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