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,PetscViewerAndFormat*),PetscErrorCode (*monitorsetup)(TS,PetscViewerAndFormat*)) 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 PetscViewerAndFormat *vf; 58 ierr = PetscViewerAndFormatCreate(viewer,format,&vf);CHKERRQ(ierr); 59 ierr = PetscObjectDereference((PetscObject)viewer);CHKERRQ(ierr); 60 if (monitorsetup) { 61 ierr = (*monitorsetup)(ts,vf);CHKERRQ(ierr); 62 } 63 ierr = TSMonitorSet(ts,(PetscErrorCode (*)(TS,PetscInt,PetscReal,Vec,void*))monitor,vf,(PetscErrorCode (*)(void**))PetscViewerAndFormatDestroy);CHKERRQ(ierr); 64 } 65 PetscFunctionReturn(0); 66 } 67 68 #undef __FUNCT__ 69 #define __FUNCT__ "TSAdjointMonitorSetFromOptions" 70 /*@C 71 TSAdjointMonitorSetFromOptions - Sets a monitor function and viewer appropriate for the type indicated by the user 72 73 Collective on TS 74 75 Input Parameters: 76 + ts - TS object you wish to monitor 77 . name - the monitor type one is seeking 78 . help - message indicating what monitoring is done 79 . manual - manual page for the monitor 80 . monitor - the monitor function 81 - 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 82 83 Level: developer 84 85 .seealso: PetscOptionsGetViewer(), PetscOptionsGetReal(), PetscOptionsHasName(), PetscOptionsGetString(), 86 PetscOptionsGetIntArray(), PetscOptionsGetRealArray(), PetscOptionsBool() 87 PetscOptionsInt(), PetscOptionsString(), PetscOptionsReal(), PetscOptionsBool(), 88 PetscOptionsName(), PetscOptionsBegin(), PetscOptionsEnd(), PetscOptionsHead(), 89 PetscOptionsStringArray(),PetscOptionsRealArray(), PetscOptionsScalar(), 90 PetscOptionsBoolGroupBegin(), PetscOptionsBoolGroup(), PetscOptionsBoolGroupEnd(), 91 PetscOptionsFList(), PetscOptionsEList() 92 @*/ 93 PetscErrorCode TSAdjointMonitorSetFromOptions(TS ts,const char name[],const char help[], const char manual[],PetscErrorCode (*monitor)(TS,PetscInt,PetscReal,Vec,PetscInt,Vec*,Vec*,PetscViewerAndFormat*),PetscErrorCode (*monitorsetup)(TS,PetscViewerAndFormat*)) 94 { 95 PetscErrorCode ierr; 96 PetscViewer viewer; 97 PetscViewerFormat format; 98 PetscBool flg; 99 100 PetscFunctionBegin; 101 ierr = PetscOptionsGetViewer(PetscObjectComm((PetscObject)ts),((PetscObject)ts)->prefix,name,&viewer,&format,&flg);CHKERRQ(ierr); 102 if (flg) { 103 PetscViewerAndFormat *vf; 104 ierr = PetscViewerAndFormatCreate(viewer,format,&vf);CHKERRQ(ierr); 105 ierr = PetscObjectDereference((PetscObject)viewer);CHKERRQ(ierr); 106 if (monitorsetup) { 107 ierr = (*monitorsetup)(ts,vf);CHKERRQ(ierr); 108 } 109 ierr = TSAdjointMonitorSet(ts,(PetscErrorCode (*)(TS,PetscInt,PetscReal,Vec,PetscInt,Vec*,Vec*,void*))monitor,vf,(PetscErrorCode (*)(void**))PetscViewerAndFormatDestroy);CHKERRQ(ierr); 110 } 111 PetscFunctionReturn(0); 112 } 113 114 #undef __FUNCT__ 115 #define __FUNCT__ "TSSetFromOptions" 116 /*@ 117 TSSetFromOptions - Sets various TS parameters from user options. 118 119 Collective on TS 120 121 Input Parameter: 122 . ts - the TS context obtained from TSCreate() 123 124 Options Database Keys: 125 + -ts_type <type> - TSEULER, TSBEULER, TSSUNDIALS, TSPSEUDO, TSCN, TSRK, TSTHETA, TSALPHA, TSGLLE, TSSSP, TSGLEE 126 . -ts_save_trajectory - checkpoint the solution at each time-step 127 . -ts_max_steps <maxsteps> - maximum number of time-steps to take 128 . -ts_final_time <time> - maximum time to compute to 129 . -ts_dt <dt> - initial time step 130 . -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 131 . -ts_max_snes_failures <maxfailures> - Maximum number of nonlinear solve failures allowed 132 . -ts_max_reject <maxrejects> - Maximum number of step rejections before step fails 133 . -ts_error_if_step_fails <true,false> - Error if no step succeeds 134 . -ts_rtol <rtol> - relative tolerance for local truncation error 135 . -ts_atol <atol> Absolute tolerance for local truncation error 136 . -ts_adjoint_solve <yes,no> After solving the ODE/DAE solve the adjoint problem (requires -ts_save_trajectory) 137 . -ts_fd_color - Use finite differences with coloring to compute IJacobian 138 . -ts_monitor - print information at each timestep 139 . -ts_monitor_lg_solution - Monitor solution graphically 140 . -ts_monitor_lg_error - Monitor error graphically 141 . -ts_monitor_lg_timestep - Monitor timestep size graphically 142 . -ts_monitor_lg_snes_iterations - Monitor number nonlinear iterations for each timestep graphically 143 . -ts_monitor_lg_ksp_iterations - Monitor number nonlinear iterations for each timestep graphically 144 . -ts_monitor_sp_eig - Monitor eigenvalues of linearized operator graphically 145 . -ts_monitor_draw_solution - Monitor solution graphically 146 . -ts_monitor_draw_solution_phase <xleft,yleft,xright,yright> - Monitor solution graphically with phase diagram, requires problem with exactly 2 degrees of freedom 147 . -ts_monitor_draw_error - Monitor error graphically, requires use to have provided TSSetSolutionFunction() 148 . -ts_monitor_solution [ascii binary draw][:filename][:viewerformat] - monitors the solution at each timestep 149 . -ts_monitor_solution_vtk <filename.vts> - Save each time step to a binary file, use filename-%%03D.vts 150 . -ts_monitor_envelope - determine maximum and minimum value of each component of the solution over the solution time 151 . -ts_adjoint_monitor - print information at each adjoint time step 152 - -ts_adjoint_monitor_draw_sensi - monitor the sensitivity of the first cost function wrt initial conditions (lambda[0]) graphically 153 154 Developer Note: We should unify all the -ts_monitor options in the way that -xxx_view has been unified 155 156 Level: beginner 157 158 .keywords: TS, timestep, set, options, database 159 160 .seealso: TSGetType() 161 @*/ 162 PetscErrorCode TSSetFromOptions(TS ts) 163 { 164 PetscBool opt,flg,tflg; 165 PetscErrorCode ierr; 166 char monfilename[PETSC_MAX_PATH_LEN]; 167 PetscReal time_step; 168 TSExactFinalTimeOption eftopt; 169 char dir[16]; 170 TSIFunction ifun; 171 const char *defaultType; 172 char typeName[256]; 173 174 PetscFunctionBegin; 175 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 176 177 ierr = TSRegisterAll();CHKERRQ(ierr); 178 ierr = TSGetIFunction(ts,NULL,&ifun,NULL);CHKERRQ(ierr); 179 180 ierr = PetscObjectOptionsBegin((PetscObject)ts);CHKERRQ(ierr); 181 if (((PetscObject)ts)->type_name) 182 defaultType = ((PetscObject)ts)->type_name; 183 else 184 defaultType = ifun ? TSBEULER : TSEULER; 185 ierr = PetscOptionsFList("-ts_type","TS method","TSSetType",TSList,defaultType,typeName,256,&opt);CHKERRQ(ierr); 186 if (opt) { 187 ierr = TSSetType(ts,typeName);CHKERRQ(ierr); 188 } else { 189 ierr = TSSetType(ts,defaultType);CHKERRQ(ierr); 190 } 191 192 /* Handle generic TS options */ 193 ierr = PetscOptionsInt("-ts_max_steps","Maximum number of time steps","TSSetDuration",ts->max_steps,&ts->max_steps,NULL);CHKERRQ(ierr); 194 ierr = PetscOptionsReal("-ts_final_time","Time to run to","TSSetDuration",ts->max_time,&ts->max_time,NULL);CHKERRQ(ierr); 195 ierr = PetscOptionsReal("-ts_init_time","Initial time","TSSetTime",ts->ptime,&ts->ptime,NULL);CHKERRQ(ierr); 196 ierr = PetscOptionsReal("-ts_dt","Initial time step","TSSetTimeStep",ts->time_step,&time_step,&flg);CHKERRQ(ierr); 197 if (flg) {ierr = TSSetTimeStep(ts,time_step);CHKERRQ(ierr);} 198 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); 199 if (flg) {ierr = TSSetExactFinalTime(ts,eftopt);CHKERRQ(ierr);} 200 ierr = PetscOptionsInt("-ts_max_snes_failures","Maximum number of nonlinear solve failures","TSSetMaxSNESFailures",ts->max_snes_failures,&ts->max_snes_failures,NULL);CHKERRQ(ierr); 201 ierr = PetscOptionsInt("-ts_max_reject","Maximum number of step rejections before step fails","TSSetMaxStepRejections",ts->max_reject,&ts->max_reject,NULL);CHKERRQ(ierr); 202 ierr = PetscOptionsBool("-ts_error_if_step_fails","Error if no step succeeds","TSSetErrorIfStepFails",ts->errorifstepfailed,&ts->errorifstepfailed,NULL);CHKERRQ(ierr); 203 ierr = PetscOptionsReal("-ts_rtol","Relative tolerance for local truncation error","TSSetTolerances",ts->rtol,&ts->rtol,NULL);CHKERRQ(ierr); 204 ierr = PetscOptionsReal("-ts_atol","Absolute tolerance for local truncation error","TSSetTolerances",ts->atol,&ts->atol,NULL);CHKERRQ(ierr); 205 206 #if defined(PETSC_HAVE_SAWS) 207 { 208 PetscBool set; 209 flg = PETSC_FALSE; 210 ierr = PetscOptionsBool("-ts_saws_block","Block for SAWs memory snooper at end of TSSolve","PetscObjectSAWsBlock",((PetscObject)ts)->amspublishblock,&flg,&set);CHKERRQ(ierr); 211 if (set) { 212 ierr = PetscObjectSAWsSetBlock((PetscObject)ts,flg);CHKERRQ(ierr); 213 } 214 } 215 #endif 216 217 /* Monitor options */ 218 ierr = TSMonitorSetFromOptions(ts,"-ts_monitor","Monitor time and timestep size","TSMonitorDefault",TSMonitorDefault,NULL);CHKERRQ(ierr); 219 ierr = TSMonitorSetFromOptions(ts,"-ts_monitor_solution","View the solution at each timestep","TSMonitorSolution",TSMonitorSolution,NULL);CHKERRQ(ierr); 220 ierr = TSAdjointMonitorSetFromOptions(ts,"-ts_adjoint_monitor","Monitor adjoint timestep size","TSAdjointMonitorDefault",TSAdjointMonitorDefault,NULL);CHKERRQ(ierr); 221 222 ierr = PetscOptionsString("-ts_monitor_python","Use Python function","TSMonitorSet",0,monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr); 223 if (flg) {ierr = PetscPythonMonitorSet((PetscObject)ts,monfilename);CHKERRQ(ierr);} 224 225 ierr = PetscOptionsName("-ts_monitor_lg_solution","Monitor solution graphically","TSMonitorLGSolution",&opt);CHKERRQ(ierr); 226 if (opt) { 227 TSMonitorLGCtx ctx; 228 PetscInt howoften = 1; 229 230 ierr = PetscOptionsInt("-ts_monitor_lg_solution","Monitor solution graphically","TSMonitorLGSolution",howoften,&howoften,NULL);CHKERRQ(ierr); 231 ierr = TSMonitorLGCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);CHKERRQ(ierr); 232 ierr = TSMonitorSet(ts,TSMonitorLGSolution,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 233 } 234 235 ierr = PetscOptionsName("-ts_monitor_lg_error","Monitor error graphically","TSMonitorLGError",&opt);CHKERRQ(ierr); 236 if (opt) { 237 TSMonitorLGCtx ctx; 238 PetscInt howoften = 1; 239 240 ierr = PetscOptionsInt("-ts_monitor_lg_error","Monitor error graphically","TSMonitorLGError",howoften,&howoften,NULL);CHKERRQ(ierr); 241 ierr = TSMonitorLGCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);CHKERRQ(ierr); 242 ierr = TSMonitorSet(ts,TSMonitorLGError,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 243 } 244 245 ierr = PetscOptionsName("-ts_monitor_lg_timestep","Monitor timestep size graphically","TSMonitorLGTimeStep",&opt);CHKERRQ(ierr); 246 if (opt) { 247 TSMonitorLGCtx ctx; 248 PetscInt howoften = 1; 249 250 ierr = PetscOptionsInt("-ts_monitor_lg_timestep","Monitor timestep size graphically","TSMonitorLGTimeStep",howoften,&howoften,NULL);CHKERRQ(ierr); 251 ierr = TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);CHKERRQ(ierr); 252 ierr = TSMonitorSet(ts,TSMonitorLGTimeStep,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 253 } 254 ierr = PetscOptionsName("-ts_monitor_lg_snes_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGSNESIterations",&opt);CHKERRQ(ierr); 255 if (opt) { 256 TSMonitorLGCtx ctx; 257 PetscInt howoften = 1; 258 259 ierr = PetscOptionsInt("-ts_monitor_lg_snes_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGSNESIterations",howoften,&howoften,NULL);CHKERRQ(ierr); 260 ierr = TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);CHKERRQ(ierr); 261 ierr = TSMonitorSet(ts,TSMonitorLGSNESIterations,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 262 } 263 ierr = PetscOptionsName("-ts_monitor_lg_ksp_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGKSPIterations",&opt);CHKERRQ(ierr); 264 if (opt) { 265 TSMonitorLGCtx ctx; 266 PetscInt howoften = 1; 267 268 ierr = PetscOptionsInt("-ts_monitor_lg_ksp_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGKSPIterations",howoften,&howoften,NULL);CHKERRQ(ierr); 269 ierr = TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);CHKERRQ(ierr); 270 ierr = TSMonitorSet(ts,TSMonitorLGKSPIterations,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 271 } 272 ierr = PetscOptionsName("-ts_monitor_sp_eig","Monitor eigenvalues of linearized operator graphically","TSMonitorSPEig",&opt);CHKERRQ(ierr); 273 if (opt) { 274 TSMonitorSPEigCtx ctx; 275 PetscInt howoften = 1; 276 277 ierr = PetscOptionsInt("-ts_monitor_sp_eig","Monitor eigenvalues of linearized operator graphically","TSMonitorSPEig",howoften,&howoften,NULL);CHKERRQ(ierr); 278 ierr = TSMonitorSPEigCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);CHKERRQ(ierr); 279 ierr = TSMonitorSet(ts,TSMonitorSPEig,ctx,(PetscErrorCode (*)(void**))TSMonitorSPEigCtxDestroy);CHKERRQ(ierr); 280 } 281 opt = PETSC_FALSE; 282 ierr = PetscOptionsName("-ts_monitor_draw_solution","Monitor solution graphically","TSMonitorDrawSolution",&opt);CHKERRQ(ierr); 283 if (opt) { 284 TSMonitorDrawCtx ctx; 285 PetscInt howoften = 1; 286 287 ierr = PetscOptionsInt("-ts_monitor_draw_solution","Monitor solution graphically","TSMonitorDrawSolution",howoften,&howoften,NULL);CHKERRQ(ierr); 288 ierr = TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);CHKERRQ(ierr); 289 ierr = TSMonitorSet(ts,TSMonitorDrawSolution,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);CHKERRQ(ierr); 290 } 291 opt = PETSC_FALSE; 292 ierr = PetscOptionsName("-ts_adjoint_monitor_draw_sensi","Monitor adjoint sensitivities (lambda only) graphically","TSAdjointMonitorDrawSensi",&opt);CHKERRQ(ierr); 293 if (opt) { 294 TSMonitorDrawCtx ctx; 295 PetscInt howoften = 1; 296 297 ierr = PetscOptionsInt("-ts_adjoint_monitor_draw_sensi","Monitor adjoint sensitivities (lambda only) graphically","TSAdjointMonitorDrawSensi",howoften,&howoften,NULL);CHKERRQ(ierr); 298 ierr = TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);CHKERRQ(ierr); 299 ierr = TSAdjointMonitorSet(ts,TSAdjointMonitorDrawSensi,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);CHKERRQ(ierr); 300 } 301 opt = PETSC_FALSE; 302 ierr = PetscOptionsName("-ts_monitor_draw_solution_phase","Monitor solution graphically","TSMonitorDrawSolutionPhase",&opt);CHKERRQ(ierr); 303 if (opt) { 304 TSMonitorDrawCtx ctx; 305 PetscReal bounds[4]; 306 PetscInt n = 4; 307 PetscDraw draw; 308 PetscDrawAxis axis; 309 310 ierr = PetscOptionsRealArray("-ts_monitor_draw_solution_phase","Monitor solution graphically","TSMonitorDrawSolutionPhase",bounds,&n,NULL);CHKERRQ(ierr); 311 if (n != 4) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Must provide bounding box of phase field"); 312 ierr = TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,1,&ctx);CHKERRQ(ierr); 313 ierr = PetscViewerDrawGetDraw(ctx->viewer,0,&draw);CHKERRQ(ierr); 314 ierr = PetscViewerDrawGetDrawAxis(ctx->viewer,0,&axis);CHKERRQ(ierr); 315 ierr = PetscDrawAxisSetLimits(axis,bounds[0],bounds[2],bounds[1],bounds[3]);CHKERRQ(ierr); 316 ierr = PetscDrawAxisSetLabels(axis,"Phase Diagram","Variable 1","Variable 2");CHKERRQ(ierr); 317 ierr = TSMonitorSet(ts,TSMonitorDrawSolutionPhase,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);CHKERRQ(ierr); 318 } 319 opt = PETSC_FALSE; 320 ierr = PetscOptionsName("-ts_monitor_draw_error","Monitor error graphically","TSMonitorDrawError",&opt);CHKERRQ(ierr); 321 if (opt) { 322 TSMonitorDrawCtx ctx; 323 PetscInt howoften = 1; 324 325 ierr = PetscOptionsInt("-ts_monitor_draw_error","Monitor error graphically","TSMonitorDrawError",howoften,&howoften,NULL);CHKERRQ(ierr); 326 ierr = TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);CHKERRQ(ierr); 327 ierr = TSMonitorSet(ts,TSMonitorDrawError,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);CHKERRQ(ierr); 328 } 329 330 opt = PETSC_FALSE; 331 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); 332 if (flg) { 333 const char *ptr,*ptr2; 334 char *filetemplate; 335 if (!monfilename[0]) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"-ts_monitor_solution_vtk requires a file template, e.g. filename-%%03D.vts"); 336 /* Do some cursory validation of the input. */ 337 ierr = PetscStrstr(monfilename,"%",(char**)&ptr);CHKERRQ(ierr); 338 if (!ptr) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"-ts_monitor_solution_vtk requires a file template, e.g. filename-%%03D.vts"); 339 for (ptr++; ptr && *ptr; ptr++) { 340 ierr = PetscStrchr("DdiouxX",*ptr,(char**)&ptr2);CHKERRQ(ierr); 341 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"); 342 if (ptr2) break; 343 } 344 ierr = PetscStrallocpy(monfilename,&filetemplate);CHKERRQ(ierr); 345 ierr = TSMonitorSet(ts,TSMonitorSolutionVTK,filetemplate,(PetscErrorCode (*)(void**))TSMonitorSolutionVTKDestroy);CHKERRQ(ierr); 346 } 347 348 ierr = PetscOptionsString("-ts_monitor_dmda_ray","Display a ray of the solution","None","y=0",dir,16,&flg);CHKERRQ(ierr); 349 if (flg) { 350 TSMonitorDMDARayCtx *rayctx; 351 int ray = 0; 352 DMDADirection ddir; 353 DM da; 354 PetscMPIInt rank; 355 356 if (dir[1] != '=') SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Unknown ray %s",dir); 357 if (dir[0] == 'x') ddir = DMDA_X; 358 else if (dir[0] == 'y') ddir = DMDA_Y; 359 else SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Unknown ray %s",dir); 360 sscanf(dir+2,"%d",&ray); 361 362 ierr = PetscInfo2(((PetscObject)ts),"Displaying DMDA ray %c = %D\n",dir[0],ray);CHKERRQ(ierr); 363 ierr = PetscNew(&rayctx);CHKERRQ(ierr); 364 ierr = TSGetDM(ts,&da);CHKERRQ(ierr); 365 ierr = DMDAGetRay(da,ddir,ray,&rayctx->ray,&rayctx->scatter);CHKERRQ(ierr); 366 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)ts),&rank);CHKERRQ(ierr); 367 if (!rank) { 368 ierr = PetscViewerDrawOpen(PETSC_COMM_SELF,0,0,0,0,600,300,&rayctx->viewer);CHKERRQ(ierr); 369 } 370 rayctx->lgctx = NULL; 371 ierr = TSMonitorSet(ts,TSMonitorDMDARay,rayctx,TSMonitorDMDARayDestroy);CHKERRQ(ierr); 372 } 373 ierr = PetscOptionsString("-ts_monitor_lg_dmda_ray","Display a ray of the solution","None","x=0",dir,16,&flg);CHKERRQ(ierr); 374 if (flg) { 375 TSMonitorDMDARayCtx *rayctx; 376 int ray = 0; 377 DMDADirection ddir; 378 DM da; 379 PetscInt howoften = 1; 380 381 if (dir[1] != '=') SETERRQ1(PetscObjectComm((PetscObject) ts), PETSC_ERR_ARG_WRONG, "Malformed ray %s", dir); 382 if (dir[0] == 'x') ddir = DMDA_X; 383 else if (dir[0] == 'y') ddir = DMDA_Y; 384 else SETERRQ1(PetscObjectComm((PetscObject) ts), PETSC_ERR_ARG_WRONG, "Unknown ray direction %s", dir); 385 sscanf(dir+2, "%d", &ray); 386 387 ierr = PetscInfo2(((PetscObject) ts),"Displaying LG DMDA ray %c = %D\n", dir[0], ray);CHKERRQ(ierr); 388 ierr = PetscNew(&rayctx);CHKERRQ(ierr); 389 ierr = TSGetDM(ts, &da);CHKERRQ(ierr); 390 ierr = DMDAGetRay(da, ddir, ray, &rayctx->ray, &rayctx->scatter);CHKERRQ(ierr); 391 ierr = TSMonitorLGCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,600,400,howoften,&rayctx->lgctx);CHKERRQ(ierr); 392 ierr = TSMonitorSet(ts, TSMonitorLGDMDARay, rayctx, TSMonitorDMDARayDestroy);CHKERRQ(ierr); 393 } 394 395 ierr = PetscOptionsName("-ts_monitor_envelope","Monitor maximum and minimum value of each component of the solution","TSMonitorEnvelope",&opt);CHKERRQ(ierr); 396 if (opt) { 397 TSMonitorEnvelopeCtx ctx; 398 399 ierr = TSMonitorEnvelopeCtxCreate(ts,&ctx);CHKERRQ(ierr); 400 ierr = TSMonitorSet(ts,TSMonitorEnvelope,ctx,(PetscErrorCode (*)(void**))TSMonitorEnvelopeCtxDestroy);CHKERRQ(ierr); 401 } 402 403 flg = PETSC_FALSE; 404 ierr = PetscOptionsBool("-ts_fd_color", "Use finite differences with coloring to compute IJacobian", "TSComputeJacobianDefaultColor", flg, &flg, NULL);CHKERRQ(ierr); 405 if (flg) { 406 DM dm; 407 DMTS tdm; 408 409 ierr = TSGetDM(ts, &dm);CHKERRQ(ierr); 410 ierr = DMGetDMTS(dm, &tdm);CHKERRQ(ierr); 411 tdm->ijacobianctx = NULL; 412 ierr = TSSetIJacobian(ts, NULL, NULL, TSComputeIJacobianDefaultColor, 0);CHKERRQ(ierr); 413 ierr = PetscInfo(ts, "Setting default finite difference coloring Jacobian matrix\n");CHKERRQ(ierr); 414 } 415 416 if (ts->adapt) { 417 ierr = TSAdaptSetFromOptions(PetscOptionsObject,ts->adapt);CHKERRQ(ierr); 418 } 419 420 /* Handle specific TS options */ 421 if (ts->ops->setfromoptions) { 422 ierr = (*ts->ops->setfromoptions)(PetscOptionsObject,ts);CHKERRQ(ierr); 423 } 424 425 /* TS trajectory must be set after TS, since it may use some TS options above */ 426 tflg = ts->trajectory ? PETSC_TRUE : PETSC_FALSE; 427 ierr = PetscOptionsBool("-ts_save_trajectory","Save the solution at each timestep","TSSetSaveTrajectory",tflg,&tflg,NULL);CHKERRQ(ierr); 428 if (tflg) { 429 ierr = TSSetSaveTrajectory(ts);CHKERRQ(ierr); 430 } 431 tflg = ts->adjoint_solve ? PETSC_TRUE : PETSC_FALSE; 432 ierr = PetscOptionsBool("-ts_adjoint_solve","Solve the adjoint problem immediately after solving the forward problem","",tflg,&tflg,&flg);CHKERRQ(ierr); 433 if (flg) { 434 ierr = TSSetSaveTrajectory(ts);CHKERRQ(ierr); 435 ts->adjoint_solve = tflg; 436 } 437 438 /* process any options handlers added with PetscObjectAddOptionsHandler() */ 439 ierr = PetscObjectProcessOptionsHandlers(PetscOptionsObject,(PetscObject)ts);CHKERRQ(ierr); 440 ierr = PetscOptionsEnd();CHKERRQ(ierr); 441 442 if (ts->trajectory) { 443 ierr = TSTrajectorySetFromOptions(ts->trajectory,ts);CHKERRQ(ierr); 444 } 445 446 ierr = TSGetSNES(ts,&ts->snes);CHKERRQ(ierr); 447 if (ts->problem_type == TS_LINEAR) {ierr = SNESSetType(ts->snes,SNESKSPONLY);CHKERRQ(ierr);} 448 ierr = SNESSetFromOptions(ts->snes);CHKERRQ(ierr); 449 PetscFunctionReturn(0); 450 } 451 452 #undef __FUNCT__ 453 #define __FUNCT__ "TSSetSaveTrajectory" 454 /*@ 455 TSSetSaveTrajectory - Causes the TS to save its solutions as it iterates forward in time in a TSTrajectory object 456 457 Collective on TS 458 459 Input Parameters: 460 . ts - the TS context obtained from TSCreate() 461 462 Note: This routine should be called after all TS options have been set 463 464 Level: intermediate 465 466 .seealso: TSGetTrajectory(), TSAdjointSolve() 467 468 .keywords: TS, set, checkpoint, 469 @*/ 470 PetscErrorCode TSSetSaveTrajectory(TS ts) 471 { 472 PetscErrorCode ierr; 473 474 PetscFunctionBegin; 475 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 476 if (!ts->trajectory) { 477 ierr = TSTrajectoryCreate(PetscObjectComm((PetscObject)ts),&ts->trajectory);CHKERRQ(ierr); 478 ierr = TSTrajectorySetFromOptions(ts->trajectory,ts);CHKERRQ(ierr); 479 } 480 PetscFunctionReturn(0); 481 } 482 483 #undef __FUNCT__ 484 #define __FUNCT__ "TSComputeRHSJacobian" 485 /*@ 486 TSComputeRHSJacobian - Computes the Jacobian matrix that has been 487 set with TSSetRHSJacobian(). 488 489 Collective on TS and Vec 490 491 Input Parameters: 492 + ts - the TS context 493 . t - current timestep 494 - U - input vector 495 496 Output Parameters: 497 + A - Jacobian matrix 498 . B - optional preconditioning matrix 499 - flag - flag indicating matrix structure 500 501 Notes: 502 Most users should not need to explicitly call this routine, as it 503 is used internally within the nonlinear solvers. 504 505 See KSPSetOperators() for important information about setting the 506 flag parameter. 507 508 Level: developer 509 510 .keywords: SNES, compute, Jacobian, matrix 511 512 .seealso: TSSetRHSJacobian(), KSPSetOperators() 513 @*/ 514 PetscErrorCode TSComputeRHSJacobian(TS ts,PetscReal t,Vec U,Mat A,Mat B) 515 { 516 PetscErrorCode ierr; 517 PetscObjectState Ustate; 518 DM dm; 519 DMTS tsdm; 520 TSRHSJacobian rhsjacobianfunc; 521 void *ctx; 522 TSIJacobian ijacobianfunc; 523 TSRHSFunction rhsfunction; 524 525 PetscFunctionBegin; 526 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 527 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 528 PetscCheckSameComm(ts,1,U,3); 529 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 530 ierr = DMGetDMTS(dm,&tsdm);CHKERRQ(ierr); 531 ierr = DMTSGetRHSJacobian(dm,&rhsjacobianfunc,&ctx);CHKERRQ(ierr); 532 ierr = DMTSGetIJacobian(dm,&ijacobianfunc,NULL);CHKERRQ(ierr); 533 ierr = DMTSGetRHSFunction(dm,&rhsfunction,&ctx);CHKERRQ(ierr); 534 ierr = PetscObjectStateGet((PetscObject)U,&Ustate);CHKERRQ(ierr); 535 if (ts->rhsjacobian.time == t && (ts->problem_type == TS_LINEAR || (ts->rhsjacobian.X == U && ts->rhsjacobian.Xstate == Ustate)) && (rhsfunction != TSComputeRHSFunctionLinear)) { 536 PetscFunctionReturn(0); 537 } 538 539 if (!rhsjacobianfunc && !ijacobianfunc) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSJacobian() and / or TSSetIJacobian()"); 540 541 if (ts->rhsjacobian.reuse) { 542 ierr = MatShift(A,-ts->rhsjacobian.shift);CHKERRQ(ierr); 543 ierr = MatScale(A,1./ts->rhsjacobian.scale);CHKERRQ(ierr); 544 if (A != B) { 545 ierr = MatShift(B,-ts->rhsjacobian.shift);CHKERRQ(ierr); 546 ierr = MatScale(B,1./ts->rhsjacobian.scale);CHKERRQ(ierr); 547 } 548 ts->rhsjacobian.shift = 0; 549 ts->rhsjacobian.scale = 1.; 550 } 551 552 if (rhsjacobianfunc) { 553 PetscBool missing; 554 ierr = PetscLogEventBegin(TS_JacobianEval,ts,U,A,B);CHKERRQ(ierr); 555 PetscStackPush("TS user Jacobian function"); 556 ierr = (*rhsjacobianfunc)(ts,t,U,A,B,ctx);CHKERRQ(ierr); 557 PetscStackPop; 558 ierr = PetscLogEventEnd(TS_JacobianEval,ts,U,A,B);CHKERRQ(ierr); 559 if (A) { 560 ierr = MatMissingDiagonal(A,&missing,NULL);CHKERRQ(ierr); 561 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"); 562 } 563 if (B && B != A) { 564 ierr = MatMissingDiagonal(B,&missing,NULL);CHKERRQ(ierr); 565 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"); 566 } 567 } else { 568 ierr = MatZeroEntries(A);CHKERRQ(ierr); 569 if (A != B) {ierr = MatZeroEntries(B);CHKERRQ(ierr);} 570 } 571 ts->rhsjacobian.time = t; 572 ts->rhsjacobian.X = U; 573 ierr = PetscObjectStateGet((PetscObject)U,&ts->rhsjacobian.Xstate);CHKERRQ(ierr); 574 PetscFunctionReturn(0); 575 } 576 577 #undef __FUNCT__ 578 #define __FUNCT__ "TSComputeRHSFunction" 579 /*@ 580 TSComputeRHSFunction - Evaluates the right-hand-side function. 581 582 Collective on TS and Vec 583 584 Input Parameters: 585 + ts - the TS context 586 . t - current time 587 - U - state vector 588 589 Output Parameter: 590 . y - right hand side 591 592 Note: 593 Most users should not need to explicitly call this routine, as it 594 is used internally within the nonlinear solvers. 595 596 Level: developer 597 598 .keywords: TS, compute 599 600 .seealso: TSSetRHSFunction(), TSComputeIFunction() 601 @*/ 602 PetscErrorCode TSComputeRHSFunction(TS ts,PetscReal t,Vec U,Vec y) 603 { 604 PetscErrorCode ierr; 605 TSRHSFunction rhsfunction; 606 TSIFunction ifunction; 607 void *ctx; 608 DM dm; 609 610 PetscFunctionBegin; 611 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 612 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 613 PetscValidHeaderSpecific(y,VEC_CLASSID,4); 614 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 615 ierr = DMTSGetRHSFunction(dm,&rhsfunction,&ctx);CHKERRQ(ierr); 616 ierr = DMTSGetIFunction(dm,&ifunction,NULL);CHKERRQ(ierr); 617 618 if (!rhsfunction && !ifunction) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSFunction() and / or TSSetIFunction()"); 619 620 ierr = PetscLogEventBegin(TS_FunctionEval,ts,U,y,0);CHKERRQ(ierr); 621 if (rhsfunction) { 622 PetscStackPush("TS user right-hand-side function"); 623 ierr = (*rhsfunction)(ts,t,U,y,ctx);CHKERRQ(ierr); 624 PetscStackPop; 625 } else { 626 ierr = VecZeroEntries(y);CHKERRQ(ierr); 627 } 628 629 ierr = PetscLogEventEnd(TS_FunctionEval,ts,U,y,0);CHKERRQ(ierr); 630 PetscFunctionReturn(0); 631 } 632 633 #undef __FUNCT__ 634 #define __FUNCT__ "TSComputeSolutionFunction" 635 /*@ 636 TSComputeSolutionFunction - Evaluates the solution function. 637 638 Collective on TS and Vec 639 640 Input Parameters: 641 + ts - the TS context 642 - t - current time 643 644 Output Parameter: 645 . U - the solution 646 647 Note: 648 Most users should not need to explicitly call this routine, as it 649 is used internally within the nonlinear solvers. 650 651 Level: developer 652 653 .keywords: TS, compute 654 655 .seealso: TSSetSolutionFunction(), TSSetRHSFunction(), TSComputeIFunction() 656 @*/ 657 PetscErrorCode TSComputeSolutionFunction(TS ts,PetscReal t,Vec U) 658 { 659 PetscErrorCode ierr; 660 TSSolutionFunction solutionfunction; 661 void *ctx; 662 DM dm; 663 664 PetscFunctionBegin; 665 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 666 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 667 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 668 ierr = DMTSGetSolutionFunction(dm,&solutionfunction,&ctx);CHKERRQ(ierr); 669 670 if (solutionfunction) { 671 PetscStackPush("TS user solution function"); 672 ierr = (*solutionfunction)(ts,t,U,ctx);CHKERRQ(ierr); 673 PetscStackPop; 674 } 675 PetscFunctionReturn(0); 676 } 677 #undef __FUNCT__ 678 #define __FUNCT__ "TSComputeForcingFunction" 679 /*@ 680 TSComputeForcingFunction - Evaluates the forcing function. 681 682 Collective on TS and Vec 683 684 Input Parameters: 685 + ts - the TS context 686 - t - current time 687 688 Output Parameter: 689 . U - the function value 690 691 Note: 692 Most users should not need to explicitly call this routine, as it 693 is used internally within the nonlinear solvers. 694 695 Level: developer 696 697 .keywords: TS, compute 698 699 .seealso: TSSetSolutionFunction(), TSSetRHSFunction(), TSComputeIFunction() 700 @*/ 701 PetscErrorCode TSComputeForcingFunction(TS ts,PetscReal t,Vec U) 702 { 703 PetscErrorCode ierr, (*forcing)(TS,PetscReal,Vec,void*); 704 void *ctx; 705 DM dm; 706 707 PetscFunctionBegin; 708 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 709 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 710 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 711 ierr = DMTSGetForcingFunction(dm,&forcing,&ctx);CHKERRQ(ierr); 712 713 if (forcing) { 714 PetscStackPush("TS user forcing function"); 715 ierr = (*forcing)(ts,t,U,ctx);CHKERRQ(ierr); 716 PetscStackPop; 717 } 718 PetscFunctionReturn(0); 719 } 720 721 #undef __FUNCT__ 722 #define __FUNCT__ "TSGetRHSVec_Private" 723 static PetscErrorCode TSGetRHSVec_Private(TS ts,Vec *Frhs) 724 { 725 Vec F; 726 PetscErrorCode ierr; 727 728 PetscFunctionBegin; 729 *Frhs = NULL; 730 ierr = TSGetIFunction(ts,&F,NULL,NULL);CHKERRQ(ierr); 731 if (!ts->Frhs) { 732 ierr = VecDuplicate(F,&ts->Frhs);CHKERRQ(ierr); 733 } 734 *Frhs = ts->Frhs; 735 PetscFunctionReturn(0); 736 } 737 738 #undef __FUNCT__ 739 #define __FUNCT__ "TSGetRHSMats_Private" 740 static PetscErrorCode TSGetRHSMats_Private(TS ts,Mat *Arhs,Mat *Brhs) 741 { 742 Mat A,B; 743 PetscErrorCode ierr; 744 745 PetscFunctionBegin; 746 if (Arhs) *Arhs = NULL; 747 if (Brhs) *Brhs = NULL; 748 ierr = TSGetIJacobian(ts,&A,&B,NULL,NULL);CHKERRQ(ierr); 749 if (Arhs) { 750 if (!ts->Arhs) { 751 ierr = MatDuplicate(A,MAT_DO_NOT_COPY_VALUES,&ts->Arhs);CHKERRQ(ierr); 752 } 753 *Arhs = ts->Arhs; 754 } 755 if (Brhs) { 756 if (!ts->Brhs) { 757 if (A != B) { 758 ierr = MatDuplicate(B,MAT_DO_NOT_COPY_VALUES,&ts->Brhs);CHKERRQ(ierr); 759 } else { 760 ierr = PetscObjectReference((PetscObject)ts->Arhs);CHKERRQ(ierr); 761 ts->Brhs = ts->Arhs; 762 } 763 } 764 *Brhs = ts->Brhs; 765 } 766 PetscFunctionReturn(0); 767 } 768 769 #undef __FUNCT__ 770 #define __FUNCT__ "TSComputeIFunction" 771 /*@ 772 TSComputeIFunction - Evaluates the DAE residual written in implicit form F(t,U,Udot)=0 773 774 Collective on TS and Vec 775 776 Input Parameters: 777 + ts - the TS context 778 . t - current time 779 . U - state vector 780 . Udot - time derivative of state vector 781 - imex - flag indicates if the method is IMEX so that the RHSFunction should be kept separate 782 783 Output Parameter: 784 . Y - right hand side 785 786 Note: 787 Most users should not need to explicitly call this routine, as it 788 is used internally within the nonlinear solvers. 789 790 If the user did did not write their equations in implicit form, this 791 function recasts them in implicit form. 792 793 Level: developer 794 795 .keywords: TS, compute 796 797 .seealso: TSSetIFunction(), TSComputeRHSFunction() 798 @*/ 799 PetscErrorCode TSComputeIFunction(TS ts,PetscReal t,Vec U,Vec Udot,Vec Y,PetscBool imex) 800 { 801 PetscErrorCode ierr; 802 TSIFunction ifunction; 803 TSRHSFunction rhsfunction; 804 void *ctx; 805 DM dm; 806 807 PetscFunctionBegin; 808 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 809 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 810 PetscValidHeaderSpecific(Udot,VEC_CLASSID,4); 811 PetscValidHeaderSpecific(Y,VEC_CLASSID,5); 812 813 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 814 ierr = DMTSGetIFunction(dm,&ifunction,&ctx);CHKERRQ(ierr); 815 ierr = DMTSGetRHSFunction(dm,&rhsfunction,NULL);CHKERRQ(ierr); 816 817 if (!rhsfunction && !ifunction) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSFunction() and / or TSSetIFunction()"); 818 819 ierr = PetscLogEventBegin(TS_FunctionEval,ts,U,Udot,Y);CHKERRQ(ierr); 820 if (ifunction) { 821 PetscStackPush("TS user implicit function"); 822 ierr = (*ifunction)(ts,t,U,Udot,Y,ctx);CHKERRQ(ierr); 823 PetscStackPop; 824 } 825 if (imex) { 826 if (!ifunction) { 827 ierr = VecCopy(Udot,Y);CHKERRQ(ierr); 828 } 829 } else if (rhsfunction) { 830 if (ifunction) { 831 Vec Frhs; 832 ierr = TSGetRHSVec_Private(ts,&Frhs);CHKERRQ(ierr); 833 ierr = TSComputeRHSFunction(ts,t,U,Frhs);CHKERRQ(ierr); 834 ierr = VecAXPY(Y,-1,Frhs);CHKERRQ(ierr); 835 } else { 836 ierr = TSComputeRHSFunction(ts,t,U,Y);CHKERRQ(ierr); 837 ierr = VecAYPX(Y,-1,Udot);CHKERRQ(ierr); 838 } 839 } 840 ierr = PetscLogEventEnd(TS_FunctionEval,ts,U,Udot,Y);CHKERRQ(ierr); 841 PetscFunctionReturn(0); 842 } 843 844 #undef __FUNCT__ 845 #define __FUNCT__ "TSComputeIJacobian" 846 /*@ 847 TSComputeIJacobian - Evaluates the Jacobian of the DAE 848 849 Collective on TS and Vec 850 851 Input 852 Input Parameters: 853 + ts - the TS context 854 . t - current timestep 855 . U - state vector 856 . Udot - time derivative of state vector 857 . shift - shift to apply, see note below 858 - imex - flag indicates if the method is IMEX so that the RHSJacobian should be kept separate 859 860 Output Parameters: 861 + A - Jacobian matrix 862 . B - optional preconditioning matrix 863 - flag - flag indicating matrix structure 864 865 Notes: 866 If F(t,U,Udot)=0 is the DAE, the required Jacobian is 867 868 dF/dU + shift*dF/dUdot 869 870 Most users should not need to explicitly call this routine, as it 871 is used internally within the nonlinear solvers. 872 873 Level: developer 874 875 .keywords: TS, compute, Jacobian, matrix 876 877 .seealso: TSSetIJacobian() 878 @*/ 879 PetscErrorCode TSComputeIJacobian(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat A,Mat B,PetscBool imex) 880 { 881 PetscErrorCode ierr; 882 TSIJacobian ijacobian; 883 TSRHSJacobian rhsjacobian; 884 DM dm; 885 void *ctx; 886 887 PetscFunctionBegin; 888 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 889 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 890 PetscValidHeaderSpecific(Udot,VEC_CLASSID,4); 891 PetscValidPointer(A,6); 892 PetscValidHeaderSpecific(A,MAT_CLASSID,6); 893 PetscValidPointer(B,7); 894 PetscValidHeaderSpecific(B,MAT_CLASSID,7); 895 896 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 897 ierr = DMTSGetIJacobian(dm,&ijacobian,&ctx);CHKERRQ(ierr); 898 ierr = DMTSGetRHSJacobian(dm,&rhsjacobian,NULL);CHKERRQ(ierr); 899 900 if (!rhsjacobian && !ijacobian) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSJacobian() and / or TSSetIJacobian()"); 901 902 ierr = PetscLogEventBegin(TS_JacobianEval,ts,U,A,B);CHKERRQ(ierr); 903 if (ijacobian) { 904 PetscBool missing; 905 PetscStackPush("TS user implicit Jacobian"); 906 ierr = (*ijacobian)(ts,t,U,Udot,shift,A,B,ctx);CHKERRQ(ierr); 907 PetscStackPop; 908 if (A) { 909 ierr = MatMissingDiagonal(A,&missing,NULL);CHKERRQ(ierr); 910 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"); 911 } 912 if (B && B != A) { 913 ierr = MatMissingDiagonal(B,&missing,NULL);CHKERRQ(ierr); 914 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"); 915 } 916 } 917 if (imex) { 918 if (!ijacobian) { /* system was written as Udot = G(t,U) */ 919 ierr = MatZeroEntries(A);CHKERRQ(ierr); 920 ierr = MatShift(A,shift);CHKERRQ(ierr); 921 if (A != B) { 922 ierr = MatZeroEntries(B);CHKERRQ(ierr); 923 ierr = MatShift(B,shift);CHKERRQ(ierr); 924 } 925 } 926 } else { 927 Mat Arhs = NULL,Brhs = NULL; 928 if (rhsjacobian) { 929 ierr = TSGetRHSMats_Private(ts,&Arhs,&Brhs);CHKERRQ(ierr); 930 ierr = TSComputeRHSJacobian(ts,t,U,Arhs,Brhs);CHKERRQ(ierr); 931 } 932 if (Arhs == A) { /* No IJacobian, so we only have the RHS matrix */ 933 ts->rhsjacobian.scale = -1; 934 ts->rhsjacobian.shift = shift; 935 ierr = MatScale(A,-1);CHKERRQ(ierr); 936 ierr = MatShift(A,shift);CHKERRQ(ierr); 937 if (A != B) { 938 ierr = MatScale(B,-1);CHKERRQ(ierr); 939 ierr = MatShift(B,shift);CHKERRQ(ierr); 940 } 941 } else if (Arhs) { /* Both IJacobian and RHSJacobian */ 942 MatStructure axpy = DIFFERENT_NONZERO_PATTERN; 943 if (!ijacobian) { /* No IJacobian provided, but we have a separate RHS matrix */ 944 ierr = MatZeroEntries(A);CHKERRQ(ierr); 945 ierr = MatShift(A,shift);CHKERRQ(ierr); 946 if (A != B) { 947 ierr = MatZeroEntries(B);CHKERRQ(ierr); 948 ierr = MatShift(B,shift);CHKERRQ(ierr); 949 } 950 } 951 ierr = MatAXPY(A,-1,Arhs,axpy);CHKERRQ(ierr); 952 if (A != B) { 953 ierr = MatAXPY(B,-1,Brhs,axpy);CHKERRQ(ierr); 954 } 955 } 956 } 957 ierr = PetscLogEventEnd(TS_JacobianEval,ts,U,A,B);CHKERRQ(ierr); 958 PetscFunctionReturn(0); 959 } 960 961 #undef __FUNCT__ 962 #define __FUNCT__ "TSSetRHSFunction" 963 /*@C 964 TSSetRHSFunction - Sets the routine for evaluating the function, 965 where U_t = G(t,u). 966 967 Logically Collective on TS 968 969 Input Parameters: 970 + ts - the TS context obtained from TSCreate() 971 . r - vector to put the computed right hand side (or NULL to have it created) 972 . f - routine for evaluating the right-hand-side function 973 - ctx - [optional] user-defined context for private data for the 974 function evaluation routine (may be NULL) 975 976 Calling sequence of func: 977 $ func (TS ts,PetscReal t,Vec u,Vec F,void *ctx); 978 979 + t - current timestep 980 . u - input vector 981 . F - function vector 982 - ctx - [optional] user-defined function context 983 984 Level: beginner 985 986 Notes: You must call this function or TSSetIFunction() to define your ODE. You cannot use this function when solving a DAE. 987 988 .keywords: TS, timestep, set, right-hand-side, function 989 990 .seealso: TSSetRHSJacobian(), TSSetIJacobian(), TSSetIFunction() 991 @*/ 992 PetscErrorCode TSSetRHSFunction(TS ts,Vec r,PetscErrorCode (*f)(TS,PetscReal,Vec,Vec,void*),void *ctx) 993 { 994 PetscErrorCode ierr; 995 SNES snes; 996 Vec ralloc = NULL; 997 DM dm; 998 999 PetscFunctionBegin; 1000 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1001 if (r) PetscValidHeaderSpecific(r,VEC_CLASSID,2); 1002 1003 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1004 ierr = DMTSSetRHSFunction(dm,f,ctx);CHKERRQ(ierr); 1005 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1006 if (!r && !ts->dm && ts->vec_sol) { 1007 ierr = VecDuplicate(ts->vec_sol,&ralloc);CHKERRQ(ierr); 1008 r = ralloc; 1009 } 1010 ierr = SNESSetFunction(snes,r,SNESTSFormFunction,ts);CHKERRQ(ierr); 1011 ierr = VecDestroy(&ralloc);CHKERRQ(ierr); 1012 PetscFunctionReturn(0); 1013 } 1014 1015 #undef __FUNCT__ 1016 #define __FUNCT__ "TSSetSolutionFunction" 1017 /*@C 1018 TSSetSolutionFunction - Provide a function that computes the solution of the ODE or DAE 1019 1020 Logically Collective on TS 1021 1022 Input Parameters: 1023 + ts - the TS context obtained from TSCreate() 1024 . f - routine for evaluating the solution 1025 - ctx - [optional] user-defined context for private data for the 1026 function evaluation routine (may be NULL) 1027 1028 Calling sequence of func: 1029 $ func (TS ts,PetscReal t,Vec u,void *ctx); 1030 1031 + t - current timestep 1032 . u - output vector 1033 - ctx - [optional] user-defined function context 1034 1035 Notes: 1036 This routine is used for testing accuracy of time integration schemes when you already know the solution. 1037 If analytic solutions are not known for your system, consider using the Method of Manufactured Solutions to 1038 create closed-form solutions with non-physical forcing terms. 1039 1040 For low-dimensional problems solved in serial, such as small discrete systems, TSMonitorLGError() can be used to monitor the error history. 1041 1042 Level: beginner 1043 1044 .keywords: TS, timestep, set, right-hand-side, function 1045 1046 .seealso: TSSetRHSJacobian(), TSSetIJacobian(), TSComputeSolutionFunction(), TSSetForcingFunction() 1047 @*/ 1048 PetscErrorCode TSSetSolutionFunction(TS ts,PetscErrorCode (*f)(TS,PetscReal,Vec,void*),void *ctx) 1049 { 1050 PetscErrorCode ierr; 1051 DM dm; 1052 1053 PetscFunctionBegin; 1054 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1055 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1056 ierr = DMTSSetSolutionFunction(dm,f,ctx);CHKERRQ(ierr); 1057 PetscFunctionReturn(0); 1058 } 1059 1060 #undef __FUNCT__ 1061 #define __FUNCT__ "TSSetForcingFunction" 1062 /*@C 1063 TSSetForcingFunction - Provide a function that computes a forcing term for a ODE or PDE 1064 1065 Logically Collective on TS 1066 1067 Input Parameters: 1068 + ts - the TS context obtained from TSCreate() 1069 . f - routine for evaluating the forcing function 1070 - ctx - [optional] user-defined context for private data for the 1071 function evaluation routine (may be NULL) 1072 1073 Calling sequence of func: 1074 $ func (TS ts,PetscReal t,Vec u,void *ctx); 1075 1076 + t - current timestep 1077 . u - output vector 1078 - ctx - [optional] user-defined function context 1079 1080 Notes: 1081 This routine is useful for testing accuracy of time integration schemes when using the Method of Manufactured Solutions to 1082 create closed-form solutions with a non-physical forcing term. 1083 1084 For low-dimensional problems solved in serial, such as small discrete systems, TSMonitorLGError() can be used to monitor the error history. 1085 1086 Level: beginner 1087 1088 .keywords: TS, timestep, set, right-hand-side, function 1089 1090 .seealso: TSSetRHSJacobian(), TSSetIJacobian(), TSComputeSolutionFunction(), TSSetSolutionFunction() 1091 @*/ 1092 PetscErrorCode TSSetForcingFunction(TS ts,TSForcingFunction f,void *ctx) 1093 { 1094 PetscErrorCode ierr; 1095 DM dm; 1096 1097 PetscFunctionBegin; 1098 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1099 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1100 ierr = DMTSSetForcingFunction(dm,f,ctx);CHKERRQ(ierr); 1101 PetscFunctionReturn(0); 1102 } 1103 1104 #undef __FUNCT__ 1105 #define __FUNCT__ "TSSetRHSJacobian" 1106 /*@C 1107 TSSetRHSJacobian - Sets the function to compute the Jacobian of G, 1108 where U_t = G(U,t), as well as the location to store the matrix. 1109 1110 Logically Collective on TS 1111 1112 Input Parameters: 1113 + ts - the TS context obtained from TSCreate() 1114 . Amat - (approximate) Jacobian matrix 1115 . Pmat - matrix from which preconditioner is to be constructed (usually the same as Amat) 1116 . f - the Jacobian evaluation routine 1117 - ctx - [optional] user-defined context for private data for the 1118 Jacobian evaluation routine (may be NULL) 1119 1120 Calling sequence of f: 1121 $ func (TS ts,PetscReal t,Vec u,Mat A,Mat B,void *ctx); 1122 1123 + t - current timestep 1124 . u - input vector 1125 . Amat - (approximate) Jacobian matrix 1126 . Pmat - matrix from which preconditioner is to be constructed (usually the same as Amat) 1127 - ctx - [optional] user-defined context for matrix evaluation routine 1128 1129 Notes: 1130 You must set all the diagonal entries of the matrices, if they are zero you must still set them with a zero value 1131 1132 The TS solver may modify the nonzero structure and the entries of the matrices Amat and Pmat between the calls to f() 1133 You should not assume the values are the same in the next call to f() as you set them in the previous call. 1134 1135 Level: beginner 1136 1137 .keywords: TS, timestep, set, right-hand-side, Jacobian 1138 1139 .seealso: SNESComputeJacobianDefaultColor(), TSSetRHSFunction(), TSRHSJacobianSetReuse(), TSSetIJacobian() 1140 1141 @*/ 1142 PetscErrorCode TSSetRHSJacobian(TS ts,Mat Amat,Mat Pmat,TSRHSJacobian f,void *ctx) 1143 { 1144 PetscErrorCode ierr; 1145 SNES snes; 1146 DM dm; 1147 TSIJacobian ijacobian; 1148 1149 PetscFunctionBegin; 1150 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1151 if (Amat) PetscValidHeaderSpecific(Amat,MAT_CLASSID,2); 1152 if (Pmat) PetscValidHeaderSpecific(Pmat,MAT_CLASSID,3); 1153 if (Amat) PetscCheckSameComm(ts,1,Amat,2); 1154 if (Pmat) PetscCheckSameComm(ts,1,Pmat,3); 1155 1156 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1157 ierr = DMTSSetRHSJacobian(dm,f,ctx);CHKERRQ(ierr); 1158 if (f == TSComputeRHSJacobianConstant) { 1159 /* Handle this case automatically for the user; otherwise user should call themselves. */ 1160 ierr = TSRHSJacobianSetReuse(ts,PETSC_TRUE);CHKERRQ(ierr); 1161 } 1162 ierr = DMTSGetIJacobian(dm,&ijacobian,NULL);CHKERRQ(ierr); 1163 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1164 if (!ijacobian) { 1165 ierr = SNESSetJacobian(snes,Amat,Pmat,SNESTSFormJacobian,ts);CHKERRQ(ierr); 1166 } 1167 if (Amat) { 1168 ierr = PetscObjectReference((PetscObject)Amat);CHKERRQ(ierr); 1169 ierr = MatDestroy(&ts->Arhs);CHKERRQ(ierr); 1170 ts->Arhs = Amat; 1171 } 1172 if (Pmat) { 1173 ierr = PetscObjectReference((PetscObject)Pmat);CHKERRQ(ierr); 1174 ierr = MatDestroy(&ts->Brhs);CHKERRQ(ierr); 1175 ts->Brhs = Pmat; 1176 } 1177 PetscFunctionReturn(0); 1178 } 1179 1180 1181 #undef __FUNCT__ 1182 #define __FUNCT__ "TSSetIFunction" 1183 /*@C 1184 TSSetIFunction - Set the function to compute F(t,U,U_t) where F() = 0 is the DAE to be solved. 1185 1186 Logically Collective on TS 1187 1188 Input Parameters: 1189 + ts - the TS context obtained from TSCreate() 1190 . r - vector to hold the residual (or NULL to have it created internally) 1191 . f - the function evaluation routine 1192 - ctx - user-defined context for private data for the function evaluation routine (may be NULL) 1193 1194 Calling sequence of f: 1195 $ f(TS ts,PetscReal t,Vec u,Vec u_t,Vec F,ctx); 1196 1197 + t - time at step/stage being solved 1198 . u - state vector 1199 . u_t - time derivative of state vector 1200 . F - function vector 1201 - ctx - [optional] user-defined context for matrix evaluation routine 1202 1203 Important: 1204 The user MUST call either this routine or TSSetRHSFunction() to define the ODE. When solving DAEs you must use this function. 1205 1206 Level: beginner 1207 1208 .keywords: TS, timestep, set, DAE, Jacobian 1209 1210 .seealso: TSSetRHSJacobian(), TSSetRHSFunction(), TSSetIJacobian() 1211 @*/ 1212 PetscErrorCode TSSetIFunction(TS ts,Vec r,TSIFunction f,void *ctx) 1213 { 1214 PetscErrorCode ierr; 1215 SNES snes; 1216 Vec ralloc = NULL; 1217 DM dm; 1218 1219 PetscFunctionBegin; 1220 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1221 if (r) PetscValidHeaderSpecific(r,VEC_CLASSID,2); 1222 1223 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1224 ierr = DMTSSetIFunction(dm,f,ctx);CHKERRQ(ierr); 1225 1226 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1227 if (!r && !ts->dm && ts->vec_sol) { 1228 ierr = VecDuplicate(ts->vec_sol,&ralloc);CHKERRQ(ierr); 1229 r = ralloc; 1230 } 1231 ierr = SNESSetFunction(snes,r,SNESTSFormFunction,ts);CHKERRQ(ierr); 1232 ierr = VecDestroy(&ralloc);CHKERRQ(ierr); 1233 PetscFunctionReturn(0); 1234 } 1235 1236 #undef __FUNCT__ 1237 #define __FUNCT__ "TSGetIFunction" 1238 /*@C 1239 TSGetIFunction - Returns the vector where the implicit residual is stored and the function/contex to compute it. 1240 1241 Not Collective 1242 1243 Input Parameter: 1244 . ts - the TS context 1245 1246 Output Parameter: 1247 + r - vector to hold residual (or NULL) 1248 . func - the function to compute residual (or NULL) 1249 - ctx - the function context (or NULL) 1250 1251 Level: advanced 1252 1253 .keywords: TS, nonlinear, get, function 1254 1255 .seealso: TSSetIFunction(), SNESGetFunction() 1256 @*/ 1257 PetscErrorCode TSGetIFunction(TS ts,Vec *r,TSIFunction *func,void **ctx) 1258 { 1259 PetscErrorCode ierr; 1260 SNES snes; 1261 DM dm; 1262 1263 PetscFunctionBegin; 1264 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1265 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1266 ierr = SNESGetFunction(snes,r,NULL,NULL);CHKERRQ(ierr); 1267 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1268 ierr = DMTSGetIFunction(dm,func,ctx);CHKERRQ(ierr); 1269 PetscFunctionReturn(0); 1270 } 1271 1272 #undef __FUNCT__ 1273 #define __FUNCT__ "TSGetRHSFunction" 1274 /*@C 1275 TSGetRHSFunction - Returns the vector where the right hand side is stored and the function/context to compute it. 1276 1277 Not Collective 1278 1279 Input Parameter: 1280 . ts - the TS context 1281 1282 Output Parameter: 1283 + r - vector to hold computed right hand side (or NULL) 1284 . func - the function to compute right hand side (or NULL) 1285 - ctx - the function context (or NULL) 1286 1287 Level: advanced 1288 1289 .keywords: TS, nonlinear, get, function 1290 1291 .seealso: TSSetRHSFunction(), SNESGetFunction() 1292 @*/ 1293 PetscErrorCode TSGetRHSFunction(TS ts,Vec *r,TSRHSFunction *func,void **ctx) 1294 { 1295 PetscErrorCode ierr; 1296 SNES snes; 1297 DM dm; 1298 1299 PetscFunctionBegin; 1300 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1301 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1302 ierr = SNESGetFunction(snes,r,NULL,NULL);CHKERRQ(ierr); 1303 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1304 ierr = DMTSGetRHSFunction(dm,func,ctx);CHKERRQ(ierr); 1305 PetscFunctionReturn(0); 1306 } 1307 1308 #undef __FUNCT__ 1309 #define __FUNCT__ "TSSetIJacobian" 1310 /*@C 1311 TSSetIJacobian - Set the function to compute the matrix dF/dU + a*dF/dU_t where F(t,U,U_t) is the function 1312 provided with TSSetIFunction(). 1313 1314 Logically Collective on TS 1315 1316 Input Parameters: 1317 + ts - the TS context obtained from TSCreate() 1318 . Amat - (approximate) Jacobian matrix 1319 . Pmat - matrix used to compute preconditioner (usually the same as Amat) 1320 . f - the Jacobian evaluation routine 1321 - ctx - user-defined context for private data for the Jacobian evaluation routine (may be NULL) 1322 1323 Calling sequence of f: 1324 $ f(TS ts,PetscReal t,Vec U,Vec U_t,PetscReal a,Mat Amat,Mat Pmat,void *ctx); 1325 1326 + t - time at step/stage being solved 1327 . U - state vector 1328 . U_t - time derivative of state vector 1329 . a - shift 1330 . Amat - (approximate) Jacobian of F(t,U,W+a*U), equivalent to dF/dU + a*dF/dU_t 1331 . Pmat - matrix used for constructing preconditioner, usually the same as Amat 1332 - ctx - [optional] user-defined context for matrix evaluation routine 1333 1334 Notes: 1335 The matrices Amat and Pmat are exactly the matrices that are used by SNES for the nonlinear solve. 1336 1337 If you know the operator Amat has a null space you can use MatSetNullSpace() and MatSetTransposeNullSpace() to supply the null 1338 space to Amat and the KSP solvers will automatically use that null space as needed during the solution process. 1339 1340 The matrix dF/dU + a*dF/dU_t you provide turns out to be 1341 the Jacobian of F(t,U,W+a*U) where F(t,U,U_t) = 0 is the DAE to be solved. 1342 The time integrator internally approximates U_t by W+a*U where the positive "shift" 1343 a and vector W depend on the integration method, step size, and past states. For example with 1344 the backward Euler method a = 1/dt and W = -a*U(previous timestep) so 1345 W + a*U = a*(U - U(previous timestep)) = (U - U(previous timestep))/dt 1346 1347 You must set all the diagonal entries of the matrices, if they are zero you must still set them with a zero value 1348 1349 The TS solver may modify the nonzero structure and the entries of the matrices Amat and Pmat between the calls to f() 1350 You should not assume the values are the same in the next call to f() as you set them in the previous call. 1351 1352 Level: beginner 1353 1354 .keywords: TS, timestep, DAE, Jacobian 1355 1356 .seealso: TSSetIFunction(), TSSetRHSJacobian(), SNESComputeJacobianDefaultColor(), SNESComputeJacobianDefault(), TSSetRHSFunction() 1357 1358 @*/ 1359 PetscErrorCode TSSetIJacobian(TS ts,Mat Amat,Mat Pmat,TSIJacobian f,void *ctx) 1360 { 1361 PetscErrorCode ierr; 1362 SNES snes; 1363 DM dm; 1364 1365 PetscFunctionBegin; 1366 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1367 if (Amat) PetscValidHeaderSpecific(Amat,MAT_CLASSID,2); 1368 if (Pmat) PetscValidHeaderSpecific(Pmat,MAT_CLASSID,3); 1369 if (Amat) PetscCheckSameComm(ts,1,Amat,2); 1370 if (Pmat) PetscCheckSameComm(ts,1,Pmat,3); 1371 1372 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1373 ierr = DMTSSetIJacobian(dm,f,ctx);CHKERRQ(ierr); 1374 1375 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1376 ierr = SNESSetJacobian(snes,Amat,Pmat,SNESTSFormJacobian,ts);CHKERRQ(ierr); 1377 PetscFunctionReturn(0); 1378 } 1379 1380 #undef __FUNCT__ 1381 #define __FUNCT__ "TSRHSJacobianSetReuse" 1382 /*@ 1383 TSRHSJacobianSetReuse - restore RHS Jacobian before re-evaluating. Without this flag, TS will change the sign and 1384 shift the RHS Jacobian for a finite-time-step implicit solve, in which case the user function will need to recompute 1385 the entire Jacobian. The reuse flag must be set if the evaluation function will assume that the matrix entries have 1386 not been changed by the TS. 1387 1388 Logically Collective 1389 1390 Input Arguments: 1391 + ts - TS context obtained from TSCreate() 1392 - reuse - PETSC_TRUE if the RHS Jacobian 1393 1394 Level: intermediate 1395 1396 .seealso: TSSetRHSJacobian(), TSComputeRHSJacobianConstant() 1397 @*/ 1398 PetscErrorCode TSRHSJacobianSetReuse(TS ts,PetscBool reuse) 1399 { 1400 PetscFunctionBegin; 1401 ts->rhsjacobian.reuse = reuse; 1402 PetscFunctionReturn(0); 1403 } 1404 1405 #undef __FUNCT__ 1406 #define __FUNCT__ "TSSetI2Function" 1407 /*@C 1408 TSSetI2Function - Set the function to compute F(t,U,U_t,U_tt) where F = 0 is the DAE to be solved. 1409 1410 Logically Collective on TS 1411 1412 Input Parameters: 1413 + ts - the TS context obtained from TSCreate() 1414 . F - vector to hold the residual (or NULL to have it created internally) 1415 . fun - the function evaluation routine 1416 - ctx - user-defined context for private data for the function evaluation routine (may be NULL) 1417 1418 Calling sequence of fun: 1419 $ fun(TS ts,PetscReal t,Vec U,Vec U_t,Vec U_tt,Vec F,ctx); 1420 1421 + t - time at step/stage being solved 1422 . U - state vector 1423 . U_t - time derivative of state vector 1424 . U_tt - second time derivative of state vector 1425 . F - function vector 1426 - ctx - [optional] user-defined context for matrix evaluation routine (may be NULL) 1427 1428 Level: beginner 1429 1430 .keywords: TS, timestep, set, ODE, DAE, Function 1431 1432 .seealso: TSSetI2Jacobian() 1433 @*/ 1434 PetscErrorCode TSSetI2Function(TS ts,Vec F,TSI2Function fun,void *ctx) 1435 { 1436 DM dm; 1437 PetscErrorCode ierr; 1438 1439 PetscFunctionBegin; 1440 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1441 if (F) PetscValidHeaderSpecific(F,VEC_CLASSID,2); 1442 ierr = TSSetIFunction(ts,F,NULL,NULL);CHKERRQ(ierr); 1443 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1444 ierr = DMTSSetI2Function(dm,fun,ctx);CHKERRQ(ierr); 1445 PetscFunctionReturn(0); 1446 } 1447 1448 #undef __FUNCT__ 1449 #define __FUNCT__ "TSGetI2Function" 1450 /*@C 1451 TSGetI2Function - Returns the vector where the implicit residual is stored and the function/contex to compute it. 1452 1453 Not Collective 1454 1455 Input Parameter: 1456 . ts - the TS context 1457 1458 Output Parameter: 1459 + r - vector to hold residual (or NULL) 1460 . fun - the function to compute residual (or NULL) 1461 - ctx - the function context (or NULL) 1462 1463 Level: advanced 1464 1465 .keywords: TS, nonlinear, get, function 1466 1467 .seealso: TSSetI2Function(), SNESGetFunction() 1468 @*/ 1469 PetscErrorCode TSGetI2Function(TS ts,Vec *r,TSI2Function *fun,void **ctx) 1470 { 1471 PetscErrorCode ierr; 1472 SNES snes; 1473 DM dm; 1474 1475 PetscFunctionBegin; 1476 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1477 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1478 ierr = SNESGetFunction(snes,r,NULL,NULL);CHKERRQ(ierr); 1479 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1480 ierr = DMTSGetI2Function(dm,fun,ctx);CHKERRQ(ierr); 1481 PetscFunctionReturn(0); 1482 } 1483 1484 #undef __FUNCT__ 1485 #define __FUNCT__ "TSSetI2Jacobian" 1486 /*@C 1487 TSSetI2Jacobian - Set the function to compute the matrix dF/dU + v*dF/dU_t + a*dF/dU_tt 1488 where F(t,U,U_t,U_tt) is the function you provided with TSSetI2Function(). 1489 1490 Logically Collective on TS 1491 1492 Input Parameters: 1493 + ts - the TS context obtained from TSCreate() 1494 . J - Jacobian matrix 1495 . P - preconditioning matrix for J (may be same as J) 1496 . jac - the Jacobian evaluation routine 1497 - ctx - user-defined context for private data for the Jacobian evaluation routine (may be NULL) 1498 1499 Calling sequence of jac: 1500 $ jac(TS ts,PetscReal t,Vec U,Vec U_t,Vec U_tt,PetscReal v,PetscReal a,Mat J,Mat P,void *ctx); 1501 1502 + t - time at step/stage being solved 1503 . U - state vector 1504 . U_t - time derivative of state vector 1505 . U_tt - second time derivative of state vector 1506 . v - shift for U_t 1507 . a - shift for U_tt 1508 . J - Jacobian of G(U) = F(t,U,W+v*U,W'+a*U), equivalent to dF/dU + v*dF/dU_t + a*dF/dU_tt 1509 . P - preconditioning matrix for J, may be same as J 1510 - ctx - [optional] user-defined context for matrix evaluation routine 1511 1512 Notes: 1513 The matrices J and P are exactly the matrices that are used by SNES for the nonlinear solve. 1514 1515 The matrix dF/dU + v*dF/dU_t + a*dF/dU_tt you provide turns out to be 1516 the Jacobian of G(U) = F(t,U,W+v*U,W'+a*U) where F(t,U,U_t,U_tt) = 0 is the DAE to be solved. 1517 The time integrator internally approximates U_t by W+v*U and U_tt by W'+a*U where the positive "shift" 1518 parameters 'v' and 'a' and vectors W, W' depend on the integration method, step size, and past states. 1519 1520 Level: beginner 1521 1522 .keywords: TS, timestep, set, ODE, DAE, Jacobian 1523 1524 .seealso: TSSetI2Function() 1525 @*/ 1526 PetscErrorCode TSSetI2Jacobian(TS ts,Mat J,Mat P,TSI2Jacobian jac,void *ctx) 1527 { 1528 DM dm; 1529 PetscErrorCode ierr; 1530 1531 PetscFunctionBegin; 1532 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1533 if (J) PetscValidHeaderSpecific(J,MAT_CLASSID,2); 1534 if (P) PetscValidHeaderSpecific(P,MAT_CLASSID,3); 1535 ierr = TSSetIJacobian(ts,J,P,NULL,NULL);CHKERRQ(ierr); 1536 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1537 ierr = DMTSSetI2Jacobian(dm,jac,ctx);CHKERRQ(ierr); 1538 PetscFunctionReturn(0); 1539 } 1540 1541 #undef __FUNCT__ 1542 #define __FUNCT__ "TSGetI2Jacobian" 1543 /*@C 1544 TSGetI2Jacobian - Returns the implicit Jacobian at the present timestep. 1545 1546 Not Collective, but parallel objects are returned if TS is parallel 1547 1548 Input Parameter: 1549 . ts - The TS context obtained from TSCreate() 1550 1551 Output Parameters: 1552 + J - The (approximate) Jacobian of F(t,U,U_t,U_tt) 1553 . P - The matrix from which the preconditioner is constructed, often the same as J 1554 . jac - The function to compute the Jacobian matrices 1555 - ctx - User-defined context for Jacobian evaluation routine 1556 1557 Notes: You can pass in NULL for any return argument you do not need. 1558 1559 Level: advanced 1560 1561 .seealso: TSGetTimeStep(), TSGetMatrices(), TSGetTime(), TSGetTimeStepNumber() 1562 1563 .keywords: TS, timestep, get, matrix, Jacobian 1564 @*/ 1565 PetscErrorCode TSGetI2Jacobian(TS ts,Mat *J,Mat *P,TSI2Jacobian *jac,void **ctx) 1566 { 1567 PetscErrorCode ierr; 1568 SNES snes; 1569 DM dm; 1570 1571 PetscFunctionBegin; 1572 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1573 ierr = SNESSetUpMatrices(snes);CHKERRQ(ierr); 1574 ierr = SNESGetJacobian(snes,J,P,NULL,NULL);CHKERRQ(ierr); 1575 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1576 ierr = DMTSGetI2Jacobian(dm,jac,ctx);CHKERRQ(ierr); 1577 PetscFunctionReturn(0); 1578 } 1579 1580 #undef __FUNCT__ 1581 #define __FUNCT__ "TSComputeI2Function" 1582 /*@ 1583 TSComputeI2Function - Evaluates the DAE residual written in implicit form F(t,U,U_t,U_tt) = 0 1584 1585 Collective on TS and Vec 1586 1587 Input Parameters: 1588 + ts - the TS context 1589 . t - current time 1590 . U - state vector 1591 . V - time derivative of state vector (U_t) 1592 - A - second time derivative of state vector (U_tt) 1593 1594 Output Parameter: 1595 . F - the residual vector 1596 1597 Note: 1598 Most users should not need to explicitly call this routine, as it 1599 is used internally within the nonlinear solvers. 1600 1601 Level: developer 1602 1603 .keywords: TS, compute, function, vector 1604 1605 .seealso: TSSetI2Function() 1606 @*/ 1607 PetscErrorCode TSComputeI2Function(TS ts,PetscReal t,Vec U,Vec V,Vec A,Vec F) 1608 { 1609 DM dm; 1610 TSI2Function I2Function; 1611 void *ctx; 1612 TSRHSFunction rhsfunction; 1613 PetscErrorCode ierr; 1614 1615 PetscFunctionBegin; 1616 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1617 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 1618 PetscValidHeaderSpecific(V,VEC_CLASSID,4); 1619 PetscValidHeaderSpecific(A,VEC_CLASSID,5); 1620 PetscValidHeaderSpecific(F,VEC_CLASSID,6); 1621 1622 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1623 ierr = DMTSGetI2Function(dm,&I2Function,&ctx);CHKERRQ(ierr); 1624 ierr = DMTSGetRHSFunction(dm,&rhsfunction,NULL);CHKERRQ(ierr); 1625 1626 if (!I2Function) { 1627 ierr = TSComputeIFunction(ts,t,U,A,F,PETSC_FALSE);CHKERRQ(ierr); 1628 PetscFunctionReturn(0); 1629 } 1630 1631 ierr = PetscLogEventBegin(TS_FunctionEval,ts,U,V,F);CHKERRQ(ierr); 1632 1633 PetscStackPush("TS user implicit function"); 1634 ierr = I2Function(ts,t,U,V,A,F,ctx);CHKERRQ(ierr); 1635 PetscStackPop; 1636 1637 if (rhsfunction) { 1638 Vec Frhs; 1639 ierr = TSGetRHSVec_Private(ts,&Frhs);CHKERRQ(ierr); 1640 ierr = TSComputeRHSFunction(ts,t,U,Frhs);CHKERRQ(ierr); 1641 ierr = VecAXPY(F,-1,Frhs);CHKERRQ(ierr); 1642 } 1643 1644 ierr = PetscLogEventEnd(TS_FunctionEval,ts,U,V,F);CHKERRQ(ierr); 1645 PetscFunctionReturn(0); 1646 } 1647 1648 #undef __FUNCT__ 1649 #define __FUNCT__ "TSComputeI2Jacobian" 1650 /*@ 1651 TSComputeI2Jacobian - Evaluates the Jacobian of the DAE 1652 1653 Collective on TS and Vec 1654 1655 Input Parameters: 1656 + ts - the TS context 1657 . t - current timestep 1658 . U - state vector 1659 . V - time derivative of state vector 1660 . A - second time derivative of state vector 1661 . shiftV - shift to apply, see note below 1662 - shiftA - shift to apply, see note below 1663 1664 Output Parameters: 1665 + J - Jacobian matrix 1666 - P - optional preconditioning matrix 1667 1668 Notes: 1669 If F(t,U,V,A)=0 is the DAE, the required Jacobian is 1670 1671 dF/dU + shiftV*dF/dV + shiftA*dF/dA 1672 1673 Most users should not need to explicitly call this routine, as it 1674 is used internally within the nonlinear solvers. 1675 1676 Level: developer 1677 1678 .keywords: TS, compute, Jacobian, matrix 1679 1680 .seealso: TSSetI2Jacobian() 1681 @*/ 1682 PetscErrorCode TSComputeI2Jacobian(TS ts,PetscReal t,Vec U,Vec V,Vec A,PetscReal shiftV,PetscReal shiftA,Mat J,Mat P) 1683 { 1684 DM dm; 1685 TSI2Jacobian I2Jacobian; 1686 void *ctx; 1687 TSRHSJacobian rhsjacobian; 1688 PetscErrorCode ierr; 1689 1690 PetscFunctionBegin; 1691 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1692 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 1693 PetscValidHeaderSpecific(V,VEC_CLASSID,4); 1694 PetscValidHeaderSpecific(A,VEC_CLASSID,5); 1695 PetscValidHeaderSpecific(J,MAT_CLASSID,8); 1696 PetscValidHeaderSpecific(P,MAT_CLASSID,9); 1697 1698 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1699 ierr = DMTSGetI2Jacobian(dm,&I2Jacobian,&ctx);CHKERRQ(ierr); 1700 ierr = DMTSGetRHSJacobian(dm,&rhsjacobian,NULL);CHKERRQ(ierr); 1701 1702 if (!I2Jacobian) { 1703 ierr = TSComputeIJacobian(ts,t,U,A,shiftA,J,P,PETSC_FALSE);CHKERRQ(ierr); 1704 PetscFunctionReturn(0); 1705 } 1706 1707 ierr = PetscLogEventBegin(TS_JacobianEval,ts,U,J,P);CHKERRQ(ierr); 1708 1709 PetscStackPush("TS user implicit Jacobian"); 1710 ierr = I2Jacobian(ts,t,U,V,A,shiftV,shiftA,J,P,ctx);CHKERRQ(ierr); 1711 PetscStackPop; 1712 1713 if (rhsjacobian) { 1714 Mat Jrhs,Prhs; MatStructure axpy = DIFFERENT_NONZERO_PATTERN; 1715 ierr = TSGetRHSMats_Private(ts,&Jrhs,&Prhs);CHKERRQ(ierr); 1716 ierr = TSComputeRHSJacobian(ts,t,U,Jrhs,Prhs);CHKERRQ(ierr); 1717 ierr = MatAXPY(J,-1,Jrhs,axpy);CHKERRQ(ierr); 1718 if (P != J) {ierr = MatAXPY(P,-1,Prhs,axpy);CHKERRQ(ierr);} 1719 } 1720 1721 ierr = PetscLogEventEnd(TS_JacobianEval,ts,U,J,P);CHKERRQ(ierr); 1722 PetscFunctionReturn(0); 1723 } 1724 1725 #undef __FUNCT__ 1726 #define __FUNCT__ "TS2SetSolution" 1727 /*@ 1728 TS2SetSolution - Sets the initial solution and time derivative vectors 1729 for use by the TS routines handling second order equations. 1730 1731 Logically Collective on TS and Vec 1732 1733 Input Parameters: 1734 + ts - the TS context obtained from TSCreate() 1735 . u - the solution vector 1736 - v - the time derivative vector 1737 1738 Level: beginner 1739 1740 .keywords: TS, timestep, set, solution, initial conditions 1741 @*/ 1742 PetscErrorCode TS2SetSolution(TS ts,Vec u,Vec v) 1743 { 1744 PetscErrorCode ierr; 1745 1746 PetscFunctionBegin; 1747 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1748 PetscValidHeaderSpecific(u,VEC_CLASSID,2); 1749 PetscValidHeaderSpecific(v,VEC_CLASSID,3); 1750 ierr = TSSetSolution(ts,u);CHKERRQ(ierr); 1751 ierr = PetscObjectReference((PetscObject)v);CHKERRQ(ierr); 1752 ierr = VecDestroy(&ts->vec_dot);CHKERRQ(ierr); 1753 ts->vec_dot = v; 1754 PetscFunctionReturn(0); 1755 } 1756 1757 #undef __FUNCT__ 1758 #define __FUNCT__ "TS2GetSolution" 1759 /*@ 1760 TS2GetSolution - Returns the solution and time derivative at the present timestep 1761 for second order equations. It is valid to call this routine inside the function 1762 that you are evaluating in order to move to the new timestep. This vector not 1763 changed until the solution at the next timestep has been calculated. 1764 1765 Not Collective, but Vec returned is parallel if TS is parallel 1766 1767 Input Parameter: 1768 . ts - the TS context obtained from TSCreate() 1769 1770 Output Parameter: 1771 + u - the vector containing the solution 1772 - v - the vector containing the time derivative 1773 1774 Level: intermediate 1775 1776 .seealso: TS2SetSolution(), TSGetTimeStep(), TSGetTime() 1777 1778 .keywords: TS, timestep, get, solution 1779 @*/ 1780 PetscErrorCode TS2GetSolution(TS ts,Vec *u,Vec *v) 1781 { 1782 PetscFunctionBegin; 1783 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1784 if (u) PetscValidPointer(u,2); 1785 if (v) PetscValidPointer(v,3); 1786 if (u) *u = ts->vec_sol; 1787 if (v) *v = ts->vec_dot; 1788 PetscFunctionReturn(0); 1789 } 1790 1791 #undef __FUNCT__ 1792 #define __FUNCT__ "TSLoad" 1793 /*@C 1794 TSLoad - Loads a KSP that has been stored in binary with KSPView(). 1795 1796 Collective on PetscViewer 1797 1798 Input Parameters: 1799 + newdm - the newly loaded TS, this needs to have been created with TSCreate() or 1800 some related function before a call to TSLoad(). 1801 - viewer - binary file viewer, obtained from PetscViewerBinaryOpen() 1802 1803 Level: intermediate 1804 1805 Notes: 1806 The type is determined by the data in the file, any type set into the TS before this call is ignored. 1807 1808 Notes for advanced users: 1809 Most users should not need to know the details of the binary storage 1810 format, since TSLoad() and TSView() completely hide these details. 1811 But for anyone who's interested, the standard binary matrix storage 1812 format is 1813 .vb 1814 has not yet been determined 1815 .ve 1816 1817 .seealso: PetscViewerBinaryOpen(), TSView(), MatLoad(), VecLoad() 1818 @*/ 1819 PetscErrorCode TSLoad(TS ts, PetscViewer viewer) 1820 { 1821 PetscErrorCode ierr; 1822 PetscBool isbinary; 1823 PetscInt classid; 1824 char type[256]; 1825 DMTS sdm; 1826 DM dm; 1827 1828 PetscFunctionBegin; 1829 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1830 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,2); 1831 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1832 if (!isbinary) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid viewer; open viewer with PetscViewerBinaryOpen()"); 1833 1834 ierr = PetscViewerBinaryRead(viewer,&classid,1,NULL,PETSC_INT);CHKERRQ(ierr); 1835 if (classid != TS_FILE_CLASSID) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Not TS next in file"); 1836 ierr = PetscViewerBinaryRead(viewer,type,256,NULL,PETSC_CHAR);CHKERRQ(ierr); 1837 ierr = TSSetType(ts, type);CHKERRQ(ierr); 1838 if (ts->ops->load) { 1839 ierr = (*ts->ops->load)(ts,viewer);CHKERRQ(ierr); 1840 } 1841 ierr = DMCreate(PetscObjectComm((PetscObject)ts),&dm);CHKERRQ(ierr); 1842 ierr = DMLoad(dm,viewer);CHKERRQ(ierr); 1843 ierr = TSSetDM(ts,dm);CHKERRQ(ierr); 1844 ierr = DMCreateGlobalVector(ts->dm,&ts->vec_sol);CHKERRQ(ierr); 1845 ierr = VecLoad(ts->vec_sol,viewer);CHKERRQ(ierr); 1846 ierr = DMGetDMTS(ts->dm,&sdm);CHKERRQ(ierr); 1847 ierr = DMTSLoad(sdm,viewer);CHKERRQ(ierr); 1848 PetscFunctionReturn(0); 1849 } 1850 1851 #include <petscdraw.h> 1852 #if defined(PETSC_HAVE_SAWS) 1853 #include <petscviewersaws.h> 1854 #endif 1855 #undef __FUNCT__ 1856 #define __FUNCT__ "TSView" 1857 /*@C 1858 TSView - Prints the TS data structure. 1859 1860 Collective on TS 1861 1862 Input Parameters: 1863 + ts - the TS context obtained from TSCreate() 1864 - viewer - visualization context 1865 1866 Options Database Key: 1867 . -ts_view - calls TSView() at end of TSStep() 1868 1869 Notes: 1870 The available visualization contexts include 1871 + PETSC_VIEWER_STDOUT_SELF - standard output (default) 1872 - PETSC_VIEWER_STDOUT_WORLD - synchronized standard 1873 output where only the first processor opens 1874 the file. All other processors send their 1875 data to the first processor to print. 1876 1877 The user can open an alternative visualization context with 1878 PetscViewerASCIIOpen() - output to a specified file. 1879 1880 Level: beginner 1881 1882 .keywords: TS, timestep, view 1883 1884 .seealso: PetscViewerASCIIOpen() 1885 @*/ 1886 PetscErrorCode TSView(TS ts,PetscViewer viewer) 1887 { 1888 PetscErrorCode ierr; 1889 TSType type; 1890 PetscBool iascii,isstring,isundials,isbinary,isdraw; 1891 DMTS sdm; 1892 #if defined(PETSC_HAVE_SAWS) 1893 PetscBool issaws; 1894 #endif 1895 1896 PetscFunctionBegin; 1897 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1898 if (!viewer) { 1899 ierr = PetscViewerASCIIGetStdout(PetscObjectComm((PetscObject)ts),&viewer);CHKERRQ(ierr); 1900 } 1901 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,2); 1902 PetscCheckSameComm(ts,1,viewer,2); 1903 1904 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1905 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSTRING,&isstring);CHKERRQ(ierr); 1906 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1907 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1908 #if defined(PETSC_HAVE_SAWS) 1909 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSAWS,&issaws);CHKERRQ(ierr); 1910 #endif 1911 if (iascii) { 1912 ierr = PetscObjectPrintClassNamePrefixType((PetscObject)ts,viewer);CHKERRQ(ierr); 1913 ierr = PetscViewerASCIIPrintf(viewer," maximum steps=%D\n",ts->max_steps);CHKERRQ(ierr); 1914 ierr = PetscViewerASCIIPrintf(viewer," maximum time=%g\n",(double)ts->max_time);CHKERRQ(ierr); 1915 if (ts->problem_type == TS_NONLINEAR) { 1916 ierr = PetscViewerASCIIPrintf(viewer," total number of nonlinear solver iterations=%D\n",ts->snes_its);CHKERRQ(ierr); 1917 ierr = PetscViewerASCIIPrintf(viewer," total number of nonlinear solve failures=%D\n",ts->num_snes_failures);CHKERRQ(ierr); 1918 } 1919 ierr = PetscViewerASCIIPrintf(viewer," total number of linear solver iterations=%D\n",ts->ksp_its);CHKERRQ(ierr); 1920 ierr = PetscViewerASCIIPrintf(viewer," total number of rejected steps=%D\n",ts->reject);CHKERRQ(ierr); 1921 if (ts->vrtol) { 1922 ierr = PetscViewerASCIIPrintf(viewer," using vector of relative error tolerances, ");CHKERRQ(ierr); 1923 } else { 1924 ierr = PetscViewerASCIIPrintf(viewer," using relative error tolerance of %g, ",(double)ts->rtol);CHKERRQ(ierr); 1925 } 1926 if (ts->vatol) { 1927 ierr = PetscViewerASCIIPrintf(viewer," using vector of absolute error tolerances\n");CHKERRQ(ierr); 1928 } else { 1929 ierr = PetscViewerASCIIPrintf(viewer," using absolute error tolerance of %g\n",(double)ts->atol);CHKERRQ(ierr); 1930 } 1931 ierr = DMGetDMTS(ts->dm,&sdm);CHKERRQ(ierr); 1932 ierr = DMTSView(sdm,viewer);CHKERRQ(ierr); 1933 if (ts->ops->view) { 1934 ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr); 1935 ierr = (*ts->ops->view)(ts,viewer);CHKERRQ(ierr); 1936 ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr); 1937 } 1938 } else if (isstring) { 1939 ierr = TSGetType(ts,&type);CHKERRQ(ierr); 1940 ierr = PetscViewerStringSPrintf(viewer," %-7.7s",type);CHKERRQ(ierr); 1941 } else if (isbinary) { 1942 PetscInt classid = TS_FILE_CLASSID; 1943 MPI_Comm comm; 1944 PetscMPIInt rank; 1945 char type[256]; 1946 1947 ierr = PetscObjectGetComm((PetscObject)ts,&comm);CHKERRQ(ierr); 1948 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 1949 if (!rank) { 1950 ierr = PetscViewerBinaryWrite(viewer,&classid,1,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); 1951 ierr = PetscStrncpy(type,((PetscObject)ts)->type_name,256);CHKERRQ(ierr); 1952 ierr = PetscViewerBinaryWrite(viewer,type,256,PETSC_CHAR,PETSC_FALSE);CHKERRQ(ierr); 1953 } 1954 if (ts->ops->view) { 1955 ierr = (*ts->ops->view)(ts,viewer);CHKERRQ(ierr); 1956 } 1957 ierr = DMView(ts->dm,viewer);CHKERRQ(ierr); 1958 ierr = VecView(ts->vec_sol,viewer);CHKERRQ(ierr); 1959 ierr = DMGetDMTS(ts->dm,&sdm);CHKERRQ(ierr); 1960 ierr = DMTSView(sdm,viewer);CHKERRQ(ierr); 1961 } else if (isdraw) { 1962 PetscDraw draw; 1963 char str[36]; 1964 PetscReal x,y,bottom,h; 1965 1966 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1967 ierr = PetscDrawGetCurrentPoint(draw,&x,&y);CHKERRQ(ierr); 1968 ierr = PetscStrcpy(str,"TS: ");CHKERRQ(ierr); 1969 ierr = PetscStrcat(str,((PetscObject)ts)->type_name);CHKERRQ(ierr); 1970 ierr = PetscDrawStringBoxed(draw,x,y,PETSC_DRAW_BLACK,PETSC_DRAW_BLACK,str,NULL,&h);CHKERRQ(ierr); 1971 bottom = y - h; 1972 ierr = PetscDrawPushCurrentPoint(draw,x,bottom);CHKERRQ(ierr); 1973 if (ts->ops->view) { 1974 ierr = (*ts->ops->view)(ts,viewer);CHKERRQ(ierr); 1975 } 1976 ierr = PetscDrawPopCurrentPoint(draw);CHKERRQ(ierr); 1977 #if defined(PETSC_HAVE_SAWS) 1978 } else if (issaws) { 1979 PetscMPIInt rank; 1980 const char *name; 1981 1982 ierr = PetscObjectGetName((PetscObject)ts,&name);CHKERRQ(ierr); 1983 ierr = MPI_Comm_rank(PETSC_COMM_WORLD,&rank);CHKERRQ(ierr); 1984 if (!((PetscObject)ts)->amsmem && !rank) { 1985 char dir[1024]; 1986 1987 ierr = PetscObjectViewSAWs((PetscObject)ts,viewer);CHKERRQ(ierr); 1988 ierr = PetscSNPrintf(dir,1024,"/PETSc/Objects/%s/time_step",name);CHKERRQ(ierr); 1989 PetscStackCallSAWs(SAWs_Register,(dir,&ts->steps,1,SAWs_READ,SAWs_INT)); 1990 ierr = PetscSNPrintf(dir,1024,"/PETSc/Objects/%s/time",name);CHKERRQ(ierr); 1991 PetscStackCallSAWs(SAWs_Register,(dir,&ts->ptime,1,SAWs_READ,SAWs_DOUBLE)); 1992 } 1993 if (ts->ops->view) { 1994 ierr = (*ts->ops->view)(ts,viewer);CHKERRQ(ierr); 1995 } 1996 #endif 1997 } 1998 1999 ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr); 2000 ierr = PetscObjectTypeCompare((PetscObject)ts,TSSUNDIALS,&isundials);CHKERRQ(ierr); 2001 ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr); 2002 PetscFunctionReturn(0); 2003 } 2004 2005 2006 #undef __FUNCT__ 2007 #define __FUNCT__ "TSSetApplicationContext" 2008 /*@ 2009 TSSetApplicationContext - Sets an optional user-defined context for 2010 the timesteppers. 2011 2012 Logically Collective on TS 2013 2014 Input Parameters: 2015 + ts - the TS context obtained from TSCreate() 2016 - usrP - optional user context 2017 2018 Fortran Notes: To use this from Fortran you must write a Fortran interface definition for this 2019 function that tells Fortran the Fortran derived data type that you are passing in as the ctx argument. 2020 2021 Level: intermediate 2022 2023 .keywords: TS, timestep, set, application, context 2024 2025 .seealso: TSGetApplicationContext() 2026 @*/ 2027 PetscErrorCode TSSetApplicationContext(TS ts,void *usrP) 2028 { 2029 PetscFunctionBegin; 2030 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2031 ts->user = usrP; 2032 PetscFunctionReturn(0); 2033 } 2034 2035 #undef __FUNCT__ 2036 #define __FUNCT__ "TSGetApplicationContext" 2037 /*@ 2038 TSGetApplicationContext - Gets the user-defined context for the 2039 timestepper. 2040 2041 Not Collective 2042 2043 Input Parameter: 2044 . ts - the TS context obtained from TSCreate() 2045 2046 Output Parameter: 2047 . usrP - user context 2048 2049 Fortran Notes: To use this from Fortran you must write a Fortran interface definition for this 2050 function that tells Fortran the Fortran derived data type that you are passing in as the ctx argument. 2051 2052 Level: intermediate 2053 2054 .keywords: TS, timestep, get, application, context 2055 2056 .seealso: TSSetApplicationContext() 2057 @*/ 2058 PetscErrorCode TSGetApplicationContext(TS ts,void *usrP) 2059 { 2060 PetscFunctionBegin; 2061 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2062 *(void**)usrP = ts->user; 2063 PetscFunctionReturn(0); 2064 } 2065 2066 #undef __FUNCT__ 2067 #define __FUNCT__ "TSGetTimeStepNumber" 2068 /*@ 2069 TSGetTimeStepNumber - Gets the number of time steps completed. 2070 2071 Not Collective 2072 2073 Input Parameter: 2074 . ts - the TS context obtained from TSCreate() 2075 2076 Output Parameter: 2077 . iter - number of steps completed so far 2078 2079 Level: intermediate 2080 2081 .keywords: TS, timestep, get, iteration, number 2082 .seealso: TSGetTime(), TSGetTimeStep(), TSSetPreStep(), TSSetPreStage(), TSSetPostStage(), TSSetPostStep() 2083 @*/ 2084 PetscErrorCode TSGetTimeStepNumber(TS ts,PetscInt *iter) 2085 { 2086 PetscFunctionBegin; 2087 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2088 PetscValidIntPointer(iter,2); 2089 *iter = ts->steps; 2090 PetscFunctionReturn(0); 2091 } 2092 2093 #undef __FUNCT__ 2094 #define __FUNCT__ "TSSetInitialTimeStep" 2095 /*@ 2096 TSSetInitialTimeStep - Sets the initial timestep to be used, 2097 as well as the initial time. 2098 2099 Logically Collective on TS 2100 2101 Input Parameters: 2102 + ts - the TS context obtained from TSCreate() 2103 . initial_time - the initial time 2104 - time_step - the size of the timestep 2105 2106 Level: intermediate 2107 2108 .seealso: TSSetTimeStep(), TSGetTimeStep() 2109 2110 .keywords: TS, set, initial, timestep 2111 @*/ 2112 PetscErrorCode TSSetInitialTimeStep(TS ts,PetscReal initial_time,PetscReal time_step) 2113 { 2114 PetscErrorCode ierr; 2115 2116 PetscFunctionBegin; 2117 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2118 ierr = TSSetTimeStep(ts,time_step);CHKERRQ(ierr); 2119 ierr = TSSetTime(ts,initial_time);CHKERRQ(ierr); 2120 PetscFunctionReturn(0); 2121 } 2122 2123 #undef __FUNCT__ 2124 #define __FUNCT__ "TSSetTimeStep" 2125 /*@ 2126 TSSetTimeStep - Allows one to reset the timestep at any time, 2127 useful for simple pseudo-timestepping codes. 2128 2129 Logically Collective on TS 2130 2131 Input Parameters: 2132 + ts - the TS context obtained from TSCreate() 2133 - time_step - the size of the timestep 2134 2135 Level: intermediate 2136 2137 .seealso: TSSetInitialTimeStep(), TSGetTimeStep() 2138 2139 .keywords: TS, set, timestep 2140 @*/ 2141 PetscErrorCode TSSetTimeStep(TS ts,PetscReal time_step) 2142 { 2143 PetscFunctionBegin; 2144 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2145 PetscValidLogicalCollectiveReal(ts,time_step,2); 2146 ts->time_step = time_step; 2147 PetscFunctionReturn(0); 2148 } 2149 2150 #undef __FUNCT__ 2151 #define __FUNCT__ "TSSetExactFinalTime" 2152 /*@ 2153 TSSetExactFinalTime - Determines whether to adapt the final time step to 2154 match the exact final time, interpolate solution to the exact final time, 2155 or just return at the final time TS computed. 2156 2157 Logically Collective on TS 2158 2159 Input Parameter: 2160 + ts - the time-step context 2161 - eftopt - exact final time option 2162 2163 $ TS_EXACTFINALTIME_STEPOVER - Don't do anything if final time is exceeded 2164 $ TS_EXACTFINALTIME_INTERPOLATE - Interpolate back to final time 2165 $ TS_EXACTFINALTIME_MATCHSTEP - Adapt final time step to match the final time 2166 2167 Options Database: 2168 . -ts_exact_final_time <stepover,interpolate,matchstep> - select the final step at runtime 2169 2170 Warning: If you use the option TS_EXACTFINALTIME_STEPOVER the solution may be at a very different time 2171 then the final time you selected. 2172 2173 Level: beginner 2174 2175 .seealso: TSExactFinalTimeOption 2176 @*/ 2177 PetscErrorCode TSSetExactFinalTime(TS ts,TSExactFinalTimeOption eftopt) 2178 { 2179 PetscFunctionBegin; 2180 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2181 PetscValidLogicalCollectiveEnum(ts,eftopt,2); 2182 ts->exact_final_time = eftopt; 2183 PetscFunctionReturn(0); 2184 } 2185 2186 #undef __FUNCT__ 2187 #define __FUNCT__ "TSGetTimeStep" 2188 /*@ 2189 TSGetTimeStep - Gets the current timestep size. 2190 2191 Not Collective 2192 2193 Input Parameter: 2194 . ts - the TS context obtained from TSCreate() 2195 2196 Output Parameter: 2197 . dt - the current timestep size 2198 2199 Level: intermediate 2200 2201 .seealso: TSSetInitialTimeStep(), TSGetTimeStep() 2202 2203 .keywords: TS, get, timestep 2204 @*/ 2205 PetscErrorCode TSGetTimeStep(TS ts,PetscReal *dt) 2206 { 2207 PetscFunctionBegin; 2208 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2209 PetscValidRealPointer(dt,2); 2210 *dt = ts->time_step; 2211 PetscFunctionReturn(0); 2212 } 2213 2214 #undef __FUNCT__ 2215 #define __FUNCT__ "TSGetSolution" 2216 /*@ 2217 TSGetSolution - Returns the solution at the present timestep. It 2218 is valid to call this routine inside the function that you are evaluating 2219 in order to move to the new timestep. This vector not changed until 2220 the solution at the next timestep has been calculated. 2221 2222 Not Collective, but Vec returned is parallel if TS is parallel 2223 2224 Input Parameter: 2225 . ts - the TS context obtained from TSCreate() 2226 2227 Output Parameter: 2228 . v - the vector containing the solution 2229 2230 Note: If you used TSSetExactFinalTime(ts,TS_EXACTFINALTIME_MATCHSTEP); this does not return the solution at the requested 2231 final time. It returns the solution at the next timestep. 2232 2233 Level: intermediate 2234 2235 .seealso: TSGetTimeStep(), TSGetTime(), TSGetSolveTime(), TSGetSolutionComponents() 2236 2237 .keywords: TS, timestep, get, solution 2238 @*/ 2239 PetscErrorCode TSGetSolution(TS ts,Vec *v) 2240 { 2241 PetscFunctionBegin; 2242 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2243 PetscValidPointer(v,2); 2244 *v = ts->vec_sol; 2245 PetscFunctionReturn(0); 2246 } 2247 2248 #undef __FUNCT__ 2249 #define __FUNCT__ "TSGetSolutionComponents" 2250 /*@ 2251 TSGetSolutionComponents - Returns any solution components at the present 2252 timestep, if available for the time integration method being used. 2253 Solution components are quantities that share the same size and 2254 structure as the solution vector. 2255 2256 Not Collective, but Vec returned is parallel if TS is parallel 2257 2258 Parameters : 2259 . ts - the TS context obtained from TSCreate() (input parameter). 2260 . n - If v is PETSC_NULL, then the number of solution components is 2261 returned through n, else the n-th solution component is 2262 returned in v. 2263 . v - the vector containing the n-th solution component 2264 (may be PETSC_NULL to use this function to find out 2265 the number of solutions components). 2266 2267 Level: advanced 2268 2269 .seealso: TSGetSolution() 2270 2271 .keywords: TS, timestep, get, solution 2272 @*/ 2273 PetscErrorCode TSGetSolutionComponents(TS ts,PetscInt *n,Vec *v) 2274 { 2275 PetscErrorCode ierr; 2276 2277 PetscFunctionBegin; 2278 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2279 if (!ts->ops->getsolutioncomponents) *n = 0; 2280 else { 2281 ierr = (*ts->ops->getsolutioncomponents)(ts,n,v);CHKERRQ(ierr); 2282 } 2283 PetscFunctionReturn(0); 2284 } 2285 2286 #undef __FUNCT__ 2287 #define __FUNCT__ "TSGetAuxSolution" 2288 /*@ 2289 TSGetAuxSolution - Returns an auxiliary solution at the present 2290 timestep, if available for the time integration method being used. 2291 2292 Not Collective, but Vec returned is parallel if TS is parallel 2293 2294 Parameters : 2295 . ts - the TS context obtained from TSCreate() (input parameter). 2296 . v - the vector containing the auxiliary solution 2297 2298 Level: intermediate 2299 2300 .seealso: TSGetSolution() 2301 2302 .keywords: TS, timestep, get, solution 2303 @*/ 2304 PetscErrorCode TSGetAuxSolution(TS ts,Vec *v) 2305 { 2306 PetscErrorCode ierr; 2307 2308 PetscFunctionBegin; 2309 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2310 if (ts->ops->getauxsolution) { 2311 ierr = (*ts->ops->getauxsolution)(ts,v);CHKERRQ(ierr); 2312 } else { 2313 ierr = VecZeroEntries(*v); CHKERRQ(ierr); 2314 } 2315 PetscFunctionReturn(0); 2316 } 2317 2318 #undef __FUNCT__ 2319 #define __FUNCT__ "TSGetTimeError" 2320 /*@ 2321 TSGetTimeError - Returns the estimated error vector, if the chosen 2322 TSType has an error estimation functionality. 2323 2324 Not Collective, but Vec returned is parallel if TS is parallel 2325 2326 Note: MUST call after TSSetUp() 2327 2328 Parameters : 2329 . ts - the TS context obtained from TSCreate() (input parameter). 2330 . n - current estimate (n=0) or previous one (n=-1) 2331 . v - the vector containing the error (same size as the solution). 2332 2333 Level: intermediate 2334 2335 .seealso: TSGetSolution(), TSSetTimeError() 2336 2337 .keywords: TS, timestep, get, error 2338 @*/ 2339 PetscErrorCode TSGetTimeError(TS ts,PetscInt n,Vec *v) 2340 { 2341 PetscErrorCode ierr; 2342 2343 PetscFunctionBegin; 2344 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2345 if (ts->ops->gettimeerror) { 2346 ierr = (*ts->ops->gettimeerror)(ts,n,v);CHKERRQ(ierr); 2347 } else { 2348 ierr = VecZeroEntries(*v);CHKERRQ(ierr); 2349 } 2350 PetscFunctionReturn(0); 2351 } 2352 2353 #undef __FUNCT__ 2354 #define __FUNCT__ "TSSetTimeError" 2355 /*@ 2356 TSSetTimeError - Sets the estimated error vector, if the chosen 2357 TSType has an error estimation functionality. This can be used 2358 to restart such a time integrator with a given error vector. 2359 2360 Not Collective, but Vec returned is parallel if TS is parallel 2361 2362 Parameters : 2363 . ts - the TS context obtained from TSCreate() (input parameter). 2364 . v - the vector containing the error (same size as the solution). 2365 2366 Level: intermediate 2367 2368 .seealso: TSSetSolution(), TSGetTimeError) 2369 2370 .keywords: TS, timestep, get, error 2371 @*/ 2372 PetscErrorCode TSSetTimeError(TS ts,Vec v) 2373 { 2374 PetscErrorCode ierr; 2375 2376 PetscFunctionBegin; 2377 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2378 if (!ts->setupcalled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call TSSetUp() first"); 2379 if (ts->ops->settimeerror) { 2380 ierr = (*ts->ops->settimeerror)(ts,v);CHKERRQ(ierr); 2381 } 2382 PetscFunctionReturn(0); 2383 } 2384 2385 #undef __FUNCT__ 2386 #define __FUNCT__ "TSGetCostGradients" 2387 /*@ 2388 TSGetCostGradients - Returns the gradients from the TSAdjointSolve() 2389 2390 Not Collective, but Vec returned is parallel if TS is parallel 2391 2392 Input Parameter: 2393 . ts - the TS context obtained from TSCreate() 2394 2395 Output Parameter: 2396 + lambda - vectors containing the gradients of the cost functions with respect to the ODE/DAE solution variables 2397 - mu - vectors containing the gradients of the cost functions with respect to the problem parameters 2398 2399 Level: intermediate 2400 2401 .seealso: TSGetTimeStep() 2402 2403 .keywords: TS, timestep, get, sensitivity 2404 @*/ 2405 PetscErrorCode TSGetCostGradients(TS ts,PetscInt *numcost,Vec **lambda,Vec **mu) 2406 { 2407 PetscFunctionBegin; 2408 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2409 if (numcost) *numcost = ts->numcost; 2410 if (lambda) *lambda = ts->vecs_sensi; 2411 if (mu) *mu = ts->vecs_sensip; 2412 PetscFunctionReturn(0); 2413 } 2414 2415 /* ----- Routines to initialize and destroy a timestepper ---- */ 2416 #undef __FUNCT__ 2417 #define __FUNCT__ "TSSetProblemType" 2418 /*@ 2419 TSSetProblemType - Sets the type of problem to be solved. 2420 2421 Not collective 2422 2423 Input Parameters: 2424 + ts - The TS 2425 - type - One of TS_LINEAR, TS_NONLINEAR where these types refer to problems of the forms 2426 .vb 2427 U_t - A U = 0 (linear) 2428 U_t - A(t) U = 0 (linear) 2429 F(t,U,U_t) = 0 (nonlinear) 2430 .ve 2431 2432 Level: beginner 2433 2434 .keywords: TS, problem type 2435 .seealso: TSSetUp(), TSProblemType, TS 2436 @*/ 2437 PetscErrorCode TSSetProblemType(TS ts, TSProblemType type) 2438 { 2439 PetscErrorCode ierr; 2440 2441 PetscFunctionBegin; 2442 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 2443 ts->problem_type = type; 2444 if (type == TS_LINEAR) { 2445 SNES snes; 2446 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 2447 ierr = SNESSetType(snes,SNESKSPONLY);CHKERRQ(ierr); 2448 } 2449 PetscFunctionReturn(0); 2450 } 2451 2452 #undef __FUNCT__ 2453 #define __FUNCT__ "TSGetProblemType" 2454 /*@C 2455 TSGetProblemType - Gets the type of problem to be solved. 2456 2457 Not collective 2458 2459 Input Parameter: 2460 . ts - The TS 2461 2462 Output Parameter: 2463 . type - One of TS_LINEAR, TS_NONLINEAR where these types refer to problems of the forms 2464 .vb 2465 M U_t = A U 2466 M(t) U_t = A(t) U 2467 F(t,U,U_t) 2468 .ve 2469 2470 Level: beginner 2471 2472 .keywords: TS, problem type 2473 .seealso: TSSetUp(), TSProblemType, TS 2474 @*/ 2475 PetscErrorCode TSGetProblemType(TS ts, TSProblemType *type) 2476 { 2477 PetscFunctionBegin; 2478 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 2479 PetscValidIntPointer(type,2); 2480 *type = ts->problem_type; 2481 PetscFunctionReturn(0); 2482 } 2483 2484 #undef __FUNCT__ 2485 #define __FUNCT__ "TSSetUp" 2486 /*@ 2487 TSSetUp - Sets up the internal data structures for the later use 2488 of a timestepper. 2489 2490 Collective on TS 2491 2492 Input Parameter: 2493 . ts - the TS context obtained from TSCreate() 2494 2495 Notes: 2496 For basic use of the TS solvers the user need not explicitly call 2497 TSSetUp(), since these actions will automatically occur during 2498 the call to TSStep(). However, if one wishes to control this 2499 phase separately, TSSetUp() should be called after TSCreate() 2500 and optional routines of the form TSSetXXX(), but before TSStep(). 2501 2502 Level: advanced 2503 2504 .keywords: TS, timestep, setup 2505 2506 .seealso: TSCreate(), TSStep(), TSDestroy() 2507 @*/ 2508 PetscErrorCode TSSetUp(TS ts) 2509 { 2510 PetscErrorCode ierr; 2511 DM dm; 2512 PetscErrorCode (*func)(SNES,Vec,Vec,void*); 2513 PetscErrorCode (*jac)(SNES,Vec,Mat,Mat,void*); 2514 TSIFunction ifun; 2515 TSIJacobian ijac; 2516 TSI2Jacobian i2jac; 2517 TSRHSJacobian rhsjac; 2518 2519 PetscFunctionBegin; 2520 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2521 if (ts->setupcalled) PetscFunctionReturn(0); 2522 2523 ts->total_steps = 0; 2524 if (!((PetscObject)ts)->type_name) { 2525 ierr = TSGetIFunction(ts,NULL,&ifun,NULL);CHKERRQ(ierr); 2526 ierr = TSSetType(ts,ifun ? TSBEULER : TSEULER);CHKERRQ(ierr); 2527 } 2528 2529 if (!ts->vec_sol) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call TSSetSolution() first"); 2530 2531 if (ts->rhsjacobian.reuse) { 2532 Mat Amat,Pmat; 2533 SNES snes; 2534 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 2535 ierr = SNESGetJacobian(snes,&Amat,&Pmat,NULL,NULL);CHKERRQ(ierr); 2536 /* Matching matrices implies that an IJacobian is NOT set, because if it had been set, the IJacobian's matrix would 2537 * have displaced the RHS matrix */ 2538 if (Amat == ts->Arhs) { 2539 ierr = MatDuplicate(ts->Arhs,MAT_DO_NOT_COPY_VALUES,&Amat);CHKERRQ(ierr); 2540 ierr = SNESSetJacobian(snes,Amat,NULL,NULL,NULL);CHKERRQ(ierr); 2541 ierr = MatDestroy(&Amat);CHKERRQ(ierr); 2542 } 2543 if (Pmat == ts->Brhs) { 2544 ierr = MatDuplicate(ts->Brhs,MAT_DO_NOT_COPY_VALUES,&Pmat);CHKERRQ(ierr); 2545 ierr = SNESSetJacobian(snes,NULL,Pmat,NULL,NULL);CHKERRQ(ierr); 2546 ierr = MatDestroy(&Pmat);CHKERRQ(ierr); 2547 } 2548 } 2549 if (ts->ops->setup) { 2550 ierr = (*ts->ops->setup)(ts);CHKERRQ(ierr); 2551 } 2552 2553 /* In the case where we've set a DMTSFunction or what have you, we need the default SNESFunction 2554 to be set right but can't do it elsewhere due to the overreliance on ctx=ts. 2555 */ 2556 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 2557 ierr = DMSNESGetFunction(dm,&func,NULL);CHKERRQ(ierr); 2558 if (!func) { 2559 ierr = DMSNESSetFunction(dm,SNESTSFormFunction,ts);CHKERRQ(ierr); 2560 } 2561 /* If the SNES doesn't have a jacobian set and the TS has an ijacobian or rhsjacobian set, set the SNES to use it. 2562 Otherwise, the SNES will use coloring internally to form the Jacobian. 2563 */ 2564 ierr = DMSNESGetJacobian(dm,&jac,NULL);CHKERRQ(ierr); 2565 ierr = DMTSGetIJacobian(dm,&ijac,NULL);CHKERRQ(ierr); 2566 ierr = DMTSGetI2Jacobian(dm,&i2jac,NULL);CHKERRQ(ierr); 2567 ierr = DMTSGetRHSJacobian(dm,&rhsjac,NULL);CHKERRQ(ierr); 2568 if (!jac && (ijac || i2jac || rhsjac)) { 2569 ierr = DMSNESSetJacobian(dm,SNESTSFormJacobian,ts);CHKERRQ(ierr); 2570 } 2571 2572 /* if time integration scheme has a starting method, call it */ 2573 if (ts->ops->startingmethod) { 2574 ierr = (*ts->ops->startingmethod)(ts);CHKERRQ(ierr); 2575 } 2576 2577 ts->setupcalled = PETSC_TRUE; 2578 PetscFunctionReturn(0); 2579 } 2580 2581 #undef __FUNCT__ 2582 #define __FUNCT__ "TSAdjointSetUp" 2583 /*@ 2584 TSAdjointSetUp - Sets up the internal data structures for the later use 2585 of an adjoint solver 2586 2587 Collective on TS 2588 2589 Input Parameter: 2590 . ts - the TS context obtained from TSCreate() 2591 2592 Level: advanced 2593 2594 .keywords: TS, timestep, setup 2595 2596 .seealso: TSCreate(), TSAdjointStep(), TSSetCostGradients() 2597 @*/ 2598 PetscErrorCode TSAdjointSetUp(TS ts) 2599 { 2600 PetscErrorCode ierr; 2601 2602 PetscFunctionBegin; 2603 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2604 if (ts->adjointsetupcalled) PetscFunctionReturn(0); 2605 if (!ts->vecs_sensi) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call TSSetCostGradients() first"); 2606 2607 if (ts->vec_costintegral) { /* if there is integral in the cost function*/ 2608 ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&ts->vecs_drdy);CHKERRQ(ierr); 2609 if (ts->vecs_sensip){ 2610 ierr = VecDuplicateVecs(ts->vecs_sensip[0],ts->numcost,&ts->vecs_drdp);CHKERRQ(ierr); 2611 } 2612 } 2613 2614 if (ts->ops->adjointsetup) { 2615 ierr = (*ts->ops->adjointsetup)(ts);CHKERRQ(ierr); 2616 } 2617 ts->adjointsetupcalled = PETSC_TRUE; 2618 PetscFunctionReturn(0); 2619 } 2620 2621 #undef __FUNCT__ 2622 #define __FUNCT__ "TSReset" 2623 /*@ 2624 TSReset - Resets a TS context and removes any allocated Vecs and Mats. 2625 2626 Collective on TS 2627 2628 Input Parameter: 2629 . ts - the TS context obtained from TSCreate() 2630 2631 Level: beginner 2632 2633 .keywords: TS, timestep, reset 2634 2635 .seealso: TSCreate(), TSSetup(), TSDestroy() 2636 @*/ 2637 PetscErrorCode TSReset(TS ts) 2638 { 2639 PetscErrorCode ierr; 2640 2641 PetscFunctionBegin; 2642 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2643 2644 if (ts->ops->reset) { 2645 ierr = (*ts->ops->reset)(ts);CHKERRQ(ierr); 2646 } 2647 if (ts->snes) {ierr = SNESReset(ts->snes);CHKERRQ(ierr);} 2648 if (ts->adapt) {ierr = TSAdaptReset(ts->adapt);CHKERRQ(ierr);} 2649 2650 ierr = MatDestroy(&ts->Arhs);CHKERRQ(ierr); 2651 ierr = MatDestroy(&ts->Brhs);CHKERRQ(ierr); 2652 ierr = VecDestroy(&ts->Frhs);CHKERRQ(ierr); 2653 ierr = VecDestroy(&ts->vec_sol);CHKERRQ(ierr); 2654 ierr = VecDestroy(&ts->vec_dot);CHKERRQ(ierr); 2655 ierr = VecDestroy(&ts->vatol);CHKERRQ(ierr); 2656 ierr = VecDestroy(&ts->vrtol);CHKERRQ(ierr); 2657 ierr = VecDestroyVecs(ts->nwork,&ts->work);CHKERRQ(ierr); 2658 2659 if (ts->vec_costintegral) { 2660 ierr = VecDestroyVecs(ts->numcost,&ts->vecs_drdy);CHKERRQ(ierr); 2661 if (ts->vecs_drdp){ 2662 ierr = VecDestroyVecs(ts->numcost,&ts->vecs_drdp);CHKERRQ(ierr); 2663 } 2664 } 2665 ts->vecs_sensi = NULL; 2666 ts->vecs_sensip = NULL; 2667 ierr = MatDestroy(&ts->Jacp);CHKERRQ(ierr); 2668 ierr = VecDestroy(&ts->vec_costintegral);CHKERRQ(ierr); 2669 ierr = VecDestroy(&ts->vec_costintegrand);CHKERRQ(ierr); 2670 ts->setupcalled = PETSC_FALSE; 2671 PetscFunctionReturn(0); 2672 } 2673 2674 #undef __FUNCT__ 2675 #define __FUNCT__ "TSDestroy" 2676 /*@ 2677 TSDestroy - Destroys the timestepper context that was created 2678 with TSCreate(). 2679 2680 Collective on TS 2681 2682 Input Parameter: 2683 . ts - the TS context obtained from TSCreate() 2684 2685 Level: beginner 2686 2687 .keywords: TS, timestepper, destroy 2688 2689 .seealso: TSCreate(), TSSetUp(), TSSolve() 2690 @*/ 2691 PetscErrorCode TSDestroy(TS *ts) 2692 { 2693 PetscErrorCode ierr; 2694 2695 PetscFunctionBegin; 2696 if (!*ts) PetscFunctionReturn(0); 2697 PetscValidHeaderSpecific((*ts),TS_CLASSID,1); 2698 if (--((PetscObject)(*ts))->refct > 0) {*ts = 0; PetscFunctionReturn(0);} 2699 2700 ierr = TSReset((*ts));CHKERRQ(ierr); 2701 2702 /* if memory was published with SAWs then destroy it */ 2703 ierr = PetscObjectSAWsViewOff((PetscObject)*ts);CHKERRQ(ierr); 2704 if ((*ts)->ops->destroy) {ierr = (*(*ts)->ops->destroy)((*ts));CHKERRQ(ierr);} 2705 2706 ierr = TSTrajectoryDestroy(&(*ts)->trajectory);CHKERRQ(ierr); 2707 2708 ierr = TSAdaptDestroy(&(*ts)->adapt);CHKERRQ(ierr); 2709 ierr = TSEventDestroy(&(*ts)->event);CHKERRQ(ierr); 2710 2711 ierr = SNESDestroy(&(*ts)->snes);CHKERRQ(ierr); 2712 ierr = DMDestroy(&(*ts)->dm);CHKERRQ(ierr); 2713 ierr = TSMonitorCancel((*ts));CHKERRQ(ierr); 2714 ierr = TSAdjointMonitorCancel((*ts));CHKERRQ(ierr); 2715 2716 ierr = PetscHeaderDestroy(ts);CHKERRQ(ierr); 2717 PetscFunctionReturn(0); 2718 } 2719 2720 #undef __FUNCT__ 2721 #define __FUNCT__ "TSGetSNES" 2722 /*@ 2723 TSGetSNES - Returns the SNES (nonlinear solver) associated with 2724 a TS (timestepper) context. Valid only for nonlinear problems. 2725 2726 Not Collective, but SNES is parallel if TS is parallel 2727 2728 Input Parameter: 2729 . ts - the TS context obtained from TSCreate() 2730 2731 Output Parameter: 2732 . snes - the nonlinear solver context 2733 2734 Notes: 2735 The user can then directly manipulate the SNES context to set various 2736 options, etc. Likewise, the user can then extract and manipulate the 2737 KSP, KSP, and PC contexts as well. 2738 2739 TSGetSNES() does not work for integrators that do not use SNES; in 2740 this case TSGetSNES() returns NULL in snes. 2741 2742 Level: beginner 2743 2744 .keywords: timestep, get, SNES 2745 @*/ 2746 PetscErrorCode TSGetSNES(TS ts,SNES *snes) 2747 { 2748 PetscErrorCode ierr; 2749 2750 PetscFunctionBegin; 2751 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2752 PetscValidPointer(snes,2); 2753 if (!ts->snes) { 2754 ierr = SNESCreate(PetscObjectComm((PetscObject)ts),&ts->snes);CHKERRQ(ierr); 2755 ierr = SNESSetFunction(ts->snes,NULL,SNESTSFormFunction,ts);CHKERRQ(ierr); 2756 ierr = PetscLogObjectParent((PetscObject)ts,(PetscObject)ts->snes);CHKERRQ(ierr); 2757 ierr = PetscObjectIncrementTabLevel((PetscObject)ts->snes,(PetscObject)ts,1);CHKERRQ(ierr); 2758 if (ts->dm) {ierr = SNESSetDM(ts->snes,ts->dm);CHKERRQ(ierr);} 2759 if (ts->problem_type == TS_LINEAR) { 2760 ierr = SNESSetType(ts->snes,SNESKSPONLY);CHKERRQ(ierr); 2761 } 2762 } 2763 *snes = ts->snes; 2764 PetscFunctionReturn(0); 2765 } 2766 2767 #undef __FUNCT__ 2768 #define __FUNCT__ "TSSetSNES" 2769 /*@ 2770 TSSetSNES - Set the SNES (nonlinear solver) to be used by the timestepping context 2771 2772 Collective 2773 2774 Input Parameter: 2775 + ts - the TS context obtained from TSCreate() 2776 - snes - the nonlinear solver context 2777 2778 Notes: 2779 Most users should have the TS created by calling TSGetSNES() 2780 2781 Level: developer 2782 2783 .keywords: timestep, set, SNES 2784 @*/ 2785 PetscErrorCode TSSetSNES(TS ts,SNES snes) 2786 { 2787 PetscErrorCode ierr; 2788 PetscErrorCode (*func)(SNES,Vec,Mat,Mat,void*); 2789 2790 PetscFunctionBegin; 2791 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2792 PetscValidHeaderSpecific(snes,SNES_CLASSID,2); 2793 ierr = PetscObjectReference((PetscObject)snes);CHKERRQ(ierr); 2794 ierr = SNESDestroy(&ts->snes);CHKERRQ(ierr); 2795 2796 ts->snes = snes; 2797 2798 ierr = SNESSetFunction(ts->snes,NULL,SNESTSFormFunction,ts);CHKERRQ(ierr); 2799 ierr = SNESGetJacobian(ts->snes,NULL,NULL,&func,NULL);CHKERRQ(ierr); 2800 if (func == SNESTSFormJacobian) { 2801 ierr = SNESSetJacobian(ts->snes,NULL,NULL,SNESTSFormJacobian,ts);CHKERRQ(ierr); 2802 } 2803 PetscFunctionReturn(0); 2804 } 2805 2806 #undef __FUNCT__ 2807 #define __FUNCT__ "TSGetKSP" 2808 /*@ 2809 TSGetKSP - Returns the KSP (linear solver) associated with 2810 a TS (timestepper) context. 2811 2812 Not Collective, but KSP is parallel if TS is parallel 2813 2814 Input Parameter: 2815 . ts - the TS context obtained from TSCreate() 2816 2817 Output Parameter: 2818 . ksp - the nonlinear solver context 2819 2820 Notes: 2821 The user can then directly manipulate the KSP context to set various 2822 options, etc. Likewise, the user can then extract and manipulate the 2823 KSP and PC contexts as well. 2824 2825 TSGetKSP() does not work for integrators that do not use KSP; 2826 in this case TSGetKSP() returns NULL in ksp. 2827 2828 Level: beginner 2829 2830 .keywords: timestep, get, KSP 2831 @*/ 2832 PetscErrorCode TSGetKSP(TS ts,KSP *ksp) 2833 { 2834 PetscErrorCode ierr; 2835 SNES snes; 2836 2837 PetscFunctionBegin; 2838 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2839 PetscValidPointer(ksp,2); 2840 if (!((PetscObject)ts)->type_name) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_NULL,"KSP is not created yet. Call TSSetType() first"); 2841 if (ts->problem_type != TS_LINEAR) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Linear only; use TSGetSNES()"); 2842 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 2843 ierr = SNESGetKSP(snes,ksp);CHKERRQ(ierr); 2844 PetscFunctionReturn(0); 2845 } 2846 2847 /* ----------- Routines to set solver parameters ---------- */ 2848 2849 #undef __FUNCT__ 2850 #define __FUNCT__ "TSGetDuration" 2851 /*@ 2852 TSGetDuration - Gets the maximum number of timesteps to use and 2853 maximum time for iteration. 2854 2855 Not Collective 2856 2857 Input Parameters: 2858 + ts - the TS context obtained from TSCreate() 2859 . maxsteps - maximum number of iterations to use, or NULL 2860 - maxtime - final time to iterate to, or NULL 2861 2862 Level: intermediate 2863 2864 .keywords: TS, timestep, get, maximum, iterations, time 2865 @*/ 2866 PetscErrorCode TSGetDuration(TS ts, PetscInt *maxsteps, PetscReal *maxtime) 2867 { 2868 PetscFunctionBegin; 2869 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 2870 if (maxsteps) { 2871 PetscValidIntPointer(maxsteps,2); 2872 *maxsteps = ts->max_steps; 2873 } 2874 if (maxtime) { 2875 PetscValidScalarPointer(maxtime,3); 2876 *maxtime = ts->max_time; 2877 } 2878 PetscFunctionReturn(0); 2879 } 2880 2881 #undef __FUNCT__ 2882 #define __FUNCT__ "TSSetDuration" 2883 /*@ 2884 TSSetDuration - Sets the maximum number of timesteps to use and 2885 maximum time for iteration. 2886 2887 Logically Collective on TS 2888 2889 Input Parameters: 2890 + ts - the TS context obtained from TSCreate() 2891 . maxsteps - maximum number of iterations to use 2892 - maxtime - final time to iterate to 2893 2894 Options Database Keys: 2895 . -ts_max_steps <maxsteps> - Sets maxsteps 2896 . -ts_final_time <maxtime> - Sets maxtime 2897 2898 Notes: 2899 The default maximum number of iterations is 5000. Default time is 5.0 2900 2901 Level: intermediate 2902 2903 .keywords: TS, timestep, set, maximum, iterations 2904 2905 .seealso: TSSetExactFinalTime() 2906 @*/ 2907 PetscErrorCode TSSetDuration(TS ts,PetscInt maxsteps,PetscReal maxtime) 2908 { 2909 PetscFunctionBegin; 2910 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2911 PetscValidLogicalCollectiveInt(ts,maxsteps,2); 2912 PetscValidLogicalCollectiveReal(ts,maxtime,2); 2913 if (maxsteps >= 0) ts->max_steps = maxsteps; 2914 if (maxtime != PETSC_DEFAULT) ts->max_time = maxtime; 2915 PetscFunctionReturn(0); 2916 } 2917 2918 #undef __FUNCT__ 2919 #define __FUNCT__ "TSSetSolution" 2920 /*@ 2921 TSSetSolution - Sets the initial solution vector 2922 for use by the TS routines. 2923 2924 Logically Collective on TS and Vec 2925 2926 Input Parameters: 2927 + ts - the TS context obtained from TSCreate() 2928 - u - the solution vector 2929 2930 Level: beginner 2931 2932 .keywords: TS, timestep, set, solution, initial conditions 2933 @*/ 2934 PetscErrorCode TSSetSolution(TS ts,Vec u) 2935 { 2936 PetscErrorCode ierr; 2937 DM dm; 2938 2939 PetscFunctionBegin; 2940 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2941 PetscValidHeaderSpecific(u,VEC_CLASSID,2); 2942 ierr = PetscObjectReference((PetscObject)u);CHKERRQ(ierr); 2943 ierr = VecDestroy(&ts->vec_sol);CHKERRQ(ierr); 2944 ts->vec_sol = u; 2945 2946 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 2947 ierr = DMShellSetGlobalVector(dm,u);CHKERRQ(ierr); 2948 PetscFunctionReturn(0); 2949 } 2950 2951 #undef __FUNCT__ 2952 #define __FUNCT__ "TSAdjointSetSteps" 2953 /*@ 2954 TSAdjointSetSteps - Sets the number of steps the adjoint solver should take backward in time 2955 2956 Logically Collective on TS 2957 2958 Input Parameters: 2959 + ts - the TS context obtained from TSCreate() 2960 . steps - number of steps to use 2961 2962 Level: intermediate 2963 2964 Notes: Normally one does not call this and TSAdjointSolve() integrates back to the original timestep. One can call this 2965 so as to integrate back to less than the original timestep 2966 2967 .keywords: TS, timestep, set, maximum, iterations 2968 2969 .seealso: TSSetExactFinalTime() 2970 @*/ 2971 PetscErrorCode TSAdjointSetSteps(TS ts,PetscInt steps) 2972 { 2973 PetscFunctionBegin; 2974 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2975 PetscValidLogicalCollectiveInt(ts,steps,2); 2976 if (steps < 0) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Cannot step back a negative number of steps"); 2977 if (steps > ts->total_steps) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Cannot step back more than the total number of forward steps"); 2978 ts->adjoint_max_steps = steps; 2979 PetscFunctionReturn(0); 2980 } 2981 2982 #undef __FUNCT__ 2983 #define __FUNCT__ "TSSetCostGradients" 2984 /*@ 2985 TSSetCostGradients - Sets the initial value of the gradients of the cost function w.r.t. initial conditions and w.r.t. the problem parameters 2986 for use by the TSAdjoint routines. 2987 2988 Logically Collective on TS and Vec 2989 2990 Input Parameters: 2991 + ts - the TS context obtained from TSCreate() 2992 . 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 2993 - mu - gradients with respect to the parameters, the number of entries in these vectors is the same as the number of parameters 2994 2995 Level: beginner 2996 2997 Notes: the entries in these vectors must be correctly initialized with the values lamda_i = df/dy|finaltime mu_i = df/dp|finaltime 2998 2999 .keywords: TS, timestep, set, sensitivity, initial conditions 3000 @*/ 3001 PetscErrorCode TSSetCostGradients(TS ts,PetscInt numcost,Vec *lambda,Vec *mu) 3002 { 3003 PetscFunctionBegin; 3004 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3005 PetscValidPointer(lambda,2); 3006 ts->vecs_sensi = lambda; 3007 ts->vecs_sensip = mu; 3008 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"); 3009 ts->numcost = numcost; 3010 PetscFunctionReturn(0); 3011 } 3012 3013 #undef __FUNCT__ 3014 #define __FUNCT__ "TSAdjointSetRHSJacobian" 3015 /*@C 3016 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. 3017 3018 Logically Collective on TS 3019 3020 Input Parameters: 3021 + ts - The TS context obtained from TSCreate() 3022 - func - The function 3023 3024 Calling sequence of func: 3025 $ func (TS ts,PetscReal t,Vec y,Mat A,void *ctx); 3026 + t - current timestep 3027 . y - input vector (current ODE solution) 3028 . A - output matrix 3029 - ctx - [optional] user-defined function context 3030 3031 Level: intermediate 3032 3033 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 3034 3035 .keywords: TS, sensitivity 3036 .seealso: 3037 @*/ 3038 PetscErrorCode TSAdjointSetRHSJacobian(TS ts,Mat Amat,PetscErrorCode (*func)(TS,PetscReal,Vec,Mat,void*),void *ctx) 3039 { 3040 PetscErrorCode ierr; 3041 3042 PetscFunctionBegin; 3043 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3044 if (Amat) PetscValidHeaderSpecific(Amat,MAT_CLASSID,2); 3045 3046 ts->rhsjacobianp = func; 3047 ts->rhsjacobianpctx = ctx; 3048 if(Amat) { 3049 ierr = PetscObjectReference((PetscObject)Amat);CHKERRQ(ierr); 3050 ierr = MatDestroy(&ts->Jacp);CHKERRQ(ierr); 3051 ts->Jacp = Amat; 3052 } 3053 PetscFunctionReturn(0); 3054 } 3055 3056 #undef __FUNCT__ 3057 #define __FUNCT__ "TSAdjointComputeRHSJacobian" 3058 /*@C 3059 TSAdjointComputeRHSJacobian - Runs the user-defined Jacobian function. 3060 3061 Collective on TS 3062 3063 Input Parameters: 3064 . ts - The TS context obtained from TSCreate() 3065 3066 Level: developer 3067 3068 .keywords: TS, sensitivity 3069 .seealso: TSAdjointSetRHSJacobian() 3070 @*/ 3071 PetscErrorCode TSAdjointComputeRHSJacobian(TS ts,PetscReal t,Vec X,Mat Amat) 3072 { 3073 PetscErrorCode ierr; 3074 3075 PetscFunctionBegin; 3076 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3077 PetscValidHeaderSpecific(X,VEC_CLASSID,3); 3078 PetscValidPointer(Amat,4); 3079 3080 PetscStackPush("TS user JacobianP function for sensitivity analysis"); 3081 ierr = (*ts->rhsjacobianp)(ts,t,X,Amat,ts->rhsjacobianpctx); CHKERRQ(ierr); 3082 PetscStackPop; 3083 PetscFunctionReturn(0); 3084 } 3085 3086 #undef __FUNCT__ 3087 #define __FUNCT__ "TSSetCostIntegrand" 3088 /*@C 3089 TSSetCostIntegrand - Sets the routine for evaluating the integral term in one or more cost functions 3090 3091 Logically Collective on TS 3092 3093 Input Parameters: 3094 + ts - the TS context obtained from TSCreate() 3095 . numcost - number of gradients to be computed, this is the number of cost functions 3096 . rf - routine for evaluating the integrand function 3097 . drdyf - function that computes the gradients of the r's with respect to y,NULL if not a function y 3098 . drdpf - function that computes the gradients of the r's with respect to p, NULL if not a function of p 3099 . fwd - flag indicating whether to evaluate cost integral in the forward run or the adjoint run 3100 - ctx - [optional] user-defined context for private data for the function evaluation routine (may be NULL) 3101 3102 Calling sequence of rf: 3103 $ rf(TS ts,PetscReal t,Vec y,Vec f[],void *ctx); 3104 3105 + t - current timestep 3106 . y - input vector 3107 . f - function result; one vector entry for each cost function 3108 - ctx - [optional] user-defined function context 3109 3110 Calling sequence of drdyf: 3111 $ PetscErroCode drdyf(TS ts,PetscReal t,Vec y,Vec *drdy,void *ctx); 3112 3113 Calling sequence of drdpf: 3114 $ PetscErroCode drdpf(TS ts,PetscReal t,Vec y,Vec *drdp,void *ctx); 3115 3116 Level: intermediate 3117 3118 Notes: For optimization there is generally a single cost function, numcost = 1. For sensitivities there may be multiple cost functions 3119 3120 .keywords: TS, sensitivity analysis, timestep, set, quadrature, function 3121 3122 .seealso: TSAdjointSetRHSJacobian(),TSGetCostGradients(), TSSetCostGradients() 3123 @*/ 3124 PetscErrorCode TSSetCostIntegrand(TS ts,PetscInt numcost,PetscErrorCode (*rf)(TS,PetscReal,Vec,Vec,void*), 3125 PetscErrorCode (*drdyf)(TS,PetscReal,Vec,Vec*,void*), 3126 PetscErrorCode (*drdpf)(TS,PetscReal,Vec,Vec*,void*), 3127 PetscBool fwd,void *ctx) 3128 { 3129 PetscErrorCode ierr; 3130 3131 PetscFunctionBegin; 3132 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3133 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()"); 3134 if (!ts->numcost) ts->numcost=numcost; 3135 3136 ts->costintegralfwd = fwd; /* Evaluate the cost integral in forward run if fwd is true */ 3137 ierr = VecCreateSeq(PETSC_COMM_SELF,numcost,&ts->vec_costintegral);CHKERRQ(ierr); 3138 ierr = VecDuplicate(ts->vec_costintegral,&ts->vec_costintegrand);CHKERRQ(ierr); 3139 ts->costintegrand = rf; 3140 ts->costintegrandctx = ctx; 3141 ts->drdyfunction = drdyf; 3142 ts->drdpfunction = drdpf; 3143 PetscFunctionReturn(0); 3144 } 3145 3146 #undef __FUNCT__ 3147 #define __FUNCT__ "TSGetCostIntegral" 3148 /*@ 3149 TSGetCostIntegral - Returns the values of the integral term in the cost functions. 3150 It is valid to call the routine after a backward run. 3151 3152 Not Collective 3153 3154 Input Parameter: 3155 . ts - the TS context obtained from TSCreate() 3156 3157 Output Parameter: 3158 . v - the vector containing the integrals for each cost function 3159 3160 Level: intermediate 3161 3162 .seealso: TSSetCostIntegrand() 3163 3164 .keywords: TS, sensitivity analysis 3165 @*/ 3166 PetscErrorCode TSGetCostIntegral(TS ts,Vec *v) 3167 { 3168 PetscFunctionBegin; 3169 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3170 PetscValidPointer(v,2); 3171 *v = ts->vec_costintegral; 3172 PetscFunctionReturn(0); 3173 } 3174 3175 #undef __FUNCT__ 3176 #define __FUNCT__ "TSAdjointComputeCostIntegrand" 3177 /*@ 3178 TSAdjointComputeCostIntegrand - Evaluates the integral function in the cost functions. 3179 3180 Input Parameters: 3181 + ts - the TS context 3182 . t - current time 3183 - y - state vector, i.e. current solution 3184 3185 Output Parameter: 3186 . q - vector of size numcost to hold the outputs 3187 3188 Note: 3189 Most users should not need to explicitly call this routine, as it 3190 is used internally within the sensitivity analysis context. 3191 3192 Level: developer 3193 3194 .keywords: TS, compute 3195 3196 .seealso: TSSetCostIntegrand() 3197 @*/ 3198 PetscErrorCode TSAdjointComputeCostIntegrand(TS ts,PetscReal t,Vec y,Vec q) 3199 { 3200 PetscErrorCode ierr; 3201 3202 PetscFunctionBegin; 3203 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3204 PetscValidHeaderSpecific(y,VEC_CLASSID,3); 3205 PetscValidHeaderSpecific(q,VEC_CLASSID,4); 3206 3207 ierr = PetscLogEventBegin(TS_FunctionEval,ts,y,q,0);CHKERRQ(ierr); 3208 if (ts->costintegrand) { 3209 PetscStackPush("TS user integrand in the cost function"); 3210 ierr = (*ts->costintegrand)(ts,t,y,q,ts->costintegrandctx);CHKERRQ(ierr); 3211 PetscStackPop; 3212 } else { 3213 ierr = VecZeroEntries(q);CHKERRQ(ierr); 3214 } 3215 3216 ierr = PetscLogEventEnd(TS_FunctionEval,ts,y,q,0);CHKERRQ(ierr); 3217 PetscFunctionReturn(0); 3218 } 3219 3220 #undef __FUNCT__ 3221 #define __FUNCT__ "TSAdjointComputeDRDYFunction" 3222 /*@ 3223 TSAdjointComputeDRDYFunction - Runs the user-defined DRDY function. 3224 3225 Collective on TS 3226 3227 Input Parameters: 3228 . ts - The TS context obtained from TSCreate() 3229 3230 Notes: 3231 TSAdjointComputeDRDYFunction() is typically used for sensitivity implementation, 3232 so most users would not generally call this routine themselves. 3233 3234 Level: developer 3235 3236 .keywords: TS, sensitivity 3237 .seealso: TSAdjointComputeDRDYFunction() 3238 @*/ 3239 PetscErrorCode TSAdjointComputeDRDYFunction(TS ts,PetscReal t,Vec y,Vec *drdy) 3240 { 3241 PetscErrorCode ierr; 3242 3243 PetscFunctionBegin; 3244 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3245 PetscValidHeaderSpecific(y,VEC_CLASSID,3); 3246 3247 PetscStackPush("TS user DRDY function for sensitivity analysis"); 3248 ierr = (*ts->drdyfunction)(ts,t,y,drdy,ts->costintegrandctx); CHKERRQ(ierr); 3249 PetscStackPop; 3250 PetscFunctionReturn(0); 3251 } 3252 3253 #undef __FUNCT__ 3254 #define __FUNCT__ "TSAdjointComputeDRDPFunction" 3255 /*@ 3256 TSAdjointComputeDRDPFunction - Runs the user-defined DRDP function. 3257 3258 Collective on TS 3259 3260 Input Parameters: 3261 . ts - The TS context obtained from TSCreate() 3262 3263 Notes: 3264 TSDRDPFunction() is typically used for sensitivity implementation, 3265 so most users would not generally call this routine themselves. 3266 3267 Level: developer 3268 3269 .keywords: TS, sensitivity 3270 .seealso: TSAdjointSetDRDPFunction() 3271 @*/ 3272 PetscErrorCode TSAdjointComputeDRDPFunction(TS ts,PetscReal t,Vec y,Vec *drdp) 3273 { 3274 PetscErrorCode ierr; 3275 3276 PetscFunctionBegin; 3277 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3278 PetscValidHeaderSpecific(y,VEC_CLASSID,3); 3279 3280 PetscStackPush("TS user DRDP function for sensitivity analysis"); 3281 ierr = (*ts->drdpfunction)(ts,t,y,drdp,ts->costintegrandctx); CHKERRQ(ierr); 3282 PetscStackPop; 3283 PetscFunctionReturn(0); 3284 } 3285 3286 #undef __FUNCT__ 3287 #define __FUNCT__ "TSSetPreStep" 3288 /*@C 3289 TSSetPreStep - Sets the general-purpose function 3290 called once at the beginning of each time step. 3291 3292 Logically Collective on TS 3293 3294 Input Parameters: 3295 + ts - The TS context obtained from TSCreate() 3296 - func - The function 3297 3298 Calling sequence of func: 3299 . func (TS ts); 3300 3301 Level: intermediate 3302 3303 Note: 3304 If a step is rejected, TSStep() will call this routine again before each attempt. 3305 The last completed time step number can be queried using TSGetTimeStepNumber(), the 3306 size of the step being attempted can be obtained using TSGetTimeStep(). 3307 3308 .keywords: TS, timestep 3309 .seealso: TSSetPreStage(), TSSetPostStage(), TSSetPostStep(), TSStep() 3310 @*/ 3311 PetscErrorCode TSSetPreStep(TS ts, PetscErrorCode (*func)(TS)) 3312 { 3313 PetscFunctionBegin; 3314 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3315 ts->prestep = func; 3316 PetscFunctionReturn(0); 3317 } 3318 3319 #undef __FUNCT__ 3320 #define __FUNCT__ "TSPreStep" 3321 /*@ 3322 TSPreStep - Runs the user-defined pre-step function. 3323 3324 Collective on TS 3325 3326 Input Parameters: 3327 . ts - The TS context obtained from TSCreate() 3328 3329 Notes: 3330 TSPreStep() is typically used within time stepping implementations, 3331 so most users would not generally call this routine themselves. 3332 3333 Level: developer 3334 3335 .keywords: TS, timestep 3336 .seealso: TSSetPreStep(), TSPreStage(), TSPostStage(), TSPostStep() 3337 @*/ 3338 PetscErrorCode TSPreStep(TS ts) 3339 { 3340 PetscErrorCode ierr; 3341 3342 PetscFunctionBegin; 3343 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3344 if (ts->prestep) { 3345 PetscStackCallStandard((*ts->prestep),(ts)); 3346 } 3347 PetscFunctionReturn(0); 3348 } 3349 3350 #undef __FUNCT__ 3351 #define __FUNCT__ "TSSetPreStage" 3352 /*@C 3353 TSSetPreStage - Sets the general-purpose function 3354 called once at the beginning of each stage. 3355 3356 Logically Collective on TS 3357 3358 Input Parameters: 3359 + ts - The TS context obtained from TSCreate() 3360 - func - The function 3361 3362 Calling sequence of func: 3363 . PetscErrorCode func(TS ts, PetscReal stagetime); 3364 3365 Level: intermediate 3366 3367 Note: 3368 There may be several stages per time step. If the solve for a given stage fails, the step may be rejected and retried. 3369 The time step number being computed can be queried using TSGetTimeStepNumber() and the total size of the step being 3370 attempted can be obtained using TSGetTimeStep(). The time at the start of the step is available via TSGetTime(). 3371 3372 .keywords: TS, timestep 3373 .seealso: TSSetPostStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext() 3374 @*/ 3375 PetscErrorCode TSSetPreStage(TS ts, PetscErrorCode (*func)(TS,PetscReal)) 3376 { 3377 PetscFunctionBegin; 3378 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3379 ts->prestage = func; 3380 PetscFunctionReturn(0); 3381 } 3382 3383 #undef __FUNCT__ 3384 #define __FUNCT__ "TSSetPostStage" 3385 /*@C 3386 TSSetPostStage - Sets the general-purpose function 3387 called once at the end of each stage. 3388 3389 Logically Collective on TS 3390 3391 Input Parameters: 3392 + ts - The TS context obtained from TSCreate() 3393 - func - The function 3394 3395 Calling sequence of func: 3396 . PetscErrorCode func(TS ts, PetscReal stagetime, PetscInt stageindex, Vec* Y); 3397 3398 Level: intermediate 3399 3400 Note: 3401 There may be several stages per time step. If the solve for a given stage fails, the step may be rejected and retried. 3402 The time step number being computed can be queried using TSGetTimeStepNumber() and the total size of the step being 3403 attempted can be obtained using TSGetTimeStep(). The time at the start of the step is available via TSGetTime(). 3404 3405 .keywords: TS, timestep 3406 .seealso: TSSetPreStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext() 3407 @*/ 3408 PetscErrorCode TSSetPostStage(TS ts, PetscErrorCode (*func)(TS,PetscReal,PetscInt,Vec*)) 3409 { 3410 PetscFunctionBegin; 3411 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3412 ts->poststage = func; 3413 PetscFunctionReturn(0); 3414 } 3415 3416 #undef __FUNCT__ 3417 #define __FUNCT__ "TSSetPostEvaluate" 3418 /*@C 3419 TSSetPostEvaluate - Sets the general-purpose function 3420 called once at the end of each step evaluation. 3421 3422 Logically Collective on TS 3423 3424 Input Parameters: 3425 + ts - The TS context obtained from TSCreate() 3426 - func - The function 3427 3428 Calling sequence of func: 3429 . PetscErrorCode func(TS ts); 3430 3431 Level: intermediate 3432 3433 Note: 3434 Semantically, TSSetPostEvaluate() differs from TSSetPostStep() since the function it sets is called before event-handling 3435 thus guaranteeing the same solution (computed by the time-stepper) will be passed to it. On the other hand, TSPostStep() 3436 may be passed a different solution, possibly changed by the event handler. TSPostEvaluate() is called after the next step 3437 solution is evaluated allowing to modify it, if need be. The solution can be obtained with TSGetSolution(), the time step 3438 with TSGetTimeStep(), and the time at the start of the step is available via TSGetTime() 3439 3440 .keywords: TS, timestep 3441 .seealso: TSSetPreStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext() 3442 @*/ 3443 PetscErrorCode TSSetPostEvaluate(TS ts, PetscErrorCode (*func)(TS)) 3444 { 3445 PetscFunctionBegin; 3446 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3447 ts->postevaluate = func; 3448 PetscFunctionReturn(0); 3449 } 3450 3451 #undef __FUNCT__ 3452 #define __FUNCT__ "TSPreStage" 3453 /*@ 3454 TSPreStage - Runs the user-defined pre-stage function set using TSSetPreStage() 3455 3456 Collective on TS 3457 3458 Input Parameters: 3459 . ts - The TS context obtained from TSCreate() 3460 stagetime - The absolute time of the current stage 3461 3462 Notes: 3463 TSPreStage() is typically used within time stepping implementations, 3464 most users would not generally call this routine themselves. 3465 3466 Level: developer 3467 3468 .keywords: TS, timestep 3469 .seealso: TSPostStage(), TSSetPreStep(), TSPreStep(), TSPostStep() 3470 @*/ 3471 PetscErrorCode TSPreStage(TS ts, PetscReal stagetime) 3472 { 3473 PetscErrorCode ierr; 3474 3475 PetscFunctionBegin; 3476 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3477 if (ts->prestage) { 3478 PetscStackCallStandard((*ts->prestage),(ts,stagetime)); 3479 } 3480 PetscFunctionReturn(0); 3481 } 3482 3483 #undef __FUNCT__ 3484 #define __FUNCT__ "TSPostStage" 3485 /*@ 3486 TSPostStage - Runs the user-defined post-stage function set using TSSetPostStage() 3487 3488 Collective on TS 3489 3490 Input Parameters: 3491 . ts - The TS context obtained from TSCreate() 3492 stagetime - The absolute time of the current stage 3493 stageindex - Stage number 3494 Y - Array of vectors (of size = total number 3495 of stages) with the stage solutions 3496 3497 Notes: 3498 TSPostStage() is typically used within time stepping implementations, 3499 most users would not generally call this routine themselves. 3500 3501 Level: developer 3502 3503 .keywords: TS, timestep 3504 .seealso: TSPreStage(), TSSetPreStep(), TSPreStep(), TSPostStep() 3505 @*/ 3506 PetscErrorCode TSPostStage(TS ts, PetscReal stagetime, PetscInt stageindex, Vec *Y) 3507 { 3508 PetscErrorCode ierr; 3509 3510 PetscFunctionBegin; 3511 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3512 if (ts->poststage) { 3513 PetscStackCallStandard((*ts->poststage),(ts,stagetime,stageindex,Y)); 3514 } 3515 PetscFunctionReturn(0); 3516 } 3517 3518 #undef __FUNCT__ 3519 #define __FUNCT__ "TSPostEvaluate" 3520 /*@ 3521 TSPostEvaluate - Runs the user-defined post-evaluate function set using TSSetPostEvaluate() 3522 3523 Collective on TS 3524 3525 Input Parameters: 3526 . ts - The TS context obtained from TSCreate() 3527 3528 Notes: 3529 TSPostEvaluate() is typically used within time stepping implementations, 3530 most users would not generally call this routine themselves. 3531 3532 Level: developer 3533 3534 .keywords: TS, timestep 3535 .seealso: TSSetPostEvaluate(), TSSetPreStep(), TSPreStep(), TSPostStep() 3536 @*/ 3537 PetscErrorCode TSPostEvaluate(TS ts) 3538 { 3539 PetscErrorCode ierr; 3540 3541 PetscFunctionBegin; 3542 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3543 if (ts->postevaluate) { 3544 PetscStackCallStandard((*ts->postevaluate),(ts)); 3545 } 3546 PetscFunctionReturn(0); 3547 } 3548 3549 #undef __FUNCT__ 3550 #define __FUNCT__ "TSSetPostStep" 3551 /*@C 3552 TSSetPostStep - Sets the general-purpose function 3553 called once at the end of each time step. 3554 3555 Logically Collective on TS 3556 3557 Input Parameters: 3558 + ts - The TS context obtained from TSCreate() 3559 - func - The function 3560 3561 Calling sequence of func: 3562 $ func (TS ts); 3563 3564 Notes: 3565 The function set by TSSetPostStep() is called after each successful step. The solution vector X 3566 obtained by TSGetSolution() may be different than that computed at the step end if the event handler 3567 locates an event and TSPostEvent() modifies it. Use TSSetPostEvaluate() if an unmodified solution is needed instead. 3568 3569 Level: intermediate 3570 3571 .keywords: TS, timestep 3572 .seealso: TSSetPreStep(), TSSetPreStage(), TSSetPostEvaluate(), TSGetTimeStep(), TSGetTimeStepNumber(), TSGetTime() 3573 @*/ 3574 PetscErrorCode TSSetPostStep(TS ts, PetscErrorCode (*func)(TS)) 3575 { 3576 PetscFunctionBegin; 3577 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3578 ts->poststep = func; 3579 PetscFunctionReturn(0); 3580 } 3581 3582 #undef __FUNCT__ 3583 #define __FUNCT__ "TSPostStep" 3584 /*@ 3585 TSPostStep - Runs the user-defined post-step function. 3586 3587 Collective on TS 3588 3589 Input Parameters: 3590 . ts - The TS context obtained from TSCreate() 3591 3592 Notes: 3593 TSPostStep() is typically used within time stepping implementations, 3594 so most users would not generally call this routine themselves. 3595 3596 Level: developer 3597 3598 .keywords: TS, timestep 3599 @*/ 3600 PetscErrorCode TSPostStep(TS ts) 3601 { 3602 PetscErrorCode ierr; 3603 3604 PetscFunctionBegin; 3605 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3606 if (ts->poststep) { 3607 PetscStackCallStandard((*ts->poststep),(ts)); 3608 } 3609 PetscFunctionReturn(0); 3610 } 3611 3612 /* ------------ Routines to set performance monitoring options ----------- */ 3613 3614 #undef __FUNCT__ 3615 #define __FUNCT__ "TSMonitorSet" 3616 /*@C 3617 TSMonitorSet - Sets an ADDITIONAL function that is to be used at every 3618 timestep to display the iteration's progress. 3619 3620 Logically Collective on TS 3621 3622 Input Parameters: 3623 + ts - the TS context obtained from TSCreate() 3624 . monitor - monitoring routine 3625 . mctx - [optional] user-defined context for private data for the 3626 monitor routine (use NULL if no context is desired) 3627 - monitordestroy - [optional] routine that frees monitor context 3628 (may be NULL) 3629 3630 Calling sequence of monitor: 3631 $ int monitor(TS ts,PetscInt steps,PetscReal time,Vec u,void *mctx) 3632 3633 + ts - the TS context 3634 . 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) 3635 . time - current time 3636 . u - current iterate 3637 - mctx - [optional] monitoring context 3638 3639 Notes: 3640 This routine adds an additional monitor to the list of monitors that 3641 already has been loaded. 3642 3643 Fortran notes: Only a single monitor function can be set for each TS object 3644 3645 Level: intermediate 3646 3647 .keywords: TS, timestep, set, monitor 3648 3649 .seealso: TSMonitorDefault(), TSMonitorCancel() 3650 @*/ 3651 PetscErrorCode TSMonitorSet(TS ts,PetscErrorCode (*monitor)(TS,PetscInt,PetscReal,Vec,void*),void *mctx,PetscErrorCode (*mdestroy)(void**)) 3652 { 3653 PetscErrorCode ierr; 3654 PetscInt i; 3655 PetscBool identical; 3656 3657 PetscFunctionBegin; 3658 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3659 for (i=0; i<ts->numbermonitors;i++) { 3660 ierr = PetscMonitorCompare((PetscErrorCode (*)(void))monitor,mctx,mdestroy,(PetscErrorCode (*)(void))ts->monitor[i],ts->monitorcontext[i],ts->monitordestroy[i],&identical);CHKERRQ(ierr); 3661 if (identical) PetscFunctionReturn(0); 3662 } 3663 if (ts->numbermonitors >= MAXTSMONITORS) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Too many monitors set"); 3664 ts->monitor[ts->numbermonitors] = monitor; 3665 ts->monitordestroy[ts->numbermonitors] = mdestroy; 3666 ts->monitorcontext[ts->numbermonitors++] = (void*)mctx; 3667 PetscFunctionReturn(0); 3668 } 3669 3670 #undef __FUNCT__ 3671 #define __FUNCT__ "TSMonitorCancel" 3672 /*@C 3673 TSMonitorCancel - Clears all the monitors that have been set on a time-step object. 3674 3675 Logically Collective on TS 3676 3677 Input Parameters: 3678 . ts - the TS context obtained from TSCreate() 3679 3680 Notes: 3681 There is no way to remove a single, specific monitor. 3682 3683 Level: intermediate 3684 3685 .keywords: TS, timestep, set, monitor 3686 3687 .seealso: TSMonitorDefault(), TSMonitorSet() 3688 @*/ 3689 PetscErrorCode TSMonitorCancel(TS ts) 3690 { 3691 PetscErrorCode ierr; 3692 PetscInt i; 3693 3694 PetscFunctionBegin; 3695 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3696 for (i=0; i<ts->numbermonitors; i++) { 3697 if (ts->monitordestroy[i]) { 3698 ierr = (*ts->monitordestroy[i])(&ts->monitorcontext[i]);CHKERRQ(ierr); 3699 } 3700 } 3701 ts->numbermonitors = 0; 3702 PetscFunctionReturn(0); 3703 } 3704 3705 #undef __FUNCT__ 3706 #define __FUNCT__ "TSMonitorDefault" 3707 /*@C 3708 TSMonitorDefault - The Default monitor, prints the timestep and time for each step 3709 3710 Level: intermediate 3711 3712 .keywords: TS, set, monitor 3713 3714 .seealso: TSMonitorSet() 3715 @*/ 3716 PetscErrorCode TSMonitorDefault(TS ts,PetscInt step,PetscReal ptime,Vec v,PetscViewerAndFormat *vf) 3717 { 3718 PetscErrorCode ierr; 3719 PetscViewer viewer = vf->viewer; 3720 PetscBool iascii,ibinary; 3721 3722 PetscFunctionBegin; 3723 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,4); 3724 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 3725 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&ibinary);CHKERRQ(ierr); 3726 ierr = PetscViewerPushFormat(viewer,vf->format);CHKERRQ(ierr); 3727 if (iascii) { 3728 ierr = PetscViewerASCIIAddTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 3729 if (step == -1){ /* this indicates it is an interpolated solution */ 3730 ierr = PetscViewerASCIIPrintf(viewer,"Interpolated solution at time %g between steps %D and %D\n",(double)ptime,ts->steps-1,ts->steps);CHKERRQ(ierr); 3731 } else { 3732 ierr = PetscViewerASCIIPrintf(viewer,"%D TS dt %g time %g%s",step,(double)ts->time_step,(double)ptime,ts->steprollback ? " (r)\n" : "\n");CHKERRQ(ierr); 3733 } 3734 ierr = PetscViewerASCIISubtractTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 3735 } else if (ibinary) { 3736 PetscMPIInt rank; 3737 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)viewer),&rank);CHKERRQ(ierr); 3738 if (!rank) { 3739 PetscBool skipHeader; 3740 PetscInt classid = REAL_FILE_CLASSID; 3741 3742 ierr = PetscViewerBinaryGetSkipHeader(viewer,&skipHeader);CHKERRQ(ierr); 3743 if (!skipHeader) { 3744 ierr = PetscViewerBinaryWrite(viewer,&classid,1,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); 3745 } 3746 ierr = PetscRealView(1,&ptime,viewer);CHKERRQ(ierr); 3747 } else { 3748 ierr = PetscRealView(0,&ptime,viewer);CHKERRQ(ierr); 3749 } 3750 } 3751 ierr = PetscViewerPopFormat(viewer);CHKERRQ(ierr); 3752 PetscFunctionReturn(0); 3753 } 3754 3755 #undef __FUNCT__ 3756 #define __FUNCT__ "TSAdjointMonitorSet" 3757 /*@C 3758 TSAdjointMonitorSet - Sets an ADDITIONAL function that is to be used at every 3759 timestep to display the iteration's progress. 3760 3761 Logically Collective on TS 3762 3763 Input Parameters: 3764 + ts - the TS context obtained from TSCreate() 3765 . adjointmonitor - monitoring routine 3766 . adjointmctx - [optional] user-defined context for private data for the 3767 monitor routine (use NULL if no context is desired) 3768 - adjointmonitordestroy - [optional] routine that frees monitor context 3769 (may be NULL) 3770 3771 Calling sequence of monitor: 3772 $ int adjointmonitor(TS ts,PetscInt steps,PetscReal time,Vec u,PetscInt numcost,Vec *lambda, Vec *mu,void *adjointmctx) 3773 3774 + ts - the TS context 3775 . 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 3776 been interpolated to) 3777 . time - current time 3778 . u - current iterate 3779 . numcost - number of cost functionos 3780 . lambda - sensitivities to initial conditions 3781 . mu - sensitivities to parameters 3782 - adjointmctx - [optional] adjoint monitoring context 3783 3784 Notes: 3785 This routine adds an additional monitor to the list of monitors that 3786 already has been loaded. 3787 3788 Fortran notes: Only a single monitor function can be set for each TS object 3789 3790 Level: intermediate 3791 3792 .keywords: TS, timestep, set, adjoint, monitor 3793 3794 .seealso: TSAdjointMonitorCancel() 3795 @*/ 3796 PetscErrorCode TSAdjointMonitorSet(TS ts,PetscErrorCode (*adjointmonitor)(TS,PetscInt,PetscReal,Vec,PetscInt,Vec*,Vec*,void*),void *adjointmctx,PetscErrorCode (*adjointmdestroy)(void**)) 3797 { 3798 PetscErrorCode ierr; 3799 PetscInt i; 3800 PetscBool identical; 3801 3802 PetscFunctionBegin; 3803 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3804 for (i=0; i<ts->numbermonitors;i++) { 3805 ierr = PetscMonitorCompare((PetscErrorCode (*)(void))adjointmonitor,adjointmctx,adjointmdestroy,(PetscErrorCode (*)(void))ts->adjointmonitor[i],ts->adjointmonitorcontext[i],ts->adjointmonitordestroy[i],&identical);CHKERRQ(ierr); 3806 if (identical) PetscFunctionReturn(0); 3807 } 3808 if (ts->numberadjointmonitors >= MAXTSMONITORS) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Too many adjoint monitors set"); 3809 ts->adjointmonitor[ts->numberadjointmonitors] = adjointmonitor; 3810 ts->adjointmonitordestroy[ts->numberadjointmonitors] = adjointmdestroy; 3811 ts->adjointmonitorcontext[ts->numberadjointmonitors++] = (void*)adjointmctx; 3812 PetscFunctionReturn(0); 3813 } 3814 3815 #undef __FUNCT__ 3816 #define __FUNCT__ "TSAdjointMonitorCancel" 3817 /*@C 3818 TSAdjointMonitorCancel - Clears all the adjoint monitors that have been set on a time-step object. 3819 3820 Logically Collective on TS 3821 3822 Input Parameters: 3823 . ts - the TS context obtained from TSCreate() 3824 3825 Notes: 3826 There is no way to remove a single, specific monitor. 3827 3828 Level: intermediate 3829 3830 .keywords: TS, timestep, set, adjoint, monitor 3831 3832 .seealso: TSAdjointMonitorSet() 3833 @*/ 3834 PetscErrorCode TSAdjointMonitorCancel(TS ts) 3835 { 3836 PetscErrorCode ierr; 3837 PetscInt i; 3838 3839 PetscFunctionBegin; 3840 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3841 for (i=0; i<ts->numberadjointmonitors; i++) { 3842 if (ts->adjointmonitordestroy[i]) { 3843 ierr = (*ts->adjointmonitordestroy[i])(&ts->adjointmonitorcontext[i]);CHKERRQ(ierr); 3844 } 3845 } 3846 ts->numberadjointmonitors = 0; 3847 PetscFunctionReturn(0); 3848 } 3849 3850 #undef __FUNCT__ 3851 #define __FUNCT__ "TSAdjointMonitorDefault" 3852 /*@C 3853 TSAdjointMonitorDefault - the default monitor of adjoint computations 3854 3855 Level: intermediate 3856 3857 .keywords: TS, set, monitor 3858 3859 .seealso: TSAdjointMonitorSet() 3860 @*/ 3861 PetscErrorCode TSAdjointMonitorDefault(TS ts,PetscInt step,PetscReal ptime,Vec v,PetscInt numcost,Vec *lambda,Vec *mu,PetscViewerAndFormat *vf) 3862 { 3863 PetscErrorCode ierr; 3864 PetscViewer viewer = vf->viewer; 3865 3866 PetscFunctionBegin; 3867 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,4); 3868 ierr = PetscViewerPushFormat(viewer,vf->format);CHKERRQ(ierr); 3869 ierr = PetscViewerASCIIAddTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 3870 ierr = PetscViewerASCIIPrintf(viewer,"%D TS dt %g time %g%s",step,(double)ts->time_step,(double)ptime,ts->steprollback ? " (r)\n" : "\n");CHKERRQ(ierr); 3871 ierr = PetscViewerASCIISubtractTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 3872 ierr = PetscViewerPopFormat(viewer);CHKERRQ(ierr); 3873 PetscFunctionReturn(0); 3874 } 3875 3876 #undef __FUNCT__ 3877 #define __FUNCT__ "TSInterpolate" 3878 /*@ 3879 TSInterpolate - Interpolate the solution computed during the previous step to an arbitrary location in the interval 3880 3881 Collective on TS 3882 3883 Input Argument: 3884 + ts - time stepping context 3885 - t - time to interpolate to 3886 3887 Output Argument: 3888 . U - state at given time 3889 3890 Level: intermediate 3891 3892 Developer Notes: 3893 TSInterpolate() and the storing of previous steps/stages should be generalized to support delay differential equations and continuous adjoints. 3894 3895 .keywords: TS, set 3896 3897 .seealso: TSSetExactFinalTime(), TSSolve() 3898 @*/ 3899 PetscErrorCode TSInterpolate(TS ts,PetscReal t,Vec U) 3900 { 3901 PetscErrorCode ierr; 3902 3903 PetscFunctionBegin; 3904 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3905 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 3906 if (t < ts->ptime_prev || t > ts->ptime) SETERRQ3(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Requested time %g not in last time steps [%g,%g]",t,(double)ts->ptime_prev,(double)ts->ptime); 3907 if (!ts->ops->interpolate) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"%s does not provide interpolation",((PetscObject)ts)->type_name); 3908 ierr = (*ts->ops->interpolate)(ts,t,U);CHKERRQ(ierr); 3909 PetscFunctionReturn(0); 3910 } 3911 3912 #undef __FUNCT__ 3913 #define __FUNCT__ "TSStep" 3914 /*@ 3915 TSStep - Steps one time step 3916 3917 Collective on TS 3918 3919 Input Parameter: 3920 . ts - the TS context obtained from TSCreate() 3921 3922 Level: developer 3923 3924 Notes: 3925 The public interface for the ODE/DAE solvers is TSSolve(), you should almost for sure be using that routine and not this routine. 3926 3927 The hook set using TSSetPreStep() is called before each attempt to take the step. In general, the time step size may 3928 be changed due to adaptive error controller or solve failures. Note that steps may contain multiple stages. 3929 3930 This may over-step the final time provided in TSSetDuration() depending on the time-step used. TSSolve() interpolates to exactly the 3931 time provided in TSSetDuration(). One can use TSInterpolate() to determine an interpolated solution within the final timestep. 3932 3933 .keywords: TS, timestep, solve 3934 3935 .seealso: TSCreate(), TSSetUp(), TSDestroy(), TSSolve(), TSSetPreStep(), TSSetPreStage(), TSSetPostStage(), TSInterpolate() 3936 @*/ 3937 PetscErrorCode TSStep(TS ts) 3938 { 3939 PetscErrorCode ierr; 3940 static PetscBool cite = PETSC_FALSE; 3941 PetscReal ptime; 3942 3943 PetscFunctionBegin; 3944 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3945 ierr = PetscCitationsRegister("@techreport{tspaper,\n" 3946 " title = {{PETSc/TS}: A Modern Scalable {DAE/ODE} Solver Library},\n" 3947 " author = {Shrirang Abhyankar and Jed Brown and Emil Constantinescu and Debojyoti Ghosh and Barry F. Smith},\n" 3948 " type = {Preprint},\n" 3949 " number = {ANL/MCS-P5061-0114},\n" 3950 " institution = {Argonne National Laboratory},\n" 3951 " year = {2014}\n}\n",&cite);CHKERRQ(ierr); 3952 3953 ierr = TSSetUp(ts);CHKERRQ(ierr); 3954 ierr = TSTrajectorySetUp(ts->trajectory,ts);CHKERRQ(ierr); 3955 3956 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()"); 3957 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"); 3958 3959 if (!ts->steps) ts->ptime_prev = ts->ptime; 3960 ts->reason = TS_CONVERGED_ITERATING; 3961 ptime = ts->ptime; ts->ptime_prev_rollback = ts->ptime_prev; 3962 if (!ts->ops->step) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSStep not implemented for type '%s'",((PetscObject)ts)->type_name); 3963 ierr = PetscLogEventBegin(TS_Step,ts,0,0,0);CHKERRQ(ierr); 3964 ierr = (*ts->ops->step)(ts);CHKERRQ(ierr); 3965 ierr = PetscLogEventEnd(TS_Step,ts,0,0,0);CHKERRQ(ierr); 3966 ts->ptime_prev = ptime; 3967 ts->steps++; ts->total_steps++; 3968 ts->steprollback = PETSC_FALSE; 3969 ts->steprestart = PETSC_FALSE; 3970 3971 if (ts->reason < 0) { 3972 if (ts->errorifstepfailed) { 3973 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]); 3974 else SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s",TSConvergedReasons[ts->reason]); 3975 } 3976 } else if (!ts->reason) { 3977 if (ts->steps >= ts->max_steps) ts->reason = TS_CONVERGED_ITS; 3978 else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME; 3979 } 3980 PetscFunctionReturn(0); 3981 } 3982 3983 #undef __FUNCT__ 3984 #define __FUNCT__ "TSAdjointStep" 3985 /*@ 3986 TSAdjointStep - Steps one time step backward in the adjoint run 3987 3988 Collective on TS 3989 3990 Input Parameter: 3991 . ts - the TS context obtained from TSCreate() 3992 3993 Level: intermediate 3994 3995 .keywords: TS, adjoint, step 3996 3997 .seealso: TSAdjointSetUp(), TSAdjointSolve() 3998 @*/ 3999 PetscErrorCode TSAdjointStep(TS ts) 4000 { 4001 DM dm; 4002 PetscErrorCode ierr; 4003 4004 PetscFunctionBegin; 4005 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4006 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 4007 ierr = TSAdjointSetUp(ts);CHKERRQ(ierr); 4008 4009 ierr = VecViewFromOptions(ts->vec_sol,(PetscObject)ts,"-ts_view_solution");CHKERRQ(ierr); 4010 4011 ts->reason = TS_CONVERGED_ITERATING; 4012 ts->ptime_prev = ts->ptime; 4013 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); 4014 ierr = PetscLogEventBegin(TS_AdjointStep,ts,0,0,0);CHKERRQ(ierr); 4015 ierr = (*ts->ops->adjointstep)(ts);CHKERRQ(ierr); 4016 ierr = PetscLogEventEnd(TS_AdjointStep,ts,0,0,0);CHKERRQ(ierr); 4017 ts->steps++; ts->total_steps--; 4018 4019 if (ts->reason < 0) { 4020 if (ts->errorifstepfailed) { 4021 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]); 4022 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]); 4023 else SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s",TSConvergedReasons[ts->reason]); 4024 } 4025 } else if (!ts->reason) { 4026 if (ts->steps >= ts->adjoint_max_steps) ts->reason = TS_CONVERGED_ITS; 4027 } 4028 PetscFunctionReturn(0); 4029 } 4030 4031 #undef __FUNCT__ 4032 #define __FUNCT__ "TSEvaluateWLTE" 4033 /*@ 4034 TSEvaluateWLTE - Evaluate the weighted local truncation error norm 4035 at the end of a time step with a given order of accuracy. 4036 4037 Collective on TS 4038 4039 Input Arguments: 4040 + ts - time stepping context 4041 . wnormtype - norm type, either NORM_2 or NORM_INFINITY 4042 - order - optional, desired order for the error evaluation or PETSC_DECIDE 4043 4044 Output Arguments: 4045 + order - optional, the actual order of the error evaluation 4046 - wlte - the weighted local truncation error norm 4047 4048 Level: advanced 4049 4050 Notes: 4051 If the timestepper cannot evaluate the error in a particular step 4052 (eg. in the first step or restart steps after event handling), 4053 this routine returns wlte=-1.0 . 4054 4055 .seealso: TSStep(), TSAdapt, TSErrorWeightedNorm() 4056 @*/ 4057 PetscErrorCode TSEvaluateWLTE(TS ts,NormType wnormtype,PetscInt *order,PetscReal *wlte) 4058 { 4059 PetscErrorCode ierr; 4060 4061 PetscFunctionBegin; 4062 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4063 PetscValidType(ts,1); 4064 PetscValidLogicalCollectiveEnum(ts,wnormtype,4); 4065 if (order) PetscValidIntPointer(order,3); 4066 if (order) PetscValidLogicalCollectiveInt(ts,*order,3); 4067 PetscValidRealPointer(wlte,4); 4068 if (wnormtype != NORM_2 && wnormtype != NORM_INFINITY) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]); 4069 if (!ts->ops->evaluatewlte) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSEvaluateWLTE not implemented for type '%s'",((PetscObject)ts)->type_name); 4070 ierr = (*ts->ops->evaluatewlte)(ts,wnormtype,order,wlte);CHKERRQ(ierr); 4071 PetscFunctionReturn(0); 4072 } 4073 4074 #undef __FUNCT__ 4075 #define __FUNCT__ "TSEvaluateStep" 4076 /*@ 4077 TSEvaluateStep - Evaluate the solution at the end of a time step with a given order of accuracy. 4078 4079 Collective on TS 4080 4081 Input Arguments: 4082 + ts - time stepping context 4083 . order - desired order of accuracy 4084 - done - whether the step was evaluated at this order (pass NULL to generate an error if not available) 4085 4086 Output Arguments: 4087 . U - state at the end of the current step 4088 4089 Level: advanced 4090 4091 Notes: 4092 This function cannot be called until all stages have been evaluated. 4093 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. 4094 4095 .seealso: TSStep(), TSAdapt 4096 @*/ 4097 PetscErrorCode TSEvaluateStep(TS ts,PetscInt order,Vec U,PetscBool *done) 4098 { 4099 PetscErrorCode ierr; 4100 4101 PetscFunctionBegin; 4102 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4103 PetscValidType(ts,1); 4104 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 4105 if (!ts->ops->evaluatestep) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSEvaluateStep not implemented for type '%s'",((PetscObject)ts)->type_name); 4106 ierr = (*ts->ops->evaluatestep)(ts,order,U,done);CHKERRQ(ierr); 4107 PetscFunctionReturn(0); 4108 } 4109 4110 #undef __FUNCT__ 4111 #define __FUNCT__ "TSForwardCostIntegral" 4112 /*@ 4113 TSForwardCostIntegral - Evaluate the cost integral in the forward run. 4114 4115 Collective on TS 4116 4117 Input Arguments: 4118 . ts - time stepping context 4119 4120 Level: advanced 4121 4122 Notes: 4123 This function cannot be called until TSStep() has been completed. 4124 4125 .seealso: TSSolve(), TSAdjointCostIntegral() 4126 @*/ 4127 PetscErrorCode TSForwardCostIntegral(TS ts) 4128 { 4129 PetscErrorCode ierr; 4130 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4131 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); 4132 ierr = (*ts->ops->forwardintegral)(ts);CHKERRQ(ierr); 4133 PetscFunctionReturn(0); 4134 } 4135 4136 #undef __FUNCT__ 4137 #define __FUNCT__ "TSSolve" 4138 /*@ 4139 TSSolve - Steps the requested number of timesteps. 4140 4141 Collective on TS 4142 4143 Input Parameter: 4144 + ts - the TS context obtained from TSCreate() 4145 - u - the solution vector (can be null if TSSetSolution() was used and TSSetExactFinalTime(ts,TS_EXACTFINALTIME_MATCHSTEP) was not used, 4146 otherwise must contain the initial conditions and will contain the solution at the final requested time 4147 4148 Level: beginner 4149 4150 Notes: 4151 The final time returned by this function may be different from the time of the internally 4152 held state accessible by TSGetSolution() and TSGetTime() because the method may have 4153 stepped over the final time. 4154 4155 .keywords: TS, timestep, solve 4156 4157 .seealso: TSCreate(), TSSetSolution(), TSStep(), TSGetTime(), TSGetSolveTime() 4158 @*/ 4159 PetscErrorCode TSSolve(TS ts,Vec u) 4160 { 4161 Vec solution; 4162 PetscErrorCode ierr; 4163 4164 PetscFunctionBegin; 4165 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4166 if (u) PetscValidHeaderSpecific(u,VEC_CLASSID,2); 4167 4168 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 */ 4169 PetscValidHeaderSpecific(u,VEC_CLASSID,2); 4170 if (!ts->vec_sol || u == ts->vec_sol) { 4171 ierr = VecDuplicate(u,&solution);CHKERRQ(ierr); 4172 ierr = TSSetSolution(ts,solution);CHKERRQ(ierr); 4173 ierr = VecDestroy(&solution);CHKERRQ(ierr); /* grant ownership */ 4174 } 4175 ierr = VecCopy(u,ts->vec_sol);CHKERRQ(ierr); 4176 } else if (u) { 4177 ierr = TSSetSolution(ts,u);CHKERRQ(ierr); 4178 } 4179 ierr = TSSetUp(ts);CHKERRQ(ierr); 4180 ierr = TSTrajectorySetUp(ts->trajectory,ts);CHKERRQ(ierr); 4181 4182 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()"); 4183 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"); 4184 4185 /* reset time step and iteration counters */ 4186 ts->steps = 0; 4187 ts->ksp_its = 0; 4188 ts->snes_its = 0; 4189 ts->num_snes_failures = 0; 4190 ts->reject = 0; 4191 ts->reason = TS_CONVERGED_ITERATING; 4192 4193 ierr = TSViewFromOptions(ts,NULL,"-ts_view_pre");CHKERRQ(ierr); 4194 4195 if (ts->ops->solve) { /* This private interface is transitional and should be removed when all implementations are updated. */ 4196 ierr = (*ts->ops->solve)(ts);CHKERRQ(ierr); 4197 if (u) {ierr = VecCopy(ts->vec_sol,u);CHKERRQ(ierr);} 4198 ts->solvetime = ts->ptime; 4199 solution = ts->vec_sol; 4200 } else { /* Step the requested number of timesteps. */ 4201 if (ts->steps >= ts->max_steps) ts->reason = TS_CONVERGED_ITS; 4202 else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME; 4203 ierr = TSTrajectorySet(ts->trajectory,ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 4204 ierr = TSEventInitialize(ts->event,ts,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 4205 ts->steprollback = PETSC_FALSE; 4206 ts->steprestart = PETSC_TRUE; 4207 4208 while (!ts->reason) { 4209 ierr = TSMonitor(ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 4210 if (!ts->steprollback) { 4211 ierr = TSPreStep(ts);CHKERRQ(ierr); 4212 } 4213 ierr = TSStep(ts);CHKERRQ(ierr); 4214 if (ts->vec_costintegral && ts->costintegralfwd) { /* Must evaluate the cost integral before event is handled. The cost integral value can also be rolled back. */ 4215 ierr = TSForwardCostIntegral(ts);CHKERRQ(ierr); 4216 } 4217 ierr = TSEventHandler(ts);CHKERRQ(ierr); /* The right-hand side may be changed due to event. Be careful with Any computation using the RHS information after this point. */ 4218 if (!ts->steprollback) { 4219 ierr = TSTrajectorySet(ts->trajectory,ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 4220 ierr = TSPostStep(ts);CHKERRQ(ierr); 4221 } 4222 } 4223 ierr = TSMonitor(ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 4224 4225 if (ts->exact_final_time == TS_EXACTFINALTIME_INTERPOLATE && ts->ptime > ts->max_time) { 4226 ierr = TSInterpolate(ts,ts->max_time,u);CHKERRQ(ierr); 4227 ts->solvetime = ts->max_time; 4228 solution = u; 4229 ierr = TSMonitor(ts,-1,ts->solvetime,solution);CHKERRQ(ierr); 4230 } else { 4231 if (u) {ierr = VecCopy(ts->vec_sol,u);CHKERRQ(ierr);} 4232 ts->solvetime = ts->ptime; 4233 solution = ts->vec_sol; 4234 } 4235 } 4236 4237 ierr = TSViewFromOptions(ts,NULL,"-ts_view");CHKERRQ(ierr); 4238 ierr = VecViewFromOptions(solution,NULL,"-ts_view_solution");CHKERRQ(ierr); 4239 ierr = PetscObjectSAWsBlock((PetscObject)ts);CHKERRQ(ierr); 4240 if (ts->adjoint_solve) { 4241 ierr = TSAdjointSolve(ts);CHKERRQ(ierr); 4242 } 4243 PetscFunctionReturn(0); 4244 } 4245 4246 #undef __FUNCT__ 4247 #define __FUNCT__ "TSAdjointCostIntegral" 4248 /*@ 4249 TSAdjointCostIntegral - Evaluate the cost integral in the adjoint run. 4250 4251 Collective on TS 4252 4253 Input Arguments: 4254 . ts - time stepping context 4255 4256 Level: advanced 4257 4258 Notes: 4259 This function cannot be called until TSAdjointStep() has been completed. 4260 4261 .seealso: TSAdjointSolve(), TSAdjointStep 4262 @*/ 4263 PetscErrorCode TSAdjointCostIntegral(TS ts) 4264 { 4265 PetscErrorCode ierr; 4266 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4267 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); 4268 ierr = (*ts->ops->adjointintegral)(ts);CHKERRQ(ierr); 4269 PetscFunctionReturn(0); 4270 } 4271 4272 #undef __FUNCT__ 4273 #define __FUNCT__ "TSAdjointSolve" 4274 /*@ 4275 TSAdjointSolve - Solves the discrete ajoint problem for an ODE/DAE 4276 4277 Collective on TS 4278 4279 Input Parameter: 4280 . ts - the TS context obtained from TSCreate() 4281 4282 Options Database: 4283 . -ts_adjoint_view_solution <viewerinfo> - views the first gradient with respect to the initial conditions 4284 4285 Level: intermediate 4286 4287 Notes: 4288 This must be called after a call to TSSolve() that solves the forward problem 4289 4290 By default this will integrate back to the initial time, one can use TSAdjointSetSteps() to step back to a later time 4291 4292 .keywords: TS, timestep, solve 4293 4294 .seealso: TSCreate(), TSSetCostGradients(), TSSetSolution(), TSAdjointStep() 4295 @*/ 4296 PetscErrorCode TSAdjointSolve(TS ts) 4297 { 4298 PetscErrorCode ierr; 4299 4300 PetscFunctionBegin; 4301 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4302 ierr = TSAdjointSetUp(ts);CHKERRQ(ierr); 4303 4304 /* reset time step and iteration counters */ 4305 ts->steps = 0; 4306 ts->ksp_its = 0; 4307 ts->snes_its = 0; 4308 ts->num_snes_failures = 0; 4309 ts->reject = 0; 4310 ts->reason = TS_CONVERGED_ITERATING; 4311 4312 if (!ts->adjoint_max_steps) ts->adjoint_max_steps = ts->total_steps; 4313 4314 if (ts->steps >= ts->adjoint_max_steps) ts->reason = TS_CONVERGED_ITS; 4315 while (!ts->reason) { 4316 ierr = TSTrajectoryGet(ts->trajectory,ts,ts->total_steps,&ts->ptime);CHKERRQ(ierr); 4317 ierr = TSAdjointMonitor(ts,ts->total_steps,ts->ptime,ts->vec_sol,ts->numcost,ts->vecs_sensi,ts->vecs_sensip);CHKERRQ(ierr); 4318 ierr = TSAdjointEventHandler(ts);CHKERRQ(ierr); 4319 ierr = TSAdjointStep(ts);CHKERRQ(ierr); 4320 if (ts->vec_costintegral && !ts->costintegralfwd) { 4321 ierr = TSAdjointCostIntegral(ts);CHKERRQ(ierr); 4322 } 4323 } 4324 ierr = TSTrajectoryGet(ts->trajectory,ts,ts->total_steps,&ts->ptime);CHKERRQ(ierr); 4325 ierr = TSAdjointMonitor(ts,ts->total_steps,ts->ptime,ts->vec_sol,ts->numcost,ts->vecs_sensi,ts->vecs_sensip);CHKERRQ(ierr); 4326 ts->solvetime = ts->ptime; 4327 ierr = TSTrajectoryViewFromOptions(ts->trajectory,NULL,"-ts_trajectory_view");CHKERRQ(ierr); 4328 ierr = VecViewFromOptions(ts->vecs_sensi[0],(PetscObject) ts, "-ts_adjoint_view_solution");CHKERRQ(ierr); 4329 PetscFunctionReturn(0); 4330 } 4331 4332 #undef __FUNCT__ 4333 #define __FUNCT__ "TSMonitor" 4334 /*@C 4335 TSMonitor - Runs all user-provided monitor routines set using TSMonitorSet() 4336 4337 Collective on TS 4338 4339 Input Parameters: 4340 + ts - time stepping context obtained from TSCreate() 4341 . step - step number that has just completed 4342 . ptime - model time of the state 4343 - u - state at the current model time 4344 4345 Notes: 4346 TSMonitor() is typically used automatically within the time stepping implementations. 4347 Users would almost never call this routine directly. 4348 4349 A step of -1 indicates that the monitor is being called on a solution obtained by interpolating from computed solutions 4350 4351 Level: developer 4352 4353 .keywords: TS, timestep 4354 @*/ 4355 PetscErrorCode TSMonitor(TS ts,PetscInt step,PetscReal ptime,Vec u) 4356 { 4357 DM dm; 4358 PetscInt i,n = ts->numbermonitors; 4359 PetscErrorCode ierr; 4360 4361 PetscFunctionBegin; 4362 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4363 PetscValidHeaderSpecific(u,VEC_CLASSID,4); 4364 4365 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 4366 ierr = DMSetOutputSequenceNumber(dm,step,ptime);CHKERRQ(ierr); 4367 4368 ierr = VecLockPush(u);CHKERRQ(ierr); 4369 for (i=0; i<n; i++) { 4370 ierr = (*ts->monitor[i])(ts,step,ptime,u,ts->monitorcontext[i]);CHKERRQ(ierr); 4371 } 4372 ierr = VecLockPop(u);CHKERRQ(ierr); 4373 PetscFunctionReturn(0); 4374 } 4375 4376 #undef __FUNCT__ 4377 #define __FUNCT__ "TSAdjointMonitor" 4378 /*@C 4379 TSAdjointMonitor - Runs all user-provided adjoint monitor routines set using TSAdjointMonitorSet() 4380 4381 Collective on TS 4382 4383 Input Parameters: 4384 + ts - time stepping context obtained from TSCreate() 4385 . step - step number that has just completed 4386 . ptime - model time of the state 4387 . u - state at the current model time 4388 . numcost - number of cost functions (dimension of lambda or mu) 4389 . lambda - vectors containing the gradients of the cost functions with respect to the ODE/DAE solution variables 4390 - mu - vectors containing the gradients of the cost functions with respect to the problem parameters 4391 4392 Notes: 4393 TSAdjointMonitor() is typically used automatically within the time stepping implementations. 4394 Users would almost never call this routine directly. 4395 4396 Level: developer 4397 4398 .keywords: TS, timestep 4399 @*/ 4400 PetscErrorCode TSAdjointMonitor(TS ts,PetscInt step,PetscReal ptime,Vec u,PetscInt numcost,Vec *lambda, Vec *mu) 4401 { 4402 PetscErrorCode ierr; 4403 PetscInt i,n = ts->numberadjointmonitors; 4404 4405 PetscFunctionBegin; 4406 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4407 PetscValidHeaderSpecific(u,VEC_CLASSID,4); 4408 ierr = VecLockPush(u);CHKERRQ(ierr); 4409 for (i=0; i<n; i++) { 4410 ierr = (*ts->adjointmonitor[i])(ts,step,ptime,u,numcost,lambda,mu,ts->adjointmonitorcontext[i]);CHKERRQ(ierr); 4411 } 4412 ierr = VecLockPop(u);CHKERRQ(ierr); 4413 PetscFunctionReturn(0); 4414 } 4415 4416 /* ------------------------------------------------------------------------*/ 4417 #undef __FUNCT__ 4418 #define __FUNCT__ "TSMonitorLGCtxCreate" 4419 /*@C 4420 TSMonitorLGCtxCreate - Creates a TSMonitorLGCtx context for use with 4421 TS to monitor the solution process graphically in various ways 4422 4423 Collective on TS 4424 4425 Input Parameters: 4426 + host - the X display to open, or null for the local machine 4427 . label - the title to put in the title bar 4428 . x, y - the screen coordinates of the upper left coordinate of the window 4429 . m, n - the screen width and height in pixels 4430 - howoften - if positive then determines the frequency of the plotting, if -1 then only at the final time 4431 4432 Output Parameter: 4433 . ctx - the context 4434 4435 Options Database Key: 4436 + -ts_monitor_lg_timestep - automatically sets line graph monitor 4437 . -ts_monitor_lg_solution - monitor the solution (or certain values of the solution by calling TSMonitorLGSetDisplayVariables() or TSMonitorLGCtxSetDisplayVariables()) 4438 . -ts_monitor_lg_error - monitor the error 4439 . -ts_monitor_lg_ksp_iterations - monitor the number of KSP iterations needed for each timestep 4440 . -ts_monitor_lg_snes_iterations - monitor the number of SNES iterations needed for each timestep 4441 - -lg_use_markers <true,false> - mark the data points (at each time step) on the plot; default is true 4442 4443 Notes: 4444 Use TSMonitorLGCtxDestroy() to destroy. 4445 4446 One can provide a function that transforms the solution before plotting it with TSMonitorLGCtxSetTransform() or TSMonitorLGSetTransform() 4447 4448 Many of the functions that control the monitoring have two forms: TSMonitorLGSet/GetXXXX() and TSMonitorLGCtxSet/GetXXXX() the first take a TS object as the 4449 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 4450 as the first argument. 4451 4452 One can control the names displayed for each solution or error variable with TSMonitorLGCtxSetVariableNames() or TSMonitorLGSetVariableNames() 4453 4454 4455 Level: intermediate 4456 4457 .keywords: TS, monitor, line graph, residual 4458 4459 .seealso: TSMonitorLGTimeStep(), TSMonitorSet(), TSMonitorLGSolution(), TSMonitorLGError(), TSMonitorDefault(), VecView(), 4460 TSMonitorLGCtxCreate(), TSMonitorLGCtxSetVariableNames(), TSMonitorLGCtxGetVariableNames(), 4461 TSMonitorLGSetVariableNames(), TSMonitorLGGetVariableNames(), TSMonitorLGSetDisplayVariables(), TSMonitorLGCtxSetDisplayVariables(), 4462 TSMonitorLGCtxSetTransform(), TSMonitorLGSetTransform(), TSMonitorLGError(), TSMonitorLGSNESIterations(), TSMonitorLGKSPIterations(), 4463 TSMonitorEnvelopeCtxCreate(), TSMonitorEnvelopeGetBounds(), TSMonitorEnvelopeCtxDestroy(), TSMonitorEnvelop() 4464 4465 @*/ 4466 PetscErrorCode TSMonitorLGCtxCreate(MPI_Comm comm,const char host[],const char label[],int x,int y,int m,int n,PetscInt howoften,TSMonitorLGCtx *ctx) 4467 { 4468 PetscDraw draw; 4469 PetscErrorCode ierr; 4470 4471 PetscFunctionBegin; 4472 ierr = PetscNew(ctx);CHKERRQ(ierr); 4473 ierr = PetscDrawCreate(comm,host,label,x,y,m,n,&draw);CHKERRQ(ierr); 4474 ierr = PetscDrawSetFromOptions(draw);CHKERRQ(ierr); 4475 ierr = PetscDrawLGCreate(draw,1,&(*ctx)->lg);CHKERRQ(ierr); 4476 ierr = PetscDrawLGSetFromOptions((*ctx)->lg);CHKERRQ(ierr); 4477 ierr = PetscDrawDestroy(&draw);CHKERRQ(ierr); 4478 (*ctx)->howoften = howoften; 4479 PetscFunctionReturn(0); 4480 } 4481 4482 #undef __FUNCT__ 4483 #define __FUNCT__ "TSMonitorLGTimeStep" 4484 PetscErrorCode TSMonitorLGTimeStep(TS ts,PetscInt step,PetscReal ptime,Vec v,void *monctx) 4485 { 4486 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 4487 PetscReal x = ptime,y; 4488 PetscErrorCode ierr; 4489 4490 PetscFunctionBegin; 4491 if (step < 0) PetscFunctionReturn(0); /* -1 indicates an interpolated solution */ 4492 if (!step) { 4493 PetscDrawAxis axis; 4494 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 4495 ierr = PetscDrawAxisSetLabels(axis,"Timestep as function of time","Time","Time Step");CHKERRQ(ierr); 4496 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 4497 } 4498 ierr = TSGetTimeStep(ts,&y);CHKERRQ(ierr); 4499 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 4500 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 4501 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 4502 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 4503 } 4504 PetscFunctionReturn(0); 4505 } 4506 4507 #undef __FUNCT__ 4508 #define __FUNCT__ "TSMonitorLGCtxDestroy" 4509 /*@C 4510 TSMonitorLGCtxDestroy - Destroys a line graph context that was created 4511 with TSMonitorLGCtxCreate(). 4512 4513 Collective on TSMonitorLGCtx 4514 4515 Input Parameter: 4516 . ctx - the monitor context 4517 4518 Level: intermediate 4519 4520 .keywords: TS, monitor, line graph, destroy 4521 4522 .seealso: TSMonitorLGCtxCreate(), TSMonitorSet(), TSMonitorLGTimeStep(); 4523 @*/ 4524 PetscErrorCode TSMonitorLGCtxDestroy(TSMonitorLGCtx *ctx) 4525 { 4526 PetscErrorCode ierr; 4527 4528 PetscFunctionBegin; 4529 if ((*ctx)->transformdestroy) { 4530 ierr = ((*ctx)->transformdestroy)((*ctx)->transformctx);CHKERRQ(ierr); 4531 } 4532 ierr = PetscDrawLGDestroy(&(*ctx)->lg);CHKERRQ(ierr); 4533 ierr = PetscStrArrayDestroy(&(*ctx)->names);CHKERRQ(ierr); 4534 ierr = PetscStrArrayDestroy(&(*ctx)->displaynames);CHKERRQ(ierr); 4535 ierr = PetscFree((*ctx)->displayvariables);CHKERRQ(ierr); 4536 ierr = PetscFree((*ctx)->displayvalues);CHKERRQ(ierr); 4537 ierr = PetscFree(*ctx);CHKERRQ(ierr); 4538 PetscFunctionReturn(0); 4539 } 4540 4541 #undef __FUNCT__ 4542 #define __FUNCT__ "TSGetTime" 4543 /*@ 4544 TSGetTime - Gets the time of the most recently completed step. 4545 4546 Not Collective 4547 4548 Input Parameter: 4549 . ts - the TS context obtained from TSCreate() 4550 4551 Output Parameter: 4552 . t - the current time. This time may not corresponds to the final time set with TSSetDuration(), use TSGetSolveTime(). 4553 4554 Level: beginner 4555 4556 Note: 4557 When called during time step evaluation (e.g. during residual evaluation or via hooks set using TSSetPreStep(), 4558 TSSetPreStage(), TSSetPostStage(), or TSSetPostStep()), the time is the time at the start of the step being evaluated. 4559 4560 .seealso: TSSetInitialTimeStep(), TSGetTimeStep(), TSGetSolveTime() 4561 4562 .keywords: TS, get, time 4563 @*/ 4564 PetscErrorCode TSGetTime(TS ts,PetscReal *t) 4565 { 4566 PetscFunctionBegin; 4567 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4568 PetscValidRealPointer(t,2); 4569 *t = ts->ptime; 4570 PetscFunctionReturn(0); 4571 } 4572 4573 #undef __FUNCT__ 4574 #define __FUNCT__ "TSGetPrevTime" 4575 /*@ 4576 TSGetPrevTime - Gets the starting time of the previously completed step. 4577 4578 Not Collective 4579 4580 Input Parameter: 4581 . ts - the TS context obtained from TSCreate() 4582 4583 Output Parameter: 4584 . t - the previous time 4585 4586 Level: beginner 4587 4588 .seealso: TSSetInitialTimeStep(), TSGetTimeStep() 4589 4590 .keywords: TS, get, time 4591 @*/ 4592 PetscErrorCode TSGetPrevTime(TS ts,PetscReal *t) 4593 { 4594 PetscFunctionBegin; 4595 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4596 PetscValidRealPointer(t,2); 4597 *t = ts->ptime_prev; 4598 PetscFunctionReturn(0); 4599 } 4600 4601 #undef __FUNCT__ 4602 #define __FUNCT__ "TSSetTime" 4603 /*@ 4604 TSSetTime - Allows one to reset the time. 4605 4606 Logically Collective on TS 4607 4608 Input Parameters: 4609 + ts - the TS context obtained from TSCreate() 4610 - time - the time 4611 4612 Level: intermediate 4613 4614 .seealso: TSGetTime(), TSSetDuration() 4615 4616 .keywords: TS, set, time 4617 @*/ 4618 PetscErrorCode TSSetTime(TS ts, PetscReal t) 4619 { 4620 PetscFunctionBegin; 4621 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4622 PetscValidLogicalCollectiveReal(ts,t,2); 4623 ts->ptime = t; 4624 PetscFunctionReturn(0); 4625 } 4626 4627 #undef __FUNCT__ 4628 #define __FUNCT__ "TSSetOptionsPrefix" 4629 /*@C 4630 TSSetOptionsPrefix - Sets the prefix used for searching for all 4631 TS options in the database. 4632 4633 Logically Collective on TS 4634 4635 Input Parameter: 4636 + ts - The TS context 4637 - prefix - The prefix to prepend to all option names 4638 4639 Notes: 4640 A hyphen (-) must NOT be given at the beginning of the prefix name. 4641 The first character of all runtime options is AUTOMATICALLY the 4642 hyphen. 4643 4644 Level: advanced 4645 4646 .keywords: TS, set, options, prefix, database 4647 4648 .seealso: TSSetFromOptions() 4649 4650 @*/ 4651 PetscErrorCode TSSetOptionsPrefix(TS ts,const char prefix[]) 4652 { 4653 PetscErrorCode ierr; 4654 SNES snes; 4655 4656 PetscFunctionBegin; 4657 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4658 ierr = PetscObjectSetOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 4659 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4660 ierr = SNESSetOptionsPrefix(snes,prefix);CHKERRQ(ierr); 4661 PetscFunctionReturn(0); 4662 } 4663 4664 4665 #undef __FUNCT__ 4666 #define __FUNCT__ "TSAppendOptionsPrefix" 4667 /*@C 4668 TSAppendOptionsPrefix - Appends to the prefix used for searching for all 4669 TS options in the database. 4670 4671 Logically Collective on TS 4672 4673 Input Parameter: 4674 + ts - The TS context 4675 - prefix - The prefix to prepend to all option names 4676 4677 Notes: 4678 A hyphen (-) must NOT be given at the beginning of the prefix name. 4679 The first character of all runtime options is AUTOMATICALLY the 4680 hyphen. 4681 4682 Level: advanced 4683 4684 .keywords: TS, append, options, prefix, database 4685 4686 .seealso: TSGetOptionsPrefix() 4687 4688 @*/ 4689 PetscErrorCode TSAppendOptionsPrefix(TS ts,const char prefix[]) 4690 { 4691 PetscErrorCode ierr; 4692 SNES snes; 4693 4694 PetscFunctionBegin; 4695 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4696 ierr = PetscObjectAppendOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 4697 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4698 ierr = SNESAppendOptionsPrefix(snes,prefix);CHKERRQ(ierr); 4699 PetscFunctionReturn(0); 4700 } 4701 4702 #undef __FUNCT__ 4703 #define __FUNCT__ "TSGetOptionsPrefix" 4704 /*@C 4705 TSGetOptionsPrefix - Sets the prefix used for searching for all 4706 TS options in the database. 4707 4708 Not Collective 4709 4710 Input Parameter: 4711 . ts - The TS context 4712 4713 Output Parameter: 4714 . prefix - A pointer to the prefix string used 4715 4716 Notes: On the fortran side, the user should pass in a string 'prifix' of 4717 sufficient length to hold the prefix. 4718 4719 Level: intermediate 4720 4721 .keywords: TS, get, options, prefix, database 4722 4723 .seealso: TSAppendOptionsPrefix() 4724 @*/ 4725 PetscErrorCode TSGetOptionsPrefix(TS ts,const char *prefix[]) 4726 { 4727 PetscErrorCode ierr; 4728 4729 PetscFunctionBegin; 4730 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4731 PetscValidPointer(prefix,2); 4732 ierr = PetscObjectGetOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 4733 PetscFunctionReturn(0); 4734 } 4735 4736 #undef __FUNCT__ 4737 #define __FUNCT__ "TSGetRHSJacobian" 4738 /*@C 4739 TSGetRHSJacobian - Returns the Jacobian J at the present timestep. 4740 4741 Not Collective, but parallel objects are returned if TS is parallel 4742 4743 Input Parameter: 4744 . ts - The TS context obtained from TSCreate() 4745 4746 Output Parameters: 4747 + Amat - The (approximate) Jacobian J of G, where U_t = G(U,t) (or NULL) 4748 . Pmat - The matrix from which the preconditioner is constructed, usually the same as Amat (or NULL) 4749 . func - Function to compute the Jacobian of the RHS (or NULL) 4750 - ctx - User-defined context for Jacobian evaluation routine (or NULL) 4751 4752 Notes: You can pass in NULL for any return argument you do not need. 4753 4754 Level: intermediate 4755 4756 .seealso: TSGetTimeStep(), TSGetMatrices(), TSGetTime(), TSGetTimeStepNumber() 4757 4758 .keywords: TS, timestep, get, matrix, Jacobian 4759 @*/ 4760 PetscErrorCode TSGetRHSJacobian(TS ts,Mat *Amat,Mat *Pmat,TSRHSJacobian *func,void **ctx) 4761 { 4762 PetscErrorCode ierr; 4763 SNES snes; 4764 DM dm; 4765 4766 PetscFunctionBegin; 4767 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4768 ierr = SNESGetJacobian(snes,Amat,Pmat,NULL,NULL);CHKERRQ(ierr); 4769 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 4770 ierr = DMTSGetRHSJacobian(dm,func,ctx);CHKERRQ(ierr); 4771 PetscFunctionReturn(0); 4772 } 4773 4774 #undef __FUNCT__ 4775 #define __FUNCT__ "TSGetIJacobian" 4776 /*@C 4777 TSGetIJacobian - Returns the implicit Jacobian at the present timestep. 4778 4779 Not Collective, but parallel objects are returned if TS is parallel 4780 4781 Input Parameter: 4782 . ts - The TS context obtained from TSCreate() 4783 4784 Output Parameters: 4785 + Amat - The (approximate) Jacobian of F(t,U,U_t) 4786 . Pmat - The matrix from which the preconditioner is constructed, often the same as Amat 4787 . f - The function to compute the matrices 4788 - ctx - User-defined context for Jacobian evaluation routine 4789 4790 Notes: You can pass in NULL for any return argument you do not need. 4791 4792 Level: advanced 4793 4794 .seealso: TSGetTimeStep(), TSGetRHSJacobian(), TSGetMatrices(), TSGetTime(), TSGetTimeStepNumber() 4795 4796 .keywords: TS, timestep, get, matrix, Jacobian 4797 @*/ 4798 PetscErrorCode TSGetIJacobian(TS ts,Mat *Amat,Mat *Pmat,TSIJacobian *f,void **ctx) 4799 { 4800 PetscErrorCode ierr; 4801 SNES snes; 4802 DM dm; 4803 4804 PetscFunctionBegin; 4805 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4806 ierr = SNESSetUpMatrices(snes);CHKERRQ(ierr); 4807 ierr = SNESGetJacobian(snes,Amat,Pmat,NULL,NULL);CHKERRQ(ierr); 4808 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 4809 ierr = DMTSGetIJacobian(dm,f,ctx);CHKERRQ(ierr); 4810 PetscFunctionReturn(0); 4811 } 4812 4813 4814 #undef __FUNCT__ 4815 #define __FUNCT__ "TSMonitorDrawSolution" 4816 /*@C 4817 TSMonitorDrawSolution - Monitors progress of the TS solvers by calling 4818 VecView() for the solution at each timestep 4819 4820 Collective on TS 4821 4822 Input Parameters: 4823 + ts - the TS context 4824 . step - current time-step 4825 . ptime - current time 4826 - dummy - either a viewer or NULL 4827 4828 Options Database: 4829 . -ts_monitor_draw_solution_initial - show initial solution as well as current solution 4830 4831 Notes: the initial solution and current solution are not display with a common axis scaling so generally the option -ts_monitor_draw_solution_initial 4832 will look bad 4833 4834 Level: intermediate 4835 4836 .keywords: TS, vector, monitor, view 4837 4838 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 4839 @*/ 4840 PetscErrorCode TSMonitorDrawSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 4841 { 4842 PetscErrorCode ierr; 4843 TSMonitorDrawCtx ictx = (TSMonitorDrawCtx)dummy; 4844 PetscDraw draw; 4845 4846 PetscFunctionBegin; 4847 if (!step && ictx->showinitial) { 4848 if (!ictx->initialsolution) { 4849 ierr = VecDuplicate(u,&ictx->initialsolution);CHKERRQ(ierr); 4850 } 4851 ierr = VecCopy(u,ictx->initialsolution);CHKERRQ(ierr); 4852 } 4853 if (!(((ictx->howoften > 0) && (!(step % ictx->howoften))) || ((ictx->howoften == -1) && ts->reason))) PetscFunctionReturn(0); 4854 4855 if (ictx->showinitial) { 4856 PetscReal pause; 4857 ierr = PetscViewerDrawGetPause(ictx->viewer,&pause);CHKERRQ(ierr); 4858 ierr = PetscViewerDrawSetPause(ictx->viewer,0.0);CHKERRQ(ierr); 4859 ierr = VecView(ictx->initialsolution,ictx->viewer);CHKERRQ(ierr); 4860 ierr = PetscViewerDrawSetPause(ictx->viewer,pause);CHKERRQ(ierr); 4861 ierr = PetscViewerDrawSetHold(ictx->viewer,PETSC_TRUE);CHKERRQ(ierr); 4862 } 4863 ierr = VecView(u,ictx->viewer);CHKERRQ(ierr); 4864 if (ictx->showtimestepandtime) { 4865 PetscReal xl,yl,xr,yr,h; 4866 char time[32]; 4867 4868 ierr = PetscViewerDrawGetDraw(ictx->viewer,0,&draw);CHKERRQ(ierr); 4869 ierr = PetscSNPrintf(time,32,"Timestep %d Time %g",(int)step,(double)ptime);CHKERRQ(ierr); 4870 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 4871 h = yl + .95*(yr - yl); 4872 ierr = PetscDrawStringCentered(draw,.5*(xl+xr),h,PETSC_DRAW_BLACK,time);CHKERRQ(ierr); 4873 ierr = PetscDrawFlush(draw);CHKERRQ(ierr); 4874 } 4875 4876 if (ictx->showinitial) { 4877 ierr = PetscViewerDrawSetHold(ictx->viewer,PETSC_FALSE);CHKERRQ(ierr); 4878 } 4879 PetscFunctionReturn(0); 4880 } 4881 4882 #undef __FUNCT__ 4883 #define __FUNCT__ "TSAdjointMonitorDrawSensi" 4884 /*@C 4885 TSAdjointMonitorDrawSensi - Monitors progress of the adjoint TS solvers by calling 4886 VecView() for the sensitivities to initial states at each timestep 4887 4888 Collective on TS 4889 4890 Input Parameters: 4891 + ts - the TS context 4892 . step - current time-step 4893 . ptime - current time 4894 . u - current state 4895 . numcost - number of cost functions 4896 . lambda - sensitivities to initial conditions 4897 . mu - sensitivities to parameters 4898 - dummy - either a viewer or NULL 4899 4900 Level: intermediate 4901 4902 .keywords: TS, vector, adjoint, monitor, view 4903 4904 .seealso: TSAdjointMonitorSet(), TSAdjointMonitorDefault(), VecView() 4905 @*/ 4906 PetscErrorCode TSAdjointMonitorDrawSensi(TS ts,PetscInt step,PetscReal ptime,Vec u,PetscInt numcost,Vec *lambda,Vec *mu,void *dummy) 4907 { 4908 PetscErrorCode ierr; 4909 TSMonitorDrawCtx ictx = (TSMonitorDrawCtx)dummy; 4910 PetscDraw draw; 4911 PetscReal xl,yl,xr,yr,h; 4912 char time[32]; 4913 4914 PetscFunctionBegin; 4915 if (!(((ictx->howoften > 0) && (!(step % ictx->howoften))) || ((ictx->howoften == -1) && ts->reason))) PetscFunctionReturn(0); 4916 4917 ierr = VecView(lambda[0],ictx->viewer);CHKERRQ(ierr); 4918 ierr = PetscViewerDrawGetDraw(ictx->viewer,0,&draw);CHKERRQ(ierr); 4919 ierr = PetscSNPrintf(time,32,"Timestep %d Time %g",(int)step,(double)ptime);CHKERRQ(ierr); 4920 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 4921 h = yl + .95*(yr - yl); 4922 ierr = PetscDrawStringCentered(draw,.5*(xl+xr),h,PETSC_DRAW_BLACK,time);CHKERRQ(ierr); 4923 ierr = PetscDrawFlush(draw);CHKERRQ(ierr); 4924 PetscFunctionReturn(0); 4925 } 4926 4927 #undef __FUNCT__ 4928 #define __FUNCT__ "TSMonitorDrawSolutionPhase" 4929 /*@C 4930 TSMonitorDrawSolutionPhase - Monitors progress of the TS solvers by plotting the solution as a phase diagram 4931 4932 Collective on TS 4933 4934 Input Parameters: 4935 + ts - the TS context 4936 . step - current time-step 4937 . ptime - current time 4938 - dummy - either a viewer or NULL 4939 4940 Level: intermediate 4941 4942 .keywords: TS, vector, monitor, view 4943 4944 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 4945 @*/ 4946 PetscErrorCode TSMonitorDrawSolutionPhase(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 4947 { 4948 PetscErrorCode ierr; 4949 TSMonitorDrawCtx ictx = (TSMonitorDrawCtx)dummy; 4950 PetscDraw draw; 4951 PetscDrawAxis axis; 4952 PetscInt n; 4953 PetscMPIInt size; 4954 PetscReal U0,U1,xl,yl,xr,yr,h; 4955 char time[32]; 4956 const PetscScalar *U; 4957 4958 PetscFunctionBegin; 4959 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)ts),&size);CHKERRQ(ierr); 4960 if (size != 1) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Only allowed for sequential runs"); 4961 ierr = VecGetSize(u,&n);CHKERRQ(ierr); 4962 if (n != 2) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Only for ODEs with two unknowns"); 4963 4964 ierr = PetscViewerDrawGetDraw(ictx->viewer,0,&draw);CHKERRQ(ierr); 4965 ierr = PetscViewerDrawGetDrawAxis(ictx->viewer,0,&axis);CHKERRQ(ierr); 4966 ierr = PetscDrawAxisGetLimits(axis,&xl,&xr,&yl,&yr);CHKERRQ(ierr); 4967 if (!step) { 4968 ierr = PetscDrawClear(draw);CHKERRQ(ierr); 4969 ierr = PetscDrawAxisDraw(axis);CHKERRQ(ierr); 4970 } 4971 4972 ierr = VecGetArrayRead(u,&U);CHKERRQ(ierr); 4973 U0 = PetscRealPart(U[0]); 4974 U1 = PetscRealPart(U[1]); 4975 ierr = VecRestoreArrayRead(u,&U);CHKERRQ(ierr); 4976 if ((U0 < xl) || (U1 < yl) || (U0 > xr) || (U1 > yr)) PetscFunctionReturn(0); 4977 4978 ierr = PetscDrawCollectiveBegin(draw);CHKERRQ(ierr); 4979 ierr = PetscDrawPoint(draw,U0,U1,PETSC_DRAW_BLACK);CHKERRQ(ierr); 4980 if (ictx->showtimestepandtime) { 4981 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 4982 ierr = PetscSNPrintf(time,32,"Timestep %d Time %g",(int)step,(double)ptime);CHKERRQ(ierr); 4983 h = yl + .95*(yr - yl); 4984 ierr = PetscDrawStringCentered(draw,.5*(xl+xr),h,PETSC_DRAW_BLACK,time);CHKERRQ(ierr); 4985 } 4986 ierr = PetscDrawCollectiveEnd(draw);CHKERRQ(ierr); 4987 ierr = PetscDrawFlush(draw);CHKERRQ(ierr); 4988 ierr = PetscDrawSave(draw);CHKERRQ(ierr); 4989 PetscFunctionReturn(0); 4990 } 4991 4992 4993 #undef __FUNCT__ 4994 #define __FUNCT__ "TSMonitorDrawCtxDestroy" 4995 /*@C 4996 TSMonitorDrawCtxDestroy - Destroys the monitor context for TSMonitorDrawSolution() 4997 4998 Collective on TS 4999 5000 Input Parameters: 5001 . ctx - the monitor context 5002 5003 Level: intermediate 5004 5005 .keywords: TS, vector, monitor, view 5006 5007 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorDrawSolution(), TSMonitorDrawError() 5008 @*/ 5009 PetscErrorCode TSMonitorDrawCtxDestroy(TSMonitorDrawCtx *ictx) 5010 { 5011 PetscErrorCode ierr; 5012 5013 PetscFunctionBegin; 5014 ierr = PetscViewerDestroy(&(*ictx)->viewer);CHKERRQ(ierr); 5015 ierr = VecDestroy(&(*ictx)->initialsolution);CHKERRQ(ierr); 5016 ierr = PetscFree(*ictx);CHKERRQ(ierr); 5017 PetscFunctionReturn(0); 5018 } 5019 5020 #undef __FUNCT__ 5021 #define __FUNCT__ "TSMonitorDrawCtxCreate" 5022 /*@C 5023 TSMonitorDrawCtxCreate - Creates the monitor context for TSMonitorDrawCtx 5024 5025 Collective on TS 5026 5027 Input Parameter: 5028 . ts - time-step context 5029 5030 Output Patameter: 5031 . ctx - the monitor context 5032 5033 Options Database: 5034 . -ts_monitor_draw_solution_initial - show initial solution as well as current solution 5035 5036 Level: intermediate 5037 5038 .keywords: TS, vector, monitor, view 5039 5040 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorDrawCtx() 5041 @*/ 5042 PetscErrorCode TSMonitorDrawCtxCreate(MPI_Comm comm,const char host[],const char label[],int x,int y,int m,int n,PetscInt howoften,TSMonitorDrawCtx *ctx) 5043 { 5044 PetscErrorCode ierr; 5045 5046 PetscFunctionBegin; 5047 ierr = PetscNew(ctx);CHKERRQ(ierr); 5048 ierr = PetscViewerDrawOpen(comm,host,label,x,y,m,n,&(*ctx)->viewer);CHKERRQ(ierr); 5049 ierr = PetscViewerSetFromOptions((*ctx)->viewer);CHKERRQ(ierr); 5050 5051 (*ctx)->howoften = howoften; 5052 (*ctx)->showinitial = PETSC_FALSE; 5053 ierr = PetscOptionsGetBool(NULL,NULL,"-ts_monitor_draw_solution_initial",&(*ctx)->showinitial,NULL);CHKERRQ(ierr); 5054 5055 (*ctx)->showtimestepandtime = PETSC_FALSE; 5056 ierr = PetscOptionsGetBool(NULL,NULL,"-ts_monitor_draw_solution_show_time",&(*ctx)->showtimestepandtime,NULL);CHKERRQ(ierr); 5057 PetscFunctionReturn(0); 5058 } 5059 5060 #undef __FUNCT__ 5061 #define __FUNCT__ "TSMonitorDrawError" 5062 /*@C 5063 TSMonitorDrawError - Monitors progress of the TS solvers by calling 5064 VecView() for the error at each timestep 5065 5066 Collective on TS 5067 5068 Input Parameters: 5069 + ts - the TS context 5070 . step - current time-step 5071 . ptime - current time 5072 - dummy - either a viewer or NULL 5073 5074 Level: intermediate 5075 5076 .keywords: TS, vector, monitor, view 5077 5078 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 5079 @*/ 5080 PetscErrorCode TSMonitorDrawError(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 5081 { 5082 PetscErrorCode ierr; 5083 TSMonitorDrawCtx ctx = (TSMonitorDrawCtx)dummy; 5084 PetscViewer viewer = ctx->viewer; 5085 Vec work; 5086 5087 PetscFunctionBegin; 5088 if (!(((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason))) PetscFunctionReturn(0); 5089 ierr = VecDuplicate(u,&work);CHKERRQ(ierr); 5090 ierr = TSComputeSolutionFunction(ts,ptime,work);CHKERRQ(ierr); 5091 ierr = VecAXPY(work,-1.0,u);CHKERRQ(ierr); 5092 ierr = VecView(work,viewer);CHKERRQ(ierr); 5093 ierr = VecDestroy(&work);CHKERRQ(ierr); 5094 PetscFunctionReturn(0); 5095 } 5096 5097 #include <petsc/private/dmimpl.h> 5098 #undef __FUNCT__ 5099 #define __FUNCT__ "TSSetDM" 5100 /*@ 5101 TSSetDM - Sets the DM that may be used by some nonlinear solvers or preconditioners under the TS 5102 5103 Logically Collective on TS and DM 5104 5105 Input Parameters: 5106 + ts - the ODE integrator object 5107 - dm - the dm, cannot be NULL 5108 5109 Level: intermediate 5110 5111 5112 .seealso: TSGetDM(), SNESSetDM(), SNESGetDM() 5113 @*/ 5114 PetscErrorCode TSSetDM(TS ts,DM dm) 5115 { 5116 PetscErrorCode ierr; 5117 SNES snes; 5118 DMTS tsdm; 5119 5120 PetscFunctionBegin; 5121 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5122 PetscValidHeaderSpecific(dm,DM_CLASSID,2); 5123 ierr = PetscObjectReference((PetscObject)dm);CHKERRQ(ierr); 5124 if (ts->dm) { /* Move the DMTS context over to the new DM unless the new DM already has one */ 5125 if (ts->dm->dmts && !dm->dmts) { 5126 ierr = DMCopyDMTS(ts->dm,dm);CHKERRQ(ierr); 5127 ierr = DMGetDMTS(ts->dm,&tsdm);CHKERRQ(ierr); 5128 if (tsdm->originaldm == ts->dm) { /* Grant write privileges to the replacement DM */ 5129 tsdm->originaldm = dm; 5130 } 5131 } 5132 ierr = DMDestroy(&ts->dm);CHKERRQ(ierr); 5133 } 5134 ts->dm = dm; 5135 5136 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 5137 ierr = SNESSetDM(snes,dm);CHKERRQ(ierr); 5138 PetscFunctionReturn(0); 5139 } 5140 5141 #undef __FUNCT__ 5142 #define __FUNCT__ "TSGetDM" 5143 /*@ 5144 TSGetDM - Gets the DM that may be used by some preconditioners 5145 5146 Not Collective 5147 5148 Input Parameter: 5149 . ts - the preconditioner context 5150 5151 Output Parameter: 5152 . dm - the dm 5153 5154 Level: intermediate 5155 5156 5157 .seealso: TSSetDM(), SNESSetDM(), SNESGetDM() 5158 @*/ 5159 PetscErrorCode TSGetDM(TS ts,DM *dm) 5160 { 5161 PetscErrorCode ierr; 5162 5163 PetscFunctionBegin; 5164 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5165 if (!ts->dm) { 5166 ierr = DMShellCreate(PetscObjectComm((PetscObject)ts),&ts->dm);CHKERRQ(ierr); 5167 if (ts->snes) {ierr = SNESSetDM(ts->snes,ts->dm);CHKERRQ(ierr);} 5168 } 5169 *dm = ts->dm; 5170 PetscFunctionReturn(0); 5171 } 5172 5173 #undef __FUNCT__ 5174 #define __FUNCT__ "SNESTSFormFunction" 5175 /*@ 5176 SNESTSFormFunction - Function to evaluate nonlinear residual 5177 5178 Logically Collective on SNES 5179 5180 Input Parameter: 5181 + snes - nonlinear solver 5182 . U - the current state at which to evaluate the residual 5183 - ctx - user context, must be a TS 5184 5185 Output Parameter: 5186 . F - the nonlinear residual 5187 5188 Notes: 5189 This function is not normally called by users and is automatically registered with the SNES used by TS. 5190 It is most frequently passed to MatFDColoringSetFunction(). 5191 5192 Level: advanced 5193 5194 .seealso: SNESSetFunction(), MatFDColoringSetFunction() 5195 @*/ 5196 PetscErrorCode SNESTSFormFunction(SNES snes,Vec U,Vec F,void *ctx) 5197 { 5198 TS ts = (TS)ctx; 5199 PetscErrorCode ierr; 5200 5201 PetscFunctionBegin; 5202 PetscValidHeaderSpecific(snes,SNES_CLASSID,1); 5203 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 5204 PetscValidHeaderSpecific(F,VEC_CLASSID,3); 5205 PetscValidHeaderSpecific(ts,TS_CLASSID,4); 5206 ierr = (ts->ops->snesfunction)(snes,U,F,ts);CHKERRQ(ierr); 5207 PetscFunctionReturn(0); 5208 } 5209 5210 #undef __FUNCT__ 5211 #define __FUNCT__ "SNESTSFormJacobian" 5212 /*@ 5213 SNESTSFormJacobian - Function to evaluate the Jacobian 5214 5215 Collective on SNES 5216 5217 Input Parameter: 5218 + snes - nonlinear solver 5219 . U - the current state at which to evaluate the residual 5220 - ctx - user context, must be a TS 5221 5222 Output Parameter: 5223 + A - the Jacobian 5224 . B - the preconditioning matrix (may be the same as A) 5225 - flag - indicates any structure change in the matrix 5226 5227 Notes: 5228 This function is not normally called by users and is automatically registered with the SNES used by TS. 5229 5230 Level: developer 5231 5232 .seealso: SNESSetJacobian() 5233 @*/ 5234 PetscErrorCode SNESTSFormJacobian(SNES snes,Vec U,Mat A,Mat B,void *ctx) 5235 { 5236 TS ts = (TS)ctx; 5237 PetscErrorCode ierr; 5238 5239 PetscFunctionBegin; 5240 PetscValidHeaderSpecific(snes,SNES_CLASSID,1); 5241 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 5242 PetscValidPointer(A,3); 5243 PetscValidHeaderSpecific(A,MAT_CLASSID,3); 5244 PetscValidPointer(B,4); 5245 PetscValidHeaderSpecific(B,MAT_CLASSID,4); 5246 PetscValidHeaderSpecific(ts,TS_CLASSID,6); 5247 ierr = (ts->ops->snesjacobian)(snes,U,A,B,ts);CHKERRQ(ierr); 5248 PetscFunctionReturn(0); 5249 } 5250 5251 #undef __FUNCT__ 5252 #define __FUNCT__ "TSComputeRHSFunctionLinear" 5253 /*@C 5254 TSComputeRHSFunctionLinear - Evaluate the right hand side via the user-provided Jacobian, for linear problems Udot = A U only 5255 5256 Collective on TS 5257 5258 Input Arguments: 5259 + ts - time stepping context 5260 . t - time at which to evaluate 5261 . U - state at which to evaluate 5262 - ctx - context 5263 5264 Output Arguments: 5265 . F - right hand side 5266 5267 Level: intermediate 5268 5269 Notes: 5270 This function is intended to be passed to TSSetRHSFunction() to evaluate the right hand side for linear problems. 5271 The matrix (and optionally the evaluation context) should be passed to TSSetRHSJacobian(). 5272 5273 .seealso: TSSetRHSFunction(), TSSetRHSJacobian(), TSComputeRHSJacobianConstant() 5274 @*/ 5275 PetscErrorCode TSComputeRHSFunctionLinear(TS ts,PetscReal t,Vec U,Vec F,void *ctx) 5276 { 5277 PetscErrorCode ierr; 5278 Mat Arhs,Brhs; 5279 5280 PetscFunctionBegin; 5281 ierr = TSGetRHSMats_Private(ts,&Arhs,&Brhs);CHKERRQ(ierr); 5282 ierr = TSComputeRHSJacobian(ts,t,U,Arhs,Brhs);CHKERRQ(ierr); 5283 ierr = MatMult(Arhs,U,F);CHKERRQ(ierr); 5284 PetscFunctionReturn(0); 5285 } 5286 5287 #undef __FUNCT__ 5288 #define __FUNCT__ "TSComputeRHSJacobianConstant" 5289 /*@C 5290 TSComputeRHSJacobianConstant - Reuses a Jacobian that is time-independent. 5291 5292 Collective on TS 5293 5294 Input Arguments: 5295 + ts - time stepping context 5296 . t - time at which to evaluate 5297 . U - state at which to evaluate 5298 - ctx - context 5299 5300 Output Arguments: 5301 + A - pointer to operator 5302 . B - pointer to preconditioning matrix 5303 - flg - matrix structure flag 5304 5305 Level: intermediate 5306 5307 Notes: 5308 This function is intended to be passed to TSSetRHSJacobian() to evaluate the Jacobian for linear time-independent problems. 5309 5310 .seealso: TSSetRHSFunction(), TSSetRHSJacobian(), TSComputeRHSFunctionLinear() 5311 @*/ 5312 PetscErrorCode TSComputeRHSJacobianConstant(TS ts,PetscReal t,Vec U,Mat A,Mat B,void *ctx) 5313 { 5314 PetscFunctionBegin; 5315 PetscFunctionReturn(0); 5316 } 5317 5318 #undef __FUNCT__ 5319 #define __FUNCT__ "TSComputeIFunctionLinear" 5320 /*@C 5321 TSComputeIFunctionLinear - Evaluate the left hand side via the user-provided Jacobian, for linear problems only 5322 5323 Collective on TS 5324 5325 Input Arguments: 5326 + ts - time stepping context 5327 . t - time at which to evaluate 5328 . U - state at which to evaluate 5329 . Udot - time derivative of state vector 5330 - ctx - context 5331 5332 Output Arguments: 5333 . F - left hand side 5334 5335 Level: intermediate 5336 5337 Notes: 5338 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 5339 user is required to write their own TSComputeIFunction. 5340 This function is intended to be passed to TSSetIFunction() to evaluate the left hand side for linear problems. 5341 The matrix (and optionally the evaluation context) should be passed to TSSetIJacobian(). 5342 5343 Note that using this function is NOT equivalent to using TSComputeRHSFunctionLinear() since that solves Udot = A U 5344 5345 .seealso: TSSetIFunction(), TSSetIJacobian(), TSComputeIJacobianConstant(), TSComputeRHSFunctionLinear() 5346 @*/ 5347 PetscErrorCode TSComputeIFunctionLinear(TS ts,PetscReal t,Vec U,Vec Udot,Vec F,void *ctx) 5348 { 5349 PetscErrorCode ierr; 5350 Mat A,B; 5351 5352 PetscFunctionBegin; 5353 ierr = TSGetIJacobian(ts,&A,&B,NULL,NULL);CHKERRQ(ierr); 5354 ierr = TSComputeIJacobian(ts,t,U,Udot,1.0,A,B,PETSC_TRUE);CHKERRQ(ierr); 5355 ierr = MatMult(A,Udot,F);CHKERRQ(ierr); 5356 PetscFunctionReturn(0); 5357 } 5358 5359 #undef __FUNCT__ 5360 #define __FUNCT__ "TSComputeIJacobianConstant" 5361 /*@C 5362 TSComputeIJacobianConstant - Reuses a time-independent for a semi-implicit DAE or ODE 5363 5364 Collective on TS 5365 5366 Input Arguments: 5367 + ts - time stepping context 5368 . t - time at which to evaluate 5369 . U - state at which to evaluate 5370 . Udot - time derivative of state vector 5371 . shift - shift to apply 5372 - ctx - context 5373 5374 Output Arguments: 5375 + A - pointer to operator 5376 . B - pointer to preconditioning matrix 5377 - flg - matrix structure flag 5378 5379 Level: advanced 5380 5381 Notes: 5382 This function is intended to be passed to TSSetIJacobian() to evaluate the Jacobian for linear time-independent problems. 5383 5384 It is only appropriate for problems of the form 5385 5386 $ M Udot = F(U,t) 5387 5388 where M is constant and F is non-stiff. The user must pass M to TSSetIJacobian(). The current implementation only 5389 works with IMEX time integration methods such as TSROSW and TSARKIMEX, since there is no support for de-constructing 5390 an implicit operator of the form 5391 5392 $ shift*M + J 5393 5394 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 5395 a copy of M or reassemble it when requested. 5396 5397 .seealso: TSSetIFunction(), TSSetIJacobian(), TSComputeIFunctionLinear() 5398 @*/ 5399 PetscErrorCode TSComputeIJacobianConstant(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat A,Mat B,void *ctx) 5400 { 5401 PetscErrorCode ierr; 5402 5403 PetscFunctionBegin; 5404 ierr = MatScale(A, shift / ts->ijacobian.shift);CHKERRQ(ierr); 5405 ts->ijacobian.shift = shift; 5406 PetscFunctionReturn(0); 5407 } 5408 5409 #undef __FUNCT__ 5410 #define __FUNCT__ "TSGetEquationType" 5411 /*@ 5412 TSGetEquationType - Gets the type of the equation that TS is solving. 5413 5414 Not Collective 5415 5416 Input Parameter: 5417 . ts - the TS context 5418 5419 Output Parameter: 5420 . equation_type - see TSEquationType 5421 5422 Level: beginner 5423 5424 .keywords: TS, equation type 5425 5426 .seealso: TSSetEquationType(), TSEquationType 5427 @*/ 5428 PetscErrorCode TSGetEquationType(TS ts,TSEquationType *equation_type) 5429 { 5430 PetscFunctionBegin; 5431 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5432 PetscValidPointer(equation_type,2); 5433 *equation_type = ts->equation_type; 5434 PetscFunctionReturn(0); 5435 } 5436 5437 #undef __FUNCT__ 5438 #define __FUNCT__ "TSSetEquationType" 5439 /*@ 5440 TSSetEquationType - Sets the type of the equation that TS is solving. 5441 5442 Not Collective 5443 5444 Input Parameter: 5445 + ts - the TS context 5446 - equation_type - see TSEquationType 5447 5448 Level: advanced 5449 5450 .keywords: TS, equation type 5451 5452 .seealso: TSGetEquationType(), TSEquationType 5453 @*/ 5454 PetscErrorCode TSSetEquationType(TS ts,TSEquationType equation_type) 5455 { 5456 PetscFunctionBegin; 5457 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5458 ts->equation_type = equation_type; 5459 PetscFunctionReturn(0); 5460 } 5461 5462 #undef __FUNCT__ 5463 #define __FUNCT__ "TSGetConvergedReason" 5464 /*@ 5465 TSGetConvergedReason - Gets the reason the TS iteration was stopped. 5466 5467 Not Collective 5468 5469 Input Parameter: 5470 . ts - the TS context 5471 5472 Output Parameter: 5473 . reason - negative value indicates diverged, positive value converged, see TSConvergedReason or the 5474 manual pages for the individual convergence tests for complete lists 5475 5476 Level: beginner 5477 5478 Notes: 5479 Can only be called after the call to TSSolve() is complete. 5480 5481 .keywords: TS, nonlinear, set, convergence, test 5482 5483 .seealso: TSSetConvergenceTest(), TSConvergedReason 5484 @*/ 5485 PetscErrorCode TSGetConvergedReason(TS ts,TSConvergedReason *reason) 5486 { 5487 PetscFunctionBegin; 5488 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5489 PetscValidPointer(reason,2); 5490 *reason = ts->reason; 5491 PetscFunctionReturn(0); 5492 } 5493 5494 #undef __FUNCT__ 5495 #define __FUNCT__ "TSSetConvergedReason" 5496 /*@ 5497 TSSetConvergedReason - Sets the reason for handling the convergence of TSSolve. 5498 5499 Not Collective 5500 5501 Input Parameter: 5502 + ts - the TS context 5503 . reason - negative value indicates diverged, positive value converged, see TSConvergedReason or the 5504 manual pages for the individual convergence tests for complete lists 5505 5506 Level: advanced 5507 5508 Notes: 5509 Can only be called during TSSolve() is active. 5510 5511 .keywords: TS, nonlinear, set, convergence, test 5512 5513 .seealso: TSConvergedReason 5514 @*/ 5515 PetscErrorCode TSSetConvergedReason(TS ts,TSConvergedReason reason) 5516 { 5517 PetscFunctionBegin; 5518 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5519 ts->reason = reason; 5520 PetscFunctionReturn(0); 5521 } 5522 5523 #undef __FUNCT__ 5524 #define __FUNCT__ "TSGetSolveTime" 5525 /*@ 5526 TSGetSolveTime - Gets the time after a call to TSSolve() 5527 5528 Not Collective 5529 5530 Input Parameter: 5531 . ts - the TS context 5532 5533 Output Parameter: 5534 . ftime - the final time. This time corresponds to the final time set with TSSetDuration() 5535 5536 Level: beginner 5537 5538 Notes: 5539 Can only be called after the call to TSSolve() is complete. 5540 5541 .keywords: TS, nonlinear, set, convergence, test 5542 5543 .seealso: TSSetConvergenceTest(), TSConvergedReason 5544 @*/ 5545 PetscErrorCode TSGetSolveTime(TS ts,PetscReal *ftime) 5546 { 5547 PetscFunctionBegin; 5548 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5549 PetscValidPointer(ftime,2); 5550 *ftime = ts->solvetime; 5551 PetscFunctionReturn(0); 5552 } 5553 5554 #undef __FUNCT__ 5555 #define __FUNCT__ "TSGetTotalSteps" 5556 /*@ 5557 TSGetTotalSteps - Gets the total number of steps done since the last call to TSSetUp() or TSCreate() 5558 5559 Not Collective 5560 5561 Input Parameter: 5562 . ts - the TS context 5563 5564 Output Parameter: 5565 . steps - the number of steps 5566 5567 Level: beginner 5568 5569 Notes: 5570 Includes the number of steps for all calls to TSSolve() since TSSetUp() was called 5571 5572 .keywords: TS, nonlinear, set, convergence, test 5573 5574 .seealso: TSSetConvergenceTest(), TSConvergedReason 5575 @*/ 5576 PetscErrorCode TSGetTotalSteps(TS ts,PetscInt *steps) 5577 { 5578 PetscFunctionBegin; 5579 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5580 PetscValidPointer(steps,2); 5581 *steps = ts->total_steps; 5582 PetscFunctionReturn(0); 5583 } 5584 5585 #undef __FUNCT__ 5586 #define __FUNCT__ "TSGetSNESIterations" 5587 /*@ 5588 TSGetSNESIterations - Gets the total number of nonlinear iterations 5589 used by the time integrator. 5590 5591 Not Collective 5592 5593 Input Parameter: 5594 . ts - TS context 5595 5596 Output Parameter: 5597 . nits - number of nonlinear iterations 5598 5599 Notes: 5600 This counter is reset to zero for each successive call to TSSolve(). 5601 5602 Level: intermediate 5603 5604 .keywords: TS, get, number, nonlinear, iterations 5605 5606 .seealso: TSGetKSPIterations() 5607 @*/ 5608 PetscErrorCode TSGetSNESIterations(TS ts,PetscInt *nits) 5609 { 5610 PetscFunctionBegin; 5611 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5612 PetscValidIntPointer(nits,2); 5613 *nits = ts->snes_its; 5614 PetscFunctionReturn(0); 5615 } 5616 5617 #undef __FUNCT__ 5618 #define __FUNCT__ "TSGetKSPIterations" 5619 /*@ 5620 TSGetKSPIterations - Gets the total number of linear iterations 5621 used by the time integrator. 5622 5623 Not Collective 5624 5625 Input Parameter: 5626 . ts - TS context 5627 5628 Output Parameter: 5629 . lits - number of linear iterations 5630 5631 Notes: 5632 This counter is reset to zero for each successive call to TSSolve(). 5633 5634 Level: intermediate 5635 5636 .keywords: TS, get, number, linear, iterations 5637 5638 .seealso: TSGetSNESIterations(), SNESGetKSPIterations() 5639 @*/ 5640 PetscErrorCode TSGetKSPIterations(TS ts,PetscInt *lits) 5641 { 5642 PetscFunctionBegin; 5643 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5644 PetscValidIntPointer(lits,2); 5645 *lits = ts->ksp_its; 5646 PetscFunctionReturn(0); 5647 } 5648 5649 #undef __FUNCT__ 5650 #define __FUNCT__ "TSGetStepRejections" 5651 /*@ 5652 TSGetStepRejections - Gets the total number of rejected steps. 5653 5654 Not Collective 5655 5656 Input Parameter: 5657 . ts - TS context 5658 5659 Output Parameter: 5660 . rejects - number of steps rejected 5661 5662 Notes: 5663 This counter is reset to zero for each successive call to TSSolve(). 5664 5665 Level: intermediate 5666 5667 .keywords: TS, get, number 5668 5669 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetSNESFailures(), TSSetMaxSNESFailures(), TSSetErrorIfStepFails() 5670 @*/ 5671 PetscErrorCode TSGetStepRejections(TS ts,PetscInt *rejects) 5672 { 5673 PetscFunctionBegin; 5674 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5675 PetscValidIntPointer(rejects,2); 5676 *rejects = ts->reject; 5677 PetscFunctionReturn(0); 5678 } 5679 5680 #undef __FUNCT__ 5681 #define __FUNCT__ "TSGetSNESFailures" 5682 /*@ 5683 TSGetSNESFailures - Gets the total number of failed SNES solves 5684 5685 Not Collective 5686 5687 Input Parameter: 5688 . ts - TS context 5689 5690 Output Parameter: 5691 . fails - number of failed nonlinear solves 5692 5693 Notes: 5694 This counter is reset to zero for each successive call to TSSolve(). 5695 5696 Level: intermediate 5697 5698 .keywords: TS, get, number 5699 5700 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSSetMaxSNESFailures() 5701 @*/ 5702 PetscErrorCode TSGetSNESFailures(TS ts,PetscInt *fails) 5703 { 5704 PetscFunctionBegin; 5705 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5706 PetscValidIntPointer(fails,2); 5707 *fails = ts->num_snes_failures; 5708 PetscFunctionReturn(0); 5709 } 5710 5711 #undef __FUNCT__ 5712 #define __FUNCT__ "TSSetMaxStepRejections" 5713 /*@ 5714 TSSetMaxStepRejections - Sets the maximum number of step rejections before a step fails 5715 5716 Not Collective 5717 5718 Input Parameter: 5719 + ts - TS context 5720 - rejects - maximum number of rejected steps, pass -1 for unlimited 5721 5722 Notes: 5723 The counter is reset to zero for each step 5724 5725 Options Database Key: 5726 . -ts_max_reject - Maximum number of step rejections before a step fails 5727 5728 Level: intermediate 5729 5730 .keywords: TS, set, maximum, number 5731 5732 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxSNESFailures(), TSGetStepRejections(), TSGetSNESFailures(), TSSetErrorIfStepFails(), TSGetConvergedReason() 5733 @*/ 5734 PetscErrorCode TSSetMaxStepRejections(TS ts,PetscInt rejects) 5735 { 5736 PetscFunctionBegin; 5737 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5738 ts->max_reject = rejects; 5739 PetscFunctionReturn(0); 5740 } 5741 5742 #undef __FUNCT__ 5743 #define __FUNCT__ "TSSetMaxSNESFailures" 5744 /*@ 5745 TSSetMaxSNESFailures - Sets the maximum number of failed SNES solves 5746 5747 Not Collective 5748 5749 Input Parameter: 5750 + ts - TS context 5751 - fails - maximum number of failed nonlinear solves, pass -1 for unlimited 5752 5753 Notes: 5754 The counter is reset to zero for each successive call to TSSolve(). 5755 5756 Options Database Key: 5757 . -ts_max_snes_failures - Maximum number of nonlinear solve failures 5758 5759 Level: intermediate 5760 5761 .keywords: TS, set, maximum, number 5762 5763 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSGetSNESFailures(), SNESGetConvergedReason(), TSGetConvergedReason() 5764 @*/ 5765 PetscErrorCode TSSetMaxSNESFailures(TS ts,PetscInt fails) 5766 { 5767 PetscFunctionBegin; 5768 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5769 ts->max_snes_failures = fails; 5770 PetscFunctionReturn(0); 5771 } 5772 5773 #undef __FUNCT__ 5774 #define __FUNCT__ "TSSetErrorIfStepFails" 5775 /*@ 5776 TSSetErrorIfStepFails - Error if no step succeeds 5777 5778 Not Collective 5779 5780 Input Parameter: 5781 + ts - TS context 5782 - err - PETSC_TRUE to error if no step succeeds, PETSC_FALSE to return without failure 5783 5784 Options Database Key: 5785 . -ts_error_if_step_fails - Error if no step succeeds 5786 5787 Level: intermediate 5788 5789 .keywords: TS, set, error 5790 5791 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSGetSNESFailures(), TSSetErrorIfStepFails(), TSGetConvergedReason() 5792 @*/ 5793 PetscErrorCode TSSetErrorIfStepFails(TS ts,PetscBool err) 5794 { 5795 PetscFunctionBegin; 5796 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5797 ts->errorifstepfailed = err; 5798 PetscFunctionReturn(0); 5799 } 5800 5801 #undef __FUNCT__ 5802 #define __FUNCT__ "TSMonitorSolution" 5803 /*@C 5804 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 5805 5806 Collective on TS 5807 5808 Input Parameters: 5809 + ts - the TS context 5810 . step - current time-step 5811 . ptime - current time 5812 . u - current state 5813 - vf - viewer and its format 5814 5815 Level: intermediate 5816 5817 .keywords: TS, vector, monitor, view 5818 5819 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 5820 @*/ 5821 PetscErrorCode TSMonitorSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,PetscViewerAndFormat *vf) 5822 { 5823 PetscErrorCode ierr; 5824 5825 PetscFunctionBegin; 5826 ierr = PetscViewerPushFormat(vf->viewer,vf->format);CHKERRQ(ierr); 5827 ierr = VecView(u,vf->viewer);CHKERRQ(ierr); 5828 ierr = PetscViewerPopFormat(vf->viewer);CHKERRQ(ierr); 5829 PetscFunctionReturn(0); 5830 } 5831 5832 #undef __FUNCT__ 5833 #define __FUNCT__ "TSMonitorSolutionVTK" 5834 /*@C 5835 TSMonitorSolutionVTK - Monitors progress of the TS solvers by VecView() for the solution at each timestep. 5836 5837 Collective on TS 5838 5839 Input Parameters: 5840 + ts - the TS context 5841 . step - current time-step 5842 . ptime - current time 5843 . u - current state 5844 - filenametemplate - string containing a format specifier for the integer time step (e.g. %03D) 5845 5846 Level: intermediate 5847 5848 Notes: 5849 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. 5850 These are named according to the file name template. 5851 5852 This function is normally passed as an argument to TSMonitorSet() along with TSMonitorSolutionVTKDestroy(). 5853 5854 .keywords: TS, vector, monitor, view 5855 5856 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 5857 @*/ 5858 PetscErrorCode TSMonitorSolutionVTK(TS ts,PetscInt step,PetscReal ptime,Vec u,void *filenametemplate) 5859 { 5860 PetscErrorCode ierr; 5861 char filename[PETSC_MAX_PATH_LEN]; 5862 PetscViewer viewer; 5863 5864 PetscFunctionBegin; 5865 if (step < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */ 5866 ierr = PetscSNPrintf(filename,sizeof(filename),(const char*)filenametemplate,step);CHKERRQ(ierr); 5867 ierr = PetscViewerVTKOpen(PetscObjectComm((PetscObject)ts),filename,FILE_MODE_WRITE,&viewer);CHKERRQ(ierr); 5868 ierr = VecView(u,viewer);CHKERRQ(ierr); 5869 ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr); 5870 PetscFunctionReturn(0); 5871 } 5872 5873 #undef __FUNCT__ 5874 #define __FUNCT__ "TSMonitorSolutionVTKDestroy" 5875 /*@C 5876 TSMonitorSolutionVTKDestroy - Destroy context for monitoring 5877 5878 Collective on TS 5879 5880 Input Parameters: 5881 . filenametemplate - string containing a format specifier for the integer time step (e.g. %03D) 5882 5883 Level: intermediate 5884 5885 Note: 5886 This function is normally passed to TSMonitorSet() along with TSMonitorSolutionVTK(). 5887 5888 .keywords: TS, vector, monitor, view 5889 5890 .seealso: TSMonitorSet(), TSMonitorSolutionVTK() 5891 @*/ 5892 PetscErrorCode TSMonitorSolutionVTKDestroy(void *filenametemplate) 5893 { 5894 PetscErrorCode ierr; 5895 5896 PetscFunctionBegin; 5897 ierr = PetscFree(*(char**)filenametemplate);CHKERRQ(ierr); 5898 PetscFunctionReturn(0); 5899 } 5900 5901 #undef __FUNCT__ 5902 #define __FUNCT__ "TSGetAdapt" 5903 /*@ 5904 TSGetAdapt - Get the adaptive controller context for the current method 5905 5906 Collective on TS if controller has not been created yet 5907 5908 Input Arguments: 5909 . ts - time stepping context 5910 5911 Output Arguments: 5912 . adapt - adaptive controller 5913 5914 Level: intermediate 5915 5916 .seealso: TSAdapt, TSAdaptSetType(), TSAdaptChoose() 5917 @*/ 5918 PetscErrorCode TSGetAdapt(TS ts,TSAdapt *adapt) 5919 { 5920 PetscErrorCode ierr; 5921 5922 PetscFunctionBegin; 5923 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5924 PetscValidPointer(adapt,2); 5925 if (!ts->adapt) { 5926 ierr = TSAdaptCreate(PetscObjectComm((PetscObject)ts),&ts->adapt);CHKERRQ(ierr); 5927 ierr = PetscLogObjectParent((PetscObject)ts,(PetscObject)ts->adapt);CHKERRQ(ierr); 5928 ierr = PetscObjectIncrementTabLevel((PetscObject)ts->adapt,(PetscObject)ts,1);CHKERRQ(ierr); 5929 } 5930 *adapt = ts->adapt; 5931 PetscFunctionReturn(0); 5932 } 5933 5934 #undef __FUNCT__ 5935 #define __FUNCT__ "TSSetTolerances" 5936 /*@ 5937 TSSetTolerances - Set tolerances for local truncation error when using adaptive controller 5938 5939 Logically Collective 5940 5941 Input Arguments: 5942 + ts - time integration context 5943 . atol - scalar absolute tolerances, PETSC_DECIDE to leave current value 5944 . vatol - vector of absolute tolerances or NULL, used in preference to atol if present 5945 . rtol - scalar relative tolerances, PETSC_DECIDE to leave current value 5946 - vrtol - vector of relative tolerances or NULL, used in preference to atol if present 5947 5948 Options Database keys: 5949 + -ts_rtol <rtol> - relative tolerance for local truncation error 5950 - -ts_atol <atol> Absolute tolerance for local truncation error 5951 5952 Notes: 5953 With PETSc's implicit schemes for DAE problems, the calculation of the local truncation error 5954 (LTE) includes both the differential and the algebraic variables. If one wants the LTE to be 5955 computed only for the differential or the algebraic part then this can be done using the vector of 5956 tolerances vatol. For example, by setting the tolerance vector with the desired tolerance for the 5957 differential part and infinity for the algebraic part, the LTE calculation will include only the 5958 differential variables. 5959 5960 Level: beginner 5961 5962 .seealso: TS, TSAdapt, TSVecNormWRMS(), TSGetTolerances() 5963 @*/ 5964 PetscErrorCode TSSetTolerances(TS ts,PetscReal atol,Vec vatol,PetscReal rtol,Vec vrtol) 5965 { 5966 PetscErrorCode ierr; 5967 5968 PetscFunctionBegin; 5969 if (atol != PETSC_DECIDE && atol != PETSC_DEFAULT) ts->atol = atol; 5970 if (vatol) { 5971 ierr = PetscObjectReference((PetscObject)vatol);CHKERRQ(ierr); 5972 ierr = VecDestroy(&ts->vatol);CHKERRQ(ierr); 5973 ts->vatol = vatol; 5974 } 5975 if (rtol != PETSC_DECIDE && rtol != PETSC_DEFAULT) ts->rtol = rtol; 5976 if (vrtol) { 5977 ierr = PetscObjectReference((PetscObject)vrtol);CHKERRQ(ierr); 5978 ierr = VecDestroy(&ts->vrtol);CHKERRQ(ierr); 5979 ts->vrtol = vrtol; 5980 } 5981 PetscFunctionReturn(0); 5982 } 5983 5984 #undef __FUNCT__ 5985 #define __FUNCT__ "TSGetTolerances" 5986 /*@ 5987 TSGetTolerances - Get tolerances for local truncation error when using adaptive controller 5988 5989 Logically Collective 5990 5991 Input Arguments: 5992 . ts - time integration context 5993 5994 Output Arguments: 5995 + atol - scalar absolute tolerances, NULL to ignore 5996 . vatol - vector of absolute tolerances, NULL to ignore 5997 . rtol - scalar relative tolerances, NULL to ignore 5998 - vrtol - vector of relative tolerances, NULL to ignore 5999 6000 Level: beginner 6001 6002 .seealso: TS, TSAdapt, TSVecNormWRMS(), TSSetTolerances() 6003 @*/ 6004 PetscErrorCode TSGetTolerances(TS ts,PetscReal *atol,Vec *vatol,PetscReal *rtol,Vec *vrtol) 6005 { 6006 PetscFunctionBegin; 6007 if (atol) *atol = ts->atol; 6008 if (vatol) *vatol = ts->vatol; 6009 if (rtol) *rtol = ts->rtol; 6010 if (vrtol) *vrtol = ts->vrtol; 6011 PetscFunctionReturn(0); 6012 } 6013 6014 #undef __FUNCT__ 6015 #define __FUNCT__ "TSErrorWeightedNorm2" 6016 /*@ 6017 TSErrorWeightedNorm2 - compute a weighted 2-norm of the difference between two state vectors 6018 6019 Collective on TS 6020 6021 Input Arguments: 6022 + ts - time stepping context 6023 . U - state vector, usually ts->vec_sol 6024 - Y - state vector to be compared to U 6025 6026 Output Arguments: 6027 . norm - weighted norm, a value of 1.0 means that the error matches the tolerances 6028 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 6029 . normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 6030 6031 Level: developer 6032 6033 .seealso: TSErrorWeightedNorm(), TSErrorWeightedNormInfinity() 6034 @*/ 6035 PetscErrorCode TSErrorWeightedNorm2(TS ts,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6036 { 6037 PetscErrorCode ierr; 6038 PetscInt i,n,N,rstart; 6039 PetscInt n_loc,na_loc,nr_loc; 6040 PetscReal n_glb,na_glb,nr_glb; 6041 const PetscScalar *u,*y; 6042 PetscReal sum,suma,sumr,gsum,gsuma,gsumr,diff; 6043 PetscReal tol,tola,tolr; 6044 PetscReal err_loc[6],err_glb[6]; 6045 6046 PetscFunctionBegin; 6047 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6048 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 6049 PetscValidHeaderSpecific(Y,VEC_CLASSID,3); 6050 PetscValidType(U,2); 6051 PetscValidType(Y,3); 6052 PetscCheckSameComm(U,2,Y,3); 6053 PetscValidPointer(norm,4); 6054 PetscValidPointer(norma,5); 6055 PetscValidPointer(normr,6); 6056 if (U == Y) SETERRQ(PetscObjectComm((PetscObject)U),PETSC_ERR_ARG_IDN,"U and Y cannot be the same vector"); 6057 6058 ierr = VecGetSize(U,&N);CHKERRQ(ierr); 6059 ierr = VecGetLocalSize(U,&n);CHKERRQ(ierr); 6060 ierr = VecGetOwnershipRange(U,&rstart,NULL);CHKERRQ(ierr); 6061 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 6062 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 6063 sum = 0.; n_loc = 0; 6064 suma = 0.; na_loc = 0; 6065 sumr = 0.; nr_loc = 0; 6066 if (ts->vatol && ts->vrtol) { 6067 const PetscScalar *atol,*rtol; 6068 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6069 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6070 for (i=0; i<n; i++) { 6071 diff = PetscAbsScalar(y[i] - u[i]); 6072 tola = PetscRealPart(atol[i]); 6073 if(tola>0.){ 6074 suma += PetscSqr(diff/tola); 6075 na_loc++; 6076 } 6077 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6078 if(tolr>0.){ 6079 sumr += PetscSqr(diff/tolr); 6080 nr_loc++; 6081 } 6082 tol=tola+tolr; 6083 if(tol>0.){ 6084 sum += PetscSqr(diff/tol); 6085 n_loc++; 6086 } 6087 } 6088 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6089 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6090 } else if (ts->vatol) { /* vector atol, scalar rtol */ 6091 const PetscScalar *atol; 6092 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6093 for (i=0; i<n; i++) { 6094 diff = PetscAbsScalar(y[i] - u[i]); 6095 tola = PetscRealPart(atol[i]); 6096 if(tola>0.){ 6097 suma += PetscSqr(diff/tola); 6098 na_loc++; 6099 } 6100 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6101 if(tolr>0.){ 6102 sumr += PetscSqr(diff/tolr); 6103 nr_loc++; 6104 } 6105 tol=tola+tolr; 6106 if(tol>0.){ 6107 sum += PetscSqr(diff/tol); 6108 n_loc++; 6109 } 6110 } 6111 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6112 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 6113 const PetscScalar *rtol; 6114 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6115 for (i=0; i<n; i++) { 6116 diff = PetscAbsScalar(y[i] - u[i]); 6117 tola = ts->atol; 6118 if(tola>0.){ 6119 suma += PetscSqr(diff/tola); 6120 na_loc++; 6121 } 6122 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6123 if(tolr>0.){ 6124 sumr += PetscSqr(diff/tolr); 6125 nr_loc++; 6126 } 6127 tol=tola+tolr; 6128 if(tol>0.){ 6129 sum += PetscSqr(diff/tol); 6130 n_loc++; 6131 } 6132 } 6133 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6134 } else { /* scalar atol, scalar rtol */ 6135 for (i=0; i<n; i++) { 6136 diff = PetscAbsScalar(y[i] - u[i]); 6137 tola = ts->atol; 6138 if(tola>0.){ 6139 suma += PetscSqr(diff/tola); 6140 na_loc++; 6141 } 6142 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6143 if(tolr>0.){ 6144 sumr += PetscSqr(diff/tolr); 6145 nr_loc++; 6146 } 6147 tol=tola+tolr; 6148 if(tol>0.){ 6149 sum += PetscSqr(diff/tol); 6150 n_loc++; 6151 } 6152 } 6153 } 6154 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 6155 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 6156 6157 err_loc[0] = sum; 6158 err_loc[1] = suma; 6159 err_loc[2] = sumr; 6160 err_loc[3] = (PetscReal)n_loc; 6161 err_loc[4] = (PetscReal)na_loc; 6162 err_loc[5] = (PetscReal)nr_loc; 6163 6164 ierr = MPIU_Allreduce(&err_loc,&err_glb,6,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6165 6166 gsum = err_glb[0]; 6167 gsuma = err_glb[1]; 6168 gsumr = err_glb[2]; 6169 n_glb = err_glb[3]; 6170 na_glb = err_glb[4]; 6171 nr_glb = err_glb[5]; 6172 6173 *norm = 0.; 6174 if(n_glb>0. ){*norm = PetscSqrtReal(gsum / n_glb );} 6175 *norma = 0.; 6176 if(na_glb>0.){*norma = PetscSqrtReal(gsuma / na_glb);} 6177 *normr = 0.; 6178 if(nr_glb>0.){*normr = PetscSqrtReal(gsumr / nr_glb);} 6179 6180 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 6181 if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 6182 if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 6183 PetscFunctionReturn(0); 6184 } 6185 6186 #undef __FUNCT__ 6187 #define __FUNCT__ "TSErrorWeightedNormInfinity" 6188 /*@ 6189 TSErrorWeightedNormInfinity - compute a weighted infinity-norm of the difference between two state vectors 6190 6191 Collective on TS 6192 6193 Input Arguments: 6194 + ts - time stepping context 6195 . U - state vector, usually ts->vec_sol 6196 - Y - state vector to be compared to U 6197 6198 Output Arguments: 6199 . norm - weighted norm, a value of 1.0 means that the error matches the tolerances 6200 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 6201 . normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 6202 6203 Level: developer 6204 6205 .seealso: TSErrorWeightedNorm(), TSErrorWeightedNorm2() 6206 @*/ 6207 PetscErrorCode TSErrorWeightedNormInfinity(TS ts,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6208 { 6209 PetscErrorCode ierr; 6210 PetscInt i,n,N,rstart; 6211 const PetscScalar *u,*y; 6212 PetscReal max,gmax,maxa,gmaxa,maxr,gmaxr; 6213 PetscReal tol,tola,tolr,diff; 6214 PetscReal err_loc[3],err_glb[3]; 6215 6216 PetscFunctionBegin; 6217 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6218 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 6219 PetscValidHeaderSpecific(Y,VEC_CLASSID,3); 6220 PetscValidType(U,2); 6221 PetscValidType(Y,3); 6222 PetscCheckSameComm(U,2,Y,3); 6223 PetscValidPointer(norm,4); 6224 PetscValidPointer(norma,5); 6225 PetscValidPointer(normr,6); 6226 if (U == Y) SETERRQ(PetscObjectComm((PetscObject)U),PETSC_ERR_ARG_IDN,"U and Y cannot be the same vector"); 6227 6228 ierr = VecGetSize(U,&N);CHKERRQ(ierr); 6229 ierr = VecGetLocalSize(U,&n);CHKERRQ(ierr); 6230 ierr = VecGetOwnershipRange(U,&rstart,NULL);CHKERRQ(ierr); 6231 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 6232 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 6233 6234 max=0.; 6235 maxa=0.; 6236 maxr=0.; 6237 6238 if (ts->vatol && ts->vrtol) { /* vector atol, vector rtol */ 6239 const PetscScalar *atol,*rtol; 6240 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6241 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6242 6243 for (i=0; i<n; i++) { 6244 diff = PetscAbsScalar(y[i] - u[i]); 6245 tola = PetscRealPart(atol[i]); 6246 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6247 tol = tola+tolr; 6248 if(tola>0.){ 6249 maxa = PetscMax(maxa,diff / tola); 6250 } 6251 if(tolr>0.){ 6252 maxr = PetscMax(maxr,diff / tolr); 6253 } 6254 if(tol>0.){ 6255 max = PetscMax(max,diff / tol); 6256 } 6257 } 6258 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6259 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6260 } else if (ts->vatol) { /* vector atol, scalar rtol */ 6261 const PetscScalar *atol; 6262 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6263 for (i=0; i<n; i++) { 6264 diff = PetscAbsScalar(y[i] - u[i]); 6265 tola = PetscRealPart(atol[i]); 6266 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6267 tol = tola+tolr; 6268 if(tola>0.){ 6269 maxa = PetscMax(maxa,diff / tola); 6270 } 6271 if(tolr>0.){ 6272 maxr = PetscMax(maxr,diff / tolr); 6273 } 6274 if(tol>0.){ 6275 max = PetscMax(max,diff / tol); 6276 } 6277 } 6278 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6279 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 6280 const PetscScalar *rtol; 6281 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6282 6283 for (i=0; i<n; i++) { 6284 diff = PetscAbsScalar(y[i] - u[i]); 6285 tola = ts->atol; 6286 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6287 tol = tola+tolr; 6288 if(tola>0.){ 6289 maxa = PetscMax(maxa,diff / tola); 6290 } 6291 if(tolr>0.){ 6292 maxr = PetscMax(maxr,diff / tolr); 6293 } 6294 if(tol>0.){ 6295 max = PetscMax(max,diff / tol); 6296 } 6297 } 6298 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6299 } else { /* scalar atol, scalar rtol */ 6300 6301 for (i=0; i<n; i++) { 6302 diff = PetscAbsScalar(y[i] - u[i]); 6303 tola = ts->atol; 6304 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6305 tol = tola+tolr; 6306 if(tola>0.){ 6307 maxa = PetscMax(maxa,diff / tola); 6308 } 6309 if(tolr>0.){ 6310 maxr = PetscMax(maxr,diff / tolr); 6311 } 6312 if(tol>0.){ 6313 max = PetscMax(max,diff / tol); 6314 } 6315 } 6316 } 6317 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 6318 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 6319 err_loc[0] = max; 6320 err_loc[1] = maxa; 6321 err_loc[2] = maxr; 6322 ierr = MPIU_Allreduce(&err_loc,&err_glb,3,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6323 gmax = err_glb[0]; 6324 gmaxa = err_glb[1]; 6325 gmaxr = err_glb[2]; 6326 6327 *norm = gmax; 6328 *norma = gmaxa; 6329 *normr = gmaxr; 6330 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 6331 if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 6332 if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 6333 PetscFunctionReturn(0); 6334 } 6335 6336 #undef __FUNCT__ 6337 #define __FUNCT__ "TSErrorWeightedNorm" 6338 /*@ 6339 TSErrorWeightedNorm - compute a weighted norm of the difference between two state vectors based on supplied absolute and relative tolerances 6340 6341 Collective on TS 6342 6343 Input Arguments: 6344 + ts - time stepping context 6345 . U - state vector, usually ts->vec_sol 6346 . Y - state vector to be compared to U 6347 - wnormtype - norm type, either NORM_2 or NORM_INFINITY 6348 6349 Output Arguments: 6350 . norm - weighted norm, a value of 1.0 achieves a balance between absolute and relative tolerances 6351 . norma - weighted norm, a value of 1.0 means that the error meets the absolute tolerance set by the user 6352 . normr - weighted norm, a value of 1.0 means that the error meets the relative tolerance set by the user 6353 6354 Options Database Keys: 6355 . -ts_adapt_wnormtype <wnormtype> - 2, INFINITY 6356 6357 Level: developer 6358 6359 .seealso: TSErrorWeightedNormInfinity(), TSErrorWeightedNorm2(), TSErrorWeightedENorm 6360 @*/ 6361 PetscErrorCode TSErrorWeightedNorm(TS ts,Vec U,Vec Y,NormType wnormtype,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6362 { 6363 PetscErrorCode ierr; 6364 6365 PetscFunctionBegin; 6366 if (wnormtype == NORM_2) { 6367 ierr = TSErrorWeightedNorm2(ts,U,Y,norm,norma,normr);CHKERRQ(ierr); 6368 } else if(wnormtype == NORM_INFINITY) { 6369 ierr = TSErrorWeightedNormInfinity(ts,U,Y,norm,norma,normr);CHKERRQ(ierr); 6370 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]); 6371 PetscFunctionReturn(0); 6372 } 6373 6374 6375 #undef __FUNCT__ 6376 #define __FUNCT__ "TSErrorWeightedENorm2" 6377 /*@ 6378 TSErrorWeightedENorm2 - compute a weighted 2 error norm based on supplied absolute and relative tolerances 6379 6380 Collective on TS 6381 6382 Input Arguments: 6383 + ts - time stepping context 6384 . E - error vector 6385 . U - state vector, usually ts->vec_sol 6386 - Y - state vector, previous time step 6387 6388 Output Arguments: 6389 . norm - weighted norm, a value of 1.0 means that the error matches the tolerances 6390 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 6391 . normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 6392 6393 Level: developer 6394 6395 .seealso: TSErrorWeightedENorm(), TSErrorWeightedENormInfinity() 6396 @*/ 6397 PetscErrorCode TSErrorWeightedENorm2(TS ts,Vec E,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6398 { 6399 PetscErrorCode ierr; 6400 PetscInt i,n,N,rstart; 6401 PetscInt n_loc,na_loc,nr_loc; 6402 PetscReal n_glb,na_glb,nr_glb; 6403 const PetscScalar *e,*u,*y; 6404 PetscReal err,sum,suma,sumr,gsum,gsuma,gsumr; 6405 PetscReal tol,tola,tolr; 6406 PetscReal err_loc[6],err_glb[6]; 6407 6408 PetscFunctionBegin; 6409 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6410 PetscValidHeaderSpecific(E,VEC_CLASSID,2); 6411 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 6412 PetscValidHeaderSpecific(Y,VEC_CLASSID,4); 6413 PetscValidType(E,2); 6414 PetscValidType(U,3); 6415 PetscValidType(Y,4); 6416 PetscCheckSameComm(E,2,U,3); 6417 PetscCheckSameComm(U,2,Y,3); 6418 PetscValidPointer(norm,5); 6419 PetscValidPointer(norma,6); 6420 PetscValidPointer(normr,7); 6421 6422 ierr = VecGetSize(E,&N);CHKERRQ(ierr); 6423 ierr = VecGetLocalSize(E,&n);CHKERRQ(ierr); 6424 ierr = VecGetOwnershipRange(E,&rstart,NULL);CHKERRQ(ierr); 6425 ierr = VecGetArrayRead(E,&e);CHKERRQ(ierr); 6426 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 6427 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 6428 sum = 0.; n_loc = 0; 6429 suma = 0.; na_loc = 0; 6430 sumr = 0.; nr_loc = 0; 6431 if (ts->vatol && ts->vrtol) { 6432 const PetscScalar *atol,*rtol; 6433 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6434 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6435 for (i=0; i<n; i++) { 6436 err = PetscAbsScalar(e[i]); 6437 tola = PetscRealPart(atol[i]); 6438 if(tola>0.){ 6439 suma += PetscSqr(err/tola); 6440 na_loc++; 6441 } 6442 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6443 if(tolr>0.){ 6444 sumr += PetscSqr(err/tolr); 6445 nr_loc++; 6446 } 6447 tol=tola+tolr; 6448 if(tol>0.){ 6449 sum += PetscSqr(err/tol); 6450 n_loc++; 6451 } 6452 } 6453 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6454 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6455 } else if (ts->vatol) { /* vector atol, scalar rtol */ 6456 const PetscScalar *atol; 6457 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6458 for (i=0; i<n; i++) { 6459 err = PetscAbsScalar(e[i]); 6460 tola = PetscRealPart(atol[i]); 6461 if(tola>0.){ 6462 suma += PetscSqr(err/tola); 6463 na_loc++; 6464 } 6465 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6466 if(tolr>0.){ 6467 sumr += PetscSqr(err/tolr); 6468 nr_loc++; 6469 } 6470 tol=tola+tolr; 6471 if(tol>0.){ 6472 sum += PetscSqr(err/tol); 6473 n_loc++; 6474 } 6475 } 6476 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6477 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 6478 const PetscScalar *rtol; 6479 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6480 for (i=0; i<n; i++) { 6481 err = PetscAbsScalar(e[i]); 6482 tola = ts->atol; 6483 if(tola>0.){ 6484 suma += PetscSqr(err/tola); 6485 na_loc++; 6486 } 6487 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6488 if(tolr>0.){ 6489 sumr += PetscSqr(err/tolr); 6490 nr_loc++; 6491 } 6492 tol=tola+tolr; 6493 if(tol>0.){ 6494 sum += PetscSqr(err/tol); 6495 n_loc++; 6496 } 6497 } 6498 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6499 } else { /* scalar atol, scalar rtol */ 6500 for (i=0; i<n; i++) { 6501 err = PetscAbsScalar(e[i]); 6502 tola = ts->atol; 6503 if(tola>0.){ 6504 suma += PetscSqr(err/tola); 6505 na_loc++; 6506 } 6507 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6508 if(tolr>0.){ 6509 sumr += PetscSqr(err/tolr); 6510 nr_loc++; 6511 } 6512 tol=tola+tolr; 6513 if(tol>0.){ 6514 sum += PetscSqr(err/tol); 6515 n_loc++; 6516 } 6517 } 6518 } 6519 ierr = VecRestoreArrayRead(E,&e);CHKERRQ(ierr); 6520 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 6521 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 6522 6523 err_loc[0] = sum; 6524 err_loc[1] = suma; 6525 err_loc[2] = sumr; 6526 err_loc[3] = (PetscReal)n_loc; 6527 err_loc[4] = (PetscReal)na_loc; 6528 err_loc[5] = (PetscReal)nr_loc; 6529 6530 ierr = MPIU_Allreduce(&err_loc,&err_glb,6,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6531 6532 gsum = err_glb[0]; 6533 gsuma = err_glb[1]; 6534 gsumr = err_glb[2]; 6535 n_glb = err_glb[3]; 6536 na_glb = err_glb[4]; 6537 nr_glb = err_glb[5]; 6538 6539 *norm = 0.; 6540 if(n_glb>0. ){*norm = PetscSqrtReal(gsum / n_glb );} 6541 *norma = 0.; 6542 if(na_glb>0.){*norma = PetscSqrtReal(gsuma / na_glb);} 6543 *normr = 0.; 6544 if(nr_glb>0.){*normr = PetscSqrtReal(gsumr / nr_glb);} 6545 6546 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 6547 if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 6548 if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 6549 PetscFunctionReturn(0); 6550 } 6551 6552 #undef __FUNCT__ 6553 #define __FUNCT__ "TSErrorWeightedENormInfinity" 6554 /*@ 6555 TSErrorWeightedENormInfinity - compute a weighted infinity error norm based on supplied absolute and relative tolerances 6556 Collective on TS 6557 6558 Input Arguments: 6559 + ts - time stepping context 6560 . E - error vector 6561 . U - state vector, usually ts->vec_sol 6562 - Y - state vector, previous time step 6563 6564 Output Arguments: 6565 . norm - weighted norm, a value of 1.0 means that the error matches the tolerances 6566 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 6567 . normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 6568 6569 Level: developer 6570 6571 .seealso: TSErrorWeightedENorm(), TSErrorWeightedENorm2() 6572 @*/ 6573 PetscErrorCode TSErrorWeightedENormInfinity(TS ts,Vec E,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6574 { 6575 PetscErrorCode ierr; 6576 PetscInt i,n,N,rstart; 6577 const PetscScalar *e,*u,*y; 6578 PetscReal err,max,gmax,maxa,gmaxa,maxr,gmaxr; 6579 PetscReal tol,tola,tolr; 6580 PetscReal err_loc[3],err_glb[3]; 6581 6582 PetscFunctionBegin; 6583 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6584 PetscValidHeaderSpecific(E,VEC_CLASSID,2); 6585 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 6586 PetscValidHeaderSpecific(Y,VEC_CLASSID,4); 6587 PetscValidType(E,2); 6588 PetscValidType(U,3); 6589 PetscValidType(Y,4); 6590 PetscCheckSameComm(E,2,U,3); 6591 PetscCheckSameComm(U,2,Y,3); 6592 PetscValidPointer(norm,5); 6593 PetscValidPointer(norma,6); 6594 PetscValidPointer(normr,7); 6595 6596 ierr = VecGetSize(E,&N);CHKERRQ(ierr); 6597 ierr = VecGetLocalSize(E,&n);CHKERRQ(ierr); 6598 ierr = VecGetOwnershipRange(E,&rstart,NULL);CHKERRQ(ierr); 6599 ierr = VecGetArrayRead(E,&e);CHKERRQ(ierr); 6600 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 6601 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 6602 6603 max=0.; 6604 maxa=0.; 6605 maxr=0.; 6606 6607 if (ts->vatol && ts->vrtol) { /* vector atol, vector rtol */ 6608 const PetscScalar *atol,*rtol; 6609 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6610 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6611 6612 for (i=0; i<n; i++) { 6613 err = PetscAbsScalar(e[i]); 6614 tola = PetscRealPart(atol[i]); 6615 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6616 tol = tola+tolr; 6617 if(tola>0.){ 6618 maxa = PetscMax(maxa,err / tola); 6619 } 6620 if(tolr>0.){ 6621 maxr = PetscMax(maxr,err / tolr); 6622 } 6623 if(tol>0.){ 6624 max = PetscMax(max,err / tol); 6625 } 6626 } 6627 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6628 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6629 } else if (ts->vatol) { /* vector atol, scalar rtol */ 6630 const PetscScalar *atol; 6631 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6632 for (i=0; i<n; i++) { 6633 err = PetscAbsScalar(e[i]); 6634 tola = PetscRealPart(atol[i]); 6635 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6636 tol = tola+tolr; 6637 if(tola>0.){ 6638 maxa = PetscMax(maxa,err / tola); 6639 } 6640 if(tolr>0.){ 6641 maxr = PetscMax(maxr,err / tolr); 6642 } 6643 if(tol>0.){ 6644 max = PetscMax(max,err / tol); 6645 } 6646 } 6647 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6648 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 6649 const PetscScalar *rtol; 6650 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6651 6652 for (i=0; i<n; i++) { 6653 err = PetscAbsScalar(e[i]); 6654 tola = ts->atol; 6655 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6656 tol = tola+tolr; 6657 if(tola>0.){ 6658 maxa = PetscMax(maxa,err / tola); 6659 } 6660 if(tolr>0.){ 6661 maxr = PetscMax(maxr,err / tolr); 6662 } 6663 if(tol>0.){ 6664 max = PetscMax(max,err / tol); 6665 } 6666 } 6667 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6668 } else { /* scalar atol, scalar rtol */ 6669 6670 for (i=0; i<n; i++) { 6671 err = PetscAbsScalar(e[i]); 6672 tola = ts->atol; 6673 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6674 tol = tola+tolr; 6675 if(tola>0.){ 6676 maxa = PetscMax(maxa,err / tola); 6677 } 6678 if(tolr>0.){ 6679 maxr = PetscMax(maxr,err / tolr); 6680 } 6681 if(tol>0.){ 6682 max = PetscMax(max,err / tol); 6683 } 6684 } 6685 } 6686 ierr = VecRestoreArrayRead(E,&e);CHKERRQ(ierr); 6687 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 6688 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 6689 err_loc[0] = max; 6690 err_loc[1] = maxa; 6691 err_loc[2] = maxr; 6692 ierr = MPIU_Allreduce(&err_loc,&err_glb,3,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6693 gmax = err_glb[0]; 6694 gmaxa = err_glb[1]; 6695 gmaxr = err_glb[2]; 6696 6697 *norm = gmax; 6698 *norma = gmaxa; 6699 *normr = gmaxr; 6700 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 6701 if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 6702 if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 6703 PetscFunctionReturn(0); 6704 } 6705 6706 #undef __FUNCT__ 6707 #define __FUNCT__ "TSErrorWeightedENorm" 6708 /*@ 6709 TSErrorWeightedENorm - compute a weighted error norm based on supplied absolute and relative tolerances 6710 6711 Collective on TS 6712 6713 Input Arguments: 6714 + ts - time stepping context 6715 . E - error vector 6716 . U - state vector, usually ts->vec_sol 6717 . Y - state vector, previous time step 6718 - wnormtype - norm type, either NORM_2 or NORM_INFINITY 6719 6720 Output Arguments: 6721 . norm - weighted norm, a value of 1.0 achieves a balance between absolute and relative tolerances 6722 . norma - weighted norm, a value of 1.0 means that the error meets the absolute tolerance set by the user 6723 . normr - weighted norm, a value of 1.0 means that the error meets the relative tolerance set by the user 6724 6725 Options Database Keys: 6726 . -ts_adapt_wnormtype <wnormtype> - 2, INFINITY 6727 6728 Level: developer 6729 6730 .seealso: TSErrorWeightedENormInfinity(), TSErrorWeightedENorm2(), TSErrorWeightedNormInfinity(), TSErrorWeightedNorm2() 6731 @*/ 6732 PetscErrorCode TSErrorWeightedENorm(TS ts,Vec E,Vec U,Vec Y,NormType wnormtype,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6733 { 6734 PetscErrorCode ierr; 6735 6736 PetscFunctionBegin; 6737 if (wnormtype == NORM_2) { 6738 ierr = TSErrorWeightedENorm2(ts,E,U,Y,norm,norma,normr);CHKERRQ(ierr); 6739 } else if(wnormtype == NORM_INFINITY) { 6740 ierr = TSErrorWeightedENormInfinity(ts,E,U,Y,norm,norma,normr);CHKERRQ(ierr); 6741 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]); 6742 PetscFunctionReturn(0); 6743 } 6744 6745 6746 #undef __FUNCT__ 6747 #define __FUNCT__ "TSSetCFLTimeLocal" 6748 /*@ 6749 TSSetCFLTimeLocal - Set the local CFL constraint relative to forward Euler 6750 6751 Logically Collective on TS 6752 6753 Input Arguments: 6754 + ts - time stepping context 6755 - cfltime - maximum stable time step if using forward Euler (value can be different on each process) 6756 6757 Note: 6758 After calling this function, the global CFL time can be obtained by calling TSGetCFLTime() 6759 6760 Level: intermediate 6761 6762 .seealso: TSGetCFLTime(), TSADAPTCFL 6763 @*/ 6764 PetscErrorCode TSSetCFLTimeLocal(TS ts,PetscReal cfltime) 6765 { 6766 PetscFunctionBegin; 6767 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6768 ts->cfltime_local = cfltime; 6769 ts->cfltime = -1.; 6770 PetscFunctionReturn(0); 6771 } 6772 6773 #undef __FUNCT__ 6774 #define __FUNCT__ "TSGetCFLTime" 6775 /*@ 6776 TSGetCFLTime - Get the maximum stable time step according to CFL criteria applied to forward Euler 6777 6778 Collective on TS 6779 6780 Input Arguments: 6781 . ts - time stepping context 6782 6783 Output Arguments: 6784 . cfltime - maximum stable time step for forward Euler 6785 6786 Level: advanced 6787 6788 .seealso: TSSetCFLTimeLocal() 6789 @*/ 6790 PetscErrorCode TSGetCFLTime(TS ts,PetscReal *cfltime) 6791 { 6792 PetscErrorCode ierr; 6793 6794 PetscFunctionBegin; 6795 if (ts->cfltime < 0) { 6796 ierr = MPIU_Allreduce(&ts->cfltime_local,&ts->cfltime,1,MPIU_REAL,MPIU_MIN,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6797 } 6798 *cfltime = ts->cfltime; 6799 PetscFunctionReturn(0); 6800 } 6801 6802 #undef __FUNCT__ 6803 #define __FUNCT__ "TSVISetVariableBounds" 6804 /*@ 6805 TSVISetVariableBounds - Sets the lower and upper bounds for the solution vector. xl <= x <= xu 6806 6807 Input Parameters: 6808 . ts - the TS context. 6809 . xl - lower bound. 6810 . xu - upper bound. 6811 6812 Notes: 6813 If this routine is not called then the lower and upper bounds are set to 6814 PETSC_NINFINITY and PETSC_INFINITY respectively during SNESSetUp(). 6815 6816 Level: advanced 6817 6818 @*/ 6819 PetscErrorCode TSVISetVariableBounds(TS ts, Vec xl, Vec xu) 6820 { 6821 PetscErrorCode ierr; 6822 SNES snes; 6823 6824 PetscFunctionBegin; 6825 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 6826 ierr = SNESVISetVariableBounds(snes,xl,xu);CHKERRQ(ierr); 6827 PetscFunctionReturn(0); 6828 } 6829 6830 #if defined(PETSC_HAVE_MATLAB_ENGINE) 6831 #include <mex.h> 6832 6833 typedef struct {char *funcname; mxArray *ctx;} TSMatlabContext; 6834 6835 #undef __FUNCT__ 6836 #define __FUNCT__ "TSComputeFunction_Matlab" 6837 /* 6838 TSComputeFunction_Matlab - Calls the function that has been set with 6839 TSSetFunctionMatlab(). 6840 6841 Collective on TS 6842 6843 Input Parameters: 6844 + snes - the TS context 6845 - u - input vector 6846 6847 Output Parameter: 6848 . y - function vector, as set by TSSetFunction() 6849 6850 Notes: 6851 TSComputeFunction() is typically used within nonlinear solvers 6852 implementations, so most users would not generally call this routine 6853 themselves. 6854 6855 Level: developer 6856 6857 .keywords: TS, nonlinear, compute, function 6858 6859 .seealso: TSSetFunction(), TSGetFunction() 6860 */ 6861 PetscErrorCode TSComputeFunction_Matlab(TS snes,PetscReal time,Vec u,Vec udot,Vec y, void *ctx) 6862 { 6863 PetscErrorCode ierr; 6864 TSMatlabContext *sctx = (TSMatlabContext*)ctx; 6865 int nlhs = 1,nrhs = 7; 6866 mxArray *plhs[1],*prhs[7]; 6867 long long int lx = 0,lxdot = 0,ly = 0,ls = 0; 6868 6869 PetscFunctionBegin; 6870 PetscValidHeaderSpecific(snes,TS_CLASSID,1); 6871 PetscValidHeaderSpecific(u,VEC_CLASSID,3); 6872 PetscValidHeaderSpecific(udot,VEC_CLASSID,4); 6873 PetscValidHeaderSpecific(y,VEC_CLASSID,5); 6874 PetscCheckSameComm(snes,1,u,3); 6875 PetscCheckSameComm(snes,1,y,5); 6876 6877 ierr = PetscMemcpy(&ls,&snes,sizeof(snes));CHKERRQ(ierr); 6878 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 6879 ierr = PetscMemcpy(&lxdot,&udot,sizeof(udot));CHKERRQ(ierr); 6880 ierr = PetscMemcpy(&ly,&y,sizeof(u));CHKERRQ(ierr); 6881 6882 prhs[0] = mxCreateDoubleScalar((double)ls); 6883 prhs[1] = mxCreateDoubleScalar(time); 6884 prhs[2] = mxCreateDoubleScalar((double)lx); 6885 prhs[3] = mxCreateDoubleScalar((double)lxdot); 6886 prhs[4] = mxCreateDoubleScalar((double)ly); 6887 prhs[5] = mxCreateString(sctx->funcname); 6888 prhs[6] = sctx->ctx; 6889 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSComputeFunctionInternal");CHKERRQ(ierr); 6890 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 6891 mxDestroyArray(prhs[0]); 6892 mxDestroyArray(prhs[1]); 6893 mxDestroyArray(prhs[2]); 6894 mxDestroyArray(prhs[3]); 6895 mxDestroyArray(prhs[4]); 6896 mxDestroyArray(prhs[5]); 6897 mxDestroyArray(plhs[0]); 6898 PetscFunctionReturn(0); 6899 } 6900 6901 6902 #undef __FUNCT__ 6903 #define __FUNCT__ "TSSetFunctionMatlab" 6904 /* 6905 TSSetFunctionMatlab - Sets the function evaluation routine and function 6906 vector for use by the TS routines in solving ODEs 6907 equations from MATLAB. Here the function is a string containing the name of a MATLAB function 6908 6909 Logically Collective on TS 6910 6911 Input Parameters: 6912 + ts - the TS context 6913 - func - function evaluation routine 6914 6915 Calling sequence of func: 6916 $ func (TS ts,PetscReal time,Vec u,Vec udot,Vec f,void *ctx); 6917 6918 Level: beginner 6919 6920 .keywords: TS, nonlinear, set, function 6921 6922 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 6923 */ 6924 PetscErrorCode TSSetFunctionMatlab(TS ts,const char *func,mxArray *ctx) 6925 { 6926 PetscErrorCode ierr; 6927 TSMatlabContext *sctx; 6928 6929 PetscFunctionBegin; 6930 /* currently sctx is memory bleed */ 6931 ierr = PetscNew(&sctx);CHKERRQ(ierr); 6932 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 6933 /* 6934 This should work, but it doesn't 6935 sctx->ctx = ctx; 6936 mexMakeArrayPersistent(sctx->ctx); 6937 */ 6938 sctx->ctx = mxDuplicateArray(ctx); 6939 6940 ierr = TSSetIFunction(ts,NULL,TSComputeFunction_Matlab,sctx);CHKERRQ(ierr); 6941 PetscFunctionReturn(0); 6942 } 6943 6944 #undef __FUNCT__ 6945 #define __FUNCT__ "TSComputeJacobian_Matlab" 6946 /* 6947 TSComputeJacobian_Matlab - Calls the function that has been set with 6948 TSSetJacobianMatlab(). 6949 6950 Collective on TS 6951 6952 Input Parameters: 6953 + ts - the TS context 6954 . u - input vector 6955 . A, B - the matrices 6956 - ctx - user context 6957 6958 Level: developer 6959 6960 .keywords: TS, nonlinear, compute, function 6961 6962 .seealso: TSSetFunction(), TSGetFunction() 6963 @*/ 6964 PetscErrorCode TSComputeJacobian_Matlab(TS ts,PetscReal time,Vec u,Vec udot,PetscReal shift,Mat A,Mat B,void *ctx) 6965 { 6966 PetscErrorCode ierr; 6967 TSMatlabContext *sctx = (TSMatlabContext*)ctx; 6968 int nlhs = 2,nrhs = 9; 6969 mxArray *plhs[2],*prhs[9]; 6970 long long int lx = 0,lxdot = 0,lA = 0,ls = 0, lB = 0; 6971 6972 PetscFunctionBegin; 6973 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6974 PetscValidHeaderSpecific(u,VEC_CLASSID,3); 6975 6976 /* call Matlab function in ctx with arguments u and y */ 6977 6978 ierr = PetscMemcpy(&ls,&ts,sizeof(ts));CHKERRQ(ierr); 6979 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 6980 ierr = PetscMemcpy(&lxdot,&udot,sizeof(u));CHKERRQ(ierr); 6981 ierr = PetscMemcpy(&lA,A,sizeof(u));CHKERRQ(ierr); 6982 ierr = PetscMemcpy(&lB,B,sizeof(u));CHKERRQ(ierr); 6983 6984 prhs[0] = mxCreateDoubleScalar((double)ls); 6985 prhs[1] = mxCreateDoubleScalar((double)time); 6986 prhs[2] = mxCreateDoubleScalar((double)lx); 6987 prhs[3] = mxCreateDoubleScalar((double)lxdot); 6988 prhs[4] = mxCreateDoubleScalar((double)shift); 6989 prhs[5] = mxCreateDoubleScalar((double)lA); 6990 prhs[6] = mxCreateDoubleScalar((double)lB); 6991 prhs[7] = mxCreateString(sctx->funcname); 6992 prhs[8] = sctx->ctx; 6993 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSComputeJacobianInternal");CHKERRQ(ierr); 6994 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 6995 mxDestroyArray(prhs[0]); 6996 mxDestroyArray(prhs[1]); 6997 mxDestroyArray(prhs[2]); 6998 mxDestroyArray(prhs[3]); 6999 mxDestroyArray(prhs[4]); 7000 mxDestroyArray(prhs[5]); 7001 mxDestroyArray(prhs[6]); 7002 mxDestroyArray(prhs[7]); 7003 mxDestroyArray(plhs[0]); 7004 mxDestroyArray(plhs[1]); 7005 PetscFunctionReturn(0); 7006 } 7007 7008 7009 #undef __FUNCT__ 7010 #define __FUNCT__ "TSSetJacobianMatlab" 7011 /* 7012 TSSetJacobianMatlab - Sets the Jacobian function evaluation routine and two empty Jacobian matrices 7013 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 7014 7015 Logically Collective on TS 7016 7017 Input Parameters: 7018 + ts - the TS context 7019 . A,B - Jacobian matrices 7020 . func - function evaluation routine 7021 - ctx - user context 7022 7023 Calling sequence of func: 7024 $ flag = func (TS ts,PetscReal time,Vec u,Vec udot,Mat A,Mat B,void *ctx); 7025 7026 7027 Level: developer 7028 7029 .keywords: TS, nonlinear, set, function 7030 7031 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 7032 */ 7033 PetscErrorCode TSSetJacobianMatlab(TS ts,Mat A,Mat B,const char *func,mxArray *ctx) 7034 { 7035 PetscErrorCode ierr; 7036 TSMatlabContext *sctx; 7037 7038 PetscFunctionBegin; 7039 /* currently sctx is memory bleed */ 7040 ierr = PetscNew(&sctx);CHKERRQ(ierr); 7041 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 7042 /* 7043 This should work, but it doesn't 7044 sctx->ctx = ctx; 7045 mexMakeArrayPersistent(sctx->ctx); 7046 */ 7047 sctx->ctx = mxDuplicateArray(ctx); 7048 7049 ierr = TSSetIJacobian(ts,A,B,TSComputeJacobian_Matlab,sctx);CHKERRQ(ierr); 7050 PetscFunctionReturn(0); 7051 } 7052 7053 #undef __FUNCT__ 7054 #define __FUNCT__ "TSMonitor_Matlab" 7055 /* 7056 TSMonitor_Matlab - Calls the function that has been set with TSMonitorSetMatlab(). 7057 7058 Collective on TS 7059 7060 .seealso: TSSetFunction(), TSGetFunction() 7061 @*/ 7062 PetscErrorCode TSMonitor_Matlab(TS ts,PetscInt it, PetscReal time,Vec u, void *ctx) 7063 { 7064 PetscErrorCode ierr; 7065 TSMatlabContext *sctx = (TSMatlabContext*)ctx; 7066 int nlhs = 1,nrhs = 6; 7067 mxArray *plhs[1],*prhs[6]; 7068 long long int lx = 0,ls = 0; 7069 7070 PetscFunctionBegin; 7071 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 7072 PetscValidHeaderSpecific(u,VEC_CLASSID,4); 7073 7074 ierr = PetscMemcpy(&ls,&ts,sizeof(ts));CHKERRQ(ierr); 7075 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 7076 7077 prhs[0] = mxCreateDoubleScalar((double)ls); 7078 prhs[1] = mxCreateDoubleScalar((double)it); 7079 prhs[2] = mxCreateDoubleScalar((double)time); 7080 prhs[3] = mxCreateDoubleScalar((double)lx); 7081 prhs[4] = mxCreateString(sctx->funcname); 7082 prhs[5] = sctx->ctx; 7083 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSMonitorInternal");CHKERRQ(ierr); 7084 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 7085 mxDestroyArray(prhs[0]); 7086 mxDestroyArray(prhs[1]); 7087 mxDestroyArray(prhs[2]); 7088 mxDestroyArray(prhs[3]); 7089 mxDestroyArray(prhs[4]); 7090 mxDestroyArray(plhs[0]); 7091 PetscFunctionReturn(0); 7092 } 7093 7094 7095 #undef __FUNCT__ 7096 #define __FUNCT__ "TSMonitorSetMatlab" 7097 /* 7098 TSMonitorSetMatlab - Sets the monitor function from Matlab 7099 7100 Level: developer 7101 7102 .keywords: TS, nonlinear, set, function 7103 7104 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 7105 */ 7106 PetscErrorCode TSMonitorSetMatlab(TS ts,const char *func,mxArray *ctx) 7107 { 7108 PetscErrorCode ierr; 7109 TSMatlabContext *sctx; 7110 7111 PetscFunctionBegin; 7112 /* currently sctx is memory bleed */ 7113 ierr = PetscNew(&sctx);CHKERRQ(ierr); 7114 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 7115 /* 7116 This should work, but it doesn't 7117 sctx->ctx = ctx; 7118 mexMakeArrayPersistent(sctx->ctx); 7119 */ 7120 sctx->ctx = mxDuplicateArray(ctx); 7121 7122 ierr = TSMonitorSet(ts,TSMonitor_Matlab,sctx,NULL);CHKERRQ(ierr); 7123 PetscFunctionReturn(0); 7124 } 7125 #endif 7126 7127 #undef __FUNCT__ 7128 #define __FUNCT__ "TSMonitorLGSolution" 7129 /*@C 7130 TSMonitorLGSolution - Monitors progress of the TS solvers by plotting each component of the solution vector 7131 in a time based line graph 7132 7133 Collective on TS 7134 7135 Input Parameters: 7136 + ts - the TS context 7137 . step - current time-step 7138 . ptime - current time 7139 . u - current solution 7140 - dctx - the TSMonitorLGCtx object that contains all the options for the monitoring, this is created with TSMonitorLGCtxCreate() 7141 7142 Options Database: 7143 . -ts_monitor_lg_solution_variables 7144 7145 Level: intermediate 7146 7147 Notes: Each process in a parallel run displays its component solutions in a separate window 7148 7149 .keywords: TS, vector, monitor, view 7150 7151 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGCtxCreate(), TSMonitorLGCtxSetVariableNames(), TSMonitorLGCtxGetVariableNames(), 7152 TSMonitorLGSetVariableNames(), TSMonitorLGGetVariableNames(), TSMonitorLGSetDisplayVariables(), TSMonitorLGCtxSetDisplayVariables(), 7153 TSMonitorLGCtxSetTransform(), TSMonitorLGSetTransform(), TSMonitorLGError(), TSMonitorLGSNESIterations(), TSMonitorLGKSPIterations(), 7154 TSMonitorEnvelopeCtxCreate(), TSMonitorEnvelopeGetBounds(), TSMonitorEnvelopeCtxDestroy(), TSMonitorEnvelop() 7155 @*/ 7156 PetscErrorCode TSMonitorLGSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dctx) 7157 { 7158 PetscErrorCode ierr; 7159 TSMonitorLGCtx ctx = (TSMonitorLGCtx)dctx; 7160 const PetscScalar *yy; 7161 Vec v; 7162 7163 PetscFunctionBegin; 7164 if (step < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */ 7165 if (!step) { 7166 PetscDrawAxis axis; 7167 PetscInt dim; 7168 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 7169 ierr = PetscDrawAxisSetLabels(axis,"Solution as function of time","Time","Solution");CHKERRQ(ierr); 7170 if (!ctx->names) { 7171 PetscBool flg; 7172 /* user provides names of variables to plot but no names has been set so assume names are integer values */ 7173 ierr = PetscOptionsHasName(((PetscObject)ts)->options,((PetscObject)ts)->prefix,"-ts_monitor_lg_solution_variables",&flg);CHKERRQ(ierr); 7174 if (flg) { 7175 PetscInt i,n; 7176 char **names; 7177 ierr = VecGetSize(u,&n);CHKERRQ(ierr); 7178 ierr = PetscMalloc1(n+1,&names);CHKERRQ(ierr); 7179 for (i=0; i<n; i++) { 7180 ierr = PetscMalloc1(5,&names[i]);CHKERRQ(ierr); 7181 ierr = PetscSNPrintf(names[i],5,"%D",i);CHKERRQ(ierr); 7182 } 7183 names[n] = NULL; 7184 ctx->names = names; 7185 } 7186 } 7187 if (ctx->names && !ctx->displaynames) { 7188 char **displaynames; 7189 PetscBool flg; 7190 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 7191 ierr = PetscMalloc1(dim+1,&displaynames);CHKERRQ(ierr); 7192 ierr = PetscMemzero(displaynames,(dim+1)*sizeof(char*));CHKERRQ(ierr); 7193 ierr = PetscOptionsGetStringArray(((PetscObject)ts)->options,((PetscObject)ts)->prefix,"-ts_monitor_lg_solution_variables",displaynames,&dim,&flg);CHKERRQ(ierr); 7194 if (flg) { 7195 ierr = TSMonitorLGCtxSetDisplayVariables(ctx,(const char *const *)displaynames);CHKERRQ(ierr); 7196 } 7197 ierr = PetscStrArrayDestroy(&displaynames);CHKERRQ(ierr); 7198 } 7199 if (ctx->displaynames) { 7200 ierr = PetscDrawLGSetDimension(ctx->lg,ctx->ndisplayvariables);CHKERRQ(ierr); 7201 ierr = PetscDrawLGSetLegend(ctx->lg,(const char *const *)ctx->displaynames);CHKERRQ(ierr); 7202 } else if (ctx->names) { 7203 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 7204 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 7205 ierr = PetscDrawLGSetLegend(ctx->lg,(const char *const *)ctx->names);CHKERRQ(ierr); 7206 } else { 7207 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 7208 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 7209 } 7210 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 7211 } 7212 7213 if (!ctx->transform) v = u; 7214 else {ierr = (*ctx->transform)(ctx->transformctx,u,&v);CHKERRQ(ierr);} 7215 ierr = VecGetArrayRead(v,&yy);CHKERRQ(ierr); 7216 if (ctx->displaynames) { 7217 PetscInt i; 7218 for (i=0; i<ctx->ndisplayvariables; i++) 7219 ctx->displayvalues[i] = PetscRealPart(yy[ctx->displayvariables[i]]); 7220 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,ctx->displayvalues);CHKERRQ(ierr); 7221 } else { 7222 #if defined(PETSC_USE_COMPLEX) 7223 PetscInt i,n; 7224 PetscReal *yreal; 7225 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 7226 ierr = PetscMalloc1(n,&yreal);CHKERRQ(ierr); 7227 for (i=0; i<n; i++) yreal[i] = PetscRealPart(yy[i]); 7228 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yreal);CHKERRQ(ierr); 7229 ierr = PetscFree(yreal);CHKERRQ(ierr); 7230 #else 7231 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yy);CHKERRQ(ierr); 7232 #endif 7233 } 7234 ierr = VecRestoreArrayRead(v,&yy);CHKERRQ(ierr); 7235 if (ctx->transform) {ierr = VecDestroy(&v);CHKERRQ(ierr);} 7236 7237 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 7238 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 7239 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 7240 } 7241 PetscFunctionReturn(0); 7242 } 7243 7244 7245 #undef __FUNCT__ 7246 #define __FUNCT__ "TSMonitorLGSetVariableNames" 7247 /*@C 7248 TSMonitorLGSetVariableNames - Sets the name of each component in the solution vector so that it may be displayed in the plot 7249 7250 Collective on TS 7251 7252 Input Parameters: 7253 + ts - the TS context 7254 - names - the names of the components, final string must be NULL 7255 7256 Level: intermediate 7257 7258 Notes: If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored 7259 7260 .keywords: TS, vector, monitor, view 7261 7262 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables(), TSMonitorLGCtxSetVariableNames() 7263 @*/ 7264 PetscErrorCode TSMonitorLGSetVariableNames(TS ts,const char * const *names) 7265 { 7266 PetscErrorCode ierr; 7267 PetscInt i; 7268 7269 PetscFunctionBegin; 7270 for (i=0; i<ts->numbermonitors; i++) { 7271 if (ts->monitor[i] == TSMonitorLGSolution) { 7272 ierr = TSMonitorLGCtxSetVariableNames((TSMonitorLGCtx)ts->monitorcontext[i],names);CHKERRQ(ierr); 7273 break; 7274 } 7275 } 7276 PetscFunctionReturn(0); 7277 } 7278 7279 #undef __FUNCT__ 7280 #define __FUNCT__ "TSMonitorLGCtxSetVariableNames" 7281 /*@C 7282 TSMonitorLGCtxSetVariableNames - Sets the name of each component in the solution vector so that it may be displayed in the plot 7283 7284 Collective on TS 7285 7286 Input Parameters: 7287 + ts - the TS context 7288 - names - the names of the components, final string must be NULL 7289 7290 Level: intermediate 7291 7292 .keywords: TS, vector, monitor, view 7293 7294 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables(), TSMonitorLGSetVariableNames() 7295 @*/ 7296 PetscErrorCode TSMonitorLGCtxSetVariableNames(TSMonitorLGCtx ctx,const char * const *names) 7297 { 7298 PetscErrorCode ierr; 7299 7300 PetscFunctionBegin; 7301 ierr = PetscStrArrayDestroy(&ctx->names);CHKERRQ(ierr); 7302 ierr = PetscStrArrayallocpy(names,&ctx->names);CHKERRQ(ierr); 7303 PetscFunctionReturn(0); 7304 } 7305 7306 #undef __FUNCT__ 7307 #define __FUNCT__ "TSMonitorLGGetVariableNames" 7308 /*@C 7309 TSMonitorLGGetVariableNames - Gets the name of each component in the solution vector so that it may be displayed in the plot 7310 7311 Collective on TS 7312 7313 Input Parameter: 7314 . ts - the TS context 7315 7316 Output Parameter: 7317 . names - the names of the components, final string must be NULL 7318 7319 Level: intermediate 7320 7321 Notes: If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored 7322 7323 .keywords: TS, vector, monitor, view 7324 7325 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables() 7326 @*/ 7327 PetscErrorCode TSMonitorLGGetVariableNames(TS ts,const char *const **names) 7328 { 7329 PetscInt i; 7330 7331 PetscFunctionBegin; 7332 *names = NULL; 7333 for (i=0; i<ts->numbermonitors; i++) { 7334 if (ts->monitor[i] == TSMonitorLGSolution) { 7335 TSMonitorLGCtx ctx = (TSMonitorLGCtx) ts->monitorcontext[i]; 7336 *names = (const char *const *)ctx->names; 7337 break; 7338 } 7339 } 7340 PetscFunctionReturn(0); 7341 } 7342 7343 #undef __FUNCT__ 7344 #define __FUNCT__ "TSMonitorLGCtxSetDisplayVariables" 7345 /*@C 7346 TSMonitorLGCtxSetDisplayVariables - Sets the variables that are to be display in the monitor 7347 7348 Collective on TS 7349 7350 Input Parameters: 7351 + ctx - the TSMonitorLG context 7352 . displaynames - the names of the components, final string must be NULL 7353 7354 Level: intermediate 7355 7356 .keywords: TS, vector, monitor, view 7357 7358 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames() 7359 @*/ 7360 PetscErrorCode TSMonitorLGCtxSetDisplayVariables(TSMonitorLGCtx ctx,const char * const *displaynames) 7361 { 7362 PetscInt j = 0,k; 7363 PetscErrorCode ierr; 7364 7365 PetscFunctionBegin; 7366 if (!ctx->names) PetscFunctionReturn(0); 7367 ierr = PetscStrArrayDestroy(&ctx->displaynames);CHKERRQ(ierr); 7368 ierr = PetscStrArrayallocpy(displaynames,&ctx->displaynames);CHKERRQ(ierr); 7369 while (displaynames[j]) j++; 7370 ctx->ndisplayvariables = j; 7371 ierr = PetscMalloc1(ctx->ndisplayvariables,&ctx->displayvariables);CHKERRQ(ierr); 7372 ierr = PetscMalloc1(ctx->ndisplayvariables,&ctx->displayvalues);CHKERRQ(ierr); 7373 j = 0; 7374 while (displaynames[j]) { 7375 k = 0; 7376 while (ctx->names[k]) { 7377 PetscBool flg; 7378 ierr = PetscStrcmp(displaynames[j],ctx->names[k],&flg);CHKERRQ(ierr); 7379 if (flg) { 7380 ctx->displayvariables[j] = k; 7381 break; 7382 } 7383 k++; 7384 } 7385 j++; 7386 } 7387 PetscFunctionReturn(0); 7388 } 7389 7390 7391 #undef __FUNCT__ 7392 #define __FUNCT__ "TSMonitorLGSetDisplayVariables" 7393 /*@C 7394 TSMonitorLGSetDisplayVariables - Sets the variables that are to be display in the monitor 7395 7396 Collective on TS 7397 7398 Input Parameters: 7399 + ts - the TS context 7400 . displaynames - the names of the components, final string must be NULL 7401 7402 Notes: If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored 7403 7404 Level: intermediate 7405 7406 .keywords: TS, vector, monitor, view 7407 7408 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames() 7409 @*/ 7410 PetscErrorCode TSMonitorLGSetDisplayVariables(TS ts,const char * const *displaynames) 7411 { 7412 PetscInt i; 7413 PetscErrorCode ierr; 7414 7415 PetscFunctionBegin; 7416 for (i=0; i<ts->numbermonitors; i++) { 7417 if (ts->monitor[i] == TSMonitorLGSolution) { 7418 ierr = TSMonitorLGCtxSetDisplayVariables((TSMonitorLGCtx)ts->monitorcontext[i],displaynames);CHKERRQ(ierr); 7419 break; 7420 } 7421 } 7422 PetscFunctionReturn(0); 7423 } 7424 7425 #undef __FUNCT__ 7426 #define __FUNCT__ "TSMonitorLGSetTransform" 7427 /*@C 7428 TSMonitorLGSetTransform - Solution vector will be transformed by provided function before being displayed 7429 7430 Collective on TS 7431 7432 Input Parameters: 7433 + ts - the TS context 7434 . transform - the transform function 7435 . destroy - function to destroy the optional context 7436 - ctx - optional context used by transform function 7437 7438 Notes: If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored 7439 7440 Level: intermediate 7441 7442 .keywords: TS, vector, monitor, view 7443 7444 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames(), TSMonitorLGCtxSetTransform() 7445 @*/ 7446 PetscErrorCode TSMonitorLGSetTransform(TS ts,PetscErrorCode (*transform)(void*,Vec,Vec*),PetscErrorCode (*destroy)(void*),void *tctx) 7447 { 7448 PetscInt i; 7449 PetscErrorCode ierr; 7450 7451 PetscFunctionBegin; 7452 for (i=0; i<ts->numbermonitors; i++) { 7453 if (ts->monitor[i] == TSMonitorLGSolution) { 7454 ierr = TSMonitorLGCtxSetTransform((TSMonitorLGCtx)ts->monitorcontext[i],transform,destroy,tctx);CHKERRQ(ierr); 7455 } 7456 } 7457 PetscFunctionReturn(0); 7458 } 7459 7460 #undef __FUNCT__ 7461 #define __FUNCT__ "TSMonitorLGCtxSetTransform" 7462 /*@C 7463 TSMonitorLGCtxSetTransform - Solution vector will be transformed by provided function before being displayed 7464 7465 Collective on TSLGCtx 7466 7467 Input Parameters: 7468 + ts - the TS context 7469 . transform - the transform function 7470 . destroy - function to destroy the optional context 7471 - ctx - optional context used by transform function 7472 7473 Level: intermediate 7474 7475 .keywords: TS, vector, monitor, view 7476 7477 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames(), TSMonitorLGSetTransform() 7478 @*/ 7479 PetscErrorCode TSMonitorLGCtxSetTransform(TSMonitorLGCtx ctx,PetscErrorCode (*transform)(void*,Vec,Vec*),PetscErrorCode (*destroy)(void*),void *tctx) 7480 { 7481 PetscFunctionBegin; 7482 ctx->transform = transform; 7483 ctx->transformdestroy = destroy; 7484 ctx->transformctx = tctx; 7485 PetscFunctionReturn(0); 7486 } 7487 7488 #undef __FUNCT__ 7489 #define __FUNCT__ "TSMonitorLGError" 7490 /*@C 7491 TSMonitorLGError - Monitors progress of the TS solvers by plotting each component of the solution vector 7492 in a time based line graph 7493 7494 Collective on TS 7495 7496 Input Parameters: 7497 + ts - the TS context 7498 . step - current time-step 7499 . ptime - current time 7500 . u - current solution 7501 - dctx - TSMonitorLGCtx object created with TSMonitorLGCtxCreate() 7502 7503 Level: intermediate 7504 7505 Notes: Each process in a parallel run displays its component errors in a separate window 7506 7507 The user must provide the solution using TSSetSolutionFunction() to use this monitor. 7508 7509 Options Database Keys: 7510 . -ts_monitor_lg_error - create a graphical monitor of error history 7511 7512 .keywords: TS, vector, monitor, view 7513 7514 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSSetSolutionFunction() 7515 @*/ 7516 PetscErrorCode TSMonitorLGError(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 7517 { 7518 PetscErrorCode ierr; 7519 TSMonitorLGCtx ctx = (TSMonitorLGCtx)dummy; 7520 const PetscScalar *yy; 7521 Vec y; 7522 7523 PetscFunctionBegin; 7524 if (!step) { 7525 PetscDrawAxis axis; 7526 PetscInt dim; 7527 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 7528 ierr = PetscDrawAxisSetLabels(axis,"Error in solution as function of time","Time","Solution");CHKERRQ(ierr); 7529 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 7530 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 7531 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 7532 } 7533 ierr = VecDuplicate(u,&y);CHKERRQ(ierr); 7534 ierr = TSComputeSolutionFunction(ts,ptime,y);CHKERRQ(ierr); 7535 ierr = VecAXPY(y,-1.0,u);CHKERRQ(ierr); 7536 ierr = VecGetArrayRead(y,&yy);CHKERRQ(ierr); 7537 #if defined(PETSC_USE_COMPLEX) 7538 { 7539 PetscReal *yreal; 7540 PetscInt i,n; 7541 ierr = VecGetLocalSize(y,&n);CHKERRQ(ierr); 7542 ierr = PetscMalloc1(n,&yreal);CHKERRQ(ierr); 7543 for (i=0; i<n; i++) yreal[i] = PetscRealPart(yy[i]); 7544 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yreal);CHKERRQ(ierr); 7545 ierr = PetscFree(yreal);CHKERRQ(ierr); 7546 } 7547 #else 7548 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yy);CHKERRQ(ierr); 7549 #endif 7550 ierr = VecRestoreArrayRead(y,&yy);CHKERRQ(ierr); 7551 ierr = VecDestroy(&y);CHKERRQ(ierr); 7552 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 7553 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 7554 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 7555 } 7556 PetscFunctionReturn(0); 7557 } 7558 7559 #undef __FUNCT__ 7560 #define __FUNCT__ "TSMonitorLGSNESIterations" 7561 PetscErrorCode TSMonitorLGSNESIterations(TS ts,PetscInt n,PetscReal ptime,Vec v,void *monctx) 7562 { 7563 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 7564 PetscReal x = ptime,y; 7565 PetscErrorCode ierr; 7566 PetscInt its; 7567 7568 PetscFunctionBegin; 7569 if (n < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */ 7570 if (!n) { 7571 PetscDrawAxis axis; 7572 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 7573 ierr = PetscDrawAxisSetLabels(axis,"Nonlinear iterations as function of time","Time","SNES Iterations");CHKERRQ(ierr); 7574 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 7575 ctx->snes_its = 0; 7576 } 7577 ierr = TSGetSNESIterations(ts,&its);CHKERRQ(ierr); 7578 y = its - ctx->snes_its; 7579 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 7580 if (((ctx->howoften > 0) && (!(n % ctx->howoften)) && (n > -1)) || ((ctx->howoften == -1) && (n == -1))) { 7581 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 7582 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 7583 } 7584 ctx->snes_its = its; 7585 PetscFunctionReturn(0); 7586 } 7587 7588 #undef __FUNCT__ 7589 #define __FUNCT__ "TSMonitorLGKSPIterations" 7590 PetscErrorCode TSMonitorLGKSPIterations(TS ts,PetscInt n,PetscReal ptime,Vec v,void *monctx) 7591 { 7592 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 7593 PetscReal x = ptime,y; 7594 PetscErrorCode ierr; 7595 PetscInt its; 7596 7597 PetscFunctionBegin; 7598 if (n < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */ 7599 if (!n) { 7600 PetscDrawAxis axis; 7601 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 7602 ierr = PetscDrawAxisSetLabels(axis,"Linear iterations as function of time","Time","KSP Iterations");CHKERRQ(ierr); 7603 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 7604 ctx->ksp_its = 0; 7605 } 7606 ierr = TSGetKSPIterations(ts,&its);CHKERRQ(ierr); 7607 y = its - ctx->ksp_its; 7608 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 7609 if (((ctx->howoften > 0) && (!(n % ctx->howoften)) && (n > -1)) || ((ctx->howoften == -1) && (n == -1))) { 7610 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 7611 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 7612 } 7613 ctx->ksp_its = its; 7614 PetscFunctionReturn(0); 7615 } 7616 7617 #undef __FUNCT__ 7618 #define __FUNCT__ "TSComputeLinearStability" 7619 /*@ 7620 TSComputeLinearStability - computes the linear stability function at a point 7621 7622 Collective on TS and Vec 7623 7624 Input Parameters: 7625 + ts - the TS context 7626 - xr,xi - real and imaginary part of input arguments 7627 7628 Output Parameters: 7629 . yr,yi - real and imaginary part of function value 7630 7631 Level: developer 7632 7633 .keywords: TS, compute 7634 7635 .seealso: TSSetRHSFunction(), TSComputeIFunction() 7636 @*/ 7637 PetscErrorCode TSComputeLinearStability(TS ts,PetscReal xr,PetscReal xi,PetscReal *yr,PetscReal *yi) 7638 { 7639 PetscErrorCode ierr; 7640 7641 PetscFunctionBegin; 7642 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 7643 if (!ts->ops->linearstability) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Linearized stability function not provided for this method"); 7644 ierr = (*ts->ops->linearstability)(ts,xr,xi,yr,yi);CHKERRQ(ierr); 7645 PetscFunctionReturn(0); 7646 } 7647 7648 /* ------------------------------------------------------------------------*/ 7649 #undef __FUNCT__ 7650 #define __FUNCT__ "TSMonitorEnvelopeCtxCreate" 7651 /*@C 7652 TSMonitorEnvelopeCtxCreate - Creates a context for use with TSMonitorEnvelope() 7653 7654 Collective on TS 7655 7656 Input Parameters: 7657 . ts - the ODE solver object 7658 7659 Output Parameter: 7660 . ctx - the context 7661 7662 Level: intermediate 7663 7664 .keywords: TS, monitor, line graph, residual, seealso 7665 7666 .seealso: TSMonitorLGTimeStep(), TSMonitorSet(), TSMonitorLGSolution(), TSMonitorLGError() 7667 7668 @*/ 7669 PetscErrorCode TSMonitorEnvelopeCtxCreate(TS ts,TSMonitorEnvelopeCtx *ctx) 7670 { 7671 PetscErrorCode ierr; 7672 7673 PetscFunctionBegin; 7674 ierr = PetscNew(ctx);CHKERRQ(ierr); 7675 PetscFunctionReturn(0); 7676 } 7677 7678 #undef __FUNCT__ 7679 #define __FUNCT__ "TSMonitorEnvelope" 7680 /*@C 7681 TSMonitorEnvelope - Monitors the maximum and minimum value of each component of the solution 7682 7683 Collective on TS 7684 7685 Input Parameters: 7686 + ts - the TS context 7687 . step - current time-step 7688 . ptime - current time 7689 . u - current solution 7690 - dctx - the envelope context 7691 7692 Options Database: 7693 . -ts_monitor_envelope 7694 7695 Level: intermediate 7696 7697 Notes: after a solve you can use TSMonitorEnvelopeGetBounds() to access the envelope 7698 7699 .keywords: TS, vector, monitor, view 7700 7701 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorEnvelopeGetBounds(), TSMonitorEnvelopeCtxCreate() 7702 @*/ 7703 PetscErrorCode TSMonitorEnvelope(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dctx) 7704 { 7705 PetscErrorCode ierr; 7706 TSMonitorEnvelopeCtx ctx = (TSMonitorEnvelopeCtx)dctx; 7707 7708 PetscFunctionBegin; 7709 if (!ctx->max) { 7710 ierr = VecDuplicate(u,&ctx->max);CHKERRQ(ierr); 7711 ierr = VecDuplicate(u,&ctx->min);CHKERRQ(ierr); 7712 ierr = VecCopy(u,ctx->max);CHKERRQ(ierr); 7713 ierr = VecCopy(u,ctx->min);CHKERRQ(ierr); 7714 } else { 7715 ierr = VecPointwiseMax(ctx->max,u,ctx->max);CHKERRQ(ierr); 7716 ierr = VecPointwiseMin(ctx->min,u,ctx->min);CHKERRQ(ierr); 7717 } 7718 PetscFunctionReturn(0); 7719 } 7720 7721 7722 #undef __FUNCT__ 7723 #define __FUNCT__ "TSMonitorEnvelopeGetBounds" 7724 /*@C 7725 TSMonitorEnvelopeGetBounds - Gets the bounds for the components of the solution 7726 7727 Collective on TS 7728 7729 Input Parameter: 7730 . ts - the TS context 7731 7732 Output Parameter: 7733 + max - the maximum values 7734 - min - the minimum values 7735 7736 Notes: If the TS does not have a TSMonitorEnvelopeCtx associated with it then this function is ignored 7737 7738 Level: intermediate 7739 7740 .keywords: TS, vector, monitor, view 7741 7742 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables() 7743 @*/ 7744 PetscErrorCode TSMonitorEnvelopeGetBounds(TS ts,Vec *max,Vec *min) 7745 { 7746 PetscInt i; 7747 7748 PetscFunctionBegin; 7749 if (max) *max = NULL; 7750 if (min) *min = NULL; 7751 for (i=0; i<ts->numbermonitors; i++) { 7752 if (ts->monitor[i] == TSMonitorEnvelope) { 7753 TSMonitorEnvelopeCtx ctx = (TSMonitorEnvelopeCtx) ts->monitorcontext[i]; 7754 if (max) *max = ctx->max; 7755 if (min) *min = ctx->min; 7756 break; 7757 } 7758 } 7759 PetscFunctionReturn(0); 7760 } 7761 7762 #undef __FUNCT__ 7763 #define __FUNCT__ "TSMonitorEnvelopeCtxDestroy" 7764 /*@C 7765 TSMonitorEnvelopeCtxDestroy - Destroys a context that was created with TSMonitorEnvelopeCtxCreate(). 7766 7767 Collective on TSMonitorEnvelopeCtx 7768 7769 Input Parameter: 7770 . ctx - the monitor context 7771 7772 Level: intermediate 7773 7774 .keywords: TS, monitor, line graph, destroy 7775 7776 .seealso: TSMonitorLGCtxCreate(), TSMonitorSet(), TSMonitorLGTimeStep() 7777 @*/ 7778 PetscErrorCode TSMonitorEnvelopeCtxDestroy(TSMonitorEnvelopeCtx *ctx) 7779 { 7780 PetscErrorCode ierr; 7781 7782 PetscFunctionBegin; 7783 ierr = VecDestroy(&(*ctx)->min);CHKERRQ(ierr); 7784 ierr = VecDestroy(&(*ctx)->max);CHKERRQ(ierr); 7785 ierr = PetscFree(*ctx);CHKERRQ(ierr); 7786 PetscFunctionReturn(0); 7787 } 7788 7789 #undef __FUNCT__ 7790 #define __FUNCT__ "TSRollBack" 7791 /*@ 7792 TSRollBack - Rolls back one time step 7793 7794 Collective on TS 7795 7796 Input Parameter: 7797 . ts - the TS context obtained from TSCreate() 7798 7799 Level: advanced 7800 7801 .keywords: TS, timestep, rollback 7802 7803 .seealso: TSCreate(), TSSetUp(), TSDestroy(), TSSolve(), TSSetPreStep(), TSSetPreStage(), TSInterpolate() 7804 @*/ 7805 PetscErrorCode TSRollBack(TS ts) 7806 { 7807 PetscErrorCode ierr; 7808 7809 PetscFunctionBegin; 7810 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 7811 if (ts->steprollback) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"TSRollBack already called"); 7812 if (!ts->ops->rollback) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSRollBack not implemented for type '%s'",((PetscObject)ts)->type_name); 7813 ierr = (*ts->ops->rollback)(ts);CHKERRQ(ierr); 7814 ts->time_step = ts->ptime - ts->ptime_prev; 7815 ts->ptime = ts->ptime_prev; 7816 ts->ptime_prev = ts->ptime_prev_rollback; 7817 ts->steps--; ts->total_steps--; 7818 ts->steprollback = PETSC_TRUE; 7819 PetscFunctionReturn(0); 7820 } 7821 7822 #undef __FUNCT__ 7823 #define __FUNCT__ "TSGetStages" 7824 /*@ 7825 TSGetStages - Get the number of stages and stage values 7826 7827 Input Parameter: 7828 . ts - the TS context obtained from TSCreate() 7829 7830 Level: advanced 7831 7832 .keywords: TS, getstages 7833 7834 .seealso: TSCreate() 7835 @*/ 7836 PetscErrorCode TSGetStages(TS ts,PetscInt *ns,Vec **Y) 7837 { 7838 PetscErrorCode ierr; 7839 7840 PetscFunctionBegin; 7841 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 7842 PetscValidPointer(ns,2); 7843 7844 if (!ts->ops->getstages) *ns=0; 7845 else { 7846 ierr = (*ts->ops->getstages)(ts,ns,Y);CHKERRQ(ierr); 7847 } 7848 PetscFunctionReturn(0); 7849 } 7850 7851 #undef __FUNCT__ 7852 #define __FUNCT__ "TSComputeIJacobianDefaultColor" 7853 /*@C 7854 TSComputeIJacobianDefaultColor - Computes the Jacobian using finite differences and coloring to exploit matrix sparsity. 7855 7856 Collective on SNES 7857 7858 Input Parameters: 7859 + ts - the TS context 7860 . t - current timestep 7861 . U - state vector 7862 . Udot - time derivative of state vector 7863 . shift - shift to apply, see note below 7864 - ctx - an optional user context 7865 7866 Output Parameters: 7867 + J - Jacobian matrix (not altered in this routine) 7868 - B - newly computed Jacobian matrix to use with preconditioner (generally the same as J) 7869 7870 Level: intermediate 7871 7872 Notes: 7873 If F(t,U,Udot)=0 is the DAE, the required Jacobian is 7874 7875 dF/dU + shift*dF/dUdot 7876 7877 Most users should not need to explicitly call this routine, as it 7878 is used internally within the nonlinear solvers. 7879 7880 This will first try to get the coloring from the DM. If the DM type has no coloring 7881 routine, then it will try to get the coloring from the matrix. This requires that the 7882 matrix have nonzero entries precomputed. 7883 7884 .keywords: TS, finite differences, Jacobian, coloring, sparse 7885 .seealso: TSSetIJacobian(), MatFDColoringCreate(), MatFDColoringSetFunction() 7886 @*/ 7887 PetscErrorCode TSComputeIJacobianDefaultColor(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat J,Mat B,void *ctx) 7888 { 7889 SNES snes; 7890 MatFDColoring color; 7891 PetscBool hascolor, matcolor = PETSC_FALSE; 7892 PetscErrorCode ierr; 7893 7894 PetscFunctionBegin; 7895 ierr = PetscOptionsGetBool(((PetscObject)ts)->options,((PetscObject) ts)->prefix, "-ts_fd_color_use_mat", &matcolor, NULL);CHKERRQ(ierr); 7896 ierr = PetscObjectQuery((PetscObject) B, "TSMatFDColoring", (PetscObject *) &color);CHKERRQ(ierr); 7897 if (!color) { 7898 DM dm; 7899 ISColoring iscoloring; 7900 7901 ierr = TSGetDM(ts, &dm);CHKERRQ(ierr); 7902 ierr = DMHasColoring(dm, &hascolor);CHKERRQ(ierr); 7903 if (hascolor && !matcolor) { 7904 ierr = DMCreateColoring(dm, IS_COLORING_GLOBAL, &iscoloring);CHKERRQ(ierr); 7905 ierr = MatFDColoringCreate(B, iscoloring, &color);CHKERRQ(ierr); 7906 ierr = MatFDColoringSetFunction(color, (PetscErrorCode (*)(void)) SNESTSFormFunction, (void *) ts);CHKERRQ(ierr); 7907 ierr = MatFDColoringSetFromOptions(color);CHKERRQ(ierr); 7908 ierr = MatFDColoringSetUp(B, iscoloring, color);CHKERRQ(ierr); 7909 ierr = ISColoringDestroy(&iscoloring);CHKERRQ(ierr); 7910 } else { 7911 MatColoring mc; 7912 7913 ierr = MatColoringCreate(B, &mc);CHKERRQ(ierr); 7914 ierr = MatColoringSetDistance(mc, 2);CHKERRQ(ierr); 7915 ierr = MatColoringSetType(mc, MATCOLORINGSL);CHKERRQ(ierr); 7916 ierr = MatColoringSetFromOptions(mc);CHKERRQ(ierr); 7917 ierr = MatColoringApply(mc, &iscoloring);CHKERRQ(ierr); 7918 ierr = MatColoringDestroy(&mc);CHKERRQ(ierr); 7919 ierr = MatFDColoringCreate(B, iscoloring, &color);CHKERRQ(ierr); 7920 ierr = MatFDColoringSetFunction(color, (PetscErrorCode (*)(void)) SNESTSFormFunction, (void *) ts);CHKERRQ(ierr); 7921 ierr = MatFDColoringSetFromOptions(color);CHKERRQ(ierr); 7922 ierr = MatFDColoringSetUp(B, iscoloring, color);CHKERRQ(ierr); 7923 ierr = ISColoringDestroy(&iscoloring);CHKERRQ(ierr); 7924 } 7925 ierr = PetscObjectCompose((PetscObject) B, "TSMatFDColoring", (PetscObject) color);CHKERRQ(ierr); 7926 ierr = PetscObjectDereference((PetscObject) color);CHKERRQ(ierr); 7927 } 7928 ierr = TSGetSNES(ts, &snes);CHKERRQ(ierr); 7929 ierr = MatFDColoringApply(B, color, U, snes);CHKERRQ(ierr); 7930 if (J != B) { 7931 ierr = MatAssemblyBegin(J, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 7932 ierr = MatAssemblyEnd(J, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 7933 } 7934 PetscFunctionReturn(0); 7935 } 7936 7937 #undef __FUNCT__ 7938 #define __FUNCT__ "TSSetFunctionDomainError" 7939 /*@ 7940 TSSetFunctionDomainError - Set the function testing if the current state vector is valid 7941 7942 Input Parameters: 7943 ts - the TS context 7944 func - function called within TSFunctionDomainError 7945 7946 Level: intermediate 7947 7948 .keywords: TS, state, domain 7949 .seealso: TSAdaptCheckStage(), TSFunctionDomainError() 7950 @*/ 7951 7952 PetscErrorCode TSSetFunctionDomainError(TS ts, PetscErrorCode (*func)(TS,PetscReal,Vec,PetscBool*)) 7953 { 7954 PetscFunctionBegin; 7955 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 7956 ts->functiondomainerror = func; 7957 PetscFunctionReturn(0); 7958 } 7959 7960 #undef __FUNCT__ 7961 #define __FUNCT__ "TSFunctionDomainError" 7962 /*@ 7963 TSFunctionDomainError - Check if the current state is valid 7964 7965 Input Parameters: 7966 ts - the TS context 7967 stagetime - time of the simulation 7968 Y - state vector to check. 7969 7970 Output Parameter: 7971 accept - Set to PETSC_FALSE if the current state vector is valid. 7972 7973 Note: 7974 This function should be used to ensure the state is in a valid part of the space. 7975 For example, one can ensure here all values are positive. 7976 7977 Level: advanced 7978 @*/ 7979 PetscErrorCode TSFunctionDomainError(TS ts,PetscReal stagetime,Vec Y,PetscBool* accept) 7980 { 7981 PetscErrorCode ierr; 7982 7983 PetscFunctionBegin; 7984 7985 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 7986 *accept = PETSC_TRUE; 7987 if (ts->functiondomainerror) { 7988 PetscStackCallStandard((*ts->functiondomainerror),(ts,stagetime,Y,accept)); 7989 } 7990 PetscFunctionReturn(0); 7991 } 7992 7993 #undef __FUNCT__ 7994 #define __FUNCT__ "TSClone" 7995 /*@C 7996 TSClone - This function clones a time step object. 7997 7998 Collective on MPI_Comm 7999 8000 Input Parameter: 8001 . tsin - The input TS 8002 8003 Output Parameter: 8004 . tsout - The output TS (cloned) 8005 8006 Notes: 8007 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. 8008 8009 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); 8010 8011 Level: developer 8012 8013 .keywords: TS, clone 8014 .seealso: TSCreate(), TSSetType(), TSSetUp(), TSDestroy(), TSSetProblemType() 8015 @*/ 8016 PetscErrorCode TSClone(TS tsin, TS *tsout) 8017 { 8018 TS t; 8019 PetscErrorCode ierr; 8020 SNES snes_start; 8021 DM dm; 8022 TSType type; 8023 8024 PetscFunctionBegin; 8025 PetscValidPointer(tsin,1); 8026 *tsout = NULL; 8027 8028 ierr = PetscHeaderCreate(t, TS_CLASSID, "TS", "Time stepping", "TS", PetscObjectComm((PetscObject)tsin), TSDestroy, TSView);CHKERRQ(ierr); 8029 8030 /* General TS description */ 8031 t->numbermonitors = 0; 8032 t->setupcalled = 0; 8033 t->ksp_its = 0; 8034 t->snes_its = 0; 8035 t->nwork = 0; 8036 t->rhsjacobian.time = -1e20; 8037 t->rhsjacobian.scale = 1.; 8038 t->ijacobian.shift = 1.; 8039 8040 ierr = TSGetSNES(tsin,&snes_start);CHKERRQ(ierr); 8041 ierr = TSSetSNES(t,snes_start);CHKERRQ(ierr); 8042 8043 ierr = TSGetDM(tsin,&dm);CHKERRQ(ierr); 8044 ierr = TSSetDM(t,dm);CHKERRQ(ierr); 8045 8046 t->adapt = tsin->adapt; 8047 ierr = PetscObjectReference((PetscObject)t->adapt);CHKERRQ(ierr); 8048 8049 t->problem_type = tsin->problem_type; 8050 t->ptime = tsin->ptime; 8051 t->time_step = tsin->time_step; 8052 t->max_time = tsin->max_time; 8053 t->steps = tsin->steps; 8054 t->max_steps = tsin->max_steps; 8055 t->equation_type = tsin->equation_type; 8056 t->atol = tsin->atol; 8057 t->rtol = tsin->rtol; 8058 t->max_snes_failures = tsin->max_snes_failures; 8059 t->max_reject = tsin->max_reject; 8060 t->errorifstepfailed = tsin->errorifstepfailed; 8061 8062 ierr = TSGetType(tsin,&type);CHKERRQ(ierr); 8063 ierr = TSSetType(t,type);CHKERRQ(ierr); 8064 8065 t->vec_sol = NULL; 8066 8067 t->cfltime = tsin->cfltime; 8068 t->cfltime_local = tsin->cfltime_local; 8069 t->exact_final_time = tsin->exact_final_time; 8070 8071 ierr = PetscMemcpy(t->ops,tsin->ops,sizeof(struct _TSOps));CHKERRQ(ierr); 8072 8073 if (((PetscObject)tsin)->fortran_func_pointers) { 8074 PetscInt i; 8075 ierr = PetscMalloc((10)*sizeof(void(*)(void)),&((PetscObject)t)->fortran_func_pointers);CHKERRQ(ierr); 8076 for (i=0; i<10; i++) { 8077 ((PetscObject)t)->fortran_func_pointers[i] = ((PetscObject)tsin)->fortran_func_pointers[i]; 8078 } 8079 } 8080 *tsout = t; 8081 PetscFunctionReturn(0); 8082 } 8083