matrix, Jacobian 4900 @*/ 4901 PetscErrorCode TSGetIJacobian(TS ts,Mat *Amat,Mat *Pmat,TSIJacobian *f,void **ctx) 4902 { 4903 PetscErrorCode ierr; 4904 DM dm; 4905 4906 PetscFunctionBegin; 4907 if (Amat || Pmat) { 4908 SNES snes; 4909 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4910 ierr = SNESSetUpMatrices(snes);CHKERRQ(ierr); 4911 ierr = SNESGetJacobian(snes,Amat,Pmat,NULL,NULL);CHKERRQ(ierr); 4912 } 4913 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 4914 ierr = DMTSGetIJacobian(dm,f,ctx);CHKERRQ(ierr); 4915 PetscFunctionReturn(0); 4916 } 4917 4918 /*@C 4919 TSMonitorDrawSolution - Monitors progress of the TS solvers by calling 4920 VecView() for the solution at each timestep 4921 4922 Collective on TS 4923 4924 Input Parameters: 4925 + ts - the TS context 4926 . step - current time-step 4927 . ptime - current time 4928 - dummy - either a viewer or NULL 4929 4930 Options Database: 4931 . -ts_monitor_draw_solution_initial - show initial solution as well as current solution 4932 4933 Notes: the initial solution and current solution are not display with a common axis scaling so generally the option -ts_monitor_draw_solution_initial 4934 will look bad 4935 4936 Level: intermediate 4937 4938 .keywords: TS, vector, monitor, view 4939 4940 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 4941 @*/ 4942 PetscErrorCode TSMonitorDrawSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 4943 { 4944 PetscErrorCode ierr; 4945 TSMonitorDrawCtx ictx = (TSMonitorDrawCtx)dummy; 4946 PetscDraw draw; 4947 4948 PetscFunctionBegin; 4949 if (!step && ictx->showinitial) { 4950 if (!ictx->initialsolution) { 4951 ierr = VecDuplicate(u,&ictx->initialsolution);CHKERRQ(ierr); 4952 } 4953 ierr = VecCopy(u,ictx->initialsolution);CHKERRQ(ierr); 4954 } 4955 if (!(((ictx->howoften > 0) && (!(step % ictx->howoften))) || ((ictx->howoften == -1) && ts->reason))) PetscFunctionReturn(0); 4956 4957 if (ictx->showinitial) { 4958 PetscReal pause; 4959 ierr = PetscViewerDrawGetPause(ictx->viewer,&pause);CHKERRQ(ierr); 4960 ierr = PetscViewerDrawSetPause(ictx->viewer,0.0);CHKERRQ(ierr); 4961 ierr = VecView(ictx->initialsolution,ictx->viewer);CHKERRQ(ierr); 4962 ierr = PetscViewerDrawSetPause(ictx->viewer,pause);CHKERRQ(ierr); 4963 ierr = PetscViewerDrawSetHold(ictx->viewer,PETSC_TRUE);CHKERRQ(ierr); 4964 } 4965 ierr = VecView(u,ictx->viewer);CHKERRQ(ierr); 4966 if (ictx->showtimestepandtime) { 4967 PetscReal xl,yl,xr,yr,h; 4968 char time[32]; 4969 4970 ierr = PetscViewerDrawGetDraw(ictx->viewer,0,&draw);CHKERRQ(ierr); 4971 ierr = PetscSNPrintf(time,32,"Timestep %d Time %g",(int)step,(double)ptime);CHKERRQ(ierr); 4972 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 4973 h = yl + .95*(yr - yl); 4974 ierr = PetscDrawStringCentered(draw,.5*(xl+xr),h,PETSC_DRAW_BLACK,time);CHKERRQ(ierr); 4975 ierr = PetscDrawFlush(draw);CHKERRQ(ierr); 4976 } 4977 4978 if (ictx->showinitial) { 4979 ierr = PetscViewerDrawSetHold(ictx->viewer,PETSC_FALSE);CHKERRQ(ierr); 4980 } 4981 PetscFunctionReturn(0); 4982 } 4983 4984 /*@C 4985 TSAdjointMonitorDrawSensi - Monitors progress of the adjoint TS solvers by calling 4986 VecView() for the sensitivities to initial states at each timestep 4987 4988 Collective on TS 4989 4990 Input Parameters: 4991 + ts - the TS context 4992 . step - current time-step 4993 . ptime - current time 4994 . u - current state 4995 . numcost - number of cost functions 4996 . lambda - sensitivities to initial conditions 4997 . mu - sensitivities to parameters 4998 - dummy - either a viewer or NULL 4999 5000 Level: intermediate 5001 5002 .keywords: TS, vector, adjoint, monitor, view 5003 5004 .seealso: TSAdjointMonitorSet(), TSAdjointMonitorDefault(), VecView() 5005 @*/ 5006 PetscErrorCode TSAdjointMonitorDrawSensi(TS ts,PetscInt step,PetscReal ptime,Vec u,PetscInt numcost,Vec *lambda,Vec *mu,void *dummy) 5007 { 5008 PetscErrorCode ierr; 5009 TSMonitorDrawCtx ictx = (TSMonitorDrawCtx)dummy; 5010 PetscDraw draw; 5011 PetscReal xl,yl,xr,yr,h; 5012 char time[32]; 5013 5014 PetscFunctionBegin; 5015 if (!(((ictx->howoften > 0) && (!(step % ictx->howoften))) || ((ictx->howoften == -1) && ts->reason))) PetscFunctionReturn(0); 5016 5017 ierr = VecView(lambda[0],ictx->viewer);CHKERRQ(ierr); 5018 ierr = PetscViewerDrawGetDraw(ictx->viewer,0,&draw);CHKERRQ(ierr); 5019 ierr = PetscSNPrintf(time,32,"Timestep %d Time %g",(int)step,(double)ptime);CHKERRQ(ierr); 5020 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 5021 h = yl + .95*(yr - yl); 5022 ierr = PetscDrawStringCentered(draw,.5*(xl+xr),h,PETSC_DRAW_BLACK,time);CHKERRQ(ierr); 5023 ierr = PetscDrawFlush(draw);CHKERRQ(ierr); 5024 PetscFunctionReturn(0); 5025 } 5026 5027 /*@C 5028 TSMonitorDrawSolutionPhase - Monitors progress of the TS solvers by plotting the solution as a phase diagram 5029 5030 Collective on TS 5031 5032 Input Parameters: 5033 + ts - the TS context 5034 . step - current time-step 5035 . ptime - current time 5036 - dummy - either a viewer or NULL 5037 5038 Level: intermediate 5039 5040 .keywords: TS, vector, monitor, view 5041 5042 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 5043 @*/ 5044 PetscErrorCode TSMonitorDrawSolutionPhase(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 5045 { 5046 PetscErrorCode ierr; 5047 TSMonitorDrawCtx ictx = (TSMonitorDrawCtx)dummy; 5048 PetscDraw draw; 5049 PetscDrawAxis axis; 5050 PetscInt n; 5051 PetscMPIInt size; 5052 PetscReal U0,U1,xl,yl,xr,yr,h; 5053 char time[32]; 5054 const PetscScalar *U; 5055 5056 PetscFunctionBegin; 5057 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)ts),&size);CHKERRQ(ierr); 5058 if (size != 1) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Only allowed for sequential runs"); 5059 ierr = VecGetSize(u,&n);CHKERRQ(ierr); 5060 if (n != 2) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Only for ODEs with two unknowns"); 5061 5062 ierr = PetscViewerDrawGetDraw(ictx->viewer,0,&draw);CHKERRQ(ierr); 5063 ierr = PetscViewerDrawGetDrawAxis(ictx->viewer,0,&axis);CHKERRQ(ierr); 5064 ierr = PetscDrawAxisGetLimits(axis,&xl,&xr,&yl,&yr);CHKERRQ(ierr); 5065 if (!step) { 5066 ierr = PetscDrawClear(draw);CHKERRQ(ierr); 5067 ierr = PetscDrawAxisDraw(axis);CHKERRQ(ierr); 5068 } 5069 5070 ierr = VecGetArrayRead(u,&U);CHKERRQ(ierr); 5071 U0 = PetscRealPart(U[0]); 5072 U1 = PetscRealPart(U[1]); 5073 ierr = VecRestoreArrayRead(u,&U);CHKERRQ(ierr); 5074 if ((U0 < xl) || (U1 < yl) || (U0 > xr) || (U1 > yr)) PetscFunctionReturn(0); 5075 5076 ierr = PetscDrawCollectiveBegin(draw);CHKERRQ(ierr); 5077 ierr = PetscDrawPoint(draw,U0,U1,PETSC_DRAW_BLACK);CHKERRQ(ierr); 5078 if (ictx->showtimestepandtime) { 5079 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 5080 ierr = PetscSNPrintf(time,32,"Timestep %d Time %g",(int)step,(double)ptime);CHKERRQ(ierr); 5081 h = yl + .95*(yr - yl); 5082 ierr = PetscDrawStringCentered(draw,.5*(xl+xr),h,PETSC_DRAW_BLACK,time);CHKERRQ(ierr); 5083 } 5084 ierr = PetscDrawCollectiveEnd(draw);CHKERRQ(ierr); 5085 ierr = PetscDrawFlush(draw);CHKERRQ(ierr); 5086 ierr = PetscDrawPause(draw);CHKERRQ(ierr); 5087 ierr = PetscDrawSave(draw);CHKERRQ(ierr); 5088 PetscFunctionReturn(0); 5089 } 5090 5091 /*@C 5092 TSMonitorDrawCtxDestroy - Destroys the monitor context for TSMonitorDrawSolution() 5093 5094 Collective on TS 5095 5096 Input Parameters: 5097 . ctx - the monitor context 5098 5099 Level: intermediate 5100 5101 .keywords: TS, vector, monitor, view 5102 5103 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorDrawSolution(), TSMonitorDrawError() 5104 @*/ 5105 PetscErrorCode TSMonitorDrawCtxDestroy(TSMonitorDrawCtx *ictx) 5106 { 5107 PetscErrorCode ierr; 5108 5109 PetscFunctionBegin; 5110 ierr = PetscViewerDestroy(&(*ictx)->viewer);CHKERRQ(ierr); 5111 ierr = VecDestroy(&(*ictx)->initialsolution);CHKERRQ(ierr); 5112 ierr = PetscFree(*ictx);CHKERRQ(ierr); 5113 PetscFunctionReturn(0); 5114 } 5115 5116 /*@C 5117 TSMonitorDrawCtxCreate - Creates the monitor context for TSMonitorDrawCtx 5118 5119 Collective on TS 5120 5121 Input Parameter: 5122 . ts - time-step context 5123 5124 Output Patameter: 5125 . ctx - the monitor context 5126 5127 Options Database: 5128 . -ts_monitor_draw_solution_initial - show initial solution as well as current solution 5129 5130 Level: intermediate 5131 5132 .keywords: TS, vector, monitor, view 5133 5134 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorDrawCtx() 5135 @*/ 5136 PetscErrorCode TSMonitorDrawCtxCreate(MPI_Comm comm,const char host[],const char label[],int x,int y,int m,int n,PetscInt howoften,TSMonitorDrawCtx *ctx) 5137 { 5138 PetscErrorCode ierr; 5139 5140 PetscFunctionBegin; 5141 ierr = PetscNew(ctx);CHKERRQ(ierr); 5142 ierr = PetscViewerDrawOpen(comm,host,label,x,y,m,n,&(*ctx)->viewer);CHKERRQ(ierr); 5143 ierr = PetscViewerSetFromOptions((*ctx)->viewer);CHKERRQ(ierr); 5144 5145 (*ctx)->howoften = howoften; 5146 (*ctx)->showinitial = PETSC_FALSE; 5147 ierr = PetscOptionsGetBool(NULL,NULL,"-ts_monitor_draw_solution_initial",&(*ctx)->showinitial,NULL);CHKERRQ(ierr); 5148 5149 (*ctx)->showtimestepandtime = PETSC_FALSE; 5150 ierr = PetscOptionsGetBool(NULL,NULL,"-ts_monitor_draw_solution_show_time",&(*ctx)->showtimestepandtime,NULL);CHKERRQ(ierr); 5151 PetscFunctionReturn(0); 5152 } 5153 5154 /*@C 5155 TSMonitorDrawError - Monitors progress of the TS solvers by calling 5156 VecView() for the error at each timestep 5157 5158 Collective on TS 5159 5160 Input Parameters: 5161 + ts - the TS context 5162 . step - current time-step 5163 . ptime - current time 5164 - dummy - either a viewer or NULL 5165 5166 Level: intermediate 5167 5168 .keywords: TS, vector, monitor, view 5169 5170 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 5171 @*/ 5172 PetscErrorCode TSMonitorDrawError(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 5173 { 5174 PetscErrorCode ierr; 5175 TSMonitorDrawCtx ctx = (TSMonitorDrawCtx)dummy; 5176 PetscViewer viewer = ctx->viewer; 5177 Vec work; 5178 5179 PetscFunctionBegin; 5180 if (!(((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason))) PetscFunctionReturn(0); 5181 ierr = VecDuplicate(u,&work);CHKERRQ(ierr); 5182 ierr = TSComputeSolutionFunction(ts,ptime,work);CHKERRQ(ierr); 5183 ierr = VecAXPY(work,-1.0,u);CHKERRQ(ierr); 5184 ierr = VecView(work,viewer);CHKERRQ(ierr); 5185 ierr = VecDestroy(&work);CHKERRQ(ierr); 5186 PetscFunctionReturn(0); 5187 } 5188 5189 #include <petsc/private/dmimpl.h> 5190 /*@ 5191 TSSetDM - Sets the DM that may be used by some nonlinear solvers or preconditioners under the TS 5192 5193 Logically Collective on TS and DM 5194 5195 Input Parameters: 5196 + ts - the ODE integrator object 5197 - dm - the dm, cannot be NULL 5198 5199 Level: intermediate 5200 5201 .seealso: TSGetDM(), SNESSetDM(), SNESGetDM() 5202 @*/ 5203 PetscErrorCode TSSetDM(TS ts,DM dm) 5204 { 5205 PetscErrorCode ierr; 5206 SNES snes; 5207 DMTS tsdm; 5208 5209 PetscFunctionBegin; 5210 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5211 PetscValidHeaderSpecific(dm,DM_CLASSID,2); 5212 ierr = PetscObjectReference((PetscObject)dm);CHKERRQ(ierr); 5213 if (ts->dm) { /* Move the DMTS context over to the new DM unless the new DM already has one */ 5214 if (ts->dm->dmts && !dm->dmts) { 5215 ierr = DMCopyDMTS(ts->dm,dm);CHKERRQ(ierr); 5216 ierr = DMGetDMTS(ts->dm,&tsdm);CHKERRQ(ierr); 5217 if (tsdm->originaldm == ts->dm) { /* Grant write privileges to the replacement DM */ 5218 tsdm->originaldm = dm; 5219 } 5220 } 5221 ierr = DMDestroy(&ts->dm);CHKERRQ(ierr); 5222 } 5223 ts->dm = dm; 5224 5225 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 5226 ierr = SNESSetDM(snes,dm);CHKERRQ(ierr); 5227 PetscFunctionReturn(0); 5228 } 5229 5230 /*@ 5231 TSGetDM - Gets the DM that may be used by some preconditioners 5232 5233 Not Collective 5234 5235 Input Parameter: 5236 . ts - the preconditioner context 5237 5238 Output Parameter: 5239 . dm - the dm 5240 5241 Level: intermediate 5242 5243 .seealso: TSSetDM(), SNESSetDM(), SNESGetDM() 5244 @*/ 5245 PetscErrorCode TSGetDM(TS ts,DM *dm) 5246 { 5247 PetscErrorCode ierr; 5248 5249 PetscFunctionBegin; 5250 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5251 if (!ts->dm) { 5252 ierr = DMShellCreate(PetscObjectComm((PetscObject)ts),&ts->dm);CHKERRQ(ierr); 5253 if (ts->snes) {ierr = SNESSetDM(ts->snes,ts->dm);CHKERRQ(ierr);} 5254 } 5255 *dm = ts->dm; 5256 PetscFunctionReturn(0); 5257 } 5258 5259 /*@ 5260 SNESTSFormFunction - Function to evaluate nonlinear residual 5261 5262 Logically Collective on SNES 5263 5264 Input Parameter: 5265 + snes - nonlinear solver 5266 . U - the current state at which to evaluate the residual 5267 - ctx - user context, must be a TS 5268 5269 Output Parameter: 5270 . F - the nonlinear residual 5271 5272 Notes: 5273 This function is not normally called by users and is automatically registered with the SNES used by TS. 5274 It is most frequently passed to MatFDColoringSetFunction(). 5275 5276 Level: advanced 5277 5278 .seealso: SNESSetFunction(), MatFDColoringSetFunction() 5279 @*/ 5280 PetscErrorCode SNESTSFormFunction(SNES snes,Vec U,Vec F,void *ctx) 5281 { 5282 TS ts = (TS)ctx; 5283 PetscErrorCode ierr; 5284 5285 PetscFunctionBegin; 5286 PetscValidHeaderSpecific(snes,SNES_CLASSID,1); 5287 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 5288 PetscValidHeaderSpecific(F,VEC_CLASSID,3); 5289 PetscValidHeaderSpecific(ts,TS_CLASSID,4); 5290 ierr = (ts->ops->snesfunction)(snes,U,F,ts);CHKERRQ(ierr); 5291 PetscFunctionReturn(0); 5292 } 5293 5294 /*@ 5295 SNESTSFormJacobian - Function to evaluate the Jacobian 5296 5297 Collective on SNES 5298 5299 Input Parameter: 5300 + snes - nonlinear solver 5301 . U - the current state at which to evaluate the residual 5302 - ctx - user context, must be a TS 5303 5304 Output Parameter: 5305 + A - the Jacobian 5306 . B - the preconditioning matrix (may be the same as A) 5307 - flag - indicates any structure change in the matrix 5308 5309 Notes: 5310 This function is not normally called by users and is automatically registered with the SNES used by TS. 5311 5312 Level: developer 5313 5314 .seealso: SNESSetJacobian() 5315 @*/ 5316 PetscErrorCode SNESTSFormJacobian(SNES snes,Vec U,Mat A,Mat B,void *ctx) 5317 { 5318 TS ts = (TS)ctx; 5319 PetscErrorCode ierr; 5320 5321 PetscFunctionBegin; 5322 PetscValidHeaderSpecific(snes,SNES_CLASSID,1); 5323 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 5324 PetscValidPointer(A,3); 5325 PetscValidHeaderSpecific(A,MAT_CLASSID,3); 5326 PetscValidPointer(B,4); 5327 PetscValidHeaderSpecific(B,MAT_CLASSID,4); 5328 PetscValidHeaderSpecific(ts,TS_CLASSID,6); 5329 ierr = (ts->ops->snesjacobian)(snes,U,A,B,ts);CHKERRQ(ierr); 5330 PetscFunctionReturn(0); 5331 } 5332 5333 /*@C 5334 TSComputeRHSFunctionLinear - Evaluate the right hand side via the user-provided Jacobian, for linear problems Udot = A U only 5335 5336 Collective on TS 5337 5338 Input Arguments: 5339 + ts - time stepping context 5340 . t - time at which to evaluate 5341 . U - state at which to evaluate 5342 - ctx - context 5343 5344 Output Arguments: 5345 . F - right hand side 5346 5347 Level: intermediate 5348 5349 Notes: 5350 This function is intended to be passed to TSSetRHSFunction() to evaluate the right hand side for linear problems. 5351 The matrix (and optionally the evaluation context) should be passed to TSSetRHSJacobian(). 5352 5353 .seealso: TSSetRHSFunction(), TSSetRHSJacobian(), TSComputeRHSJacobianConstant() 5354 @*/ 5355 PetscErrorCode TSComputeRHSFunctionLinear(TS ts,PetscReal t,Vec U,Vec F,void *ctx) 5356 { 5357 PetscErrorCode ierr; 5358 Mat Arhs,Brhs; 5359 5360 PetscFunctionBegin; 5361 ierr = TSGetRHSMats_Private(ts,&Arhs,&Brhs);CHKERRQ(ierr); 5362 ierr = TSComputeRHSJacobian(ts,t,U,Arhs,Brhs);CHKERRQ(ierr); 5363 ierr = MatMult(Arhs,U,F);CHKERRQ(ierr); 5364 PetscFunctionReturn(0); 5365 } 5366 5367 /*@C 5368 TSComputeRHSJacobianConstant - Reuses a Jacobian that is time-independent. 5369 5370 Collective on TS 5371 5372 Input Arguments: 5373 + ts - time stepping context 5374 . t - time at which to evaluate 5375 . U - state at which to evaluate 5376 - ctx - context 5377 5378 Output Arguments: 5379 + A - pointer to operator 5380 . B - pointer to preconditioning matrix 5381 - flg - matrix structure flag 5382 5383 Level: intermediate 5384 5385 Notes: 5386 This function is intended to be passed to TSSetRHSJacobian() to evaluate the Jacobian for linear time-independent problems. 5387 5388 .seealso: TSSetRHSFunction(), TSSetRHSJacobian(), TSComputeRHSFunctionLinear() 5389 @*/ 5390 PetscErrorCode TSComputeRHSJacobianConstant(TS ts,PetscReal t,Vec U,Mat A,Mat B,void *ctx) 5391 { 5392 PetscFunctionBegin; 5393 PetscFunctionReturn(0); 5394 } 5395 5396 /*@C 5397 TSComputeIFunctionLinear - Evaluate the left hand side via the user-provided Jacobian, for linear problems only 5398 5399 Collective on TS 5400 5401 Input Arguments: 5402 + ts - time stepping context 5403 . t - time at which to evaluate 5404 . U - state at which to evaluate 5405 . Udot - time derivative of state vector 5406 - ctx - context 5407 5408 Output Arguments: 5409 . F - left hand side 5410 5411 Level: intermediate 5412 5413 Notes: 5414 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 5415 user is required to write their own TSComputeIFunction. 5416 This function is intended to be passed to TSSetIFunction() to evaluate the left hand side for linear problems. 5417 The matrix (and optionally the evaluation context) should be passed to TSSetIJacobian(). 5418 5419 Note that using this function is NOT equivalent to using TSComputeRHSFunctionLinear() since that solves Udot = A U 5420 5421 .seealso: TSSetIFunction(), TSSetIJacobian(), TSComputeIJacobianConstant(), TSComputeRHSFunctionLinear() 5422 @*/ 5423 PetscErrorCode TSComputeIFunctionLinear(TS ts,PetscReal t,Vec U,Vec Udot,Vec F,void *ctx) 5424 { 5425 PetscErrorCode ierr; 5426 Mat A,B; 5427 5428 PetscFunctionBegin; 5429 ierr = TSGetIJacobian(ts,&A,&B,NULL,NULL);CHKERRQ(ierr); 5430 ierr = TSComputeIJacobian(ts,t,U,Udot,1.0,A,B,PETSC_TRUE);CHKERRQ(ierr); 5431 ierr = MatMult(A,Udot,F);CHKERRQ(ierr); 5432 PetscFunctionReturn(0); 5433 } 5434 5435 /*@C 5436 TSComputeIJacobianConstant - Reuses a time-independent for a semi-implicit DAE or ODE 5437 5438 Collective on TS 5439 5440 Input Arguments: 5441 + ts - time stepping context 5442 . t - time at which to evaluate 5443 . U - state at which to evaluate 5444 . Udot - time derivative of state vector 5445 . shift - shift to apply 5446 - ctx - context 5447 5448 Output Arguments: 5449 + A - pointer to operator 5450 . B - pointer to preconditioning matrix 5451 - flg - matrix structure flag 5452 5453 Level: advanced 5454 5455 Notes: 5456 This function is intended to be passed to TSSetIJacobian() to evaluate the Jacobian for linear time-independent problems. 5457 5458 It is only appropriate for problems of the form 5459 5460 $ M Udot = F(U,t) 5461 5462 where M is constant and F is non-stiff. The user must pass M to TSSetIJacobian(). The current implementation only 5463 works with IMEX time integration methods such as TSROSW and TSARKIMEX, since there is no support for de-constructing 5464 an implicit operator of the form 5465 5466 $ shift*M + J 5467 5468 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 5469 a copy of M or reassemble it when requested. 5470 5471 .seealso: TSSetIFunction(), TSSetIJacobian(), TSComputeIFunctionLinear() 5472 @*/ 5473 PetscErrorCode TSComputeIJacobianConstant(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat A,Mat B,void *ctx) 5474 { 5475 PetscErrorCode ierr; 5476 5477 PetscFunctionBegin; 5478 ierr = MatScale(A, shift / ts->ijacobian.shift);CHKERRQ(ierr); 5479 ts->ijacobian.shift = shift; 5480 PetscFunctionReturn(0); 5481 } 5482 5483 /*@ 5484 TSGetEquationType - Gets the type of the equation that TS is solving. 5485 5486 Not Collective 5487 5488 Input Parameter: 5489 . ts - the TS context 5490 5491 Output Parameter: 5492 . equation_type - see TSEquationType 5493 5494 Level: beginner 5495 5496 .keywords: TS, equation type 5497 5498 .seealso: TSSetEquationType(), TSEquationType 5499 @*/ 5500 PetscErrorCode TSGetEquationType(TS ts,TSEquationType *equation_type) 5501 { 5502 PetscFunctionBegin; 5503 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5504 PetscValidPointer(equation_type,2); 5505 *equation_type = ts->equation_type; 5506 PetscFunctionReturn(0); 5507 } 5508 5509 /*@ 5510 TSSetEquationType - Sets the type of the equation that TS is solving. 5511 5512 Not Collective 5513 5514 Input Parameter: 5515 + ts - the TS context 5516 - equation_type - see TSEquationType 5517 5518 Level: advanced 5519 5520 .keywords: TS, equation type 5521 5522 .seealso: TSGetEquationType(), TSEquationType 5523 @*/ 5524 PetscErrorCode TSSetEquationType(TS ts,TSEquationType equation_type) 5525 { 5526 PetscFunctionBegin; 5527 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5528 ts->equation_type = equation_type; 5529 PetscFunctionReturn(0); 5530 } 5531 5532 /*@ 5533 TSGetConvergedReason - Gets the reason the TS iteration was stopped. 5534 5535 Not Collective 5536 5537 Input Parameter: 5538 . ts - the TS context 5539 5540 Output Parameter: 5541 . reason - negative value indicates diverged, positive value converged, see TSConvergedReason or the 5542 manual pages for the individual convergence tests for complete lists 5543 5544 Level: beginner 5545 5546 Notes: 5547 Can only be called after the call to TSSolve() is complete. 5548 5549 .keywords: TS, nonlinear, set, convergence, test 5550 5551 .seealso: TSSetConvergenceTest(), TSConvergedReason 5552 @*/ 5553 PetscErrorCode TSGetConvergedReason(TS ts,TSConvergedReason *reason) 5554 { 5555 PetscFunctionBegin; 5556 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5557 PetscValidPointer(reason,2); 5558 *reason = ts->reason; 5559 PetscFunctionReturn(0); 5560 } 5561 5562 /*@ 5563 TSSetConvergedReason - Sets the reason for handling the convergence of TSSolve. 5564 5565 Not Collective 5566 5567 Input Parameter: 5568 + ts - the TS context 5569 . reason - negative value indicates diverged, positive value converged, see TSConvergedReason or the 5570 manual pages for the individual convergence tests for complete lists 5571 5572 Level: advanced 5573 5574 Notes: 5575 Can only be called during TSSolve() is active. 5576 5577 .keywords: TS, nonlinear, set, convergence, test 5578 5579 .seealso: TSConvergedReason 5580 @*/ 5581 PetscErrorCode TSSetConvergedReason(TS ts,TSConvergedReason reason) 5582 { 5583 PetscFunctionBegin; 5584 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5585 ts->reason = reason; 5586 PetscFunctionReturn(0); 5587 } 5588 5589 /*@ 5590 TSGetSolveTime - Gets the time after a call to TSSolve() 5591 5592 Not Collective 5593 5594 Input Parameter: 5595 . ts - the TS context 5596 5597 Output Parameter: 5598 . ftime - the final time. This time corresponds to the final time set with TSSetMaxTime() 5599 5600 Level: beginner 5601 5602 Notes: 5603 Can only be called after the call to TSSolve() is complete. 5604 5605 .keywords: TS, nonlinear, set, convergence, test 5606 5607 .seealso: TSSetConvergenceTest(), TSConvergedReason 5608 @*/ 5609 PetscErrorCode TSGetSolveTime(TS ts,PetscReal *ftime) 5610 { 5611 PetscFunctionBegin; 5612 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5613 PetscValidPointer(ftime,2); 5614 *ftime = ts->solvetime; 5615 PetscFunctionReturn(0); 5616 } 5617 5618 /*@ 5619 TSGetSNESIterations - Gets the total number of nonlinear iterations 5620 used by the time integrator. 5621 5622 Not Collective 5623 5624 Input Parameter: 5625 . ts - TS context 5626 5627 Output Parameter: 5628 . nits - number of nonlinear iterations 5629 5630 Notes: 5631 This counter is reset to zero for each successive call to TSSolve(). 5632 5633 Level: intermediate 5634 5635 .keywords: TS, get, number, nonlinear, iterations 5636 5637 .seealso: TSGetKSPIterations() 5638 @*/ 5639 PetscErrorCode TSGetSNESIterations(TS ts,PetscInt *nits) 5640 { 5641 PetscFunctionBegin; 5642 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5643 PetscValidIntPointer(nits,2); 5644 *nits = ts->snes_its; 5645 PetscFunctionReturn(0); 5646 } 5647 5648 /*@ 5649 TSGetKSPIterations - Gets the total number of linear iterations 5650 used by the time integrator. 5651 5652 Not Collective 5653 5654 Input Parameter: 5655 . ts - TS context 5656 5657 Output Parameter: 5658 . lits - number of linear iterations 5659 5660 Notes: 5661 This counter is reset to zero for each successive call to TSSolve(). 5662 5663 Level: intermediate 5664 5665 .keywords: TS, get, number, linear, iterations 5666 5667 .seealso: TSGetSNESIterations(), SNESGetKSPIterations() 5668 @*/ 5669 PetscErrorCode TSGetKSPIterations(TS ts,PetscInt *lits) 5670 { 5671 PetscFunctionBegin; 5672 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5673 PetscValidIntPointer(lits,2); 5674 *lits = ts->ksp_its; 5675 PetscFunctionReturn(0); 5676 } 5677 5678 /*@ 5679 TSGetStepRejections - Gets the total number of rejected steps. 5680 5681 Not Collective 5682 5683 Input Parameter: 5684 . ts - TS context 5685 5686 Output Parameter: 5687 . rejects - number of steps rejected 5688 5689 Notes: 5690 This counter is reset to zero for each successive call to TSSolve(). 5691 5692 Level: intermediate 5693 5694 .keywords: TS, get, number 5695 5696 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetSNESFailures(), TSSetMaxSNESFailures(), TSSetErrorIfStepFails() 5697 @*/ 5698 PetscErrorCode TSGetStepRejections(TS ts,PetscInt *rejects) 5699 { 5700 PetscFunctionBegin; 5701 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5702 PetscValidIntPointer(rejects,2); 5703 *rejects = ts->reject; 5704 PetscFunctionReturn(0); 5705 } 5706 5707 /*@ 5708 TSGetSNESFailures - Gets the total number of failed SNES solves 5709 5710 Not Collective 5711 5712 Input Parameter: 5713 . ts - TS context 5714 5715 Output Parameter: 5716 . fails - number of failed nonlinear solves 5717 5718 Notes: 5719 This counter is reset to zero for each successive call to TSSolve(). 5720 5721 Level: intermediate 5722 5723 .keywords: TS, get, number 5724 5725 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSSetMaxSNESFailures() 5726 @*/ 5727 PetscErrorCode TSGetSNESFailures(TS ts,PetscInt *fails) 5728 { 5729 PetscFunctionBegin; 5730 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5731 PetscValidIntPointer(fails,2); 5732 *fails = ts->num_snes_failures; 5733 PetscFunctionReturn(0); 5734 } 5735 5736 /*@ 5737 TSSetMaxStepRejections - Sets the maximum number of step rejections before a step fails 5738 5739 Not Collective 5740 5741 Input Parameter: 5742 + ts - TS context 5743 - rejects - maximum number of rejected steps, pass -1 for unlimited 5744 5745 Notes: 5746 The counter is reset to zero for each step 5747 5748 Options Database Key: 5749 . -ts_max_reject - Maximum number of step rejections before a step fails 5750 5751 Level: intermediate 5752 5753 .keywords: TS, set, maximum, number 5754 5755 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxSNESFailures(), TSGetStepRejections(), TSGetSNESFailures(), TSSetErrorIfStepFails(), TSGetConvergedReason() 5756 @*/ 5757 PetscErrorCode TSSetMaxStepRejections(TS ts,PetscInt rejects) 5758 { 5759 PetscFunctionBegin; 5760 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5761 ts->max_reject = rejects; 5762 PetscFunctionReturn(0); 5763 } 5764 5765 /*@ 5766 TSSetMaxSNESFailures - Sets the maximum number of failed SNES solves 5767 5768 Not Collective 5769 5770 Input Parameter: 5771 + ts - TS context 5772 - fails - maximum number of failed nonlinear solves, pass -1 for unlimited 5773 5774 Notes: 5775 The counter is reset to zero for each successive call to TSSolve(). 5776 5777 Options Database Key: 5778 . -ts_max_snes_failures - Maximum number of nonlinear solve failures 5779 5780 Level: intermediate 5781 5782 .keywords: TS, set, maximum, number 5783 5784 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSGetSNESFailures(), SNESGetConvergedReason(), TSGetConvergedReason() 5785 @*/ 5786 PetscErrorCode TSSetMaxSNESFailures(TS ts,PetscInt fails) 5787 { 5788 PetscFunctionBegin; 5789 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5790 ts->max_snes_failures = fails; 5791 PetscFunctionReturn(0); 5792 } 5793 5794 /*@ 5795 TSSetErrorIfStepFails - Error if no step succeeds 5796 5797 Not Collective 5798 5799 Input Parameter: 5800 + ts - TS context 5801 - err - PETSC_TRUE to error if no step succeeds, PETSC_FALSE to return without failure 5802 5803 Options Database Key: 5804 . -ts_error_if_step_fails - Error if no step succeeds 5805 5806 Level: intermediate 5807 5808 .keywords: TS, set, error 5809 5810 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSGetSNESFailures(), TSSetErrorIfStepFails(), TSGetConvergedReason() 5811 @*/ 5812 PetscErrorCode TSSetErrorIfStepFails(TS ts,PetscBool err) 5813 { 5814 PetscFunctionBegin; 5815 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5816 ts->errorifstepfailed = err; 5817 PetscFunctionReturn(0); 5818 } 5819 5820 /*@C 5821 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 5822 5823 Collective on TS 5824 5825 Input Parameters: 5826 + ts - the TS context 5827 . step - current time-step 5828 . ptime - current time 5829 . u - current state 5830 - vf - viewer and its format 5831 5832 Level: intermediate 5833 5834 .keywords: TS, vector, monitor, view 5835 5836 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 5837 @*/ 5838 PetscErrorCode TSMonitorSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,PetscViewerAndFormat *vf) 5839 { 5840 PetscErrorCode ierr; 5841 5842 PetscFunctionBegin; 5843 ierr = PetscViewerPushFormat(vf->viewer,vf->format);CHKERRQ(ierr); 5844 ierr = VecView(u,vf->viewer);CHKERRQ(ierr); 5845 ierr = PetscViewerPopFormat(vf->viewer);CHKERRQ(ierr); 5846 PetscFunctionReturn(0); 5847 } 5848 5849 /*@C 5850 TSMonitorSolutionVTK - Monitors progress of the TS solvers by VecView() for the solution at each timestep. 5851 5852 Collective on TS 5853 5854 Input Parameters: 5855 + ts - the TS context 5856 . step - current time-step 5857 . ptime - current time 5858 . u - current state 5859 - filenametemplate - string containing a format specifier for the integer time step (e.g. %03D) 5860 5861 Level: intermediate 5862 5863 Notes: 5864 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. 5865 These are named according to the file name template. 5866 5867 This function is normally passed as an argument to TSMonitorSet() along with TSMonitorSolutionVTKDestroy(). 5868 5869 .keywords: TS, vector, monitor, view 5870 5871 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 5872 @*/ 5873 PetscErrorCode TSMonitorSolutionVTK(TS ts,PetscInt step,PetscReal ptime,Vec u,void *filenametemplate) 5874 { 5875 PetscErrorCode ierr; 5876 char filename[PETSC_MAX_PATH_LEN]; 5877 PetscViewer viewer; 5878 5879 PetscFunctionBegin; 5880 if (step < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */ 5881 ierr = PetscSNPrintf(filename,sizeof(filename),(const char*)filenametemplate,step);CHKERRQ(ierr); 5882 ierr = PetscViewerVTKOpen(PetscObjectComm((PetscObject)ts),filename,FILE_MODE_WRITE,&viewer);CHKERRQ(ierr); 5883 ierr = VecView(u,viewer);CHKERRQ(ierr); 5884 ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr); 5885 PetscFunctionReturn(0); 5886 } 5887 5888 /*@C 5889 TSMonitorSolutionVTKDestroy - Destroy context for monitoring 5890 5891 Collective on TS 5892 5893 Input Parameters: 5894 . filenametemplate - string containing a format specifier for the integer time step (e.g. %03D) 5895 5896 Level: intermediate 5897 5898 Note: 5899 This function is normally passed to TSMonitorSet() along with TSMonitorSolutionVTK(). 5900 5901 .keywords: TS, vector, monitor, view 5902 5903 .seealso: TSMonitorSet(), TSMonitorSolutionVTK() 5904 @*/ 5905 PetscErrorCode TSMonitorSolutionVTKDestroy(void *filenametemplate) 5906 { 5907 PetscErrorCode ierr; 5908 5909 PetscFunctionBegin; 5910 ierr = PetscFree(*(char**)filenametemplate);CHKERRQ(ierr); 5911 PetscFunctionReturn(0); 5912 } 5913 5914 /*@ 5915 TSGetAdapt - Get the adaptive controller context for the current method 5916 5917 Collective on TS if controller has not been created yet 5918 5919 Input Arguments: 5920 . ts - time stepping context 5921 5922 Output Arguments: 5923 . adapt - adaptive controller 5924 5925 Level: intermediate 5926 5927 .seealso: TSAdapt, TSAdaptSetType(), TSAdaptChoose() 5928 @*/ 5929 PetscErrorCode TSGetAdapt(TS ts,TSAdapt *adapt) 5930 { 5931 PetscErrorCode ierr; 5932 5933 PetscFunctionBegin; 5934 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5935 PetscValidPointer(adapt,2); 5936 if (!ts->adapt) { 5937 ierr = TSAdaptCreate(PetscObjectComm((PetscObject)ts),&ts->adapt);CHKERRQ(ierr); 5938 ierr = PetscLogObjectParent((PetscObject)ts,(PetscObject)ts->adapt);CHKERRQ(ierr); 5939 ierr = PetscObjectIncrementTabLevel((PetscObject)ts->adapt,(PetscObject)ts,1);CHKERRQ(ierr); 5940 } 5941 *adapt = ts->adapt; 5942 PetscFunctionReturn(0); 5943 } 5944 5945 /*@ 5946 TSSetTolerances - Set tolerances for local truncation error when using adaptive controller 5947 5948 Logically Collective 5949 5950 Input Arguments: 5951 + ts - time integration context 5952 . atol - scalar absolute tolerances, PETSC_DECIDE to leave current value 5953 . vatol - vector of absolute tolerances or NULL, used in preference to atol if present 5954 . rtol - scalar relative tolerances, PETSC_DECIDE to leave current value 5955 - vrtol - vector of relative tolerances or NULL, used in preference to atol if present 5956 5957 Options Database keys: 5958 + -ts_rtol <rtol> - relative tolerance for local truncation error 5959 - -ts_atol <atol> Absolute tolerance for local truncation error 5960 5961 Notes: 5962 With PETSc's implicit schemes for DAE problems, the calculation of the local truncation error 5963 (LTE) includes both the differential and the algebraic variables. If one wants the LTE to be 5964 computed only for the differential or the algebraic part then this can be done using the vector of 5965 tolerances vatol. For example, by setting the tolerance vector with the desired tolerance for the 5966 differential part and infinity for the algebraic part, the LTE calculation will include only the 5967 differential variables. 5968 5969 Level: beginner 5970 5971 .seealso: TS, TSAdapt, TSVecNormWRMS(), TSGetTolerances() 5972 @*/ 5973 PetscErrorCode TSSetTolerances(TS ts,PetscReal atol,Vec vatol,PetscReal rtol,Vec vrtol) 5974 { 5975 PetscErrorCode ierr; 5976 5977 PetscFunctionBegin; 5978 if (atol != PETSC_DECIDE && atol != PETSC_DEFAULT) ts->atol = atol; 5979 if (vatol) { 5980 ierr = PetscObjectReference((PetscObject)vatol);CHKERRQ(ierr); 5981 ierr = VecDestroy(&ts->vatol);CHKERRQ(ierr); 5982 ts->vatol = vatol; 5983 } 5984 if (rtol != PETSC_DECIDE && rtol != PETSC_DEFAULT) ts->rtol = rtol; 5985 if (vrtol) { 5986 ierr = PetscObjectReference((PetscObject)vrtol);CHKERRQ(ierr); 5987 ierr = VecDestroy(&ts->vrtol);CHKERRQ(ierr); 5988 ts->vrtol = vrtol; 5989 } 5990 PetscFunctionReturn(0); 5991 } 5992 5993 /*@ 5994 TSGetTolerances - Get tolerances for local truncation error when using adaptive controller 5995 5996 Logically Collective 5997 5998 Input Arguments: 5999 . ts - time integration context 6000 6001 Output Arguments: 6002 + atol - scalar absolute tolerances, NULL to ignore 6003 . vatol - vector of absolute tolerances, NULL to ignore 6004 . rtol - scalar relative tolerances, NULL to ignore 6005 - vrtol - vector of relative tolerances, NULL to ignore 6006 6007 Level: beginner 6008 6009 .seealso: TS, TSAdapt, TSVecNormWRMS(), TSSetTolerances() 6010 @*/ 6011 PetscErrorCode TSGetTolerances(TS ts,PetscReal *atol,Vec *vatol,PetscReal *rtol,Vec *vrtol) 6012 { 6013 PetscFunctionBegin; 6014 if (atol) *atol = ts->atol; 6015 if (vatol) *vatol = ts->vatol; 6016 if (rtol) *rtol = ts->rtol; 6017 if (vrtol) *vrtol = ts->vrtol; 6018 PetscFunctionReturn(0); 6019 } 6020 6021 /*@ 6022 TSErrorWeightedNorm2 - compute a weighted 2-norm of the difference between two state vectors 6023 6024 Collective on TS 6025 6026 Input Arguments: 6027 + ts - time stepping context 6028 . U - state vector, usually ts->vec_sol 6029 - Y - state vector to be compared to U 6030 6031 Output Arguments: 6032 . norm - weighted norm, a value of 1.0 means that the error matches the tolerances 6033 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 6034 . normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 6035 6036 Level: developer 6037 6038 .seealso: TSErrorWeightedNorm(), TSErrorWeightedNormInfinity() 6039 @*/ 6040 PetscErrorCode TSErrorWeightedNorm2(TS ts,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6041 { 6042 PetscErrorCode ierr; 6043 PetscInt i,n,N,rstart; 6044 PetscInt n_loc,na_loc,nr_loc; 6045 PetscReal n_glb,na_glb,nr_glb; 6046 const PetscScalar *u,*y; 6047 PetscReal sum,suma,sumr,gsum,gsuma,gsumr,diff; 6048 PetscReal tol,tola,tolr; 6049 PetscReal err_loc[6],err_glb[6]; 6050 6051 PetscFunctionBegin; 6052 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6053 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 6054 PetscValidHeaderSpecific(Y,VEC_CLASSID,3); 6055 PetscValidType(U,2); 6056 PetscValidType(Y,3); 6057 PetscCheckSameComm(U,2,Y,3); 6058 PetscValidPointer(norm,4); 6059 PetscValidPointer(norma,5); 6060 PetscValidPointer(normr,6); 6061 if (U == Y) SETERRQ(PetscObjectComm((PetscObject)U),PETSC_ERR_ARG_IDN,"U and Y cannot be the same vector"); 6062 6063 ierr = VecGetSize(U,&N);CHKERRQ(ierr); 6064 ierr = VecGetLocalSize(U,&n);CHKERRQ(ierr); 6065 ierr = VecGetOwnershipRange(U,&rstart,NULL);CHKERRQ(ierr); 6066 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 6067 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 6068 sum = 0.; n_loc = 0; 6069 suma = 0.; na_loc = 0; 6070 sumr = 0.; nr_loc = 0; 6071 if (ts->vatol && ts->vrtol) { 6072 const PetscScalar *atol,*rtol; 6073 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6074 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6075 for (i=0; i<n; i++) { 6076 diff = PetscAbsScalar(y[i] - u[i]); 6077 tola = PetscRealPart(atol[i]); 6078 if(tola>0.){ 6079 suma += PetscSqr(diff/tola); 6080 na_loc++; 6081 } 6082 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6083 if(tolr>0.){ 6084 sumr += PetscSqr(diff/tolr); 6085 nr_loc++; 6086 } 6087 tol=tola+tolr; 6088 if(tol>0.){ 6089 sum += PetscSqr(diff/tol); 6090 n_loc++; 6091 } 6092 } 6093 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6094 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6095 } else if (ts->vatol) { /* vector atol, scalar rtol */ 6096 const PetscScalar *atol; 6097 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6098 for (i=0; i<n; i++) { 6099 diff = PetscAbsScalar(y[i] - u[i]); 6100 tola = PetscRealPart(atol[i]); 6101 if(tola>0.){ 6102 suma += PetscSqr(diff/tola); 6103 na_loc++; 6104 } 6105 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6106 if(tolr>0.){ 6107 sumr += PetscSqr(diff/tolr); 6108 nr_loc++; 6109 } 6110 tol=tola+tolr; 6111 if(tol>0.){ 6112 sum += PetscSqr(diff/tol); 6113 n_loc++; 6114 } 6115 } 6116 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6117 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 6118 const PetscScalar *rtol; 6119 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6120 for (i=0; i<n; i++) { 6121 diff = PetscAbsScalar(y[i] - u[i]); 6122 tola = ts->atol; 6123 if(tola>0.){ 6124 suma += PetscSqr(diff/tola); 6125 na_loc++; 6126 } 6127 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6128 if(tolr>0.){ 6129 sumr += PetscSqr(diff/tolr); 6130 nr_loc++; 6131 } 6132 tol=tola+tolr; 6133 if(tol>0.){ 6134 sum += PetscSqr(diff/tol); 6135 n_loc++; 6136 } 6137 } 6138 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6139 } else { /* scalar atol, scalar rtol */ 6140 for (i=0; i<n; i++) { 6141 diff = PetscAbsScalar(y[i] - u[i]); 6142 tola = ts->atol; 6143 if(tola>0.){ 6144 suma += PetscSqr(diff/tola); 6145 na_loc++; 6146 } 6147 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6148 if(tolr>0.){ 6149 sumr += PetscSqr(diff/tolr); 6150 nr_loc++; 6151 } 6152 tol=tola+tolr; 6153 if(tol>0.){ 6154 sum += PetscSqr(diff/tol); 6155 n_loc++; 6156 } 6157 } 6158 } 6159 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 6160 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 6161 6162 err_loc[0] = sum; 6163 err_loc[1] = suma; 6164 err_loc[2] = sumr; 6165 err_loc[3] = (PetscReal)n_loc; 6166 err_loc[4] = (PetscReal)na_loc; 6167 err_loc[5] = (PetscReal)nr_loc; 6168 6169 ierr = MPIU_Allreduce(err_loc,err_glb,6,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6170 6171 gsum = err_glb[0]; 6172 gsuma = err_glb[1]; 6173 gsumr = err_glb[2]; 6174 n_glb = err_glb[3]; 6175 na_glb = err_glb[4]; 6176 nr_glb = err_glb[5]; 6177 6178 *norm = 0.; 6179 if(n_glb>0. ){*norm = PetscSqrtReal(gsum / n_glb );} 6180 *norma = 0.; 6181 if(na_glb>0.){*norma = PetscSqrtReal(gsuma / na_glb);} 6182 *normr = 0.; 6183 if(nr_glb>0.){*normr = PetscSqrtReal(gsumr / nr_glb);} 6184 6185 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 6186 if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 6187 if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 6188 PetscFunctionReturn(0); 6189 } 6190 6191 /*@ 6192 TSErrorWeightedNormInfinity - compute a weighted infinity-norm of the difference between two state vectors 6193 6194 Collective on TS 6195 6196 Input Arguments: 6197 + ts - time stepping context 6198 . U - state vector, usually ts->vec_sol 6199 - Y - state vector to be compared to U 6200 6201 Output Arguments: 6202 . norm - weighted norm, a value of 1.0 means that the error matches the tolerances 6203 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 6204 . normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 6205 6206 Level: developer 6207 6208 .seealso: TSErrorWeightedNorm(), TSErrorWeightedNorm2() 6209 @*/ 6210 PetscErrorCode TSErrorWeightedNormInfinity(TS ts,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6211 { 6212 PetscErrorCode ierr; 6213 PetscInt i,n,N,rstart; 6214 const PetscScalar *u,*y; 6215 PetscReal max,gmax,maxa,gmaxa,maxr,gmaxr; 6216 PetscReal tol,tola,tolr,diff; 6217 PetscReal err_loc[3],err_glb[3]; 6218 6219 PetscFunctionBegin; 6220 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6221 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 6222 PetscValidHeaderSpecific(Y,VEC_CLASSID,3); 6223 PetscValidType(U,2); 6224 PetscValidType(Y,3); 6225 PetscCheckSameComm(U,2,Y,3); 6226 PetscValidPointer(norm,4); 6227 PetscValidPointer(norma,5); 6228 PetscValidPointer(normr,6); 6229 if (U == Y) SETERRQ(PetscObjectComm((PetscObject)U),PETSC_ERR_ARG_IDN,"U and Y cannot be the same vector"); 6230 6231 ierr = VecGetSize(U,&N);CHKERRQ(ierr); 6232 ierr = VecGetLocalSize(U,&n);CHKERRQ(ierr); 6233 ierr = VecGetOwnershipRange(U,&rstart,NULL);CHKERRQ(ierr); 6234 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 6235 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 6236 6237 max=0.; 6238 maxa=0.; 6239 maxr=0.; 6240 6241 if (ts->vatol && ts->vrtol) { /* vector atol, vector rtol */ 6242 const PetscScalar *atol,*rtol; 6243 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6244 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6245 6246 for (i=0; i<n; i++) { 6247 diff = PetscAbsScalar(y[i] - u[i]); 6248 tola = PetscRealPart(atol[i]); 6249 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6250 tol = tola+tolr; 6251 if(tola>0.){ 6252 maxa = PetscMax(maxa,diff / tola); 6253 } 6254 if(tolr>0.){ 6255 maxr = PetscMax(maxr,diff / tolr); 6256 } 6257 if(tol>0.){ 6258 max = PetscMax(max,diff / tol); 6259 } 6260 } 6261 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6262 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6263 } else if (ts->vatol) { /* vector atol, scalar rtol */ 6264 const PetscScalar *atol; 6265 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6266 for (i=0; i<n; i++) { 6267 diff = PetscAbsScalar(y[i] - u[i]); 6268 tola = PetscRealPart(atol[i]); 6269 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6270 tol = tola+tolr; 6271 if(tola>0.){ 6272 maxa = PetscMax(maxa,diff / tola); 6273 } 6274 if(tolr>0.){ 6275 maxr = PetscMax(maxr,diff / tolr); 6276 } 6277 if(tol>0.){ 6278 max = PetscMax(max,diff / tol); 6279 } 6280 } 6281 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6282 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 6283 const PetscScalar *rtol; 6284 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6285 6286 for (i=0; i<n; i++) { 6287 diff = PetscAbsScalar(y[i] - u[i]); 6288 tola = ts->atol; 6289 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6290 tol = tola+tolr; 6291 if(tola>0.){ 6292 maxa = PetscMax(maxa,diff / tola); 6293 } 6294 if(tolr>0.){ 6295 maxr = PetscMax(maxr,diff / tolr); 6296 } 6297 if(tol>0.){ 6298 max = PetscMax(max,diff / tol); 6299 } 6300 } 6301 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6302 } else { /* scalar atol, scalar rtol */ 6303 6304 for (i=0; i<n; i++) { 6305 diff = PetscAbsScalar(y[i] - u[i]); 6306 tola = ts->atol; 6307 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6308 tol = tola+tolr; 6309 if(tola>0.){ 6310 maxa = PetscMax(maxa,diff / tola); 6311 } 6312 if(tolr>0.){ 6313 maxr = PetscMax(maxr,diff / tolr); 6314 } 6315 if(tol>0.){ 6316 max = PetscMax(max,diff / tol); 6317 } 6318 } 6319 } 6320 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 6321 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 6322 err_loc[0] = max; 6323 err_loc[1] = maxa; 6324 err_loc[2] = maxr; 6325 ierr = MPIU_Allreduce(err_loc,err_glb,3,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6326 gmax = err_glb[0]; 6327 gmaxa = err_glb[1]; 6328 gmaxr = err_glb[2]; 6329 6330 *norm = gmax; 6331 *norma = gmaxa; 6332 *normr = gmaxr; 6333 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 6334 if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 6335 if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 6336 PetscFunctionReturn(0); 6337 } 6338 6339 /*@ 6340 TSErrorWeightedNorm - compute a weighted norm of the difference between two state vectors based on supplied absolute and relative tolerances 6341 6342 Collective on TS 6343 6344 Input Arguments: 6345 + ts - time stepping context 6346 . U - state vector, usually ts->vec_sol 6347 . Y - state vector to be compared to U 6348 - wnormtype - norm type, either NORM_2 or NORM_INFINITY 6349 6350 Output Arguments: 6351 . norm - weighted norm, a value of 1.0 achieves a balance between absolute and relative tolerances 6352 . norma - weighted norm, a value of 1.0 means that the error meets the absolute tolerance set by the user 6353 . normr - weighted norm, a value of 1.0 means that the error meets the relative tolerance set by the user 6354 6355 Options Database Keys: 6356 . -ts_adapt_wnormtype <wnormtype> - 2, INFINITY 6357 6358 Level: developer 6359 6360 .seealso: TSErrorWeightedNormInfinity(), TSErrorWeightedNorm2(), TSErrorWeightedENorm 6361 @*/ 6362 PetscErrorCode TSErrorWeightedNorm(TS ts,Vec U,Vec Y,NormType wnormtype,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6363 { 6364 PetscErrorCode ierr; 6365 6366 PetscFunctionBegin; 6367 if (wnormtype == NORM_2) { 6368 ierr = TSErrorWeightedNorm2(ts,U,Y,norm,norma,normr);CHKERRQ(ierr); 6369 } else if(wnormtype == NORM_INFINITY) { 6370 ierr = TSErrorWeightedNormInfinity(ts,U,Y,norm,norma,normr);CHKERRQ(ierr); 6371 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]); 6372 PetscFunctionReturn(0); 6373 } 6374 6375 6376 /*@ 6377 TSErrorWeightedENorm2 - compute a weighted 2 error norm based on supplied absolute and relative tolerances 6378 6379 Collective on TS 6380 6381 Input Arguments: 6382 + ts - time stepping context 6383 . E - error vector 6384 . U - state vector, usually ts->vec_sol 6385 - Y - state vector, previous time step 6386 6387 Output Arguments: 6388 . norm - weighted norm, a value of 1.0 means that the error matches the tolerances 6389 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 6390 . normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 6391 6392 Level: developer 6393 6394 .seealso: TSErrorWeightedENorm(), TSErrorWeightedENormInfinity() 6395 @*/ 6396 PetscErrorCode TSErrorWeightedENorm2(TS ts,Vec E,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6397 { 6398 PetscErrorCode ierr; 6399 PetscInt i,n,N,rstart; 6400 PetscInt n_loc,na_loc,nr_loc; 6401 PetscReal n_glb,na_glb,nr_glb; 6402 const PetscScalar *e,*u,*y; 6403 PetscReal err,sum,suma,sumr,gsum,gsuma,gsumr; 6404 PetscReal tol,tola,tolr; 6405 PetscReal err_loc[6],err_glb[6]; 6406 6407 PetscFunctionBegin; 6408 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6409 PetscValidHeaderSpecific(E,VEC_CLASSID,2); 6410 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 6411 PetscValidHeaderSpecific(Y,VEC_CLASSID,4); 6412 PetscValidType(E,2); 6413 PetscValidType(U,3); 6414 PetscValidType(Y,4); 6415 PetscCheckSameComm(E,2,U,3); 6416 PetscCheckSameComm(U,2,Y,3); 6417 PetscValidPointer(norm,5); 6418 PetscValidPointer(norma,6); 6419 PetscValidPointer(normr,7); 6420 6421 ierr = VecGetSize(E,&N);CHKERRQ(ierr); 6422 ierr = VecGetLocalSize(E,&n);CHKERRQ(ierr); 6423 ierr = VecGetOwnershipRange(E,&rstart,NULL);CHKERRQ(ierr); 6424 ierr = VecGetArrayRead(E,&e);CHKERRQ(ierr); 6425 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 6426 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 6427 sum = 0.; n_loc = 0; 6428 suma = 0.; na_loc = 0; 6429 sumr = 0.; nr_loc = 0; 6430 if (ts->vatol && ts->vrtol) { 6431 const PetscScalar *atol,*rtol; 6432 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6433 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6434 for (i=0; i<n; i++) { 6435 err = PetscAbsScalar(e[i]); 6436 tola = PetscRealPart(atol[i]); 6437 if(tola>0.){ 6438 suma += PetscSqr(err/tola); 6439 na_loc++; 6440 } 6441 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6442 if(tolr>0.){ 6443 sumr += PetscSqr(err/tolr); 6444 nr_loc++; 6445 } 6446 tol=tola+tolr; 6447 if(tol>0.){ 6448 sum += PetscSqr(err/tol); 6449 n_loc++; 6450 } 6451 } 6452 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6453 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6454 } else if (ts->vatol) { /* vector atol, scalar rtol */ 6455 const PetscScalar *atol; 6456 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6457 for (i=0; i<n; i++) { 6458 err = PetscAbsScalar(e[i]); 6459 tola = PetscRealPart(atol[i]); 6460 if(tola>0.){ 6461 suma += PetscSqr(err/tola); 6462 na_loc++; 6463 } 6464 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6465 if(tolr>0.){ 6466 sumr += PetscSqr(err/tolr); 6467 nr_loc++; 6468 } 6469 tol=tola+tolr; 6470 if(tol>0.){ 6471 sum += PetscSqr(err/tol); 6472 n_loc++; 6473 } 6474 } 6475 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6476 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 6477 const PetscScalar *rtol; 6478 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6479 for (i=0; i<n; i++) { 6480 err = PetscAbsScalar(e[i]); 6481 tola = ts->atol; 6482 if(tola>0.){ 6483 suma += PetscSqr(err/tola); 6484 na_loc++; 6485 } 6486 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6487 if(tolr>0.){ 6488 sumr += PetscSqr(err/tolr); 6489 nr_loc++; 6490 } 6491 tol=tola+tolr; 6492 if(tol>0.){ 6493 sum += PetscSqr(err/tol); 6494 n_loc++; 6495 } 6496 } 6497 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6498 } else { /* scalar atol, scalar rtol */ 6499 for (i=0; i<n; i++) { 6500 err = PetscAbsScalar(e[i]); 6501 tola = ts->atol; 6502 if(tola>0.){ 6503 suma += PetscSqr(err/tola); 6504 na_loc++; 6505 } 6506 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6507 if(tolr>0.){ 6508 sumr += PetscSqr(err/tolr); 6509 nr_loc++; 6510 } 6511 tol=tola+tolr; 6512 if(tol>0.){ 6513 sum += PetscSqr(err/tol); 6514 n_loc++; 6515 } 6516 } 6517 } 6518 ierr = VecRestoreArrayRead(E,&e);CHKERRQ(ierr); 6519 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 6520 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 6521 6522 err_loc[0] = sum; 6523 err_loc[1] = suma; 6524 err_loc[2] = sumr; 6525 err_loc[3] = (PetscReal)n_loc; 6526 err_loc[4] = (PetscReal)na_loc; 6527 err_loc[5] = (PetscReal)nr_loc; 6528 6529 ierr = MPIU_Allreduce(err_loc,err_glb,6,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6530 6531 gsum = err_glb[0]; 6532 gsuma = err_glb[1]; 6533 gsumr = err_glb[2]; 6534 n_glb = err_glb[3]; 6535 na_glb = err_glb[4]; 6536 nr_glb = err_glb[5]; 6537 6538 *norm = 0.; 6539 if(n_glb>0. ){*norm = PetscSqrtReal(gsum / n_glb );} 6540 *norma = 0.; 6541 if(na_glb>0.){*norma = PetscSqrtReal(gsuma / na_glb);} 6542 *normr = 0.; 6543 if(nr_glb>0.){*normr = PetscSqrtReal(gsumr / nr_glb);} 6544 6545 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 6546 if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 6547 if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 6548 PetscFunctionReturn(0); 6549 } 6550 6551 /*@ 6552 TSErrorWeightedENormInfinity - compute a weighted infinity error norm based on supplied absolute and relative tolerances 6553 Collective on TS 6554 6555 Input Arguments: 6556 + ts - time stepping context 6557 . E - error vector 6558 . U - state vector, usually ts->vec_sol 6559 - Y - state vector, previous time step 6560 6561 Output Arguments: 6562 . norm - weighted norm, a value of 1.0 means that the error matches the tolerances 6563 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 6564 . normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 6565 6566 Level: developer 6567 6568 .seealso: TSErrorWeightedENorm(), TSErrorWeightedENorm2() 6569 @*/ 6570 PetscErrorCode TSErrorWeightedENormInfinity(TS ts,Vec E,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6571 { 6572 PetscErrorCode ierr; 6573 PetscInt i,n,N,rstart; 6574 const PetscScalar *e,*u,*y; 6575 PetscReal err,max,gmax,maxa,gmaxa,maxr,gmaxr; 6576 PetscReal tol,tola,tolr; 6577 PetscReal err_loc[3],err_glb[3]; 6578 6579 PetscFunctionBegin; 6580 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6581 PetscValidHeaderSpecific(E,VEC_CLASSID,2); 6582 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 6583 PetscValidHeaderSpecific(Y,VEC_CLASSID,4); 6584 PetscValidType(E,2); 6585 PetscValidType(U,3); 6586 PetscValidType(Y,4); 6587 PetscCheckSameComm(E,2,U,3); 6588 PetscCheckSameComm(U,2,Y,3); 6589 PetscValidPointer(norm,5); 6590 PetscValidPointer(norma,6); 6591 PetscValidPointer(normr,7); 6592 6593 ierr = VecGetSize(E,&N);CHKERRQ(ierr); 6594 ierr = VecGetLocalSize(E,&n);CHKERRQ(ierr); 6595 ierr = VecGetOwnershipRange(E,&rstart,NULL);CHKERRQ(ierr); 6596 ierr = VecGetArrayRead(E,&e);CHKERRQ(ierr); 6597 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 6598 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 6599 6600 max=0.; 6601 maxa=0.; 6602 maxr=0.; 6603 6604 if (ts->vatol && ts->vrtol) { /* vector atol, vector rtol */ 6605 const PetscScalar *atol,*rtol; 6606 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6607 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6608 6609 for (i=0; i<n; i++) { 6610 err = PetscAbsScalar(e[i]); 6611 tola = PetscRealPart(atol[i]); 6612 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6613 tol = tola+tolr; 6614 if(tola>0.){ 6615 maxa = PetscMax(maxa,err / tola); 6616 } 6617 if(tolr>0.){ 6618 maxr = PetscMax(maxr,err / tolr); 6619 } 6620 if(tol>0.){ 6621 max = PetscMax(max,err / tol); 6622 } 6623 } 6624 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6625 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6626 } else if (ts->vatol) { /* vector atol, scalar rtol */ 6627 const PetscScalar *atol; 6628 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6629 for (i=0; i<n; i++) { 6630 err = PetscAbsScalar(e[i]); 6631 tola = PetscRealPart(atol[i]); 6632 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6633 tol = tola+tolr; 6634 if(tola>0.){ 6635 maxa = PetscMax(maxa,err / tola); 6636 } 6637 if(tolr>0.){ 6638 maxr = PetscMax(maxr,err / tolr); 6639 } 6640 if(tol>0.){ 6641 max = PetscMax(max,err / tol); 6642 } 6643 } 6644 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6645 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 6646 const PetscScalar *rtol; 6647 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6648 6649 for (i=0; i<n; i++) { 6650 err = PetscAbsScalar(e[i]); 6651 tola = ts->atol; 6652 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6653 tol = tola+tolr; 6654 if(tola>0.){ 6655 maxa = PetscMax(maxa,err / tola); 6656 } 6657 if(tolr>0.){ 6658 maxr = PetscMax(maxr,err / tolr); 6659 } 6660 if(tol>0.){ 6661 max = PetscMax(max,err / tol); 6662 } 6663 } 6664 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6665 } else { /* scalar atol, scalar rtol */ 6666 6667 for (i=0; i<n; i++) { 6668 err = PetscAbsScalar(e[i]); 6669 tola = ts->atol; 6670 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6671 tol = tola+tolr; 6672 if(tola>0.){ 6673 maxa = PetscMax(maxa,err / tola); 6674 } 6675 if(tolr>0.){ 6676 maxr = PetscMax(maxr,err / tolr); 6677 } 6678 if(tol>0.){ 6679 max = PetscMax(max,err / tol); 6680 } 6681 } 6682 } 6683 ierr = VecRestoreArrayRead(E,&e);CHKERRQ(ierr); 6684 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 6685 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 6686 err_loc[0] = max; 6687 err_loc[1] = maxa; 6688 err_loc[2] = maxr; 6689 ierr = MPIU_Allreduce(err_loc,err_glb,3,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6690 gmax = err_glb[0]; 6691 gmaxa = err_glb[1]; 6692 gmaxr = err_glb[2]; 6693 6694 *norm = gmax; 6695 *norma = gmaxa; 6696 *normr = gmaxr; 6697 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 6698 if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 6699 if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 6700 PetscFunctionReturn(0); 6701 } 6702 6703 /*@ 6704 TSErrorWeightedENorm - compute a weighted error norm based on supplied absolute and relative tolerances 6705 6706 Collective on TS 6707 6708 Input Arguments: 6709 + ts - time stepping context 6710 . E - error vector 6711 . U - state vector, usually ts->vec_sol 6712 . Y - state vector, previous time step 6713 - wnormtype - norm type, either NORM_2 or NORM_INFINITY 6714 6715 Output Arguments: 6716 . norm - weighted norm, a value of 1.0 achieves a balance between absolute and relative tolerances 6717 . norma - weighted norm, a value of 1.0 means that the error meets the absolute tolerance set by the user 6718 . normr - weighted norm, a value of 1.0 means that the error meets the relative tolerance set by the user 6719 6720 Options Database Keys: 6721 . -ts_adapt_wnormtype <wnormtype> - 2, INFINITY 6722 6723 Level: developer 6724 6725 .seealso: TSErrorWeightedENormInfinity(), TSErrorWeightedENorm2(), TSErrorWeightedNormInfinity(), TSErrorWeightedNorm2() 6726 @*/ 6727 PetscErrorCode TSErrorWeightedENorm(TS ts,Vec E,Vec U,Vec Y,NormType wnormtype,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6728 { 6729 PetscErrorCode ierr; 6730 6731 PetscFunctionBegin; 6732 if (wnormtype == NORM_2) { 6733 ierr = TSErrorWeightedENorm2(ts,E,U,Y,norm,norma,normr);CHKERRQ(ierr); 6734 } else if(wnormtype == NORM_INFINITY) { 6735 ierr = TSErrorWeightedENormInfinity(ts,E,U,Y,norm,norma,normr);CHKERRQ(ierr); 6736 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]); 6737 PetscFunctionReturn(0); 6738 } 6739 6740 6741 /*@ 6742 TSSetCFLTimeLocal - Set the local CFL constraint relative to forward Euler 6743 6744 Logically Collective on TS 6745 6746 Input Arguments: 6747 + ts - time stepping context 6748 - cfltime - maximum stable time step if using forward Euler (value can be different on each process) 6749 6750 Note: 6751 After calling this function, the global CFL time can be obtained by calling TSGetCFLTime() 6752 6753 Level: intermediate 6754 6755 .seealso: TSGetCFLTime(), TSADAPTCFL 6756 @*/ 6757 PetscErrorCode TSSetCFLTimeLocal(TS ts,PetscReal cfltime) 6758 { 6759 PetscFunctionBegin; 6760 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6761 ts->cfltime_local = cfltime; 6762 ts->cfltime = -1.; 6763 PetscFunctionReturn(0); 6764 } 6765 6766 /*@ 6767 TSGetCFLTime - Get the maximum stable time step according to CFL criteria applied to forward Euler 6768 6769 Collective on TS 6770 6771 Input Arguments: 6772 . ts - time stepping context 6773 6774 Output Arguments: 6775 . cfltime - maximum stable time step for forward Euler 6776 6777 Level: advanced 6778 6779 .seealso: TSSetCFLTimeLocal() 6780 @*/ 6781 PetscErrorCode TSGetCFLTime(TS ts,PetscReal *cfltime) 6782 { 6783 PetscErrorCode ierr; 6784 6785 PetscFunctionBegin; 6786 if (ts->cfltime < 0) { 6787 ierr = MPIU_Allreduce(&ts->cfltime_local,&ts->cfltime,1,MPIU_REAL,MPIU_MIN,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6788 } 6789 *cfltime = ts->cfltime; 6790 PetscFunctionReturn(0); 6791 } 6792 6793 /*@ 6794 TSVISetVariableBounds - Sets the lower and upper bounds for the solution vector. xl <= x <= xu 6795 6796 Input Parameters: 6797 . ts - the TS context. 6798 . xl - lower bound. 6799 . xu - upper bound. 6800 6801 Notes: 6802 If this routine is not called then the lower and upper bounds are set to 6803 PETSC_NINFINITY and PETSC_INFINITY respectively during SNESSetUp(). 6804 6805 Level: advanced 6806 6807 @*/ 6808 PetscErrorCode TSVISetVariableBounds(TS ts, Vec xl, Vec xu) 6809 { 6810 PetscErrorCode ierr; 6811 SNES snes; 6812 6813 PetscFunctionBegin; 6814 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 6815 ierr = SNESVISetVariableBounds(snes,xl,xu);CHKERRQ(ierr); 6816 PetscFunctionReturn(0); 6817 } 6818 6819 #if defined(PETSC_HAVE_MATLAB_ENGINE) 6820 #include <mex.h> 6821 6822 typedef struct {char *funcname; mxArray *ctx;} TSMatlabContext; 6823 6824 /* 6825 TSComputeFunction_Matlab - Calls the function that has been set with 6826 TSSetFunctionMatlab(). 6827 6828 Collective on TS 6829 6830 Input Parameters: 6831 + snes - the TS context 6832 - u - input vector 6833 6834 Output Parameter: 6835 . y - function vector, as set by TSSetFunction() 6836 6837 Notes: 6838 TSComputeFunction() is typically used within nonlinear solvers 6839 implementations, so most users would not generally call this routine 6840 themselves. 6841 6842 Level: developer 6843 6844 .keywords: TS, nonlinear, compute, function 6845 6846 .seealso: TSSetFunction(), TSGetFunction() 6847 */ 6848 PetscErrorCode TSComputeFunction_Matlab(TS snes,PetscReal time,Vec u,Vec udot,Vec y, void *ctx) 6849 { 6850 PetscErrorCode ierr; 6851 TSMatlabContext *sctx = (TSMatlabContext*)ctx; 6852 int nlhs = 1,nrhs = 7; 6853 mxArray *plhs[1],*prhs[7]; 6854 long long int lx = 0,lxdot = 0,ly = 0,ls = 0; 6855 6856 PetscFunctionBegin; 6857 PetscValidHeaderSpecific(snes,TS_CLASSID,1); 6858 PetscValidHeaderSpecific(u,VEC_CLASSID,3); 6859 PetscValidHeaderSpecific(udot,VEC_CLASSID,4); 6860 PetscValidHeaderSpecific(y,VEC_CLASSID,5); 6861 PetscCheckSameComm(snes,1,u,3); 6862 PetscCheckSameComm(snes,1,y,5); 6863 6864 ierr = PetscMemcpy(&ls,&snes,sizeof(snes));CHKERRQ(ierr); 6865 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 6866 ierr = PetscMemcpy(&lxdot,&udot,sizeof(udot));CHKERRQ(ierr); 6867 ierr = PetscMemcpy(&ly,&y,sizeof(u));CHKERRQ(ierr); 6868 6869 prhs[0] = mxCreateDoubleScalar((double)ls); 6870 prhs[1] = mxCreateDoubleScalar(time); 6871 prhs[2] = mxCreateDoubleScalar((double)lx); 6872 prhs[3] = mxCreateDoubleScalar((double)lxdot); 6873 prhs[4] = mxCreateDoubleScalar((double)ly); 6874 prhs[5] = mxCreateString(sctx->funcname); 6875 prhs[6] = sctx->ctx; 6876 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSComputeFunctionInternal");CHKERRQ(ierr); 6877 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 6878 mxDestroyArray(prhs[0]); 6879 mxDestroyArray(prhs[1]); 6880 mxDestroyArray(prhs[2]); 6881 mxDestroyArray(prhs[3]); 6882 mxDestroyArray(prhs[4]); 6883 mxDestroyArray(prhs[5]); 6884 mxDestroyArray(plhs[0]); 6885 PetscFunctionReturn(0); 6886 } 6887 6888 /* 6889 TSSetFunctionMatlab - Sets the function evaluation routine and function 6890 vector for use by the TS routines in solving ODEs 6891 equations from MATLAB. Here the function is a string containing the name of a MATLAB function 6892 6893 Logically Collective on TS 6894 6895 Input Parameters: 6896 + ts - the TS context 6897 - func - function evaluation routine 6898 6899 Calling sequence of func: 6900 $ func (TS ts,PetscReal time,Vec u,Vec udot,Vec f,void *ctx); 6901 6902 Level: beginner 6903 6904 .keywords: TS, nonlinear, set, function 6905 6906 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 6907 */ 6908 PetscErrorCode TSSetFunctionMatlab(TS ts,const char *func,mxArray *ctx) 6909 { 6910 PetscErrorCode ierr; 6911 TSMatlabContext *sctx; 6912 6913 PetscFunctionBegin; 6914 /* currently sctx is memory bleed */ 6915 ierr = PetscNew(&sctx);CHKERRQ(ierr); 6916 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 6917 /* 6918 This should work, but it doesn't 6919 sctx->ctx = ctx; 6920 mexMakeArrayPersistent(sctx->ctx); 6921 */ 6922 sctx->ctx = mxDuplicateArray(ctx); 6923 6924 ierr = TSSetIFunction(ts,NULL,TSComputeFunction_Matlab,sctx);CHKERRQ(ierr); 6925 PetscFunctionReturn(0); 6926 } 6927 6928 /* 6929 TSComputeJacobian_Matlab - Calls the function that has been set with 6930 TSSetJacobianMatlab(). 6931 6932 Collective on TS 6933 6934 Input Parameters: 6935 + ts - the TS context 6936 . u - input vector 6937 . A, B - the matrices 6938 - ctx - user context 6939 6940 Level: developer 6941 6942 .keywords: TS, nonlinear, compute, function 6943 6944 .seealso: TSSetFunction(), TSGetFunction() 6945 @*/ 6946 PetscErrorCode TSComputeJacobian_Matlab(TS ts,PetscReal time,Vec u,Vec udot,PetscReal shift,Mat A,Mat B,void *ctx) 6947 { 6948 PetscErrorCode ierr; 6949 TSMatlabContext *sctx = (TSMatlabContext*)ctx; 6950 int nlhs = 2,nrhs = 9; 6951 mxArray *plhs[2],*prhs[9]; 6952 long long int lx = 0,lxdot = 0,lA = 0,ls = 0, lB = 0; 6953 6954 PetscFunctionBegin; 6955 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6956 PetscValidHeaderSpecific(u,VEC_CLASSID,3); 6957 6958 /* call Matlab function in ctx with arguments u and y */ 6959 6960 ierr = PetscMemcpy(&ls,&ts,sizeof(ts));CHKERRQ(ierr); 6961 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 6962 ierr = PetscMemcpy(&lxdot,&udot,sizeof(u));CHKERRQ(ierr); 6963 ierr = PetscMemcpy(&lA,A,sizeof(u));CHKERRQ(ierr); 6964 ierr = PetscMemcpy(&lB,B,sizeof(u));CHKERRQ(ierr); 6965 6966 prhs[0] = mxCreateDoubleScalar((double)ls); 6967 prhs[1] = mxCreateDoubleScalar((double)time); 6968 prhs[2] = mxCreateDoubleScalar((double)lx); 6969 prhs[3] = mxCreateDoubleScalar((double)lxdot); 6970 prhs[4] = mxCreateDoubleScalar((double)shift); 6971 prhs[5] = mxCreateDoubleScalar((double)lA); 6972 prhs[6] = mxCreateDoubleScalar((double)lB); 6973 prhs[7] = mxCreateString(sctx->funcname); 6974 prhs[8] = sctx->ctx; 6975 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSComputeJacobianInternal");CHKERRQ(ierr); 6976 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 6977 mxDestroyArray(prhs[0]); 6978 mxDestroyArray(prhs[1]); 6979 mxDestroyArray(prhs[2]); 6980 mxDestroyArray(prhs[3]); 6981 mxDestroyArray(prhs[4]); 6982 mxDestroyArray(prhs[5]); 6983 mxDestroyArray(prhs[6]); 6984 mxDestroyArray(prhs[7]); 6985 mxDestroyArray(plhs[0]); 6986 mxDestroyArray(plhs[1]); 6987 PetscFunctionReturn(0); 6988 } 6989 6990 /* 6991 TSSetJacobianMatlab - Sets the Jacobian function evaluation routine and two empty Jacobian matrices 6992 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 6993 6994 Logically Collective on TS 6995 6996 Input Parameters: 6997 + ts - the TS context 6998 . A,B - Jacobian matrices 6999 . func - function evaluation routine 7000 - ctx - user context 7001 7002 Calling sequence of func: 7003 $ flag = func (TS ts,PetscReal time,Vec u,Vec udot,Mat A,Mat B,void *ctx); 7004 7005 Level: developer 7006 7007 .keywords: TS, nonlinear, set, function 7008 7009 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 7010 */ 7011 PetscErrorCode TSSetJacobianMatlab(TS ts,Mat A,Mat B,const char *func,mxArray *ctx) 7012 { 7013 PetscErrorCode ierr; 7014 TSMatlabContext *sctx; 7015 7016 PetscFunctionBegin; 7017 /* currently sctx is memory bleed */ 7018 ierr = PetscNew(&sctx);CHKERRQ(ierr); 7019 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 7020 /* 7021 This should work, but it doesn't 7022 sctx->ctx = ctx; 7023 mexMakeArrayPersistent(sctx->ctx); 7024 */ 7025 sctx->ctx = mxDuplicateArray(ctx); 7026 7027 ierr = TSSetIJacobian(ts,A,B,TSComputeJacobian_Matlab,sctx);CHKERRQ(ierr); 7028 PetscFunctionReturn(0); 7029 } 7030 7031 /* 7032 TSMonitor_Matlab - Calls the function that has been set with TSMonitorSetMatlab(). 7033 7034 Collective on TS 7035 7036 .seealso: TSSetFunction(), TSGetFunction() 7037 @*/ 7038 PetscErrorCode TSMonitor_Matlab(TS ts,PetscInt it, PetscReal time,Vec u, void *ctx) 7039 { 7040 PetscErrorCode ierr; 7041 TSMatlabContext *sctx = (TSMatlabContext*)ctx; 7042 int nlhs = 1,nrhs = 6; 7043 mxArray *plhs[1],*prhs[6]; 7044 long long int lx = 0,ls = 0; 7045 7046 PetscFunctionBegin; 7047 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 7048 PetscValidHeaderSpecific(u,VEC_CLASSID,4); 7049 7050 ierr = PetscMemcpy(&ls,&ts,sizeof(ts));CHKERRQ(ierr); 7051 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 7052 7053 prhs[0] = mxCreateDoubleScalar((double)ls); 7054 prhs[1] = mxCreateDoubleScalar((double)it); 7055 prhs[2] = mxCreateDoubleScalar((double)time); 7056 prhs[3] = mxCreateDoubleScalar((double)lx); 7057 prhs[4] = mxCreateString(sctx->funcname); 7058 prhs[5] = sctx->ctx; 7059 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSMonitorInternal");CHKERRQ(ierr); 7060 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 7061 mxDestroyArray(prhs[0]); 7062 mxDestroyArray(prhs[1]); 7063 mxDestroyArray(prhs[2]); 7064 mxDestroyArray(prhs[3]); 7065 mxDestroyArray(prhs[4]); 7066 mxDestroyArray(plhs[0]); 7067 PetscFunctionReturn(0); 7068 } 7069 7070 /* 7071 TSMonitorSetMatlab - Sets the monitor function from Matlab 7072 7073 Level: developer 7074 7075 .keywords: TS, nonlinear, set, function 7076 7077 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 7078 */ 7079 PetscErrorCode TSMonitorSetMatlab(TS ts,const char *func,mxArray *ctx) 7080 { 7081 PetscErrorCode ierr; 7082 TSMatlabContext *sctx; 7083 7084 PetscFunctionBegin; 7085 /* currently sctx is memory bleed */ 7086 ierr = PetscNew(&sctx);CHKERRQ(ierr); 7087 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 7088 /* 7089 This should work, but it doesn't 7090 sctx->ctx = ctx; 7091 mexMakeArrayPersistent(sctx->ctx); 7092 */ 7093 sctx->ctx = mxDuplicateArray(ctx); 7094 7095 ierr = TSMonitorSet(ts,TSMonitor_Matlab,sctx,NULL);CHKERRQ(ierr); 7096 PetscFunctionReturn(0); 7097 } 7098 #endif 7099 7100 /*@C 7101 TSMonitorLGSolution - Monitors progress of the TS solvers by plotting each component of the solution vector 7102 in a time based line graph 7103 7104 Collective on TS 7105 7106 Input Parameters: 7107 + ts - the TS context 7108 . step - current time-step 7109 . ptime - current time 7110 . u - current solution 7111 - dctx - the TSMonitorLGCtx object that contains all the options for the monitoring, this is created with TSMonitorLGCtxCreate() 7112 7113 Options Database: 7114 . -ts_monitor_lg_solution_variables 7115 7116 Level: intermediate 7117 7118 Notes: Each process in a parallel run displays its component solutions in a separate window 7119 7120 .keywords: TS, vector, monitor, view 7121 7122 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGCtxCreate(), TSMonitorLGCtxSetVariableNames(), TSMonitorLGCtxGetVariableNames(), 7123 TSMonitorLGSetVariableNames(), TSMonitorLGGetVariableNames(), TSMonitorLGSetDisplayVariables(), TSMonitorLGCtxSetDisplayVariables(), 7124 TSMonitorLGCtxSetTransform(), TSMonitorLGSetTransform(), TSMonitorLGError(), TSMonitorLGSNESIterations(), TSMonitorLGKSPIterations(), 7125 TSMonitorEnvelopeCtxCreate(), TSMonitorEnvelopeGetBounds(), TSMonitorEnvelopeCtxDestroy(), TSMonitorEnvelop() 7126 @*/ 7127 PetscErrorCode TSMonitorLGSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dctx) 7128 { 7129 PetscErrorCode ierr; 7130 TSMonitorLGCtx ctx = (TSMonitorLGCtx)dctx; 7131 const PetscScalar *yy; 7132 Vec v; 7133 7134 PetscFunctionBegin; 7135 if (step < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */ 7136 if (!step) { 7137 PetscDrawAxis axis; 7138 PetscInt dim; 7139 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 7140 ierr = PetscDrawAxisSetLabels(axis,"Solution as function of time","Time","Solution");CHKERRQ(ierr); 7141 if (!ctx->names) { 7142 PetscBool flg; 7143 /* user provides names of variables to plot but no names has been set so assume names are integer values */ 7144 ierr = PetscOptionsHasName(((PetscObject)ts)->options,((PetscObject)ts)->prefix,"-ts_monitor_lg_solution_variables",&flg);CHKERRQ(ierr); 7145 if (flg) { 7146 PetscInt i,n; 7147 char **names; 7148 ierr = VecGetSize(u,&n);CHKERRQ(ierr); 7149 ierr = PetscMalloc1(n+1,&names);CHKERRQ(ierr); 7150 for (i=0; i<n; i++) { 7151 ierr = PetscMalloc1(5,&names[i]);CHKERRQ(ierr); 7152 ierr = PetscSNPrintf(names[i],5,"%D",i);CHKERRQ(ierr); 7153 } 7154 names[n] = NULL; 7155 ctx->names = names; 7156 } 7157 } 7158 if (ctx->names && !ctx->displaynames) { 7159 char **displaynames; 7160 PetscBool flg; 7161 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 7162 ierr = PetscMalloc1(dim+1,&displaynames);CHKERRQ(ierr); 7163 ierr = PetscMemzero(displaynames,(dim+1)*sizeof(char*));CHKERRQ(ierr); 7164 ierr = PetscOptionsGetStringArray(((PetscObject)ts)->options,((PetscObject)ts)->prefix,"-ts_monitor_lg_solution_variables",displaynames,&dim,&flg);CHKERRQ(ierr); 7165 if (flg) { 7166 ierr = TSMonitorLGCtxSetDisplayVariables(ctx,(const char *const *)displaynames);CHKERRQ(ierr); 7167 } 7168 ierr = PetscStrArrayDestroy(&displaynames);CHKERRQ(ierr); 7169 } 7170 if (ctx->displaynames) { 7171 ierr = PetscDrawLGSetDimension(ctx->lg,ctx->ndisplayvariables);CHKERRQ(ierr); 7172 ierr = PetscDrawLGSetLegend(ctx->lg,(const char *const *)ctx->displaynames);CHKERRQ(ierr); 7173 } else if (ctx->names) { 7174 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 7175 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 7176 ierr = PetscDrawLGSetLegend(ctx->lg,(const char *const *)ctx->names);CHKERRQ(ierr); 7177 } else { 7178 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 7179 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 7180 } 7181 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 7182 } 7183 7184 if (!ctx->transform) v = u; 7185 else {ierr = (*ctx->transform)(ctx->transformctx,u,&v);CHKERRQ(ierr);} 7186 ierr = VecGetArrayRead(v,&yy);CHKERRQ(ierr); 7187 if (ctx->displaynames) { 7188 PetscInt i; 7189 for (i=0; i<ctx->ndisplayvariables; i++) 7190 ctx->displayvalues[i] = PetscRealPart(yy[ctx->displayvariables[i]]); 7191 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,ctx->displayvalues);CHKERRQ(ierr); 7192 } else { 7193 #if defined(PETSC_USE_COMPLEX) 7194 PetscInt i,n; 7195 PetscReal *yreal; 7196 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 7197 ierr = PetscMalloc1(n,&yreal);CHKERRQ(ierr); 7198 for (i=0; i<n; i++) yreal[i] = PetscRealPart(yy[i]); 7199 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yreal);CHKERRQ(ierr); 7200 ierr = PetscFree(yreal);CHKERRQ(ierr); 7201 #else 7202 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yy);CHKERRQ(ierr); 7203 #endif 7204 } 7205 ierr = VecRestoreArrayRead(v,&yy);CHKERRQ(ierr); 7206 if (ctx->transform) {ierr = VecDestroy(&v);CHKERRQ(ierr);} 7207 7208 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 7209 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 7210 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 7211 } 7212 PetscFunctionReturn(0); 7213 } 7214 7215 /*@C 7216 TSMonitorLGSetVariableNames - Sets the name of each component in the solution vector so that it may be displayed in the plot 7217 7218 Collective on TS 7219 7220 Input Parameters: 7221 + ts - the TS context 7222 - names - the names of the components, final string must be NULL 7223 7224 Level: intermediate 7225 7226 Notes: If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored 7227 7228 .keywords: TS, vector, monitor, view 7229 7230 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables(), TSMonitorLGCtxSetVariableNames() 7231 @*/ 7232 PetscErrorCode TSMonitorLGSetVariableNames(TS ts,const char * const *names) 7233 { 7234 PetscErrorCode ierr; 7235 PetscInt i; 7236 7237 PetscFunctionBegin; 7238 for (i=0; i<ts->numbermonitors; i++) { 7239 if (ts->monitor[i] == TSMonitorLGSolution) { 7240 ierr = TSMonitorLGCtxSetVariableNames((TSMonitorLGCtx)ts->monitorcontext[i],names);CHKERRQ(ierr); 7241 break; 7242 } 7243 } 7244 PetscFunctionReturn(0); 7245 } 7246 7247 /*@C 7248 TSMonitorLGCtxSetVariableNames - 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 .keywords: TS, vector, monitor, view 7259 7260 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables(), TSMonitorLGSetVariableNames() 7261 @*/ 7262 PetscErrorCode TSMonitorLGCtxSetVariableNames(TSMonitorLGCtx ctx,const char * const *names) 7263 { 7264 PetscErrorCode ierr; 7265 7266 PetscFunctionBegin; 7267 ierr = PetscStrArrayDestroy(&ctx->names);CHKERRQ(ierr); 7268 ierr = PetscStrArrayallocpy(names,&ctx->names);CHKERRQ(ierr); 7269 PetscFunctionReturn(0); 7270 } 7271 7272 /*@C 7273 TSMonitorLGGetVariableNames - Gets the name of each component in the solution vector so that it may be displayed in the plot 7274 7275 Collective on TS 7276 7277 Input Parameter: 7278 . ts - the TS context 7279 7280 Output Parameter: 7281 . names - the names of the components, final string must be NULL 7282 7283 Level: intermediate 7284 7285 Notes: If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored 7286 7287 .keywords: TS, vector, monitor, view 7288 7289 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables() 7290 @*/ 7291 PetscErrorCode TSMonitorLGGetVariableNames(TS ts,const char *const **names) 7292 { 7293 PetscInt i; 7294 7295 PetscFunctionBegin; 7296 *names = NULL; 7297 for (i=0; i<ts->numbermonitors; i++) { 7298 if (ts->monitor[i] == TSMonitorLGSolution) { 7299 TSMonitorLGCtx ctx = (TSMonitorLGCtx) ts->monitorcontext[i]; 7300 *names = (const char *const *)ctx->names; 7301 break; 7302 } 7303 } 7304 PetscFunctionReturn(0); 7305 } 7306 7307 /*@C 7308 TSMonitorLGCtxSetDisplayVariables - Sets the variables that are to be display in the monitor 7309 7310 Collective on TS 7311 7312 Input Parameters: 7313 + ctx - the TSMonitorLG context 7314 . displaynames - the names of the components, final string must be NULL 7315 7316 Level: intermediate 7317 7318 .keywords: TS, vector, monitor, view 7319 7320 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames() 7321 @*/ 7322 PetscErrorCode TSMonitorLGCtxSetDisplayVariables(TSMonitorLGCtx ctx,const char * const *displaynames) 7323 { 7324 PetscInt j = 0,k; 7325 PetscErrorCode ierr; 7326 7327 PetscFunctionBegin; 7328 if (!ctx->names) PetscFunctionReturn(0); 7329 ierr = PetscStrArrayDestroy(&ctx->displaynames);CHKERRQ(ierr); 7330 ierr = PetscStrArrayallocpy(displaynames,&ctx->displaynames);CHKERRQ(ierr); 7331 while (displaynames[j]) j++; 7332 ctx->ndisplayvariables = j; 7333 ierr = PetscMalloc1(ctx->ndisplayvariables,&ctx->displayvariables);CHKERRQ(ierr); 7334 ierr = PetscMalloc1(ctx->ndisplayvariables,&ctx->displayvalues);CHKERRQ(ierr); 7335 j = 0; 7336 while (displaynames[j]) { 7337 k = 0; 7338 while (ctx->names[k]) { 7339 PetscBool flg; 7340 ierr = PetscStrcmp(displaynames[j],ctx->names[k],&flg);CHKERRQ(ierr); 7341 if (flg) { 7342 ctx->displayvariables[j] = k; 7343 break; 7344 } 7345 k++; 7346 } 7347 j++; 7348 } 7349 PetscFunctionReturn(0); 7350 } 7351 7352 /*@C 7353 TSMonitorLGSetDisplayVariables - Sets the variables that are to be display in the monitor 7354 7355 Collective on TS 7356 7357 Input Parameters: 7358 + ts - the TS context 7359 . displaynames - the names of the components, final string must be NULL 7360 7361 Notes: If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored 7362 7363 Level: intermediate 7364 7365 .keywords: TS, vector, monitor, view 7366 7367 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames() 7368 @*/ 7369 PetscErrorCode TSMonitorLGSetDisplayVariables(TS ts,const char * const *displaynames) 7370 { 7371 PetscInt i; 7372 PetscErrorCode ierr; 7373 7374 PetscFunctionBegin; 7375 for (i=0; i<ts->numbermonitors; i++) { 7376 if (ts->monitor[i] == TSMonitorLGSolution) { 7377 ierr = TSMonitorLGCtxSetDisplayVariables((TSMonitorLGCtx)ts->monitorcontext[i],displaynames);CHKERRQ(ierr); 7378 break; 7379 } 7380 } 7381 PetscFunctionReturn(0); 7382 } 7383 7384 /*@C 7385 TSMonitorLGSetTransform - Solution vector will be transformed by provided function before being displayed 7386 7387 Collective on TS 7388 7389 Input Parameters: 7390 + ts - the TS context 7391 . transform - the transform function 7392 . destroy - function to destroy the optional context 7393 - ctx - optional context used by transform function 7394 7395 Notes: If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored 7396 7397 Level: intermediate 7398 7399 .keywords: TS, vector, monitor, view 7400 7401 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames(), TSMonitorLGCtxSetTransform() 7402 @*/ 7403 PetscErrorCode TSMonitorLGSetTransform(TS ts,PetscErrorCode (*transform)(void*,Vec,Vec*),PetscErrorCode (*destroy)(void*),void *tctx) 7404 { 7405 PetscInt i; 7406 PetscErrorCode ierr; 7407 7408 PetscFunctionBegin; 7409 for (i=0; i<ts->numbermonitors; i++) { 7410 if (ts->monitor[i] == TSMonitorLGSolution) { 7411 ierr = TSMonitorLGCtxSetTransform((TSMonitorLGCtx)ts->monitorcontext[i],transform,destroy,tctx);CHKERRQ(ierr); 7412 } 7413 } 7414 PetscFunctionReturn(0); 7415 } 7416 7417 /*@C 7418 TSMonitorLGCtxSetTransform - Solution vector will be transformed by provided function before being displayed 7419 7420 Collective on TSLGCtx 7421 7422 Input Parameters: 7423 + ts - the TS context 7424 . transform - the transform function 7425 . destroy - function to destroy the optional context 7426 - ctx - optional context used by transform function 7427 7428 Level: intermediate 7429 7430 .keywords: TS, vector, monitor, view 7431 7432 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames(), TSMonitorLGSetTransform() 7433 @*/ 7434 PetscErrorCode TSMonitorLGCtxSetTransform(TSMonitorLGCtx ctx,PetscErrorCode (*transform)(void*,Vec,Vec*),PetscErrorCode (*destroy)(void*),void *tctx) 7435 { 7436 PetscFunctionBegin; 7437 ctx->transform = transform; 7438 ctx->transformdestroy = destroy; 7439 ctx->transformctx = tctx; 7440 PetscFunctionReturn(0); 7441 } 7442 7443 /*@C 7444 TSMonitorLGError - Monitors progress of the TS solvers by plotting each component of the error 7445 in a time based line graph 7446 7447 Collective on TS 7448 7449 Input Parameters: 7450 + ts - the TS context 7451 . step - current time-step 7452 . ptime - current time 7453 . u - current solution 7454 - dctx - TSMonitorLGCtx object created with TSMonitorLGCtxCreate() 7455 7456 Level: intermediate 7457 7458 Notes: Each process in a parallel run displays its component errors in a separate window 7459 7460 The user must provide the solution using TSSetSolutionFunction() to use this monitor. 7461 7462 Options Database Keys: 7463 . -ts_monitor_lg_error - create a graphical monitor of error history 7464 7465 .keywords: TS, vector, monitor, view 7466 7467 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSSetSolutionFunction() 7468 @*/ 7469 PetscErrorCode TSMonitorLGError(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 7470 { 7471 PetscErrorCode ierr; 7472 TSMonitorLGCtx ctx = (TSMonitorLGCtx)dummy; 7473 const PetscScalar *yy; 7474 Vec y; 7475 7476 PetscFunctionBegin; 7477 if (!step) { 7478 PetscDrawAxis axis; 7479 PetscInt dim; 7480 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 7481 ierr = PetscDrawAxisSetLabels(axis,"Error in solution as function of time","Time","Error");CHKERRQ(ierr); 7482 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 7483 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 7484 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 7485 } 7486 ierr = VecDuplicate(u,&y);CHKERRQ(ierr); 7487 ierr = TSComputeSolutionFunction(ts,ptime,y);CHKERRQ(ierr); 7488 ierr = VecAXPY(y,-1.0,u);CHKERRQ(ierr); 7489 ierr = VecGetArrayRead(y,&yy);CHKERRQ(ierr); 7490 #if defined(PETSC_USE_COMPLEX) 7491 { 7492 PetscReal *yreal; 7493 PetscInt i,n; 7494 ierr = VecGetLocalSize(y,&n);CHKERRQ(ierr); 7495 ierr = PetscMalloc1(n,&yreal);CHKERRQ(ierr); 7496 for (i=0; i<n; i++) yreal[i] = PetscRealPart(yy[i]); 7497 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yreal);CHKERRQ(ierr); 7498 ierr = PetscFree(yreal);CHKERRQ(ierr); 7499 } 7500 #else 7501 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yy);CHKERRQ(ierr); 7502 #endif 7503 ierr = VecRestoreArrayRead(y,&yy);CHKERRQ(ierr); 7504 ierr = VecDestroy(&y);CHKERRQ(ierr); 7505 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 7506 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 7507 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 7508 } 7509 PetscFunctionReturn(0); 7510 } 7511 7512 PetscErrorCode TSMonitorLGSNESIterations(TS ts,PetscInt n,PetscReal ptime,Vec v,void *monctx) 7513 { 7514 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 7515 PetscReal x = ptime,y; 7516 PetscErrorCode ierr; 7517 PetscInt its; 7518 7519 PetscFunctionBegin; 7520 if (n < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */ 7521 if (!n) { 7522 PetscDrawAxis axis; 7523 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 7524 ierr = PetscDrawAxisSetLabels(axis,"Nonlinear iterations as function of time","Time","SNES Iterations");CHKERRQ(ierr); 7525 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 7526 ctx->snes_its = 0; 7527 } 7528 ierr = TSGetSNESIterations(ts,&its);CHKERRQ(ierr); 7529 y = its - ctx->snes_its; 7530 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 7531 if (((ctx->howoften > 0) && (!(n % ctx->howoften)) && (n > -1)) || ((ctx->howoften == -1) && (n == -1))) { 7532 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 7533 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 7534 } 7535 ctx->snes_its = its; 7536 PetscFunctionReturn(0); 7537 } 7538 7539 PetscErrorCode TSMonitorLGKSPIterations(TS ts,PetscInt n,PetscReal ptime,Vec v,void *monctx) 7540 { 7541 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 7542 PetscReal x = ptime,y; 7543 PetscErrorCode ierr; 7544 PetscInt its; 7545 7546 PetscFunctionBegin; 7547 if (n < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */ 7548 if (!n) { 7549 PetscDrawAxis axis; 7550 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 7551 ierr = PetscDrawAxisSetLabels(axis,"Linear iterations as function of time","Time","KSP Iterations");CHKERRQ(ierr); 7552 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 7553 ctx->ksp_its = 0; 7554 } 7555 ierr = TSGetKSPIterations(ts,&its);CHKERRQ(ierr); 7556 y = its - ctx->ksp_its; 7557 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 7558 if (((ctx->howoften > 0) && (!(n % ctx->howoften)) && (n > -1)) || ((ctx->howoften == -1) && (n == -1))) { 7559 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 7560 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 7561 } 7562 ctx->ksp_its = its; 7563 PetscFunctionReturn(0); 7564 } 7565 7566 /*@ 7567 TSComputeLinearStability - computes the linear stability function at a point 7568 7569 Collective on TS and Vec 7570 7571 Input Parameters: 7572 + ts - the TS context 7573 - xr,xi - real and imaginary part of input arguments 7574 7575 Output Parameters: 7576 . yr,yi - real and imaginary part of function value 7577 7578 Level: developer 7579 7580 .keywords: TS, compute 7581 7582 .seealso: TSSetRHSFunction(), TSComputeIFunction() 7583 @*/ 7584 PetscErrorCode TSComputeLinearStability(TS ts,PetscReal xr,PetscReal xi,PetscReal *yr,PetscReal *yi) 7585 { 7586 PetscErrorCode ierr; 7587 7588 PetscFunctionBegin; 7589 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 7590 if (!ts->ops->linearstability) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Linearized stability function not provided for this method"); 7591 ierr = (*ts->ops->linearstability)(ts,xr,xi,yr,yi);CHKERRQ(ierr); 7592 PetscFunctionReturn(0); 7593 } 7594 7595 /* ------------------------------------------------------------------------*/ 7596 /*@C 7597 TSMonitorEnvelopeCtxCreate - Creates a context for use with TSMonitorEnvelope() 7598 7599 Collective on TS 7600 7601 Input Parameters: 7602 . ts - the ODE solver object 7603 7604 Output Parameter: 7605 . ctx - the context 7606 7607 Level: intermediate 7608 7609 .keywords: TS, monitor, line graph, residual, seealso 7610 7611 .seealso: TSMonitorLGTimeStep(), TSMonitorSet(), TSMonitorLGSolution(), TSMonitorLGError() 7612 7613 @*/ 7614 PetscErrorCode TSMonitorEnvelopeCtxCreate(TS ts,TSMonitorEnvelopeCtx *ctx) 7615 { 7616 PetscErrorCode ierr; 7617 7618 PetscFunctionBegin; 7619 ierr = PetscNew(ctx);CHKERRQ(ierr); 7620 PetscFunctionReturn(0); 7621 } 7622 7623 /*@C 7624 TSMonitorEnvelope - Monitors the maximum and minimum value of each component of the solution 7625 7626 Collective on TS 7627 7628 Input Parameters: 7629 + ts - the TS context 7630 . step - current time-step 7631 . ptime - current time 7632 . u - current solution 7633 - dctx - the envelope context 7634 7635 Options Database: 7636 . -ts_monitor_envelope 7637 7638 Level: intermediate 7639 7640 Notes: after a solve you can use TSMonitorEnvelopeGetBounds() to access the envelope 7641 7642 .keywords: TS, vector, monitor, view 7643 7644 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorEnvelopeGetBounds(), TSMonitorEnvelopeCtxCreate() 7645 @*/ 7646 PetscErrorCode TSMonitorEnvelope(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dctx) 7647 { 7648 PetscErrorCode ierr; 7649 TSMonitorEnvelopeCtx ctx = (TSMonitorEnvelopeCtx)dctx; 7650 7651 PetscFunctionBegin; 7652 if (!ctx->max) { 7653 ierr = VecDuplicate(u,&ctx->max);CHKERRQ(ierr); 7654 ierr = VecDuplicate(u,&ctx->min);CHKERRQ(ierr); 7655 ierr = VecCopy(u,ctx->max);CHKERRQ(ierr); 7656 ierr = VecCopy(u,ctx->min);CHKERRQ(ierr); 7657 } else { 7658 ierr = VecPointwiseMax(ctx->max,u,ctx->max);CHKERRQ(ierr); 7659 ierr = VecPointwiseMin(ctx->min,u,ctx->min);CHKERRQ(ierr); 7660 } 7661 PetscFunctionReturn(0); 7662 } 7663 7664 /*@C 7665 TSMonitorEnvelopeGetBounds - Gets the bounds for the components of the solution 7666 7667 Collective on TS 7668 7669 Input Parameter: 7670 . ts - the TS context 7671 7672 Output Parameter: 7673 + max - the maximum values 7674 - min - the minimum values 7675 7676 Notes: If the TS does not have a TSMonitorEnvelopeCtx associated with it then this function is ignored 7677 7678 Level: intermediate 7679 7680 .keywords: TS, vector, monitor, view 7681 7682 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables() 7683 @*/ 7684 PetscErrorCode TSMonitorEnvelopeGetBounds(TS ts,Vec *max,Vec *min) 7685 { 7686 PetscInt i; 7687 7688 PetscFunctionBegin; 7689 if (max) *max = NULL; 7690 if (min) *min = NULL; 7691 for (i=0; i<ts->numbermonitors; i++) { 7692 if (ts->monitor[i] == TSMonitorEnvelope) { 7693 TSMonitorEnvelopeCtx ctx = (TSMonitorEnvelopeCtx) ts->monitorcontext[i]; 7694 if (max) *max = ctx->max; 7695 if (min) *min = ctx->min; 7696 break; 7697 } 7698 } 7699 PetscFunctionReturn(0); 7700 } 7701 7702 /*@C 7703 TSMonitorEnvelopeCtxDestroy - Destroys a context that was created with TSMonitorEnvelopeCtxCreate(). 7704 7705 Collective on TSMonitorEnvelopeCtx 7706 7707 Input Parameter: 7708 . ctx - the monitor context 7709 7710 Level: intermediate 7711 7712 .keywords: TS, monitor, line graph, destroy 7713 7714 .seealso: TSMonitorLGCtxCreate(), TSMonitorSet(), TSMonitorLGTimeStep() 7715 @*/ 7716 PetscErrorCode TSMonitorEnvelopeCtxDestroy(TSMonitorEnvelopeCtx *ctx) 7717 { 7718 PetscErrorCode ierr; 7719 7720 PetscFunctionBegin; 7721 ierr = VecDestroy(&(*ctx)->min);CHKERRQ(ierr); 7722 ierr = VecDestroy(&(*ctx)->max);CHKERRQ(ierr); 7723 ierr = PetscFree(*ctx);CHKERRQ(ierr); 7724 PetscFunctionReturn(0); 7725 } 7726 7727 /*@ 7728 TSRollBack - Rolls back one time step 7729 7730 Collective on TS 7731 7732 Input Parameter: 7733 . ts - the TS context obtained from TSCreate() 7734 7735 Level: advanced 7736 7737 .keywords: TS, timestep, rollback 7738 7739 .seealso: TSCreate(), TSSetUp(), TSDestroy(), TSSolve(), TSSetPreStep(), TSSetPreStage(), TSInterpolate() 7740 @*/ 7741 PetscErrorCode TSRollBack(TS ts) 7742 { 7743 PetscErrorCode ierr; 7744 7745 PetscFunctionBegin; 7746 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 7747 if (ts->steprollback) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"TSRollBack already called"); 7748 if (!ts->ops->rollback) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSRollBack not implemented for type '%s'",((PetscObject)ts)->type_name); 7749 ierr = (*ts->ops->rollback)(ts);CHKERRQ(ierr); 7750 ts->time_step = ts->ptime - ts->ptime_prev; 7751 ts->ptime = ts->ptime_prev; 7752 ts->ptime_prev = ts->ptime_prev_rollback; 7753 ts->steps--; 7754 ierr = TSPostEvaluate(ts);CHKERRQ(ierr); 7755 ts->steprollback = PETSC_TRUE; 7756 PetscFunctionReturn(0); 7757 } 7758 7759 /*@ 7760 TSGetStages - Get the number of stages and stage values 7761 7762 Input Parameter: 7763 . ts - the TS context obtained from TSCreate() 7764 7765 Level: advanced 7766 7767 .keywords: TS, getstages 7768 7769 .seealso: TSCreate() 7770 @*/ 7771 PetscErrorCode TSGetStages(TS ts,PetscInt *ns,Vec **Y) 7772 { 7773 PetscErrorCode ierr; 7774 7775 PetscFunctionBegin; 7776 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 7777 PetscValidPointer(ns,2); 7778 7779 if (!ts->ops->getstages) *ns=0; 7780 else { 7781 ierr = (*ts->ops->getstages)(ts,ns,Y);CHKERRQ(ierr); 7782 } 7783 PetscFunctionReturn(0); 7784 } 7785 7786 /*@C 7787 TSComputeIJacobianDefaultColor - Computes the Jacobian using finite differences and coloring to exploit matrix sparsity. 7788 7789 Collective on SNES 7790 7791 Input Parameters: 7792 + ts - the TS context 7793 . t - current timestep 7794 . U - state vector 7795 . Udot - time derivative of state vector 7796 . shift - shift to apply, see note below 7797 - ctx - an optional user context 7798 7799 Output Parameters: 7800 + J - Jacobian matrix (not altered in this routine) 7801 - B - newly computed Jacobian matrix to use with preconditioner (generally the same as J) 7802 7803 Level: intermediate 7804 7805 Notes: 7806 If F(t,U,Udot)=0 is the DAE, the required Jacobian is 7807 7808 dF/dU + shift*dF/dUdot 7809 7810 Most users should not need to explicitly call this routine, as it 7811 is used internally within the nonlinear solvers. 7812 7813 This will first try to get the coloring from the DM. If the DM type has no coloring 7814 routine, then it will try to get the coloring from the matrix. This requires that the 7815 matrix have nonzero entries precomputed. 7816 7817 .keywords: TS, finite differences, Jacobian, coloring, sparse 7818 .seealso: TSSetIJacobian(), MatFDColoringCreate(), MatFDColoringSetFunction() 7819 @*/ 7820 PetscErrorCode TSComputeIJacobianDefaultColor(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat J,Mat B,void *ctx) 7821 { 7822 SNES snes; 7823 MatFDColoring color; 7824 PetscBool hascolor, matcolor = PETSC_FALSE; 7825 PetscErrorCode ierr; 7826 7827 PetscFunctionBegin; 7828 ierr = PetscOptionsGetBool(((PetscObject)ts)->options,((PetscObject) ts)->prefix, "-ts_fd_color_use_mat", &matcolor, NULL);CHKERRQ(ierr); 7829 ierr = PetscObjectQuery((PetscObject) B, "TSMatFDColoring", (PetscObject *) &color);CHKERRQ(ierr); 7830 if (!color) { 7831 DM dm; 7832 ISColoring iscoloring; 7833 7834 ierr = TSGetDM(ts, &dm);CHKERRQ(ierr); 7835 ierr = DMHasColoring(dm, &hascolor);CHKERRQ(ierr); 7836 if (hascolor && !matcolor) { 7837 ierr = DMCreateColoring(dm, IS_COLORING_GLOBAL, &iscoloring);CHKERRQ(ierr); 7838 ierr = MatFDColoringCreate(B, iscoloring, &color);CHKERRQ(ierr); 7839 ierr = MatFDColoringSetFunction(color, (PetscErrorCode (*)(void)) SNESTSFormFunction, (void *) ts);CHKERRQ(ierr); 7840 ierr = MatFDColoringSetFromOptions(color);CHKERRQ(ierr); 7841 ierr = MatFDColoringSetUp(B, iscoloring, color);CHKERRQ(ierr); 7842 ierr = ISColoringDestroy(&iscoloring);CHKERRQ(ierr); 7843 } else { 7844 MatColoring mc; 7845 7846 ierr = MatColoringCreate(B, &mc);CHKERRQ(ierr); 7847 ierr = MatColoringSetDistance(mc, 2);CHKERRQ(ierr); 7848 ierr = MatColoringSetType(mc, MATCOLORINGSL);CHKERRQ(ierr); 7849 ierr = MatColoringSetFromOptions(mc);CHKERRQ(ierr); 7850 ierr = MatColoringApply(mc, &iscoloring);CHKERRQ(ierr); 7851 ierr = MatColoringDestroy(&mc);CHKERRQ(ierr); 7852 ierr = MatFDColoringCreate(B, iscoloring, &color);CHKERRQ(ierr); 7853 ierr = MatFDColoringSetFunction(color, (PetscErrorCode (*)(void)) SNESTSFormFunction, (void *) ts);CHKERRQ(ierr); 7854 ierr = MatFDColoringSetFromOptions(color);CHKERRQ(ierr); 7855 ierr = MatFDColoringSetUp(B, iscoloring, color);CHKERRQ(ierr); 7856 ierr = ISColoringDestroy(&iscoloring);CHKERRQ(ierr); 7857 } 7858 ierr = PetscObjectCompose((PetscObject) B, "TSMatFDColoring", (PetscObject) color);CHKERRQ(ierr); 7859 ierr = PetscObjectDereference((PetscObject) color);CHKERRQ(ierr); 7860 } 7861 ierr = TSGetSNES(ts, &snes);CHKERRQ(ierr); 7862 ierr = MatFDColoringApply(B, color, U, snes);CHKERRQ(ierr); 7863 if (J != B) { 7864 ierr = MatAssemblyBegin(J, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 7865 ierr = MatAssemblyEnd(J, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 7866 } 7867 PetscFunctionReturn(0); 7868 } 7869 7870 /*@ 7871 TSSetFunctionDomainError - Set the function testing if the current state vector is valid 7872 7873 Input Parameters: 7874 ts - the TS context 7875 func - function called within TSFunctionDomainError 7876 7877 Level: intermediate 7878 7879 .keywords: TS, state, domain 7880 .seealso: TSAdaptCheckStage(), TSFunctionDomainError() 7881 @*/ 7882 7883 PetscErrorCode TSSetFunctionDomainError(TS ts, PetscErrorCode (*func)(TS,PetscReal,Vec,PetscBool*)) 7884 { 7885 PetscFunctionBegin; 7886 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 7887 ts->functiondomainerror = func; 7888 PetscFunctionReturn(0); 7889 } 7890 7891 /*@ 7892 TSFunctionDomainError - Check if the current state is valid 7893 7894 Input Parameters: 7895 ts - the TS context 7896 stagetime - time of the simulation 7897 Y - state vector to check. 7898 7899 Output Parameter: 7900 accept - Set to PETSC_FALSE if the current state vector is valid. 7901 7902 Note: 7903 This function should be used to ensure the state is in a valid part of the space. 7904 For example, one can ensure here all values are positive. 7905 7906 Level: advanced 7907 @*/ 7908 PetscErrorCode TSFunctionDomainError(TS ts,PetscReal stagetime,Vec Y,PetscBool* accept) 7909 { 7910 PetscErrorCode ierr; 7911 7912 PetscFunctionBegin; 7913 7914 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 7915 *accept = PETSC_TRUE; 7916 if (ts->functiondomainerror) { 7917 PetscStackCallStandard((*ts->functiondomainerror),(ts,stagetime,Y,accept)); 7918 } 7919 PetscFunctionReturn(0); 7920 } 7921 7922 /*@C 7923 TSClone - This function clones a time step object. 7924 7925 Collective on MPI_Comm 7926 7927 Input Parameter: 7928 . tsin - The input TS 7929 7930 Output Parameter: 7931 . tsout - The output TS (cloned) 7932 7933 Notes: 7934 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. 7935 7936 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); 7937 7938 Level: developer 7939 7940 .keywords: TS, clone 7941 .seealso: TSCreate(), TSSetType(), TSSetUp(), TSDestroy(), TSSetProblemType() 7942 @*/ 7943 PetscErrorCode TSClone(TS tsin, TS *tsout) 7944 { 7945 TS t; 7946 PetscErrorCode ierr; 7947 SNES snes_start; 7948 DM dm; 7949 TSType type; 7950 7951 PetscFunctionBegin; 7952 PetscValidPointer(tsin,1); 7953 *tsout = NULL; 7954 7955 ierr = PetscHeaderCreate(t, TS_CLASSID, "TS", "Time stepping", "TS", PetscObjectComm((PetscObject)tsin), TSDestroy, TSView);CHKERRQ(ierr); 7956 7957 /* General TS description */ 7958 t->numbermonitors = 0; 7959 t->setupcalled = 0; 7960 t->ksp_its = 0; 7961 t->snes_its = 0; 7962 t->nwork = 0; 7963 t->rhsjacobian.time = -1e20; 7964 t->rhsjacobian.scale = 1.; 7965 t->ijacobian.shift = 1.; 7966 7967 ierr = TSGetSNES(tsin,&snes_start);CHKERRQ(ierr); 7968 ierr = TSSetSNES(t,snes_start);CHKERRQ(ierr); 7969 7970 ierr = TSGetDM(tsin,&dm);CHKERRQ(ierr); 7971 ierr = TSSetDM(t,dm);CHKERRQ(ierr); 7972 7973 t->adapt = tsin->adapt; 7974 ierr = PetscObjectReference((PetscObject)t->adapt);CHKERRQ(ierr); 7975 7976 t->trajectory = tsin->trajectory; 7977 ierr = PetscObjectReference((PetscObject)t->trajectory);CHKERRQ(ierr); 7978 7979 t->event = tsin->event; 7980 if (t->event) t->event->refct++; 7981 7982 t->problem_type = tsin->problem_type; 7983 t->ptime = tsin->ptime; 7984 t->ptime_prev = tsin->ptime_prev; 7985 t->time_step = tsin->time_step; 7986 t->max_time = tsin->max_time; 7987 t->steps = tsin->steps; 7988 t->max_steps = tsin->max_steps; 7989 t->equation_type = tsin->equation_type; 7990 t->atol = tsin->atol; 7991 t->rtol = tsin->rtol; 7992 t->max_snes_failures = tsin->max_snes_failures; 7993 t->max_reject = tsin->max_reject; 7994 t->errorifstepfailed = tsin->errorifstepfailed; 7995 7996 ierr = TSGetType(tsin,&type);CHKERRQ(ierr); 7997 ierr = TSSetType(t,type);CHKERRQ(ierr); 7998 7999 t->vec_sol = NULL; 8000 8001 t->cfltime = tsin->cfltime; 8002 t->cfltime_local = tsin->cfltime_local; 8003 t->exact_final_time = tsin->exact_final_time; 8004 8005 ierr = PetscMemcpy(t->ops,tsin->ops,sizeof(struct _TSOps));CHKERRQ(ierr); 8006 8007 if (((PetscObject)tsin)->fortran_func_pointers) { 8008 PetscInt i; 8009 ierr = PetscMalloc((10)*sizeof(void(*)(void)),&((PetscObject)t)->fortran_func_pointers);CHKERRQ(ierr); 8010 for (i=0; i<10; i++) { 8011 ((PetscObject)t)->fortran_func_pointers[i] = ((PetscObject)tsin)->fortran_func_pointers[i]; 8012 } 8013 } 8014 *tsout = t; 8015 PetscFunctionReturn(0); 8016 } 8017