1 #include <petsc/private/tsimpl.h> /*I "petscts.h" I*/ 2 #include <petscdmshell.h> 3 #include <petscdmda.h> 4 #include <petscviewer.h> 5 #include <petscdraw.h> 6 7 /* Logging support */ 8 PetscClassId TS_CLASSID, DMTS_CLASSID; 9 PetscLogEvent TS_Step, TS_PseudoComputeTimeStep, TS_FunctionEval, TS_JacobianEval; 10 11 const char *const TSExactFinalTimeOptions[] = {"UNSPECIFIED","STEPOVER","INTERPOLATE","MATCHSTEP","TSExactFinalTimeOption","TS_EXACTFINALTIME_",0}; 12 13 /*@C 14 TSMonitorSetFromOptions - Sets a monitor function and viewer appropriate for the type indicated by the user 15 16 Collective on TS 17 18 Input Parameters: 19 + ts - TS object you wish to monitor 20 . name - the monitor type one is seeking 21 . help - message indicating what monitoring is done 22 . manual - manual page for the monitor 23 . monitor - the monitor function 24 - 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 25 26 Level: developer 27 28 .seealso: PetscOptionsGetViewer(), PetscOptionsGetReal(), PetscOptionsHasName(), PetscOptionsGetString(), 29 PetscOptionsGetIntArray(), PetscOptionsGetRealArray(), PetscOptionsBool() 30 PetscOptionsInt(), PetscOptionsString(), PetscOptionsReal(), PetscOptionsBool(), 31 PetscOptionsName(), PetscOptionsBegin(), PetscOptionsEnd(), PetscOptionsHead(), 32 PetscOptionsStringArray(),PetscOptionsRealArray(), PetscOptionsScalar(), 33 PetscOptionsBoolGroupBegin(), PetscOptionsBoolGroup(), PetscOptionsBoolGroupEnd(), 34 PetscOptionsFList(), PetscOptionsEList() 35 @*/ 36 PetscErrorCode TSMonitorSetFromOptions(TS ts,const char name[],const char help[], const char manual[],PetscErrorCode (*monitor)(TS,PetscInt,PetscReal,Vec,PetscViewerAndFormat*),PetscErrorCode (*monitorsetup)(TS,PetscViewerAndFormat*)) 37 { 38 PetscErrorCode ierr; 39 PetscViewer viewer; 40 PetscViewerFormat format; 41 PetscBool flg; 42 43 PetscFunctionBegin; 44 ierr = PetscOptionsGetViewer(PetscObjectComm((PetscObject)ts),((PetscObject) ts)->options,((PetscObject)ts)->prefix,name,&viewer,&format,&flg);CHKERRQ(ierr); 45 if (flg) { 46 PetscViewerAndFormat *vf; 47 ierr = PetscViewerAndFormatCreate(viewer,format,&vf);CHKERRQ(ierr); 48 ierr = PetscObjectDereference((PetscObject)viewer);CHKERRQ(ierr); 49 if (monitorsetup) { 50 ierr = (*monitorsetup)(ts,vf);CHKERRQ(ierr); 51 } 52 ierr = TSMonitorSet(ts,(PetscErrorCode (*)(TS,PetscInt,PetscReal,Vec,void*))monitor,vf,(PetscErrorCode (*)(void**))PetscViewerAndFormatDestroy);CHKERRQ(ierr); 53 } 54 PetscFunctionReturn(0); 55 } 56 57 static PetscErrorCode TSAdaptSetDefaultType(TSAdapt adapt,TSAdaptType default_type) 58 { 59 PetscErrorCode ierr; 60 61 PetscFunctionBegin; 62 PetscValidHeaderSpecific(adapt,TSADAPT_CLASSID,1); 63 PetscValidCharPointer(default_type,2); 64 if (!((PetscObject)adapt)->type_name) { 65 ierr = TSAdaptSetType(adapt,default_type);CHKERRQ(ierr); 66 } 67 PetscFunctionReturn(0); 68 } 69 70 /*@ 71 TSSetFromOptions - Sets various TS parameters from user options. 72 73 Collective on TS 74 75 Input Parameter: 76 . ts - the TS context obtained from TSCreate() 77 78 Options Database Keys: 79 + -ts_type <type> - TSEULER, TSBEULER, TSSUNDIALS, TSPSEUDO, TSCN, TSRK, TSTHETA, TSALPHA, TSGLLE, TSSSP, TSGLEE, TSBSYMP 80 . -ts_save_trajectory - checkpoint the solution at each time-step 81 . -ts_max_time <time> - maximum time to compute to 82 . -ts_max_steps <steps> - maximum number of time-steps to take 83 . -ts_init_time <time> - initial time to start computation 84 . -ts_final_time <time> - final time to compute to (deprecated: use -ts_max_time) 85 . -ts_dt <dt> - initial time step 86 . -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 87 . -ts_max_snes_failures <maxfailures> - Maximum number of nonlinear solve failures allowed 88 . -ts_max_reject <maxrejects> - Maximum number of step rejections before step fails 89 . -ts_error_if_step_fails <true,false> - Error if no step succeeds 90 . -ts_rtol <rtol> - relative tolerance for local truncation error 91 . -ts_atol <atol> Absolute tolerance for local truncation error 92 . -ts_rhs_jacobian_test_mult -mat_shell_test_mult_view - test the Jacobian at each iteration against finite difference with RHS function 93 . -ts_rhs_jacobian_test_mult_transpose -mat_shell_test_mult_transpose_view - test the Jacobian at each iteration against finite difference with RHS function 94 . -ts_adjoint_solve <yes,no> After solving the ODE/DAE solve the adjoint problem (requires -ts_save_trajectory) 95 . -ts_fd_color - Use finite differences with coloring to compute IJacobian 96 . -ts_monitor - print information at each timestep 97 . -ts_monitor_lg_solution - Monitor solution graphically 98 . -ts_monitor_lg_error - Monitor error graphically 99 . -ts_monitor_error - Monitors norm of error 100 . -ts_monitor_lg_timestep - Monitor timestep size graphically 101 . -ts_monitor_lg_timestep_log - Monitor log timestep size graphically 102 . -ts_monitor_lg_snes_iterations - Monitor number nonlinear iterations for each timestep graphically 103 . -ts_monitor_lg_ksp_iterations - Monitor number nonlinear iterations for each timestep graphically 104 . -ts_monitor_sp_eig - Monitor eigenvalues of linearized operator graphically 105 . -ts_monitor_draw_solution - Monitor solution graphically 106 . -ts_monitor_draw_solution_phase <xleft,yleft,xright,yright> - Monitor solution graphically with phase diagram, requires problem with exactly 2 degrees of freedom 107 . -ts_monitor_draw_error - Monitor error graphically, requires use to have provided TSSetSolutionFunction() 108 . -ts_monitor_solution [ascii binary draw][:filename][:viewerformat] - monitors the solution at each timestep 109 . -ts_monitor_solution_vtk <filename.vts,filename.vtu> - Save each time step to a binary file, use filename-%%03D.vts (filename-%%03D.vtu) 110 . -ts_monitor_envelope - determine maximum and minimum value of each component of the solution over the solution time 111 112 Developer Note: We should unify all the -ts_monitor options in the way that -xxx_view has been unified 113 114 Level: beginner 115 116 .keywords: TS, timestep, set, options, database 117 118 .seealso: TSGetType() 119 @*/ 120 PetscErrorCode TSSetFromOptions(TS ts) 121 { 122 PetscBool opt,flg,tflg; 123 PetscErrorCode ierr; 124 char monfilename[PETSC_MAX_PATH_LEN]; 125 PetscReal time_step; 126 TSExactFinalTimeOption eftopt; 127 char dir[16]; 128 TSIFunction ifun; 129 const char *defaultType; 130 char typeName[256]; 131 132 PetscFunctionBegin; 133 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 134 135 ierr = TSRegisterAll();CHKERRQ(ierr); 136 ierr = TSGetIFunction(ts,NULL,&ifun,NULL);CHKERRQ(ierr); 137 138 ierr = PetscObjectOptionsBegin((PetscObject)ts);CHKERRQ(ierr); 139 if (((PetscObject)ts)->type_name) defaultType = ((PetscObject)ts)->type_name; 140 else defaultType = ifun ? TSBEULER : TSEULER; 141 ierr = PetscOptionsFList("-ts_type","TS method","TSSetType",TSList,defaultType,typeName,256,&opt);CHKERRQ(ierr); 142 if (opt) { 143 ierr = TSSetType(ts,typeName);CHKERRQ(ierr); 144 } else { 145 ierr = TSSetType(ts,defaultType);CHKERRQ(ierr); 146 } 147 148 /* Handle generic TS options */ 149 ierr = PetscOptionsDeprecated("-ts_final_time","-ts_max_time","3.10",NULL);CHKERRQ(ierr); 150 ierr = PetscOptionsReal("-ts_max_time","Maximum time to run to","TSSetMaxTime",ts->max_time,&ts->max_time,NULL);CHKERRQ(ierr); 151 ierr = PetscOptionsInt("-ts_max_steps","Maximum number of time steps","TSSetMaxSteps",ts->max_steps,&ts->max_steps,NULL);CHKERRQ(ierr); 152 ierr = PetscOptionsReal("-ts_init_time","Initial time","TSSetTime",ts->ptime,&ts->ptime,NULL);CHKERRQ(ierr); 153 ierr = PetscOptionsReal("-ts_dt","Initial time step","TSSetTimeStep",ts->time_step,&time_step,&flg);CHKERRQ(ierr); 154 if (flg) {ierr = TSSetTimeStep(ts,time_step);CHKERRQ(ierr);} 155 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); 156 if (flg) {ierr = TSSetExactFinalTime(ts,eftopt);CHKERRQ(ierr);} 157 ierr = PetscOptionsInt("-ts_max_snes_failures","Maximum number of nonlinear solve failures","TSSetMaxSNESFailures",ts->max_snes_failures,&ts->max_snes_failures,NULL);CHKERRQ(ierr); 158 ierr = PetscOptionsInt("-ts_max_reject","Maximum number of step rejections before step fails","TSSetMaxStepRejections",ts->max_reject,&ts->max_reject,NULL);CHKERRQ(ierr); 159 ierr = PetscOptionsBool("-ts_error_if_step_fails","Error if no step succeeds","TSSetErrorIfStepFails",ts->errorifstepfailed,&ts->errorifstepfailed,NULL);CHKERRQ(ierr); 160 ierr = PetscOptionsReal("-ts_rtol","Relative tolerance for local truncation error","TSSetTolerances",ts->rtol,&ts->rtol,NULL);CHKERRQ(ierr); 161 ierr = PetscOptionsReal("-ts_atol","Absolute tolerance for local truncation error","TSSetTolerances",ts->atol,&ts->atol,NULL);CHKERRQ(ierr); 162 163 ierr = PetscOptionsBool("-ts_rhs_jacobian_test_mult","Test the RHS Jacobian for consistency with RHS at each solve ","None",ts->testjacobian,&ts->testjacobian,NULL);CHKERRQ(ierr); 164 ierr = PetscOptionsBool("-ts_rhs_jacobian_test_mult_transpose","Test the RHS Jacobian transpose for consistency with RHS at each solve ","None",ts->testjacobiantranspose,&ts->testjacobiantranspose,NULL);CHKERRQ(ierr); 165 ierr = PetscOptionsBool("-ts_use_splitrhsfunction","Use the split RHS function for multirate solvers ","TSSetUseSplitRHSFunction",ts->use_splitrhsfunction,&ts->use_splitrhsfunction,NULL);CHKERRQ(ierr); 166 #if defined(PETSC_HAVE_SAWS) 167 { 168 PetscBool set; 169 flg = PETSC_FALSE; 170 ierr = PetscOptionsBool("-ts_saws_block","Block for SAWs memory snooper at end of TSSolve","PetscObjectSAWsBlock",((PetscObject)ts)->amspublishblock,&flg,&set);CHKERRQ(ierr); 171 if (set) { 172 ierr = PetscObjectSAWsSetBlock((PetscObject)ts,flg);CHKERRQ(ierr); 173 } 174 } 175 #endif 176 177 /* Monitor options */ 178 ierr = TSMonitorSetFromOptions(ts,"-ts_monitor","Monitor time and timestep size","TSMonitorDefault",TSMonitorDefault,NULL);CHKERRQ(ierr); 179 ierr = TSMonitorSetFromOptions(ts,"-ts_monitor_extreme","Monitor extreme values of the solution","TSMonitorExtreme",TSMonitorExtreme,NULL);CHKERRQ(ierr); 180 ierr = TSMonitorSetFromOptions(ts,"-ts_monitor_solution","View the solution at each timestep","TSMonitorSolution",TSMonitorSolution,NULL);CHKERRQ(ierr); 181 182 ierr = PetscOptionsString("-ts_monitor_python","Use Python function","TSMonitorSet",0,monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr); 183 if (flg) {ierr = PetscPythonMonitorSet((PetscObject)ts,monfilename);CHKERRQ(ierr);} 184 185 ierr = PetscOptionsName("-ts_monitor_lg_solution","Monitor solution graphically","TSMonitorLGSolution",&opt);CHKERRQ(ierr); 186 if (opt) { 187 TSMonitorLGCtx ctx; 188 PetscInt howoften = 1; 189 190 ierr = PetscOptionsInt("-ts_monitor_lg_solution","Monitor solution graphically","TSMonitorLGSolution",howoften,&howoften,NULL);CHKERRQ(ierr); 191 ierr = TSMonitorLGCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);CHKERRQ(ierr); 192 ierr = TSMonitorSet(ts,TSMonitorLGSolution,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 193 } 194 195 ierr = PetscOptionsName("-ts_monitor_lg_error","Monitor error graphically","TSMonitorLGError",&opt);CHKERRQ(ierr); 196 if (opt) { 197 TSMonitorLGCtx ctx; 198 PetscInt howoften = 1; 199 200 ierr = PetscOptionsInt("-ts_monitor_lg_error","Monitor error graphically","TSMonitorLGError",howoften,&howoften,NULL);CHKERRQ(ierr); 201 ierr = TSMonitorLGCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);CHKERRQ(ierr); 202 ierr = TSMonitorSet(ts,TSMonitorLGError,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 203 } 204 ierr = TSMonitorSetFromOptions(ts,"-ts_monitor_error","View the error at each timestep","TSMonitorError",TSMonitorError,NULL);CHKERRQ(ierr); 205 206 ierr = PetscOptionsName("-ts_monitor_lg_timestep","Monitor timestep size graphically","TSMonitorLGTimeStep",&opt);CHKERRQ(ierr); 207 if (opt) { 208 TSMonitorLGCtx ctx; 209 PetscInt howoften = 1; 210 211 ierr = PetscOptionsInt("-ts_monitor_lg_timestep","Monitor timestep size graphically","TSMonitorLGTimeStep",howoften,&howoften,NULL);CHKERRQ(ierr); 212 ierr = TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);CHKERRQ(ierr); 213 ierr = TSMonitorSet(ts,TSMonitorLGTimeStep,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 214 } 215 ierr = PetscOptionsName("-ts_monitor_lg_timestep_log","Monitor log timestep size graphically","TSMonitorLGTimeStep",&opt);CHKERRQ(ierr); 216 if (opt) { 217 TSMonitorLGCtx ctx; 218 PetscInt howoften = 1; 219 220 ierr = PetscOptionsInt("-ts_monitor_lg_timestep_log","Monitor log timestep size graphically","TSMonitorLGTimeStep",howoften,&howoften,NULL);CHKERRQ(ierr); 221 ierr = TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);CHKERRQ(ierr); 222 ierr = TSMonitorSet(ts,TSMonitorLGTimeStep,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 223 ctx->semilogy = PETSC_TRUE; 224 } 225 226 ierr = PetscOptionsName("-ts_monitor_lg_snes_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGSNESIterations",&opt);CHKERRQ(ierr); 227 if (opt) { 228 TSMonitorLGCtx ctx; 229 PetscInt howoften = 1; 230 231 ierr = PetscOptionsInt("-ts_monitor_lg_snes_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGSNESIterations",howoften,&howoften,NULL);CHKERRQ(ierr); 232 ierr = TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);CHKERRQ(ierr); 233 ierr = TSMonitorSet(ts,TSMonitorLGSNESIterations,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 234 } 235 ierr = PetscOptionsName("-ts_monitor_lg_ksp_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGKSPIterations",&opt);CHKERRQ(ierr); 236 if (opt) { 237 TSMonitorLGCtx ctx; 238 PetscInt howoften = 1; 239 240 ierr = PetscOptionsInt("-ts_monitor_lg_ksp_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGKSPIterations",howoften,&howoften,NULL);CHKERRQ(ierr); 241 ierr = TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx);CHKERRQ(ierr); 242 ierr = TSMonitorSet(ts,TSMonitorLGKSPIterations,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 243 } 244 ierr = PetscOptionsName("-ts_monitor_sp_eig","Monitor eigenvalues of linearized operator graphically","TSMonitorSPEig",&opt);CHKERRQ(ierr); 245 if (opt) { 246 TSMonitorSPEigCtx ctx; 247 PetscInt howoften = 1; 248 249 ierr = PetscOptionsInt("-ts_monitor_sp_eig","Monitor eigenvalues of linearized operator graphically","TSMonitorSPEig",howoften,&howoften,NULL);CHKERRQ(ierr); 250 ierr = TSMonitorSPEigCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);CHKERRQ(ierr); 251 ierr = TSMonitorSet(ts,TSMonitorSPEig,ctx,(PetscErrorCode (*)(void**))TSMonitorSPEigCtxDestroy);CHKERRQ(ierr); 252 } 253 ierr = PetscOptionsName("-ts_monitor_sp_swarm","Display particle phase from the DMSwarm","TSMonitorSPSwarm",&opt);CHKERRQ(ierr); 254 if (opt) { 255 TSMonitorSPCtx ctx; 256 PetscInt howoften = 1; 257 ierr = PetscOptionsInt("-ts_monitor_sp_swarm","Display particles phase from the DMSwarm","TSMonitorSPSwarm",howoften,&howoften,NULL);CHKERRQ(ierr); 258 ierr = TSMonitorSPCtxCreate(PETSC_COMM_SELF, NULL, NULL, PETSC_DECIDE, PETSC_DECIDE, 300, 300, howoften, &ctx);CHKERRQ(ierr); 259 ierr = TSMonitorSet(ts, TSMonitorSPSwarmSolution, ctx, (PetscErrorCode (*)(void**))TSMonitorSPCtxDestroy);CHKERRQ(ierr); 260 } 261 opt = PETSC_FALSE; 262 ierr = PetscOptionsName("-ts_monitor_draw_solution","Monitor solution graphically","TSMonitorDrawSolution",&opt);CHKERRQ(ierr); 263 if (opt) { 264 TSMonitorDrawCtx ctx; 265 PetscInt howoften = 1; 266 267 ierr = PetscOptionsInt("-ts_monitor_draw_solution","Monitor solution graphically","TSMonitorDrawSolution",howoften,&howoften,NULL);CHKERRQ(ierr); 268 ierr = TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),0,"Computed Solution",PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);CHKERRQ(ierr); 269 ierr = TSMonitorSet(ts,TSMonitorDrawSolution,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);CHKERRQ(ierr); 270 } 271 opt = PETSC_FALSE; 272 ierr = PetscOptionsName("-ts_monitor_draw_solution_phase","Monitor solution graphically","TSMonitorDrawSolutionPhase",&opt);CHKERRQ(ierr); 273 if (opt) { 274 TSMonitorDrawCtx ctx; 275 PetscReal bounds[4]; 276 PetscInt n = 4; 277 PetscDraw draw; 278 PetscDrawAxis axis; 279 280 ierr = PetscOptionsRealArray("-ts_monitor_draw_solution_phase","Monitor solution graphically","TSMonitorDrawSolutionPhase",bounds,&n,NULL);CHKERRQ(ierr); 281 if (n != 4) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Must provide bounding box of phase field"); 282 ierr = TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,1,&ctx);CHKERRQ(ierr); 283 ierr = PetscViewerDrawGetDraw(ctx->viewer,0,&draw);CHKERRQ(ierr); 284 ierr = PetscViewerDrawGetDrawAxis(ctx->viewer,0,&axis);CHKERRQ(ierr); 285 ierr = PetscDrawAxisSetLimits(axis,bounds[0],bounds[2],bounds[1],bounds[3]);CHKERRQ(ierr); 286 ierr = PetscDrawAxisSetLabels(axis,"Phase Diagram","Variable 1","Variable 2");CHKERRQ(ierr); 287 ierr = TSMonitorSet(ts,TSMonitorDrawSolutionPhase,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);CHKERRQ(ierr); 288 } 289 opt = PETSC_FALSE; 290 ierr = PetscOptionsName("-ts_monitor_draw_error","Monitor error graphically","TSMonitorDrawError",&opt);CHKERRQ(ierr); 291 if (opt) { 292 TSMonitorDrawCtx ctx; 293 PetscInt howoften = 1; 294 295 ierr = PetscOptionsInt("-ts_monitor_draw_error","Monitor error graphically","TSMonitorDrawError",howoften,&howoften,NULL);CHKERRQ(ierr); 296 ierr = TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),0,"Error",PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);CHKERRQ(ierr); 297 ierr = TSMonitorSet(ts,TSMonitorDrawError,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);CHKERRQ(ierr); 298 } 299 opt = PETSC_FALSE; 300 ierr = PetscOptionsName("-ts_monitor_draw_solution_function","Monitor solution provided by TSMonitorSetSolutionFunction() graphically","TSMonitorDrawSolutionFunction",&opt);CHKERRQ(ierr); 301 if (opt) { 302 TSMonitorDrawCtx ctx; 303 PetscInt howoften = 1; 304 305 ierr = PetscOptionsInt("-ts_monitor_draw_solution_function","Monitor solution provided by TSMonitorSetSolutionFunction() graphically","TSMonitorDrawSolutionFunction",howoften,&howoften,NULL);CHKERRQ(ierr); 306 ierr = TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),0,"Solution provided by user function",PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);CHKERRQ(ierr); 307 ierr = TSMonitorSet(ts,TSMonitorDrawSolutionFunction,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);CHKERRQ(ierr); 308 } 309 310 opt = PETSC_FALSE; 311 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); 312 if (flg) { 313 const char *ptr,*ptr2; 314 char *filetemplate; 315 if (!monfilename[0]) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"-ts_monitor_solution_vtk requires a file template, e.g. filename-%%03D.vts"); 316 /* Do some cursory validation of the input. */ 317 ierr = PetscStrstr(monfilename,"%",(char**)&ptr);CHKERRQ(ierr); 318 if (!ptr) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"-ts_monitor_solution_vtk requires a file template, e.g. filename-%%03D.vts"); 319 for (ptr++; ptr && *ptr; ptr++) { 320 ierr = PetscStrchr("DdiouxX",*ptr,(char**)&ptr2);CHKERRQ(ierr); 321 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"); 322 if (ptr2) break; 323 } 324 ierr = PetscStrallocpy(monfilename,&filetemplate);CHKERRQ(ierr); 325 ierr = TSMonitorSet(ts,TSMonitorSolutionVTK,filetemplate,(PetscErrorCode (*)(void**))TSMonitorSolutionVTKDestroy);CHKERRQ(ierr); 326 } 327 328 ierr = PetscOptionsString("-ts_monitor_dmda_ray","Display a ray of the solution","None","y=0",dir,16,&flg);CHKERRQ(ierr); 329 if (flg) { 330 TSMonitorDMDARayCtx *rayctx; 331 int ray = 0; 332 DMDADirection ddir; 333 DM da; 334 PetscMPIInt rank; 335 336 if (dir[1] != '=') SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Unknown ray %s",dir); 337 if (dir[0] == 'x') ddir = DMDA_X; 338 else if (dir[0] == 'y') ddir = DMDA_Y; 339 else SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Unknown ray %s",dir); 340 sscanf(dir+2,"%d",&ray); 341 342 ierr = PetscInfo2(((PetscObject)ts),"Displaying DMDA ray %c = %D\n",dir[0],ray);CHKERRQ(ierr); 343 ierr = PetscNew(&rayctx);CHKERRQ(ierr); 344 ierr = TSGetDM(ts,&da);CHKERRQ(ierr); 345 ierr = DMDAGetRay(da,ddir,ray,&rayctx->ray,&rayctx->scatter);CHKERRQ(ierr); 346 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)ts),&rank);CHKERRQ(ierr); 347 if (!rank) { 348 ierr = PetscViewerDrawOpen(PETSC_COMM_SELF,0,0,0,0,600,300,&rayctx->viewer);CHKERRQ(ierr); 349 } 350 rayctx->lgctx = NULL; 351 ierr = TSMonitorSet(ts,TSMonitorDMDARay,rayctx,TSMonitorDMDARayDestroy);CHKERRQ(ierr); 352 } 353 ierr = PetscOptionsString("-ts_monitor_lg_dmda_ray","Display a ray of the solution","None","x=0",dir,16,&flg);CHKERRQ(ierr); 354 if (flg) { 355 TSMonitorDMDARayCtx *rayctx; 356 int ray = 0; 357 DMDADirection ddir; 358 DM da; 359 PetscInt howoften = 1; 360 361 if (dir[1] != '=') SETERRQ1(PetscObjectComm((PetscObject) ts), PETSC_ERR_ARG_WRONG, "Malformed ray %s", dir); 362 if (dir[0] == 'x') ddir = DMDA_X; 363 else if (dir[0] == 'y') ddir = DMDA_Y; 364 else SETERRQ1(PetscObjectComm((PetscObject) ts), PETSC_ERR_ARG_WRONG, "Unknown ray direction %s", dir); 365 sscanf(dir+2, "%d", &ray); 366 367 ierr = PetscInfo2(((PetscObject) ts),"Displaying LG DMDA ray %c = %D\n", dir[0], ray);CHKERRQ(ierr); 368 ierr = PetscNew(&rayctx);CHKERRQ(ierr); 369 ierr = TSGetDM(ts, &da);CHKERRQ(ierr); 370 ierr = DMDAGetRay(da, ddir, ray, &rayctx->ray, &rayctx->scatter);CHKERRQ(ierr); 371 ierr = TSMonitorLGCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,600,400,howoften,&rayctx->lgctx);CHKERRQ(ierr); 372 ierr = TSMonitorSet(ts, TSMonitorLGDMDARay, rayctx, TSMonitorDMDARayDestroy);CHKERRQ(ierr); 373 } 374 375 ierr = PetscOptionsName("-ts_monitor_envelope","Monitor maximum and minimum value of each component of the solution","TSMonitorEnvelope",&opt);CHKERRQ(ierr); 376 if (opt) { 377 TSMonitorEnvelopeCtx ctx; 378 379 ierr = TSMonitorEnvelopeCtxCreate(ts,&ctx);CHKERRQ(ierr); 380 ierr = TSMonitorSet(ts,TSMonitorEnvelope,ctx,(PetscErrorCode (*)(void**))TSMonitorEnvelopeCtxDestroy);CHKERRQ(ierr); 381 } 382 383 flg = PETSC_FALSE; 384 ierr = PetscOptionsBool("-ts_fd_color", "Use finite differences with coloring to compute IJacobian", "TSComputeJacobianDefaultColor", flg, &flg, NULL);CHKERRQ(ierr); 385 if (flg) { 386 DM dm; 387 DMTS tdm; 388 389 ierr = TSGetDM(ts, &dm);CHKERRQ(ierr); 390 ierr = DMGetDMTS(dm, &tdm);CHKERRQ(ierr); 391 tdm->ijacobianctx = NULL; 392 ierr = TSSetIJacobian(ts, NULL, NULL, TSComputeIJacobianDefaultColor, 0);CHKERRQ(ierr); 393 ierr = PetscInfo(ts, "Setting default finite difference coloring Jacobian matrix\n");CHKERRQ(ierr); 394 } 395 396 /* Handle specific TS options */ 397 if (ts->ops->setfromoptions) { 398 ierr = (*ts->ops->setfromoptions)(PetscOptionsObject,ts);CHKERRQ(ierr); 399 } 400 401 /* Handle TSAdapt options */ 402 ierr = TSGetAdapt(ts,&ts->adapt);CHKERRQ(ierr); 403 ierr = TSAdaptSetDefaultType(ts->adapt,ts->default_adapt_type);CHKERRQ(ierr); 404 ierr = TSAdaptSetFromOptions(PetscOptionsObject,ts->adapt);CHKERRQ(ierr); 405 406 /* TS trajectory must be set after TS, since it may use some TS options above */ 407 tflg = ts->trajectory ? PETSC_TRUE : PETSC_FALSE; 408 ierr = PetscOptionsBool("-ts_save_trajectory","Save the solution at each timestep","TSSetSaveTrajectory",tflg,&tflg,NULL);CHKERRQ(ierr); 409 if (tflg) { 410 ierr = TSSetSaveTrajectory(ts);CHKERRQ(ierr); 411 } 412 413 ierr = TSAdjointSetFromOptions(PetscOptionsObject,ts);CHKERRQ(ierr); 414 415 /* process any options handlers added with PetscObjectAddOptionsHandler() */ 416 ierr = PetscObjectProcessOptionsHandlers(PetscOptionsObject,(PetscObject)ts);CHKERRQ(ierr); 417 ierr = PetscOptionsEnd();CHKERRQ(ierr); 418 419 if (ts->trajectory) { 420 ierr = TSTrajectorySetFromOptions(ts->trajectory,ts);CHKERRQ(ierr); 421 } 422 423 /* why do we have to do this here and not during TSSetUp? */ 424 ierr = TSGetSNES(ts,&ts->snes);CHKERRQ(ierr); 425 if (ts->problem_type == TS_LINEAR) { 426 ierr = PetscObjectTypeCompareAny((PetscObject)ts->snes,&flg,SNESKSPONLY,SNESKSPTRANSPOSEONLY,"");CHKERRQ(ierr); 427 if (!flg) { ierr = SNESSetType(ts->snes,SNESKSPONLY);CHKERRQ(ierr); } 428 } 429 ierr = SNESSetFromOptions(ts->snes);CHKERRQ(ierr); 430 PetscFunctionReturn(0); 431 } 432 433 /*@ 434 TSGetTrajectory - Gets the trajectory from a TS if it exists 435 436 Collective on TS 437 438 Input Parameters: 439 . ts - the TS context obtained from TSCreate() 440 441 Output Parameters; 442 . tr - the TSTrajectory object, if it exists 443 444 Note: This routine should be called after all TS options have been set 445 446 Level: advanced 447 448 .seealso: TSGetTrajectory(), TSAdjointSolve(), TSTrajectory, TSTrajectoryCreate() 449 450 .keywords: TS, set, checkpoint, 451 @*/ 452 PetscErrorCode TSGetTrajectory(TS ts,TSTrajectory *tr) 453 { 454 PetscFunctionBegin; 455 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 456 *tr = ts->trajectory; 457 PetscFunctionReturn(0); 458 } 459 460 /*@ 461 TSSetSaveTrajectory - Causes the TS to save its solutions as it iterates forward in time in a TSTrajectory object 462 463 Collective on TS 464 465 Input Parameters: 466 . ts - the TS context obtained from TSCreate() 467 468 Options Database: 469 + -ts_save_trajectory - saves the trajectory to a file 470 - -ts_trajectory_type type 471 472 Note: This routine should be called after all TS options have been set 473 474 The TSTRAJECTORYVISUALIZATION files can be loaded into Python with $PETSC_DIR/lib/petsc/bin/PetscBinaryIOTrajectory.py and 475 MATLAB with $PETSC_DIR/share/petsc/matlab/PetscReadBinaryTrajectory.m 476 477 Level: intermediate 478 479 .seealso: TSGetTrajectory(), TSAdjointSolve() 480 481 .keywords: TS, set, checkpoint, 482 @*/ 483 PetscErrorCode TSSetSaveTrajectory(TS ts) 484 { 485 PetscErrorCode ierr; 486 487 PetscFunctionBegin; 488 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 489 if (!ts->trajectory) { 490 ierr = TSTrajectoryCreate(PetscObjectComm((PetscObject)ts),&ts->trajectory);CHKERRQ(ierr); 491 } 492 PetscFunctionReturn(0); 493 } 494 495 /*@ 496 TSResetTrajectory - Destroys and recreates the internal TSTrajectory object 497 498 Collective on TS 499 500 Input Parameters: 501 . ts - the TS context obtained from TSCreate() 502 503 Level: intermediate 504 505 .seealso: TSGetTrajectory(), TSAdjointSolve() 506 507 .keywords: TS, set, checkpoint, 508 @*/ 509 PetscErrorCode TSResetTrajectory(TS ts) 510 { 511 PetscErrorCode ierr; 512 513 PetscFunctionBegin; 514 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 515 if (ts->trajectory) { 516 ierr = TSTrajectoryDestroy(&ts->trajectory);CHKERRQ(ierr); 517 ierr = TSTrajectoryCreate(PetscObjectComm((PetscObject)ts),&ts->trajectory);CHKERRQ(ierr); 518 } 519 PetscFunctionReturn(0); 520 } 521 522 /*@ 523 TSComputeRHSJacobian - Computes the Jacobian matrix that has been 524 set with TSSetRHSJacobian(). 525 526 Collective on TS and Vec 527 528 Input Parameters: 529 + ts - the TS context 530 . t - current timestep 531 - U - input vector 532 533 Output Parameters: 534 + A - Jacobian matrix 535 . B - optional preconditioning matrix 536 - flag - flag indicating matrix structure 537 538 Notes: 539 Most users should not need to explicitly call this routine, as it 540 is used internally within the nonlinear solvers. 541 542 See KSPSetOperators() for important information about setting the 543 flag parameter. 544 545 Level: developer 546 547 .keywords: SNES, compute, Jacobian, matrix 548 549 .seealso: TSSetRHSJacobian(), KSPSetOperators() 550 @*/ 551 PetscErrorCode TSComputeRHSJacobian(TS ts,PetscReal t,Vec U,Mat A,Mat B) 552 { 553 PetscErrorCode ierr; 554 PetscObjectState Ustate; 555 PetscObjectId Uid; 556 DM dm; 557 DMTS tsdm; 558 TSRHSJacobian rhsjacobianfunc; 559 void *ctx; 560 TSIJacobian ijacobianfunc; 561 TSRHSFunction rhsfunction; 562 563 PetscFunctionBegin; 564 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 565 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 566 PetscCheckSameComm(ts,1,U,3); 567 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 568 ierr = DMGetDMTS(dm,&tsdm);CHKERRQ(ierr); 569 ierr = DMTSGetRHSJacobian(dm,&rhsjacobianfunc,&ctx);CHKERRQ(ierr); 570 ierr = DMTSGetIJacobian(dm,&ijacobianfunc,NULL);CHKERRQ(ierr); 571 ierr = DMTSGetRHSFunction(dm,&rhsfunction,&ctx);CHKERRQ(ierr); 572 ierr = PetscObjectStateGet((PetscObject)U,&Ustate);CHKERRQ(ierr); 573 ierr = PetscObjectGetId((PetscObject)U,&Uid);CHKERRQ(ierr); 574 575 if (ts->rhsjacobian.time == t && (ts->problem_type == TS_LINEAR || (ts->rhsjacobian.Xid == Uid && ts->rhsjacobian.Xstate == Ustate)) && (rhsfunction != TSComputeRHSFunctionLinear)) { 576 /* restore back RHS Jacobian matrices if they have been shifted/scaled */ 577 if (A == ts->Arhs) { 578 if (ts->rhsjacobian.shift != 0) { 579 ierr = MatShift(A,-ts->rhsjacobian.shift);CHKERRQ(ierr); 580 } 581 if (ts->rhsjacobian.scale != 1.) { 582 ierr = MatScale(A,1./ts->rhsjacobian.scale);CHKERRQ(ierr); 583 } 584 } 585 if (B && B == ts->Brhs && A != B) { 586 if (ts->rhsjacobian.shift != 0) { 587 ierr = MatShift(B,-ts->rhsjacobian.shift);CHKERRQ(ierr); 588 } 589 if (ts->rhsjacobian.scale != 1.) { 590 ierr = MatScale(B,1./ts->rhsjacobian.scale);CHKERRQ(ierr); 591 } 592 } 593 ts->rhsjacobian.shift = 0; 594 ts->rhsjacobian.scale = 1.; 595 PetscFunctionReturn(0); 596 } 597 598 if (!rhsjacobianfunc && !ijacobianfunc) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSJacobian() and / or TSSetIJacobian()"); 599 600 if (ts->rhsjacobian.reuse) { 601 if (A == ts->Arhs) { 602 /* MatScale has a short path for this case. 603 However, this code path is taken the first time TSComputeRHSJacobian is called 604 and the matrices have not assembled yet */ 605 if (ts->rhsjacobian.shift != 0) { 606 ierr = MatShift(A,-ts->rhsjacobian.shift);CHKERRQ(ierr); 607 } 608 if (ts->rhsjacobian.scale != 1.) { 609 ierr = MatScale(A,1./ts->rhsjacobian.scale);CHKERRQ(ierr); 610 } 611 } 612 if (B && B == ts->Brhs && A != B) { 613 if (ts->rhsjacobian.shift != 0) { 614 ierr = MatShift(B,-ts->rhsjacobian.shift);CHKERRQ(ierr); 615 } 616 if (ts->rhsjacobian.scale != 1.) { 617 ierr = MatScale(B,1./ts->rhsjacobian.scale);CHKERRQ(ierr); 618 } 619 } 620 } 621 622 if (rhsjacobianfunc) { 623 PetscBool missing; 624 ierr = PetscLogEventBegin(TS_JacobianEval,ts,U,A,B);CHKERRQ(ierr); 625 PetscStackPush("TS user Jacobian function"); 626 ierr = (*rhsjacobianfunc)(ts,t,U,A,B,ctx);CHKERRQ(ierr); 627 PetscStackPop; 628 ierr = PetscLogEventEnd(TS_JacobianEval,ts,U,A,B);CHKERRQ(ierr); 629 if (A) { 630 ierr = MatMissingDiagonal(A,&missing,NULL);CHKERRQ(ierr); 631 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"); 632 } 633 if (B && B != A) { 634 ierr = MatMissingDiagonal(B,&missing,NULL);CHKERRQ(ierr); 635 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"); 636 } 637 } else { 638 ierr = MatZeroEntries(A);CHKERRQ(ierr); 639 if (B && A != B) {ierr = MatZeroEntries(B);CHKERRQ(ierr);} 640 } 641 ts->rhsjacobian.time = t; 642 ts->rhsjacobian.shift = 0; 643 ts->rhsjacobian.scale = 1.; 644 ierr = PetscObjectGetId((PetscObject)U,&ts->rhsjacobian.Xid);CHKERRQ(ierr); 645 ierr = PetscObjectStateGet((PetscObject)U,&ts->rhsjacobian.Xstate);CHKERRQ(ierr); 646 PetscFunctionReturn(0); 647 } 648 649 /*@ 650 TSComputeRHSFunction - Evaluates the right-hand-side function. 651 652 Collective on TS and Vec 653 654 Input Parameters: 655 + ts - the TS context 656 . t - current time 657 - U - state vector 658 659 Output Parameter: 660 . y - right hand side 661 662 Note: 663 Most users should not need to explicitly call this routine, as it 664 is used internally within the nonlinear solvers. 665 666 Level: developer 667 668 .keywords: TS, compute 669 670 .seealso: TSSetRHSFunction(), TSComputeIFunction() 671 @*/ 672 PetscErrorCode TSComputeRHSFunction(TS ts,PetscReal t,Vec U,Vec y) 673 { 674 PetscErrorCode ierr; 675 TSRHSFunction rhsfunction; 676 TSIFunction ifunction; 677 void *ctx; 678 DM dm; 679 680 PetscFunctionBegin; 681 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 682 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 683 PetscValidHeaderSpecific(y,VEC_CLASSID,4); 684 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 685 ierr = DMTSGetRHSFunction(dm,&rhsfunction,&ctx);CHKERRQ(ierr); 686 ierr = DMTSGetIFunction(dm,&ifunction,NULL);CHKERRQ(ierr); 687 688 if (!rhsfunction && !ifunction) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSFunction() and / or TSSetIFunction()"); 689 690 ierr = PetscLogEventBegin(TS_FunctionEval,ts,U,y,0);CHKERRQ(ierr); 691 if (rhsfunction) { 692 PetscStackPush("TS user right-hand-side function"); 693 ierr = (*rhsfunction)(ts,t,U,y,ctx);CHKERRQ(ierr); 694 PetscStackPop; 695 } else { 696 ierr = VecZeroEntries(y);CHKERRQ(ierr); 697 } 698 699 ierr = PetscLogEventEnd(TS_FunctionEval,ts,U,y,0);CHKERRQ(ierr); 700 PetscFunctionReturn(0); 701 } 702 703 /*@ 704 TSComputeSolutionFunction - Evaluates the solution function. 705 706 Collective on TS and Vec 707 708 Input Parameters: 709 + ts - the TS context 710 - t - current time 711 712 Output Parameter: 713 . U - the solution 714 715 Note: 716 Most users should not need to explicitly call this routine, as it 717 is used internally within the nonlinear solvers. 718 719 Level: developer 720 721 .keywords: TS, compute 722 723 .seealso: TSSetSolutionFunction(), TSSetRHSFunction(), TSComputeIFunction() 724 @*/ 725 PetscErrorCode TSComputeSolutionFunction(TS ts,PetscReal t,Vec U) 726 { 727 PetscErrorCode ierr; 728 TSSolutionFunction solutionfunction; 729 void *ctx; 730 DM dm; 731 732 PetscFunctionBegin; 733 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 734 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 735 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 736 ierr = DMTSGetSolutionFunction(dm,&solutionfunction,&ctx);CHKERRQ(ierr); 737 738 if (solutionfunction) { 739 PetscStackPush("TS user solution function"); 740 ierr = (*solutionfunction)(ts,t,U,ctx);CHKERRQ(ierr); 741 PetscStackPop; 742 } 743 PetscFunctionReturn(0); 744 } 745 /*@ 746 TSComputeForcingFunction - Evaluates the forcing function. 747 748 Collective on TS and Vec 749 750 Input Parameters: 751 + ts - the TS context 752 - t - current time 753 754 Output Parameter: 755 . U - the function value 756 757 Note: 758 Most users should not need to explicitly call this routine, as it 759 is used internally within the nonlinear solvers. 760 761 Level: developer 762 763 .keywords: TS, compute 764 765 .seealso: TSSetSolutionFunction(), TSSetRHSFunction(), TSComputeIFunction() 766 @*/ 767 PetscErrorCode TSComputeForcingFunction(TS ts,PetscReal t,Vec U) 768 { 769 PetscErrorCode ierr, (*forcing)(TS,PetscReal,Vec,void*); 770 void *ctx; 771 DM dm; 772 773 PetscFunctionBegin; 774 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 775 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 776 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 777 ierr = DMTSGetForcingFunction(dm,&forcing,&ctx);CHKERRQ(ierr); 778 779 if (forcing) { 780 PetscStackPush("TS user forcing function"); 781 ierr = (*forcing)(ts,t,U,ctx);CHKERRQ(ierr); 782 PetscStackPop; 783 } 784 PetscFunctionReturn(0); 785 } 786 787 static PetscErrorCode TSGetRHSVec_Private(TS ts,Vec *Frhs) 788 { 789 Vec F; 790 PetscErrorCode ierr; 791 792 PetscFunctionBegin; 793 *Frhs = NULL; 794 ierr = TSGetIFunction(ts,&F,NULL,NULL);CHKERRQ(ierr); 795 if (!ts->Frhs) { 796 ierr = VecDuplicate(F,&ts->Frhs);CHKERRQ(ierr); 797 } 798 *Frhs = ts->Frhs; 799 PetscFunctionReturn(0); 800 } 801 802 PetscErrorCode TSGetRHSMats_Private(TS ts,Mat *Arhs,Mat *Brhs) 803 { 804 Mat A,B; 805 PetscErrorCode ierr; 806 TSIJacobian ijacobian; 807 808 PetscFunctionBegin; 809 if (Arhs) *Arhs = NULL; 810 if (Brhs) *Brhs = NULL; 811 ierr = TSGetIJacobian(ts,&A,&B,&ijacobian,NULL);CHKERRQ(ierr); 812 if (Arhs) { 813 if (!ts->Arhs) { 814 if (ijacobian) { 815 ierr = MatDuplicate(A,MAT_DO_NOT_COPY_VALUES,&ts->Arhs);CHKERRQ(ierr); 816 } else { 817 ts->Arhs = A; 818 ierr = PetscObjectReference((PetscObject)A);CHKERRQ(ierr); 819 } 820 } else { 821 PetscBool flg; 822 ierr = SNESGetUseMatrixFree(ts->snes,NULL,&flg);CHKERRQ(ierr); 823 /* Handle case where user provided only RHSJacobian and used -snes_mf_operator */ 824 if (flg && !ijacobian && ts->Arhs == ts->Brhs){ 825 ierr = PetscObjectDereference((PetscObject)ts->Arhs);CHKERRQ(ierr); 826 ts->Arhs = A; 827 ierr = PetscObjectReference((PetscObject)A);CHKERRQ(ierr); 828 } 829 } 830 *Arhs = ts->Arhs; 831 } 832 if (Brhs) { 833 if (!ts->Brhs) { 834 if (A != B) { 835 if (ijacobian) { 836 ierr = MatDuplicate(B,MAT_DO_NOT_COPY_VALUES,&ts->Brhs);CHKERRQ(ierr); 837 } else { 838 ts->Brhs = B; 839 ierr = PetscObjectReference((PetscObject)B);CHKERRQ(ierr); 840 } 841 } else { 842 ierr = PetscObjectReference((PetscObject)ts->Arhs);CHKERRQ(ierr); 843 ts->Brhs = ts->Arhs; 844 } 845 } 846 *Brhs = ts->Brhs; 847 } 848 PetscFunctionReturn(0); 849 } 850 851 /*@ 852 TSComputeIFunction - Evaluates the DAE residual written in implicit form F(t,U,Udot)=0 853 854 Collective on TS and Vec 855 856 Input Parameters: 857 + ts - the TS context 858 . t - current time 859 . U - state vector 860 . Udot - time derivative of state vector 861 - imex - flag indicates if the method is IMEX so that the RHSFunction should be kept separate 862 863 Output Parameter: 864 . Y - right hand side 865 866 Note: 867 Most users should not need to explicitly call this routine, as it 868 is used internally within the nonlinear solvers. 869 870 If the user did did not write their equations in implicit form, this 871 function recasts them in implicit form. 872 873 Level: developer 874 875 .keywords: TS, compute 876 877 .seealso: TSSetIFunction(), TSComputeRHSFunction() 878 @*/ 879 PetscErrorCode TSComputeIFunction(TS ts,PetscReal t,Vec U,Vec Udot,Vec Y,PetscBool imex) 880 { 881 PetscErrorCode ierr; 882 TSIFunction ifunction; 883 TSRHSFunction rhsfunction; 884 void *ctx; 885 DM dm; 886 887 PetscFunctionBegin; 888 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 889 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 890 PetscValidHeaderSpecific(Udot,VEC_CLASSID,4); 891 PetscValidHeaderSpecific(Y,VEC_CLASSID,5); 892 893 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 894 ierr = DMTSGetIFunction(dm,&ifunction,&ctx);CHKERRQ(ierr); 895 ierr = DMTSGetRHSFunction(dm,&rhsfunction,NULL);CHKERRQ(ierr); 896 897 if (!rhsfunction && !ifunction) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSFunction() and / or TSSetIFunction()"); 898 899 ierr = PetscLogEventBegin(TS_FunctionEval,ts,U,Udot,Y);CHKERRQ(ierr); 900 if (ifunction) { 901 PetscStackPush("TS user implicit function"); 902 ierr = (*ifunction)(ts,t,U,Udot,Y,ctx);CHKERRQ(ierr); 903 PetscStackPop; 904 } 905 if (imex) { 906 if (!ifunction) { 907 ierr = VecCopy(Udot,Y);CHKERRQ(ierr); 908 } 909 } else if (rhsfunction) { 910 if (ifunction) { 911 Vec Frhs; 912 ierr = TSGetRHSVec_Private(ts,&Frhs);CHKERRQ(ierr); 913 ierr = TSComputeRHSFunction(ts,t,U,Frhs);CHKERRQ(ierr); 914 ierr = VecAXPY(Y,-1,Frhs);CHKERRQ(ierr); 915 } else { 916 ierr = TSComputeRHSFunction(ts,t,U,Y);CHKERRQ(ierr); 917 ierr = VecAYPX(Y,-1,Udot);CHKERRQ(ierr); 918 } 919 } 920 ierr = PetscLogEventEnd(TS_FunctionEval,ts,U,Udot,Y);CHKERRQ(ierr); 921 PetscFunctionReturn(0); 922 } 923 924 /*@ 925 TSComputeIJacobian - Evaluates the Jacobian of the DAE 926 927 Collective on TS and Vec 928 929 Input 930 Input Parameters: 931 + ts - the TS context 932 . t - current timestep 933 . U - state vector 934 . Udot - time derivative of state vector 935 . shift - shift to apply, see note below 936 - imex - flag indicates if the method is IMEX so that the RHSJacobian should be kept separate 937 938 Output Parameters: 939 + A - Jacobian matrix 940 - B - matrix from which the preconditioner is constructed; often the same as A 941 942 Notes: 943 If F(t,U,Udot)=0 is the DAE, the required Jacobian is 944 945 dF/dU + shift*dF/dUdot 946 947 Most users should not need to explicitly call this routine, as it 948 is used internally within the nonlinear solvers. 949 950 Level: developer 951 952 .keywords: TS, compute, Jacobian, matrix 953 954 .seealso: TSSetIJacobian() 955 @*/ 956 PetscErrorCode TSComputeIJacobian(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat A,Mat B,PetscBool imex) 957 { 958 PetscErrorCode ierr; 959 TSIJacobian ijacobian; 960 TSRHSJacobian rhsjacobian; 961 DM dm; 962 void *ctx; 963 964 PetscFunctionBegin; 965 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 966 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 967 PetscValidHeaderSpecific(Udot,VEC_CLASSID,4); 968 PetscValidPointer(A,6); 969 PetscValidHeaderSpecific(A,MAT_CLASSID,6); 970 PetscValidPointer(B,7); 971 PetscValidHeaderSpecific(B,MAT_CLASSID,7); 972 973 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 974 ierr = DMTSGetIJacobian(dm,&ijacobian,&ctx);CHKERRQ(ierr); 975 ierr = DMTSGetRHSJacobian(dm,&rhsjacobian,NULL);CHKERRQ(ierr); 976 977 if (!rhsjacobian && !ijacobian) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSJacobian() and / or TSSetIJacobian()"); 978 979 ierr = PetscLogEventBegin(TS_JacobianEval,ts,U,A,B);CHKERRQ(ierr); 980 if (ijacobian) { 981 PetscBool missing; 982 PetscStackPush("TS user implicit Jacobian"); 983 ierr = (*ijacobian)(ts,t,U,Udot,shift,A,B,ctx);CHKERRQ(ierr); 984 PetscStackPop; 985 ierr = MatMissingDiagonal(A,&missing,NULL);CHKERRQ(ierr); 986 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"); 987 if (B != A) { 988 ierr = MatMissingDiagonal(B,&missing,NULL);CHKERRQ(ierr); 989 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"); 990 } 991 } 992 if (imex) { 993 if (!ijacobian) { /* system was written as Udot = G(t,U) */ 994 PetscBool assembled; 995 if (rhsjacobian) { 996 Mat Arhs = NULL; 997 ierr = TSGetRHSMats_Private(ts,&Arhs,NULL);CHKERRQ(ierr); 998 if (A == Arhs) { 999 if (rhsjacobian == TSComputeRHSJacobianConstant) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Unsupported operation! cannot use TSComputeRHSJacobianConstant"); 1000 ts->rhsjacobian.time = PETSC_MIN_REAL; 1001 } 1002 } 1003 ierr = MatZeroEntries(A);CHKERRQ(ierr); 1004 ierr = MatAssembled(A,&assembled);CHKERRQ(ierr); 1005 if (!assembled) { 1006 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1007 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1008 } 1009 ierr = MatShift(A,shift);CHKERRQ(ierr); 1010 if (A != B) { 1011 ierr = MatZeroEntries(B);CHKERRQ(ierr); 1012 ierr = MatAssembled(B,&assembled);CHKERRQ(ierr); 1013 if (!assembled) { 1014 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1015 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1016 } 1017 ierr = MatShift(B,shift);CHKERRQ(ierr); 1018 } 1019 } 1020 } else { 1021 Mat Arhs = NULL,Brhs = NULL; 1022 if (rhsjacobian) { 1023 ierr = TSGetRHSMats_Private(ts,&Arhs,&Brhs);CHKERRQ(ierr); 1024 ierr = TSComputeRHSJacobian(ts,t,U,Arhs,Brhs);CHKERRQ(ierr); 1025 } 1026 if (Arhs == A) { /* No IJacobian, so we only have the RHS matrix */ 1027 PetscBool flg; 1028 ts->rhsjacobian.scale = -1; 1029 ts->rhsjacobian.shift = shift; 1030 ierr = SNESGetUseMatrixFree(ts->snes,NULL,&flg);CHKERRQ(ierr); 1031 /* since -snes_mf_operator uses the full SNES function it does not need to be shifted or scaled here */ 1032 if (!flg) { 1033 ierr = MatScale(A,-1);CHKERRQ(ierr); 1034 ierr = MatShift(A,shift);CHKERRQ(ierr); 1035 } 1036 if (A != B) { 1037 ierr = MatScale(B,-1);CHKERRQ(ierr); 1038 ierr = MatShift(B,shift);CHKERRQ(ierr); 1039 } 1040 } else if (Arhs) { /* Both IJacobian and RHSJacobian */ 1041 MatStructure axpy = DIFFERENT_NONZERO_PATTERN; 1042 if (!ijacobian) { /* No IJacobian provided, but we have a separate RHS matrix */ 1043 ierr = MatZeroEntries(A);CHKERRQ(ierr); 1044 ierr = MatShift(A,shift);CHKERRQ(ierr); 1045 if (A != B) { 1046 ierr = MatZeroEntries(B);CHKERRQ(ierr); 1047 ierr = MatShift(B,shift);CHKERRQ(ierr); 1048 } 1049 } 1050 ierr = MatAXPY(A,-1,Arhs,axpy);CHKERRQ(ierr); 1051 if (A != B) { 1052 ierr = MatAXPY(B,-1,Brhs,axpy);CHKERRQ(ierr); 1053 } 1054 } 1055 } 1056 ierr = PetscLogEventEnd(TS_JacobianEval,ts,U,A,B);CHKERRQ(ierr); 1057 PetscFunctionReturn(0); 1058 } 1059 1060 /*@C 1061 TSSetRHSFunction - Sets the routine for evaluating the function, 1062 where U_t = G(t,u). 1063 1064 Logically Collective on TS 1065 1066 Input Parameters: 1067 + ts - the TS context obtained from TSCreate() 1068 . r - vector to put the computed right hand side (or NULL to have it created) 1069 . f - routine for evaluating the right-hand-side 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,Vec F,void *ctx); 1075 1076 + t - current timestep 1077 . u - input vector 1078 . F - function vector 1079 - ctx - [optional] user-defined function context 1080 1081 Level: beginner 1082 1083 Notes: 1084 You must call this function or TSSetIFunction() to define your ODE. You cannot use this function when solving a DAE. 1085 1086 .keywords: TS, timestep, set, right-hand-side, function 1087 1088 .seealso: TSSetRHSJacobian(), TSSetIJacobian(), TSSetIFunction() 1089 @*/ 1090 PetscErrorCode TSSetRHSFunction(TS ts,Vec r,PetscErrorCode (*f)(TS,PetscReal,Vec,Vec,void*),void *ctx) 1091 { 1092 PetscErrorCode ierr; 1093 SNES snes; 1094 Vec ralloc = NULL; 1095 DM dm; 1096 1097 PetscFunctionBegin; 1098 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1099 if (r) PetscValidHeaderSpecific(r,VEC_CLASSID,2); 1100 1101 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1102 ierr = DMTSSetRHSFunction(dm,f,ctx);CHKERRQ(ierr); 1103 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1104 if (!r && !ts->dm && ts->vec_sol) { 1105 ierr = VecDuplicate(ts->vec_sol,&ralloc);CHKERRQ(ierr); 1106 r = ralloc; 1107 } 1108 ierr = SNESSetFunction(snes,r,SNESTSFormFunction,ts);CHKERRQ(ierr); 1109 ierr = VecDestroy(&ralloc);CHKERRQ(ierr); 1110 PetscFunctionReturn(0); 1111 } 1112 1113 /*@C 1114 TSSetSolutionFunction - Provide a function that computes the solution of the ODE or DAE 1115 1116 Logically Collective on TS 1117 1118 Input Parameters: 1119 + ts - the TS context obtained from TSCreate() 1120 . f - routine for evaluating the solution 1121 - ctx - [optional] user-defined context for private data for the 1122 function evaluation routine (may be NULL) 1123 1124 Calling sequence of func: 1125 $ func (TS ts,PetscReal t,Vec u,void *ctx); 1126 1127 + t - current timestep 1128 . u - output vector 1129 - ctx - [optional] user-defined function context 1130 1131 Options Database: 1132 + -ts_monitor_lg_error - create a graphical monitor of error history, requires user to have provided TSSetSolutionFunction() 1133 - -ts_monitor_draw_error - Monitor error graphically, requires user to have provided TSSetSolutionFunction() 1134 1135 Notes: 1136 This routine is used for testing accuracy of time integration schemes when you already know the solution. 1137 If analytic solutions are not known for your system, consider using the Method of Manufactured Solutions to 1138 create closed-form solutions with non-physical forcing terms. 1139 1140 For low-dimensional problems solved in serial, such as small discrete systems, TSMonitorLGError() can be used to monitor the error history. 1141 1142 Level: beginner 1143 1144 .keywords: TS, timestep, set, right-hand-side, function 1145 1146 .seealso: TSSetRHSJacobian(), TSSetIJacobian(), TSComputeSolutionFunction(), TSSetForcingFunction(), TSSetSolution(), TSGetSolution(), TSMonitorLGError(), TSMonitorDrawError() 1147 @*/ 1148 PetscErrorCode TSSetSolutionFunction(TS ts,PetscErrorCode (*f)(TS,PetscReal,Vec,void*),void *ctx) 1149 { 1150 PetscErrorCode ierr; 1151 DM dm; 1152 1153 PetscFunctionBegin; 1154 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1155 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1156 ierr = DMTSSetSolutionFunction(dm,f,ctx);CHKERRQ(ierr); 1157 PetscFunctionReturn(0); 1158 } 1159 1160 /*@C 1161 TSSetForcingFunction - Provide a function that computes a forcing term for a ODE or PDE 1162 1163 Logically Collective on TS 1164 1165 Input Parameters: 1166 + ts - the TS context obtained from TSCreate() 1167 . func - routine for evaluating the forcing function 1168 - ctx - [optional] user-defined context for private data for the 1169 function evaluation routine (may be NULL) 1170 1171 Calling sequence of func: 1172 $ func (TS ts,PetscReal t,Vec f,void *ctx); 1173 1174 + t - current timestep 1175 . f - output vector 1176 - ctx - [optional] user-defined function context 1177 1178 Notes: 1179 This routine is useful for testing accuracy of time integration schemes when using the Method of Manufactured Solutions to 1180 create closed-form solutions with a non-physical forcing term. It allows you to use the Method of Manufactored Solution without directly editing the 1181 definition of the problem you are solving and hence possibly introducing bugs. 1182 1183 This replaces the ODE F(u,u_t,t) = 0 the TS is solving with F(u,u_t,t) - func(t) = 0 1184 1185 This forcing function does not depend on the solution to the equations, it can only depend on spatial location, time, and possibly parameters, the 1186 parameters can be passed in the ctx variable. 1187 1188 For low-dimensional problems solved in serial, such as small discrete systems, TSMonitorLGError() can be used to monitor the error history. 1189 1190 Level: beginner 1191 1192 .keywords: TS, timestep, set, right-hand-side, function 1193 1194 .seealso: TSSetRHSJacobian(), TSSetIJacobian(), TSComputeSolutionFunction(), TSSetSolutionFunction() 1195 @*/ 1196 PetscErrorCode TSSetForcingFunction(TS ts,TSForcingFunction func,void *ctx) 1197 { 1198 PetscErrorCode ierr; 1199 DM dm; 1200 1201 PetscFunctionBegin; 1202 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1203 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1204 ierr = DMTSSetForcingFunction(dm,func,ctx);CHKERRQ(ierr); 1205 PetscFunctionReturn(0); 1206 } 1207 1208 /*@C 1209 TSSetRHSJacobian - Sets the function to compute the Jacobian of G, 1210 where U_t = G(U,t), as well as the location to store the matrix. 1211 1212 Logically Collective on TS 1213 1214 Input Parameters: 1215 + ts - the TS context obtained from TSCreate() 1216 . Amat - (approximate) Jacobian matrix 1217 . Pmat - matrix from which preconditioner is to be constructed (usually the same as Amat) 1218 . f - the Jacobian evaluation routine 1219 - ctx - [optional] user-defined context for private data for the 1220 Jacobian evaluation routine (may be NULL) 1221 1222 Calling sequence of f: 1223 $ func (TS ts,PetscReal t,Vec u,Mat A,Mat B,void *ctx); 1224 1225 + t - current timestep 1226 . u - input vector 1227 . Amat - (approximate) Jacobian matrix 1228 . Pmat - matrix from which preconditioner is to be constructed (usually the same as Amat) 1229 - ctx - [optional] user-defined context for matrix evaluation routine 1230 1231 Notes: 1232 You must set all the diagonal entries of the matrices, if they are zero you must still set them with a zero value 1233 1234 The TS solver may modify the nonzero structure and the entries of the matrices Amat and Pmat between the calls to f() 1235 You should not assume the values are the same in the next call to f() as you set them in the previous call. 1236 1237 Level: beginner 1238 1239 .keywords: TS, timestep, set, right-hand-side, Jacobian 1240 1241 .seealso: SNESComputeJacobianDefaultColor(), TSSetRHSFunction(), TSRHSJacobianSetReuse(), TSSetIJacobian() 1242 1243 @*/ 1244 PetscErrorCode TSSetRHSJacobian(TS ts,Mat Amat,Mat Pmat,TSRHSJacobian f,void *ctx) 1245 { 1246 PetscErrorCode ierr; 1247 SNES snes; 1248 DM dm; 1249 TSIJacobian ijacobian; 1250 1251 PetscFunctionBegin; 1252 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1253 if (Amat) PetscValidHeaderSpecific(Amat,MAT_CLASSID,2); 1254 if (Pmat) PetscValidHeaderSpecific(Pmat,MAT_CLASSID,3); 1255 if (Amat) PetscCheckSameComm(ts,1,Amat,2); 1256 if (Pmat) PetscCheckSameComm(ts,1,Pmat,3); 1257 1258 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1259 ierr = DMTSSetRHSJacobian(dm,f,ctx);CHKERRQ(ierr); 1260 if (f == TSComputeRHSJacobianConstant) { 1261 /* Handle this case automatically for the user; otherwise user should call themselves. */ 1262 ierr = TSRHSJacobianSetReuse(ts,PETSC_TRUE);CHKERRQ(ierr); 1263 } 1264 ierr = DMTSGetIJacobian(dm,&ijacobian,NULL);CHKERRQ(ierr); 1265 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1266 if (!ijacobian) { 1267 ierr = SNESSetJacobian(snes,Amat,Pmat,SNESTSFormJacobian,ts);CHKERRQ(ierr); 1268 } 1269 if (Amat) { 1270 ierr = PetscObjectReference((PetscObject)Amat);CHKERRQ(ierr); 1271 ierr = MatDestroy(&ts->Arhs);CHKERRQ(ierr); 1272 ts->Arhs = Amat; 1273 } 1274 if (Pmat) { 1275 ierr = PetscObjectReference((PetscObject)Pmat);CHKERRQ(ierr); 1276 ierr = MatDestroy(&ts->Brhs);CHKERRQ(ierr); 1277 ts->Brhs = Pmat; 1278 } 1279 PetscFunctionReturn(0); 1280 } 1281 1282 /*@C 1283 TSSetIFunction - Set the function to compute F(t,U,U_t) where F() = 0 is the DAE to be solved. 1284 1285 Logically Collective on TS 1286 1287 Input Parameters: 1288 + ts - the TS context obtained from TSCreate() 1289 . r - vector to hold the residual (or NULL to have it created internally) 1290 . f - the function evaluation routine 1291 - ctx - user-defined context for private data for the function evaluation routine (may be NULL) 1292 1293 Calling sequence of f: 1294 $ f(TS ts,PetscReal t,Vec u,Vec u_t,Vec F,ctx); 1295 1296 + t - time at step/stage being solved 1297 . u - state vector 1298 . u_t - time derivative of state vector 1299 . F - function vector 1300 - ctx - [optional] user-defined context for matrix evaluation routine 1301 1302 Important: 1303 The user MUST call either this routine or TSSetRHSFunction() to define the ODE. When solving DAEs you must use this function. 1304 1305 Level: beginner 1306 1307 .keywords: TS, timestep, set, DAE, Jacobian 1308 1309 .seealso: TSSetRHSJacobian(), TSSetRHSFunction(), TSSetIJacobian() 1310 @*/ 1311 PetscErrorCode TSSetIFunction(TS ts,Vec r,TSIFunction f,void *ctx) 1312 { 1313 PetscErrorCode ierr; 1314 SNES snes; 1315 Vec ralloc = NULL; 1316 DM dm; 1317 1318 PetscFunctionBegin; 1319 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1320 if (r) PetscValidHeaderSpecific(r,VEC_CLASSID,2); 1321 1322 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1323 ierr = DMTSSetIFunction(dm,f,ctx);CHKERRQ(ierr); 1324 1325 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1326 if (!r && !ts->dm && ts->vec_sol) { 1327 ierr = VecDuplicate(ts->vec_sol,&ralloc);CHKERRQ(ierr); 1328 r = ralloc; 1329 } 1330 ierr = SNESSetFunction(snes,r,SNESTSFormFunction,ts);CHKERRQ(ierr); 1331 ierr = VecDestroy(&ralloc);CHKERRQ(ierr); 1332 PetscFunctionReturn(0); 1333 } 1334 1335 /*@C 1336 TSGetIFunction - Returns the vector where the implicit residual is stored and the function/contex to compute it. 1337 1338 Not Collective 1339 1340 Input Parameter: 1341 . ts - the TS context 1342 1343 Output Parameter: 1344 + r - vector to hold residual (or NULL) 1345 . func - the function to compute residual (or NULL) 1346 - ctx - the function context (or NULL) 1347 1348 Level: advanced 1349 1350 .keywords: TS, nonlinear, get, function 1351 1352 .seealso: TSSetIFunction(), SNESGetFunction() 1353 @*/ 1354 PetscErrorCode TSGetIFunction(TS ts,Vec *r,TSIFunction *func,void **ctx) 1355 { 1356 PetscErrorCode ierr; 1357 SNES snes; 1358 DM dm; 1359 1360 PetscFunctionBegin; 1361 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1362 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1363 ierr = SNESGetFunction(snes,r,NULL,NULL);CHKERRQ(ierr); 1364 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1365 ierr = DMTSGetIFunction(dm,func,ctx);CHKERRQ(ierr); 1366 PetscFunctionReturn(0); 1367 } 1368 1369 /*@C 1370 TSGetRHSFunction - Returns the vector where the right hand side is stored and the function/context to compute it. 1371 1372 Not Collective 1373 1374 Input Parameter: 1375 . ts - the TS context 1376 1377 Output Parameter: 1378 + r - vector to hold computed right hand side (or NULL) 1379 . func - the function to compute right hand side (or NULL) 1380 - ctx - the function context (or NULL) 1381 1382 Level: advanced 1383 1384 .keywords: TS, nonlinear, get, function 1385 1386 .seealso: TSSetRHSFunction(), SNESGetFunction() 1387 @*/ 1388 PetscErrorCode TSGetRHSFunction(TS ts,Vec *r,TSRHSFunction *func,void **ctx) 1389 { 1390 PetscErrorCode ierr; 1391 SNES snes; 1392 DM dm; 1393 1394 PetscFunctionBegin; 1395 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1396 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1397 ierr = SNESGetFunction(snes,r,NULL,NULL);CHKERRQ(ierr); 1398 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1399 ierr = DMTSGetRHSFunction(dm,func,ctx);CHKERRQ(ierr); 1400 PetscFunctionReturn(0); 1401 } 1402 1403 /*@C 1404 TSSetIJacobian - Set the function to compute the matrix dF/dU + a*dF/dU_t where F(t,U,U_t) is the function 1405 provided with TSSetIFunction(). 1406 1407 Logically Collective on TS 1408 1409 Input Parameters: 1410 + ts - the TS context obtained from TSCreate() 1411 . Amat - (approximate) Jacobian matrix 1412 . Pmat - matrix used to compute preconditioner (usually the same as Amat) 1413 . f - the Jacobian evaluation routine 1414 - ctx - user-defined context for private data for the Jacobian evaluation routine (may be NULL) 1415 1416 Calling sequence of f: 1417 $ f(TS ts,PetscReal t,Vec U,Vec U_t,PetscReal a,Mat Amat,Mat Pmat,void *ctx); 1418 1419 + t - time at step/stage being solved 1420 . U - state vector 1421 . U_t - time derivative of state vector 1422 . a - shift 1423 . Amat - (approximate) Jacobian of F(t,U,W+a*U), equivalent to dF/dU + a*dF/dU_t 1424 . Pmat - matrix used for constructing preconditioner, usually the same as Amat 1425 - ctx - [optional] user-defined context for matrix evaluation routine 1426 1427 Notes: 1428 The matrices Amat and Pmat are exactly the matrices that are used by SNES for the nonlinear solve. 1429 1430 If you know the operator Amat has a null space you can use MatSetNullSpace() and MatSetTransposeNullSpace() to supply the null 1431 space to Amat and the KSP solvers will automatically use that null space as needed during the solution process. 1432 1433 The matrix dF/dU + a*dF/dU_t you provide turns out to be 1434 the Jacobian of F(t,U,W+a*U) where F(t,U,U_t) = 0 is the DAE to be solved. 1435 The time integrator internally approximates U_t by W+a*U where the positive "shift" 1436 a and vector W depend on the integration method, step size, and past states. For example with 1437 the backward Euler method a = 1/dt and W = -a*U(previous timestep) so 1438 W + a*U = a*(U - U(previous timestep)) = (U - U(previous timestep))/dt 1439 1440 You must set all the diagonal entries of the matrices, if they are zero you must still set them with a zero value 1441 1442 The TS solver may modify the nonzero structure and the entries of the matrices Amat and Pmat between the calls to f() 1443 You should not assume the values are the same in the next call to f() as you set them in the previous call. 1444 1445 Level: beginner 1446 1447 .keywords: TS, timestep, DAE, Jacobian 1448 1449 .seealso: TSSetIFunction(), TSSetRHSJacobian(), SNESComputeJacobianDefaultColor(), SNESComputeJacobianDefault(), TSSetRHSFunction() 1450 1451 @*/ 1452 PetscErrorCode TSSetIJacobian(TS ts,Mat Amat,Mat Pmat,TSIJacobian f,void *ctx) 1453 { 1454 PetscErrorCode ierr; 1455 SNES snes; 1456 DM dm; 1457 1458 PetscFunctionBegin; 1459 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1460 if (Amat) PetscValidHeaderSpecific(Amat,MAT_CLASSID,2); 1461 if (Pmat) PetscValidHeaderSpecific(Pmat,MAT_CLASSID,3); 1462 if (Amat) PetscCheckSameComm(ts,1,Amat,2); 1463 if (Pmat) PetscCheckSameComm(ts,1,Pmat,3); 1464 1465 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1466 ierr = DMTSSetIJacobian(dm,f,ctx);CHKERRQ(ierr); 1467 1468 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1469 ierr = SNESSetJacobian(snes,Amat,Pmat,SNESTSFormJacobian,ts);CHKERRQ(ierr); 1470 PetscFunctionReturn(0); 1471 } 1472 1473 /*@ 1474 TSRHSJacobianSetReuse - restore RHS Jacobian before re-evaluating. Without this flag, TS will change the sign and 1475 shift the RHS Jacobian for a finite-time-step implicit solve, in which case the user function will need to recompute 1476 the entire Jacobian. The reuse flag must be set if the evaluation function will assume that the matrix entries have 1477 not been changed by the TS. 1478 1479 Logically Collective 1480 1481 Input Arguments: 1482 + ts - TS context obtained from TSCreate() 1483 - reuse - PETSC_TRUE if the RHS Jacobian 1484 1485 Level: intermediate 1486 1487 .seealso: TSSetRHSJacobian(), TSComputeRHSJacobianConstant() 1488 @*/ 1489 PetscErrorCode TSRHSJacobianSetReuse(TS ts,PetscBool reuse) 1490 { 1491 PetscFunctionBegin; 1492 ts->rhsjacobian.reuse = reuse; 1493 PetscFunctionReturn(0); 1494 } 1495 1496 /*@C 1497 TSSetI2Function - Set the function to compute F(t,U,U_t,U_tt) where F = 0 is the DAE to be solved. 1498 1499 Logically Collective on TS 1500 1501 Input Parameters: 1502 + ts - the TS context obtained from TSCreate() 1503 . F - vector to hold the residual (or NULL to have it created internally) 1504 . fun - the function evaluation routine 1505 - ctx - user-defined context for private data for the function evaluation routine (may be NULL) 1506 1507 Calling sequence of fun: 1508 $ fun(TS ts,PetscReal t,Vec U,Vec U_t,Vec U_tt,Vec F,ctx); 1509 1510 + t - time at step/stage being solved 1511 . U - state vector 1512 . U_t - time derivative of state vector 1513 . U_tt - second time derivative of state vector 1514 . F - function vector 1515 - ctx - [optional] user-defined context for matrix evaluation routine (may be NULL) 1516 1517 Level: beginner 1518 1519 .keywords: TS, timestep, set, ODE, DAE, Function 1520 1521 .seealso: TSSetI2Jacobian() 1522 @*/ 1523 PetscErrorCode TSSetI2Function(TS ts,Vec F,TSI2Function fun,void *ctx) 1524 { 1525 DM dm; 1526 PetscErrorCode ierr; 1527 1528 PetscFunctionBegin; 1529 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1530 if (F) PetscValidHeaderSpecific(F,VEC_CLASSID,2); 1531 ierr = TSSetIFunction(ts,F,NULL,NULL);CHKERRQ(ierr); 1532 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1533 ierr = DMTSSetI2Function(dm,fun,ctx);CHKERRQ(ierr); 1534 PetscFunctionReturn(0); 1535 } 1536 1537 /*@C 1538 TSGetI2Function - Returns the vector where the implicit residual is stored and the function/contex to compute it. 1539 1540 Not Collective 1541 1542 Input Parameter: 1543 . ts - the TS context 1544 1545 Output Parameter: 1546 + r - vector to hold residual (or NULL) 1547 . fun - the function to compute residual (or NULL) 1548 - ctx - the function context (or NULL) 1549 1550 Level: advanced 1551 1552 .keywords: TS, nonlinear, get, function 1553 1554 .seealso: TSSetI2Function(), SNESGetFunction() 1555 @*/ 1556 PetscErrorCode TSGetI2Function(TS ts,Vec *r,TSI2Function *fun,void **ctx) 1557 { 1558 PetscErrorCode ierr; 1559 SNES snes; 1560 DM dm; 1561 1562 PetscFunctionBegin; 1563 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1564 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1565 ierr = SNESGetFunction(snes,r,NULL,NULL);CHKERRQ(ierr); 1566 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1567 ierr = DMTSGetI2Function(dm,fun,ctx);CHKERRQ(ierr); 1568 PetscFunctionReturn(0); 1569 } 1570 1571 /*@C 1572 TSSetI2Jacobian - Set the function to compute the matrix dF/dU + v*dF/dU_t + a*dF/dU_tt 1573 where F(t,U,U_t,U_tt) is the function you provided with TSSetI2Function(). 1574 1575 Logically Collective on TS 1576 1577 Input Parameters: 1578 + ts - the TS context obtained from TSCreate() 1579 . J - Jacobian matrix 1580 . P - preconditioning matrix for J (may be same as J) 1581 . jac - the Jacobian evaluation routine 1582 - ctx - user-defined context for private data for the Jacobian evaluation routine (may be NULL) 1583 1584 Calling sequence of jac: 1585 $ jac(TS ts,PetscReal t,Vec U,Vec U_t,Vec U_tt,PetscReal v,PetscReal a,Mat J,Mat P,void *ctx); 1586 1587 + t - time at step/stage being solved 1588 . U - state vector 1589 . U_t - time derivative of state vector 1590 . U_tt - second time derivative of state vector 1591 . v - shift for U_t 1592 . a - shift for U_tt 1593 . 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 1594 . P - preconditioning matrix for J, may be same as J 1595 - ctx - [optional] user-defined context for matrix evaluation routine 1596 1597 Notes: 1598 The matrices J and P are exactly the matrices that are used by SNES for the nonlinear solve. 1599 1600 The matrix dF/dU + v*dF/dU_t + a*dF/dU_tt you provide turns out to be 1601 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. 1602 The time integrator internally approximates U_t by W+v*U and U_tt by W'+a*U where the positive "shift" 1603 parameters 'v' and 'a' and vectors W, W' depend on the integration method, step size, and past states. 1604 1605 Level: beginner 1606 1607 .keywords: TS, timestep, set, ODE, DAE, Jacobian 1608 1609 .seealso: TSSetI2Function() 1610 @*/ 1611 PetscErrorCode TSSetI2Jacobian(TS ts,Mat J,Mat P,TSI2Jacobian jac,void *ctx) 1612 { 1613 DM dm; 1614 PetscErrorCode ierr; 1615 1616 PetscFunctionBegin; 1617 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1618 if (J) PetscValidHeaderSpecific(J,MAT_CLASSID,2); 1619 if (P) PetscValidHeaderSpecific(P,MAT_CLASSID,3); 1620 ierr = TSSetIJacobian(ts,J,P,NULL,NULL);CHKERRQ(ierr); 1621 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1622 ierr = DMTSSetI2Jacobian(dm,jac,ctx);CHKERRQ(ierr); 1623 PetscFunctionReturn(0); 1624 } 1625 1626 /*@C 1627 TSGetI2Jacobian - Returns the implicit Jacobian at the present timestep. 1628 1629 Not Collective, but parallel objects are returned if TS is parallel 1630 1631 Input Parameter: 1632 . ts - The TS context obtained from TSCreate() 1633 1634 Output Parameters: 1635 + J - The (approximate) Jacobian of F(t,U,U_t,U_tt) 1636 . P - The matrix from which the preconditioner is constructed, often the same as J 1637 . jac - The function to compute the Jacobian matrices 1638 - ctx - User-defined context for Jacobian evaluation routine 1639 1640 Notes: 1641 You can pass in NULL for any return argument you do not need. 1642 1643 Level: advanced 1644 1645 .seealso: TSGetTimeStep(), TSGetMatrices(), TSGetTime(), TSGetStepNumber() 1646 1647 .keywords: TS, timestep, get, matrix, Jacobian 1648 @*/ 1649 PetscErrorCode TSGetI2Jacobian(TS ts,Mat *J,Mat *P,TSI2Jacobian *jac,void **ctx) 1650 { 1651 PetscErrorCode ierr; 1652 SNES snes; 1653 DM dm; 1654 1655 PetscFunctionBegin; 1656 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1657 ierr = SNESSetUpMatrices(snes);CHKERRQ(ierr); 1658 ierr = SNESGetJacobian(snes,J,P,NULL,NULL);CHKERRQ(ierr); 1659 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1660 ierr = DMTSGetI2Jacobian(dm,jac,ctx);CHKERRQ(ierr); 1661 PetscFunctionReturn(0); 1662 } 1663 1664 /*@ 1665 TSComputeI2Function - Evaluates the DAE residual written in implicit form F(t,U,U_t,U_tt) = 0 1666 1667 Collective on TS and Vec 1668 1669 Input Parameters: 1670 + ts - the TS context 1671 . t - current time 1672 . U - state vector 1673 . V - time derivative of state vector (U_t) 1674 - A - second time derivative of state vector (U_tt) 1675 1676 Output Parameter: 1677 . F - the residual vector 1678 1679 Note: 1680 Most users should not need to explicitly call this routine, as it 1681 is used internally within the nonlinear solvers. 1682 1683 Level: developer 1684 1685 .keywords: TS, compute, function, vector 1686 1687 .seealso: TSSetI2Function() 1688 @*/ 1689 PetscErrorCode TSComputeI2Function(TS ts,PetscReal t,Vec U,Vec V,Vec A,Vec F) 1690 { 1691 DM dm; 1692 TSI2Function I2Function; 1693 void *ctx; 1694 TSRHSFunction rhsfunction; 1695 PetscErrorCode ierr; 1696 1697 PetscFunctionBegin; 1698 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1699 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 1700 PetscValidHeaderSpecific(V,VEC_CLASSID,4); 1701 PetscValidHeaderSpecific(A,VEC_CLASSID,5); 1702 PetscValidHeaderSpecific(F,VEC_CLASSID,6); 1703 1704 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1705 ierr = DMTSGetI2Function(dm,&I2Function,&ctx);CHKERRQ(ierr); 1706 ierr = DMTSGetRHSFunction(dm,&rhsfunction,NULL);CHKERRQ(ierr); 1707 1708 if (!I2Function) { 1709 ierr = TSComputeIFunction(ts,t,U,A,F,PETSC_FALSE);CHKERRQ(ierr); 1710 PetscFunctionReturn(0); 1711 } 1712 1713 ierr = PetscLogEventBegin(TS_FunctionEval,ts,U,V,F);CHKERRQ(ierr); 1714 1715 PetscStackPush("TS user implicit function"); 1716 ierr = I2Function(ts,t,U,V,A,F,ctx);CHKERRQ(ierr); 1717 PetscStackPop; 1718 1719 if (rhsfunction) { 1720 Vec Frhs; 1721 ierr = TSGetRHSVec_Private(ts,&Frhs);CHKERRQ(ierr); 1722 ierr = TSComputeRHSFunction(ts,t,U,Frhs);CHKERRQ(ierr); 1723 ierr = VecAXPY(F,-1,Frhs);CHKERRQ(ierr); 1724 } 1725 1726 ierr = PetscLogEventEnd(TS_FunctionEval,ts,U,V,F);CHKERRQ(ierr); 1727 PetscFunctionReturn(0); 1728 } 1729 1730 /*@ 1731 TSComputeI2Jacobian - Evaluates the Jacobian of the DAE 1732 1733 Collective on TS and Vec 1734 1735 Input Parameters: 1736 + ts - the TS context 1737 . t - current timestep 1738 . U - state vector 1739 . V - time derivative of state vector 1740 . A - second time derivative of state vector 1741 . shiftV - shift to apply, see note below 1742 - shiftA - shift to apply, see note below 1743 1744 Output Parameters: 1745 + J - Jacobian matrix 1746 - P - optional preconditioning matrix 1747 1748 Notes: 1749 If F(t,U,V,A)=0 is the DAE, the required Jacobian is 1750 1751 dF/dU + shiftV*dF/dV + shiftA*dF/dA 1752 1753 Most users should not need to explicitly call this routine, as it 1754 is used internally within the nonlinear solvers. 1755 1756 Level: developer 1757 1758 .keywords: TS, compute, Jacobian, matrix 1759 1760 .seealso: TSSetI2Jacobian() 1761 @*/ 1762 PetscErrorCode TSComputeI2Jacobian(TS ts,PetscReal t,Vec U,Vec V,Vec A,PetscReal shiftV,PetscReal shiftA,Mat J,Mat P) 1763 { 1764 DM dm; 1765 TSI2Jacobian I2Jacobian; 1766 void *ctx; 1767 TSRHSJacobian rhsjacobian; 1768 PetscErrorCode ierr; 1769 1770 PetscFunctionBegin; 1771 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1772 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 1773 PetscValidHeaderSpecific(V,VEC_CLASSID,4); 1774 PetscValidHeaderSpecific(A,VEC_CLASSID,5); 1775 PetscValidHeaderSpecific(J,MAT_CLASSID,8); 1776 PetscValidHeaderSpecific(P,MAT_CLASSID,9); 1777 1778 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1779 ierr = DMTSGetI2Jacobian(dm,&I2Jacobian,&ctx);CHKERRQ(ierr); 1780 ierr = DMTSGetRHSJacobian(dm,&rhsjacobian,NULL);CHKERRQ(ierr); 1781 1782 if (!I2Jacobian) { 1783 ierr = TSComputeIJacobian(ts,t,U,A,shiftA,J,P,PETSC_FALSE);CHKERRQ(ierr); 1784 PetscFunctionReturn(0); 1785 } 1786 1787 ierr = PetscLogEventBegin(TS_JacobianEval,ts,U,J,P);CHKERRQ(ierr); 1788 1789 PetscStackPush("TS user implicit Jacobian"); 1790 ierr = I2Jacobian(ts,t,U,V,A,shiftV,shiftA,J,P,ctx);CHKERRQ(ierr); 1791 PetscStackPop; 1792 1793 if (rhsjacobian) { 1794 Mat Jrhs,Prhs; MatStructure axpy = DIFFERENT_NONZERO_PATTERN; 1795 ierr = TSGetRHSMats_Private(ts,&Jrhs,&Prhs);CHKERRQ(ierr); 1796 ierr = TSComputeRHSJacobian(ts,t,U,Jrhs,Prhs);CHKERRQ(ierr); 1797 ierr = MatAXPY(J,-1,Jrhs,axpy);CHKERRQ(ierr); 1798 if (P != J) {ierr = MatAXPY(P,-1,Prhs,axpy);CHKERRQ(ierr);} 1799 } 1800 1801 ierr = PetscLogEventEnd(TS_JacobianEval,ts,U,J,P);CHKERRQ(ierr); 1802 PetscFunctionReturn(0); 1803 } 1804 1805 /*@ 1806 TS2SetSolution - Sets the initial solution and time derivative vectors 1807 for use by the TS routines handling second order equations. 1808 1809 Logically Collective on TS and Vec 1810 1811 Input Parameters: 1812 + ts - the TS context obtained from TSCreate() 1813 . u - the solution vector 1814 - v - the time derivative vector 1815 1816 Level: beginner 1817 1818 .keywords: TS, timestep, set, solution, initial conditions 1819 @*/ 1820 PetscErrorCode TS2SetSolution(TS ts,Vec u,Vec v) 1821 { 1822 PetscErrorCode ierr; 1823 1824 PetscFunctionBegin; 1825 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1826 PetscValidHeaderSpecific(u,VEC_CLASSID,2); 1827 PetscValidHeaderSpecific(v,VEC_CLASSID,3); 1828 ierr = TSSetSolution(ts,u);CHKERRQ(ierr); 1829 ierr = PetscObjectReference((PetscObject)v);CHKERRQ(ierr); 1830 ierr = VecDestroy(&ts->vec_dot);CHKERRQ(ierr); 1831 ts->vec_dot = v; 1832 PetscFunctionReturn(0); 1833 } 1834 1835 /*@ 1836 TS2GetSolution - Returns the solution and time derivative at the present timestep 1837 for second order equations. It is valid to call this routine inside the function 1838 that you are evaluating in order to move to the new timestep. This vector not 1839 changed until the solution at the next timestep has been calculated. 1840 1841 Not Collective, but Vec returned is parallel if TS is parallel 1842 1843 Input Parameter: 1844 . ts - the TS context obtained from TSCreate() 1845 1846 Output Parameter: 1847 + u - the vector containing the solution 1848 - v - the vector containing the time derivative 1849 1850 Level: intermediate 1851 1852 .seealso: TS2SetSolution(), TSGetTimeStep(), TSGetTime() 1853 1854 .keywords: TS, timestep, get, solution 1855 @*/ 1856 PetscErrorCode TS2GetSolution(TS ts,Vec *u,Vec *v) 1857 { 1858 PetscFunctionBegin; 1859 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1860 if (u) PetscValidPointer(u,2); 1861 if (v) PetscValidPointer(v,3); 1862 if (u) *u = ts->vec_sol; 1863 if (v) *v = ts->vec_dot; 1864 PetscFunctionReturn(0); 1865 } 1866 1867 /*@C 1868 TSLoad - Loads a KSP that has been stored in binary with KSPView(). 1869 1870 Collective on PetscViewer 1871 1872 Input Parameters: 1873 + newdm - the newly loaded TS, this needs to have been created with TSCreate() or 1874 some related function before a call to TSLoad(). 1875 - viewer - binary file viewer, obtained from PetscViewerBinaryOpen() 1876 1877 Level: intermediate 1878 1879 Notes: 1880 The type is determined by the data in the file, any type set into the TS before this call is ignored. 1881 1882 Notes for advanced users: 1883 Most users should not need to know the details of the binary storage 1884 format, since TSLoad() and TSView() completely hide these details. 1885 But for anyone who's interested, the standard binary matrix storage 1886 format is 1887 .vb 1888 has not yet been determined 1889 .ve 1890 1891 .seealso: PetscViewerBinaryOpen(), TSView(), MatLoad(), VecLoad() 1892 @*/ 1893 PetscErrorCode TSLoad(TS ts, PetscViewer viewer) 1894 { 1895 PetscErrorCode ierr; 1896 PetscBool isbinary; 1897 PetscInt classid; 1898 char type[256]; 1899 DMTS sdm; 1900 DM dm; 1901 1902 PetscFunctionBegin; 1903 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1904 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,2); 1905 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1906 if (!isbinary) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid viewer; open viewer with PetscViewerBinaryOpen()"); 1907 1908 ierr = PetscViewerBinaryRead(viewer,&classid,1,NULL,PETSC_INT);CHKERRQ(ierr); 1909 if (classid != TS_FILE_CLASSID) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Not TS next in file"); 1910 ierr = PetscViewerBinaryRead(viewer,type,256,NULL,PETSC_CHAR);CHKERRQ(ierr); 1911 ierr = TSSetType(ts, type);CHKERRQ(ierr); 1912 if (ts->ops->load) { 1913 ierr = (*ts->ops->load)(ts,viewer);CHKERRQ(ierr); 1914 } 1915 ierr = DMCreate(PetscObjectComm((PetscObject)ts),&dm);CHKERRQ(ierr); 1916 ierr = DMLoad(dm,viewer);CHKERRQ(ierr); 1917 ierr = TSSetDM(ts,dm);CHKERRQ(ierr); 1918 ierr = DMCreateGlobalVector(ts->dm,&ts->vec_sol);CHKERRQ(ierr); 1919 ierr = VecLoad(ts->vec_sol,viewer);CHKERRQ(ierr); 1920 ierr = DMGetDMTS(ts->dm,&sdm);CHKERRQ(ierr); 1921 ierr = DMTSLoad(sdm,viewer);CHKERRQ(ierr); 1922 PetscFunctionReturn(0); 1923 } 1924 1925 #include <petscdraw.h> 1926 #if defined(PETSC_HAVE_SAWS) 1927 #include <petscviewersaws.h> 1928 #endif 1929 /*@C 1930 TSView - Prints the TS data structure. 1931 1932 Collective on TS 1933 1934 Input Parameters: 1935 + ts - the TS context obtained from TSCreate() 1936 - viewer - visualization context 1937 1938 Options Database Key: 1939 . -ts_view - calls TSView() at end of TSStep() 1940 1941 Notes: 1942 The available visualization contexts include 1943 + PETSC_VIEWER_STDOUT_SELF - standard output (default) 1944 - PETSC_VIEWER_STDOUT_WORLD - synchronized standard 1945 output where only the first processor opens 1946 the file. All other processors send their 1947 data to the first processor to print. 1948 1949 The user can open an alternative visualization context with 1950 PetscViewerASCIIOpen() - output to a specified file. 1951 1952 Level: beginner 1953 1954 .keywords: TS, timestep, view 1955 1956 .seealso: PetscViewerASCIIOpen() 1957 @*/ 1958 PetscErrorCode TSView(TS ts,PetscViewer viewer) 1959 { 1960 PetscErrorCode ierr; 1961 TSType type; 1962 PetscBool iascii,isstring,isundials,isbinary,isdraw; 1963 DMTS sdm; 1964 #if defined(PETSC_HAVE_SAWS) 1965 PetscBool issaws; 1966 #endif 1967 1968 PetscFunctionBegin; 1969 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1970 if (!viewer) { 1971 ierr = PetscViewerASCIIGetStdout(PetscObjectComm((PetscObject)ts),&viewer);CHKERRQ(ierr); 1972 } 1973 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,2); 1974 PetscCheckSameComm(ts,1,viewer,2); 1975 1976 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1977 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSTRING,&isstring);CHKERRQ(ierr); 1978 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1979 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1980 #if defined(PETSC_HAVE_SAWS) 1981 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSAWS,&issaws);CHKERRQ(ierr); 1982 #endif 1983 if (iascii) { 1984 ierr = PetscObjectPrintClassNamePrefixType((PetscObject)ts,viewer);CHKERRQ(ierr); 1985 if (ts->ops->view) { 1986 ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr); 1987 ierr = (*ts->ops->view)(ts,viewer);CHKERRQ(ierr); 1988 ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr); 1989 } 1990 if (ts->max_steps < PETSC_MAX_INT) { 1991 ierr = PetscViewerASCIIPrintf(viewer," maximum steps=%D\n",ts->max_steps);CHKERRQ(ierr); 1992 } 1993 if (ts->max_time < PETSC_MAX_REAL) { 1994 ierr = PetscViewerASCIIPrintf(viewer," maximum time=%g\n",(double)ts->max_time);CHKERRQ(ierr); 1995 } 1996 if (ts->usessnes) { 1997 PetscBool lin; 1998 if (ts->problem_type == TS_NONLINEAR) { 1999 ierr = PetscViewerASCIIPrintf(viewer," total number of nonlinear solver iterations=%D\n",ts->snes_its);CHKERRQ(ierr); 2000 } 2001 ierr = PetscViewerASCIIPrintf(viewer," total number of linear solver iterations=%D\n",ts->ksp_its);CHKERRQ(ierr); 2002 ierr = PetscObjectTypeCompareAny((PetscObject)ts->snes,&lin,SNESKSPONLY,SNESKSPTRANSPOSEONLY,"");CHKERRQ(ierr); 2003 ierr = PetscViewerASCIIPrintf(viewer," total number of %slinear solve failures=%D\n",lin ? "" : "non",ts->num_snes_failures);CHKERRQ(ierr); 2004 } 2005 ierr = PetscViewerASCIIPrintf(viewer," total number of rejected steps=%D\n",ts->reject);CHKERRQ(ierr); 2006 if (ts->vrtol) { 2007 ierr = PetscViewerASCIIPrintf(viewer," using vector of relative error tolerances, ");CHKERRQ(ierr); 2008 } else { 2009 ierr = PetscViewerASCIIPrintf(viewer," using relative error tolerance of %g, ",(double)ts->rtol);CHKERRQ(ierr); 2010 } 2011 if (ts->vatol) { 2012 ierr = PetscViewerASCIIPrintf(viewer," using vector of absolute error tolerances\n");CHKERRQ(ierr); 2013 } else { 2014 ierr = PetscViewerASCIIPrintf(viewer," using absolute error tolerance of %g\n",(double)ts->atol);CHKERRQ(ierr); 2015 } 2016 ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr); 2017 ierr = TSAdaptView(ts->adapt,viewer);CHKERRQ(ierr); 2018 ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr); 2019 if (ts->snes && ts->usessnes) { 2020 ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr); 2021 ierr = SNESView(ts->snes,viewer);CHKERRQ(ierr); 2022 ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr); 2023 } 2024 ierr = DMGetDMTS(ts->dm,&sdm);CHKERRQ(ierr); 2025 ierr = DMTSView(sdm,viewer);CHKERRQ(ierr); 2026 } else if (isstring) { 2027 ierr = TSGetType(ts,&type);CHKERRQ(ierr); 2028 ierr = PetscViewerStringSPrintf(viewer," %-7.7s",type);CHKERRQ(ierr); 2029 } else if (isbinary) { 2030 PetscInt classid = TS_FILE_CLASSID; 2031 MPI_Comm comm; 2032 PetscMPIInt rank; 2033 char type[256]; 2034 2035 ierr = PetscObjectGetComm((PetscObject)ts,&comm);CHKERRQ(ierr); 2036 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2037 if (!rank) { 2038 ierr = PetscViewerBinaryWrite(viewer,&classid,1,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); 2039 ierr = PetscStrncpy(type,((PetscObject)ts)->type_name,256);CHKERRQ(ierr); 2040 ierr = PetscViewerBinaryWrite(viewer,type,256,PETSC_CHAR,PETSC_FALSE);CHKERRQ(ierr); 2041 } 2042 if (ts->ops->view) { 2043 ierr = (*ts->ops->view)(ts,viewer);CHKERRQ(ierr); 2044 } 2045 if (ts->adapt) {ierr = TSAdaptView(ts->adapt,viewer);CHKERRQ(ierr);} 2046 ierr = DMView(ts->dm,viewer);CHKERRQ(ierr); 2047 ierr = VecView(ts->vec_sol,viewer);CHKERRQ(ierr); 2048 ierr = DMGetDMTS(ts->dm,&sdm);CHKERRQ(ierr); 2049 ierr = DMTSView(sdm,viewer);CHKERRQ(ierr); 2050 } else if (isdraw) { 2051 PetscDraw draw; 2052 char str[36]; 2053 PetscReal x,y,bottom,h; 2054 2055 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 2056 ierr = PetscDrawGetCurrentPoint(draw,&x,&y);CHKERRQ(ierr); 2057 ierr = PetscStrcpy(str,"TS: ");CHKERRQ(ierr); 2058 ierr = PetscStrcat(str,((PetscObject)ts)->type_name);CHKERRQ(ierr); 2059 ierr = PetscDrawStringBoxed(draw,x,y,PETSC_DRAW_BLACK,PETSC_DRAW_BLACK,str,NULL,&h);CHKERRQ(ierr); 2060 bottom = y - h; 2061 ierr = PetscDrawPushCurrentPoint(draw,x,bottom);CHKERRQ(ierr); 2062 if (ts->ops->view) { 2063 ierr = (*ts->ops->view)(ts,viewer);CHKERRQ(ierr); 2064 } 2065 if (ts->adapt) {ierr = TSAdaptView(ts->adapt,viewer);CHKERRQ(ierr);} 2066 if (ts->snes) {ierr = SNESView(ts->snes,viewer);CHKERRQ(ierr);} 2067 ierr = PetscDrawPopCurrentPoint(draw);CHKERRQ(ierr); 2068 #if defined(PETSC_HAVE_SAWS) 2069 } else if (issaws) { 2070 PetscMPIInt rank; 2071 const char *name; 2072 2073 ierr = PetscObjectGetName((PetscObject)ts,&name);CHKERRQ(ierr); 2074 ierr = MPI_Comm_rank(PETSC_COMM_WORLD,&rank);CHKERRQ(ierr); 2075 if (!((PetscObject)ts)->amsmem && !rank) { 2076 char dir[1024]; 2077 2078 ierr = PetscObjectViewSAWs((PetscObject)ts,viewer);CHKERRQ(ierr); 2079 ierr = PetscSNPrintf(dir,1024,"/PETSc/Objects/%s/time_step",name);CHKERRQ(ierr); 2080 PetscStackCallSAWs(SAWs_Register,(dir,&ts->steps,1,SAWs_READ,SAWs_INT)); 2081 ierr = PetscSNPrintf(dir,1024,"/PETSc/Objects/%s/time",name);CHKERRQ(ierr); 2082 PetscStackCallSAWs(SAWs_Register,(dir,&ts->ptime,1,SAWs_READ,SAWs_DOUBLE)); 2083 } 2084 if (ts->ops->view) { 2085 ierr = (*ts->ops->view)(ts,viewer);CHKERRQ(ierr); 2086 } 2087 #endif 2088 } 2089 2090 ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr); 2091 ierr = PetscObjectTypeCompare((PetscObject)ts,TSSUNDIALS,&isundials);CHKERRQ(ierr); 2092 ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr); 2093 PetscFunctionReturn(0); 2094 } 2095 2096 /*@ 2097 TSSetApplicationContext - Sets an optional user-defined context for 2098 the timesteppers. 2099 2100 Logically Collective on TS 2101 2102 Input Parameters: 2103 + ts - the TS context obtained from TSCreate() 2104 - usrP - optional user context 2105 2106 Fortran Notes: 2107 To use this from Fortran you must write a Fortran interface definition for this 2108 function that tells Fortran the Fortran derived data type that you are passing in as the ctx argument. 2109 2110 Level: intermediate 2111 2112 .keywords: TS, timestep, set, application, context 2113 2114 .seealso: TSGetApplicationContext() 2115 @*/ 2116 PetscErrorCode TSSetApplicationContext(TS ts,void *usrP) 2117 { 2118 PetscFunctionBegin; 2119 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2120 ts->user = usrP; 2121 PetscFunctionReturn(0); 2122 } 2123 2124 /*@ 2125 TSGetApplicationContext - Gets the user-defined context for the 2126 timestepper. 2127 2128 Not Collective 2129 2130 Input Parameter: 2131 . ts - the TS context obtained from TSCreate() 2132 2133 Output Parameter: 2134 . usrP - user context 2135 2136 Fortran Notes: 2137 To use this from Fortran you must write a Fortran interface definition for this 2138 function that tells Fortran the Fortran derived data type that you are passing in as the ctx argument. 2139 2140 Level: intermediate 2141 2142 .keywords: TS, timestep, get, application, context 2143 2144 .seealso: TSSetApplicationContext() 2145 @*/ 2146 PetscErrorCode TSGetApplicationContext(TS ts,void *usrP) 2147 { 2148 PetscFunctionBegin; 2149 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2150 *(void**)usrP = ts->user; 2151 PetscFunctionReturn(0); 2152 } 2153 2154 /*@ 2155 TSGetStepNumber - Gets the number of steps completed. 2156 2157 Not Collective 2158 2159 Input Parameter: 2160 . ts - the TS context obtained from TSCreate() 2161 2162 Output Parameter: 2163 . steps - number of steps completed so far 2164 2165 Level: intermediate 2166 2167 .keywords: TS, timestep, get, iteration, number 2168 .seealso: TSGetTime(), TSGetTimeStep(), TSSetPreStep(), TSSetPreStage(), TSSetPostStage(), TSSetPostStep() 2169 @*/ 2170 PetscErrorCode TSGetStepNumber(TS ts,PetscInt *steps) 2171 { 2172 PetscFunctionBegin; 2173 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2174 PetscValidIntPointer(steps,2); 2175 *steps = ts->steps; 2176 PetscFunctionReturn(0); 2177 } 2178 2179 /*@ 2180 TSSetStepNumber - Sets the number of steps completed. 2181 2182 Logically Collective on TS 2183 2184 Input Parameters: 2185 + ts - the TS context 2186 - steps - number of steps completed so far 2187 2188 Notes: 2189 For most uses of the TS solvers the user need not explicitly call 2190 TSSetStepNumber(), as the step counter is appropriately updated in 2191 TSSolve()/TSStep()/TSRollBack(). Power users may call this routine to 2192 reinitialize timestepping by setting the step counter to zero (and time 2193 to the initial time) to solve a similar problem with different initial 2194 conditions or parameters. Other possible use case is to continue 2195 timestepping from a previously interrupted run in such a way that TS 2196 monitors will be called with a initial nonzero step counter. 2197 2198 Level: advanced 2199 2200 .keywords: TS, timestep, set, iteration, number 2201 .seealso: TSGetStepNumber(), TSSetTime(), TSSetTimeStep(), TSSetSolution() 2202 @*/ 2203 PetscErrorCode TSSetStepNumber(TS ts,PetscInt steps) 2204 { 2205 PetscFunctionBegin; 2206 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2207 PetscValidLogicalCollectiveInt(ts,steps,2); 2208 if (steps < 0) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Step number must be non-negative"); 2209 ts->steps = steps; 2210 PetscFunctionReturn(0); 2211 } 2212 2213 /*@ 2214 TSSetTimeStep - Allows one to reset the timestep at any time, 2215 useful for simple pseudo-timestepping codes. 2216 2217 Logically Collective on TS 2218 2219 Input Parameters: 2220 + ts - the TS context obtained from TSCreate() 2221 - time_step - the size of the timestep 2222 2223 Level: intermediate 2224 2225 .seealso: TSGetTimeStep(), TSSetTime() 2226 2227 .keywords: TS, set, timestep 2228 @*/ 2229 PetscErrorCode TSSetTimeStep(TS ts,PetscReal time_step) 2230 { 2231 PetscFunctionBegin; 2232 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2233 PetscValidLogicalCollectiveReal(ts,time_step,2); 2234 ts->time_step = time_step; 2235 PetscFunctionReturn(0); 2236 } 2237 2238 /*@ 2239 TSSetExactFinalTime - Determines whether to adapt the final time step to 2240 match the exact final time, interpolate solution to the exact final time, 2241 or just return at the final time TS computed. 2242 2243 Logically Collective on TS 2244 2245 Input Parameter: 2246 + ts - the time-step context 2247 - eftopt - exact final time option 2248 2249 $ TS_EXACTFINALTIME_STEPOVER - Don't do anything if final time is exceeded 2250 $ TS_EXACTFINALTIME_INTERPOLATE - Interpolate back to final time 2251 $ TS_EXACTFINALTIME_MATCHSTEP - Adapt final time step to match the final time 2252 2253 Options Database: 2254 . -ts_exact_final_time <stepover,interpolate,matchstep> - select the final step at runtime 2255 2256 Warning: If you use the option TS_EXACTFINALTIME_STEPOVER the solution may be at a very different time 2257 then the final time you selected. 2258 2259 Level: beginner 2260 2261 .seealso: TSExactFinalTimeOption, TSGetExactFinalTime() 2262 @*/ 2263 PetscErrorCode TSSetExactFinalTime(TS ts,TSExactFinalTimeOption eftopt) 2264 { 2265 PetscFunctionBegin; 2266 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2267 PetscValidLogicalCollectiveEnum(ts,eftopt,2); 2268 ts->exact_final_time = eftopt; 2269 PetscFunctionReturn(0); 2270 } 2271 2272 /*@ 2273 TSGetExactFinalTime - Gets the exact final time option. 2274 2275 Not Collective 2276 2277 Input Parameter: 2278 . ts - the TS context 2279 2280 Output Parameter: 2281 . eftopt - exact final time option 2282 2283 Level: beginner 2284 2285 .seealso: TSExactFinalTimeOption, TSSetExactFinalTime() 2286 @*/ 2287 PetscErrorCode TSGetExactFinalTime(TS ts,TSExactFinalTimeOption *eftopt) 2288 { 2289 PetscFunctionBegin; 2290 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2291 PetscValidPointer(eftopt,2); 2292 *eftopt = ts->exact_final_time; 2293 PetscFunctionReturn(0); 2294 } 2295 2296 /*@ 2297 TSGetTimeStep - Gets the current timestep size. 2298 2299 Not Collective 2300 2301 Input Parameter: 2302 . ts - the TS context obtained from TSCreate() 2303 2304 Output Parameter: 2305 . dt - the current timestep size 2306 2307 Level: intermediate 2308 2309 .seealso: TSSetTimeStep(), TSGetTime() 2310 2311 .keywords: TS, get, timestep 2312 @*/ 2313 PetscErrorCode TSGetTimeStep(TS ts,PetscReal *dt) 2314 { 2315 PetscFunctionBegin; 2316 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2317 PetscValidRealPointer(dt,2); 2318 *dt = ts->time_step; 2319 PetscFunctionReturn(0); 2320 } 2321 2322 /*@ 2323 TSGetSolution - Returns the solution at the present timestep. It 2324 is valid to call this routine inside the function that you are evaluating 2325 in order to move to the new timestep. This vector not changed until 2326 the solution at the next timestep has been calculated. 2327 2328 Not Collective, but Vec returned is parallel if TS is parallel 2329 2330 Input Parameter: 2331 . ts - the TS context obtained from TSCreate() 2332 2333 Output Parameter: 2334 . v - the vector containing the solution 2335 2336 Note: If you used TSSetExactFinalTime(ts,TS_EXACTFINALTIME_MATCHSTEP); this does not return the solution at the requested 2337 final time. It returns the solution at the next timestep. 2338 2339 Level: intermediate 2340 2341 .seealso: TSGetTimeStep(), TSGetTime(), TSGetSolveTime(), TSGetSolutionComponents(), TSSetSolutionFunction() 2342 2343 .keywords: TS, timestep, get, solution 2344 @*/ 2345 PetscErrorCode TSGetSolution(TS ts,Vec *v) 2346 { 2347 PetscFunctionBegin; 2348 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2349 PetscValidPointer(v,2); 2350 *v = ts->vec_sol; 2351 PetscFunctionReturn(0); 2352 } 2353 2354 /*@ 2355 TSGetSolutionComponents - Returns any solution components at the present 2356 timestep, if available for the time integration method being used. 2357 Solution components are quantities that share the same size and 2358 structure as the solution 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 . n - If v is PETSC_NULL, then the number of solution components is 2365 returned through n, else the n-th solution component is 2366 returned in v. 2367 . v - the vector containing the n-th solution component 2368 (may be PETSC_NULL to use this function to find out 2369 the number of solutions components). 2370 2371 Level: advanced 2372 2373 .seealso: TSGetSolution() 2374 2375 .keywords: TS, timestep, get, solution 2376 @*/ 2377 PetscErrorCode TSGetSolutionComponents(TS ts,PetscInt *n,Vec *v) 2378 { 2379 PetscErrorCode ierr; 2380 2381 PetscFunctionBegin; 2382 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2383 if (!ts->ops->getsolutioncomponents) *n = 0; 2384 else { 2385 ierr = (*ts->ops->getsolutioncomponents)(ts,n,v);CHKERRQ(ierr); 2386 } 2387 PetscFunctionReturn(0); 2388 } 2389 2390 /*@ 2391 TSGetAuxSolution - Returns an auxiliary solution at the present 2392 timestep, if available for the time integration method being used. 2393 2394 Not Collective, but Vec returned is parallel if TS is parallel 2395 2396 Parameters : 2397 . ts - the TS context obtained from TSCreate() (input parameter). 2398 . v - the vector containing the auxiliary solution 2399 2400 Level: intermediate 2401 2402 .seealso: TSGetSolution() 2403 2404 .keywords: TS, timestep, get, solution 2405 @*/ 2406 PetscErrorCode TSGetAuxSolution(TS ts,Vec *v) 2407 { 2408 PetscErrorCode ierr; 2409 2410 PetscFunctionBegin; 2411 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2412 if (ts->ops->getauxsolution) { 2413 ierr = (*ts->ops->getauxsolution)(ts,v);CHKERRQ(ierr); 2414 } else { 2415 ierr = VecZeroEntries(*v); CHKERRQ(ierr); 2416 } 2417 PetscFunctionReturn(0); 2418 } 2419 2420 /*@ 2421 TSGetTimeError - Returns the estimated error vector, if the chosen 2422 TSType has an error estimation functionality. 2423 2424 Not Collective, but Vec returned is parallel if TS is parallel 2425 2426 Note: MUST call after TSSetUp() 2427 2428 Parameters : 2429 . ts - the TS context obtained from TSCreate() (input parameter). 2430 . n - current estimate (n=0) or previous one (n=-1) 2431 . v - the vector containing the error (same size as the solution). 2432 2433 Level: intermediate 2434 2435 .seealso: TSGetSolution(), TSSetTimeError() 2436 2437 .keywords: TS, timestep, get, error 2438 @*/ 2439 PetscErrorCode TSGetTimeError(TS ts,PetscInt n,Vec *v) 2440 { 2441 PetscErrorCode ierr; 2442 2443 PetscFunctionBegin; 2444 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2445 if (ts->ops->gettimeerror) { 2446 ierr = (*ts->ops->gettimeerror)(ts,n,v);CHKERRQ(ierr); 2447 } else { 2448 ierr = VecZeroEntries(*v);CHKERRQ(ierr); 2449 } 2450 PetscFunctionReturn(0); 2451 } 2452 2453 /*@ 2454 TSSetTimeError - Sets the estimated error vector, if the chosen 2455 TSType has an error estimation functionality. This can be used 2456 to restart such a time integrator with a given error vector. 2457 2458 Not Collective, but Vec returned is parallel if TS is parallel 2459 2460 Parameters : 2461 . ts - the TS context obtained from TSCreate() (input parameter). 2462 . v - the vector containing the error (same size as the solution). 2463 2464 Level: intermediate 2465 2466 .seealso: TSSetSolution(), TSGetTimeError) 2467 2468 .keywords: TS, timestep, get, error 2469 @*/ 2470 PetscErrorCode TSSetTimeError(TS ts,Vec v) 2471 { 2472 PetscErrorCode ierr; 2473 2474 PetscFunctionBegin; 2475 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2476 if (!ts->setupcalled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call TSSetUp() first"); 2477 if (ts->ops->settimeerror) { 2478 ierr = (*ts->ops->settimeerror)(ts,v);CHKERRQ(ierr); 2479 } 2480 PetscFunctionReturn(0); 2481 } 2482 2483 /* ----- Routines to initialize and destroy a timestepper ---- */ 2484 /*@ 2485 TSSetProblemType - Sets the type of problem to be solved. 2486 2487 Not collective 2488 2489 Input Parameters: 2490 + ts - The TS 2491 - type - One of TS_LINEAR, TS_NONLINEAR where these types refer to problems of the forms 2492 .vb 2493 U_t - A U = 0 (linear) 2494 U_t - A(t) U = 0 (linear) 2495 F(t,U,U_t) = 0 (nonlinear) 2496 .ve 2497 2498 Level: beginner 2499 2500 .keywords: TS, problem type 2501 .seealso: TSSetUp(), TSProblemType, TS 2502 @*/ 2503 PetscErrorCode TSSetProblemType(TS ts, TSProblemType type) 2504 { 2505 PetscErrorCode ierr; 2506 2507 PetscFunctionBegin; 2508 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 2509 ts->problem_type = type; 2510 if (type == TS_LINEAR) { 2511 SNES snes; 2512 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 2513 ierr = SNESSetType(snes,SNESKSPONLY);CHKERRQ(ierr); 2514 } 2515 PetscFunctionReturn(0); 2516 } 2517 2518 /*@C 2519 TSGetProblemType - Gets the type of problem to be solved. 2520 2521 Not collective 2522 2523 Input Parameter: 2524 . ts - The TS 2525 2526 Output Parameter: 2527 . type - One of TS_LINEAR, TS_NONLINEAR where these types refer to problems of the forms 2528 .vb 2529 M U_t = A U 2530 M(t) U_t = A(t) U 2531 F(t,U,U_t) 2532 .ve 2533 2534 Level: beginner 2535 2536 .keywords: TS, problem type 2537 .seealso: TSSetUp(), TSProblemType, TS 2538 @*/ 2539 PetscErrorCode TSGetProblemType(TS ts, TSProblemType *type) 2540 { 2541 PetscFunctionBegin; 2542 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 2543 PetscValidIntPointer(type,2); 2544 *type = ts->problem_type; 2545 PetscFunctionReturn(0); 2546 } 2547 2548 /*@ 2549 TSSetUp - Sets up the internal data structures for the later use 2550 of a timestepper. 2551 2552 Collective on TS 2553 2554 Input Parameter: 2555 . ts - the TS context obtained from TSCreate() 2556 2557 Notes: 2558 For basic use of the TS solvers the user need not explicitly call 2559 TSSetUp(), since these actions will automatically occur during 2560 the call to TSStep() or TSSolve(). However, if one wishes to control this 2561 phase separately, TSSetUp() should be called after TSCreate() 2562 and optional routines of the form TSSetXXX(), but before TSStep() and TSSolve(). 2563 2564 Level: advanced 2565 2566 .keywords: TS, timestep, setup 2567 2568 .seealso: TSCreate(), TSStep(), TSDestroy(), TSSolve() 2569 @*/ 2570 PetscErrorCode TSSetUp(TS ts) 2571 { 2572 PetscErrorCode ierr; 2573 DM dm; 2574 PetscErrorCode (*func)(SNES,Vec,Vec,void*); 2575 PetscErrorCode (*jac)(SNES,Vec,Mat,Mat,void*); 2576 TSIFunction ifun; 2577 TSIJacobian ijac; 2578 TSI2Jacobian i2jac; 2579 TSRHSJacobian rhsjac; 2580 PetscBool isnone; 2581 2582 PetscFunctionBegin; 2583 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2584 if (ts->setupcalled) PetscFunctionReturn(0); 2585 2586 if (!((PetscObject)ts)->type_name) { 2587 ierr = TSGetIFunction(ts,NULL,&ifun,NULL);CHKERRQ(ierr); 2588 ierr = TSSetType(ts,ifun ? TSBEULER : TSEULER);CHKERRQ(ierr); 2589 } 2590 2591 if (!ts->vec_sol) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call TSSetSolution() first"); 2592 2593 ierr = TSGetRHSJacobian(ts,NULL,NULL,&rhsjac,NULL);CHKERRQ(ierr); 2594 if (ts->rhsjacobian.reuse && rhsjac == TSComputeRHSJacobianConstant) { 2595 Mat Amat,Pmat; 2596 SNES snes; 2597 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 2598 ierr = SNESGetJacobian(snes,&Amat,&Pmat,NULL,NULL);CHKERRQ(ierr); 2599 /* Matching matrices implies that an IJacobian is NOT set, because if it had been set, the IJacobian's matrix would 2600 * have displaced the RHS matrix */ 2601 if (Amat && Amat == ts->Arhs) { 2602 /* we need to copy the values of the matrix because for the constant Jacobian case the user will never set the numerical values in this new location */ 2603 ierr = MatDuplicate(ts->Arhs,MAT_COPY_VALUES,&Amat);CHKERRQ(ierr); 2604 ierr = SNESSetJacobian(snes,Amat,NULL,NULL,NULL);CHKERRQ(ierr); 2605 ierr = MatDestroy(&Amat);CHKERRQ(ierr); 2606 } 2607 if (Pmat && Pmat == ts->Brhs) { 2608 ierr = MatDuplicate(ts->Brhs,MAT_COPY_VALUES,&Pmat);CHKERRQ(ierr); 2609 ierr = SNESSetJacobian(snes,NULL,Pmat,NULL,NULL);CHKERRQ(ierr); 2610 ierr = MatDestroy(&Pmat);CHKERRQ(ierr); 2611 } 2612 } 2613 2614 ierr = TSGetAdapt(ts,&ts->adapt);CHKERRQ(ierr); 2615 ierr = TSAdaptSetDefaultType(ts->adapt,ts->default_adapt_type);CHKERRQ(ierr); 2616 2617 if (ts->ops->setup) { 2618 ierr = (*ts->ops->setup)(ts);CHKERRQ(ierr); 2619 } 2620 2621 /* Attempt to check/preset a default value for the exact final time option */ 2622 ierr = PetscObjectTypeCompare((PetscObject)ts->adapt,TSADAPTNONE,&isnone);CHKERRQ(ierr); 2623 if (!isnone && ts->exact_final_time == TS_EXACTFINALTIME_UNSPECIFIED) 2624 ts->exact_final_time = TS_EXACTFINALTIME_MATCHSTEP; 2625 2626 /* In the case where we've set a DMTSFunction or what have you, we need the default SNESFunction 2627 to be set right but can't do it elsewhere due to the overreliance on ctx=ts. 2628 */ 2629 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 2630 ierr = DMSNESGetFunction(dm,&func,NULL);CHKERRQ(ierr); 2631 if (!func) { 2632 ierr = DMSNESSetFunction(dm,SNESTSFormFunction,ts);CHKERRQ(ierr); 2633 } 2634 /* If the SNES doesn't have a jacobian set and the TS has an ijacobian or rhsjacobian set, set the SNES to use it. 2635 Otherwise, the SNES will use coloring internally to form the Jacobian. 2636 */ 2637 ierr = DMSNESGetJacobian(dm,&jac,NULL);CHKERRQ(ierr); 2638 ierr = DMTSGetIJacobian(dm,&ijac,NULL);CHKERRQ(ierr); 2639 ierr = DMTSGetI2Jacobian(dm,&i2jac,NULL);CHKERRQ(ierr); 2640 ierr = DMTSGetRHSJacobian(dm,&rhsjac,NULL);CHKERRQ(ierr); 2641 if (!jac && (ijac || i2jac || rhsjac)) { 2642 ierr = DMSNESSetJacobian(dm,SNESTSFormJacobian,ts);CHKERRQ(ierr); 2643 } 2644 2645 /* if time integration scheme has a starting method, call it */ 2646 if (ts->ops->startingmethod) { 2647 ierr = (*ts->ops->startingmethod)(ts);CHKERRQ(ierr); 2648 } 2649 2650 ts->setupcalled = PETSC_TRUE; 2651 PetscFunctionReturn(0); 2652 } 2653 2654 /*@ 2655 TSReset - Resets a TS context and removes any allocated Vecs and Mats. 2656 2657 Collective on TS 2658 2659 Input Parameter: 2660 . ts - the TS context obtained from TSCreate() 2661 2662 Level: beginner 2663 2664 .keywords: TS, timestep, reset 2665 2666 .seealso: TSCreate(), TSSetup(), TSDestroy() 2667 @*/ 2668 PetscErrorCode TSReset(TS ts) 2669 { 2670 TS_RHSSplitLink ilink = ts->tsrhssplit,next; 2671 PetscErrorCode ierr; 2672 2673 PetscFunctionBegin; 2674 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2675 2676 if (ts->ops->reset) { 2677 ierr = (*ts->ops->reset)(ts);CHKERRQ(ierr); 2678 } 2679 if (ts->snes) {ierr = SNESReset(ts->snes);CHKERRQ(ierr);} 2680 if (ts->adapt) {ierr = TSAdaptReset(ts->adapt);CHKERRQ(ierr);} 2681 2682 ierr = MatDestroy(&ts->Arhs);CHKERRQ(ierr); 2683 ierr = MatDestroy(&ts->Brhs);CHKERRQ(ierr); 2684 ierr = VecDestroy(&ts->Frhs);CHKERRQ(ierr); 2685 ierr = VecDestroy(&ts->vec_sol);CHKERRQ(ierr); 2686 ierr = VecDestroy(&ts->vec_dot);CHKERRQ(ierr); 2687 ierr = VecDestroy(&ts->vatol);CHKERRQ(ierr); 2688 ierr = VecDestroy(&ts->vrtol);CHKERRQ(ierr); 2689 ierr = VecDestroyVecs(ts->nwork,&ts->work);CHKERRQ(ierr); 2690 2691 ierr = VecDestroyVecs(ts->numcost,&ts->vecs_drdu);CHKERRQ(ierr); 2692 ierr = VecDestroyVecs(ts->numcost,&ts->vecs_drdp);CHKERRQ(ierr); 2693 2694 ierr = MatDestroy(&ts->Jacp);CHKERRQ(ierr); 2695 ierr = VecDestroy(&ts->vec_costintegral);CHKERRQ(ierr); 2696 ierr = VecDestroy(&ts->vec_costintegrand);CHKERRQ(ierr); 2697 2698 while (ilink) { 2699 next = ilink->next; 2700 ierr = TSDestroy(&ilink->ts);CHKERRQ(ierr); 2701 ierr = PetscFree(ilink->splitname);CHKERRQ(ierr); 2702 ierr = ISDestroy(&ilink->is);CHKERRQ(ierr); 2703 ierr = PetscFree(ilink);CHKERRQ(ierr); 2704 ilink = next; 2705 } 2706 ts->num_rhs_splits = 0; 2707 ts->setupcalled = PETSC_FALSE; 2708 PetscFunctionReturn(0); 2709 } 2710 2711 /*@ 2712 TSDestroy - Destroys the timestepper context that was created 2713 with TSCreate(). 2714 2715 Collective on TS 2716 2717 Input Parameter: 2718 . ts - the TS context obtained from TSCreate() 2719 2720 Level: beginner 2721 2722 .keywords: TS, timestepper, destroy 2723 2724 .seealso: TSCreate(), TSSetUp(), TSSolve() 2725 @*/ 2726 PetscErrorCode TSDestroy(TS *ts) 2727 { 2728 PetscErrorCode ierr; 2729 2730 PetscFunctionBegin; 2731 if (!*ts) PetscFunctionReturn(0); 2732 PetscValidHeaderSpecific((*ts),TS_CLASSID,1); 2733 if (--((PetscObject)(*ts))->refct > 0) {*ts = 0; PetscFunctionReturn(0);} 2734 2735 ierr = TSReset((*ts));CHKERRQ(ierr); 2736 ierr = TSAdjointReset((*ts));CHKERRQ(ierr); 2737 ierr = TSForwardReset((*ts));CHKERRQ(ierr); 2738 2739 /* if memory was published with SAWs then destroy it */ 2740 ierr = PetscObjectSAWsViewOff((PetscObject)*ts);CHKERRQ(ierr); 2741 if ((*ts)->ops->destroy) {ierr = (*(*ts)->ops->destroy)((*ts));CHKERRQ(ierr);} 2742 2743 ierr = TSTrajectoryDestroy(&(*ts)->trajectory);CHKERRQ(ierr); 2744 2745 ierr = TSAdaptDestroy(&(*ts)->adapt);CHKERRQ(ierr); 2746 ierr = TSEventDestroy(&(*ts)->event);CHKERRQ(ierr); 2747 2748 ierr = SNESDestroy(&(*ts)->snes);CHKERRQ(ierr); 2749 ierr = DMDestroy(&(*ts)->dm);CHKERRQ(ierr); 2750 ierr = TSMonitorCancel((*ts));CHKERRQ(ierr); 2751 ierr = TSAdjointMonitorCancel((*ts));CHKERRQ(ierr); 2752 2753 ierr = PetscHeaderDestroy(ts);CHKERRQ(ierr); 2754 PetscFunctionReturn(0); 2755 } 2756 2757 /*@ 2758 TSGetSNES - Returns the SNES (nonlinear solver) associated with 2759 a TS (timestepper) context. Valid only for nonlinear problems. 2760 2761 Not Collective, but SNES is parallel if TS is parallel 2762 2763 Input Parameter: 2764 . ts - the TS context obtained from TSCreate() 2765 2766 Output Parameter: 2767 . snes - the nonlinear solver context 2768 2769 Notes: 2770 The user can then directly manipulate the SNES context to set various 2771 options, etc. Likewise, the user can then extract and manipulate the 2772 KSP, KSP, and PC contexts as well. 2773 2774 TSGetSNES() does not work for integrators that do not use SNES; in 2775 this case TSGetSNES() returns NULL in snes. 2776 2777 Level: beginner 2778 2779 .keywords: timestep, get, SNES 2780 @*/ 2781 PetscErrorCode TSGetSNES(TS ts,SNES *snes) 2782 { 2783 PetscErrorCode ierr; 2784 2785 PetscFunctionBegin; 2786 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2787 PetscValidPointer(snes,2); 2788 if (!ts->snes) { 2789 ierr = SNESCreate(PetscObjectComm((PetscObject)ts),&ts->snes);CHKERRQ(ierr); 2790 ierr = PetscObjectSetOptions((PetscObject)ts->snes,((PetscObject)ts)->options);CHKERRQ(ierr); 2791 ierr = SNESSetFunction(ts->snes,NULL,SNESTSFormFunction,ts);CHKERRQ(ierr); 2792 ierr = PetscLogObjectParent((PetscObject)ts,(PetscObject)ts->snes);CHKERRQ(ierr); 2793 ierr = PetscObjectIncrementTabLevel((PetscObject)ts->snes,(PetscObject)ts,1);CHKERRQ(ierr); 2794 if (ts->dm) {ierr = SNESSetDM(ts->snes,ts->dm);CHKERRQ(ierr);} 2795 if (ts->problem_type == TS_LINEAR) { 2796 ierr = SNESSetType(ts->snes,SNESKSPONLY);CHKERRQ(ierr); 2797 } 2798 } 2799 *snes = ts->snes; 2800 PetscFunctionReturn(0); 2801 } 2802 2803 /*@ 2804 TSSetSNES - Set the SNES (nonlinear solver) to be used by the timestepping context 2805 2806 Collective 2807 2808 Input Parameter: 2809 + ts - the TS context obtained from TSCreate() 2810 - snes - the nonlinear solver context 2811 2812 Notes: 2813 Most users should have the TS created by calling TSGetSNES() 2814 2815 Level: developer 2816 2817 .keywords: timestep, set, SNES 2818 @*/ 2819 PetscErrorCode TSSetSNES(TS ts,SNES snes) 2820 { 2821 PetscErrorCode ierr; 2822 PetscErrorCode (*func)(SNES,Vec,Mat,Mat,void*); 2823 2824 PetscFunctionBegin; 2825 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2826 PetscValidHeaderSpecific(snes,SNES_CLASSID,2); 2827 ierr = PetscObjectReference((PetscObject)snes);CHKERRQ(ierr); 2828 ierr = SNESDestroy(&ts->snes);CHKERRQ(ierr); 2829 2830 ts->snes = snes; 2831 2832 ierr = SNESSetFunction(ts->snes,NULL,SNESTSFormFunction,ts);CHKERRQ(ierr); 2833 ierr = SNESGetJacobian(ts->snes,NULL,NULL,&func,NULL);CHKERRQ(ierr); 2834 if (func == SNESTSFormJacobian) { 2835 ierr = SNESSetJacobian(ts->snes,NULL,NULL,SNESTSFormJacobian,ts);CHKERRQ(ierr); 2836 } 2837 PetscFunctionReturn(0); 2838 } 2839 2840 /*@ 2841 TSGetKSP - Returns the KSP (linear solver) associated with 2842 a TS (timestepper) context. 2843 2844 Not Collective, but KSP is parallel if TS is parallel 2845 2846 Input Parameter: 2847 . ts - the TS context obtained from TSCreate() 2848 2849 Output Parameter: 2850 . ksp - the nonlinear solver context 2851 2852 Notes: 2853 The user can then directly manipulate the KSP context to set various 2854 options, etc. Likewise, the user can then extract and manipulate the 2855 KSP and PC contexts as well. 2856 2857 TSGetKSP() does not work for integrators that do not use KSP; 2858 in this case TSGetKSP() returns NULL in ksp. 2859 2860 Level: beginner 2861 2862 .keywords: timestep, get, KSP 2863 @*/ 2864 PetscErrorCode TSGetKSP(TS ts,KSP *ksp) 2865 { 2866 PetscErrorCode ierr; 2867 SNES snes; 2868 2869 PetscFunctionBegin; 2870 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2871 PetscValidPointer(ksp,2); 2872 if (!((PetscObject)ts)->type_name) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_NULL,"KSP is not created yet. Call TSSetType() first"); 2873 if (ts->problem_type != TS_LINEAR) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Linear only; use TSGetSNES()"); 2874 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 2875 ierr = SNESGetKSP(snes,ksp);CHKERRQ(ierr); 2876 PetscFunctionReturn(0); 2877 } 2878 2879 /* ----------- Routines to set solver parameters ---------- */ 2880 2881 /*@ 2882 TSSetMaxSteps - Sets the maximum number of steps to use. 2883 2884 Logically Collective on TS 2885 2886 Input Parameters: 2887 + ts - the TS context obtained from TSCreate() 2888 - maxsteps - maximum number of steps to use 2889 2890 Options Database Keys: 2891 . -ts_max_steps <maxsteps> - Sets maxsteps 2892 2893 Notes: 2894 The default maximum number of steps is 5000 2895 2896 Level: intermediate 2897 2898 .keywords: TS, timestep, set, maximum, steps 2899 2900 .seealso: TSGetMaxSteps(), TSSetMaxTime(), TSSetExactFinalTime() 2901 @*/ 2902 PetscErrorCode TSSetMaxSteps(TS ts,PetscInt maxsteps) 2903 { 2904 PetscFunctionBegin; 2905 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2906 PetscValidLogicalCollectiveInt(ts,maxsteps,2); 2907 if (maxsteps < 0 ) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Maximum number of steps must be non-negative"); 2908 ts->max_steps = maxsteps; 2909 PetscFunctionReturn(0); 2910 } 2911 2912 /*@ 2913 TSGetMaxSteps - Gets the maximum number of steps to use. 2914 2915 Not Collective 2916 2917 Input Parameters: 2918 . ts - the TS context obtained from TSCreate() 2919 2920 Output Parameter: 2921 . maxsteps - maximum number of steps to use 2922 2923 Level: advanced 2924 2925 .keywords: TS, timestep, get, maximum, steps 2926 2927 .seealso: TSSetMaxSteps(), TSGetMaxTime(), TSSetMaxTime() 2928 @*/ 2929 PetscErrorCode TSGetMaxSteps(TS ts,PetscInt *maxsteps) 2930 { 2931 PetscFunctionBegin; 2932 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2933 PetscValidIntPointer(maxsteps,2); 2934 *maxsteps = ts->max_steps; 2935 PetscFunctionReturn(0); 2936 } 2937 2938 /*@ 2939 TSSetMaxTime - Sets the maximum (or final) time for timestepping. 2940 2941 Logically Collective on TS 2942 2943 Input Parameters: 2944 + ts - the TS context obtained from TSCreate() 2945 - maxtime - final time to step to 2946 2947 Options Database Keys: 2948 . -ts_max_time <maxtime> - Sets maxtime 2949 2950 Notes: 2951 The default maximum time is 5.0 2952 2953 Level: intermediate 2954 2955 .keywords: TS, timestep, set, maximum, time 2956 2957 .seealso: TSGetMaxTime(), TSSetMaxSteps(), TSSetExactFinalTime() 2958 @*/ 2959 PetscErrorCode TSSetMaxTime(TS ts,PetscReal maxtime) 2960 { 2961 PetscFunctionBegin; 2962 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2963 PetscValidLogicalCollectiveReal(ts,maxtime,2); 2964 ts->max_time = maxtime; 2965 PetscFunctionReturn(0); 2966 } 2967 2968 /*@ 2969 TSGetMaxTime - Gets the maximum (or final) time for timestepping. 2970 2971 Not Collective 2972 2973 Input Parameters: 2974 . ts - the TS context obtained from TSCreate() 2975 2976 Output Parameter: 2977 . maxtime - final time to step to 2978 2979 Level: advanced 2980 2981 .keywords: TS, timestep, get, maximum, time 2982 2983 .seealso: TSSetMaxTime(), TSGetMaxSteps(), TSSetMaxSteps() 2984 @*/ 2985 PetscErrorCode TSGetMaxTime(TS ts,PetscReal *maxtime) 2986 { 2987 PetscFunctionBegin; 2988 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2989 PetscValidRealPointer(maxtime,2); 2990 *maxtime = ts->max_time; 2991 PetscFunctionReturn(0); 2992 } 2993 2994 /*@ 2995 TSSetInitialTimeStep - Deprecated, use TSSetTime() and TSSetTimeStep(). 2996 2997 Level: deprecated 2998 2999 @*/ 3000 PetscErrorCode TSSetInitialTimeStep(TS ts,PetscReal initial_time,PetscReal time_step) 3001 { 3002 PetscErrorCode ierr; 3003 PetscFunctionBegin; 3004 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3005 ierr = TSSetTime(ts,initial_time);CHKERRQ(ierr); 3006 ierr = TSSetTimeStep(ts,time_step);CHKERRQ(ierr); 3007 PetscFunctionReturn(0); 3008 } 3009 3010 /*@ 3011 TSGetDuration - Deprecated, use TSGetMaxSteps() and TSGetMaxTime(). 3012 3013 Level: deprecated 3014 3015 @*/ 3016 PetscErrorCode TSGetDuration(TS ts, PetscInt *maxsteps, PetscReal *maxtime) 3017 { 3018 PetscFunctionBegin; 3019 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3020 if (maxsteps) { 3021 PetscValidIntPointer(maxsteps,2); 3022 *maxsteps = ts->max_steps; 3023 } 3024 if (maxtime) { 3025 PetscValidScalarPointer(maxtime,3); 3026 *maxtime = ts->max_time; 3027 } 3028 PetscFunctionReturn(0); 3029 } 3030 3031 /*@ 3032 TSSetDuration - Deprecated, use TSSetMaxSteps() and TSSetMaxTime(). 3033 3034 Level: deprecated 3035 3036 @*/ 3037 PetscErrorCode TSSetDuration(TS ts,PetscInt maxsteps,PetscReal maxtime) 3038 { 3039 PetscFunctionBegin; 3040 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3041 PetscValidLogicalCollectiveInt(ts,maxsteps,2); 3042 PetscValidLogicalCollectiveReal(ts,maxtime,2); 3043 if (maxsteps >= 0) ts->max_steps = maxsteps; 3044 if (maxtime != PETSC_DEFAULT) ts->max_time = maxtime; 3045 PetscFunctionReturn(0); 3046 } 3047 3048 /*@ 3049 TSGetTimeStepNumber - Deprecated, use TSGetStepNumber(). 3050 3051 Level: deprecated 3052 3053 @*/ 3054 PetscErrorCode TSGetTimeStepNumber(TS ts,PetscInt *steps) { return TSGetStepNumber(ts,steps); } 3055 3056 /*@ 3057 TSGetTotalSteps - Deprecated, use TSGetStepNumber(). 3058 3059 Level: deprecated 3060 3061 @*/ 3062 PetscErrorCode TSGetTotalSteps(TS ts,PetscInt *steps) { return TSGetStepNumber(ts,steps); } 3063 3064 /*@ 3065 TSSetSolution - Sets the initial solution vector 3066 for use by the TS routines. 3067 3068 Logically Collective on TS and Vec 3069 3070 Input Parameters: 3071 + ts - the TS context obtained from TSCreate() 3072 - u - the solution vector 3073 3074 Level: beginner 3075 3076 .keywords: TS, timestep, set, solution, initial values 3077 3078 .seealso: TSSetSolutionFunction(), TSGetSolution(), TSCreate() 3079 @*/ 3080 PetscErrorCode TSSetSolution(TS ts,Vec u) 3081 { 3082 PetscErrorCode ierr; 3083 DM dm; 3084 3085 PetscFunctionBegin; 3086 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3087 PetscValidHeaderSpecific(u,VEC_CLASSID,2); 3088 ierr = PetscObjectReference((PetscObject)u);CHKERRQ(ierr); 3089 ierr = VecDestroy(&ts->vec_sol);CHKERRQ(ierr); 3090 ts->vec_sol = u; 3091 3092 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 3093 ierr = DMShellSetGlobalVector(dm,u);CHKERRQ(ierr); 3094 PetscFunctionReturn(0); 3095 } 3096 3097 /*@C 3098 TSSetPreStep - Sets the general-purpose function 3099 called once at the beginning of each time step. 3100 3101 Logically Collective on TS 3102 3103 Input Parameters: 3104 + ts - The TS context obtained from TSCreate() 3105 - func - The function 3106 3107 Calling sequence of func: 3108 . func (TS ts); 3109 3110 Level: intermediate 3111 3112 .keywords: TS, timestep 3113 .seealso: TSSetPreStage(), TSSetPostStage(), TSSetPostStep(), TSStep(), TSRestartStep() 3114 @*/ 3115 PetscErrorCode TSSetPreStep(TS ts, PetscErrorCode (*func)(TS)) 3116 { 3117 PetscFunctionBegin; 3118 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3119 ts->prestep = func; 3120 PetscFunctionReturn(0); 3121 } 3122 3123 /*@ 3124 TSPreStep - Runs the user-defined pre-step function. 3125 3126 Collective on TS 3127 3128 Input Parameters: 3129 . ts - The TS context obtained from TSCreate() 3130 3131 Notes: 3132 TSPreStep() is typically used within time stepping implementations, 3133 so most users would not generally call this routine themselves. 3134 3135 Level: developer 3136 3137 .keywords: TS, timestep 3138 .seealso: TSSetPreStep(), TSPreStage(), TSPostStage(), TSPostStep() 3139 @*/ 3140 PetscErrorCode TSPreStep(TS ts) 3141 { 3142 PetscErrorCode ierr; 3143 3144 PetscFunctionBegin; 3145 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3146 if (ts->prestep) { 3147 Vec U; 3148 PetscObjectState sprev,spost; 3149 3150 ierr = TSGetSolution(ts,&U);CHKERRQ(ierr); 3151 ierr = PetscObjectStateGet((PetscObject)U,&sprev);CHKERRQ(ierr); 3152 PetscStackCallStandard((*ts->prestep),(ts)); 3153 ierr = PetscObjectStateGet((PetscObject)U,&spost);CHKERRQ(ierr); 3154 if (sprev != spost) {ierr = TSRestartStep(ts);CHKERRQ(ierr);} 3155 } 3156 PetscFunctionReturn(0); 3157 } 3158 3159 /*@C 3160 TSSetPreStage - Sets the general-purpose function 3161 called once at the beginning of each stage. 3162 3163 Logically Collective on TS 3164 3165 Input Parameters: 3166 + ts - The TS context obtained from TSCreate() 3167 - func - The function 3168 3169 Calling sequence of func: 3170 . PetscErrorCode func(TS ts, PetscReal stagetime); 3171 3172 Level: intermediate 3173 3174 Note: 3175 There may be several stages per time step. If the solve for a given stage fails, the step may be rejected and retried. 3176 The time step number being computed can be queried using TSGetStepNumber() and the total size of the step being 3177 attempted can be obtained using TSGetTimeStep(). The time at the start of the step is available via TSGetTime(). 3178 3179 .keywords: TS, timestep 3180 .seealso: TSSetPostStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext() 3181 @*/ 3182 PetscErrorCode TSSetPreStage(TS ts, PetscErrorCode (*func)(TS,PetscReal)) 3183 { 3184 PetscFunctionBegin; 3185 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3186 ts->prestage = func; 3187 PetscFunctionReturn(0); 3188 } 3189 3190 /*@C 3191 TSSetPostStage - Sets the general-purpose function 3192 called once at the end of each stage. 3193 3194 Logically Collective on TS 3195 3196 Input Parameters: 3197 + ts - The TS context obtained from TSCreate() 3198 - func - The function 3199 3200 Calling sequence of func: 3201 . PetscErrorCode func(TS ts, PetscReal stagetime, PetscInt stageindex, Vec* Y); 3202 3203 Level: intermediate 3204 3205 Note: 3206 There may be several stages per time step. If the solve for a given stage fails, the step may be rejected and retried. 3207 The time step number being computed can be queried using TSGetStepNumber() and the total size of the step being 3208 attempted can be obtained using TSGetTimeStep(). The time at the start of the step is available via TSGetTime(). 3209 3210 .keywords: TS, timestep 3211 .seealso: TSSetPreStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext() 3212 @*/ 3213 PetscErrorCode TSSetPostStage(TS ts, PetscErrorCode (*func)(TS,PetscReal,PetscInt,Vec*)) 3214 { 3215 PetscFunctionBegin; 3216 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3217 ts->poststage = func; 3218 PetscFunctionReturn(0); 3219 } 3220 3221 /*@C 3222 TSSetPostEvaluate - Sets the general-purpose function 3223 called once at the end of each step evaluation. 3224 3225 Logically Collective on TS 3226 3227 Input Parameters: 3228 + ts - The TS context obtained from TSCreate() 3229 - func - The function 3230 3231 Calling sequence of func: 3232 . PetscErrorCode func(TS ts); 3233 3234 Level: intermediate 3235 3236 Note: 3237 Semantically, TSSetPostEvaluate() differs from TSSetPostStep() since the function it sets is called before event-handling 3238 thus guaranteeing the same solution (computed by the time-stepper) will be passed to it. On the other hand, TSPostStep() 3239 may be passed a different solution, possibly changed by the event handler. TSPostEvaluate() is called after the next step 3240 solution is evaluated allowing to modify it, if need be. The solution can be obtained with TSGetSolution(), the time step 3241 with TSGetTimeStep(), and the time at the start of the step is available via TSGetTime() 3242 3243 .keywords: TS, timestep 3244 .seealso: TSSetPreStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext() 3245 @*/ 3246 PetscErrorCode TSSetPostEvaluate(TS ts, PetscErrorCode (*func)(TS)) 3247 { 3248 PetscFunctionBegin; 3249 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3250 ts->postevaluate = func; 3251 PetscFunctionReturn(0); 3252 } 3253 3254 /*@ 3255 TSPreStage - Runs the user-defined pre-stage function set using TSSetPreStage() 3256 3257 Collective on TS 3258 3259 Input Parameters: 3260 . ts - The TS context obtained from TSCreate() 3261 stagetime - The absolute time of the current stage 3262 3263 Notes: 3264 TSPreStage() is typically used within time stepping implementations, 3265 most users would not generally call this routine themselves. 3266 3267 Level: developer 3268 3269 .keywords: TS, timestep 3270 .seealso: TSPostStage(), TSSetPreStep(), TSPreStep(), TSPostStep() 3271 @*/ 3272 PetscErrorCode TSPreStage(TS ts, PetscReal stagetime) 3273 { 3274 PetscFunctionBegin; 3275 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3276 if (ts->prestage) { 3277 PetscStackCallStandard((*ts->prestage),(ts,stagetime)); 3278 } 3279 PetscFunctionReturn(0); 3280 } 3281 3282 /*@ 3283 TSPostStage - Runs the user-defined post-stage function set using TSSetPostStage() 3284 3285 Collective on TS 3286 3287 Input Parameters: 3288 . ts - The TS context obtained from TSCreate() 3289 stagetime - The absolute time of the current stage 3290 stageindex - Stage number 3291 Y - Array of vectors (of size = total number 3292 of stages) with the stage solutions 3293 3294 Notes: 3295 TSPostStage() is typically used within time stepping implementations, 3296 most users would not generally call this routine themselves. 3297 3298 Level: developer 3299 3300 .keywords: TS, timestep 3301 .seealso: TSPreStage(), TSSetPreStep(), TSPreStep(), TSPostStep() 3302 @*/ 3303 PetscErrorCode TSPostStage(TS ts, PetscReal stagetime, PetscInt stageindex, Vec *Y) 3304 { 3305 PetscFunctionBegin; 3306 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3307 if (ts->poststage) { 3308 PetscStackCallStandard((*ts->poststage),(ts,stagetime,stageindex,Y)); 3309 } 3310 PetscFunctionReturn(0); 3311 } 3312 3313 /*@ 3314 TSPostEvaluate - Runs the user-defined post-evaluate function set using TSSetPostEvaluate() 3315 3316 Collective on TS 3317 3318 Input Parameters: 3319 . ts - The TS context obtained from TSCreate() 3320 3321 Notes: 3322 TSPostEvaluate() is typically used within time stepping implementations, 3323 most users would not generally call this routine themselves. 3324 3325 Level: developer 3326 3327 .keywords: TS, timestep 3328 .seealso: TSSetPostEvaluate(), TSSetPreStep(), TSPreStep(), TSPostStep() 3329 @*/ 3330 PetscErrorCode TSPostEvaluate(TS ts) 3331 { 3332 PetscErrorCode ierr; 3333 3334 PetscFunctionBegin; 3335 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3336 if (ts->postevaluate) { 3337 Vec U; 3338 PetscObjectState sprev,spost; 3339 3340 ierr = TSGetSolution(ts,&U);CHKERRQ(ierr); 3341 ierr = PetscObjectStateGet((PetscObject)U,&sprev);CHKERRQ(ierr); 3342 PetscStackCallStandard((*ts->postevaluate),(ts)); 3343 ierr = PetscObjectStateGet((PetscObject)U,&spost);CHKERRQ(ierr); 3344 if (sprev != spost) {ierr = TSRestartStep(ts);CHKERRQ(ierr);} 3345 } 3346 PetscFunctionReturn(0); 3347 } 3348 3349 /*@C 3350 TSSetPostStep - Sets the general-purpose function 3351 called once at the end of each time step. 3352 3353 Logically Collective on TS 3354 3355 Input Parameters: 3356 + ts - The TS context obtained from TSCreate() 3357 - func - The function 3358 3359 Calling sequence of func: 3360 $ func (TS ts); 3361 3362 Notes: 3363 The function set by TSSetPostStep() is called after each successful step. The solution vector X 3364 obtained by TSGetSolution() may be different than that computed at the step end if the event handler 3365 locates an event and TSPostEvent() modifies it. Use TSSetPostEvaluate() if an unmodified solution is needed instead. 3366 3367 Level: intermediate 3368 3369 .keywords: TS, timestep 3370 .seealso: TSSetPreStep(), TSSetPreStage(), TSSetPostEvaluate(), TSGetTimeStep(), TSGetStepNumber(), TSGetTime(), TSRestartStep() 3371 @*/ 3372 PetscErrorCode TSSetPostStep(TS ts, PetscErrorCode (*func)(TS)) 3373 { 3374 PetscFunctionBegin; 3375 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3376 ts->poststep = func; 3377 PetscFunctionReturn(0); 3378 } 3379 3380 /*@ 3381 TSPostStep - Runs the user-defined post-step function. 3382 3383 Collective on TS 3384 3385 Input Parameters: 3386 . ts - The TS context obtained from TSCreate() 3387 3388 Notes: 3389 TSPostStep() is typically used within time stepping implementations, 3390 so most users would not generally call this routine themselves. 3391 3392 Level: developer 3393 3394 .keywords: TS, timestep 3395 @*/ 3396 PetscErrorCode TSPostStep(TS ts) 3397 { 3398 PetscErrorCode ierr; 3399 3400 PetscFunctionBegin; 3401 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3402 if (ts->poststep) { 3403 Vec U; 3404 PetscObjectState sprev,spost; 3405 3406 ierr = TSGetSolution(ts,&U);CHKERRQ(ierr); 3407 ierr = PetscObjectStateGet((PetscObject)U,&sprev);CHKERRQ(ierr); 3408 PetscStackCallStandard((*ts->poststep),(ts)); 3409 ierr = PetscObjectStateGet((PetscObject)U,&spost);CHKERRQ(ierr); 3410 if (sprev != spost) {ierr = TSRestartStep(ts);CHKERRQ(ierr);} 3411 } 3412 PetscFunctionReturn(0); 3413 } 3414 3415 /* ------------ Routines to set performance monitoring options ----------- */ 3416 3417 /*@C 3418 TSMonitorSet - Sets an ADDITIONAL function that is to be used at every 3419 timestep to display the iteration's progress. 3420 3421 Logically Collective on TS 3422 3423 Input Parameters: 3424 + ts - the TS context obtained from TSCreate() 3425 . monitor - monitoring routine 3426 . mctx - [optional] user-defined context for private data for the 3427 monitor routine (use NULL if no context is desired) 3428 - monitordestroy - [optional] routine that frees monitor context 3429 (may be NULL) 3430 3431 Calling sequence of monitor: 3432 $ PetscErrorCode monitor(TS ts,PetscInt steps,PetscReal time,Vec u,void *mctx) 3433 3434 + ts - the TS context 3435 . 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) 3436 . time - current time 3437 . u - current iterate 3438 - mctx - [optional] monitoring context 3439 3440 Notes: 3441 This routine adds an additional monitor to the list of monitors that 3442 already has been loaded. 3443 3444 Fortran Notes: 3445 Only a single monitor function can be set for each TS object 3446 3447 Level: intermediate 3448 3449 .keywords: TS, timestep, set, monitor 3450 3451 .seealso: TSMonitorDefault(), TSMonitorCancel() 3452 @*/ 3453 PetscErrorCode TSMonitorSet(TS ts,PetscErrorCode (*monitor)(TS,PetscInt,PetscReal,Vec,void*),void *mctx,PetscErrorCode (*mdestroy)(void**)) 3454 { 3455 PetscErrorCode ierr; 3456 PetscInt i; 3457 PetscBool identical; 3458 3459 PetscFunctionBegin; 3460 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3461 for (i=0; i<ts->numbermonitors;i++) { 3462 ierr = PetscMonitorCompare((PetscErrorCode (*)(void))monitor,mctx,mdestroy,(PetscErrorCode (*)(void))ts->monitor[i],ts->monitorcontext[i],ts->monitordestroy[i],&identical);CHKERRQ(ierr); 3463 if (identical) PetscFunctionReturn(0); 3464 } 3465 if (ts->numbermonitors >= MAXTSMONITORS) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Too many monitors set"); 3466 ts->monitor[ts->numbermonitors] = monitor; 3467 ts->monitordestroy[ts->numbermonitors] = mdestroy; 3468 ts->monitorcontext[ts->numbermonitors++] = (void*)mctx; 3469 PetscFunctionReturn(0); 3470 } 3471 3472 /*@C 3473 TSMonitorCancel - Clears all the monitors that have been set on a time-step object. 3474 3475 Logically Collective on TS 3476 3477 Input Parameters: 3478 . ts - the TS context obtained from TSCreate() 3479 3480 Notes: 3481 There is no way to remove a single, specific monitor. 3482 3483 Level: intermediate 3484 3485 .keywords: TS, timestep, set, monitor 3486 3487 .seealso: TSMonitorDefault(), TSMonitorSet() 3488 @*/ 3489 PetscErrorCode TSMonitorCancel(TS ts) 3490 { 3491 PetscErrorCode ierr; 3492 PetscInt i; 3493 3494 PetscFunctionBegin; 3495 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3496 for (i=0; i<ts->numbermonitors; i++) { 3497 if (ts->monitordestroy[i]) { 3498 ierr = (*ts->monitordestroy[i])(&ts->monitorcontext[i]);CHKERRQ(ierr); 3499 } 3500 } 3501 ts->numbermonitors = 0; 3502 PetscFunctionReturn(0); 3503 } 3504 3505 /*@C 3506 TSMonitorDefault - The Default monitor, prints the timestep and time for each step 3507 3508 Level: intermediate 3509 3510 .keywords: TS, set, monitor 3511 3512 .seealso: TSMonitorSet() 3513 @*/ 3514 PetscErrorCode TSMonitorDefault(TS ts,PetscInt step,PetscReal ptime,Vec v,PetscViewerAndFormat *vf) 3515 { 3516 PetscErrorCode ierr; 3517 PetscViewer viewer = vf->viewer; 3518 PetscBool iascii,ibinary; 3519 3520 PetscFunctionBegin; 3521 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,4); 3522 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 3523 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&ibinary);CHKERRQ(ierr); 3524 ierr = PetscViewerPushFormat(viewer,vf->format);CHKERRQ(ierr); 3525 if (iascii) { 3526 ierr = PetscViewerASCIIAddTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 3527 if (step == -1){ /* this indicates it is an interpolated solution */ 3528 ierr = PetscViewerASCIIPrintf(viewer,"Interpolated solution at time %g between steps %D and %D\n",(double)ptime,ts->steps-1,ts->steps);CHKERRQ(ierr); 3529 } else { 3530 ierr = PetscViewerASCIIPrintf(viewer,"%D TS dt %g time %g%s",step,(double)ts->time_step,(double)ptime,ts->steprollback ? " (r)\n" : "\n");CHKERRQ(ierr); 3531 } 3532 ierr = PetscViewerASCIISubtractTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 3533 } else if (ibinary) { 3534 PetscMPIInt rank; 3535 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)viewer),&rank);CHKERRQ(ierr); 3536 if (!rank) { 3537 PetscBool skipHeader; 3538 PetscInt classid = REAL_FILE_CLASSID; 3539 3540 ierr = PetscViewerBinaryGetSkipHeader(viewer,&skipHeader);CHKERRQ(ierr); 3541 if (!skipHeader) { 3542 ierr = PetscViewerBinaryWrite(viewer,&classid,1,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); 3543 } 3544 ierr = PetscRealView(1,&ptime,viewer);CHKERRQ(ierr); 3545 } else { 3546 ierr = PetscRealView(0,&ptime,viewer);CHKERRQ(ierr); 3547 } 3548 } 3549 ierr = PetscViewerPopFormat(viewer);CHKERRQ(ierr); 3550 PetscFunctionReturn(0); 3551 } 3552 3553 /*@C 3554 TSMonitorExtreme - Prints the extreme values of the solution at each timestep 3555 3556 Level: intermediate 3557 3558 .keywords: TS, set, monitor 3559 3560 .seealso: TSMonitorSet() 3561 @*/ 3562 PetscErrorCode TSMonitorExtreme(TS ts,PetscInt step,PetscReal ptime,Vec v,PetscViewerAndFormat *vf) 3563 { 3564 PetscErrorCode ierr; 3565 PetscViewer viewer = vf->viewer; 3566 PetscBool iascii; 3567 PetscReal max,min; 3568 3569 3570 PetscFunctionBegin; 3571 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,4); 3572 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 3573 ierr = PetscViewerPushFormat(viewer,vf->format);CHKERRQ(ierr); 3574 if (iascii) { 3575 ierr = VecMax(v,NULL,&max);CHKERRQ(ierr); 3576 ierr = VecMin(v,NULL,&min);CHKERRQ(ierr); 3577 ierr = PetscViewerASCIIAddTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 3578 ierr = PetscViewerASCIIPrintf(viewer,"%D TS dt %g time %g%s max %g min %g\n",step,(double)ts->time_step,(double)ptime,ts->steprollback ? " (r)" : "",(double)max,(double)min);CHKERRQ(ierr); 3579 ierr = PetscViewerASCIISubtractTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 3580 } 3581 ierr = PetscViewerPopFormat(viewer);CHKERRQ(ierr); 3582 PetscFunctionReturn(0); 3583 } 3584 3585 /*@ 3586 TSInterpolate - Interpolate the solution computed during the previous step to an arbitrary location in the interval 3587 3588 Collective on TS 3589 3590 Input Argument: 3591 + ts - time stepping context 3592 - t - time to interpolate to 3593 3594 Output Argument: 3595 . U - state at given time 3596 3597 Level: intermediate 3598 3599 Developer Notes: 3600 TSInterpolate() and the storing of previous steps/stages should be generalized to support delay differential equations and continuous adjoints. 3601 3602 .keywords: TS, set 3603 3604 .seealso: TSSetExactFinalTime(), TSSolve() 3605 @*/ 3606 PetscErrorCode TSInterpolate(TS ts,PetscReal t,Vec U) 3607 { 3608 PetscErrorCode ierr; 3609 3610 PetscFunctionBegin; 3611 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3612 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 3613 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); 3614 if (!ts->ops->interpolate) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"%s does not provide interpolation",((PetscObject)ts)->type_name); 3615 ierr = (*ts->ops->interpolate)(ts,t,U);CHKERRQ(ierr); 3616 PetscFunctionReturn(0); 3617 } 3618 3619 /*@ 3620 TSStep - Steps one time step 3621 3622 Collective on TS 3623 3624 Input Parameter: 3625 . ts - the TS context obtained from TSCreate() 3626 3627 Level: developer 3628 3629 Notes: 3630 The public interface for the ODE/DAE solvers is TSSolve(), you should almost for sure be using that routine and not this routine. 3631 3632 The hook set using TSSetPreStep() is called before each attempt to take the step. In general, the time step size may 3633 be changed due to adaptive error controller or solve failures. Note that steps may contain multiple stages. 3634 3635 This may over-step the final time provided in TSSetMaxTime() depending on the time-step used. TSSolve() interpolates to exactly the 3636 time provided in TSSetMaxTime(). One can use TSInterpolate() to determine an interpolated solution within the final timestep. 3637 3638 .keywords: TS, timestep, solve 3639 3640 .seealso: TSCreate(), TSSetUp(), TSDestroy(), TSSolve(), TSSetPreStep(), TSSetPreStage(), TSSetPostStage(), TSInterpolate() 3641 @*/ 3642 PetscErrorCode TSStep(TS ts) 3643 { 3644 PetscErrorCode ierr; 3645 static PetscBool cite = PETSC_FALSE; 3646 PetscReal ptime; 3647 3648 PetscFunctionBegin; 3649 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3650 ierr = PetscCitationsRegister("@techreport{tspaper,\n" 3651 " title = {{PETSc/TS}: A Modern Scalable {DAE/ODE} Solver Library},\n" 3652 " author = {Shrirang Abhyankar and Jed Brown and Emil Constantinescu and Debojyoti Ghosh and Barry F. Smith},\n" 3653 " type = {Preprint},\n" 3654 " number = {ANL/MCS-P5061-0114},\n" 3655 " institution = {Argonne National Laboratory},\n" 3656 " year = {2014}\n}\n",&cite);CHKERRQ(ierr); 3657 3658 ierr = TSSetUp(ts);CHKERRQ(ierr); 3659 ierr = TSTrajectorySetUp(ts->trajectory,ts);CHKERRQ(ierr); 3660 3661 if (ts->max_time >= PETSC_MAX_REAL && ts->max_steps == PETSC_MAX_INT) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"You must call TSSetMaxTime() or TSSetMaxSteps(), or use -ts_max_time <time> or -ts_max_steps <steps>"); 3662 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()"); 3663 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"); 3664 3665 if (!ts->steps) ts->ptime_prev = ts->ptime; 3666 ptime = ts->ptime; ts->ptime_prev_rollback = ts->ptime_prev; 3667 ts->reason = TS_CONVERGED_ITERATING; 3668 if (!ts->ops->step) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSStep not implemented for type '%s'",((PetscObject)ts)->type_name); 3669 ierr = PetscLogEventBegin(TS_Step,ts,0,0,0);CHKERRQ(ierr); 3670 ierr = (*ts->ops->step)(ts);CHKERRQ(ierr); 3671 ierr = PetscLogEventEnd(TS_Step,ts,0,0,0);CHKERRQ(ierr); 3672 ts->ptime_prev = ptime; 3673 ts->steps++; 3674 ts->steprollback = PETSC_FALSE; 3675 ts->steprestart = PETSC_FALSE; 3676 3677 if (ts->reason < 0) { 3678 if (ts->errorifstepfailed) { 3679 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]); 3680 else SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s",TSConvergedReasons[ts->reason]); 3681 } 3682 } else if (!ts->reason) { 3683 if (ts->steps >= ts->max_steps) ts->reason = TS_CONVERGED_ITS; 3684 else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME; 3685 } 3686 PetscFunctionReturn(0); 3687 } 3688 3689 /*@ 3690 TSEvaluateWLTE - Evaluate the weighted local truncation error norm 3691 at the end of a time step with a given order of accuracy. 3692 3693 Collective on TS 3694 3695 Input Arguments: 3696 + ts - time stepping context 3697 . wnormtype - norm type, either NORM_2 or NORM_INFINITY 3698 - order - optional, desired order for the error evaluation or PETSC_DECIDE 3699 3700 Output Arguments: 3701 + order - optional, the actual order of the error evaluation 3702 - wlte - the weighted local truncation error norm 3703 3704 Level: advanced 3705 3706 Notes: 3707 If the timestepper cannot evaluate the error in a particular step 3708 (eg. in the first step or restart steps after event handling), 3709 this routine returns wlte=-1.0 . 3710 3711 .seealso: TSStep(), TSAdapt, TSErrorWeightedNorm() 3712 @*/ 3713 PetscErrorCode TSEvaluateWLTE(TS ts,NormType wnormtype,PetscInt *order,PetscReal *wlte) 3714 { 3715 PetscErrorCode ierr; 3716 3717 PetscFunctionBegin; 3718 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3719 PetscValidType(ts,1); 3720 PetscValidLogicalCollectiveEnum(ts,wnormtype,4); 3721 if (order) PetscValidIntPointer(order,3); 3722 if (order) PetscValidLogicalCollectiveInt(ts,*order,3); 3723 PetscValidRealPointer(wlte,4); 3724 if (wnormtype != NORM_2 && wnormtype != NORM_INFINITY) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]); 3725 if (!ts->ops->evaluatewlte) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSEvaluateWLTE not implemented for type '%s'",((PetscObject)ts)->type_name); 3726 ierr = (*ts->ops->evaluatewlte)(ts,wnormtype,order,wlte);CHKERRQ(ierr); 3727 PetscFunctionReturn(0); 3728 } 3729 3730 /*@ 3731 TSEvaluateStep - Evaluate the solution at the end of a time step with a given order of accuracy. 3732 3733 Collective on TS 3734 3735 Input Arguments: 3736 + ts - time stepping context 3737 . order - desired order of accuracy 3738 - done - whether the step was evaluated at this order (pass NULL to generate an error if not available) 3739 3740 Output Arguments: 3741 . U - state at the end of the current step 3742 3743 Level: advanced 3744 3745 Notes: 3746 This function cannot be called until all stages have been evaluated. 3747 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. 3748 3749 .seealso: TSStep(), TSAdapt 3750 @*/ 3751 PetscErrorCode TSEvaluateStep(TS ts,PetscInt order,Vec U,PetscBool *done) 3752 { 3753 PetscErrorCode ierr; 3754 3755 PetscFunctionBegin; 3756 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3757 PetscValidType(ts,1); 3758 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 3759 if (!ts->ops->evaluatestep) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSEvaluateStep not implemented for type '%s'",((PetscObject)ts)->type_name); 3760 ierr = (*ts->ops->evaluatestep)(ts,order,U,done);CHKERRQ(ierr); 3761 PetscFunctionReturn(0); 3762 } 3763 3764 /*@ 3765 TSSolve - Steps the requested number of timesteps. 3766 3767 Collective on TS 3768 3769 Input Parameter: 3770 + ts - the TS context obtained from TSCreate() 3771 - u - the solution vector (can be null if TSSetSolution() was used and TSSetExactFinalTime(ts,TS_EXACTFINALTIME_MATCHSTEP) was not used, 3772 otherwise must contain the initial conditions and will contain the solution at the final requested time 3773 3774 Level: beginner 3775 3776 Notes: 3777 The final time returned by this function may be different from the time of the internally 3778 held state accessible by TSGetSolution() and TSGetTime() because the method may have 3779 stepped over the final time. 3780 3781 .keywords: TS, timestep, solve 3782 3783 .seealso: TSCreate(), TSSetSolution(), TSStep(), TSGetTime(), TSGetSolveTime() 3784 @*/ 3785 PetscErrorCode TSSolve(TS ts,Vec u) 3786 { 3787 Vec solution; 3788 PetscErrorCode ierr; 3789 3790 PetscFunctionBegin; 3791 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3792 if (u) PetscValidHeaderSpecific(u,VEC_CLASSID,2); 3793 3794 if (ts->exact_final_time == TS_EXACTFINALTIME_INTERPOLATE && u) { /* Need ts->vec_sol to be distinct so it is not overwritten when we interpolate at the end */ 3795 if (!ts->vec_sol || u == ts->vec_sol) { 3796 ierr = VecDuplicate(u,&solution);CHKERRQ(ierr); 3797 ierr = TSSetSolution(ts,solution);CHKERRQ(ierr); 3798 ierr = VecDestroy(&solution);CHKERRQ(ierr); /* grant ownership */ 3799 } 3800 ierr = VecCopy(u,ts->vec_sol);CHKERRQ(ierr); 3801 if (ts->forward_solve) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Sensitivity analysis does not support the mode TS_EXACTFINALTIME_INTERPOLATE"); 3802 } else if (u) { 3803 ierr = TSSetSolution(ts,u);CHKERRQ(ierr); 3804 } 3805 ierr = TSSetUp(ts);CHKERRQ(ierr); 3806 ierr = TSTrajectorySetUp(ts->trajectory,ts);CHKERRQ(ierr); 3807 3808 if (ts->max_time >= PETSC_MAX_REAL && ts->max_steps == PETSC_MAX_INT) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"You must call TSSetMaxTime() or TSSetMaxSteps(), or use -ts_max_time <time> or -ts_max_steps <steps>"); 3809 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()"); 3810 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"); 3811 3812 if (ts->forward_solve) { 3813 ierr = TSForwardSetUp(ts);CHKERRQ(ierr); 3814 } 3815 3816 /* reset number of steps only when the step is not restarted. ARKIMEX 3817 restarts the step after an event. Resetting these counters in such case causes 3818 TSTrajectory to incorrectly save the output files 3819 */ 3820 /* reset time step and iteration counters */ 3821 if (!ts->steps) { 3822 ts->ksp_its = 0; 3823 ts->snes_its = 0; 3824 ts->num_snes_failures = 0; 3825 ts->reject = 0; 3826 ts->steprestart = PETSC_TRUE; 3827 ts->steprollback = PETSC_FALSE; 3828 } 3829 if (ts->exact_final_time == TS_EXACTFINALTIME_MATCHSTEP && ts->ptime + ts->time_step > ts->max_time) ts->time_step = ts->max_time - ts->ptime; 3830 ts->reason = TS_CONVERGED_ITERATING; 3831 3832 ierr = TSViewFromOptions(ts,NULL,"-ts_view_pre");CHKERRQ(ierr); 3833 3834 if (ts->ops->solve) { /* This private interface is transitional and should be removed when all implementations are updated. */ 3835 ierr = (*ts->ops->solve)(ts);CHKERRQ(ierr); 3836 if (u) {ierr = VecCopy(ts->vec_sol,u);CHKERRQ(ierr);} 3837 ts->solvetime = ts->ptime; 3838 solution = ts->vec_sol; 3839 } else { /* Step the requested number of timesteps. */ 3840 if (ts->steps >= ts->max_steps) ts->reason = TS_CONVERGED_ITS; 3841 else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME; 3842 3843 if (!ts->steps) { 3844 ierr = TSTrajectorySet(ts->trajectory,ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 3845 ierr = TSEventInitialize(ts->event,ts,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 3846 } 3847 3848 while (!ts->reason) { 3849 ierr = TSMonitor(ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 3850 if (!ts->steprollback) { 3851 ierr = TSPreStep(ts);CHKERRQ(ierr); 3852 } 3853 ierr = TSStep(ts);CHKERRQ(ierr); 3854 if (ts->testjacobian) { 3855 ierr = TSRHSJacobianTest(ts,NULL);CHKERRQ(ierr); 3856 } 3857 if (ts->testjacobiantranspose) { 3858 ierr = TSRHSJacobianTestTranspose(ts,NULL);CHKERRQ(ierr); 3859 } 3860 if (ts->vec_costintegral && ts->costintegralfwd) { /* Must evaluate the cost integral before event is handled. The cost integral value can also be rolled back. */ 3861 ierr = TSForwardCostIntegral(ts);CHKERRQ(ierr); 3862 } 3863 if (ts->forward_solve) { /* compute forward sensitivities before event handling because postevent() may change RHS and jump conditions may have to be applied */ 3864 ierr = TSForwardStep(ts);CHKERRQ(ierr); 3865 } 3866 ierr = TSPostEvaluate(ts);CHKERRQ(ierr); 3867 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. */ 3868 if (ts->steprollback) { 3869 ierr = TSPostEvaluate(ts);CHKERRQ(ierr); 3870 } 3871 if (!ts->steprollback) { 3872 ierr = TSTrajectorySet(ts->trajectory,ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 3873 ierr = TSPostStep(ts);CHKERRQ(ierr); 3874 } 3875 } 3876 ierr = TSMonitor(ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 3877 3878 if (ts->exact_final_time == TS_EXACTFINALTIME_INTERPOLATE && ts->ptime > ts->max_time) { 3879 ierr = TSInterpolate(ts,ts->max_time,u);CHKERRQ(ierr); 3880 ts->solvetime = ts->max_time; 3881 solution = u; 3882 ierr = TSMonitor(ts,-1,ts->solvetime,solution);CHKERRQ(ierr); 3883 } else { 3884 if (u) {ierr = VecCopy(ts->vec_sol,u);CHKERRQ(ierr);} 3885 ts->solvetime = ts->ptime; 3886 solution = ts->vec_sol; 3887 } 3888 } 3889 3890 ierr = TSViewFromOptions(ts,NULL,"-ts_view");CHKERRQ(ierr); 3891 ierr = VecViewFromOptions(solution,NULL,"-ts_view_solution");CHKERRQ(ierr); 3892 ierr = PetscObjectSAWsBlock((PetscObject)ts);CHKERRQ(ierr); 3893 if (ts->adjoint_solve) { 3894 ierr = TSAdjointSolve(ts);CHKERRQ(ierr); 3895 } 3896 PetscFunctionReturn(0); 3897 } 3898 3899 /*@C 3900 TSMonitor - Runs all user-provided monitor routines set using TSMonitorSet() 3901 3902 Collective on TS 3903 3904 Input Parameters: 3905 + ts - time stepping context obtained from TSCreate() 3906 . step - step number that has just completed 3907 . ptime - model time of the state 3908 - u - state at the current model time 3909 3910 Notes: 3911 TSMonitor() is typically used automatically within the time stepping implementations. 3912 Users would almost never call this routine directly. 3913 3914 A step of -1 indicates that the monitor is being called on a solution obtained by interpolating from computed solutions 3915 3916 Level: developer 3917 3918 .keywords: TS, timestep 3919 @*/ 3920 PetscErrorCode TSMonitor(TS ts,PetscInt step,PetscReal ptime,Vec u) 3921 { 3922 DM dm; 3923 PetscInt i,n = ts->numbermonitors; 3924 PetscErrorCode ierr; 3925 3926 PetscFunctionBegin; 3927 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3928 PetscValidHeaderSpecific(u,VEC_CLASSID,4); 3929 3930 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 3931 ierr = DMSetOutputSequenceNumber(dm,step,ptime);CHKERRQ(ierr); 3932 3933 ierr = VecLockReadPush(u);CHKERRQ(ierr); 3934 for (i=0; i<n; i++) { 3935 ierr = (*ts->monitor[i])(ts,step,ptime,u,ts->monitorcontext[i]);CHKERRQ(ierr); 3936 } 3937 ierr = VecLockReadPop(u);CHKERRQ(ierr); 3938 PetscFunctionReturn(0); 3939 } 3940 3941 /* ------------------------------------------------------------------------*/ 3942 /*@C 3943 TSMonitorLGCtxCreate - Creates a TSMonitorLGCtx context for use with 3944 TS to monitor the solution process graphically in various ways 3945 3946 Collective on TS 3947 3948 Input Parameters: 3949 + host - the X display to open, or null for the local machine 3950 . label - the title to put in the title bar 3951 . x, y - the screen coordinates of the upper left coordinate of the window 3952 . m, n - the screen width and height in pixels 3953 - howoften - if positive then determines the frequency of the plotting, if -1 then only at the final time 3954 3955 Output Parameter: 3956 . ctx - the context 3957 3958 Options Database Key: 3959 + -ts_monitor_lg_timestep - automatically sets line graph monitor 3960 + -ts_monitor_lg_timestep_log - automatically sets line graph monitor 3961 . -ts_monitor_lg_solution - monitor the solution (or certain values of the solution by calling TSMonitorLGSetDisplayVariables() or TSMonitorLGCtxSetDisplayVariables()) 3962 . -ts_monitor_lg_error - monitor the error 3963 . -ts_monitor_lg_ksp_iterations - monitor the number of KSP iterations needed for each timestep 3964 . -ts_monitor_lg_snes_iterations - monitor the number of SNES iterations needed for each timestep 3965 - -lg_use_markers <true,false> - mark the data points (at each time step) on the plot; default is true 3966 3967 Notes: 3968 Use TSMonitorLGCtxDestroy() to destroy. 3969 3970 One can provide a function that transforms the solution before plotting it with TSMonitorLGCtxSetTransform() or TSMonitorLGSetTransform() 3971 3972 Many of the functions that control the monitoring have two forms: TSMonitorLGSet/GetXXXX() and TSMonitorLGCtxSet/GetXXXX() the first take a TS object as the 3973 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 3974 as the first argument. 3975 3976 One can control the names displayed for each solution or error variable with TSMonitorLGCtxSetVariableNames() or TSMonitorLGSetVariableNames() 3977 3978 Level: intermediate 3979 3980 .keywords: TS, monitor, line graph, residual 3981 3982 .seealso: TSMonitorLGTimeStep(), TSMonitorSet(), TSMonitorLGSolution(), TSMonitorLGError(), TSMonitorDefault(), VecView(), 3983 TSMonitorLGCtxCreate(), TSMonitorLGCtxSetVariableNames(), TSMonitorLGCtxGetVariableNames(), 3984 TSMonitorLGSetVariableNames(), TSMonitorLGGetVariableNames(), TSMonitorLGSetDisplayVariables(), TSMonitorLGCtxSetDisplayVariables(), 3985 TSMonitorLGCtxSetTransform(), TSMonitorLGSetTransform(), TSMonitorLGError(), TSMonitorLGSNESIterations(), TSMonitorLGKSPIterations(), 3986 TSMonitorEnvelopeCtxCreate(), TSMonitorEnvelopeGetBounds(), TSMonitorEnvelopeCtxDestroy(), TSMonitorEnvelop() 3987 3988 @*/ 3989 PetscErrorCode TSMonitorLGCtxCreate(MPI_Comm comm,const char host[],const char label[],int x,int y,int m,int n,PetscInt howoften,TSMonitorLGCtx *ctx) 3990 { 3991 PetscDraw draw; 3992 PetscErrorCode ierr; 3993 3994 PetscFunctionBegin; 3995 ierr = PetscNew(ctx);CHKERRQ(ierr); 3996 ierr = PetscDrawCreate(comm,host,label,x,y,m,n,&draw);CHKERRQ(ierr); 3997 ierr = PetscDrawSetFromOptions(draw);CHKERRQ(ierr); 3998 ierr = PetscDrawLGCreate(draw,1,&(*ctx)->lg);CHKERRQ(ierr); 3999 ierr = PetscDrawLGSetFromOptions((*ctx)->lg);CHKERRQ(ierr); 4000 ierr = PetscDrawDestroy(&draw);CHKERRQ(ierr); 4001 (*ctx)->howoften = howoften; 4002 PetscFunctionReturn(0); 4003 } 4004 4005 PetscErrorCode TSMonitorLGTimeStep(TS ts,PetscInt step,PetscReal ptime,Vec v,void *monctx) 4006 { 4007 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 4008 PetscReal x = ptime,y; 4009 PetscErrorCode ierr; 4010 4011 PetscFunctionBegin; 4012 if (step < 0) PetscFunctionReturn(0); /* -1 indicates an interpolated solution */ 4013 if (!step) { 4014 PetscDrawAxis axis; 4015 const char *ylabel = ctx->semilogy ? "Log Time Step" : "Time Step"; 4016 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 4017 ierr = PetscDrawAxisSetLabels(axis,"Timestep as function of time","Time",ylabel);CHKERRQ(ierr); 4018 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 4019 } 4020 ierr = TSGetTimeStep(ts,&y);CHKERRQ(ierr); 4021 if (ctx->semilogy) y = PetscLog10Real(y); 4022 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 4023 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 4024 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 4025 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 4026 } 4027 PetscFunctionReturn(0); 4028 } 4029 4030 /*@C 4031 TSMonitorLGCtxDestroy - Destroys a line graph context that was created 4032 with TSMonitorLGCtxCreate(). 4033 4034 Collective on TSMonitorLGCtx 4035 4036 Input Parameter: 4037 . ctx - the monitor context 4038 4039 Level: intermediate 4040 4041 .keywords: TS, monitor, line graph, destroy 4042 4043 .seealso: TSMonitorLGCtxCreate(), TSMonitorSet(), TSMonitorLGTimeStep(); 4044 @*/ 4045 PetscErrorCode TSMonitorLGCtxDestroy(TSMonitorLGCtx *ctx) 4046 { 4047 PetscErrorCode ierr; 4048 4049 PetscFunctionBegin; 4050 if ((*ctx)->transformdestroy) { 4051 ierr = ((*ctx)->transformdestroy)((*ctx)->transformctx);CHKERRQ(ierr); 4052 } 4053 ierr = PetscDrawLGDestroy(&(*ctx)->lg);CHKERRQ(ierr); 4054 ierr = PetscStrArrayDestroy(&(*ctx)->names);CHKERRQ(ierr); 4055 ierr = PetscStrArrayDestroy(&(*ctx)->displaynames);CHKERRQ(ierr); 4056 ierr = PetscFree((*ctx)->displayvariables);CHKERRQ(ierr); 4057 ierr = PetscFree((*ctx)->displayvalues);CHKERRQ(ierr); 4058 ierr = PetscFree(*ctx);CHKERRQ(ierr); 4059 PetscFunctionReturn(0); 4060 } 4061 4062 /* 4063 4064 Creates a TS Monitor SPCtx for use with DM Swarm particle visualizations 4065 4066 */ 4067 PetscErrorCode TSMonitorSPCtxCreate(MPI_Comm comm,const char host[],const char label[],int x,int y,int m,int n,PetscInt howoften,TSMonitorSPCtx *ctx) 4068 { 4069 PetscDraw draw; 4070 PetscErrorCode ierr; 4071 4072 PetscFunctionBegin; 4073 ierr = PetscNew(ctx);CHKERRQ(ierr); 4074 ierr = PetscDrawCreate(comm,host,label,x,y,m,n,&draw);CHKERRQ(ierr); 4075 ierr = PetscDrawSetFromOptions(draw);CHKERRQ(ierr); 4076 ierr = PetscDrawSPCreate(draw,1,&(*ctx)->sp);CHKERRQ(ierr); 4077 ierr = PetscDrawDestroy(&draw);CHKERRQ(ierr); 4078 (*ctx)->howoften = howoften; 4079 PetscFunctionReturn(0); 4080 4081 } 4082 4083 /* 4084 Destroys a TSMonitorSPCtx that was created with TSMonitorSPCtxCreate 4085 */ 4086 PetscErrorCode TSMonitorSPCtxDestroy(TSMonitorSPCtx *ctx) 4087 { 4088 PetscErrorCode ierr; 4089 4090 PetscFunctionBegin; 4091 4092 ierr = PetscDrawSPDestroy(&(*ctx)->sp);CHKERRQ(ierr); 4093 ierr = PetscFree(*ctx);CHKERRQ(ierr); 4094 4095 PetscFunctionReturn(0); 4096 4097 } 4098 4099 /*@ 4100 TSGetTime - Gets the time of the most recently completed step. 4101 4102 Not Collective 4103 4104 Input Parameter: 4105 . ts - the TS context obtained from TSCreate() 4106 4107 Output Parameter: 4108 . t - the current time. This time may not corresponds to the final time set with TSSetMaxTime(), use TSGetSolveTime(). 4109 4110 Level: beginner 4111 4112 Note: 4113 When called during time step evaluation (e.g. during residual evaluation or via hooks set using TSSetPreStep(), 4114 TSSetPreStage(), TSSetPostStage(), or TSSetPostStep()), the time is the time at the start of the step being evaluated. 4115 4116 .seealso: TSGetSolveTime(), TSSetTime(), TSGetTimeStep() 4117 4118 .keywords: TS, get, time 4119 @*/ 4120 PetscErrorCode TSGetTime(TS ts,PetscReal *t) 4121 { 4122 PetscFunctionBegin; 4123 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4124 PetscValidRealPointer(t,2); 4125 *t = ts->ptime; 4126 PetscFunctionReturn(0); 4127 } 4128 4129 /*@ 4130 TSGetPrevTime - Gets the starting time of the previously completed step. 4131 4132 Not Collective 4133 4134 Input Parameter: 4135 . ts - the TS context obtained from TSCreate() 4136 4137 Output Parameter: 4138 . t - the previous time 4139 4140 Level: beginner 4141 4142 .seealso: TSGetTime(), TSGetSolveTime(), TSGetTimeStep() 4143 4144 .keywords: TS, get, time 4145 @*/ 4146 PetscErrorCode TSGetPrevTime(TS ts,PetscReal *t) 4147 { 4148 PetscFunctionBegin; 4149 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4150 PetscValidRealPointer(t,2); 4151 *t = ts->ptime_prev; 4152 PetscFunctionReturn(0); 4153 } 4154 4155 /*@ 4156 TSSetTime - Allows one to reset the time. 4157 4158 Logically Collective on TS 4159 4160 Input Parameters: 4161 + ts - the TS context obtained from TSCreate() 4162 - time - the time 4163 4164 Level: intermediate 4165 4166 .seealso: TSGetTime(), TSSetMaxSteps() 4167 4168 .keywords: TS, set, time 4169 @*/ 4170 PetscErrorCode TSSetTime(TS ts, PetscReal t) 4171 { 4172 PetscFunctionBegin; 4173 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4174 PetscValidLogicalCollectiveReal(ts,t,2); 4175 ts->ptime = t; 4176 PetscFunctionReturn(0); 4177 } 4178 4179 /*@C 4180 TSSetOptionsPrefix - Sets the prefix used for searching for all 4181 TS options in the database. 4182 4183 Logically Collective on TS 4184 4185 Input Parameter: 4186 + ts - The TS context 4187 - prefix - The prefix to prepend to all option names 4188 4189 Notes: 4190 A hyphen (-) must NOT be given at the beginning of the prefix name. 4191 The first character of all runtime options is AUTOMATICALLY the 4192 hyphen. 4193 4194 Level: advanced 4195 4196 .keywords: TS, set, options, prefix, database 4197 4198 .seealso: TSSetFromOptions() 4199 4200 @*/ 4201 PetscErrorCode TSSetOptionsPrefix(TS ts,const char prefix[]) 4202 { 4203 PetscErrorCode ierr; 4204 SNES snes; 4205 4206 PetscFunctionBegin; 4207 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4208 ierr = PetscObjectSetOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 4209 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4210 ierr = SNESSetOptionsPrefix(snes,prefix);CHKERRQ(ierr); 4211 PetscFunctionReturn(0); 4212 } 4213 4214 /*@C 4215 TSAppendOptionsPrefix - Appends to the prefix used for searching for all 4216 TS options in the database. 4217 4218 Logically Collective on TS 4219 4220 Input Parameter: 4221 + ts - The TS context 4222 - prefix - The prefix to prepend to all option names 4223 4224 Notes: 4225 A hyphen (-) must NOT be given at the beginning of the prefix name. 4226 The first character of all runtime options is AUTOMATICALLY the 4227 hyphen. 4228 4229 Level: advanced 4230 4231 .keywords: TS, append, options, prefix, database 4232 4233 .seealso: TSGetOptionsPrefix() 4234 4235 @*/ 4236 PetscErrorCode TSAppendOptionsPrefix(TS ts,const char prefix[]) 4237 { 4238 PetscErrorCode ierr; 4239 SNES snes; 4240 4241 PetscFunctionBegin; 4242 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4243 ierr = PetscObjectAppendOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 4244 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4245 ierr = SNESAppendOptionsPrefix(snes,prefix);CHKERRQ(ierr); 4246 PetscFunctionReturn(0); 4247 } 4248 4249 /*@C 4250 TSGetOptionsPrefix - Sets the prefix used for searching for all 4251 TS options in the database. 4252 4253 Not Collective 4254 4255 Input Parameter: 4256 . ts - The TS context 4257 4258 Output Parameter: 4259 . prefix - A pointer to the prefix string used 4260 4261 Notes: 4262 On the fortran side, the user should pass in a string 'prifix' of 4263 sufficient length to hold the prefix. 4264 4265 Level: intermediate 4266 4267 .keywords: TS, get, options, prefix, database 4268 4269 .seealso: TSAppendOptionsPrefix() 4270 @*/ 4271 PetscErrorCode TSGetOptionsPrefix(TS ts,const char *prefix[]) 4272 { 4273 PetscErrorCode ierr; 4274 4275 PetscFunctionBegin; 4276 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4277 PetscValidPointer(prefix,2); 4278 ierr = PetscObjectGetOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 4279 PetscFunctionReturn(0); 4280 } 4281 4282 /*@C 4283 TSGetRHSJacobian - Returns the Jacobian J at the present timestep. 4284 4285 Not Collective, but parallel objects are returned if TS is parallel 4286 4287 Input Parameter: 4288 . ts - The TS context obtained from TSCreate() 4289 4290 Output Parameters: 4291 + Amat - The (approximate) Jacobian J of G, where U_t = G(U,t) (or NULL) 4292 . Pmat - The matrix from which the preconditioner is constructed, usually the same as Amat (or NULL) 4293 . func - Function to compute the Jacobian of the RHS (or NULL) 4294 - ctx - User-defined context for Jacobian evaluation routine (or NULL) 4295 4296 Notes: 4297 You can pass in NULL for any return argument you do not need. 4298 4299 Level: intermediate 4300 4301 .seealso: TSGetTimeStep(), TSGetMatrices(), TSGetTime(), TSGetStepNumber() 4302 4303 .keywords: TS, timestep, get, matrix, Jacobian 4304 @*/ 4305 PetscErrorCode TSGetRHSJacobian(TS ts,Mat *Amat,Mat *Pmat,TSRHSJacobian *func,void **ctx) 4306 { 4307 PetscErrorCode ierr; 4308 DM dm; 4309 4310 PetscFunctionBegin; 4311 if (Amat || Pmat) { 4312 SNES snes; 4313 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4314 ierr = SNESSetUpMatrices(snes);CHKERRQ(ierr); 4315 ierr = SNESGetJacobian(snes,Amat,Pmat,NULL,NULL);CHKERRQ(ierr); 4316 } 4317 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 4318 ierr = DMTSGetRHSJacobian(dm,func,ctx);CHKERRQ(ierr); 4319 PetscFunctionReturn(0); 4320 } 4321 4322 /*@C 4323 TSGetIJacobian - Returns the implicit Jacobian at the present timestep. 4324 4325 Not Collective, but parallel objects are returned if TS is parallel 4326 4327 Input Parameter: 4328 . ts - The TS context obtained from TSCreate() 4329 4330 Output Parameters: 4331 + Amat - The (approximate) Jacobian of F(t,U,U_t) 4332 . Pmat - The matrix from which the preconditioner is constructed, often the same as Amat 4333 . f - The function to compute the matrices 4334 - ctx - User-defined context for Jacobian evaluation routine 4335 4336 Notes: 4337 You can pass in NULL for any return argument you do not need. 4338 4339 Level: advanced 4340 4341 .seealso: TSGetTimeStep(), TSGetRHSJacobian(), TSGetMatrices(), TSGetTime(), TSGetStepNumber() 4342 4343 .keywords: TS, timestep, get, matrix, Jacobian 4344 @*/ 4345 PetscErrorCode TSGetIJacobian(TS ts,Mat *Amat,Mat *Pmat,TSIJacobian *f,void **ctx) 4346 { 4347 PetscErrorCode ierr; 4348 DM dm; 4349 4350 PetscFunctionBegin; 4351 if (Amat || Pmat) { 4352 SNES snes; 4353 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4354 ierr = SNESSetUpMatrices(snes);CHKERRQ(ierr); 4355 ierr = SNESGetJacobian(snes,Amat,Pmat,NULL,NULL);CHKERRQ(ierr); 4356 } 4357 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 4358 ierr = DMTSGetIJacobian(dm,f,ctx);CHKERRQ(ierr); 4359 PetscFunctionReturn(0); 4360 } 4361 4362 /*@C 4363 TSMonitorDrawSolution - Monitors progress of the TS solvers by calling 4364 VecView() for the solution at each timestep 4365 4366 Collective on TS 4367 4368 Input Parameters: 4369 + ts - the TS context 4370 . step - current time-step 4371 . ptime - current time 4372 - dummy - either a viewer or NULL 4373 4374 Options Database: 4375 . -ts_monitor_draw_solution_initial - show initial solution as well as current solution 4376 4377 Notes: 4378 the initial solution and current solution are not display with a common axis scaling so generally the option -ts_monitor_draw_solution_initial 4379 will look bad 4380 4381 Level: intermediate 4382 4383 .keywords: TS, vector, monitor, view 4384 4385 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 4386 @*/ 4387 PetscErrorCode TSMonitorDrawSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 4388 { 4389 PetscErrorCode ierr; 4390 TSMonitorDrawCtx ictx = (TSMonitorDrawCtx)dummy; 4391 PetscDraw draw; 4392 4393 PetscFunctionBegin; 4394 if (!step && ictx->showinitial) { 4395 if (!ictx->initialsolution) { 4396 ierr = VecDuplicate(u,&ictx->initialsolution);CHKERRQ(ierr); 4397 } 4398 ierr = VecCopy(u,ictx->initialsolution);CHKERRQ(ierr); 4399 } 4400 if (!(((ictx->howoften > 0) && (!(step % ictx->howoften))) || ((ictx->howoften == -1) && ts->reason))) PetscFunctionReturn(0); 4401 4402 if (ictx->showinitial) { 4403 PetscReal pause; 4404 ierr = PetscViewerDrawGetPause(ictx->viewer,&pause);CHKERRQ(ierr); 4405 ierr = PetscViewerDrawSetPause(ictx->viewer,0.0);CHKERRQ(ierr); 4406 ierr = VecView(ictx->initialsolution,ictx->viewer);CHKERRQ(ierr); 4407 ierr = PetscViewerDrawSetPause(ictx->viewer,pause);CHKERRQ(ierr); 4408 ierr = PetscViewerDrawSetHold(ictx->viewer,PETSC_TRUE);CHKERRQ(ierr); 4409 } 4410 ierr = VecView(u,ictx->viewer);CHKERRQ(ierr); 4411 if (ictx->showtimestepandtime) { 4412 PetscReal xl,yl,xr,yr,h; 4413 char time[32]; 4414 4415 ierr = PetscViewerDrawGetDraw(ictx->viewer,0,&draw);CHKERRQ(ierr); 4416 ierr = PetscSNPrintf(time,32,"Timestep %d Time %g",(int)step,(double)ptime);CHKERRQ(ierr); 4417 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 4418 h = yl + .95*(yr - yl); 4419 ierr = PetscDrawStringCentered(draw,.5*(xl+xr),h,PETSC_DRAW_BLACK,time);CHKERRQ(ierr); 4420 ierr = PetscDrawFlush(draw);CHKERRQ(ierr); 4421 } 4422 4423 if (ictx->showinitial) { 4424 ierr = PetscViewerDrawSetHold(ictx->viewer,PETSC_FALSE);CHKERRQ(ierr); 4425 } 4426 PetscFunctionReturn(0); 4427 } 4428 4429 /*@C 4430 TSMonitorDrawSolutionPhase - Monitors progress of the TS solvers by plotting the solution as a phase diagram 4431 4432 Collective on TS 4433 4434 Input Parameters: 4435 + ts - the TS context 4436 . step - current time-step 4437 . ptime - current time 4438 - dummy - either a viewer or NULL 4439 4440 Level: intermediate 4441 4442 .keywords: TS, vector, monitor, view 4443 4444 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 4445 @*/ 4446 PetscErrorCode TSMonitorDrawSolutionPhase(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 4447 { 4448 PetscErrorCode ierr; 4449 TSMonitorDrawCtx ictx = (TSMonitorDrawCtx)dummy; 4450 PetscDraw draw; 4451 PetscDrawAxis axis; 4452 PetscInt n; 4453 PetscMPIInt size; 4454 PetscReal U0,U1,xl,yl,xr,yr,h; 4455 char time[32]; 4456 const PetscScalar *U; 4457 4458 PetscFunctionBegin; 4459 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)ts),&size);CHKERRQ(ierr); 4460 if (size != 1) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Only allowed for sequential runs"); 4461 ierr = VecGetSize(u,&n);CHKERRQ(ierr); 4462 if (n != 2) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Only for ODEs with two unknowns"); 4463 4464 ierr = PetscViewerDrawGetDraw(ictx->viewer,0,&draw);CHKERRQ(ierr); 4465 ierr = PetscViewerDrawGetDrawAxis(ictx->viewer,0,&axis);CHKERRQ(ierr); 4466 ierr = PetscDrawAxisGetLimits(axis,&xl,&xr,&yl,&yr);CHKERRQ(ierr); 4467 if (!step) { 4468 ierr = PetscDrawClear(draw);CHKERRQ(ierr); 4469 ierr = PetscDrawAxisDraw(axis);CHKERRQ(ierr); 4470 } 4471 4472 ierr = VecGetArrayRead(u,&U);CHKERRQ(ierr); 4473 U0 = PetscRealPart(U[0]); 4474 U1 = PetscRealPart(U[1]); 4475 ierr = VecRestoreArrayRead(u,&U);CHKERRQ(ierr); 4476 if ((U0 < xl) || (U1 < yl) || (U0 > xr) || (U1 > yr)) PetscFunctionReturn(0); 4477 4478 ierr = PetscDrawCollectiveBegin(draw);CHKERRQ(ierr); 4479 ierr = PetscDrawPoint(draw,U0,U1,PETSC_DRAW_BLACK);CHKERRQ(ierr); 4480 if (ictx->showtimestepandtime) { 4481 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 4482 ierr = PetscSNPrintf(time,32,"Timestep %d Time %g",(int)step,(double)ptime);CHKERRQ(ierr); 4483 h = yl + .95*(yr - yl); 4484 ierr = PetscDrawStringCentered(draw,.5*(xl+xr),h,PETSC_DRAW_BLACK,time);CHKERRQ(ierr); 4485 } 4486 ierr = PetscDrawCollectiveEnd(draw);CHKERRQ(ierr); 4487 ierr = PetscDrawFlush(draw);CHKERRQ(ierr); 4488 ierr = PetscDrawPause(draw);CHKERRQ(ierr); 4489 ierr = PetscDrawSave(draw);CHKERRQ(ierr); 4490 PetscFunctionReturn(0); 4491 } 4492 4493 /*@C 4494 TSMonitorDrawCtxDestroy - Destroys the monitor context for TSMonitorDrawSolution() 4495 4496 Collective on TS 4497 4498 Input Parameters: 4499 . ctx - the monitor context 4500 4501 Level: intermediate 4502 4503 .keywords: TS, vector, monitor, view 4504 4505 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorDrawSolution(), TSMonitorDrawError() 4506 @*/ 4507 PetscErrorCode TSMonitorDrawCtxDestroy(TSMonitorDrawCtx *ictx) 4508 { 4509 PetscErrorCode ierr; 4510 4511 PetscFunctionBegin; 4512 ierr = PetscViewerDestroy(&(*ictx)->viewer);CHKERRQ(ierr); 4513 ierr = VecDestroy(&(*ictx)->initialsolution);CHKERRQ(ierr); 4514 ierr = PetscFree(*ictx);CHKERRQ(ierr); 4515 PetscFunctionReturn(0); 4516 } 4517 4518 /*@C 4519 TSMonitorDrawCtxCreate - Creates the monitor context for TSMonitorDrawCtx 4520 4521 Collective on TS 4522 4523 Input Parameter: 4524 . ts - time-step context 4525 4526 Output Patameter: 4527 . ctx - the monitor context 4528 4529 Options Database: 4530 . -ts_monitor_draw_solution_initial - show initial solution as well as current solution 4531 4532 Level: intermediate 4533 4534 .keywords: TS, vector, monitor, view 4535 4536 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorDrawCtx() 4537 @*/ 4538 PetscErrorCode TSMonitorDrawCtxCreate(MPI_Comm comm,const char host[],const char label[],int x,int y,int m,int n,PetscInt howoften,TSMonitorDrawCtx *ctx) 4539 { 4540 PetscErrorCode ierr; 4541 4542 PetscFunctionBegin; 4543 ierr = PetscNew(ctx);CHKERRQ(ierr); 4544 ierr = PetscViewerDrawOpen(comm,host,label,x,y,m,n,&(*ctx)->viewer);CHKERRQ(ierr); 4545 ierr = PetscViewerSetFromOptions((*ctx)->viewer);CHKERRQ(ierr); 4546 4547 (*ctx)->howoften = howoften; 4548 (*ctx)->showinitial = PETSC_FALSE; 4549 ierr = PetscOptionsGetBool(NULL,NULL,"-ts_monitor_draw_solution_initial",&(*ctx)->showinitial,NULL);CHKERRQ(ierr); 4550 4551 (*ctx)->showtimestepandtime = PETSC_FALSE; 4552 ierr = PetscOptionsGetBool(NULL,NULL,"-ts_monitor_draw_solution_show_time",&(*ctx)->showtimestepandtime,NULL);CHKERRQ(ierr); 4553 PetscFunctionReturn(0); 4554 } 4555 4556 /*@C 4557 TSMonitorDrawSolutionFunction - Monitors progress of the TS solvers by calling 4558 VecView() for the solution provided by TSSetSolutionFunction() at each timestep 4559 4560 Collective on TS 4561 4562 Input Parameters: 4563 + ts - the TS context 4564 . step - current time-step 4565 . ptime - current time 4566 - dummy - either a viewer or NULL 4567 4568 Options Database: 4569 . -ts_monitor_draw_solution_function - Monitor error graphically, requires user to have provided TSSetSolutionFunction() 4570 4571 Level: intermediate 4572 4573 .keywords: TS, vector, monitor, view 4574 4575 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSSetSolutionFunction() 4576 @*/ 4577 PetscErrorCode TSMonitorDrawSolutionFunction(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 4578 { 4579 PetscErrorCode ierr; 4580 TSMonitorDrawCtx ctx = (TSMonitorDrawCtx)dummy; 4581 PetscViewer viewer = ctx->viewer; 4582 Vec work; 4583 4584 PetscFunctionBegin; 4585 if (!(((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason))) PetscFunctionReturn(0); 4586 ierr = VecDuplicate(u,&work);CHKERRQ(ierr); 4587 ierr = TSComputeSolutionFunction(ts,ptime,work);CHKERRQ(ierr); 4588 ierr = VecView(work,viewer);CHKERRQ(ierr); 4589 ierr = VecDestroy(&work);CHKERRQ(ierr); 4590 PetscFunctionReturn(0); 4591 } 4592 4593 /*@C 4594 TSMonitorDrawError - Monitors progress of the TS solvers by calling 4595 VecView() for the error at each timestep 4596 4597 Collective on TS 4598 4599 Input Parameters: 4600 + ts - the TS context 4601 . step - current time-step 4602 . ptime - current time 4603 - dummy - either a viewer or NULL 4604 4605 Options Database: 4606 . -ts_monitor_draw_error - Monitor error graphically, requires user to have provided TSSetSolutionFunction() 4607 4608 Level: intermediate 4609 4610 .keywords: TS, vector, monitor, view 4611 4612 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSSetSolutionFunction() 4613 @*/ 4614 PetscErrorCode TSMonitorDrawError(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 4615 { 4616 PetscErrorCode ierr; 4617 TSMonitorDrawCtx ctx = (TSMonitorDrawCtx)dummy; 4618 PetscViewer viewer = ctx->viewer; 4619 Vec work; 4620 4621 PetscFunctionBegin; 4622 if (!(((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason))) PetscFunctionReturn(0); 4623 ierr = VecDuplicate(u,&work);CHKERRQ(ierr); 4624 ierr = TSComputeSolutionFunction(ts,ptime,work);CHKERRQ(ierr); 4625 ierr = VecAXPY(work,-1.0,u);CHKERRQ(ierr); 4626 ierr = VecView(work,viewer);CHKERRQ(ierr); 4627 ierr = VecDestroy(&work);CHKERRQ(ierr); 4628 PetscFunctionReturn(0); 4629 } 4630 4631 #include <petsc/private/dmimpl.h> 4632 /*@ 4633 TSSetDM - Sets the DM that may be used by some nonlinear solvers or preconditioners under the TS 4634 4635 Logically Collective on TS and DM 4636 4637 Input Parameters: 4638 + ts - the ODE integrator object 4639 - dm - the dm, cannot be NULL 4640 4641 Notes: 4642 A DM can only be used for solving one problem at a time because information about the problem is stored on the DM, 4643 even when not using interfaces like DMTSSetIFunction(). Use DMClone() to get a distinct DM when solving 4644 different problems using the same function space. 4645 4646 Level: intermediate 4647 4648 .seealso: TSGetDM(), SNESSetDM(), SNESGetDM() 4649 @*/ 4650 PetscErrorCode TSSetDM(TS ts,DM dm) 4651 { 4652 PetscErrorCode ierr; 4653 SNES snes; 4654 DMTS tsdm; 4655 4656 PetscFunctionBegin; 4657 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4658 PetscValidHeaderSpecific(dm,DM_CLASSID,2); 4659 ierr = PetscObjectReference((PetscObject)dm);CHKERRQ(ierr); 4660 if (ts->dm) { /* Move the DMTS context over to the new DM unless the new DM already has one */ 4661 if (ts->dm->dmts && !dm->dmts) { 4662 ierr = DMCopyDMTS(ts->dm,dm);CHKERRQ(ierr); 4663 ierr = DMGetDMTS(ts->dm,&tsdm);CHKERRQ(ierr); 4664 if (tsdm->originaldm == ts->dm) { /* Grant write privileges to the replacement DM */ 4665 tsdm->originaldm = dm; 4666 } 4667 } 4668 ierr = DMDestroy(&ts->dm);CHKERRQ(ierr); 4669 } 4670 ts->dm = dm; 4671 4672 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4673 ierr = SNESSetDM(snes,dm);CHKERRQ(ierr); 4674 PetscFunctionReturn(0); 4675 } 4676 4677 /*@ 4678 TSGetDM - Gets the DM that may be used by some preconditioners 4679 4680 Not Collective 4681 4682 Input Parameter: 4683 . ts - the preconditioner context 4684 4685 Output Parameter: 4686 . dm - the dm 4687 4688 Level: intermediate 4689 4690 .seealso: TSSetDM(), SNESSetDM(), SNESGetDM() 4691 @*/ 4692 PetscErrorCode TSGetDM(TS ts,DM *dm) 4693 { 4694 PetscErrorCode ierr; 4695 4696 PetscFunctionBegin; 4697 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4698 if (!ts->dm) { 4699 ierr = DMShellCreate(PetscObjectComm((PetscObject)ts),&ts->dm);CHKERRQ(ierr); 4700 if (ts->snes) {ierr = SNESSetDM(ts->snes,ts->dm);CHKERRQ(ierr);} 4701 } 4702 *dm = ts->dm; 4703 PetscFunctionReturn(0); 4704 } 4705 4706 /*@ 4707 SNESTSFormFunction - Function to evaluate nonlinear residual 4708 4709 Logically Collective on SNES 4710 4711 Input Parameter: 4712 + snes - nonlinear solver 4713 . U - the current state at which to evaluate the residual 4714 - ctx - user context, must be a TS 4715 4716 Output Parameter: 4717 . F - the nonlinear residual 4718 4719 Notes: 4720 This function is not normally called by users and is automatically registered with the SNES used by TS. 4721 It is most frequently passed to MatFDColoringSetFunction(). 4722 4723 Level: advanced 4724 4725 .seealso: SNESSetFunction(), MatFDColoringSetFunction() 4726 @*/ 4727 PetscErrorCode SNESTSFormFunction(SNES snes,Vec U,Vec F,void *ctx) 4728 { 4729 TS ts = (TS)ctx; 4730 PetscErrorCode ierr; 4731 4732 PetscFunctionBegin; 4733 PetscValidHeaderSpecific(snes,SNES_CLASSID,1); 4734 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 4735 PetscValidHeaderSpecific(F,VEC_CLASSID,3); 4736 PetscValidHeaderSpecific(ts,TS_CLASSID,4); 4737 ierr = (ts->ops->snesfunction)(snes,U,F,ts);CHKERRQ(ierr); 4738 PetscFunctionReturn(0); 4739 } 4740 4741 /*@ 4742 SNESTSFormJacobian - Function to evaluate the Jacobian 4743 4744 Collective on SNES 4745 4746 Input Parameter: 4747 + snes - nonlinear solver 4748 . U - the current state at which to evaluate the residual 4749 - ctx - user context, must be a TS 4750 4751 Output Parameter: 4752 + A - the Jacobian 4753 . B - the preconditioning matrix (may be the same as A) 4754 - flag - indicates any structure change in the matrix 4755 4756 Notes: 4757 This function is not normally called by users and is automatically registered with the SNES used by TS. 4758 4759 Level: developer 4760 4761 .seealso: SNESSetJacobian() 4762 @*/ 4763 PetscErrorCode SNESTSFormJacobian(SNES snes,Vec U,Mat A,Mat B,void *ctx) 4764 { 4765 TS ts = (TS)ctx; 4766 PetscErrorCode ierr; 4767 4768 PetscFunctionBegin; 4769 PetscValidHeaderSpecific(snes,SNES_CLASSID,1); 4770 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 4771 PetscValidPointer(A,3); 4772 PetscValidHeaderSpecific(A,MAT_CLASSID,3); 4773 PetscValidPointer(B,4); 4774 PetscValidHeaderSpecific(B,MAT_CLASSID,4); 4775 PetscValidHeaderSpecific(ts,TS_CLASSID,6); 4776 ierr = (ts->ops->snesjacobian)(snes,U,A,B,ts);CHKERRQ(ierr); 4777 PetscFunctionReturn(0); 4778 } 4779 4780 /*@C 4781 TSComputeRHSFunctionLinear - Evaluate the right hand side via the user-provided Jacobian, for linear problems Udot = A U only 4782 4783 Collective on TS 4784 4785 Input Arguments: 4786 + ts - time stepping context 4787 . t - time at which to evaluate 4788 . U - state at which to evaluate 4789 - ctx - context 4790 4791 Output Arguments: 4792 . F - right hand side 4793 4794 Level: intermediate 4795 4796 Notes: 4797 This function is intended to be passed to TSSetRHSFunction() to evaluate the right hand side for linear problems. 4798 The matrix (and optionally the evaluation context) should be passed to TSSetRHSJacobian(). 4799 4800 .seealso: TSSetRHSFunction(), TSSetRHSJacobian(), TSComputeRHSJacobianConstant() 4801 @*/ 4802 PetscErrorCode TSComputeRHSFunctionLinear(TS ts,PetscReal t,Vec U,Vec F,void *ctx) 4803 { 4804 PetscErrorCode ierr; 4805 Mat Arhs,Brhs; 4806 4807 PetscFunctionBegin; 4808 ierr = TSGetRHSMats_Private(ts,&Arhs,&Brhs);CHKERRQ(ierr); 4809 ierr = TSComputeRHSJacobian(ts,t,U,Arhs,Brhs);CHKERRQ(ierr); 4810 ierr = MatMult(Arhs,U,F);CHKERRQ(ierr); 4811 PetscFunctionReturn(0); 4812 } 4813 4814 /*@C 4815 TSComputeRHSJacobianConstant - Reuses a Jacobian that is time-independent. 4816 4817 Collective on TS 4818 4819 Input Arguments: 4820 + ts - time stepping context 4821 . t - time at which to evaluate 4822 . U - state at which to evaluate 4823 - ctx - context 4824 4825 Output Arguments: 4826 + A - pointer to operator 4827 . B - pointer to preconditioning matrix 4828 - flg - matrix structure flag 4829 4830 Level: intermediate 4831 4832 Notes: 4833 This function is intended to be passed to TSSetRHSJacobian() to evaluate the Jacobian for linear time-independent problems. 4834 4835 .seealso: TSSetRHSFunction(), TSSetRHSJacobian(), TSComputeRHSFunctionLinear() 4836 @*/ 4837 PetscErrorCode TSComputeRHSJacobianConstant(TS ts,PetscReal t,Vec U,Mat A,Mat B,void *ctx) 4838 { 4839 PetscFunctionBegin; 4840 PetscFunctionReturn(0); 4841 } 4842 4843 /*@C 4844 TSComputeIFunctionLinear - Evaluate the left hand side via the user-provided Jacobian, for linear problems only 4845 4846 Collective on TS 4847 4848 Input Arguments: 4849 + ts - time stepping context 4850 . t - time at which to evaluate 4851 . U - state at which to evaluate 4852 . Udot - time derivative of state vector 4853 - ctx - context 4854 4855 Output Arguments: 4856 . F - left hand side 4857 4858 Level: intermediate 4859 4860 Notes: 4861 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 4862 user is required to write their own TSComputeIFunction. 4863 This function is intended to be passed to TSSetIFunction() to evaluate the left hand side for linear problems. 4864 The matrix (and optionally the evaluation context) should be passed to TSSetIJacobian(). 4865 4866 Note that using this function is NOT equivalent to using TSComputeRHSFunctionLinear() since that solves Udot = A U 4867 4868 .seealso: TSSetIFunction(), TSSetIJacobian(), TSComputeIJacobianConstant(), TSComputeRHSFunctionLinear() 4869 @*/ 4870 PetscErrorCode TSComputeIFunctionLinear(TS ts,PetscReal t,Vec U,Vec Udot,Vec F,void *ctx) 4871 { 4872 PetscErrorCode ierr; 4873 Mat A,B; 4874 4875 PetscFunctionBegin; 4876 ierr = TSGetIJacobian(ts,&A,&B,NULL,NULL);CHKERRQ(ierr); 4877 ierr = TSComputeIJacobian(ts,t,U,Udot,1.0,A,B,PETSC_TRUE);CHKERRQ(ierr); 4878 ierr = MatMult(A,Udot,F);CHKERRQ(ierr); 4879 PetscFunctionReturn(0); 4880 } 4881 4882 /*@C 4883 TSComputeIJacobianConstant - Reuses a time-independent for a semi-implicit DAE or ODE 4884 4885 Collective on TS 4886 4887 Input Arguments: 4888 + ts - time stepping context 4889 . t - time at which to evaluate 4890 . U - state at which to evaluate 4891 . Udot - time derivative of state vector 4892 . shift - shift to apply 4893 - ctx - context 4894 4895 Output Arguments: 4896 + A - pointer to operator 4897 . B - pointer to preconditioning matrix 4898 - flg - matrix structure flag 4899 4900 Level: advanced 4901 4902 Notes: 4903 This function is intended to be passed to TSSetIJacobian() to evaluate the Jacobian for linear time-independent problems. 4904 4905 It is only appropriate for problems of the form 4906 4907 $ M Udot = F(U,t) 4908 4909 where M is constant and F is non-stiff. The user must pass M to TSSetIJacobian(). The current implementation only 4910 works with IMEX time integration methods such as TSROSW and TSARKIMEX, since there is no support for de-constructing 4911 an implicit operator of the form 4912 4913 $ shift*M + J 4914 4915 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 4916 a copy of M or reassemble it when requested. 4917 4918 .seealso: TSSetIFunction(), TSSetIJacobian(), TSComputeIFunctionLinear() 4919 @*/ 4920 PetscErrorCode TSComputeIJacobianConstant(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat A,Mat B,void *ctx) 4921 { 4922 PetscErrorCode ierr; 4923 4924 PetscFunctionBegin; 4925 ierr = MatScale(A, shift / ts->ijacobian.shift);CHKERRQ(ierr); 4926 ts->ijacobian.shift = shift; 4927 PetscFunctionReturn(0); 4928 } 4929 4930 /*@ 4931 TSGetEquationType - Gets the type of the equation that TS is solving. 4932 4933 Not Collective 4934 4935 Input Parameter: 4936 . ts - the TS context 4937 4938 Output Parameter: 4939 . equation_type - see TSEquationType 4940 4941 Level: beginner 4942 4943 .keywords: TS, equation type 4944 4945 .seealso: TSSetEquationType(), TSEquationType 4946 @*/ 4947 PetscErrorCode TSGetEquationType(TS ts,TSEquationType *equation_type) 4948 { 4949 PetscFunctionBegin; 4950 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4951 PetscValidPointer(equation_type,2); 4952 *equation_type = ts->equation_type; 4953 PetscFunctionReturn(0); 4954 } 4955 4956 /*@ 4957 TSSetEquationType - Sets the type of the equation that TS is solving. 4958 4959 Not Collective 4960 4961 Input Parameter: 4962 + ts - the TS context 4963 - equation_type - see TSEquationType 4964 4965 Level: advanced 4966 4967 .keywords: TS, equation type 4968 4969 .seealso: TSGetEquationType(), TSEquationType 4970 @*/ 4971 PetscErrorCode TSSetEquationType(TS ts,TSEquationType equation_type) 4972 { 4973 PetscFunctionBegin; 4974 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4975 ts->equation_type = equation_type; 4976 PetscFunctionReturn(0); 4977 } 4978 4979 /*@ 4980 TSGetConvergedReason - Gets the reason the TS iteration was stopped. 4981 4982 Not Collective 4983 4984 Input Parameter: 4985 . ts - the TS context 4986 4987 Output Parameter: 4988 . reason - negative value indicates diverged, positive value converged, see TSConvergedReason or the 4989 manual pages for the individual convergence tests for complete lists 4990 4991 Level: beginner 4992 4993 Notes: 4994 Can only be called after the call to TSSolve() is complete. 4995 4996 .keywords: TS, nonlinear, set, convergence, test 4997 4998 .seealso: TSSetConvergenceTest(), TSConvergedReason 4999 @*/ 5000 PetscErrorCode TSGetConvergedReason(TS ts,TSConvergedReason *reason) 5001 { 5002 PetscFunctionBegin; 5003 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5004 PetscValidPointer(reason,2); 5005 *reason = ts->reason; 5006 PetscFunctionReturn(0); 5007 } 5008 5009 /*@ 5010 TSSetConvergedReason - Sets the reason for handling the convergence of TSSolve. 5011 5012 Not Collective 5013 5014 Input Parameter: 5015 + ts - the TS context 5016 . reason - negative value indicates diverged, positive value converged, see TSConvergedReason or the 5017 manual pages for the individual convergence tests for complete lists 5018 5019 Level: advanced 5020 5021 Notes: 5022 Can only be called during TSSolve() is active. 5023 5024 .keywords: TS, nonlinear, set, convergence, test 5025 5026 .seealso: TSConvergedReason 5027 @*/ 5028 PetscErrorCode TSSetConvergedReason(TS ts,TSConvergedReason reason) 5029 { 5030 PetscFunctionBegin; 5031 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5032 ts->reason = reason; 5033 PetscFunctionReturn(0); 5034 } 5035 5036 /*@ 5037 TSGetSolveTime - Gets the time after a call to TSSolve() 5038 5039 Not Collective 5040 5041 Input Parameter: 5042 . ts - the TS context 5043 5044 Output Parameter: 5045 . ftime - the final time. This time corresponds to the final time set with TSSetMaxTime() 5046 5047 Level: beginner 5048 5049 Notes: 5050 Can only be called after the call to TSSolve() is complete. 5051 5052 .keywords: TS, nonlinear, set, convergence, test 5053 5054 .seealso: TSSetConvergenceTest(), TSConvergedReason 5055 @*/ 5056 PetscErrorCode TSGetSolveTime(TS ts,PetscReal *ftime) 5057 { 5058 PetscFunctionBegin; 5059 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5060 PetscValidPointer(ftime,2); 5061 *ftime = ts->solvetime; 5062 PetscFunctionReturn(0); 5063 } 5064 5065 /*@ 5066 TSGetSNESIterations - Gets the total number of nonlinear iterations 5067 used by the time integrator. 5068 5069 Not Collective 5070 5071 Input Parameter: 5072 . ts - TS context 5073 5074 Output Parameter: 5075 . nits - number of nonlinear iterations 5076 5077 Notes: 5078 This counter is reset to zero for each successive call to TSSolve(). 5079 5080 Level: intermediate 5081 5082 .keywords: TS, get, number, nonlinear, iterations 5083 5084 .seealso: TSGetKSPIterations() 5085 @*/ 5086 PetscErrorCode TSGetSNESIterations(TS ts,PetscInt *nits) 5087 { 5088 PetscFunctionBegin; 5089 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5090 PetscValidIntPointer(nits,2); 5091 *nits = ts->snes_its; 5092 PetscFunctionReturn(0); 5093 } 5094 5095 /*@ 5096 TSGetKSPIterations - Gets the total number of linear iterations 5097 used by the time integrator. 5098 5099 Not Collective 5100 5101 Input Parameter: 5102 . ts - TS context 5103 5104 Output Parameter: 5105 . lits - number of linear iterations 5106 5107 Notes: 5108 This counter is reset to zero for each successive call to TSSolve(). 5109 5110 Level: intermediate 5111 5112 .keywords: TS, get, number, linear, iterations 5113 5114 .seealso: TSGetSNESIterations(), SNESGetKSPIterations() 5115 @*/ 5116 PetscErrorCode TSGetKSPIterations(TS ts,PetscInt *lits) 5117 { 5118 PetscFunctionBegin; 5119 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5120 PetscValidIntPointer(lits,2); 5121 *lits = ts->ksp_its; 5122 PetscFunctionReturn(0); 5123 } 5124 5125 /*@ 5126 TSGetStepRejections - Gets the total number of rejected steps. 5127 5128 Not Collective 5129 5130 Input Parameter: 5131 . ts - TS context 5132 5133 Output Parameter: 5134 . rejects - number of steps rejected 5135 5136 Notes: 5137 This counter is reset to zero for each successive call to TSSolve(). 5138 5139 Level: intermediate 5140 5141 .keywords: TS, get, number 5142 5143 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetSNESFailures(), TSSetMaxSNESFailures(), TSSetErrorIfStepFails() 5144 @*/ 5145 PetscErrorCode TSGetStepRejections(TS ts,PetscInt *rejects) 5146 { 5147 PetscFunctionBegin; 5148 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5149 PetscValidIntPointer(rejects,2); 5150 *rejects = ts->reject; 5151 PetscFunctionReturn(0); 5152 } 5153 5154 /*@ 5155 TSGetSNESFailures - Gets the total number of failed SNES solves 5156 5157 Not Collective 5158 5159 Input Parameter: 5160 . ts - TS context 5161 5162 Output Parameter: 5163 . fails - number of failed nonlinear solves 5164 5165 Notes: 5166 This counter is reset to zero for each successive call to TSSolve(). 5167 5168 Level: intermediate 5169 5170 .keywords: TS, get, number 5171 5172 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSSetMaxSNESFailures() 5173 @*/ 5174 PetscErrorCode TSGetSNESFailures(TS ts,PetscInt *fails) 5175 { 5176 PetscFunctionBegin; 5177 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5178 PetscValidIntPointer(fails,2); 5179 *fails = ts->num_snes_failures; 5180 PetscFunctionReturn(0); 5181 } 5182 5183 /*@ 5184 TSSetMaxStepRejections - Sets the maximum number of step rejections before a step fails 5185 5186 Not Collective 5187 5188 Input Parameter: 5189 + ts - TS context 5190 - rejects - maximum number of rejected steps, pass -1 for unlimited 5191 5192 Notes: 5193 The counter is reset to zero for each step 5194 5195 Options Database Key: 5196 . -ts_max_reject - Maximum number of step rejections before a step fails 5197 5198 Level: intermediate 5199 5200 .keywords: TS, set, maximum, number 5201 5202 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxSNESFailures(), TSGetStepRejections(), TSGetSNESFailures(), TSSetErrorIfStepFails(), TSGetConvergedReason() 5203 @*/ 5204 PetscErrorCode TSSetMaxStepRejections(TS ts,PetscInt rejects) 5205 { 5206 PetscFunctionBegin; 5207 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5208 ts->max_reject = rejects; 5209 PetscFunctionReturn(0); 5210 } 5211 5212 /*@ 5213 TSSetMaxSNESFailures - Sets the maximum number of failed SNES solves 5214 5215 Not Collective 5216 5217 Input Parameter: 5218 + ts - TS context 5219 - fails - maximum number of failed nonlinear solves, pass -1 for unlimited 5220 5221 Notes: 5222 The counter is reset to zero for each successive call to TSSolve(). 5223 5224 Options Database Key: 5225 . -ts_max_snes_failures - Maximum number of nonlinear solve failures 5226 5227 Level: intermediate 5228 5229 .keywords: TS, set, maximum, number 5230 5231 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSGetSNESFailures(), SNESGetConvergedReason(), TSGetConvergedReason() 5232 @*/ 5233 PetscErrorCode TSSetMaxSNESFailures(TS ts,PetscInt fails) 5234 { 5235 PetscFunctionBegin; 5236 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5237 ts->max_snes_failures = fails; 5238 PetscFunctionReturn(0); 5239 } 5240 5241 /*@ 5242 TSSetErrorIfStepFails - Error if no step succeeds 5243 5244 Not Collective 5245 5246 Input Parameter: 5247 + ts - TS context 5248 - err - PETSC_TRUE to error if no step succeeds, PETSC_FALSE to return without failure 5249 5250 Options Database Key: 5251 . -ts_error_if_step_fails - Error if no step succeeds 5252 5253 Level: intermediate 5254 5255 .keywords: TS, set, error 5256 5257 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSGetSNESFailures(), TSSetErrorIfStepFails(), TSGetConvergedReason() 5258 @*/ 5259 PetscErrorCode TSSetErrorIfStepFails(TS ts,PetscBool err) 5260 { 5261 PetscFunctionBegin; 5262 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5263 ts->errorifstepfailed = err; 5264 PetscFunctionReturn(0); 5265 } 5266 5267 /*@C 5268 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 5269 5270 Collective on TS 5271 5272 Input Parameters: 5273 + ts - the TS context 5274 . step - current time-step 5275 . ptime - current time 5276 . u - current state 5277 - vf - viewer and its format 5278 5279 Level: intermediate 5280 5281 .keywords: TS, vector, monitor, view 5282 5283 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 5284 @*/ 5285 PetscErrorCode TSMonitorSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,PetscViewerAndFormat *vf) 5286 { 5287 PetscErrorCode ierr; 5288 5289 PetscFunctionBegin; 5290 ierr = PetscViewerPushFormat(vf->viewer,vf->format);CHKERRQ(ierr); 5291 ierr = VecView(u,vf->viewer);CHKERRQ(ierr); 5292 ierr = PetscViewerPopFormat(vf->viewer);CHKERRQ(ierr); 5293 PetscFunctionReturn(0); 5294 } 5295 5296 /*@C 5297 TSMonitorSolutionVTK - Monitors progress of the TS solvers by VecView() for the solution at each timestep. 5298 5299 Collective on TS 5300 5301 Input Parameters: 5302 + ts - the TS context 5303 . step - current time-step 5304 . ptime - current time 5305 . u - current state 5306 - filenametemplate - string containing a format specifier for the integer time step (e.g. %03D) 5307 5308 Level: intermediate 5309 5310 Notes: 5311 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. 5312 These are named according to the file name template. 5313 5314 This function is normally passed as an argument to TSMonitorSet() along with TSMonitorSolutionVTKDestroy(). 5315 5316 .keywords: TS, vector, monitor, view 5317 5318 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 5319 @*/ 5320 PetscErrorCode TSMonitorSolutionVTK(TS ts,PetscInt step,PetscReal ptime,Vec u,void *filenametemplate) 5321 { 5322 PetscErrorCode ierr; 5323 char filename[PETSC_MAX_PATH_LEN]; 5324 PetscViewer viewer; 5325 5326 PetscFunctionBegin; 5327 if (step < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */ 5328 ierr = PetscSNPrintf(filename,sizeof(filename),(const char*)filenametemplate,step);CHKERRQ(ierr); 5329 ierr = PetscViewerVTKOpen(PetscObjectComm((PetscObject)ts),filename,FILE_MODE_WRITE,&viewer);CHKERRQ(ierr); 5330 ierr = VecView(u,viewer);CHKERRQ(ierr); 5331 ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr); 5332 PetscFunctionReturn(0); 5333 } 5334 5335 /*@C 5336 TSMonitorSolutionVTKDestroy - Destroy context for monitoring 5337 5338 Collective on TS 5339 5340 Input Parameters: 5341 . filenametemplate - string containing a format specifier for the integer time step (e.g. %03D) 5342 5343 Level: intermediate 5344 5345 Note: 5346 This function is normally passed to TSMonitorSet() along with TSMonitorSolutionVTK(). 5347 5348 .keywords: TS, vector, monitor, view 5349 5350 .seealso: TSMonitorSet(), TSMonitorSolutionVTK() 5351 @*/ 5352 PetscErrorCode TSMonitorSolutionVTKDestroy(void *filenametemplate) 5353 { 5354 PetscErrorCode ierr; 5355 5356 PetscFunctionBegin; 5357 ierr = PetscFree(*(char**)filenametemplate);CHKERRQ(ierr); 5358 PetscFunctionReturn(0); 5359 } 5360 5361 /*@ 5362 TSGetAdapt - Get the adaptive controller context for the current method 5363 5364 Collective on TS if controller has not been created yet 5365 5366 Input Arguments: 5367 . ts - time stepping context 5368 5369 Output Arguments: 5370 . adapt - adaptive controller 5371 5372 Level: intermediate 5373 5374 .seealso: TSAdapt, TSAdaptSetType(), TSAdaptChoose() 5375 @*/ 5376 PetscErrorCode TSGetAdapt(TS ts,TSAdapt *adapt) 5377 { 5378 PetscErrorCode ierr; 5379 5380 PetscFunctionBegin; 5381 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5382 PetscValidPointer(adapt,2); 5383 if (!ts->adapt) { 5384 ierr = TSAdaptCreate(PetscObjectComm((PetscObject)ts),&ts->adapt);CHKERRQ(ierr); 5385 ierr = PetscLogObjectParent((PetscObject)ts,(PetscObject)ts->adapt);CHKERRQ(ierr); 5386 ierr = PetscObjectIncrementTabLevel((PetscObject)ts->adapt,(PetscObject)ts,1);CHKERRQ(ierr); 5387 } 5388 *adapt = ts->adapt; 5389 PetscFunctionReturn(0); 5390 } 5391 5392 /*@ 5393 TSSetTolerances - Set tolerances for local truncation error when using adaptive controller 5394 5395 Logically Collective 5396 5397 Input Arguments: 5398 + ts - time integration context 5399 . atol - scalar absolute tolerances, PETSC_DECIDE to leave current value 5400 . vatol - vector of absolute tolerances or NULL, used in preference to atol if present 5401 . rtol - scalar relative tolerances, PETSC_DECIDE to leave current value 5402 - vrtol - vector of relative tolerances or NULL, used in preference to atol if present 5403 5404 Options Database keys: 5405 + -ts_rtol <rtol> - relative tolerance for local truncation error 5406 - -ts_atol <atol> Absolute tolerance for local truncation error 5407 5408 Notes: 5409 With PETSc's implicit schemes for DAE problems, the calculation of the local truncation error 5410 (LTE) includes both the differential and the algebraic variables. If one wants the LTE to be 5411 computed only for the differential or the algebraic part then this can be done using the vector of 5412 tolerances vatol. For example, by setting the tolerance vector with the desired tolerance for the 5413 differential part and infinity for the algebraic part, the LTE calculation will include only the 5414 differential variables. 5415 5416 Level: beginner 5417 5418 .seealso: TS, TSAdapt, TSVecNormWRMS(), TSGetTolerances() 5419 @*/ 5420 PetscErrorCode TSSetTolerances(TS ts,PetscReal atol,Vec vatol,PetscReal rtol,Vec vrtol) 5421 { 5422 PetscErrorCode ierr; 5423 5424 PetscFunctionBegin; 5425 if (atol != PETSC_DECIDE && atol != PETSC_DEFAULT) ts->atol = atol; 5426 if (vatol) { 5427 ierr = PetscObjectReference((PetscObject)vatol);CHKERRQ(ierr); 5428 ierr = VecDestroy(&ts->vatol);CHKERRQ(ierr); 5429 ts->vatol = vatol; 5430 } 5431 if (rtol != PETSC_DECIDE && rtol != PETSC_DEFAULT) ts->rtol = rtol; 5432 if (vrtol) { 5433 ierr = PetscObjectReference((PetscObject)vrtol);CHKERRQ(ierr); 5434 ierr = VecDestroy(&ts->vrtol);CHKERRQ(ierr); 5435 ts->vrtol = vrtol; 5436 } 5437 PetscFunctionReturn(0); 5438 } 5439 5440 /*@ 5441 TSGetTolerances - Get tolerances for local truncation error when using adaptive controller 5442 5443 Logically Collective 5444 5445 Input Arguments: 5446 . ts - time integration context 5447 5448 Output Arguments: 5449 + atol - scalar absolute tolerances, NULL to ignore 5450 . vatol - vector of absolute tolerances, NULL to ignore 5451 . rtol - scalar relative tolerances, NULL to ignore 5452 - vrtol - vector of relative tolerances, NULL to ignore 5453 5454 Level: beginner 5455 5456 .seealso: TS, TSAdapt, TSVecNormWRMS(), TSSetTolerances() 5457 @*/ 5458 PetscErrorCode TSGetTolerances(TS ts,PetscReal *atol,Vec *vatol,PetscReal *rtol,Vec *vrtol) 5459 { 5460 PetscFunctionBegin; 5461 if (atol) *atol = ts->atol; 5462 if (vatol) *vatol = ts->vatol; 5463 if (rtol) *rtol = ts->rtol; 5464 if (vrtol) *vrtol = ts->vrtol; 5465 PetscFunctionReturn(0); 5466 } 5467 5468 /*@ 5469 TSErrorWeightedNorm2 - compute a weighted 2-norm of the difference between two state vectors 5470 5471 Collective on TS 5472 5473 Input Arguments: 5474 + ts - time stepping context 5475 . U - state vector, usually ts->vec_sol 5476 - Y - state vector to be compared to U 5477 5478 Output Arguments: 5479 . norm - weighted norm, a value of 1.0 means that the error matches the tolerances 5480 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 5481 . normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 5482 5483 Level: developer 5484 5485 .seealso: TSErrorWeightedNorm(), TSErrorWeightedNormInfinity() 5486 @*/ 5487 PetscErrorCode TSErrorWeightedNorm2(TS ts,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 5488 { 5489 PetscErrorCode ierr; 5490 PetscInt i,n,N,rstart; 5491 PetscInt n_loc,na_loc,nr_loc; 5492 PetscReal n_glb,na_glb,nr_glb; 5493 const PetscScalar *u,*y; 5494 PetscReal sum,suma,sumr,gsum,gsuma,gsumr,diff; 5495 PetscReal tol,tola,tolr; 5496 PetscReal err_loc[6],err_glb[6]; 5497 5498 PetscFunctionBegin; 5499 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5500 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 5501 PetscValidHeaderSpecific(Y,VEC_CLASSID,3); 5502 PetscValidType(U,2); 5503 PetscValidType(Y,3); 5504 PetscCheckSameComm(U,2,Y,3); 5505 PetscValidPointer(norm,4); 5506 PetscValidPointer(norma,5); 5507 PetscValidPointer(normr,6); 5508 if (U == Y) SETERRQ(PetscObjectComm((PetscObject)U),PETSC_ERR_ARG_IDN,"U and Y cannot be the same vector"); 5509 5510 ierr = VecGetSize(U,&N);CHKERRQ(ierr); 5511 ierr = VecGetLocalSize(U,&n);CHKERRQ(ierr); 5512 ierr = VecGetOwnershipRange(U,&rstart,NULL);CHKERRQ(ierr); 5513 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 5514 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 5515 sum = 0.; n_loc = 0; 5516 suma = 0.; na_loc = 0; 5517 sumr = 0.; nr_loc = 0; 5518 if (ts->vatol && ts->vrtol) { 5519 const PetscScalar *atol,*rtol; 5520 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5521 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5522 for (i=0; i<n; i++) { 5523 diff = PetscAbsScalar(y[i] - u[i]); 5524 tola = PetscRealPart(atol[i]); 5525 if(tola>0.){ 5526 suma += PetscSqr(diff/tola); 5527 na_loc++; 5528 } 5529 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5530 if(tolr>0.){ 5531 sumr += PetscSqr(diff/tolr); 5532 nr_loc++; 5533 } 5534 tol=tola+tolr; 5535 if(tol>0.){ 5536 sum += PetscSqr(diff/tol); 5537 n_loc++; 5538 } 5539 } 5540 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5541 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5542 } else if (ts->vatol) { /* vector atol, scalar rtol */ 5543 const PetscScalar *atol; 5544 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5545 for (i=0; i<n; i++) { 5546 diff = PetscAbsScalar(y[i] - u[i]); 5547 tola = PetscRealPart(atol[i]); 5548 if(tola>0.){ 5549 suma += PetscSqr(diff/tola); 5550 na_loc++; 5551 } 5552 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5553 if(tolr>0.){ 5554 sumr += PetscSqr(diff/tolr); 5555 nr_loc++; 5556 } 5557 tol=tola+tolr; 5558 if(tol>0.){ 5559 sum += PetscSqr(diff/tol); 5560 n_loc++; 5561 } 5562 } 5563 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5564 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 5565 const PetscScalar *rtol; 5566 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5567 for (i=0; i<n; i++) { 5568 diff = PetscAbsScalar(y[i] - u[i]); 5569 tola = ts->atol; 5570 if(tola>0.){ 5571 suma += PetscSqr(diff/tola); 5572 na_loc++; 5573 } 5574 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5575 if(tolr>0.){ 5576 sumr += PetscSqr(diff/tolr); 5577 nr_loc++; 5578 } 5579 tol=tola+tolr; 5580 if(tol>0.){ 5581 sum += PetscSqr(diff/tol); 5582 n_loc++; 5583 } 5584 } 5585 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5586 } else { /* scalar atol, scalar rtol */ 5587 for (i=0; i<n; i++) { 5588 diff = PetscAbsScalar(y[i] - u[i]); 5589 tola = ts->atol; 5590 if(tola>0.){ 5591 suma += PetscSqr(diff/tola); 5592 na_loc++; 5593 } 5594 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5595 if(tolr>0.){ 5596 sumr += PetscSqr(diff/tolr); 5597 nr_loc++; 5598 } 5599 tol=tola+tolr; 5600 if(tol>0.){ 5601 sum += PetscSqr(diff/tol); 5602 n_loc++; 5603 } 5604 } 5605 } 5606 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 5607 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 5608 5609 err_loc[0] = sum; 5610 err_loc[1] = suma; 5611 err_loc[2] = sumr; 5612 err_loc[3] = (PetscReal)n_loc; 5613 err_loc[4] = (PetscReal)na_loc; 5614 err_loc[5] = (PetscReal)nr_loc; 5615 5616 ierr = MPIU_Allreduce(err_loc,err_glb,6,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 5617 5618 gsum = err_glb[0]; 5619 gsuma = err_glb[1]; 5620 gsumr = err_glb[2]; 5621 n_glb = err_glb[3]; 5622 na_glb = err_glb[4]; 5623 nr_glb = err_glb[5]; 5624 5625 *norm = 0.; 5626 if(n_glb>0. ){*norm = PetscSqrtReal(gsum / n_glb );} 5627 *norma = 0.; 5628 if(na_glb>0.){*norma = PetscSqrtReal(gsuma / na_glb);} 5629 *normr = 0.; 5630 if(nr_glb>0.){*normr = PetscSqrtReal(gsumr / nr_glb);} 5631 5632 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 5633 if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 5634 if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 5635 PetscFunctionReturn(0); 5636 } 5637 5638 /*@ 5639 TSErrorWeightedNormInfinity - compute a weighted infinity-norm of the difference between two state vectors 5640 5641 Collective on TS 5642 5643 Input Arguments: 5644 + ts - time stepping context 5645 . U - state vector, usually ts->vec_sol 5646 - Y - state vector to be compared to U 5647 5648 Output Arguments: 5649 . norm - weighted norm, a value of 1.0 means that the error matches the tolerances 5650 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 5651 . normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 5652 5653 Level: developer 5654 5655 .seealso: TSErrorWeightedNorm(), TSErrorWeightedNorm2() 5656 @*/ 5657 PetscErrorCode TSErrorWeightedNormInfinity(TS ts,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 5658 { 5659 PetscErrorCode ierr; 5660 PetscInt i,n,N,rstart; 5661 const PetscScalar *u,*y; 5662 PetscReal max,gmax,maxa,gmaxa,maxr,gmaxr; 5663 PetscReal tol,tola,tolr,diff; 5664 PetscReal err_loc[3],err_glb[3]; 5665 5666 PetscFunctionBegin; 5667 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5668 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 5669 PetscValidHeaderSpecific(Y,VEC_CLASSID,3); 5670 PetscValidType(U,2); 5671 PetscValidType(Y,3); 5672 PetscCheckSameComm(U,2,Y,3); 5673 PetscValidPointer(norm,4); 5674 PetscValidPointer(norma,5); 5675 PetscValidPointer(normr,6); 5676 if (U == Y) SETERRQ(PetscObjectComm((PetscObject)U),PETSC_ERR_ARG_IDN,"U and Y cannot be the same vector"); 5677 5678 ierr = VecGetSize(U,&N);CHKERRQ(ierr); 5679 ierr = VecGetLocalSize(U,&n);CHKERRQ(ierr); 5680 ierr = VecGetOwnershipRange(U,&rstart,NULL);CHKERRQ(ierr); 5681 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 5682 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 5683 5684 max=0.; 5685 maxa=0.; 5686 maxr=0.; 5687 5688 if (ts->vatol && ts->vrtol) { /* vector atol, vector rtol */ 5689 const PetscScalar *atol,*rtol; 5690 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5691 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5692 5693 for (i=0; i<n; i++) { 5694 diff = PetscAbsScalar(y[i] - u[i]); 5695 tola = PetscRealPart(atol[i]); 5696 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5697 tol = tola+tolr; 5698 if(tola>0.){ 5699 maxa = PetscMax(maxa,diff / tola); 5700 } 5701 if(tolr>0.){ 5702 maxr = PetscMax(maxr,diff / tolr); 5703 } 5704 if(tol>0.){ 5705 max = PetscMax(max,diff / tol); 5706 } 5707 } 5708 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5709 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5710 } else if (ts->vatol) { /* vector atol, scalar rtol */ 5711 const PetscScalar *atol; 5712 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5713 for (i=0; i<n; i++) { 5714 diff = PetscAbsScalar(y[i] - u[i]); 5715 tola = PetscRealPart(atol[i]); 5716 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5717 tol = tola+tolr; 5718 if(tola>0.){ 5719 maxa = PetscMax(maxa,diff / tola); 5720 } 5721 if(tolr>0.){ 5722 maxr = PetscMax(maxr,diff / tolr); 5723 } 5724 if(tol>0.){ 5725 max = PetscMax(max,diff / tol); 5726 } 5727 } 5728 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5729 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 5730 const PetscScalar *rtol; 5731 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5732 5733 for (i=0; i<n; i++) { 5734 diff = PetscAbsScalar(y[i] - u[i]); 5735 tola = ts->atol; 5736 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5737 tol = tola+tolr; 5738 if(tola>0.){ 5739 maxa = PetscMax(maxa,diff / tola); 5740 } 5741 if(tolr>0.){ 5742 maxr = PetscMax(maxr,diff / tolr); 5743 } 5744 if(tol>0.){ 5745 max = PetscMax(max,diff / tol); 5746 } 5747 } 5748 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5749 } else { /* scalar atol, scalar rtol */ 5750 5751 for (i=0; i<n; i++) { 5752 diff = PetscAbsScalar(y[i] - u[i]); 5753 tola = ts->atol; 5754 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5755 tol = tola+tolr; 5756 if(tola>0.){ 5757 maxa = PetscMax(maxa,diff / tola); 5758 } 5759 if(tolr>0.){ 5760 maxr = PetscMax(maxr,diff / tolr); 5761 } 5762 if(tol>0.){ 5763 max = PetscMax(max,diff / tol); 5764 } 5765 } 5766 } 5767 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 5768 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 5769 err_loc[0] = max; 5770 err_loc[1] = maxa; 5771 err_loc[2] = maxr; 5772 ierr = MPIU_Allreduce(err_loc,err_glb,3,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 5773 gmax = err_glb[0]; 5774 gmaxa = err_glb[1]; 5775 gmaxr = err_glb[2]; 5776 5777 *norm = gmax; 5778 *norma = gmaxa; 5779 *normr = gmaxr; 5780 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 5781 if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 5782 if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 5783 PetscFunctionReturn(0); 5784 } 5785 5786 /*@ 5787 TSErrorWeightedNorm - compute a weighted norm of the difference between two state vectors based on supplied absolute and relative tolerances 5788 5789 Collective on TS 5790 5791 Input Arguments: 5792 + ts - time stepping context 5793 . U - state vector, usually ts->vec_sol 5794 . Y - state vector to be compared to U 5795 - wnormtype - norm type, either NORM_2 or NORM_INFINITY 5796 5797 Output Arguments: 5798 . norm - weighted norm, a value of 1.0 achieves a balance between absolute and relative tolerances 5799 . norma - weighted norm, a value of 1.0 means that the error meets the absolute tolerance set by the user 5800 . normr - weighted norm, a value of 1.0 means that the error meets the relative tolerance set by the user 5801 5802 Options Database Keys: 5803 . -ts_adapt_wnormtype <wnormtype> - 2, INFINITY 5804 5805 Level: developer 5806 5807 .seealso: TSErrorWeightedNormInfinity(), TSErrorWeightedNorm2(), TSErrorWeightedENorm 5808 @*/ 5809 PetscErrorCode TSErrorWeightedNorm(TS ts,Vec U,Vec Y,NormType wnormtype,PetscReal *norm,PetscReal *norma,PetscReal *normr) 5810 { 5811 PetscErrorCode ierr; 5812 5813 PetscFunctionBegin; 5814 if (wnormtype == NORM_2) { 5815 ierr = TSErrorWeightedNorm2(ts,U,Y,norm,norma,normr);CHKERRQ(ierr); 5816 } else if(wnormtype == NORM_INFINITY) { 5817 ierr = TSErrorWeightedNormInfinity(ts,U,Y,norm,norma,normr);CHKERRQ(ierr); 5818 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]); 5819 PetscFunctionReturn(0); 5820 } 5821 5822 5823 /*@ 5824 TSErrorWeightedENorm2 - compute a weighted 2 error norm based on supplied absolute and relative tolerances 5825 5826 Collective on TS 5827 5828 Input Arguments: 5829 + ts - time stepping context 5830 . E - error vector 5831 . U - state vector, usually ts->vec_sol 5832 - Y - state vector, previous time step 5833 5834 Output Arguments: 5835 . norm - weighted norm, a value of 1.0 means that the error matches the tolerances 5836 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 5837 . normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 5838 5839 Level: developer 5840 5841 .seealso: TSErrorWeightedENorm(), TSErrorWeightedENormInfinity() 5842 @*/ 5843 PetscErrorCode TSErrorWeightedENorm2(TS ts,Vec E,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 5844 { 5845 PetscErrorCode ierr; 5846 PetscInt i,n,N,rstart; 5847 PetscInt n_loc,na_loc,nr_loc; 5848 PetscReal n_glb,na_glb,nr_glb; 5849 const PetscScalar *e,*u,*y; 5850 PetscReal err,sum,suma,sumr,gsum,gsuma,gsumr; 5851 PetscReal tol,tola,tolr; 5852 PetscReal err_loc[6],err_glb[6]; 5853 5854 PetscFunctionBegin; 5855 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5856 PetscValidHeaderSpecific(E,VEC_CLASSID,2); 5857 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 5858 PetscValidHeaderSpecific(Y,VEC_CLASSID,4); 5859 PetscValidType(E,2); 5860 PetscValidType(U,3); 5861 PetscValidType(Y,4); 5862 PetscCheckSameComm(E,2,U,3); 5863 PetscCheckSameComm(U,2,Y,3); 5864 PetscValidPointer(norm,5); 5865 PetscValidPointer(norma,6); 5866 PetscValidPointer(normr,7); 5867 5868 ierr = VecGetSize(E,&N);CHKERRQ(ierr); 5869 ierr = VecGetLocalSize(E,&n);CHKERRQ(ierr); 5870 ierr = VecGetOwnershipRange(E,&rstart,NULL);CHKERRQ(ierr); 5871 ierr = VecGetArrayRead(E,&e);CHKERRQ(ierr); 5872 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 5873 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 5874 sum = 0.; n_loc = 0; 5875 suma = 0.; na_loc = 0; 5876 sumr = 0.; nr_loc = 0; 5877 if (ts->vatol && ts->vrtol) { 5878 const PetscScalar *atol,*rtol; 5879 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5880 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5881 for (i=0; i<n; i++) { 5882 err = PetscAbsScalar(e[i]); 5883 tola = PetscRealPart(atol[i]); 5884 if(tola>0.){ 5885 suma += PetscSqr(err/tola); 5886 na_loc++; 5887 } 5888 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5889 if(tolr>0.){ 5890 sumr += PetscSqr(err/tolr); 5891 nr_loc++; 5892 } 5893 tol=tola+tolr; 5894 if(tol>0.){ 5895 sum += PetscSqr(err/tol); 5896 n_loc++; 5897 } 5898 } 5899 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5900 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5901 } else if (ts->vatol) { /* vector atol, scalar rtol */ 5902 const PetscScalar *atol; 5903 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5904 for (i=0; i<n; i++) { 5905 err = PetscAbsScalar(e[i]); 5906 tola = PetscRealPart(atol[i]); 5907 if(tola>0.){ 5908 suma += PetscSqr(err/tola); 5909 na_loc++; 5910 } 5911 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5912 if(tolr>0.){ 5913 sumr += PetscSqr(err/tolr); 5914 nr_loc++; 5915 } 5916 tol=tola+tolr; 5917 if(tol>0.){ 5918 sum += PetscSqr(err/tol); 5919 n_loc++; 5920 } 5921 } 5922 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5923 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 5924 const PetscScalar *rtol; 5925 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5926 for (i=0; i<n; i++) { 5927 err = PetscAbsScalar(e[i]); 5928 tola = ts->atol; 5929 if(tola>0.){ 5930 suma += PetscSqr(err/tola); 5931 na_loc++; 5932 } 5933 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5934 if(tolr>0.){ 5935 sumr += PetscSqr(err/tolr); 5936 nr_loc++; 5937 } 5938 tol=tola+tolr; 5939 if(tol>0.){ 5940 sum += PetscSqr(err/tol); 5941 n_loc++; 5942 } 5943 } 5944 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5945 } else { /* scalar atol, scalar rtol */ 5946 for (i=0; i<n; i++) { 5947 err = PetscAbsScalar(e[i]); 5948 tola = ts->atol; 5949 if(tola>0.){ 5950 suma += PetscSqr(err/tola); 5951 na_loc++; 5952 } 5953 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5954 if(tolr>0.){ 5955 sumr += PetscSqr(err/tolr); 5956 nr_loc++; 5957 } 5958 tol=tola+tolr; 5959 if(tol>0.){ 5960 sum += PetscSqr(err/tol); 5961 n_loc++; 5962 } 5963 } 5964 } 5965 ierr = VecRestoreArrayRead(E,&e);CHKERRQ(ierr); 5966 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 5967 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 5968 5969 err_loc[0] = sum; 5970 err_loc[1] = suma; 5971 err_loc[2] = sumr; 5972 err_loc[3] = (PetscReal)n_loc; 5973 err_loc[4] = (PetscReal)na_loc; 5974 err_loc[5] = (PetscReal)nr_loc; 5975 5976 ierr = MPIU_Allreduce(err_loc,err_glb,6,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 5977 5978 gsum = err_glb[0]; 5979 gsuma = err_glb[1]; 5980 gsumr = err_glb[2]; 5981 n_glb = err_glb[3]; 5982 na_glb = err_glb[4]; 5983 nr_glb = err_glb[5]; 5984 5985 *norm = 0.; 5986 if(n_glb>0. ){*norm = PetscSqrtReal(gsum / n_glb );} 5987 *norma = 0.; 5988 if(na_glb>0.){*norma = PetscSqrtReal(gsuma / na_glb);} 5989 *normr = 0.; 5990 if(nr_glb>0.){*normr = PetscSqrtReal(gsumr / nr_glb);} 5991 5992 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 5993 if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 5994 if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 5995 PetscFunctionReturn(0); 5996 } 5997 5998 /*@ 5999 TSErrorWeightedENormInfinity - compute a weighted infinity error norm based on supplied absolute and relative tolerances 6000 Collective on TS 6001 6002 Input Arguments: 6003 + ts - time stepping context 6004 . E - error vector 6005 . U - state vector, usually ts->vec_sol 6006 - Y - state vector, previous time step 6007 6008 Output Arguments: 6009 . norm - weighted norm, a value of 1.0 means that the error matches the tolerances 6010 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 6011 . normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 6012 6013 Level: developer 6014 6015 .seealso: TSErrorWeightedENorm(), TSErrorWeightedENorm2() 6016 @*/ 6017 PetscErrorCode TSErrorWeightedENormInfinity(TS ts,Vec E,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6018 { 6019 PetscErrorCode ierr; 6020 PetscInt i,n,N,rstart; 6021 const PetscScalar *e,*u,*y; 6022 PetscReal err,max,gmax,maxa,gmaxa,maxr,gmaxr; 6023 PetscReal tol,tola,tolr; 6024 PetscReal err_loc[3],err_glb[3]; 6025 6026 PetscFunctionBegin; 6027 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6028 PetscValidHeaderSpecific(E,VEC_CLASSID,2); 6029 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 6030 PetscValidHeaderSpecific(Y,VEC_CLASSID,4); 6031 PetscValidType(E,2); 6032 PetscValidType(U,3); 6033 PetscValidType(Y,4); 6034 PetscCheckSameComm(E,2,U,3); 6035 PetscCheckSameComm(U,2,Y,3); 6036 PetscValidPointer(norm,5); 6037 PetscValidPointer(norma,6); 6038 PetscValidPointer(normr,7); 6039 6040 ierr = VecGetSize(E,&N);CHKERRQ(ierr); 6041 ierr = VecGetLocalSize(E,&n);CHKERRQ(ierr); 6042 ierr = VecGetOwnershipRange(E,&rstart,NULL);CHKERRQ(ierr); 6043 ierr = VecGetArrayRead(E,&e);CHKERRQ(ierr); 6044 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 6045 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 6046 6047 max=0.; 6048 maxa=0.; 6049 maxr=0.; 6050 6051 if (ts->vatol && ts->vrtol) { /* vector atol, vector rtol */ 6052 const PetscScalar *atol,*rtol; 6053 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6054 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6055 6056 for (i=0; i<n; i++) { 6057 err = PetscAbsScalar(e[i]); 6058 tola = PetscRealPart(atol[i]); 6059 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6060 tol = tola+tolr; 6061 if(tola>0.){ 6062 maxa = PetscMax(maxa,err / tola); 6063 } 6064 if(tolr>0.){ 6065 maxr = PetscMax(maxr,err / tolr); 6066 } 6067 if(tol>0.){ 6068 max = PetscMax(max,err / tol); 6069 } 6070 } 6071 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6072 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6073 } else if (ts->vatol) { /* vector atol, scalar rtol */ 6074 const PetscScalar *atol; 6075 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6076 for (i=0; i<n; i++) { 6077 err = PetscAbsScalar(e[i]); 6078 tola = PetscRealPart(atol[i]); 6079 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6080 tol = tola+tolr; 6081 if(tola>0.){ 6082 maxa = PetscMax(maxa,err / tola); 6083 } 6084 if(tolr>0.){ 6085 maxr = PetscMax(maxr,err / tolr); 6086 } 6087 if(tol>0.){ 6088 max = PetscMax(max,err / tol); 6089 } 6090 } 6091 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 6092 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 6093 const PetscScalar *rtol; 6094 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6095 6096 for (i=0; i<n; i++) { 6097 err = PetscAbsScalar(e[i]); 6098 tola = ts->atol; 6099 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6100 tol = tola+tolr; 6101 if(tola>0.){ 6102 maxa = PetscMax(maxa,err / tola); 6103 } 6104 if(tolr>0.){ 6105 maxr = PetscMax(maxr,err / tolr); 6106 } 6107 if(tol>0.){ 6108 max = PetscMax(max,err / tol); 6109 } 6110 } 6111 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 6112 } else { /* scalar atol, scalar rtol */ 6113 6114 for (i=0; i<n; i++) { 6115 err = PetscAbsScalar(e[i]); 6116 tola = ts->atol; 6117 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 6118 tol = tola+tolr; 6119 if(tola>0.){ 6120 maxa = PetscMax(maxa,err / tola); 6121 } 6122 if(tolr>0.){ 6123 maxr = PetscMax(maxr,err / tolr); 6124 } 6125 if(tol>0.){ 6126 max = PetscMax(max,err / tol); 6127 } 6128 } 6129 } 6130 ierr = VecRestoreArrayRead(E,&e);CHKERRQ(ierr); 6131 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 6132 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 6133 err_loc[0] = max; 6134 err_loc[1] = maxa; 6135 err_loc[2] = maxr; 6136 ierr = MPIU_Allreduce(err_loc,err_glb,3,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6137 gmax = err_glb[0]; 6138 gmaxa = err_glb[1]; 6139 gmaxr = err_glb[2]; 6140 6141 *norm = gmax; 6142 *norma = gmaxa; 6143 *normr = gmaxr; 6144 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 6145 if (PetscIsInfOrNanScalar(*norma)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 6146 if (PetscIsInfOrNanScalar(*normr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 6147 PetscFunctionReturn(0); 6148 } 6149 6150 /*@ 6151 TSErrorWeightedENorm - compute a weighted error norm based on supplied absolute and relative tolerances 6152 6153 Collective on TS 6154 6155 Input Arguments: 6156 + ts - time stepping context 6157 . E - error vector 6158 . U - state vector, usually ts->vec_sol 6159 . Y - state vector, previous time step 6160 - wnormtype - norm type, either NORM_2 or NORM_INFINITY 6161 6162 Output Arguments: 6163 . norm - weighted norm, a value of 1.0 achieves a balance between absolute and relative tolerances 6164 . norma - weighted norm, a value of 1.0 means that the error meets the absolute tolerance set by the user 6165 . normr - weighted norm, a value of 1.0 means that the error meets the relative tolerance set by the user 6166 6167 Options Database Keys: 6168 . -ts_adapt_wnormtype <wnormtype> - 2, INFINITY 6169 6170 Level: developer 6171 6172 .seealso: TSErrorWeightedENormInfinity(), TSErrorWeightedENorm2(), TSErrorWeightedNormInfinity(), TSErrorWeightedNorm2() 6173 @*/ 6174 PetscErrorCode TSErrorWeightedENorm(TS ts,Vec E,Vec U,Vec Y,NormType wnormtype,PetscReal *norm,PetscReal *norma,PetscReal *normr) 6175 { 6176 PetscErrorCode ierr; 6177 6178 PetscFunctionBegin; 6179 if (wnormtype == NORM_2) { 6180 ierr = TSErrorWeightedENorm2(ts,E,U,Y,norm,norma,normr);CHKERRQ(ierr); 6181 } else if(wnormtype == NORM_INFINITY) { 6182 ierr = TSErrorWeightedENormInfinity(ts,E,U,Y,norm,norma,normr);CHKERRQ(ierr); 6183 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]); 6184 PetscFunctionReturn(0); 6185 } 6186 6187 6188 /*@ 6189 TSSetCFLTimeLocal - Set the local CFL constraint relative to forward Euler 6190 6191 Logically Collective on TS 6192 6193 Input Arguments: 6194 + ts - time stepping context 6195 - cfltime - maximum stable time step if using forward Euler (value can be different on each process) 6196 6197 Note: 6198 After calling this function, the global CFL time can be obtained by calling TSGetCFLTime() 6199 6200 Level: intermediate 6201 6202 .seealso: TSGetCFLTime(), TSADAPTCFL 6203 @*/ 6204 PetscErrorCode TSSetCFLTimeLocal(TS ts,PetscReal cfltime) 6205 { 6206 PetscFunctionBegin; 6207 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6208 ts->cfltime_local = cfltime; 6209 ts->cfltime = -1.; 6210 PetscFunctionReturn(0); 6211 } 6212 6213 /*@ 6214 TSGetCFLTime - Get the maximum stable time step according to CFL criteria applied to forward Euler 6215 6216 Collective on TS 6217 6218 Input Arguments: 6219 . ts - time stepping context 6220 6221 Output Arguments: 6222 . cfltime - maximum stable time step for forward Euler 6223 6224 Level: advanced 6225 6226 .seealso: TSSetCFLTimeLocal() 6227 @*/ 6228 PetscErrorCode TSGetCFLTime(TS ts,PetscReal *cfltime) 6229 { 6230 PetscErrorCode ierr; 6231 6232 PetscFunctionBegin; 6233 if (ts->cfltime < 0) { 6234 ierr = MPIU_Allreduce(&ts->cfltime_local,&ts->cfltime,1,MPIU_REAL,MPIU_MIN,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 6235 } 6236 *cfltime = ts->cfltime; 6237 PetscFunctionReturn(0); 6238 } 6239 6240 /*@ 6241 TSVISetVariableBounds - Sets the lower and upper bounds for the solution vector. xl <= x <= xu 6242 6243 Input Parameters: 6244 . ts - the TS context. 6245 . xl - lower bound. 6246 . xu - upper bound. 6247 6248 Notes: 6249 If this routine is not called then the lower and upper bounds are set to 6250 PETSC_NINFINITY and PETSC_INFINITY respectively during SNESSetUp(). 6251 6252 Level: advanced 6253 6254 @*/ 6255 PetscErrorCode TSVISetVariableBounds(TS ts, Vec xl, Vec xu) 6256 { 6257 PetscErrorCode ierr; 6258 SNES snes; 6259 6260 PetscFunctionBegin; 6261 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 6262 ierr = SNESVISetVariableBounds(snes,xl,xu);CHKERRQ(ierr); 6263 PetscFunctionReturn(0); 6264 } 6265 6266 #if defined(PETSC_HAVE_MATLAB_ENGINE) 6267 #include <mex.h> 6268 6269 typedef struct {char *funcname; mxArray *ctx;} TSMatlabContext; 6270 6271 /* 6272 TSComputeFunction_Matlab - Calls the function that has been set with 6273 TSSetFunctionMatlab(). 6274 6275 Collective on TS 6276 6277 Input Parameters: 6278 + snes - the TS context 6279 - u - input vector 6280 6281 Output Parameter: 6282 . y - function vector, as set by TSSetFunction() 6283 6284 Notes: 6285 TSComputeFunction() is typically used within nonlinear solvers 6286 implementations, so most users would not generally call this routine 6287 themselves. 6288 6289 Level: developer 6290 6291 .keywords: TS, nonlinear, compute, function 6292 6293 .seealso: TSSetFunction(), TSGetFunction() 6294 */ 6295 PetscErrorCode TSComputeFunction_Matlab(TS snes,PetscReal time,Vec u,Vec udot,Vec y, void *ctx) 6296 { 6297 PetscErrorCode ierr; 6298 TSMatlabContext *sctx = (TSMatlabContext*)ctx; 6299 int nlhs = 1,nrhs = 7; 6300 mxArray *plhs[1],*prhs[7]; 6301 long long int lx = 0,lxdot = 0,ly = 0,ls = 0; 6302 6303 PetscFunctionBegin; 6304 PetscValidHeaderSpecific(snes,TS_CLASSID,1); 6305 PetscValidHeaderSpecific(u,VEC_CLASSID,3); 6306 PetscValidHeaderSpecific(udot,VEC_CLASSID,4); 6307 PetscValidHeaderSpecific(y,VEC_CLASSID,5); 6308 PetscCheckSameComm(snes,1,u,3); 6309 PetscCheckSameComm(snes,1,y,5); 6310 6311 ierr = PetscMemcpy(&ls,&snes,sizeof(snes));CHKERRQ(ierr); 6312 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 6313 ierr = PetscMemcpy(&lxdot,&udot,sizeof(udot));CHKERRQ(ierr); 6314 ierr = PetscMemcpy(&ly,&y,sizeof(u));CHKERRQ(ierr); 6315 6316 prhs[0] = mxCreateDoubleScalar((double)ls); 6317 prhs[1] = mxCreateDoubleScalar(time); 6318 prhs[2] = mxCreateDoubleScalar((double)lx); 6319 prhs[3] = mxCreateDoubleScalar((double)lxdot); 6320 prhs[4] = mxCreateDoubleScalar((double)ly); 6321 prhs[5] = mxCreateString(sctx->funcname); 6322 prhs[6] = sctx->ctx; 6323 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSComputeFunctionInternal");CHKERRQ(ierr); 6324 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 6325 mxDestroyArray(prhs[0]); 6326 mxDestroyArray(prhs[1]); 6327 mxDestroyArray(prhs[2]); 6328 mxDestroyArray(prhs[3]); 6329 mxDestroyArray(prhs[4]); 6330 mxDestroyArray(prhs[5]); 6331 mxDestroyArray(plhs[0]); 6332 PetscFunctionReturn(0); 6333 } 6334 6335 /* 6336 TSSetFunctionMatlab - Sets the function evaluation routine and function 6337 vector for use by the TS routines in solving ODEs 6338 equations from MATLAB. Here the function is a string containing the name of a MATLAB function 6339 6340 Logically Collective on TS 6341 6342 Input Parameters: 6343 + ts - the TS context 6344 - func - function evaluation routine 6345 6346 Calling sequence of func: 6347 $ func (TS ts,PetscReal time,Vec u,Vec udot,Vec f,void *ctx); 6348 6349 Level: beginner 6350 6351 .keywords: TS, nonlinear, set, function 6352 6353 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 6354 */ 6355 PetscErrorCode TSSetFunctionMatlab(TS ts,const char *func,mxArray *ctx) 6356 { 6357 PetscErrorCode ierr; 6358 TSMatlabContext *sctx; 6359 6360 PetscFunctionBegin; 6361 /* currently sctx is memory bleed */ 6362 ierr = PetscNew(&sctx);CHKERRQ(ierr); 6363 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 6364 /* 6365 This should work, but it doesn't 6366 sctx->ctx = ctx; 6367 mexMakeArrayPersistent(sctx->ctx); 6368 */ 6369 sctx->ctx = mxDuplicateArray(ctx); 6370 6371 ierr = TSSetIFunction(ts,NULL,TSComputeFunction_Matlab,sctx);CHKERRQ(ierr); 6372 PetscFunctionReturn(0); 6373 } 6374 6375 /* 6376 TSComputeJacobian_Matlab - Calls the function that has been set with 6377 TSSetJacobianMatlab(). 6378 6379 Collective on TS 6380 6381 Input Parameters: 6382 + ts - the TS context 6383 . u - input vector 6384 . A, B - the matrices 6385 - ctx - user context 6386 6387 Level: developer 6388 6389 .keywords: TS, nonlinear, compute, function 6390 6391 .seealso: TSSetFunction(), TSGetFunction() 6392 @*/ 6393 PetscErrorCode TSComputeJacobian_Matlab(TS ts,PetscReal time,Vec u,Vec udot,PetscReal shift,Mat A,Mat B,void *ctx) 6394 { 6395 PetscErrorCode ierr; 6396 TSMatlabContext *sctx = (TSMatlabContext*)ctx; 6397 int nlhs = 2,nrhs = 9; 6398 mxArray *plhs[2],*prhs[9]; 6399 long long int lx = 0,lxdot = 0,lA = 0,ls = 0, lB = 0; 6400 6401 PetscFunctionBegin; 6402 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6403 PetscValidHeaderSpecific(u,VEC_CLASSID,3); 6404 6405 /* call Matlab function in ctx with arguments u and y */ 6406 6407 ierr = PetscMemcpy(&ls,&ts,sizeof(ts));CHKERRQ(ierr); 6408 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 6409 ierr = PetscMemcpy(&lxdot,&udot,sizeof(u));CHKERRQ(ierr); 6410 ierr = PetscMemcpy(&lA,A,sizeof(u));CHKERRQ(ierr); 6411 ierr = PetscMemcpy(&lB,B,sizeof(u));CHKERRQ(ierr); 6412 6413 prhs[0] = mxCreateDoubleScalar((double)ls); 6414 prhs[1] = mxCreateDoubleScalar((double)time); 6415 prhs[2] = mxCreateDoubleScalar((double)lx); 6416 prhs[3] = mxCreateDoubleScalar((double)lxdot); 6417 prhs[4] = mxCreateDoubleScalar((double)shift); 6418 prhs[5] = mxCreateDoubleScalar((double)lA); 6419 prhs[6] = mxCreateDoubleScalar((double)lB); 6420 prhs[7] = mxCreateString(sctx->funcname); 6421 prhs[8] = sctx->ctx; 6422 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSComputeJacobianInternal");CHKERRQ(ierr); 6423 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 6424 mxDestroyArray(prhs[0]); 6425 mxDestroyArray(prhs[1]); 6426 mxDestroyArray(prhs[2]); 6427 mxDestroyArray(prhs[3]); 6428 mxDestroyArray(prhs[4]); 6429 mxDestroyArray(prhs[5]); 6430 mxDestroyArray(prhs[6]); 6431 mxDestroyArray(prhs[7]); 6432 mxDestroyArray(plhs[0]); 6433 mxDestroyArray(plhs[1]); 6434 PetscFunctionReturn(0); 6435 } 6436 6437 /* 6438 TSSetJacobianMatlab - Sets the Jacobian function evaluation routine and two empty Jacobian matrices 6439 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 6440 6441 Logically Collective on TS 6442 6443 Input Parameters: 6444 + ts - the TS context 6445 . A,B - Jacobian matrices 6446 . func - function evaluation routine 6447 - ctx - user context 6448 6449 Calling sequence of func: 6450 $ flag = func (TS ts,PetscReal time,Vec u,Vec udot,Mat A,Mat B,void *ctx); 6451 6452 Level: developer 6453 6454 .keywords: TS, nonlinear, set, function 6455 6456 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 6457 */ 6458 PetscErrorCode TSSetJacobianMatlab(TS ts,Mat A,Mat B,const char *func,mxArray *ctx) 6459 { 6460 PetscErrorCode ierr; 6461 TSMatlabContext *sctx; 6462 6463 PetscFunctionBegin; 6464 /* currently sctx is memory bleed */ 6465 ierr = PetscNew(&sctx);CHKERRQ(ierr); 6466 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 6467 /* 6468 This should work, but it doesn't 6469 sctx->ctx = ctx; 6470 mexMakeArrayPersistent(sctx->ctx); 6471 */ 6472 sctx->ctx = mxDuplicateArray(ctx); 6473 6474 ierr = TSSetIJacobian(ts,A,B,TSComputeJacobian_Matlab,sctx);CHKERRQ(ierr); 6475 PetscFunctionReturn(0); 6476 } 6477 6478 /* 6479 TSMonitor_Matlab - Calls the function that has been set with TSMonitorSetMatlab(). 6480 6481 Collective on TS 6482 6483 .seealso: TSSetFunction(), TSGetFunction() 6484 @*/ 6485 PetscErrorCode TSMonitor_Matlab(TS ts,PetscInt it, PetscReal time,Vec u, void *ctx) 6486 { 6487 PetscErrorCode ierr; 6488 TSMatlabContext *sctx = (TSMatlabContext*)ctx; 6489 int nlhs = 1,nrhs = 6; 6490 mxArray *plhs[1],*prhs[6]; 6491 long long int lx = 0,ls = 0; 6492 6493 PetscFunctionBegin; 6494 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6495 PetscValidHeaderSpecific(u,VEC_CLASSID,4); 6496 6497 ierr = PetscMemcpy(&ls,&ts,sizeof(ts));CHKERRQ(ierr); 6498 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 6499 6500 prhs[0] = mxCreateDoubleScalar((double)ls); 6501 prhs[1] = mxCreateDoubleScalar((double)it); 6502 prhs[2] = mxCreateDoubleScalar((double)time); 6503 prhs[3] = mxCreateDoubleScalar((double)lx); 6504 prhs[4] = mxCreateString(sctx->funcname); 6505 prhs[5] = sctx->ctx; 6506 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSMonitorInternal");CHKERRQ(ierr); 6507 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 6508 mxDestroyArray(prhs[0]); 6509 mxDestroyArray(prhs[1]); 6510 mxDestroyArray(prhs[2]); 6511 mxDestroyArray(prhs[3]); 6512 mxDestroyArray(prhs[4]); 6513 mxDestroyArray(plhs[0]); 6514 PetscFunctionReturn(0); 6515 } 6516 6517 /* 6518 TSMonitorSetMatlab - Sets the monitor function from Matlab 6519 6520 Level: developer 6521 6522 .keywords: TS, nonlinear, set, function 6523 6524 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 6525 */ 6526 PetscErrorCode TSMonitorSetMatlab(TS ts,const char *func,mxArray *ctx) 6527 { 6528 PetscErrorCode ierr; 6529 TSMatlabContext *sctx; 6530 6531 PetscFunctionBegin; 6532 /* currently sctx is memory bleed */ 6533 ierr = PetscNew(&sctx);CHKERRQ(ierr); 6534 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 6535 /* 6536 This should work, but it doesn't 6537 sctx->ctx = ctx; 6538 mexMakeArrayPersistent(sctx->ctx); 6539 */ 6540 sctx->ctx = mxDuplicateArray(ctx); 6541 6542 ierr = TSMonitorSet(ts,TSMonitor_Matlab,sctx,NULL);CHKERRQ(ierr); 6543 PetscFunctionReturn(0); 6544 } 6545 #endif 6546 6547 /*@C 6548 TSMonitorLGSolution - Monitors progress of the TS solvers by plotting each component of the solution vector 6549 in a time based line graph 6550 6551 Collective on TS 6552 6553 Input Parameters: 6554 + ts - the TS context 6555 . step - current time-step 6556 . ptime - current time 6557 . u - current solution 6558 - dctx - the TSMonitorLGCtx object that contains all the options for the monitoring, this is created with TSMonitorLGCtxCreate() 6559 6560 Options Database: 6561 . -ts_monitor_lg_solution_variables 6562 6563 Level: intermediate 6564 6565 Notes: 6566 Each process in a parallel run displays its component solutions in a separate window 6567 6568 .keywords: TS, vector, monitor, view 6569 6570 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGCtxCreate(), TSMonitorLGCtxSetVariableNames(), TSMonitorLGCtxGetVariableNames(), 6571 TSMonitorLGSetVariableNames(), TSMonitorLGGetVariableNames(), TSMonitorLGSetDisplayVariables(), TSMonitorLGCtxSetDisplayVariables(), 6572 TSMonitorLGCtxSetTransform(), TSMonitorLGSetTransform(), TSMonitorLGError(), TSMonitorLGSNESIterations(), TSMonitorLGKSPIterations(), 6573 TSMonitorEnvelopeCtxCreate(), TSMonitorEnvelopeGetBounds(), TSMonitorEnvelopeCtxDestroy(), TSMonitorEnvelop() 6574 @*/ 6575 PetscErrorCode TSMonitorLGSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dctx) 6576 { 6577 PetscErrorCode ierr; 6578 TSMonitorLGCtx ctx = (TSMonitorLGCtx)dctx; 6579 const PetscScalar *yy; 6580 Vec v; 6581 6582 PetscFunctionBegin; 6583 if (step < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */ 6584 if (!step) { 6585 PetscDrawAxis axis; 6586 PetscInt dim; 6587 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 6588 ierr = PetscDrawAxisSetLabels(axis,"Solution as function of time","Time","Solution");CHKERRQ(ierr); 6589 if (!ctx->names) { 6590 PetscBool flg; 6591 /* user provides names of variables to plot but no names has been set so assume names are integer values */ 6592 ierr = PetscOptionsHasName(((PetscObject)ts)->options,((PetscObject)ts)->prefix,"-ts_monitor_lg_solution_variables",&flg);CHKERRQ(ierr); 6593 if (flg) { 6594 PetscInt i,n; 6595 char **names; 6596 ierr = VecGetSize(u,&n);CHKERRQ(ierr); 6597 ierr = PetscMalloc1(n+1,&names);CHKERRQ(ierr); 6598 for (i=0; i<n; i++) { 6599 ierr = PetscMalloc1(5,&names[i]);CHKERRQ(ierr); 6600 ierr = PetscSNPrintf(names[i],5,"%D",i);CHKERRQ(ierr); 6601 } 6602 names[n] = NULL; 6603 ctx->names = names; 6604 } 6605 } 6606 if (ctx->names && !ctx->displaynames) { 6607 char **displaynames; 6608 PetscBool flg; 6609 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 6610 ierr = PetscMalloc1(dim+1,&displaynames);CHKERRQ(ierr); 6611 ierr = PetscMemzero(displaynames,(dim+1)*sizeof(char*));CHKERRQ(ierr); 6612 ierr = PetscOptionsGetStringArray(((PetscObject)ts)->options,((PetscObject)ts)->prefix,"-ts_monitor_lg_solution_variables",displaynames,&dim,&flg);CHKERRQ(ierr); 6613 if (flg) { 6614 ierr = TSMonitorLGCtxSetDisplayVariables(ctx,(const char *const *)displaynames);CHKERRQ(ierr); 6615 } 6616 ierr = PetscStrArrayDestroy(&displaynames);CHKERRQ(ierr); 6617 } 6618 if (ctx->displaynames) { 6619 ierr = PetscDrawLGSetDimension(ctx->lg,ctx->ndisplayvariables);CHKERRQ(ierr); 6620 ierr = PetscDrawLGSetLegend(ctx->lg,(const char *const *)ctx->displaynames);CHKERRQ(ierr); 6621 } else if (ctx->names) { 6622 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 6623 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 6624 ierr = PetscDrawLGSetLegend(ctx->lg,(const char *const *)ctx->names);CHKERRQ(ierr); 6625 } else { 6626 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 6627 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 6628 } 6629 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 6630 } 6631 6632 if (!ctx->transform) v = u; 6633 else {ierr = (*ctx->transform)(ctx->transformctx,u,&v);CHKERRQ(ierr);} 6634 ierr = VecGetArrayRead(v,&yy);CHKERRQ(ierr); 6635 if (ctx->displaynames) { 6636 PetscInt i; 6637 for (i=0; i<ctx->ndisplayvariables; i++) 6638 ctx->displayvalues[i] = PetscRealPart(yy[ctx->displayvariables[i]]); 6639 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,ctx->displayvalues);CHKERRQ(ierr); 6640 } else { 6641 #if defined(PETSC_USE_COMPLEX) 6642 PetscInt i,n; 6643 PetscReal *yreal; 6644 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 6645 ierr = PetscMalloc1(n,&yreal);CHKERRQ(ierr); 6646 for (i=0; i<n; i++) yreal[i] = PetscRealPart(yy[i]); 6647 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yreal);CHKERRQ(ierr); 6648 ierr = PetscFree(yreal);CHKERRQ(ierr); 6649 #else 6650 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yy);CHKERRQ(ierr); 6651 #endif 6652 } 6653 ierr = VecRestoreArrayRead(v,&yy);CHKERRQ(ierr); 6654 if (ctx->transform) {ierr = VecDestroy(&v);CHKERRQ(ierr);} 6655 6656 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 6657 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 6658 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 6659 } 6660 PetscFunctionReturn(0); 6661 } 6662 6663 /*@C 6664 TSMonitorLGSetVariableNames - Sets the name of each component in the solution vector so that it may be displayed in the plot 6665 6666 Collective on TS 6667 6668 Input Parameters: 6669 + ts - the TS context 6670 - names - the names of the components, final string must be NULL 6671 6672 Level: intermediate 6673 6674 Notes: 6675 If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored 6676 6677 .keywords: TS, vector, monitor, view 6678 6679 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables(), TSMonitorLGCtxSetVariableNames() 6680 @*/ 6681 PetscErrorCode TSMonitorLGSetVariableNames(TS ts,const char * const *names) 6682 { 6683 PetscErrorCode ierr; 6684 PetscInt i; 6685 6686 PetscFunctionBegin; 6687 for (i=0; i<ts->numbermonitors; i++) { 6688 if (ts->monitor[i] == TSMonitorLGSolution) { 6689 ierr = TSMonitorLGCtxSetVariableNames((TSMonitorLGCtx)ts->monitorcontext[i],names);CHKERRQ(ierr); 6690 break; 6691 } 6692 } 6693 PetscFunctionReturn(0); 6694 } 6695 6696 /*@C 6697 TSMonitorLGCtxSetVariableNames - Sets the name of each component in the solution vector so that it may be displayed in the plot 6698 6699 Collective on TS 6700 6701 Input Parameters: 6702 + ts - the TS context 6703 - names - the names of the components, final string must be NULL 6704 6705 Level: intermediate 6706 6707 .keywords: TS, vector, monitor, view 6708 6709 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables(), TSMonitorLGSetVariableNames() 6710 @*/ 6711 PetscErrorCode TSMonitorLGCtxSetVariableNames(TSMonitorLGCtx ctx,const char * const *names) 6712 { 6713 PetscErrorCode ierr; 6714 6715 PetscFunctionBegin; 6716 ierr = PetscStrArrayDestroy(&ctx->names);CHKERRQ(ierr); 6717 ierr = PetscStrArrayallocpy(names,&ctx->names);CHKERRQ(ierr); 6718 PetscFunctionReturn(0); 6719 } 6720 6721 /*@C 6722 TSMonitorLGGetVariableNames - Gets the name of each component in the solution vector so that it may be displayed in the plot 6723 6724 Collective on TS 6725 6726 Input Parameter: 6727 . ts - the TS context 6728 6729 Output Parameter: 6730 . names - the names of the components, final string must be NULL 6731 6732 Level: intermediate 6733 6734 Notes: 6735 If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored 6736 6737 .keywords: TS, vector, monitor, view 6738 6739 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables() 6740 @*/ 6741 PetscErrorCode TSMonitorLGGetVariableNames(TS ts,const char *const **names) 6742 { 6743 PetscInt i; 6744 6745 PetscFunctionBegin; 6746 *names = NULL; 6747 for (i=0; i<ts->numbermonitors; i++) { 6748 if (ts->monitor[i] == TSMonitorLGSolution) { 6749 TSMonitorLGCtx ctx = (TSMonitorLGCtx) ts->monitorcontext[i]; 6750 *names = (const char *const *)ctx->names; 6751 break; 6752 } 6753 } 6754 PetscFunctionReturn(0); 6755 } 6756 6757 /*@C 6758 TSMonitorLGCtxSetDisplayVariables - Sets the variables that are to be display in the monitor 6759 6760 Collective on TS 6761 6762 Input Parameters: 6763 + ctx - the TSMonitorLG context 6764 . displaynames - the names of the components, final string must be NULL 6765 6766 Level: intermediate 6767 6768 .keywords: TS, vector, monitor, view 6769 6770 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames() 6771 @*/ 6772 PetscErrorCode TSMonitorLGCtxSetDisplayVariables(TSMonitorLGCtx ctx,const char * const *displaynames) 6773 { 6774 PetscInt j = 0,k; 6775 PetscErrorCode ierr; 6776 6777 PetscFunctionBegin; 6778 if (!ctx->names) PetscFunctionReturn(0); 6779 ierr = PetscStrArrayDestroy(&ctx->displaynames);CHKERRQ(ierr); 6780 ierr = PetscStrArrayallocpy(displaynames,&ctx->displaynames);CHKERRQ(ierr); 6781 while (displaynames[j]) j++; 6782 ctx->ndisplayvariables = j; 6783 ierr = PetscMalloc1(ctx->ndisplayvariables,&ctx->displayvariables);CHKERRQ(ierr); 6784 ierr = PetscMalloc1(ctx->ndisplayvariables,&ctx->displayvalues);CHKERRQ(ierr); 6785 j = 0; 6786 while (displaynames[j]) { 6787 k = 0; 6788 while (ctx->names[k]) { 6789 PetscBool flg; 6790 ierr = PetscStrcmp(displaynames[j],ctx->names[k],&flg);CHKERRQ(ierr); 6791 if (flg) { 6792 ctx->displayvariables[j] = k; 6793 break; 6794 } 6795 k++; 6796 } 6797 j++; 6798 } 6799 PetscFunctionReturn(0); 6800 } 6801 6802 /*@C 6803 TSMonitorLGSetDisplayVariables - Sets the variables that are to be display in the monitor 6804 6805 Collective on TS 6806 6807 Input Parameters: 6808 + ts - the TS context 6809 . displaynames - the names of the components, final string must be NULL 6810 6811 Notes: 6812 If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored 6813 6814 Level: intermediate 6815 6816 .keywords: TS, vector, monitor, view 6817 6818 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames() 6819 @*/ 6820 PetscErrorCode TSMonitorLGSetDisplayVariables(TS ts,const char * const *displaynames) 6821 { 6822 PetscInt i; 6823 PetscErrorCode ierr; 6824 6825 PetscFunctionBegin; 6826 for (i=0; i<ts->numbermonitors; i++) { 6827 if (ts->monitor[i] == TSMonitorLGSolution) { 6828 ierr = TSMonitorLGCtxSetDisplayVariables((TSMonitorLGCtx)ts->monitorcontext[i],displaynames);CHKERRQ(ierr); 6829 break; 6830 } 6831 } 6832 PetscFunctionReturn(0); 6833 } 6834 6835 /*@C 6836 TSMonitorLGSetTransform - Solution vector will be transformed by provided function before being displayed 6837 6838 Collective on TS 6839 6840 Input Parameters: 6841 + ts - the TS context 6842 . transform - the transform function 6843 . destroy - function to destroy the optional context 6844 - ctx - optional context used by transform function 6845 6846 Notes: 6847 If the TS object does not have a TSMonitorLGCtx associated with it then this function is ignored 6848 6849 Level: intermediate 6850 6851 .keywords: TS, vector, monitor, view 6852 6853 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames(), TSMonitorLGCtxSetTransform() 6854 @*/ 6855 PetscErrorCode TSMonitorLGSetTransform(TS ts,PetscErrorCode (*transform)(void*,Vec,Vec*),PetscErrorCode (*destroy)(void*),void *tctx) 6856 { 6857 PetscInt i; 6858 PetscErrorCode ierr; 6859 6860 PetscFunctionBegin; 6861 for (i=0; i<ts->numbermonitors; i++) { 6862 if (ts->monitor[i] == TSMonitorLGSolution) { 6863 ierr = TSMonitorLGCtxSetTransform((TSMonitorLGCtx)ts->monitorcontext[i],transform,destroy,tctx);CHKERRQ(ierr); 6864 } 6865 } 6866 PetscFunctionReturn(0); 6867 } 6868 6869 /*@C 6870 TSMonitorLGCtxSetTransform - Solution vector will be transformed by provided function before being displayed 6871 6872 Collective on TSLGCtx 6873 6874 Input Parameters: 6875 + ts - the TS context 6876 . transform - the transform function 6877 . destroy - function to destroy the optional context 6878 - ctx - optional context used by transform function 6879 6880 Level: intermediate 6881 6882 .keywords: TS, vector, monitor, view 6883 6884 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames(), TSMonitorLGSetTransform() 6885 @*/ 6886 PetscErrorCode TSMonitorLGCtxSetTransform(TSMonitorLGCtx ctx,PetscErrorCode (*transform)(void*,Vec,Vec*),PetscErrorCode (*destroy)(void*),void *tctx) 6887 { 6888 PetscFunctionBegin; 6889 ctx->transform = transform; 6890 ctx->transformdestroy = destroy; 6891 ctx->transformctx = tctx; 6892 PetscFunctionReturn(0); 6893 } 6894 6895 /*@C 6896 TSMonitorLGError - Monitors progress of the TS solvers by plotting each component of the error 6897 in a time based line graph 6898 6899 Collective on TS 6900 6901 Input Parameters: 6902 + ts - the TS context 6903 . step - current time-step 6904 . ptime - current time 6905 . u - current solution 6906 - dctx - TSMonitorLGCtx object created with TSMonitorLGCtxCreate() 6907 6908 Level: intermediate 6909 6910 Notes: 6911 Each process in a parallel run displays its component errors in a separate window 6912 6913 The user must provide the solution using TSSetSolutionFunction() to use this monitor. 6914 6915 Options Database Keys: 6916 . -ts_monitor_lg_error - create a graphical monitor of error history 6917 6918 .keywords: TS, vector, monitor, view 6919 6920 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSSetSolutionFunction() 6921 @*/ 6922 PetscErrorCode TSMonitorLGError(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 6923 { 6924 PetscErrorCode ierr; 6925 TSMonitorLGCtx ctx = (TSMonitorLGCtx)dummy; 6926 const PetscScalar *yy; 6927 Vec y; 6928 6929 PetscFunctionBegin; 6930 if (!step) { 6931 PetscDrawAxis axis; 6932 PetscInt dim; 6933 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 6934 ierr = PetscDrawAxisSetLabels(axis,"Error in solution as function of time","Time","Error");CHKERRQ(ierr); 6935 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 6936 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 6937 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 6938 } 6939 ierr = VecDuplicate(u,&y);CHKERRQ(ierr); 6940 ierr = TSComputeSolutionFunction(ts,ptime,y);CHKERRQ(ierr); 6941 ierr = VecAXPY(y,-1.0,u);CHKERRQ(ierr); 6942 ierr = VecGetArrayRead(y,&yy);CHKERRQ(ierr); 6943 #if defined(PETSC_USE_COMPLEX) 6944 { 6945 PetscReal *yreal; 6946 PetscInt i,n; 6947 ierr = VecGetLocalSize(y,&n);CHKERRQ(ierr); 6948 ierr = PetscMalloc1(n,&yreal);CHKERRQ(ierr); 6949 for (i=0; i<n; i++) yreal[i] = PetscRealPart(yy[i]); 6950 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yreal);CHKERRQ(ierr); 6951 ierr = PetscFree(yreal);CHKERRQ(ierr); 6952 } 6953 #else 6954 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yy);CHKERRQ(ierr); 6955 #endif 6956 ierr = VecRestoreArrayRead(y,&yy);CHKERRQ(ierr); 6957 ierr = VecDestroy(&y);CHKERRQ(ierr); 6958 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 6959 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 6960 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 6961 } 6962 PetscFunctionReturn(0); 6963 } 6964 6965 /*@C 6966 TSMonitorSPSwarmSolution - Graphically displays phase plots of DMSwarm particles on a scatter plot 6967 6968 Input Parameters: 6969 + ts - the TS context 6970 . step - current time-step 6971 . ptime - current time 6972 . u - current solution 6973 - dctx - the TSMonitorSPCtx object that contains all the options for the monitoring, this is created with TSMonitorSPCtxCreate() 6974 6975 Options Database: 6976 . -ts_monitor_sp_swarm 6977 6978 Level: intermediate 6979 6980 .keywords: TS, vector, monitor, view, swarm 6981 @*/ 6982 PetscErrorCode TSMonitorSPSwarmSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dctx) 6983 { 6984 PetscErrorCode ierr; 6985 TSMonitorSPCtx ctx = (TSMonitorSPCtx)dctx; 6986 const PetscScalar *yy; 6987 PetscReal *y,*x; 6988 PetscInt Np, p, dim=2; 6989 DM dm; 6990 6991 PetscFunctionBegin; 6992 6993 if (step < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */ 6994 if (!step) { 6995 PetscDrawAxis axis; 6996 ierr = PetscDrawSPGetAxis(ctx->sp,&axis);CHKERRQ(ierr); 6997 ierr = PetscDrawAxisSetLabels(axis,"Particles","X","Y");CHKERRQ(ierr); 6998 ierr = PetscDrawAxisSetLimits(axis, -5, 5, -5, 5);CHKERRQ(ierr); 6999 ierr = PetscDrawAxisSetHoldLimits(axis, PETSC_TRUE);CHKERRQ(ierr); 7000 ierr = TSGetDM(ts, &dm);CHKERRQ(ierr); 7001 ierr = DMGetDimension(dm, &dim); 7002 if(dim!=2) SETERRQ(PETSC_COMM_SELF, ierr, "Dimensions improper for monitor arguments! Current support: two dimensions.");CHKERRQ(ierr); 7003 ierr = VecGetLocalSize(u, &Np);CHKERRQ(ierr); 7004 Np /= 2*dim; 7005 ierr = PetscDrawSPSetDimension(ctx->sp, Np);CHKERRQ(ierr); 7006 ierr = PetscDrawSPReset(ctx->sp);CHKERRQ(ierr); 7007 } 7008 7009 ierr = VecGetLocalSize(u, &Np);CHKERRQ(ierr); 7010 Np /= 2*dim; 7011 ierr = VecGetArrayRead(u,&yy);CHKERRQ(ierr); 7012 ierr = PetscMalloc2(Np, &x, Np, &y);CHKERRQ(ierr); 7013 /* get points from solution vector */ 7014 for (p=0; p<Np; ++p){ 7015 x[p] = PetscRealPart(yy[2*dim*p]); 7016 y[p] = PetscRealPart(yy[2*dim*p+1]); 7017 } 7018 ierr = VecRestoreArrayRead(u,&yy);CHKERRQ(ierr); 7019 7020 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 7021 ierr = PetscDrawSPAddPoint(ctx->sp,x,y);CHKERRQ(ierr); 7022 ierr = PetscDrawSPDraw(ctx->sp,PETSC_FALSE);CHKERRQ(ierr); 7023 ierr = PetscDrawSPSave(ctx->sp);CHKERRQ(ierr); 7024 } 7025 7026 ierr = PetscFree2(x, y);CHKERRQ(ierr); 7027 7028 PetscFunctionReturn(0); 7029 } 7030 7031 7032 7033 /*@C 7034 TSMonitorError - Monitors progress of the TS solvers by printing the 2 norm of the error at each timestep 7035 7036 Collective on TS 7037 7038 Input Parameters: 7039 + ts - the TS context 7040 . step - current time-step 7041 . ptime - current time 7042 . u - current solution 7043 - dctx - unused context 7044 7045 Level: intermediate 7046 7047 The user must provide the solution using TSSetSolutionFunction() to use this monitor. 7048 7049 Options Database Keys: 7050 . -ts_monitor_error - create a graphical monitor of error history 7051 7052 .keywords: TS, vector, monitor, view 7053 7054 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSSetSolutionFunction() 7055 @*/ 7056 PetscErrorCode TSMonitorError(TS ts,PetscInt step,PetscReal ptime,Vec u,PetscViewerAndFormat *vf) 7057 { 7058 PetscErrorCode ierr; 7059 Vec y; 7060 PetscReal nrm; 7061 PetscBool flg; 7062 7063 PetscFunctionBegin; 7064 ierr = VecDuplicate(u,&y);CHKERRQ(ierr); 7065 ierr = TSComputeSolutionFunction(ts,ptime,y);CHKERRQ(ierr); 7066 ierr = VecAXPY(y,-1.0,u);CHKERRQ(ierr); 7067 ierr = PetscObjectTypeCompare((PetscObject)vf->viewer,PETSCVIEWERASCII,&flg);CHKERRQ(ierr); 7068 if (flg) { 7069 ierr = VecNorm(y,NORM_2,&nrm);CHKERRQ(ierr); 7070 ierr = PetscViewerASCIIPrintf(vf->viewer,"2-norm of error %g\n",(double)nrm);CHKERRQ(ierr); 7071 } 7072 ierr = PetscObjectTypeCompare((PetscObject)vf->viewer,PETSCVIEWERDRAW,&flg);CHKERRQ(ierr); 7073 if (flg) { 7074 ierr = VecView(y,vf->viewer);CHKERRQ(ierr); 7075 } 7076 ierr = VecDestroy(&y);CHKERRQ(ierr); 7077 PetscFunctionReturn(0); 7078 } 7079 7080 PetscErrorCode TSMonitorLGSNESIterations(TS ts,PetscInt n,PetscReal ptime,Vec v,void *monctx) 7081 { 7082 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 7083 PetscReal x = ptime,y; 7084 PetscErrorCode ierr; 7085 PetscInt its; 7086 7087 PetscFunctionBegin; 7088 if (n < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */ 7089 if (!n) { 7090 PetscDrawAxis axis; 7091 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 7092 ierr = PetscDrawAxisSetLabels(axis,"Nonlinear iterations as function of time","Time","SNES Iterations");CHKERRQ(ierr); 7093 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 7094 ctx->snes_its = 0; 7095 } 7096 ierr = TSGetSNESIterations(ts,&its);CHKERRQ(ierr); 7097 y = its - ctx->snes_its; 7098 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 7099 if (((ctx->howoften > 0) && (!(n % ctx->howoften)) && (n > -1)) || ((ctx->howoften == -1) && (n == -1))) { 7100 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 7101 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 7102 } 7103 ctx->snes_its = its; 7104 PetscFunctionReturn(0); 7105 } 7106 7107 PetscErrorCode TSMonitorLGKSPIterations(TS ts,PetscInt n,PetscReal ptime,Vec v,void *monctx) 7108 { 7109 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 7110 PetscReal x = ptime,y; 7111 PetscErrorCode ierr; 7112 PetscInt its; 7113 7114 PetscFunctionBegin; 7115 if (n < 0) PetscFunctionReturn(0); /* -1 indicates interpolated solution */ 7116 if (!n) { 7117 PetscDrawAxis axis; 7118 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 7119 ierr = PetscDrawAxisSetLabels(axis,"Linear iterations as function of time","Time","KSP Iterations");CHKERRQ(ierr); 7120 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 7121 ctx->ksp_its = 0; 7122 } 7123 ierr = TSGetKSPIterations(ts,&its);CHKERRQ(ierr); 7124 y = its - ctx->ksp_its; 7125 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 7126 if (((ctx->howoften > 0) && (!(n % ctx->howoften)) && (n > -1)) || ((ctx->howoften == -1) && (n == -1))) { 7127 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 7128 ierr = PetscDrawLGSave(ctx->lg);CHKERRQ(ierr); 7129 } 7130 ctx->ksp_its = its; 7131 PetscFunctionReturn(0); 7132 } 7133 7134 /*@ 7135 TSComputeLinearStability - computes the linear stability function at a point 7136 7137 Collective on TS and Vec 7138 7139 Input Parameters: 7140 + ts - the TS context 7141 - xr,xi - real and imaginary part of input arguments 7142 7143 Output Parameters: 7144 . yr,yi - real and imaginary part of function value 7145 7146 Level: developer 7147 7148 .keywords: TS, compute 7149 7150 .seealso: TSSetRHSFunction(), TSComputeIFunction() 7151 @*/ 7152 PetscErrorCode TSComputeLinearStability(TS ts,PetscReal xr,PetscReal xi,PetscReal *yr,PetscReal *yi) 7153 { 7154 PetscErrorCode ierr; 7155 7156 PetscFunctionBegin; 7157 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 7158 if (!ts->ops->linearstability) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Linearized stability function not provided for this method"); 7159 ierr = (*ts->ops->linearstability)(ts,xr,xi,yr,yi);CHKERRQ(ierr); 7160 PetscFunctionReturn(0); 7161 } 7162 7163 /* ------------------------------------------------------------------------*/ 7164 /*@C 7165 TSMonitorEnvelopeCtxCreate - Creates a context for use with TSMonitorEnvelope() 7166 7167 Collective on TS 7168 7169 Input Parameters: 7170 . ts - the ODE solver object 7171 7172 Output Parameter: 7173 . ctx - the context 7174 7175 Level: intermediate 7176 7177 .keywords: TS, monitor, line graph, residual, seealso 7178 7179 .seealso: TSMonitorLGTimeStep(), TSMonitorSet(), TSMonitorLGSolution(), TSMonitorLGError() 7180 7181 @*/ 7182 PetscErrorCode TSMonitorEnvelopeCtxCreate(TS ts,TSMonitorEnvelopeCtx *ctx) 7183 { 7184 PetscErrorCode ierr; 7185 7186 PetscFunctionBegin; 7187 ierr = PetscNew(ctx);CHKERRQ(ierr); 7188 PetscFunctionReturn(0); 7189 } 7190 7191 /*@C 7192 TSMonitorEnvelope - Monitors the maximum and minimum value of each component of the solution 7193 7194 Collective on TS 7195 7196 Input Parameters: 7197 + ts - the TS context 7198 . step - current time-step 7199 . ptime - current time 7200 . u - current solution 7201 - dctx - the envelope context 7202 7203 Options Database: 7204 . -ts_monitor_envelope 7205 7206 Level: intermediate 7207 7208 Notes: 7209 after a solve you can use TSMonitorEnvelopeGetBounds() to access the envelope 7210 7211 .keywords: TS, vector, monitor, view 7212 7213 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorEnvelopeGetBounds(), TSMonitorEnvelopeCtxCreate() 7214 @*/ 7215 PetscErrorCode TSMonitorEnvelope(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dctx) 7216 { 7217 PetscErrorCode ierr; 7218 TSMonitorEnvelopeCtx ctx = (TSMonitorEnvelopeCtx)dctx; 7219 7220 PetscFunctionBegin; 7221 if (!ctx->max) { 7222 ierr = VecDuplicate(u,&ctx->max);CHKERRQ(ierr); 7223 ierr = VecDuplicate(u,&ctx->min);CHKERRQ(ierr); 7224 ierr = VecCopy(u,ctx->max);CHKERRQ(ierr); 7225 ierr = VecCopy(u,ctx->min);CHKERRQ(ierr); 7226 } else { 7227 ierr = VecPointwiseMax(ctx->max,u,ctx->max);CHKERRQ(ierr); 7228 ierr = VecPointwiseMin(ctx->min,u,ctx->min);CHKERRQ(ierr); 7229 } 7230 PetscFunctionReturn(0); 7231 } 7232 7233 /*@C 7234 TSMonitorEnvelopeGetBounds - Gets the bounds for the components of the solution 7235 7236 Collective on TS 7237 7238 Input Parameter: 7239 . ts - the TS context 7240 7241 Output Parameter: 7242 + max - the maximum values 7243 - min - the minimum values 7244 7245 Notes: 7246 If the TS does not have a TSMonitorEnvelopeCtx associated with it then this function is ignored 7247 7248 Level: intermediate 7249 7250 .keywords: TS, vector, monitor, view 7251 7252 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables() 7253 @*/ 7254 PetscErrorCode TSMonitorEnvelopeGetBounds(TS ts,Vec *max,Vec *min) 7255 { 7256 PetscInt i; 7257 7258 PetscFunctionBegin; 7259 if (max) *max = NULL; 7260 if (min) *min = NULL; 7261 for (i=0; i<ts->numbermonitors; i++) { 7262 if (ts->monitor[i] == TSMonitorEnvelope) { 7263 TSMonitorEnvelopeCtx ctx = (TSMonitorEnvelopeCtx) ts->monitorcontext[i]; 7264 if (max) *max = ctx->max; 7265 if (min) *min = ctx->min; 7266 break; 7267 } 7268 } 7269 PetscFunctionReturn(0); 7270 } 7271 7272 /*@C 7273 TSMonitorEnvelopeCtxDestroy - Destroys a context that was created with TSMonitorEnvelopeCtxCreate(). 7274 7275 Collective on TSMonitorEnvelopeCtx 7276 7277 Input Parameter: 7278 . ctx - the monitor context 7279 7280 Level: intermediate 7281 7282 .keywords: TS, monitor, line graph, destroy 7283 7284 .seealso: TSMonitorLGCtxCreate(), TSMonitorSet(), TSMonitorLGTimeStep() 7285 @*/ 7286 PetscErrorCode TSMonitorEnvelopeCtxDestroy(TSMonitorEnvelopeCtx *ctx) 7287 { 7288 PetscErrorCode ierr; 7289 7290 PetscFunctionBegin; 7291 ierr = VecDestroy(&(*ctx)->min);CHKERRQ(ierr); 7292 ierr = VecDestroy(&(*ctx)->max);CHKERRQ(ierr); 7293 ierr = PetscFree(*ctx);CHKERRQ(ierr); 7294 PetscFunctionReturn(0); 7295 } 7296 7297 /*@ 7298 TSRestartStep - Flags the solver to restart the next step 7299 7300 Collective on TS 7301 7302 Input Parameter: 7303 . ts - the TS context obtained from TSCreate() 7304 7305 Level: advanced 7306 7307 Notes: 7308 Multistep methods like BDF or Runge-Kutta methods with FSAL property require restarting the solver in the event of 7309 discontinuities. These discontinuities may be introduced as a consequence of explicitly modifications to the solution 7310 vector (which PETSc attempts to detect and handle) or problem coefficients (which PETSc is not able to detect). For 7311 the sake of correctness and maximum safety, users are expected to call TSRestart() whenever they introduce 7312 discontinuities in callback routines (e.g. prestep and poststep routines, or implicit/rhs function routines with 7313 discontinuous source terms). 7314 7315 .keywords: TS, timestep, restart 7316 7317 .seealso: TSSolve(), TSSetPreStep(), TSSetPostStep() 7318 @*/ 7319 PetscErrorCode TSRestartStep(TS ts) 7320 { 7321 PetscFunctionBegin; 7322 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 7323 ts->steprestart = PETSC_TRUE; 7324 PetscFunctionReturn(0); 7325 } 7326 7327 /*@ 7328 TSRollBack - Rolls back one time step 7329 7330 Collective on TS 7331 7332 Input Parameter: 7333 . ts - the TS context obtained from TSCreate() 7334 7335 Level: advanced 7336 7337 .keywords: TS, timestep, rollback 7338 7339 .seealso: TSCreate(), TSSetUp(), TSDestroy(), TSSolve(), TSSetPreStep(), TSSetPreStage(), TSInterpolate() 7340 @*/ 7341 PetscErrorCode TSRollBack(TS ts) 7342 { 7343 PetscErrorCode ierr; 7344 7345 PetscFunctionBegin; 7346 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 7347 if (ts->steprollback) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"TSRollBack already called"); 7348 if (!ts->ops->rollback) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSRollBack not implemented for type '%s'",((PetscObject)ts)->type_name); 7349 ierr = (*ts->ops->rollback)(ts);CHKERRQ(ierr); 7350 ts->time_step = ts->ptime - ts->ptime_prev; 7351 ts->ptime = ts->ptime_prev; 7352 ts->ptime_prev = ts->ptime_prev_rollback; 7353 ts->steps--; 7354 ts->steprollback = PETSC_TRUE; 7355 PetscFunctionReturn(0); 7356 } 7357 7358 /*@ 7359 TSGetStages - Get the number of stages and stage values 7360 7361 Input Parameter: 7362 . ts - the TS context obtained from TSCreate() 7363 7364 Output Parameters: 7365 + ns - the number of stages 7366 - Y - the current stage vectors 7367 7368 Level: advanced 7369 7370 Notes: Both ns and Y can be NULL. 7371 7372 .keywords: TS, getstages 7373 7374 .seealso: TSCreate() 7375 @*/ 7376 PetscErrorCode TSGetStages(TS ts,PetscInt *ns,Vec **Y) 7377 { 7378 PetscErrorCode ierr; 7379 7380 PetscFunctionBegin; 7381 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 7382 if (ns) PetscValidPointer(ns,2); 7383 if (Y) PetscValidPointer(Y,3); 7384 if (!ts->ops->getstages) { 7385 if (ns) *ns = 0; 7386 if (Y) *Y = NULL; 7387 } else { 7388 ierr = (*ts->ops->getstages)(ts,ns,Y);CHKERRQ(ierr); 7389 } 7390 PetscFunctionReturn(0); 7391 } 7392 7393 /*@C 7394 TSComputeIJacobianDefaultColor - Computes the Jacobian using finite differences and coloring to exploit matrix sparsity. 7395 7396 Collective on SNES 7397 7398 Input Parameters: 7399 + ts - the TS context 7400 . t - current timestep 7401 . U - state vector 7402 . Udot - time derivative of state vector 7403 . shift - shift to apply, see note below 7404 - ctx - an optional user context 7405 7406 Output Parameters: 7407 + J - Jacobian matrix (not altered in this routine) 7408 - B - newly computed Jacobian matrix to use with preconditioner (generally the same as J) 7409 7410 Level: intermediate 7411 7412 Notes: 7413 If F(t,U,Udot)=0 is the DAE, the required Jacobian is 7414 7415 dF/dU + shift*dF/dUdot 7416 7417 Most users should not need to explicitly call this routine, as it 7418 is used internally within the nonlinear solvers. 7419 7420 This will first try to get the coloring from the DM. If the DM type has no coloring 7421 routine, then it will try to get the coloring from the matrix. This requires that the 7422 matrix have nonzero entries precomputed. 7423 7424 .keywords: TS, finite differences, Jacobian, coloring, sparse 7425 .seealso: TSSetIJacobian(), MatFDColoringCreate(), MatFDColoringSetFunction() 7426 @*/ 7427 PetscErrorCode TSComputeIJacobianDefaultColor(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat J,Mat B,void *ctx) 7428 { 7429 SNES snes; 7430 MatFDColoring color; 7431 PetscBool hascolor, matcolor = PETSC_FALSE; 7432 PetscErrorCode ierr; 7433 7434 PetscFunctionBegin; 7435 ierr = PetscOptionsGetBool(((PetscObject)ts)->options,((PetscObject) ts)->prefix, "-ts_fd_color_use_mat", &matcolor, NULL);CHKERRQ(ierr); 7436 ierr = PetscObjectQuery((PetscObject) B, "TSMatFDColoring", (PetscObject *) &color);CHKERRQ(ierr); 7437 if (!color) { 7438 DM dm; 7439 ISColoring iscoloring; 7440 7441 ierr = TSGetDM(ts, &dm);CHKERRQ(ierr); 7442 ierr = DMHasColoring(dm, &hascolor);CHKERRQ(ierr); 7443 if (hascolor && !matcolor) { 7444 ierr = DMCreateColoring(dm, IS_COLORING_GLOBAL, &iscoloring);CHKERRQ(ierr); 7445 ierr = MatFDColoringCreate(B, iscoloring, &color);CHKERRQ(ierr); 7446 ierr = MatFDColoringSetFunction(color, (PetscErrorCode (*)(void)) SNESTSFormFunction, (void *) ts);CHKERRQ(ierr); 7447 ierr = MatFDColoringSetFromOptions(color);CHKERRQ(ierr); 7448 ierr = MatFDColoringSetUp(B, iscoloring, color);CHKERRQ(ierr); 7449 ierr = ISColoringDestroy(&iscoloring);CHKERRQ(ierr); 7450 } else { 7451 MatColoring mc; 7452 7453 ierr = MatColoringCreate(B, &mc);CHKERRQ(ierr); 7454 ierr = MatColoringSetDistance(mc, 2);CHKERRQ(ierr); 7455 ierr = MatColoringSetType(mc, MATCOLORINGSL);CHKERRQ(ierr); 7456 ierr = MatColoringSetFromOptions(mc);CHKERRQ(ierr); 7457 ierr = MatColoringApply(mc, &iscoloring);CHKERRQ(ierr); 7458 ierr = MatColoringDestroy(&mc);CHKERRQ(ierr); 7459 ierr = MatFDColoringCreate(B, iscoloring, &color);CHKERRQ(ierr); 7460 ierr = MatFDColoringSetFunction(color, (PetscErrorCode (*)(void)) SNESTSFormFunction, (void *) ts);CHKERRQ(ierr); 7461 ierr = MatFDColoringSetFromOptions(color);CHKERRQ(ierr); 7462 ierr = MatFDColoringSetUp(B, iscoloring, color);CHKERRQ(ierr); 7463 ierr = ISColoringDestroy(&iscoloring);CHKERRQ(ierr); 7464 } 7465 ierr = PetscObjectCompose((PetscObject) B, "TSMatFDColoring", (PetscObject) color);CHKERRQ(ierr); 7466 ierr = PetscObjectDereference((PetscObject) color);CHKERRQ(ierr); 7467 } 7468 ierr = TSGetSNES(ts, &snes);CHKERRQ(ierr); 7469 ierr = MatFDColoringApply(B, color, U, snes);CHKERRQ(ierr); 7470 if (J != B) { 7471 ierr = MatAssemblyBegin(J, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 7472 ierr = MatAssemblyEnd(J, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 7473 } 7474 PetscFunctionReturn(0); 7475 } 7476 7477 /*@ 7478 TSSetFunctionDomainError - Set the function testing if the current state vector is valid 7479 7480 Input Parameters: 7481 ts - the TS context 7482 func - function called within TSFunctionDomainError 7483 7484 Level: intermediate 7485 7486 .keywords: TS, state, domain 7487 .seealso: TSAdaptCheckStage(), TSFunctionDomainError() 7488 @*/ 7489 7490 PetscErrorCode TSSetFunctionDomainError(TS ts, PetscErrorCode (*func)(TS,PetscReal,Vec,PetscBool*)) 7491 { 7492 PetscFunctionBegin; 7493 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 7494 ts->functiondomainerror = func; 7495 PetscFunctionReturn(0); 7496 } 7497 7498 /*@ 7499 TSFunctionDomainError - Check if the current state is valid 7500 7501 Input Parameters: 7502 ts - the TS context 7503 stagetime - time of the simulation 7504 Y - state vector to check. 7505 7506 Output Parameter: 7507 accept - Set to PETSC_FALSE if the current state vector is valid. 7508 7509 Note: 7510 This function should be used to ensure the state is in a valid part of the space. 7511 For example, one can ensure here all values are positive. 7512 7513 Level: advanced 7514 @*/ 7515 PetscErrorCode TSFunctionDomainError(TS ts,PetscReal stagetime,Vec Y,PetscBool* accept) 7516 { 7517 PetscFunctionBegin; 7518 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 7519 *accept = PETSC_TRUE; 7520 if (ts->functiondomainerror) { 7521 PetscStackCallStandard((*ts->functiondomainerror),(ts,stagetime,Y,accept)); 7522 } 7523 PetscFunctionReturn(0); 7524 } 7525 7526 /*@C 7527 TSClone - This function clones a time step object. 7528 7529 Collective on MPI_Comm 7530 7531 Input Parameter: 7532 . tsin - The input TS 7533 7534 Output Parameter: 7535 . tsout - The output TS (cloned) 7536 7537 Notes: 7538 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. 7539 7540 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); TSSetSNES(ts,snes_dup); 7541 7542 Level: developer 7543 7544 .keywords: TS, clone 7545 .seealso: TSCreate(), TSSetType(), TSSetUp(), TSDestroy(), TSSetProblemType() 7546 @*/ 7547 PetscErrorCode TSClone(TS tsin, TS *tsout) 7548 { 7549 TS t; 7550 PetscErrorCode ierr; 7551 SNES snes_start; 7552 DM dm; 7553 TSType type; 7554 7555 PetscFunctionBegin; 7556 PetscValidPointer(tsin,1); 7557 *tsout = NULL; 7558 7559 ierr = PetscHeaderCreate(t, TS_CLASSID, "TS", "Time stepping", "TS", PetscObjectComm((PetscObject)tsin), TSDestroy, TSView);CHKERRQ(ierr); 7560 7561 /* General TS description */ 7562 t->numbermonitors = 0; 7563 t->setupcalled = 0; 7564 t->ksp_its = 0; 7565 t->snes_its = 0; 7566 t->nwork = 0; 7567 t->rhsjacobian.time = -1e20; 7568 t->rhsjacobian.scale = 1.; 7569 t->ijacobian.shift = 1.; 7570 7571 ierr = TSGetSNES(tsin,&snes_start);CHKERRQ(ierr); 7572 ierr = TSSetSNES(t,snes_start);CHKERRQ(ierr); 7573 7574 ierr = TSGetDM(tsin,&dm);CHKERRQ(ierr); 7575 ierr = TSSetDM(t,dm);CHKERRQ(ierr); 7576 7577 t->adapt = tsin->adapt; 7578 ierr = PetscObjectReference((PetscObject)t->adapt);CHKERRQ(ierr); 7579 7580 t->trajectory = tsin->trajectory; 7581 ierr = PetscObjectReference((PetscObject)t->trajectory);CHKERRQ(ierr); 7582 7583 t->event = tsin->event; 7584 if (t->event) t->event->refct++; 7585 7586 t->problem_type = tsin->problem_type; 7587 t->ptime = tsin->ptime; 7588 t->ptime_prev = tsin->ptime_prev; 7589 t->time_step = tsin->time_step; 7590 t->max_time = tsin->max_time; 7591 t->steps = tsin->steps; 7592 t->max_steps = tsin->max_steps; 7593 t->equation_type = tsin->equation_type; 7594 t->atol = tsin->atol; 7595 t->rtol = tsin->rtol; 7596 t->max_snes_failures = tsin->max_snes_failures; 7597 t->max_reject = tsin->max_reject; 7598 t->errorifstepfailed = tsin->errorifstepfailed; 7599 7600 ierr = TSGetType(tsin,&type);CHKERRQ(ierr); 7601 ierr = TSSetType(t,type);CHKERRQ(ierr); 7602 7603 t->vec_sol = NULL; 7604 7605 t->cfltime = tsin->cfltime; 7606 t->cfltime_local = tsin->cfltime_local; 7607 t->exact_final_time = tsin->exact_final_time; 7608 7609 ierr = PetscMemcpy(t->ops,tsin->ops,sizeof(struct _TSOps));CHKERRQ(ierr); 7610 7611 if (((PetscObject)tsin)->fortran_func_pointers) { 7612 PetscInt i; 7613 ierr = PetscMalloc((10)*sizeof(void(*)(void)),&((PetscObject)t)->fortran_func_pointers);CHKERRQ(ierr); 7614 for (i=0; i<10; i++) { 7615 ((PetscObject)t)->fortran_func_pointers[i] = ((PetscObject)tsin)->fortran_func_pointers[i]; 7616 } 7617 } 7618 *tsout = t; 7619 PetscFunctionReturn(0); 7620 } 7621 7622 static PetscErrorCode RHSWrapperFunction_TSRHSJacobianTest(void* ctx,Vec x,Vec y) 7623 { 7624 PetscErrorCode ierr; 7625 TS ts = (TS) ctx; 7626 7627 PetscFunctionBegin; 7628 ierr = TSComputeRHSFunction(ts,0,x,y);CHKERRQ(ierr); 7629 PetscFunctionReturn(0); 7630 } 7631 7632 /*@ 7633 TSRHSJacobianTest - Compares the multiply routine provided to the MATSHELL with differencing on the TS given RHS function. 7634 7635 Logically Collective on TS and Mat 7636 7637 Input Parameters: 7638 TS - the time stepping routine 7639 7640 Output Parameter: 7641 . flg - PETSC_TRUE if the multiply is likely correct 7642 7643 Options Database: 7644 . -ts_rhs_jacobian_test_mult -mat_shell_test_mult_view - run the test at each timestep of the integrator 7645 7646 Level: advanced 7647 7648 Notes: 7649 This only works for problems defined only the RHS function and Jacobian NOT IFunction and IJacobian 7650 7651 .seealso: MatCreateShell(), MatShellGetContext(), MatShellGetOperation(), MatShellTestMultTranspose(), TSRHSJacobianTestTranspose() 7652 @*/ 7653 PetscErrorCode TSRHSJacobianTest(TS ts,PetscBool *flg) 7654 { 7655 Mat J,B; 7656 PetscErrorCode ierr; 7657 TSRHSJacobian func; 7658 void* ctx; 7659 7660 PetscFunctionBegin; 7661 ierr = TSGetRHSJacobian(ts,&J,&B,&func,&ctx);CHKERRQ(ierr); 7662 ierr = (*func)(ts,0.0,ts->vec_sol,J,B,ctx);CHKERRQ(ierr); 7663 ierr = MatShellTestMult(J,RHSWrapperFunction_TSRHSJacobianTest,ts->vec_sol,ts,flg);CHKERRQ(ierr); 7664 PetscFunctionReturn(0); 7665 } 7666 7667 /*@C 7668 TSRHSJacobianTestTranspose - Compares the multiply transpose routine provided to the MATSHELL with differencing on the TS given RHS function. 7669 7670 Logically Collective on TS and Mat 7671 7672 Input Parameters: 7673 TS - the time stepping routine 7674 7675 Output Parameter: 7676 . flg - PETSC_TRUE if the multiply is likely correct 7677 7678 Options Database: 7679 . -ts_rhs_jacobian_test_mult_transpose -mat_shell_test_mult_transpose_view - run the test at each timestep of the integrator 7680 7681 Notes: 7682 This only works for problems defined only the RHS function and Jacobian NOT IFunction and IJacobian 7683 7684 Level: advanced 7685 7686 .seealso: MatCreateShell(), MatShellGetContext(), MatShellGetOperation(), MatShellTestMultTranspose(), TSRHSJacobianTest() 7687 @*/ 7688 PetscErrorCode TSRHSJacobianTestTranspose(TS ts,PetscBool *flg) 7689 { 7690 Mat J,B; 7691 PetscErrorCode ierr; 7692 void *ctx; 7693 TSRHSJacobian func; 7694 7695 PetscFunctionBegin; 7696 ierr = TSGetRHSJacobian(ts,&J,&B,&func,&ctx);CHKERRQ(ierr); 7697 ierr = (*func)(ts,0.0,ts->vec_sol,J,B,ctx);CHKERRQ(ierr); 7698 ierr = MatShellTestMultTranspose(J,RHSWrapperFunction_TSRHSJacobianTest,ts->vec_sol,ts,flg);CHKERRQ(ierr); 7699 PetscFunctionReturn(0); 7700 } 7701 7702 /*@ 7703 TSSetUseSplitRHSFunction - Use the split RHSFunction when a multirate method is used. 7704 7705 Logically collective 7706 7707 Input Parameter: 7708 + ts - timestepping context 7709 - use_splitrhsfunction - PETSC_TRUE indicates that the split RHSFunction will be used 7710 7711 Options Database: 7712 . -ts_use_splitrhsfunction - <true,false> 7713 7714 Notes: 7715 This is only useful for multirate methods 7716 7717 Level: intermediate 7718 7719 .seealso: TSGetUseSplitRHSFunction() 7720 @*/ 7721 PetscErrorCode TSSetUseSplitRHSFunction(TS ts, PetscBool use_splitrhsfunction) 7722 { 7723 PetscFunctionBegin; 7724 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 7725 ts->use_splitrhsfunction = use_splitrhsfunction; 7726 PetscFunctionReturn(0); 7727 } 7728 7729 /*@ 7730 TSGetUseSplitRHSFunction - Gets whether to use the split RHSFunction when a multirate method is used. 7731 7732 Not collective 7733 7734 Input Parameter: 7735 . ts - timestepping context 7736 7737 Output Parameter: 7738 . use_splitrhsfunction - PETSC_TRUE indicates that the split RHSFunction will be used 7739 7740 Level: intermediate 7741 7742 .seealso: TSSetUseSplitRHSFunction() 7743 @*/ 7744 PetscErrorCode TSGetUseSplitRHSFunction(TS ts, PetscBool *use_splitrhsfunction) 7745 { 7746 PetscFunctionBegin; 7747 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 7748 *use_splitrhsfunction = ts->use_splitrhsfunction; 7749 PetscFunctionReturn(0); 7750 } 7751