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 #include <petscconvest.h> 7 8 #define SkipSmallValue(a,b,tol) if (PetscAbsScalar(a)< tol || PetscAbsScalar(b)< tol) continue; 9 10 /* Logging support */ 11 PetscClassId TS_CLASSID, DMTS_CLASSID; 12 PetscLogEvent TS_Step, TS_PseudoComputeTimeStep, TS_FunctionEval, TS_JacobianEval; 13 14 const char *const TSExactFinalTimeOptions[] = {"UNSPECIFIED","STEPOVER","INTERPOLATE","MATCHSTEP","TSExactFinalTimeOption","TS_EXACTFINALTIME_",NULL}; 15 16 static PetscErrorCode TSAdaptSetDefaultType(TSAdapt adapt,TSAdaptType default_type) 17 { 18 PetscFunctionBegin; 19 PetscValidHeaderSpecific(adapt,TSADAPT_CLASSID,1); 20 PetscValidCharPointer(default_type,2); 21 if (!((PetscObject)adapt)->type_name) PetscCall(TSAdaptSetType(adapt,default_type)); 22 PetscFunctionReturn(0); 23 } 24 25 /*@ 26 TSSetFromOptions - Sets various TS parameters from user options. 27 28 Collective on TS 29 30 Input Parameter: 31 . ts - the TS context obtained from TSCreate() 32 33 Options Database Keys: 34 + -ts_type <type> - TSEULER, TSBEULER, TSSUNDIALS, TSPSEUDO, TSCN, TSRK, TSTHETA, TSALPHA, TSGLLE, TSSSP, TSGLEE, TSBSYMP, TSIRK 35 . -ts_save_trajectory - checkpoint the solution at each time-step 36 . -ts_max_time <time> - maximum time to compute to 37 . -ts_time_span <t0,...tf> - sets the time span, solutions are computed and stored for each indicated time 38 . -ts_max_steps <steps> - maximum number of time-steps to take 39 . -ts_init_time <time> - initial time to start computation 40 . -ts_final_time <time> - final time to compute to (deprecated: use -ts_max_time) 41 . -ts_dt <dt> - initial time step 42 . -ts_exact_final_time <stepover,interpolate,matchstep> - whether to stop at the exact given final time and how to compute the solution at that time 43 . -ts_max_snes_failures <maxfailures> - Maximum number of nonlinear solve failures allowed 44 . -ts_max_reject <maxrejects> - Maximum number of step rejections before step fails 45 . -ts_error_if_step_fails <true,false> - Error if no step succeeds 46 . -ts_rtol <rtol> - relative tolerance for local truncation error 47 . -ts_atol <atol> - Absolute tolerance for local truncation error 48 . -ts_rhs_jacobian_test_mult -mat_shell_test_mult_view - test the Jacobian at each iteration against finite difference with RHS function 49 . -ts_rhs_jacobian_test_mult_transpose -mat_shell_test_mult_transpose_view - test the Jacobian at each iteration against finite difference with RHS function 50 . -ts_adjoint_solve <yes,no> - After solving the ODE/DAE solve the adjoint problem (requires -ts_save_trajectory) 51 . -ts_fd_color - Use finite differences with coloring to compute IJacobian 52 . -ts_monitor - print information at each timestep 53 . -ts_monitor_cancel - Cancel all monitors 54 . -ts_monitor_lg_solution - Monitor solution graphically 55 . -ts_monitor_lg_error - Monitor error graphically 56 . -ts_monitor_error - Monitors norm of error 57 . -ts_monitor_lg_timestep - Monitor timestep size graphically 58 . -ts_monitor_lg_timestep_log - Monitor log timestep size graphically 59 . -ts_monitor_lg_snes_iterations - Monitor number nonlinear iterations for each timestep graphically 60 . -ts_monitor_lg_ksp_iterations - Monitor number nonlinear iterations for each timestep graphically 61 . -ts_monitor_sp_eig - Monitor eigenvalues of linearized operator graphically 62 . -ts_monitor_draw_solution - Monitor solution graphically 63 . -ts_monitor_draw_solution_phase <xleft,yleft,xright,yright> - Monitor solution graphically with phase diagram, requires problem with exactly 2 degrees of freedom 64 . -ts_monitor_draw_error - Monitor error graphically, requires use to have provided TSSetSolutionFunction() 65 . -ts_monitor_solution [ascii binary draw][:filename][:viewerformat] - monitors the solution at each timestep 66 . -ts_monitor_solution_vtk <filename.vts,filename.vtu> - Save each time step to a binary file, use filename-%%03" PetscInt_FMT ".vts (filename-%%03" PetscInt_FMT ".vtu) 67 - -ts_monitor_envelope - determine maximum and minimum value of each component of the solution over the solution time 68 69 Notes: 70 See SNESSetFromOptions() and KSPSetFromOptions() for how to control the nonlinear and linear solves used by the time-stepper. 71 72 Certain SNES options get reset for each new nonlinear solver, for example -snes_lag_jacobian <its> and -snes_lag_preconditioner <its>, in order 73 to retain them over the multiple nonlinear solves that TS uses you mush also provide -snes_lag_jacobian_persists true and 74 -snes_lag_preconditioner_persists true 75 76 Developer Note: 77 We should unify all the -ts_monitor options in the way that -xxx_view has been unified 78 79 Level: beginner 80 81 .seealso: `TSGetType()` 82 @*/ 83 PetscErrorCode TSSetFromOptions(TS ts) 84 { 85 PetscBool opt,flg,tflg; 86 char monfilename[PETSC_MAX_PATH_LEN]; 87 PetscReal time_step,tspan[100]; 88 PetscInt nt = PETSC_STATIC_ARRAY_LENGTH(tspan); 89 TSExactFinalTimeOption eftopt; 90 char dir[16]; 91 TSIFunction ifun; 92 const char *defaultType; 93 char typeName[256]; 94 95 PetscFunctionBegin; 96 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 97 98 PetscCall(TSRegisterAll()); 99 PetscCall(TSGetIFunction(ts,NULL,&ifun,NULL)); 100 101 PetscObjectOptionsBegin((PetscObject)ts); 102 if (((PetscObject)ts)->type_name) defaultType = ((PetscObject)ts)->type_name; 103 else defaultType = ifun ? TSBEULER : TSEULER; 104 PetscCall(PetscOptionsFList("-ts_type","TS method","TSSetType",TSList,defaultType,typeName,256,&opt)); 105 if (opt) PetscCall(TSSetType(ts,typeName)); 106 else PetscCall(TSSetType(ts,defaultType)); 107 108 /* Handle generic TS options */ 109 PetscCall(PetscOptionsDeprecated("-ts_final_time","-ts_max_time","3.10",NULL)); 110 PetscCall(PetscOptionsReal("-ts_max_time","Maximum time to run to","TSSetMaxTime",ts->max_time,&ts->max_time,NULL)); 111 PetscCall(PetscOptionsRealArray("-ts_time_span","Time span","TSSetTimeSpan",tspan,&nt,&flg)); 112 if (flg) PetscCall(TSSetTimeSpan(ts,nt,tspan)); 113 PetscCall(PetscOptionsInt("-ts_max_steps","Maximum number of time steps","TSSetMaxSteps",ts->max_steps,&ts->max_steps,NULL)); 114 PetscCall(PetscOptionsReal("-ts_init_time","Initial time","TSSetTime",ts->ptime,&ts->ptime,NULL)); 115 PetscCall(PetscOptionsReal("-ts_dt","Initial time step","TSSetTimeStep",ts->time_step,&time_step,&flg)); 116 if (flg) PetscCall(TSSetTimeStep(ts,time_step)); 117 PetscCall(PetscOptionsEnum("-ts_exact_final_time","Option for handling of final time step","TSSetExactFinalTime",TSExactFinalTimeOptions,(PetscEnum)ts->exact_final_time,(PetscEnum*)&eftopt,&flg)); 118 if (flg) PetscCall(TSSetExactFinalTime(ts,eftopt)); 119 PetscCall(PetscOptionsInt("-ts_max_snes_failures","Maximum number of nonlinear solve failures","TSSetMaxSNESFailures",ts->max_snes_failures,&ts->max_snes_failures,NULL)); 120 PetscCall(PetscOptionsInt("-ts_max_reject","Maximum number of step rejections before step fails","TSSetMaxStepRejections",ts->max_reject,&ts->max_reject,NULL)); 121 PetscCall(PetscOptionsBool("-ts_error_if_step_fails","Error if no step succeeds","TSSetErrorIfStepFails",ts->errorifstepfailed,&ts->errorifstepfailed,NULL)); 122 PetscCall(PetscOptionsReal("-ts_rtol","Relative tolerance for local truncation error","TSSetTolerances",ts->rtol,&ts->rtol,NULL)); 123 PetscCall(PetscOptionsReal("-ts_atol","Absolute tolerance for local truncation error","TSSetTolerances",ts->atol,&ts->atol,NULL)); 124 125 PetscCall(PetscOptionsBool("-ts_rhs_jacobian_test_mult","Test the RHS Jacobian for consistency with RHS at each solve ","None",ts->testjacobian,&ts->testjacobian,NULL)); 126 PetscCall(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)); 127 PetscCall(PetscOptionsBool("-ts_use_splitrhsfunction","Use the split RHS function for multirate solvers ","TSSetUseSplitRHSFunction",ts->use_splitrhsfunction,&ts->use_splitrhsfunction,NULL)); 128 #if defined(PETSC_HAVE_SAWS) 129 { 130 PetscBool set; 131 flg = PETSC_FALSE; 132 PetscCall(PetscOptionsBool("-ts_saws_block","Block for SAWs memory snooper at end of TSSolve","PetscObjectSAWsBlock",((PetscObject)ts)->amspublishblock,&flg,&set)); 133 if (set) PetscCall(PetscObjectSAWsSetBlock((PetscObject)ts,flg)); 134 } 135 #endif 136 137 /* Monitor options */ 138 PetscCall(PetscOptionsInt("-ts_monitor_frequency", "Number of time steps between monitor output", "TSMonitorSetFrequency", ts->monitorFrequency, &ts->monitorFrequency, NULL)); 139 PetscCall(TSMonitorSetFromOptions(ts,"-ts_monitor","Monitor time and timestep size","TSMonitorDefault",TSMonitorDefault,NULL)); 140 PetscCall(TSMonitorSetFromOptions(ts,"-ts_monitor_extreme","Monitor extreme values of the solution","TSMonitorExtreme",TSMonitorExtreme,NULL)); 141 PetscCall(TSMonitorSetFromOptions(ts,"-ts_monitor_solution","View the solution at each timestep","TSMonitorSolution",TSMonitorSolution,NULL)); 142 PetscCall(TSMonitorSetFromOptions(ts,"-ts_dmswarm_monitor_moments","Monitor moments of particle distribution","TSDMSwarmMonitorMoments",TSDMSwarmMonitorMoments,NULL)); 143 144 PetscCall(PetscOptionsString("-ts_monitor_python","Use Python function","TSMonitorSet",NULL,monfilename,sizeof(monfilename),&flg)); 145 if (flg) PetscCall(PetscPythonMonitorSet((PetscObject)ts,monfilename)); 146 147 PetscCall(PetscOptionsName("-ts_monitor_lg_solution","Monitor solution graphically","TSMonitorLGSolution",&opt)); 148 if (opt) { 149 PetscInt howoften = 1; 150 DM dm; 151 PetscBool net; 152 153 PetscCall(PetscOptionsInt("-ts_monitor_lg_solution","Monitor solution graphically","TSMonitorLGSolution",howoften,&howoften,NULL)); 154 PetscCall(TSGetDM(ts,&dm)); 155 PetscCall(PetscObjectTypeCompare((PetscObject)dm,DMNETWORK,&net)); 156 if (net) { 157 TSMonitorLGCtxNetwork ctx; 158 PetscCall(TSMonitorLGCtxNetworkCreate(ts,NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,600,400,howoften,&ctx)); 159 PetscCall(TSMonitorSet(ts,TSMonitorLGCtxNetworkSolution,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxNetworkDestroy)); 160 PetscCall(PetscOptionsBool("-ts_monitor_lg_solution_semilogy","Plot the solution with a semi-log axis","",ctx->semilogy,&ctx->semilogy,NULL)); 161 } else { 162 TSMonitorLGCtx ctx; 163 PetscCall(TSMonitorLGCtxCreate(PETSC_COMM_SELF,NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx)); 164 PetscCall(TSMonitorSet(ts,TSMonitorLGSolution,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy)); 165 } 166 } 167 168 PetscCall(PetscOptionsName("-ts_monitor_lg_error","Monitor error graphically","TSMonitorLGError",&opt)); 169 if (opt) { 170 TSMonitorLGCtx ctx; 171 PetscInt howoften = 1; 172 173 PetscCall(PetscOptionsInt("-ts_monitor_lg_error","Monitor error graphically","TSMonitorLGError",howoften,&howoften,NULL)); 174 PetscCall(TSMonitorLGCtxCreate(PETSC_COMM_SELF,NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx)); 175 PetscCall(TSMonitorSet(ts,TSMonitorLGError,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy)); 176 } 177 PetscCall(TSMonitorSetFromOptions(ts,"-ts_monitor_error","View the error at each timestep","TSMonitorError",TSMonitorError,NULL)); 178 179 PetscCall(PetscOptionsName("-ts_monitor_lg_timestep","Monitor timestep size graphically","TSMonitorLGTimeStep",&opt)); 180 if (opt) { 181 TSMonitorLGCtx ctx; 182 PetscInt howoften = 1; 183 184 PetscCall(PetscOptionsInt("-ts_monitor_lg_timestep","Monitor timestep size graphically","TSMonitorLGTimeStep",howoften,&howoften,NULL)); 185 PetscCall(TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx)); 186 PetscCall(TSMonitorSet(ts,TSMonitorLGTimeStep,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy)); 187 } 188 PetscCall(PetscOptionsName("-ts_monitor_lg_timestep_log","Monitor log timestep size graphically","TSMonitorLGTimeStep",&opt)); 189 if (opt) { 190 TSMonitorLGCtx ctx; 191 PetscInt howoften = 1; 192 193 PetscCall(PetscOptionsInt("-ts_monitor_lg_timestep_log","Monitor log timestep size graphically","TSMonitorLGTimeStep",howoften,&howoften,NULL)); 194 PetscCall(TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx)); 195 PetscCall(TSMonitorSet(ts,TSMonitorLGTimeStep,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy)); 196 ctx->semilogy = PETSC_TRUE; 197 } 198 199 PetscCall(PetscOptionsName("-ts_monitor_lg_snes_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGSNESIterations",&opt)); 200 if (opt) { 201 TSMonitorLGCtx ctx; 202 PetscInt howoften = 1; 203 204 PetscCall(PetscOptionsInt("-ts_monitor_lg_snes_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGSNESIterations",howoften,&howoften,NULL)); 205 PetscCall(TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx)); 206 PetscCall(TSMonitorSet(ts,TSMonitorLGSNESIterations,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy)); 207 } 208 PetscCall(PetscOptionsName("-ts_monitor_lg_ksp_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGKSPIterations",&opt)); 209 if (opt) { 210 TSMonitorLGCtx ctx; 211 PetscInt howoften = 1; 212 213 PetscCall(PetscOptionsInt("-ts_monitor_lg_ksp_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGKSPIterations",howoften,&howoften,NULL)); 214 PetscCall(TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,400,300,howoften,&ctx)); 215 PetscCall(TSMonitorSet(ts,TSMonitorLGKSPIterations,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy)); 216 } 217 PetscCall(PetscOptionsName("-ts_monitor_sp_eig","Monitor eigenvalues of linearized operator graphically","TSMonitorSPEig",&opt)); 218 if (opt) { 219 TSMonitorSPEigCtx ctx; 220 PetscInt howoften = 1; 221 222 PetscCall(PetscOptionsInt("-ts_monitor_sp_eig","Monitor eigenvalues of linearized operator graphically","TSMonitorSPEig",howoften,&howoften,NULL)); 223 PetscCall(TSMonitorSPEigCtxCreate(PETSC_COMM_SELF,NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx)); 224 PetscCall(TSMonitorSet(ts,TSMonitorSPEig,ctx,(PetscErrorCode (*)(void**))TSMonitorSPEigCtxDestroy)); 225 } 226 PetscCall(PetscOptionsName("-ts_monitor_sp_swarm","Display particle phase from the DMSwarm","TSMonitorSPSwarm",&opt)); 227 if (opt) { 228 TSMonitorSPCtx ctx; 229 PetscInt howoften = 1, retain = 0; 230 PetscBool phase = PETSC_TRUE, create = PETSC_TRUE; 231 232 for (PetscInt i = 0; i < ts->numbermonitors; ++i) if (ts->monitor[i] == TSMonitorSPSwarmSolution) {create = PETSC_FALSE;break;} 233 if (create) { 234 PetscCall(PetscOptionsInt("-ts_monitor_sp_swarm","Display particles phase from the DMSwarm", "TSMonitorSPSwarm", howoften, &howoften, NULL)); 235 PetscCall(PetscOptionsInt("-ts_monitor_sp_swarm_retain", "Retain n points plotted to show trajectory, -1 for all points", "TSMonitorSPSwarm", retain, &retain, NULL)); 236 PetscCall(PetscOptionsBool("-ts_monitor_sp_swarm_phase", "Plot in phase space rather than coordinate space", "TSMonitorSPSwarm", phase, &phase, NULL)); 237 PetscCall(TSMonitorSPCtxCreate(PetscObjectComm((PetscObject) ts), NULL, NULL, PETSC_DECIDE, PETSC_DECIDE, 300, 300, howoften, retain, phase, &ctx)); 238 PetscCall(TSMonitorSet(ts, TSMonitorSPSwarmSolution, ctx, (PetscErrorCode (*)(void**))TSMonitorSPCtxDestroy)); 239 } 240 } 241 opt = PETSC_FALSE; 242 PetscCall(PetscOptionsName("-ts_monitor_draw_solution","Monitor solution graphically","TSMonitorDrawSolution",&opt)); 243 if (opt) { 244 TSMonitorDrawCtx ctx; 245 PetscInt howoften = 1; 246 247 PetscCall(PetscOptionsInt("-ts_monitor_draw_solution","Monitor solution graphically","TSMonitorDrawSolution",howoften,&howoften,NULL)); 248 PetscCall(TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),NULL,"Computed Solution",PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx)); 249 PetscCall(TSMonitorSet(ts,TSMonitorDrawSolution,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy)); 250 } 251 opt = PETSC_FALSE; 252 PetscCall(PetscOptionsName("-ts_monitor_draw_solution_phase","Monitor solution graphically","TSMonitorDrawSolutionPhase",&opt)); 253 if (opt) { 254 TSMonitorDrawCtx ctx; 255 PetscReal bounds[4]; 256 PetscInt n = 4; 257 PetscDraw draw; 258 PetscDrawAxis axis; 259 260 PetscCall(PetscOptionsRealArray("-ts_monitor_draw_solution_phase","Monitor solution graphically","TSMonitorDrawSolutionPhase",bounds,&n,NULL)); 261 PetscCheck(n == 4,PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Must provide bounding box of phase field"); 262 PetscCall(TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,300,300,1,&ctx)); 263 PetscCall(PetscViewerDrawGetDraw(ctx->viewer,0,&draw)); 264 PetscCall(PetscViewerDrawGetDrawAxis(ctx->viewer,0,&axis)); 265 PetscCall(PetscDrawAxisSetLimits(axis,bounds[0],bounds[2],bounds[1],bounds[3])); 266 PetscCall(PetscDrawAxisSetLabels(axis,"Phase Diagram","Variable 1","Variable 2")); 267 PetscCall(TSMonitorSet(ts,TSMonitorDrawSolutionPhase,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy)); 268 } 269 opt = PETSC_FALSE; 270 PetscCall(PetscOptionsName("-ts_monitor_draw_error","Monitor error graphically","TSMonitorDrawError",&opt)); 271 if (opt) { 272 TSMonitorDrawCtx ctx; 273 PetscInt howoften = 1; 274 275 PetscCall(PetscOptionsInt("-ts_monitor_draw_error","Monitor error graphically","TSMonitorDrawError",howoften,&howoften,NULL)); 276 PetscCall(TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),NULL,"Error",PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx)); 277 PetscCall(TSMonitorSet(ts,TSMonitorDrawError,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy)); 278 } 279 opt = PETSC_FALSE; 280 PetscCall(PetscOptionsName("-ts_monitor_draw_solution_function","Monitor solution provided by TSMonitorSetSolutionFunction() graphically","TSMonitorDrawSolutionFunction",&opt)); 281 if (opt) { 282 TSMonitorDrawCtx ctx; 283 PetscInt howoften = 1; 284 285 PetscCall(PetscOptionsInt("-ts_monitor_draw_solution_function","Monitor solution provided by TSMonitorSetSolutionFunction() graphically","TSMonitorDrawSolutionFunction",howoften,&howoften,NULL)); 286 PetscCall(TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),NULL,"Solution provided by user function",PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx)); 287 PetscCall(TSMonitorSet(ts,TSMonitorDrawSolutionFunction,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy)); 288 } 289 290 opt = PETSC_FALSE; 291 PetscCall(PetscOptionsString("-ts_monitor_solution_vtk","Save each time step to a binary file, use filename-%%03" PetscInt_FMT ".vts","TSMonitorSolutionVTK",NULL,monfilename,sizeof(monfilename),&flg)); 292 if (flg) { 293 const char *ptr,*ptr2; 294 char *filetemplate; 295 PetscCheck(monfilename[0],PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"-ts_monitor_solution_vtk requires a file template, e.g. filename-%%03" PetscInt_FMT ".vts"); 296 /* Do some cursory validation of the input. */ 297 PetscCall(PetscStrstr(monfilename,"%",(char**)&ptr)); 298 PetscCheck(ptr,PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"-ts_monitor_solution_vtk requires a file template, e.g. filename-%%03" PetscInt_FMT ".vts"); 299 for (ptr++; ptr && *ptr; ptr++) { 300 PetscCall(PetscStrchr("DdiouxX",*ptr,(char**)&ptr2)); 301 PetscCheck(ptr2 || (*ptr >= '0' && *ptr <= '9'),PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Invalid file template argument to -ts_monitor_solution_vtk, should look like filename-%%03" PetscInt_FMT ".vts"); 302 if (ptr2) break; 303 } 304 PetscCall(PetscStrallocpy(monfilename,&filetemplate)); 305 PetscCall(TSMonitorSet(ts,TSMonitorSolutionVTK,filetemplate,(PetscErrorCode (*)(void**))TSMonitorSolutionVTKDestroy)); 306 } 307 308 PetscCall(PetscOptionsString("-ts_monitor_dmda_ray","Display a ray of the solution","None","y=0",dir,sizeof(dir),&flg)); 309 if (flg) { 310 TSMonitorDMDARayCtx *rayctx; 311 int ray = 0; 312 DMDirection ddir; 313 DM da; 314 PetscMPIInt rank; 315 316 PetscCheck(dir[1] == '=',PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Unknown ray %s",dir); 317 if (dir[0] == 'x') ddir = DM_X; 318 else if (dir[0] == 'y') ddir = DM_Y; 319 else SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Unknown ray %s",dir); 320 sscanf(dir+2,"%d",&ray); 321 322 PetscCall(PetscInfo(((PetscObject)ts),"Displaying DMDA ray %c = %d\n",dir[0],ray)); 323 PetscCall(PetscNew(&rayctx)); 324 PetscCall(TSGetDM(ts,&da)); 325 PetscCall(DMDAGetRay(da,ddir,ray,&rayctx->ray,&rayctx->scatter)); 326 PetscCallMPI(MPI_Comm_rank(PetscObjectComm((PetscObject)ts),&rank)); 327 if (rank == 0) PetscCall(PetscViewerDrawOpen(PETSC_COMM_SELF,NULL,NULL,0,0,600,300,&rayctx->viewer)); 328 rayctx->lgctx = NULL; 329 PetscCall(TSMonitorSet(ts,TSMonitorDMDARay,rayctx,TSMonitorDMDARayDestroy)); 330 } 331 PetscCall(PetscOptionsString("-ts_monitor_lg_dmda_ray","Display a ray of the solution","None","x=0",dir,sizeof(dir),&flg)); 332 if (flg) { 333 TSMonitorDMDARayCtx *rayctx; 334 int ray = 0; 335 DMDirection ddir; 336 DM da; 337 PetscInt howoften = 1; 338 339 PetscCheck(dir[1] == '=',PetscObjectComm((PetscObject) ts), PETSC_ERR_ARG_WRONG, "Malformed ray %s", dir); 340 if (dir[0] == 'x') ddir = DM_X; 341 else if (dir[0] == 'y') ddir = DM_Y; 342 else SETERRQ(PetscObjectComm((PetscObject) ts), PETSC_ERR_ARG_WRONG, "Unknown ray direction %s", dir); 343 sscanf(dir+2, "%d", &ray); 344 345 PetscCall(PetscInfo(((PetscObject) ts),"Displaying LG DMDA ray %c = %d\n", dir[0], ray)); 346 PetscCall(PetscNew(&rayctx)); 347 PetscCall(TSGetDM(ts, &da)); 348 PetscCall(DMDAGetRay(da, ddir, ray, &rayctx->ray, &rayctx->scatter)); 349 PetscCall(TSMonitorLGCtxCreate(PETSC_COMM_SELF,NULL,NULL,PETSC_DECIDE,PETSC_DECIDE,600,400,howoften,&rayctx->lgctx)); 350 PetscCall(TSMonitorSet(ts, TSMonitorLGDMDARay, rayctx, TSMonitorDMDARayDestroy)); 351 } 352 353 PetscCall(PetscOptionsName("-ts_monitor_envelope","Monitor maximum and minimum value of each component of the solution","TSMonitorEnvelope",&opt)); 354 if (opt) { 355 TSMonitorEnvelopeCtx ctx; 356 357 PetscCall(TSMonitorEnvelopeCtxCreate(ts,&ctx)); 358 PetscCall(TSMonitorSet(ts,TSMonitorEnvelope,ctx,(PetscErrorCode (*)(void**))TSMonitorEnvelopeCtxDestroy)); 359 } 360 flg = PETSC_FALSE; 361 PetscCall(PetscOptionsBool("-ts_monitor_cancel","Remove all monitors","TSMonitorCancel",flg,&flg,&opt)); 362 if (opt && flg) PetscCall(TSMonitorCancel(ts)); 363 364 flg = PETSC_FALSE; 365 PetscCall(PetscOptionsBool("-ts_fd_color", "Use finite differences with coloring to compute IJacobian", "TSComputeJacobianDefaultColor", flg, &flg, NULL)); 366 if (flg) { 367 DM dm; 368 369 PetscCall(TSGetDM(ts, &dm)); PetscCall(DMTSUnsetIJacobianContext_Internal(dm)); 370 PetscCall(TSSetIJacobian(ts, NULL, NULL, TSComputeIJacobianDefaultColor, NULL)); 371 PetscCall(PetscInfo(ts, "Setting default finite difference coloring Jacobian matrix\n")); 372 } 373 374 /* Handle specific TS options */ 375 PetscTryTypeMethod(ts,setfromoptions,PetscOptionsObject); 376 377 /* Handle TSAdapt options */ 378 PetscCall(TSGetAdapt(ts,&ts->adapt)); 379 PetscCall(TSAdaptSetDefaultType(ts->adapt,ts->default_adapt_type)); 380 PetscCall(TSAdaptSetFromOptions(ts->adapt,PetscOptionsObject)); 381 382 /* TS trajectory must be set after TS, since it may use some TS options above */ 383 tflg = ts->trajectory ? PETSC_TRUE : PETSC_FALSE; 384 PetscCall(PetscOptionsBool("-ts_save_trajectory","Save the solution at each timestep","TSSetSaveTrajectory",tflg,&tflg,NULL)); 385 if (tflg) PetscCall(TSSetSaveTrajectory(ts)); 386 387 PetscCall(TSAdjointSetFromOptions(ts,PetscOptionsObject)); 388 389 /* process any options handlers added with PetscObjectAddOptionsHandler() */ 390 PetscCall(PetscObjectProcessOptionsHandlers((PetscObject)ts,PetscOptionsObject)); 391 PetscOptionsEnd(); 392 393 if (ts->trajectory) PetscCall(TSTrajectorySetFromOptions(ts->trajectory,ts)); 394 395 /* why do we have to do this here and not during TSSetUp? */ 396 PetscCall(TSGetSNES(ts,&ts->snes)); 397 if (ts->problem_type == TS_LINEAR) { 398 PetscCall(PetscObjectTypeCompareAny((PetscObject)ts->snes,&flg,SNESKSPONLY,SNESKSPTRANSPOSEONLY,"")); 399 if (!flg) PetscCall(SNESSetType(ts->snes,SNESKSPONLY)); 400 } 401 PetscCall(SNESSetFromOptions(ts->snes)); 402 PetscFunctionReturn(0); 403 } 404 405 /*@ 406 TSGetTrajectory - Gets the trajectory from a TS if it exists 407 408 Collective on TS 409 410 Input Parameters: 411 . ts - the TS context obtained from TSCreate() 412 413 Output Parameters: 414 . tr - the TSTrajectory object, if it exists 415 416 Note: This routine should be called after all TS options have been set 417 418 Level: advanced 419 420 .seealso: `TSGetTrajectory()`, `TSAdjointSolve()`, `TSTrajectory`, `TSTrajectoryCreate()` 421 422 @*/ 423 PetscErrorCode TSGetTrajectory(TS ts,TSTrajectory *tr) 424 { 425 PetscFunctionBegin; 426 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 427 *tr = ts->trajectory; 428 PetscFunctionReturn(0); 429 } 430 431 /*@ 432 TSSetSaveTrajectory - Causes the TS to save its solutions as it iterates forward in time in a TSTrajectory object 433 434 Collective on TS 435 436 Input Parameter: 437 . ts - the TS context obtained from TSCreate() 438 439 Options Database: 440 + -ts_save_trajectory - saves the trajectory to a file 441 - -ts_trajectory_type type - set trajectory type 442 443 Note: This routine should be called after all TS options have been set 444 445 The TSTRAJECTORYVISUALIZATION files can be loaded into Python with $PETSC_DIR/lib/petsc/bin/PetscBinaryIOTrajectory.py and 446 MATLAB with $PETSC_DIR/share/petsc/matlab/PetscReadBinaryTrajectory.m 447 448 Level: intermediate 449 450 .seealso: `TSGetTrajectory()`, `TSAdjointSolve()` 451 452 @*/ 453 PetscErrorCode TSSetSaveTrajectory(TS ts) 454 { 455 PetscFunctionBegin; 456 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 457 if (!ts->trajectory) PetscCall(TSTrajectoryCreate(PetscObjectComm((PetscObject)ts),&ts->trajectory)); 458 PetscFunctionReturn(0); 459 } 460 461 /*@ 462 TSResetTrajectory - Destroys and recreates the internal TSTrajectory object 463 464 Collective on TS 465 466 Input Parameters: 467 . ts - the TS context obtained from TSCreate() 468 469 Level: intermediate 470 471 .seealso: `TSGetTrajectory()`, `TSAdjointSolve()`, `TSRemoveTrajectory()` 472 473 @*/ 474 PetscErrorCode TSResetTrajectory(TS ts) 475 { 476 PetscFunctionBegin; 477 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 478 if (ts->trajectory) { 479 PetscCall(TSTrajectoryDestroy(&ts->trajectory)); 480 PetscCall(TSTrajectoryCreate(PetscObjectComm((PetscObject)ts),&ts->trajectory)); 481 } 482 PetscFunctionReturn(0); 483 } 484 485 /*@ 486 TSRemoveTrajectory - Destroys and removes the internal TSTrajectory object from TS 487 488 Collective on TS 489 490 Input Parameters: 491 . ts - the TS context obtained from TSCreate() 492 493 Level: intermediate 494 495 .seealso: `TSResetTrajectory()`, `TSAdjointSolve()` 496 497 @*/ 498 PetscErrorCode TSRemoveTrajectory(TS ts) 499 { 500 PetscFunctionBegin; 501 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 502 if (ts->trajectory) PetscCall(TSTrajectoryDestroy(&ts->trajectory)); 503 PetscFunctionReturn(0); 504 } 505 506 /*@ 507 TSComputeRHSJacobian - Computes the Jacobian matrix that has been 508 set with TSSetRHSJacobian(). 509 510 Collective on TS 511 512 Input Parameters: 513 + ts - the TS context 514 . t - current timestep 515 - U - input vector 516 517 Output Parameters: 518 + A - Jacobian matrix 519 - B - optional preconditioning matrix 520 521 Notes: 522 Most users should not need to explicitly call this routine, as it 523 is used internally within the nonlinear solvers. 524 525 Level: developer 526 527 .seealso: `TSSetRHSJacobian()`, `KSPSetOperators()` 528 @*/ 529 PetscErrorCode TSComputeRHSJacobian(TS ts,PetscReal t,Vec U,Mat A,Mat B) 530 { 531 PetscObjectState Ustate; 532 PetscObjectId Uid; 533 DM dm; 534 DMTS tsdm; 535 TSRHSJacobian rhsjacobianfunc; 536 void *ctx; 537 TSRHSFunction rhsfunction; 538 539 PetscFunctionBegin; 540 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 541 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 542 PetscCheckSameComm(ts,1,U,3); 543 PetscCall(TSGetDM(ts,&dm)); 544 PetscCall(DMGetDMTS(dm,&tsdm)); 545 PetscCall(DMTSGetRHSFunction(dm,&rhsfunction,NULL)); 546 PetscCall(DMTSGetRHSJacobian(dm,&rhsjacobianfunc,&ctx)); 547 PetscCall(PetscObjectStateGet((PetscObject)U,&Ustate)); 548 PetscCall(PetscObjectGetId((PetscObject)U,&Uid)); 549 550 if (ts->rhsjacobian.time == t && (ts->problem_type == TS_LINEAR || (ts->rhsjacobian.Xid == Uid && ts->rhsjacobian.Xstate == Ustate)) && (rhsfunction != TSComputeRHSFunctionLinear)) PetscFunctionReturn(0); 551 552 PetscCheck(ts->rhsjacobian.shift == 0.0 || !ts->rhsjacobian.reuse,PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Should not call TSComputeRHSJacobian() on a shifted matrix (shift=%lf) when RHSJacobian is reusable.",(double)ts->rhsjacobian.shift); 553 if (rhsjacobianfunc) { 554 PetscCall(PetscLogEventBegin(TS_JacobianEval,ts,U,A,B)); 555 PetscCallBack("TS callback Jacobian",(*rhsjacobianfunc)(ts,t,U,A,B,ctx)); 556 ts->rhsjacs++; 557 PetscCall(PetscLogEventEnd(TS_JacobianEval,ts,U,A,B)); 558 } else { 559 PetscCall(MatZeroEntries(A)); 560 if (B && A != B) PetscCall(MatZeroEntries(B)); 561 } 562 ts->rhsjacobian.time = t; 563 ts->rhsjacobian.shift = 0; 564 ts->rhsjacobian.scale = 1.; 565 PetscCall(PetscObjectGetId((PetscObject)U,&ts->rhsjacobian.Xid)); 566 PetscCall(PetscObjectStateGet((PetscObject)U,&ts->rhsjacobian.Xstate)); 567 PetscFunctionReturn(0); 568 } 569 570 /*@ 571 TSComputeRHSFunction - Evaluates the right-hand-side function. 572 573 Collective on TS 574 575 Input Parameters: 576 + ts - the TS context 577 . t - current time 578 - U - state vector 579 580 Output Parameter: 581 . y - right hand side 582 583 Note: 584 Most users should not need to explicitly call this routine, as it 585 is used internally within the nonlinear solvers. 586 587 Level: developer 588 589 .seealso: `TSSetRHSFunction()`, `TSComputeIFunction()` 590 @*/ 591 PetscErrorCode TSComputeRHSFunction(TS ts,PetscReal t,Vec U,Vec y) 592 { 593 TSRHSFunction rhsfunction; 594 TSIFunction ifunction; 595 void *ctx; 596 DM dm; 597 598 PetscFunctionBegin; 599 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 600 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 601 PetscValidHeaderSpecific(y,VEC_CLASSID,4); 602 PetscCall(TSGetDM(ts,&dm)); 603 PetscCall(DMTSGetRHSFunction(dm,&rhsfunction,&ctx)); 604 PetscCall(DMTSGetIFunction(dm,&ifunction,NULL)); 605 606 PetscCheck(rhsfunction || ifunction,PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSFunction() and / or TSSetIFunction()"); 607 608 if (rhsfunction) { 609 PetscCall(PetscLogEventBegin(TS_FunctionEval,ts,U,y,0)); 610 PetscCall(VecLockReadPush(U)); 611 PetscCallBack("TS callback right-hand-side",(*rhsfunction)(ts,t,U,y,ctx)); 612 PetscCall(VecLockReadPop(U)); 613 ts->rhsfuncs++; 614 PetscCall(PetscLogEventEnd(TS_FunctionEval,ts,U,y,0)); 615 } else PetscCall(VecZeroEntries(y)); 616 PetscFunctionReturn(0); 617 } 618 619 /*@ 620 TSComputeSolutionFunction - Evaluates the solution function. 621 622 Collective on TS 623 624 Input Parameters: 625 + ts - the TS context 626 - t - current time 627 628 Output Parameter: 629 . U - the solution 630 631 Note: 632 Most users should not need to explicitly call this routine, as it 633 is used internally within the nonlinear solvers. 634 635 Level: developer 636 637 .seealso: `TSSetSolutionFunction()`, `TSSetRHSFunction()`, `TSComputeIFunction()` 638 @*/ 639 PetscErrorCode TSComputeSolutionFunction(TS ts,PetscReal t,Vec U) 640 { 641 TSSolutionFunction solutionfunction; 642 void *ctx; 643 DM dm; 644 645 PetscFunctionBegin; 646 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 647 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 648 PetscCall(TSGetDM(ts,&dm)); 649 PetscCall(DMTSGetSolutionFunction(dm,&solutionfunction,&ctx)); 650 651 if (solutionfunction) PetscCallBack("TS callback solution",(*solutionfunction)(ts,t,U,ctx)); 652 PetscFunctionReturn(0); 653 } 654 /*@ 655 TSComputeForcingFunction - Evaluates the forcing function. 656 657 Collective on TS 658 659 Input Parameters: 660 + ts - the TS context 661 - t - current time 662 663 Output Parameter: 664 . U - the function value 665 666 Note: 667 Most users should not need to explicitly call this routine, as it 668 is used internally within the nonlinear solvers. 669 670 Level: developer 671 672 .seealso: `TSSetSolutionFunction()`, `TSSetRHSFunction()`, `TSComputeIFunction()` 673 @*/ 674 PetscErrorCode TSComputeForcingFunction(TS ts,PetscReal t,Vec U) 675 { 676 void *ctx; 677 DM dm; 678 TSForcingFunction forcing; 679 680 PetscFunctionBegin; 681 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 682 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 683 PetscCall(TSGetDM(ts,&dm)); 684 PetscCall(DMTSGetForcingFunction(dm,&forcing,&ctx)); 685 686 if (forcing) PetscCallBack("TS callback forcing function",(*forcing)(ts,t,U,ctx)); 687 PetscFunctionReturn(0); 688 } 689 690 static PetscErrorCode TSGetRHSVec_Private(TS ts,Vec *Frhs) 691 { 692 Vec F; 693 694 PetscFunctionBegin; 695 *Frhs = NULL; 696 PetscCall(TSGetIFunction(ts,&F,NULL,NULL)); 697 if (!ts->Frhs) PetscCall(VecDuplicate(F,&ts->Frhs)); 698 *Frhs = ts->Frhs; 699 PetscFunctionReturn(0); 700 } 701 702 PetscErrorCode TSGetRHSMats_Private(TS ts,Mat *Arhs,Mat *Brhs) 703 { 704 Mat A,B; 705 TSIJacobian ijacobian; 706 707 PetscFunctionBegin; 708 if (Arhs) *Arhs = NULL; 709 if (Brhs) *Brhs = NULL; 710 PetscCall(TSGetIJacobian(ts,&A,&B,&ijacobian,NULL)); 711 if (Arhs) { 712 if (!ts->Arhs) { 713 if (ijacobian) { 714 PetscCall(MatDuplicate(A,MAT_DO_NOT_COPY_VALUES,&ts->Arhs)); 715 PetscCall(TSSetMatStructure(ts,SAME_NONZERO_PATTERN)); 716 } else { 717 ts->Arhs = A; 718 PetscCall(PetscObjectReference((PetscObject)A)); 719 } 720 } else { 721 PetscBool flg; 722 PetscCall(SNESGetUseMatrixFree(ts->snes,NULL,&flg)); 723 /* Handle case where user provided only RHSJacobian and used -snes_mf_operator */ 724 if (flg && !ijacobian && ts->Arhs == ts->Brhs) { 725 PetscCall(PetscObjectDereference((PetscObject)ts->Arhs)); 726 ts->Arhs = A; 727 PetscCall(PetscObjectReference((PetscObject)A)); 728 } 729 } 730 *Arhs = ts->Arhs; 731 } 732 if (Brhs) { 733 if (!ts->Brhs) { 734 if (A != B) { 735 if (ijacobian) { 736 PetscCall(MatDuplicate(B,MAT_DO_NOT_COPY_VALUES,&ts->Brhs)); 737 } else { 738 ts->Brhs = B; 739 PetscCall(PetscObjectReference((PetscObject)B)); 740 } 741 } else { 742 PetscCall(PetscObjectReference((PetscObject)ts->Arhs)); 743 ts->Brhs = ts->Arhs; 744 } 745 } 746 *Brhs = ts->Brhs; 747 } 748 PetscFunctionReturn(0); 749 } 750 751 /*@ 752 TSComputeIFunction - Evaluates the DAE residual written in implicit form F(t,U,Udot)=0 753 754 Collective on TS 755 756 Input Parameters: 757 + ts - the TS context 758 . t - current time 759 . U - state vector 760 . Udot - time derivative of state vector 761 - imex - flag indicates if the method is IMEX so that the RHSFunction should be kept separate 762 763 Output Parameter: 764 . Y - right hand side 765 766 Note: 767 Most users should not need to explicitly call this routine, as it 768 is used internally within the nonlinear solvers. 769 770 If the user did did not write their equations in implicit form, this 771 function recasts them in implicit form. 772 773 Level: developer 774 775 .seealso: `TSSetIFunction()`, `TSComputeRHSFunction()` 776 @*/ 777 PetscErrorCode TSComputeIFunction(TS ts,PetscReal t,Vec U,Vec Udot,Vec Y,PetscBool imex) 778 { 779 TSIFunction ifunction; 780 TSRHSFunction rhsfunction; 781 void *ctx; 782 DM dm; 783 784 PetscFunctionBegin; 785 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 786 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 787 PetscValidHeaderSpecific(Udot,VEC_CLASSID,4); 788 PetscValidHeaderSpecific(Y,VEC_CLASSID,5); 789 790 PetscCall(TSGetDM(ts,&dm)); 791 PetscCall(DMTSGetIFunction(dm,&ifunction,&ctx)); 792 PetscCall(DMTSGetRHSFunction(dm,&rhsfunction,NULL)); 793 794 PetscCheck(rhsfunction || ifunction,PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSFunction() and / or TSSetIFunction()"); 795 796 PetscCall(PetscLogEventBegin(TS_FunctionEval,ts,U,Udot,Y)); 797 if (ifunction) { 798 PetscCallBack("TS callback implicit function",(*ifunction)(ts,t,U,Udot,Y,ctx)); 799 ts->ifuncs++; 800 } 801 if (imex) { 802 if (!ifunction) PetscCall(VecCopy(Udot,Y)); 803 } else if (rhsfunction) { 804 if (ifunction) { 805 Vec Frhs; 806 PetscCall(TSGetRHSVec_Private(ts,&Frhs)); 807 PetscCall(TSComputeRHSFunction(ts,t,U,Frhs)); 808 PetscCall(VecAXPY(Y,-1,Frhs)); 809 } else { 810 PetscCall(TSComputeRHSFunction(ts,t,U,Y)); 811 PetscCall(VecAYPX(Y,-1,Udot)); 812 } 813 } 814 PetscCall(PetscLogEventEnd(TS_FunctionEval,ts,U,Udot,Y)); 815 PetscFunctionReturn(0); 816 } 817 818 /* 819 TSRecoverRHSJacobian - Recover the Jacobian matrix so that one can call TSComputeRHSJacobian() on it. 820 821 Note: 822 This routine is needed when one switches from TSComputeIJacobian() to TSComputeRHSJacobian() because the Jacobian matrix may be shifted or scaled in TSComputeIJacobian(). 823 824 */ 825 static PetscErrorCode TSRecoverRHSJacobian(TS ts,Mat A,Mat B) 826 { 827 PetscFunctionBegin; 828 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 829 PetscCheck(A == ts->Arhs,PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Invalid Amat"); 830 PetscCheck(B == ts->Brhs,PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Invalid Bmat"); 831 832 if (ts->rhsjacobian.shift) PetscCall(MatShift(A,-ts->rhsjacobian.shift)); 833 if (ts->rhsjacobian.scale == -1.) { 834 PetscCall(MatScale(A,-1)); 835 } 836 if (B && B == ts->Brhs && A != B) { 837 if (ts->rhsjacobian.shift) PetscCall(MatShift(B,-ts->rhsjacobian.shift)); 838 if (ts->rhsjacobian.scale == -1.) PetscCall(MatScale(B,-1)); 839 } 840 ts->rhsjacobian.shift = 0; 841 ts->rhsjacobian.scale = 1.; 842 PetscFunctionReturn(0); 843 } 844 845 /*@ 846 TSComputeIJacobian - Evaluates the Jacobian of the DAE 847 848 Collective on TS 849 850 Input 851 Input Parameters: 852 + ts - the TS context 853 . t - current timestep 854 . U - state vector 855 . Udot - time derivative of state vector 856 . shift - shift to apply, see note below 857 - imex - flag indicates if the method is IMEX so that the RHSJacobian should be kept separate 858 859 Output Parameters: 860 + A - Jacobian matrix 861 - B - matrix from which the preconditioner is constructed; often the same as A 862 863 Notes: 864 If F(t,U,Udot)=0 is the DAE, the required Jacobian is 865 866 dF/dU + shift*dF/dUdot 867 868 Most users should not need to explicitly call this routine, as it 869 is used internally within the nonlinear solvers. 870 871 Level: developer 872 873 .seealso: `TSSetIJacobian()` 874 @*/ 875 PetscErrorCode TSComputeIJacobian(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat A,Mat B,PetscBool imex) 876 { 877 TSIJacobian ijacobian; 878 TSRHSJacobian rhsjacobian; 879 DM dm; 880 void *ctx; 881 882 PetscFunctionBegin; 883 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 884 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 885 PetscValidHeaderSpecific(Udot,VEC_CLASSID,4); 886 PetscValidPointer(A,6); 887 PetscValidHeaderSpecific(A,MAT_CLASSID,6); 888 PetscValidPointer(B,7); 889 PetscValidHeaderSpecific(B,MAT_CLASSID,7); 890 891 PetscCall(TSGetDM(ts,&dm)); 892 PetscCall(DMTSGetIJacobian(dm,&ijacobian,&ctx)); 893 PetscCall(DMTSGetRHSJacobian(dm,&rhsjacobian,NULL)); 894 895 PetscCheck(rhsjacobian || ijacobian,PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSJacobian() and / or TSSetIJacobian()"); 896 897 PetscCall(PetscLogEventBegin(TS_JacobianEval,ts,U,A,B)); 898 if (ijacobian) { 899 PetscCallBack("TS callback implicit Jacobian",(*ijacobian)(ts,t,U,Udot,shift,A,B,ctx)); 900 ts->ijacs++; 901 } 902 if (imex) { 903 if (!ijacobian) { /* system was written as Udot = G(t,U) */ 904 PetscBool assembled; 905 if (rhsjacobian) { 906 Mat Arhs = NULL; 907 PetscCall(TSGetRHSMats_Private(ts,&Arhs,NULL)); 908 if (A == Arhs) { 909 PetscCheck(rhsjacobian != TSComputeRHSJacobianConstant,PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Unsupported operation! cannot use TSComputeRHSJacobianConstant"); /* there is no way to reconstruct shift*M-J since J cannot be reevaluated */ 910 ts->rhsjacobian.time = PETSC_MIN_REAL; 911 } 912 } 913 PetscCall(MatZeroEntries(A)); 914 PetscCall(MatAssembled(A,&assembled)); 915 if (!assembled) { 916 PetscCall(MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY)); 917 PetscCall(MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY)); 918 } 919 PetscCall(MatShift(A,shift)); 920 if (A != B) { 921 PetscCall(MatZeroEntries(B)); 922 PetscCall(MatAssembled(B,&assembled)); 923 if (!assembled) { 924 PetscCall(MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY)); 925 PetscCall(MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY)); 926 } 927 PetscCall(MatShift(B,shift)); 928 } 929 } 930 } else { 931 Mat Arhs = NULL,Brhs = NULL; 932 933 /* RHSJacobian needs to be converted to part of IJacobian if exists */ 934 if (rhsjacobian) PetscCall(TSGetRHSMats_Private(ts,&Arhs,&Brhs)); 935 if (Arhs == A) { /* No IJacobian matrix, so we only have the RHS matrix */ 936 PetscObjectState Ustate; 937 PetscObjectId Uid; 938 TSRHSFunction rhsfunction; 939 940 PetscCall(DMTSGetRHSFunction(dm,&rhsfunction,NULL)); 941 PetscCall(PetscObjectStateGet((PetscObject)U,&Ustate)); 942 PetscCall(PetscObjectGetId((PetscObject)U,&Uid)); 943 if ((rhsjacobian == TSComputeRHSJacobianConstant || (ts->rhsjacobian.time == t && (ts->problem_type == TS_LINEAR || (ts->rhsjacobian.Xid == Uid && ts->rhsjacobian.Xstate == Ustate)) && rhsfunction != TSComputeRHSFunctionLinear)) && ts->rhsjacobian.scale == -1.) { /* No need to recompute RHSJacobian */ 944 PetscCall(MatShift(A,shift-ts->rhsjacobian.shift)); /* revert the old shift and add the new shift with a single call to MatShift */ 945 if (A != B) PetscCall(MatShift(B,shift-ts->rhsjacobian.shift)); 946 } else { 947 PetscBool flg; 948 949 if (ts->rhsjacobian.reuse) { /* Undo the damage */ 950 /* MatScale has a short path for this case. 951 However, this code path is taken the first time TSComputeRHSJacobian is called 952 and the matrices have not been assembled yet */ 953 PetscCall(TSRecoverRHSJacobian(ts,A,B)); 954 } 955 PetscCall(TSComputeRHSJacobian(ts,t,U,A,B)); 956 PetscCall(SNESGetUseMatrixFree(ts->snes,NULL,&flg)); 957 /* since -snes_mf_operator uses the full SNES function it does not need to be shifted or scaled here */ 958 if (!flg) { 959 PetscCall(MatScale(A,-1)); 960 PetscCall(MatShift(A,shift)); 961 } 962 if (A != B) { 963 PetscCall(MatScale(B,-1)); 964 PetscCall(MatShift(B,shift)); 965 } 966 } 967 ts->rhsjacobian.scale = -1; 968 ts->rhsjacobian.shift = shift; 969 } else if (Arhs) { /* Both IJacobian and RHSJacobian */ 970 if (!ijacobian) { /* No IJacobian provided, but we have a separate RHS matrix */ 971 PetscCall(MatZeroEntries(A)); 972 PetscCall(MatShift(A,shift)); 973 if (A != B) { 974 PetscCall(MatZeroEntries(B)); 975 PetscCall(MatShift(B,shift)); 976 } 977 } 978 PetscCall(TSComputeRHSJacobian(ts,t,U,Arhs,Brhs)); 979 PetscCall(MatAXPY(A,-1,Arhs,ts->axpy_pattern)); 980 if (A != B) PetscCall(MatAXPY(B,-1,Brhs,ts->axpy_pattern)); 981 } 982 } 983 PetscCall(PetscLogEventEnd(TS_JacobianEval,ts,U,A,B)); 984 PetscFunctionReturn(0); 985 } 986 987 /*@C 988 TSSetRHSFunction - Sets the routine for evaluating the function, 989 where U_t = G(t,u). 990 991 Logically Collective on TS 992 993 Input Parameters: 994 + ts - the TS context obtained from TSCreate() 995 . r - vector to put the computed right hand side (or NULL to have it created) 996 . f - routine for evaluating the right-hand-side function 997 - ctx - [optional] user-defined context for private data for the 998 function evaluation routine (may be NULL) 999 1000 Calling sequence of f: 1001 $ PetscErrorCode f(TS ts,PetscReal t,Vec u,Vec F,void *ctx); 1002 1003 + ts - timestep context 1004 . t - current timestep 1005 . u - input vector 1006 . F - function vector 1007 - ctx - [optional] user-defined function context 1008 1009 Level: beginner 1010 1011 Notes: 1012 You must call this function or TSSetIFunction() to define your ODE. You cannot use this function when solving a DAE. 1013 1014 .seealso: `TSSetRHSJacobian()`, `TSSetIJacobian()`, `TSSetIFunction()` 1015 @*/ 1016 PetscErrorCode TSSetRHSFunction(TS ts,Vec r,PetscErrorCode (*f)(TS,PetscReal,Vec,Vec,void*),void *ctx) 1017 { 1018 SNES snes; 1019 Vec ralloc = NULL; 1020 DM dm; 1021 1022 PetscFunctionBegin; 1023 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1024 if (r) PetscValidHeaderSpecific(r,VEC_CLASSID,2); 1025 1026 PetscCall(TSGetDM(ts,&dm)); 1027 PetscCall(DMTSSetRHSFunction(dm,f,ctx)); 1028 PetscCall(TSGetSNES(ts,&snes)); 1029 if (!r && !ts->dm && ts->vec_sol) { 1030 PetscCall(VecDuplicate(ts->vec_sol,&ralloc)); 1031 r = ralloc; 1032 } 1033 PetscCall(SNESSetFunction(snes,r,SNESTSFormFunction,ts)); 1034 PetscCall(VecDestroy(&ralloc)); 1035 PetscFunctionReturn(0); 1036 } 1037 1038 /*@C 1039 TSSetSolutionFunction - Provide a function that computes the solution of the ODE or DAE 1040 1041 Logically Collective on TS 1042 1043 Input Parameters: 1044 + ts - the TS context obtained from TSCreate() 1045 . f - routine for evaluating the solution 1046 - ctx - [optional] user-defined context for private data for the 1047 function evaluation routine (may be NULL) 1048 1049 Calling sequence of f: 1050 $ PetscErrorCode f(TS ts,PetscReal t,Vec u,void *ctx); 1051 1052 + t - current timestep 1053 . u - output vector 1054 - ctx - [optional] user-defined function context 1055 1056 Options Database: 1057 + -ts_monitor_lg_error - create a graphical monitor of error history, requires user to have provided TSSetSolutionFunction() 1058 - -ts_monitor_draw_error - Monitor error graphically, requires user to have provided TSSetSolutionFunction() 1059 1060 Notes: 1061 This routine is used for testing accuracy of time integration schemes when you already know the solution. 1062 If analytic solutions are not known for your system, consider using the Method of Manufactured Solutions to 1063 create closed-form solutions with non-physical forcing terms. 1064 1065 For low-dimensional problems solved in serial, such as small discrete systems, TSMonitorLGError() can be used to monitor the error history. 1066 1067 Level: beginner 1068 1069 .seealso: `TSSetRHSJacobian()`, `TSSetIJacobian()`, `TSComputeSolutionFunction()`, `TSSetForcingFunction()`, `TSSetSolution()`, `TSGetSolution()`, `TSMonitorLGError()`, `TSMonitorDrawError()` 1070 @*/ 1071 PetscErrorCode TSSetSolutionFunction(TS ts,PetscErrorCode (*f)(TS,PetscReal,Vec,void*),void *ctx) 1072 { 1073 DM dm; 1074 1075 PetscFunctionBegin; 1076 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1077 PetscCall(TSGetDM(ts,&dm)); 1078 PetscCall(DMTSSetSolutionFunction(dm,f,ctx)); 1079 PetscFunctionReturn(0); 1080 } 1081 1082 /*@C 1083 TSSetForcingFunction - Provide a function that computes a forcing term for a ODE or PDE 1084 1085 Logically Collective on TS 1086 1087 Input Parameters: 1088 + ts - the TS context obtained from TSCreate() 1089 . func - routine for evaluating the forcing function 1090 - ctx - [optional] user-defined context for private data for the 1091 function evaluation routine (may be NULL) 1092 1093 Calling sequence of func: 1094 $ PetscErrorCode func (TS ts,PetscReal t,Vec f,void *ctx); 1095 1096 + t - current timestep 1097 . f - output vector 1098 - ctx - [optional] user-defined function context 1099 1100 Notes: 1101 This routine is useful for testing accuracy of time integration schemes when using the Method of Manufactured Solutions to 1102 create closed-form solutions with a non-physical forcing term. It allows you to use the Method of Manufactored Solution without directly editing the 1103 definition of the problem you are solving and hence possibly introducing bugs. 1104 1105 This replaces the ODE F(u,u_t,t) = 0 the TS is solving with F(u,u_t,t) - func(t) = 0 1106 1107 This forcing function does not depend on the solution to the equations, it can only depend on spatial location, time, and possibly parameters, the 1108 parameters can be passed in the ctx variable. 1109 1110 For low-dimensional problems solved in serial, such as small discrete systems, TSMonitorLGError() can be used to monitor the error history. 1111 1112 Level: beginner 1113 1114 .seealso: `TSSetRHSJacobian()`, `TSSetIJacobian()`, `TSComputeSolutionFunction()`, `TSSetSolutionFunction()` 1115 @*/ 1116 PetscErrorCode TSSetForcingFunction(TS ts,TSForcingFunction func,void *ctx) 1117 { 1118 DM dm; 1119 1120 PetscFunctionBegin; 1121 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1122 PetscCall(TSGetDM(ts,&dm)); 1123 PetscCall(DMTSSetForcingFunction(dm,func,ctx)); 1124 PetscFunctionReturn(0); 1125 } 1126 1127 /*@C 1128 TSSetRHSJacobian - Sets the function to compute the Jacobian of G, 1129 where U_t = G(U,t), as well as the location to store the matrix. 1130 1131 Logically Collective on TS 1132 1133 Input Parameters: 1134 + ts - the TS context obtained from TSCreate() 1135 . Amat - (approximate) Jacobian matrix 1136 . Pmat - matrix from which preconditioner is to be constructed (usually the same as Amat) 1137 . f - the Jacobian evaluation routine 1138 - ctx - [optional] user-defined context for private data for the 1139 Jacobian evaluation routine (may be NULL) 1140 1141 Calling sequence of f: 1142 $ PetscErrorCode f(TS ts,PetscReal t,Vec u,Mat A,Mat B,void *ctx); 1143 1144 + t - current timestep 1145 . u - input vector 1146 . Amat - (approximate) Jacobian matrix 1147 . Pmat - matrix from which preconditioner is to be constructed (usually the same as Amat) 1148 - ctx - [optional] user-defined context for matrix evaluation routine 1149 1150 Notes: 1151 You must set all the diagonal entries of the matrices, if they are zero you must still set them with a zero value 1152 1153 The TS solver may modify the nonzero structure and the entries of the matrices Amat and Pmat between the calls to f() 1154 You should not assume the values are the same in the next call to f() as you set them in the previous call. 1155 1156 Level: beginner 1157 1158 .seealso: `SNESComputeJacobianDefaultColor()`, `TSSetRHSFunction()`, `TSRHSJacobianSetReuse()`, `TSSetIJacobian()` 1159 1160 @*/ 1161 PetscErrorCode TSSetRHSJacobian(TS ts,Mat Amat,Mat Pmat,TSRHSJacobian f,void *ctx) 1162 { 1163 SNES snes; 1164 DM dm; 1165 TSIJacobian ijacobian; 1166 1167 PetscFunctionBegin; 1168 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1169 if (Amat) PetscValidHeaderSpecific(Amat,MAT_CLASSID,2); 1170 if (Pmat) PetscValidHeaderSpecific(Pmat,MAT_CLASSID,3); 1171 if (Amat) PetscCheckSameComm(ts,1,Amat,2); 1172 if (Pmat) PetscCheckSameComm(ts,1,Pmat,3); 1173 1174 PetscCall(TSGetDM(ts,&dm)); 1175 PetscCall(DMTSSetRHSJacobian(dm,f,ctx)); 1176 PetscCall(DMTSGetIJacobian(dm,&ijacobian,NULL)); 1177 PetscCall(TSGetSNES(ts,&snes)); 1178 if (!ijacobian) PetscCall(SNESSetJacobian(snes,Amat,Pmat,SNESTSFormJacobian,ts)); 1179 if (Amat) { 1180 PetscCall(PetscObjectReference((PetscObject)Amat)); 1181 PetscCall(MatDestroy(&ts->Arhs)); 1182 ts->Arhs = Amat; 1183 } 1184 if (Pmat) { 1185 PetscCall(PetscObjectReference((PetscObject)Pmat)); 1186 PetscCall(MatDestroy(&ts->Brhs)); 1187 ts->Brhs = Pmat; 1188 } 1189 PetscFunctionReturn(0); 1190 } 1191 1192 /*@C 1193 TSSetIFunction - Set the function to compute F(t,U,U_t) where F() = 0 is the DAE to be solved. 1194 1195 Logically Collective on TS 1196 1197 Input Parameters: 1198 + ts - the TS context obtained from TSCreate() 1199 . r - vector to hold the residual (or NULL to have it created internally) 1200 . f - the function evaluation routine 1201 - ctx - user-defined context for private data for the function evaluation routine (may be NULL) 1202 1203 Calling sequence of f: 1204 $ PetscErrorCode f(TS ts,PetscReal t,Vec u,Vec u_t,Vec F,ctx); 1205 1206 + t - time at step/stage being solved 1207 . u - state vector 1208 . u_t - time derivative of state vector 1209 . F - function vector 1210 - ctx - [optional] user-defined context for matrix evaluation routine 1211 1212 Important: 1213 The user MUST call either this routine or TSSetRHSFunction() to define the ODE. When solving DAEs you must use this function. 1214 1215 Level: beginner 1216 1217 .seealso: `TSSetRHSJacobian()`, `TSSetRHSFunction()`, `TSSetIJacobian()` 1218 @*/ 1219 PetscErrorCode TSSetIFunction(TS ts,Vec r,TSIFunction f,void *ctx) 1220 { 1221 SNES snes; 1222 Vec ralloc = NULL; 1223 DM dm; 1224 1225 PetscFunctionBegin; 1226 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1227 if (r) PetscValidHeaderSpecific(r,VEC_CLASSID,2); 1228 1229 PetscCall(TSGetDM(ts,&dm)); 1230 PetscCall(DMTSSetIFunction(dm,f,ctx)); 1231 1232 PetscCall(TSGetSNES(ts,&snes)); 1233 if (!r && !ts->dm && ts->vec_sol) { 1234 PetscCall(VecDuplicate(ts->vec_sol,&ralloc)); 1235 r = ralloc; 1236 } 1237 PetscCall(SNESSetFunction(snes,r,SNESTSFormFunction,ts)); 1238 PetscCall(VecDestroy(&ralloc)); 1239 PetscFunctionReturn(0); 1240 } 1241 1242 /*@C 1243 TSGetIFunction - Returns the vector where the implicit residual is stored and the function/context to compute it. 1244 1245 Not Collective 1246 1247 Input Parameter: 1248 . ts - the TS context 1249 1250 Output Parameters: 1251 + r - vector to hold residual (or NULL) 1252 . func - the function to compute residual (or NULL) 1253 - ctx - the function context (or NULL) 1254 1255 Level: advanced 1256 1257 .seealso: `TSSetIFunction()`, `SNESGetFunction()` 1258 @*/ 1259 PetscErrorCode TSGetIFunction(TS ts,Vec *r,TSIFunction *func,void **ctx) 1260 { 1261 SNES snes; 1262 DM dm; 1263 1264 PetscFunctionBegin; 1265 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1266 PetscCall(TSGetSNES(ts,&snes)); 1267 PetscCall(SNESGetFunction(snes,r,NULL,NULL)); 1268 PetscCall(TSGetDM(ts,&dm)); 1269 PetscCall(DMTSGetIFunction(dm,func,ctx)); 1270 PetscFunctionReturn(0); 1271 } 1272 1273 /*@C 1274 TSGetRHSFunction - Returns the vector where the right hand side is stored and the function/context to compute it. 1275 1276 Not Collective 1277 1278 Input Parameter: 1279 . ts - the TS context 1280 1281 Output Parameters: 1282 + r - vector to hold computed right hand side (or NULL) 1283 . func - the function to compute right hand side (or NULL) 1284 - ctx - the function context (or NULL) 1285 1286 Level: advanced 1287 1288 .seealso: `TSSetRHSFunction()`, `SNESGetFunction()` 1289 @*/ 1290 PetscErrorCode TSGetRHSFunction(TS ts,Vec *r,TSRHSFunction *func,void **ctx) 1291 { 1292 SNES snes; 1293 DM dm; 1294 1295 PetscFunctionBegin; 1296 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1297 PetscCall(TSGetSNES(ts,&snes)); 1298 PetscCall(SNESGetFunction(snes,r,NULL,NULL)); 1299 PetscCall(TSGetDM(ts,&dm)); 1300 PetscCall(DMTSGetRHSFunction(dm,func,ctx)); 1301 PetscFunctionReturn(0); 1302 } 1303 1304 /*@C 1305 TSSetIJacobian - Set the function to compute the matrix dF/dU + a*dF/dU_t where F(t,U,U_t) is the function 1306 provided with TSSetIFunction(). 1307 1308 Logically Collective on TS 1309 1310 Input Parameters: 1311 + ts - the TS context obtained from TSCreate() 1312 . Amat - (approximate) Jacobian matrix 1313 . Pmat - matrix used to compute preconditioner (usually the same as Amat) 1314 . f - the Jacobian evaluation routine 1315 - ctx - user-defined context for private data for the Jacobian evaluation routine (may be NULL) 1316 1317 Calling sequence of f: 1318 $ PetscErrorCode f(TS ts,PetscReal t,Vec U,Vec U_t,PetscReal a,Mat Amat,Mat Pmat,void *ctx); 1319 1320 + t - time at step/stage being solved 1321 . U - state vector 1322 . U_t - time derivative of state vector 1323 . a - shift 1324 . Amat - (approximate) Jacobian of F(t,U,W+a*U), equivalent to dF/dU + a*dF/dU_t 1325 . Pmat - matrix used for constructing preconditioner, usually the same as Amat 1326 - ctx - [optional] user-defined context for matrix evaluation routine 1327 1328 Notes: 1329 The matrices Amat and Pmat are exactly the matrices that are used by SNES for the nonlinear solve. 1330 1331 If you know the operator Amat has a null space you can use MatSetNullSpace() and MatSetTransposeNullSpace() to supply the null 1332 space to Amat and the KSP solvers will automatically use that null space as needed during the solution process. 1333 1334 The matrix dF/dU + a*dF/dU_t you provide turns out to be 1335 the Jacobian of F(t,U,W+a*U) where F(t,U,U_t) = 0 is the DAE to be solved. 1336 The time integrator internally approximates U_t by W+a*U where the positive "shift" 1337 a and vector W depend on the integration method, step size, and past states. For example with 1338 the backward Euler method a = 1/dt and W = -a*U(previous timestep) so 1339 W + a*U = a*(U - U(previous timestep)) = (U - U(previous timestep))/dt 1340 1341 You must set all the diagonal entries of the matrices, if they are zero you must still set them with a zero value 1342 1343 The TS solver may modify the nonzero structure and the entries of the matrices Amat and Pmat between the calls to f() 1344 You should not assume the values are the same in the next call to f() as you set them in the previous call. 1345 1346 Level: beginner 1347 1348 .seealso: `TSSetIFunction()`, `TSSetRHSJacobian()`, `SNESComputeJacobianDefaultColor()`, `SNESComputeJacobianDefault()`, `TSSetRHSFunction()` 1349 1350 @*/ 1351 PetscErrorCode TSSetIJacobian(TS ts,Mat Amat,Mat Pmat,TSIJacobian f,void *ctx) 1352 { 1353 SNES snes; 1354 DM dm; 1355 1356 PetscFunctionBegin; 1357 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1358 if (Amat) PetscValidHeaderSpecific(Amat,MAT_CLASSID,2); 1359 if (Pmat) PetscValidHeaderSpecific(Pmat,MAT_CLASSID,3); 1360 if (Amat) PetscCheckSameComm(ts,1,Amat,2); 1361 if (Pmat) PetscCheckSameComm(ts,1,Pmat,3); 1362 1363 PetscCall(TSGetDM(ts,&dm)); 1364 PetscCall(DMTSSetIJacobian(dm,f,ctx)); 1365 1366 PetscCall(TSGetSNES(ts,&snes)); 1367 PetscCall(SNESSetJacobian(snes,Amat,Pmat,SNESTSFormJacobian,ts)); 1368 PetscFunctionReturn(0); 1369 } 1370 1371 /*@ 1372 TSRHSJacobianSetReuse - restore RHS Jacobian before re-evaluating. Without this flag, TS will change the sign and 1373 shift the RHS Jacobian for a finite-time-step implicit solve, in which case the user function will need to recompute 1374 the entire Jacobian. The reuse flag must be set if the evaluation function will assume that the matrix entries have 1375 not been changed by the TS. 1376 1377 Logically Collective 1378 1379 Input Parameters: 1380 + ts - TS context obtained from TSCreate() 1381 - reuse - PETSC_TRUE if the RHS Jacobian 1382 1383 Level: intermediate 1384 1385 .seealso: `TSSetRHSJacobian()`, `TSComputeRHSJacobianConstant()` 1386 @*/ 1387 PetscErrorCode TSRHSJacobianSetReuse(TS ts,PetscBool reuse) 1388 { 1389 PetscFunctionBegin; 1390 ts->rhsjacobian.reuse = reuse; 1391 PetscFunctionReturn(0); 1392 } 1393 1394 /*@C 1395 TSSetI2Function - Set the function to compute F(t,U,U_t,U_tt) where F = 0 is the DAE to be solved. 1396 1397 Logically Collective on TS 1398 1399 Input Parameters: 1400 + ts - the TS context obtained from TSCreate() 1401 . F - vector to hold the residual (or NULL to have it created internally) 1402 . fun - the function evaluation routine 1403 - ctx - user-defined context for private data for the function evaluation routine (may be NULL) 1404 1405 Calling sequence of fun: 1406 $ PetscErrorCode fun(TS ts,PetscReal t,Vec U,Vec U_t,Vec U_tt,Vec F,ctx); 1407 1408 + t - time at step/stage being solved 1409 . U - state vector 1410 . U_t - time derivative of state vector 1411 . U_tt - second time derivative of state vector 1412 . F - function vector 1413 - ctx - [optional] user-defined context for matrix evaluation routine (may be NULL) 1414 1415 Level: beginner 1416 1417 .seealso: `TSSetI2Jacobian()`, `TSSetIFunction()`, `TSCreate()`, `TSSetRHSFunction()` 1418 @*/ 1419 PetscErrorCode TSSetI2Function(TS ts,Vec F,TSI2Function fun,void *ctx) 1420 { 1421 DM dm; 1422 1423 PetscFunctionBegin; 1424 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1425 if (F) PetscValidHeaderSpecific(F,VEC_CLASSID,2); 1426 PetscCall(TSSetIFunction(ts,F,NULL,NULL)); 1427 PetscCall(TSGetDM(ts,&dm)); 1428 PetscCall(DMTSSetI2Function(dm,fun,ctx)); 1429 PetscFunctionReturn(0); 1430 } 1431 1432 /*@C 1433 TSGetI2Function - Returns the vector where the implicit residual is stored and the function/context to compute it. 1434 1435 Not Collective 1436 1437 Input Parameter: 1438 . ts - the TS context 1439 1440 Output Parameters: 1441 + r - vector to hold residual (or NULL) 1442 . fun - the function to compute residual (or NULL) 1443 - ctx - the function context (or NULL) 1444 1445 Level: advanced 1446 1447 .seealso: `TSSetIFunction()`, `SNESGetFunction()`, `TSCreate()` 1448 @*/ 1449 PetscErrorCode TSGetI2Function(TS ts,Vec *r,TSI2Function *fun,void **ctx) 1450 { 1451 SNES snes; 1452 DM dm; 1453 1454 PetscFunctionBegin; 1455 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1456 PetscCall(TSGetSNES(ts,&snes)); 1457 PetscCall(SNESGetFunction(snes,r,NULL,NULL)); 1458 PetscCall(TSGetDM(ts,&dm)); 1459 PetscCall(DMTSGetI2Function(dm,fun,ctx)); 1460 PetscFunctionReturn(0); 1461 } 1462 1463 /*@C 1464 TSSetI2Jacobian - Set the function to compute the matrix dF/dU + v*dF/dU_t + a*dF/dU_tt 1465 where F(t,U,U_t,U_tt) is the function you provided with TSSetI2Function(). 1466 1467 Logically Collective on TS 1468 1469 Input Parameters: 1470 + ts - the TS context obtained from TSCreate() 1471 . J - Jacobian matrix 1472 . P - preconditioning matrix for J (may be same as J) 1473 . jac - the Jacobian evaluation routine 1474 - ctx - user-defined context for private data for the Jacobian evaluation routine (may be NULL) 1475 1476 Calling sequence of jac: 1477 $ PetscErrorCode jac(TS ts,PetscReal t,Vec U,Vec U_t,Vec U_tt,PetscReal v,PetscReal a,Mat J,Mat P,void *ctx); 1478 1479 + t - time at step/stage being solved 1480 . U - state vector 1481 . U_t - time derivative of state vector 1482 . U_tt - second time derivative of state vector 1483 . v - shift for U_t 1484 . a - shift for U_tt 1485 . 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 1486 . P - preconditioning matrix for J, may be same as J 1487 - ctx - [optional] user-defined context for matrix evaluation routine 1488 1489 Notes: 1490 The matrices J and P are exactly the matrices that are used by SNES for the nonlinear solve. 1491 1492 The matrix dF/dU + v*dF/dU_t + a*dF/dU_tt you provide turns out to be 1493 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. 1494 The time integrator internally approximates U_t by W+v*U and U_tt by W'+a*U where the positive "shift" 1495 parameters 'v' and 'a' and vectors W, W' depend on the integration method, step size, and past states. 1496 1497 Level: beginner 1498 1499 .seealso: `TSSetI2Function()`, `TSGetI2Jacobian()` 1500 @*/ 1501 PetscErrorCode TSSetI2Jacobian(TS ts,Mat J,Mat P,TSI2Jacobian jac,void *ctx) 1502 { 1503 DM dm; 1504 1505 PetscFunctionBegin; 1506 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1507 if (J) PetscValidHeaderSpecific(J,MAT_CLASSID,2); 1508 if (P) PetscValidHeaderSpecific(P,MAT_CLASSID,3); 1509 PetscCall(TSSetIJacobian(ts,J,P,NULL,NULL)); 1510 PetscCall(TSGetDM(ts,&dm)); 1511 PetscCall(DMTSSetI2Jacobian(dm,jac,ctx)); 1512 PetscFunctionReturn(0); 1513 } 1514 1515 /*@C 1516 TSGetI2Jacobian - Returns the implicit Jacobian at the present timestep. 1517 1518 Not Collective, but parallel objects are returned if TS is parallel 1519 1520 Input Parameter: 1521 . ts - The TS context obtained from TSCreate() 1522 1523 Output Parameters: 1524 + J - The (approximate) Jacobian of F(t,U,U_t,U_tt) 1525 . P - The matrix from which the preconditioner is constructed, often the same as J 1526 . jac - The function to compute the Jacobian matrices 1527 - ctx - User-defined context for Jacobian evaluation routine 1528 1529 Notes: 1530 You can pass in NULL for any return argument you do not need. 1531 1532 Level: advanced 1533 1534 .seealso: `TSGetTimeStep()`, `TSGetMatrices()`, `TSGetTime()`, `TSGetStepNumber()`, `TSSetI2Jacobian()`, `TSGetI2Function()`, `TSCreate()` 1535 1536 @*/ 1537 PetscErrorCode TSGetI2Jacobian(TS ts,Mat *J,Mat *P,TSI2Jacobian *jac,void **ctx) 1538 { 1539 SNES snes; 1540 DM dm; 1541 1542 PetscFunctionBegin; 1543 PetscCall(TSGetSNES(ts,&snes)); 1544 PetscCall(SNESSetUpMatrices(snes)); 1545 PetscCall(SNESGetJacobian(snes,J,P,NULL,NULL)); 1546 PetscCall(TSGetDM(ts,&dm)); 1547 PetscCall(DMTSGetI2Jacobian(dm,jac,ctx)); 1548 PetscFunctionReturn(0); 1549 } 1550 1551 /*@ 1552 TSComputeI2Function - Evaluates the DAE residual written in implicit form F(t,U,U_t,U_tt) = 0 1553 1554 Collective on TS 1555 1556 Input Parameters: 1557 + ts - the TS context 1558 . t - current time 1559 . U - state vector 1560 . V - time derivative of state vector (U_t) 1561 - A - second time derivative of state vector (U_tt) 1562 1563 Output Parameter: 1564 . F - the residual vector 1565 1566 Note: 1567 Most users should not need to explicitly call this routine, as it 1568 is used internally within the nonlinear solvers. 1569 1570 Level: developer 1571 1572 .seealso: `TSSetI2Function()`, `TSGetI2Function()` 1573 @*/ 1574 PetscErrorCode TSComputeI2Function(TS ts,PetscReal t,Vec U,Vec V,Vec A,Vec F) 1575 { 1576 DM dm; 1577 TSI2Function I2Function; 1578 void *ctx; 1579 TSRHSFunction rhsfunction; 1580 1581 PetscFunctionBegin; 1582 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1583 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 1584 PetscValidHeaderSpecific(V,VEC_CLASSID,4); 1585 PetscValidHeaderSpecific(A,VEC_CLASSID,5); 1586 PetscValidHeaderSpecific(F,VEC_CLASSID,6); 1587 1588 PetscCall(TSGetDM(ts,&dm)); 1589 PetscCall(DMTSGetI2Function(dm,&I2Function,&ctx)); 1590 PetscCall(DMTSGetRHSFunction(dm,&rhsfunction,NULL)); 1591 1592 if (!I2Function) { 1593 PetscCall(TSComputeIFunction(ts,t,U,A,F,PETSC_FALSE)); 1594 PetscFunctionReturn(0); 1595 } 1596 1597 PetscCall(PetscLogEventBegin(TS_FunctionEval,ts,U,V,F)); 1598 1599 PetscCallBack("TS callback implicit function",I2Function(ts,t,U,V,A,F,ctx)); 1600 1601 if (rhsfunction) { 1602 Vec Frhs; 1603 PetscCall(TSGetRHSVec_Private(ts,&Frhs)); 1604 PetscCall(TSComputeRHSFunction(ts,t,U,Frhs)); 1605 PetscCall(VecAXPY(F,-1,Frhs)); 1606 } 1607 1608 PetscCall(PetscLogEventEnd(TS_FunctionEval,ts,U,V,F)); 1609 PetscFunctionReturn(0); 1610 } 1611 1612 /*@ 1613 TSComputeI2Jacobian - Evaluates the Jacobian of the DAE 1614 1615 Collective on TS 1616 1617 Input Parameters: 1618 + ts - the TS context 1619 . t - current timestep 1620 . U - state vector 1621 . V - time derivative of state vector 1622 . A - second time derivative of state vector 1623 . shiftV - shift to apply, see note below 1624 - shiftA - shift to apply, see note below 1625 1626 Output Parameters: 1627 + J - Jacobian matrix 1628 - P - optional preconditioning matrix 1629 1630 Notes: 1631 If F(t,U,V,A)=0 is the DAE, the required Jacobian is 1632 1633 dF/dU + shiftV*dF/dV + shiftA*dF/dA 1634 1635 Most users should not need to explicitly call this routine, as it 1636 is used internally within the nonlinear solvers. 1637 1638 Level: developer 1639 1640 .seealso: `TSSetI2Jacobian()` 1641 @*/ 1642 PetscErrorCode TSComputeI2Jacobian(TS ts,PetscReal t,Vec U,Vec V,Vec A,PetscReal shiftV,PetscReal shiftA,Mat J,Mat P) 1643 { 1644 DM dm; 1645 TSI2Jacobian I2Jacobian; 1646 void *ctx; 1647 TSRHSJacobian rhsjacobian; 1648 1649 PetscFunctionBegin; 1650 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1651 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 1652 PetscValidHeaderSpecific(V,VEC_CLASSID,4); 1653 PetscValidHeaderSpecific(A,VEC_CLASSID,5); 1654 PetscValidHeaderSpecific(J,MAT_CLASSID,8); 1655 PetscValidHeaderSpecific(P,MAT_CLASSID,9); 1656 1657 PetscCall(TSGetDM(ts,&dm)); 1658 PetscCall(DMTSGetI2Jacobian(dm,&I2Jacobian,&ctx)); 1659 PetscCall(DMTSGetRHSJacobian(dm,&rhsjacobian,NULL)); 1660 1661 if (!I2Jacobian) { 1662 PetscCall(TSComputeIJacobian(ts,t,U,A,shiftA,J,P,PETSC_FALSE)); 1663 PetscFunctionReturn(0); 1664 } 1665 1666 PetscCall(PetscLogEventBegin(TS_JacobianEval,ts,U,J,P)); 1667 PetscCallBack("TS callback implicit Jacobian",I2Jacobian(ts,t,U,V,A,shiftV,shiftA,J,P,ctx)); 1668 if (rhsjacobian) { 1669 Mat Jrhs,Prhs; 1670 PetscCall(TSGetRHSMats_Private(ts,&Jrhs,&Prhs)); 1671 PetscCall(TSComputeRHSJacobian(ts,t,U,Jrhs,Prhs)); 1672 PetscCall(MatAXPY(J,-1,Jrhs,ts->axpy_pattern)); 1673 if (P != J) PetscCall(MatAXPY(P,-1,Prhs,ts->axpy_pattern)); 1674 } 1675 1676 PetscCall(PetscLogEventEnd(TS_JacobianEval,ts,U,J,P)); 1677 PetscFunctionReturn(0); 1678 } 1679 1680 /*@C 1681 TSSetTransientVariable - sets function to transform from state to transient variables 1682 1683 Logically Collective 1684 1685 Input Parameters: 1686 + ts - time stepping context on which to change the transient variable 1687 . tvar - a function that transforms to transient variables 1688 - ctx - a context for tvar 1689 1690 Calling sequence of tvar: 1691 $ PetscErrorCode tvar(TS ts,Vec p,Vec c,void *ctx); 1692 1693 + ts - timestep context 1694 . p - input vector (primitive form) 1695 . c - output vector, transient variables (conservative form) 1696 - ctx - [optional] user-defined function context 1697 1698 Level: advanced 1699 1700 Notes: 1701 This is typically used to transform from primitive to conservative variables so that a time integrator (e.g., TSBDF) 1702 can be conservative. In this context, primitive variables P are used to model the state (e.g., because they lead to 1703 well-conditioned formulations even in limiting cases such as low-Mach or zero porosity). The transient variable is 1704 C(P), specified by calling this function. An IFunction thus receives arguments (P, Cdot) and the IJacobian must be 1705 evaluated via the chain rule, as in 1706 1707 dF/dP + shift * dF/dCdot dC/dP. 1708 1709 .seealso: `DMTSSetTransientVariable()`, `DMTSGetTransientVariable()`, `TSSetIFunction()`, `TSSetIJacobian()` 1710 @*/ 1711 PetscErrorCode TSSetTransientVariable(TS ts,TSTransientVariable tvar,void *ctx) 1712 { 1713 DM dm; 1714 1715 PetscFunctionBegin; 1716 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1717 PetscCall(TSGetDM(ts,&dm)); 1718 PetscCall(DMTSSetTransientVariable(dm,tvar,ctx)); 1719 PetscFunctionReturn(0); 1720 } 1721 1722 /*@ 1723 TSComputeTransientVariable - transforms state (primitive) variables to transient (conservative) variables 1724 1725 Logically Collective 1726 1727 Input Parameters: 1728 + ts - TS on which to compute 1729 - U - state vector to be transformed to transient variables 1730 1731 Output Parameters: 1732 . C - transient (conservative) variable 1733 1734 Developer Notes: 1735 If DMTSSetTransientVariable() has not been called, then C is not modified in this routine and C=NULL is allowed. 1736 This makes it safe to call without a guard. One can use TSHasTransientVariable() to check if transient variables are 1737 being used. 1738 1739 Level: developer 1740 1741 .seealso: `DMTSSetTransientVariable()`, `TSComputeIFunction()`, `TSComputeIJacobian()` 1742 @*/ 1743 PetscErrorCode TSComputeTransientVariable(TS ts,Vec U,Vec C) 1744 { 1745 DM dm; 1746 DMTS dmts; 1747 1748 PetscFunctionBegin; 1749 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1750 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 1751 PetscCall(TSGetDM(ts,&dm)); 1752 PetscCall(DMGetDMTS(dm,&dmts)); 1753 if (dmts->ops->transientvar) { 1754 PetscValidHeaderSpecific(C,VEC_CLASSID,3); 1755 PetscCall((*dmts->ops->transientvar)(ts,U,C,dmts->transientvarctx)); 1756 } 1757 PetscFunctionReturn(0); 1758 } 1759 1760 /*@ 1761 TSHasTransientVariable - determine whether transient variables have been set 1762 1763 Logically Collective 1764 1765 Input Parameters: 1766 . ts - TS on which to compute 1767 1768 Output Parameters: 1769 . has - PETSC_TRUE if transient variables have been set 1770 1771 Level: developer 1772 1773 .seealso: `DMTSSetTransientVariable()`, `TSComputeTransientVariable()` 1774 @*/ 1775 PetscErrorCode TSHasTransientVariable(TS ts,PetscBool *has) 1776 { 1777 DM dm; 1778 DMTS dmts; 1779 1780 PetscFunctionBegin; 1781 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1782 PetscCall(TSGetDM(ts,&dm)); 1783 PetscCall(DMGetDMTS(dm,&dmts)); 1784 *has = dmts->ops->transientvar ? PETSC_TRUE : PETSC_FALSE; 1785 PetscFunctionReturn(0); 1786 } 1787 1788 /*@ 1789 TS2SetSolution - Sets the initial solution and time derivative vectors 1790 for use by the TS routines handling second order equations. 1791 1792 Logically Collective on TS 1793 1794 Input Parameters: 1795 + ts - the TS context obtained from TSCreate() 1796 . u - the solution vector 1797 - v - the time derivative vector 1798 1799 Level: beginner 1800 1801 @*/ 1802 PetscErrorCode TS2SetSolution(TS ts,Vec u,Vec v) 1803 { 1804 PetscFunctionBegin; 1805 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1806 PetscValidHeaderSpecific(u,VEC_CLASSID,2); 1807 PetscValidHeaderSpecific(v,VEC_CLASSID,3); 1808 PetscCall(TSSetSolution(ts,u)); 1809 PetscCall(PetscObjectReference((PetscObject)v)); 1810 PetscCall(VecDestroy(&ts->vec_dot)); 1811 ts->vec_dot = v; 1812 PetscFunctionReturn(0); 1813 } 1814 1815 /*@ 1816 TS2GetSolution - Returns the solution and time derivative at the present timestep 1817 for second order equations. It is valid to call this routine inside the function 1818 that you are evaluating in order to move to the new timestep. This vector not 1819 changed until the solution at the next timestep has been calculated. 1820 1821 Not Collective, but Vec returned is parallel if TS is parallel 1822 1823 Input Parameter: 1824 . ts - the TS context obtained from TSCreate() 1825 1826 Output Parameters: 1827 + u - the vector containing the solution 1828 - v - the vector containing the time derivative 1829 1830 Level: intermediate 1831 1832 .seealso: `TS2SetSolution()`, `TSGetTimeStep()`, `TSGetTime()` 1833 1834 @*/ 1835 PetscErrorCode TS2GetSolution(TS ts,Vec *u,Vec *v) 1836 { 1837 PetscFunctionBegin; 1838 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1839 if (u) PetscValidPointer(u,2); 1840 if (v) PetscValidPointer(v,3); 1841 if (u) *u = ts->vec_sol; 1842 if (v) *v = ts->vec_dot; 1843 PetscFunctionReturn(0); 1844 } 1845 1846 /*@C 1847 TSLoad - Loads a KSP that has been stored in binary with KSPView(). 1848 1849 Collective on PetscViewer 1850 1851 Input Parameters: 1852 + newdm - the newly loaded TS, this needs to have been created with TSCreate() or 1853 some related function before a call to TSLoad(). 1854 - viewer - binary file viewer, obtained from PetscViewerBinaryOpen() 1855 1856 Level: intermediate 1857 1858 Notes: 1859 The type is determined by the data in the file, any type set into the TS before this call is ignored. 1860 1861 Notes for advanced users: 1862 Most users should not need to know the details of the binary storage 1863 format, since TSLoad() and TSView() completely hide these details. 1864 But for anyone who's interested, the standard binary matrix storage 1865 format is 1866 .vb 1867 has not yet been determined 1868 .ve 1869 1870 .seealso: `PetscViewerBinaryOpen()`, `TSView()`, `MatLoad()`, `VecLoad()` 1871 @*/ 1872 PetscErrorCode TSLoad(TS ts, PetscViewer viewer) 1873 { 1874 PetscBool isbinary; 1875 PetscInt classid; 1876 char type[256]; 1877 DMTS sdm; 1878 DM dm; 1879 1880 PetscFunctionBegin; 1881 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1882 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,2); 1883 PetscCall(PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary)); 1884 PetscCheck(isbinary,PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid viewer; open viewer with PetscViewerBinaryOpen()"); 1885 1886 PetscCall(PetscViewerBinaryRead(viewer,&classid,1,NULL,PETSC_INT)); 1887 PetscCheck(classid == TS_FILE_CLASSID,PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Not TS next in file"); 1888 PetscCall(PetscViewerBinaryRead(viewer,type,256,NULL,PETSC_CHAR)); 1889 PetscCall(TSSetType(ts, type)); 1890 PetscTryTypeMethod(ts,load,viewer); 1891 PetscCall(DMCreate(PetscObjectComm((PetscObject)ts),&dm)); 1892 PetscCall(DMLoad(dm,viewer)); 1893 PetscCall(TSSetDM(ts,dm)); 1894 PetscCall(DMCreateGlobalVector(ts->dm,&ts->vec_sol)); 1895 PetscCall(VecLoad(ts->vec_sol,viewer)); 1896 PetscCall(DMGetDMTS(ts->dm,&sdm)); 1897 PetscCall(DMTSLoad(sdm,viewer)); 1898 PetscFunctionReturn(0); 1899 } 1900 1901 #include <petscdraw.h> 1902 #if defined(PETSC_HAVE_SAWS) 1903 #include <petscviewersaws.h> 1904 #endif 1905 1906 /*@C 1907 TSViewFromOptions - View from Options 1908 1909 Collective on TS 1910 1911 Input Parameters: 1912 + A - the application ordering context 1913 . obj - Optional object 1914 - name - command line option 1915 1916 Level: intermediate 1917 .seealso: `TS`, `TSView`, `PetscObjectViewFromOptions()`, `TSCreate()` 1918 @*/ 1919 PetscErrorCode TSViewFromOptions(TS A,PetscObject obj,const char name[]) 1920 { 1921 PetscFunctionBegin; 1922 PetscValidHeaderSpecific(A,TS_CLASSID,1); 1923 PetscCall(PetscObjectViewFromOptions((PetscObject)A,obj,name)); 1924 PetscFunctionReturn(0); 1925 } 1926 1927 /*@C 1928 TSView - Prints the TS data structure. 1929 1930 Collective on TS 1931 1932 Input Parameters: 1933 + ts - the TS context obtained from TSCreate() 1934 - viewer - visualization context 1935 1936 Options Database Key: 1937 . -ts_view - calls TSView() at end of TSStep() 1938 1939 Notes: 1940 The available visualization contexts include 1941 + PETSC_VIEWER_STDOUT_SELF - standard output (default) 1942 - PETSC_VIEWER_STDOUT_WORLD - synchronized standard 1943 output where only the first processor opens 1944 the file. All other processors send their 1945 data to the first processor to print. 1946 1947 The user can open an alternative visualization context with 1948 PetscViewerASCIIOpen() - output to a specified file. 1949 1950 In the debugger you can do "call TSView(ts,0)" to display the TS solver. (The same holds for any PETSc object viewer). 1951 1952 Level: beginner 1953 1954 .seealso: `PetscViewerASCIIOpen()` 1955 @*/ 1956 PetscErrorCode TSView(TS ts,PetscViewer viewer) 1957 { 1958 TSType type; 1959 PetscBool iascii,isstring,isundials,isbinary,isdraw; 1960 DMTS sdm; 1961 #if defined(PETSC_HAVE_SAWS) 1962 PetscBool issaws; 1963 #endif 1964 1965 PetscFunctionBegin; 1966 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1967 if (!viewer) PetscCall(PetscViewerASCIIGetStdout(PetscObjectComm((PetscObject)ts),&viewer)); 1968 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,2); 1969 PetscCheckSameComm(ts,1,viewer,2); 1970 1971 PetscCall(PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii)); 1972 PetscCall(PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSTRING,&isstring)); 1973 PetscCall(PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary)); 1974 PetscCall(PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw)); 1975 #if defined(PETSC_HAVE_SAWS) 1976 PetscCall(PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSAWS,&issaws)); 1977 #endif 1978 if (iascii) { 1979 PetscCall(PetscObjectPrintClassNamePrefixType((PetscObject)ts,viewer)); 1980 if (ts->ops->view) { 1981 PetscCall(PetscViewerASCIIPushTab(viewer)); 1982 PetscUseTypeMethod(ts,view ,viewer); 1983 PetscCall(PetscViewerASCIIPopTab(viewer)); 1984 } 1985 if (ts->max_steps < PETSC_MAX_INT) PetscCall(PetscViewerASCIIPrintf(viewer," maximum steps=%" PetscInt_FMT "\n",ts->max_steps)); 1986 if (ts->max_time < PETSC_MAX_REAL) PetscCall(PetscViewerASCIIPrintf(viewer," maximum time=%g\n",(double)ts->max_time)); 1987 if (ts->ifuncs) PetscCall(PetscViewerASCIIPrintf(viewer," total number of I function evaluations=%" PetscInt_FMT "\n",ts->ifuncs)); 1988 if (ts->ijacs) PetscCall(PetscViewerASCIIPrintf(viewer," total number of I Jacobian evaluations=%" PetscInt_FMT "\n",ts->ijacs)); 1989 if (ts->rhsfuncs) PetscCall(PetscViewerASCIIPrintf(viewer," total number of RHS function evaluations=%" PetscInt_FMT "\n",ts->rhsfuncs)); 1990 if (ts->rhsjacs) PetscCall(PetscViewerASCIIPrintf(viewer," total number of RHS Jacobian evaluations=%" PetscInt_FMT "\n",ts->rhsjacs)); 1991 if (ts->usessnes) { 1992 PetscBool lin; 1993 if (ts->problem_type == TS_NONLINEAR) PetscCall(PetscViewerASCIIPrintf(viewer," total number of nonlinear solver iterations=%" PetscInt_FMT "\n",ts->snes_its)); 1994 PetscCall(PetscViewerASCIIPrintf(viewer," total number of linear solver iterations=%" PetscInt_FMT "\n",ts->ksp_its)); 1995 PetscCall(PetscObjectTypeCompareAny((PetscObject)ts->snes,&lin,SNESKSPONLY,SNESKSPTRANSPOSEONLY,"")); 1996 PetscCall(PetscViewerASCIIPrintf(viewer," total number of %slinear solve failures=%" PetscInt_FMT "\n",lin ? "" : "non",ts->num_snes_failures)); 1997 } 1998 PetscCall(PetscViewerASCIIPrintf(viewer," total number of rejected steps=%" PetscInt_FMT "\n",ts->reject)); 1999 if (ts->vrtol) PetscCall(PetscViewerASCIIPrintf(viewer," using vector of relative error tolerances, ")); 2000 else PetscCall(PetscViewerASCIIPrintf(viewer," using relative error tolerance of %g, ",(double)ts->rtol)); 2001 if (ts->vatol) PetscCall(PetscViewerASCIIPrintf(viewer," using vector of absolute error tolerances\n")); 2002 else PetscCall(PetscViewerASCIIPrintf(viewer," using absolute error tolerance of %g\n",(double)ts->atol)); 2003 PetscCall(PetscViewerASCIIPushTab(viewer)); 2004 PetscCall(TSAdaptView(ts->adapt,viewer)); 2005 PetscCall(PetscViewerASCIIPopTab(viewer)); 2006 } else if (isstring) { 2007 PetscCall(TSGetType(ts,&type)); 2008 PetscCall(PetscViewerStringSPrintf(viewer," TSType: %-7.7s",type)); 2009 PetscTryTypeMethod(ts,view,viewer); 2010 } else if (isbinary) { 2011 PetscInt classid = TS_FILE_CLASSID; 2012 MPI_Comm comm; 2013 PetscMPIInt rank; 2014 char type[256]; 2015 2016 PetscCall(PetscObjectGetComm((PetscObject)ts,&comm)); 2017 PetscCallMPI(MPI_Comm_rank(comm,&rank)); 2018 if (rank == 0) { 2019 PetscCall(PetscViewerBinaryWrite(viewer,&classid,1,PETSC_INT)); 2020 PetscCall(PetscStrncpy(type,((PetscObject)ts)->type_name,256)); 2021 PetscCall(PetscViewerBinaryWrite(viewer,type,256,PETSC_CHAR)); 2022 } 2023 PetscTryTypeMethod(ts,view,viewer); 2024 if (ts->adapt) PetscCall(TSAdaptView(ts->adapt,viewer)); 2025 PetscCall(DMView(ts->dm,viewer)); 2026 PetscCall(VecView(ts->vec_sol,viewer)); 2027 PetscCall(DMGetDMTS(ts->dm,&sdm)); 2028 PetscCall(DMTSView(sdm,viewer)); 2029 } else if (isdraw) { 2030 PetscDraw draw; 2031 char str[36]; 2032 PetscReal x,y,bottom,h; 2033 2034 PetscCall(PetscViewerDrawGetDraw(viewer,0,&draw)); 2035 PetscCall(PetscDrawGetCurrentPoint(draw,&x,&y)); 2036 PetscCall(PetscStrcpy(str,"TS: ")); 2037 PetscCall(PetscStrcat(str,((PetscObject)ts)->type_name)); 2038 PetscCall(PetscDrawStringBoxed(draw,x,y,PETSC_DRAW_BLACK,PETSC_DRAW_BLACK,str,NULL,&h)); 2039 bottom = y - h; 2040 PetscCall(PetscDrawPushCurrentPoint(draw,x,bottom)); 2041 PetscTryTypeMethod(ts,view,viewer); 2042 if (ts->adapt) PetscCall(TSAdaptView(ts->adapt,viewer)); 2043 if (ts->snes) PetscCall(SNESView(ts->snes,viewer)); 2044 PetscCall(PetscDrawPopCurrentPoint(draw)); 2045 #if defined(PETSC_HAVE_SAWS) 2046 } else if (issaws) { 2047 PetscMPIInt rank; 2048 const char *name; 2049 2050 PetscCall(PetscObjectGetName((PetscObject)ts,&name)); 2051 PetscCallMPI(MPI_Comm_rank(PETSC_COMM_WORLD,&rank)); 2052 if (!((PetscObject)ts)->amsmem && rank == 0) { 2053 char dir[1024]; 2054 2055 PetscCall(PetscObjectViewSAWs((PetscObject)ts,viewer)); 2056 PetscCall(PetscSNPrintf(dir,1024,"/PETSc/Objects/%s/time_step",name)); 2057 PetscCallSAWs(SAWs_Register,(dir,&ts->steps,1,SAWs_READ,SAWs_INT)); 2058 PetscCall(PetscSNPrintf(dir,1024,"/PETSc/Objects/%s/time",name)); 2059 PetscCallSAWs(SAWs_Register,(dir,&ts->ptime,1,SAWs_READ,SAWs_DOUBLE)); 2060 } 2061 PetscTryTypeMethod(ts,view,viewer); 2062 #endif 2063 } 2064 if (ts->snes && ts->usessnes) { 2065 PetscCall(PetscViewerASCIIPushTab(viewer)); 2066 PetscCall(SNESView(ts->snes,viewer)); 2067 PetscCall(PetscViewerASCIIPopTab(viewer)); 2068 } 2069 PetscCall(DMGetDMTS(ts->dm,&sdm)); 2070 PetscCall(DMTSView(sdm,viewer)); 2071 2072 PetscCall(PetscViewerASCIIPushTab(viewer)); 2073 PetscCall(PetscObjectTypeCompare((PetscObject)ts,TSSUNDIALS,&isundials)); 2074 PetscCall(PetscViewerASCIIPopTab(viewer)); 2075 PetscFunctionReturn(0); 2076 } 2077 2078 /*@ 2079 TSSetApplicationContext - Sets an optional user-defined context for 2080 the timesteppers. 2081 2082 Logically Collective on TS 2083 2084 Input Parameters: 2085 + ts - the TS context obtained from TSCreate() 2086 - usrP - optional user context 2087 2088 Fortran Notes: 2089 To use this from Fortran you must write a Fortran interface definition for this 2090 function that tells Fortran the Fortran derived data type that you are passing in as the ctx argument. 2091 2092 Level: intermediate 2093 2094 .seealso: `TSGetApplicationContext()` 2095 @*/ 2096 PetscErrorCode TSSetApplicationContext(TS ts,void *usrP) 2097 { 2098 PetscFunctionBegin; 2099 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2100 ts->user = usrP; 2101 PetscFunctionReturn(0); 2102 } 2103 2104 /*@ 2105 TSGetApplicationContext - Gets the user-defined context for the 2106 timestepper. 2107 2108 Not Collective 2109 2110 Input Parameter: 2111 . ts - the TS context obtained from TSCreate() 2112 2113 Output Parameter: 2114 . usrP - user context 2115 2116 Fortran Notes: 2117 To use this from Fortran you must write a Fortran interface definition for this 2118 function that tells Fortran the Fortran derived data type that you are passing in as the ctx argument. 2119 2120 Level: intermediate 2121 2122 .seealso: `TSSetApplicationContext()` 2123 @*/ 2124 PetscErrorCode TSGetApplicationContext(TS ts,void *usrP) 2125 { 2126 PetscFunctionBegin; 2127 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2128 *(void**)usrP = ts->user; 2129 PetscFunctionReturn(0); 2130 } 2131 2132 /*@ 2133 TSGetStepNumber - Gets the number of steps completed. 2134 2135 Not Collective 2136 2137 Input Parameter: 2138 . ts - the TS context obtained from TSCreate() 2139 2140 Output Parameter: 2141 . steps - number of steps completed so far 2142 2143 Level: intermediate 2144 2145 .seealso: `TSGetTime()`, `TSGetTimeStep()`, `TSSetPreStep()`, `TSSetPreStage()`, `TSSetPostStage()`, `TSSetPostStep()` 2146 @*/ 2147 PetscErrorCode TSGetStepNumber(TS ts,PetscInt *steps) 2148 { 2149 PetscFunctionBegin; 2150 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2151 PetscValidIntPointer(steps,2); 2152 *steps = ts->steps; 2153 PetscFunctionReturn(0); 2154 } 2155 2156 /*@ 2157 TSSetStepNumber - Sets the number of steps completed. 2158 2159 Logically Collective on TS 2160 2161 Input Parameters: 2162 + ts - the TS context 2163 - steps - number of steps completed so far 2164 2165 Notes: 2166 For most uses of the TS solvers the user need not explicitly call 2167 TSSetStepNumber(), as the step counter is appropriately updated in 2168 TSSolve()/TSStep()/TSRollBack(). Power users may call this routine to 2169 reinitialize timestepping by setting the step counter to zero (and time 2170 to the initial time) to solve a similar problem with different initial 2171 conditions or parameters. Other possible use case is to continue 2172 timestepping from a previously interrupted run in such a way that TS 2173 monitors will be called with a initial nonzero step counter. 2174 2175 Level: advanced 2176 2177 .seealso: `TSGetStepNumber()`, `TSSetTime()`, `TSSetTimeStep()`, `TSSetSolution()` 2178 @*/ 2179 PetscErrorCode TSSetStepNumber(TS ts,PetscInt steps) 2180 { 2181 PetscFunctionBegin; 2182 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2183 PetscValidLogicalCollectiveInt(ts,steps,2); 2184 PetscCheck(steps >= 0,PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Step number must be non-negative"); 2185 ts->steps = steps; 2186 PetscFunctionReturn(0); 2187 } 2188 2189 /*@ 2190 TSSetTimeStep - Allows one to reset the timestep at any time, 2191 useful for simple pseudo-timestepping codes. 2192 2193 Logically Collective on TS 2194 2195 Input Parameters: 2196 + ts - the TS context obtained from TSCreate() 2197 - time_step - the size of the timestep 2198 2199 Level: intermediate 2200 2201 .seealso: `TSGetTimeStep()`, `TSSetTime()` 2202 2203 @*/ 2204 PetscErrorCode TSSetTimeStep(TS ts,PetscReal time_step) 2205 { 2206 PetscFunctionBegin; 2207 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2208 PetscValidLogicalCollectiveReal(ts,time_step,2); 2209 ts->time_step = time_step; 2210 PetscFunctionReturn(0); 2211 } 2212 2213 /*@ 2214 TSSetExactFinalTime - Determines whether to adapt the final time step to 2215 match the exact final time, interpolate solution to the exact final time, 2216 or just return at the final time TS computed. 2217 2218 Logically Collective on TS 2219 2220 Input Parameters: 2221 + ts - the time-step context 2222 - eftopt - exact final time option 2223 2224 $ TS_EXACTFINALTIME_STEPOVER - Don't do anything if final time is exceeded 2225 $ TS_EXACTFINALTIME_INTERPOLATE - Interpolate back to final time 2226 $ TS_EXACTFINALTIME_MATCHSTEP - Adapt final time step to match the final time 2227 2228 Options Database: 2229 . -ts_exact_final_time <stepover,interpolate,matchstep> - select the final step at runtime 2230 2231 Warning: If you use the option TS_EXACTFINALTIME_STEPOVER the solution may be at a very different time 2232 then the final time you selected. 2233 2234 Level: beginner 2235 2236 .seealso: `TSExactFinalTimeOption`, `TSGetExactFinalTime()` 2237 @*/ 2238 PetscErrorCode TSSetExactFinalTime(TS ts,TSExactFinalTimeOption eftopt) 2239 { 2240 PetscFunctionBegin; 2241 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2242 PetscValidLogicalCollectiveEnum(ts,eftopt,2); 2243 ts->exact_final_time = eftopt; 2244 PetscFunctionReturn(0); 2245 } 2246 2247 /*@ 2248 TSGetExactFinalTime - Gets the exact final time option. 2249 2250 Not Collective 2251 2252 Input Parameter: 2253 . ts - the TS context 2254 2255 Output Parameter: 2256 . eftopt - exact final time option 2257 2258 Level: beginner 2259 2260 .seealso: `TSExactFinalTimeOption`, `TSSetExactFinalTime()` 2261 @*/ 2262 PetscErrorCode TSGetExactFinalTime(TS ts,TSExactFinalTimeOption *eftopt) 2263 { 2264 PetscFunctionBegin; 2265 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2266 PetscValidPointer(eftopt,2); 2267 *eftopt = ts->exact_final_time; 2268 PetscFunctionReturn(0); 2269 } 2270 2271 /*@ 2272 TSGetTimeStep - Gets the current timestep size. 2273 2274 Not Collective 2275 2276 Input Parameter: 2277 . ts - the TS context obtained from TSCreate() 2278 2279 Output Parameter: 2280 . dt - the current timestep size 2281 2282 Level: intermediate 2283 2284 .seealso: `TSSetTimeStep()`, `TSGetTime()` 2285 2286 @*/ 2287 PetscErrorCode TSGetTimeStep(TS ts,PetscReal *dt) 2288 { 2289 PetscFunctionBegin; 2290 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2291 PetscValidRealPointer(dt,2); 2292 *dt = ts->time_step; 2293 PetscFunctionReturn(0); 2294 } 2295 2296 /*@ 2297 TSGetSolution - Returns the solution at the present timestep. It 2298 is valid to call this routine inside the function that you are evaluating 2299 in order to move to the new timestep. This vector not changed until 2300 the solution at the next timestep has been calculated. 2301 2302 Not Collective, but Vec returned is parallel if TS is parallel 2303 2304 Input Parameter: 2305 . ts - the TS context obtained from TSCreate() 2306 2307 Output Parameter: 2308 . v - the vector containing the solution 2309 2310 Note: If you used TSSetExactFinalTime(ts,TS_EXACTFINALTIME_MATCHSTEP); this does not return the solution at the requested 2311 final time. It returns the solution at the next timestep. 2312 2313 Level: intermediate 2314 2315 .seealso: `TSGetTimeStep()`, `TSGetTime()`, `TSGetSolveTime()`, `TSGetSolutionComponents()`, `TSSetSolutionFunction()` 2316 2317 @*/ 2318 PetscErrorCode TSGetSolution(TS ts,Vec *v) 2319 { 2320 PetscFunctionBegin; 2321 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2322 PetscValidPointer(v,2); 2323 *v = ts->vec_sol; 2324 PetscFunctionReturn(0); 2325 } 2326 2327 /*@ 2328 TSGetSolutionComponents - Returns any solution components at the present 2329 timestep, if available for the time integration method being used. 2330 Solution components are quantities that share the same size and 2331 structure as the solution vector. 2332 2333 Not Collective, but Vec returned is parallel if TS is parallel 2334 2335 Parameters : 2336 + ts - the TS context obtained from TSCreate() (input parameter). 2337 . n - If v is PETSC_NULL, then the number of solution components is 2338 returned through n, else the n-th solution component is 2339 returned in v. 2340 - v - the vector containing the n-th solution component 2341 (may be PETSC_NULL to use this function to find out 2342 the number of solutions components). 2343 2344 Level: advanced 2345 2346 .seealso: `TSGetSolution()` 2347 2348 @*/ 2349 PetscErrorCode TSGetSolutionComponents(TS ts,PetscInt *n,Vec *v) 2350 { 2351 PetscFunctionBegin; 2352 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2353 if (!ts->ops->getsolutioncomponents) *n = 0; 2354 else PetscUseTypeMethod(ts,getsolutioncomponents ,n,v); 2355 PetscFunctionReturn(0); 2356 } 2357 2358 /*@ 2359 TSGetAuxSolution - Returns an auxiliary solution at the present 2360 timestep, if available for the time integration method being used. 2361 2362 Not Collective, but Vec returned is parallel if TS is parallel 2363 2364 Parameters : 2365 + ts - the TS context obtained from TSCreate() (input parameter). 2366 - v - the vector containing the auxiliary solution 2367 2368 Level: intermediate 2369 2370 .seealso: `TSGetSolution()` 2371 2372 @*/ 2373 PetscErrorCode TSGetAuxSolution(TS ts,Vec *v) 2374 { 2375 PetscFunctionBegin; 2376 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2377 if (ts->ops->getauxsolution) PetscUseTypeMethod(ts,getauxsolution,v); 2378 else PetscCall(VecZeroEntries(*v)); 2379 PetscFunctionReturn(0); 2380 } 2381 2382 /*@ 2383 TSGetTimeError - Returns the estimated error vector, if the chosen 2384 TSType has an error estimation functionality. 2385 2386 Not Collective, but Vec returned is parallel if TS is parallel 2387 2388 Note: MUST call after TSSetUp() 2389 2390 Parameters : 2391 + ts - the TS context obtained from TSCreate() (input parameter). 2392 . n - current estimate (n=0) or previous one (n=-1) 2393 - v - the vector containing the error (same size as the solution). 2394 2395 Level: intermediate 2396 2397 .seealso: `TSGetSolution()`, `TSSetTimeError()` 2398 2399 @*/ 2400 PetscErrorCode TSGetTimeError(TS ts,PetscInt n,Vec *v) 2401 { 2402 PetscFunctionBegin; 2403 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2404 if (ts->ops->gettimeerror) PetscUseTypeMethod(ts,gettimeerror,n,v); 2405 else PetscCall(VecZeroEntries(*v)); 2406 PetscFunctionReturn(0); 2407 } 2408 2409 /*@ 2410 TSSetTimeError - Sets the estimated error vector, if the chosen 2411 TSType has an error estimation functionality. This can be used 2412 to restart such a time integrator with a given error vector. 2413 2414 Not Collective, but Vec returned is parallel if TS is parallel 2415 2416 Parameters : 2417 + ts - the TS context obtained from TSCreate() (input parameter). 2418 - v - the vector containing the error (same size as the solution). 2419 2420 Level: intermediate 2421 2422 .seealso: `TSSetSolution()`, `TSGetTimeError)` 2423 2424 @*/ 2425 PetscErrorCode TSSetTimeError(TS ts,Vec v) 2426 { 2427 PetscFunctionBegin; 2428 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2429 PetscCheck(ts->setupcalled,PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call TSSetUp() first"); 2430 PetscTryTypeMethod(ts,settimeerror,v); 2431 PetscFunctionReturn(0); 2432 } 2433 2434 /* ----- Routines to initialize and destroy a timestepper ---- */ 2435 /*@ 2436 TSSetProblemType - Sets the type of problem to be solved. 2437 2438 Not collective 2439 2440 Input Parameters: 2441 + ts - The TS 2442 - type - One of TS_LINEAR, TS_NONLINEAR where these types refer to problems of the forms 2443 .vb 2444 U_t - A U = 0 (linear) 2445 U_t - A(t) U = 0 (linear) 2446 F(t,U,U_t) = 0 (nonlinear) 2447 .ve 2448 2449 Level: beginner 2450 2451 .seealso: `TSSetUp()`, `TSProblemType`, `TS` 2452 @*/ 2453 PetscErrorCode TSSetProblemType(TS ts, TSProblemType type) 2454 { 2455 PetscFunctionBegin; 2456 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 2457 ts->problem_type = type; 2458 if (type == TS_LINEAR) { 2459 SNES snes; 2460 PetscCall(TSGetSNES(ts,&snes)); 2461 PetscCall(SNESSetType(snes,SNESKSPONLY)); 2462 } 2463 PetscFunctionReturn(0); 2464 } 2465 2466 /*@C 2467 TSGetProblemType - Gets the type of problem to be solved. 2468 2469 Not collective 2470 2471 Input Parameter: 2472 . ts - The TS 2473 2474 Output Parameter: 2475 . type - One of TS_LINEAR, TS_NONLINEAR where these types refer to problems of the forms 2476 .vb 2477 M U_t = A U 2478 M(t) U_t = A(t) U 2479 F(t,U,U_t) 2480 .ve 2481 2482 Level: beginner 2483 2484 .seealso: `TSSetUp()`, `TSProblemType`, `TS` 2485 @*/ 2486 PetscErrorCode TSGetProblemType(TS ts, TSProblemType *type) 2487 { 2488 PetscFunctionBegin; 2489 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 2490 PetscValidIntPointer(type,2); 2491 *type = ts->problem_type; 2492 PetscFunctionReturn(0); 2493 } 2494 2495 /* 2496 Attempt to check/preset a default value for the exact final time option. This is needed at the beginning of TSSolve() and in TSSetUp() 2497 */ 2498 static PetscErrorCode TSSetExactFinalTimeDefault(TS ts) 2499 { 2500 PetscBool isnone; 2501 2502 PetscFunctionBegin; 2503 PetscCall(TSGetAdapt(ts,&ts->adapt)); 2504 PetscCall(TSAdaptSetDefaultType(ts->adapt,ts->default_adapt_type)); 2505 2506 PetscCall(PetscObjectTypeCompare((PetscObject)ts->adapt,TSADAPTNONE,&isnone)); 2507 if (!isnone && ts->exact_final_time == TS_EXACTFINALTIME_UNSPECIFIED) ts->exact_final_time = TS_EXACTFINALTIME_MATCHSTEP; 2508 else if (ts->exact_final_time == TS_EXACTFINALTIME_UNSPECIFIED) ts->exact_final_time = TS_EXACTFINALTIME_INTERPOLATE; 2509 PetscFunctionReturn(0); 2510 } 2511 2512 /*@ 2513 TSSetUp - Sets up the internal data structures for the later use of a timestepper. 2514 2515 Collective on TS 2516 2517 Input Parameter: 2518 . ts - the TS context obtained from TSCreate() 2519 2520 Notes: 2521 For basic use of the TS solvers the user need not explicitly call 2522 TSSetUp(), since these actions will automatically occur during 2523 the call to TSStep() or TSSolve(). However, if one wishes to control this 2524 phase separately, TSSetUp() should be called after TSCreate() 2525 and optional routines of the form TSSetXXX(), but before TSStep() and TSSolve(). 2526 2527 Level: advanced 2528 2529 .seealso: `TSCreate()`, `TSStep()`, `TSDestroy()`, `TSSolve()` 2530 @*/ 2531 PetscErrorCode TSSetUp(TS ts) 2532 { 2533 DM dm; 2534 PetscErrorCode (*func)(SNES,Vec,Vec,void*); 2535 PetscErrorCode (*jac)(SNES,Vec,Mat,Mat,void*); 2536 TSIFunction ifun; 2537 TSIJacobian ijac; 2538 TSI2Jacobian i2jac; 2539 TSRHSJacobian rhsjac; 2540 2541 PetscFunctionBegin; 2542 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2543 if (ts->setupcalled) PetscFunctionReturn(0); 2544 2545 if (!((PetscObject)ts)->type_name) { 2546 PetscCall(TSGetIFunction(ts,NULL,&ifun,NULL)); 2547 PetscCall(TSSetType(ts,ifun ? TSBEULER : TSEULER)); 2548 } 2549 2550 if (!ts->vec_sol) { 2551 PetscCheck(ts->dm,PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call TSSetSolution() first"); 2552 PetscCall(DMCreateGlobalVector(ts->dm,&ts->vec_sol)); 2553 } 2554 2555 if (ts->tspan) { 2556 if (!ts->tspan->vecs_sol) PetscCall(VecDuplicateVecs(ts->vec_sol,ts->tspan->num_span_times,&ts->tspan->vecs_sol)); 2557 } 2558 if (!ts->Jacp && ts->Jacprhs) { /* IJacobianP shares the same matrix with RHSJacobianP if only RHSJacobianP is provided */ 2559 PetscCall(PetscObjectReference((PetscObject)ts->Jacprhs)); 2560 ts->Jacp = ts->Jacprhs; 2561 } 2562 2563 if (ts->quadraturets) { 2564 PetscCall(TSSetUp(ts->quadraturets)); 2565 PetscCall(VecDestroy(&ts->vec_costintegrand)); 2566 PetscCall(VecDuplicate(ts->quadraturets->vec_sol,&ts->vec_costintegrand)); 2567 } 2568 2569 PetscCall(TSGetRHSJacobian(ts,NULL,NULL,&rhsjac,NULL)); 2570 if (rhsjac == TSComputeRHSJacobianConstant) { 2571 Mat Amat,Pmat; 2572 SNES snes; 2573 PetscCall(TSGetSNES(ts,&snes)); 2574 PetscCall(SNESGetJacobian(snes,&Amat,&Pmat,NULL,NULL)); 2575 /* Matching matrices implies that an IJacobian is NOT set, because if it had been set, the IJacobian's matrix would 2576 * have displaced the RHS matrix */ 2577 if (Amat && Amat == ts->Arhs) { 2578 /* 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 */ 2579 PetscCall(MatDuplicate(ts->Arhs,MAT_COPY_VALUES,&Amat)); 2580 PetscCall(SNESSetJacobian(snes,Amat,NULL,NULL,NULL)); 2581 PetscCall(MatDestroy(&Amat)); 2582 } 2583 if (Pmat && Pmat == ts->Brhs) { 2584 PetscCall(MatDuplicate(ts->Brhs,MAT_COPY_VALUES,&Pmat)); 2585 PetscCall(SNESSetJacobian(snes,NULL,Pmat,NULL,NULL)); 2586 PetscCall(MatDestroy(&Pmat)); 2587 } 2588 } 2589 2590 PetscCall(TSGetAdapt(ts,&ts->adapt)); 2591 PetscCall(TSAdaptSetDefaultType(ts->adapt,ts->default_adapt_type)); 2592 2593 PetscTryTypeMethod(ts,setup); 2594 2595 PetscCall(TSSetExactFinalTimeDefault(ts)); 2596 2597 /* In the case where we've set a DMTSFunction or what have you, we need the default SNESFunction 2598 to be set right but can't do it elsewhere due to the overreliance on ctx=ts. 2599 */ 2600 PetscCall(TSGetDM(ts,&dm)); 2601 PetscCall(DMSNESGetFunction(dm,&func,NULL)); 2602 if (!func) PetscCall(DMSNESSetFunction(dm,SNESTSFormFunction,ts)); 2603 2604 /* If the SNES doesn't have a jacobian set and the TS has an ijacobian or rhsjacobian set, set the SNES to use it. 2605 Otherwise, the SNES will use coloring internally to form the Jacobian. 2606 */ 2607 PetscCall(DMSNESGetJacobian(dm,&jac,NULL)); 2608 PetscCall(DMTSGetIJacobian(dm,&ijac,NULL)); 2609 PetscCall(DMTSGetI2Jacobian(dm,&i2jac,NULL)); 2610 PetscCall(DMTSGetRHSJacobian(dm,&rhsjac,NULL)); 2611 if (!jac && (ijac || i2jac || rhsjac)) PetscCall(DMSNESSetJacobian(dm,SNESTSFormJacobian,ts)); 2612 2613 /* if time integration scheme has a starting method, call it */ 2614 PetscTryTypeMethod(ts,startingmethod); 2615 2616 ts->setupcalled = PETSC_TRUE; 2617 PetscFunctionReturn(0); 2618 } 2619 2620 /*@ 2621 TSReset - Resets a TS context and removes any allocated Vecs and Mats. 2622 2623 Collective on TS 2624 2625 Input Parameter: 2626 . ts - the TS context obtained from TSCreate() 2627 2628 Level: beginner 2629 2630 .seealso: `TSCreate()`, `TSSetup()`, `TSDestroy()` 2631 @*/ 2632 PetscErrorCode TSReset(TS ts) 2633 { 2634 TS_RHSSplitLink ilink = ts->tsrhssplit,next; 2635 2636 PetscFunctionBegin; 2637 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2638 2639 PetscTryTypeMethod(ts,reset); 2640 if (ts->snes) PetscCall(SNESReset(ts->snes)); 2641 if (ts->adapt) PetscCall(TSAdaptReset(ts->adapt)); 2642 2643 PetscCall(MatDestroy(&ts->Arhs)); 2644 PetscCall(MatDestroy(&ts->Brhs)); 2645 PetscCall(VecDestroy(&ts->Frhs)); 2646 PetscCall(VecDestroy(&ts->vec_sol)); 2647 PetscCall(VecDestroy(&ts->vec_dot)); 2648 PetscCall(VecDestroy(&ts->vatol)); 2649 PetscCall(VecDestroy(&ts->vrtol)); 2650 PetscCall(VecDestroyVecs(ts->nwork,&ts->work)); 2651 2652 PetscCall(MatDestroy(&ts->Jacprhs)); 2653 PetscCall(MatDestroy(&ts->Jacp)); 2654 if (ts->forward_solve) PetscCall(TSForwardReset(ts)); 2655 if (ts->quadraturets) { 2656 PetscCall(TSReset(ts->quadraturets)); 2657 PetscCall(VecDestroy(&ts->vec_costintegrand)); 2658 } 2659 while (ilink) { 2660 next = ilink->next; 2661 PetscCall(TSDestroy(&ilink->ts)); 2662 PetscCall(PetscFree(ilink->splitname)); 2663 PetscCall(ISDestroy(&ilink->is)); 2664 PetscCall(PetscFree(ilink)); 2665 ilink = next; 2666 } 2667 ts->tsrhssplit = NULL; 2668 ts->num_rhs_splits = 0; 2669 if (ts->tspan) { 2670 PetscCall(PetscFree(ts->tspan->span_times)); 2671 PetscCall(VecDestroyVecs(ts->tspan->num_span_times,&ts->tspan->vecs_sol)); 2672 PetscCall(PetscFree(ts->tspan)); 2673 } 2674 ts->setupcalled = PETSC_FALSE; 2675 PetscFunctionReturn(0); 2676 } 2677 2678 /*@C 2679 TSDestroy - Destroys the timestepper context that was created 2680 with TSCreate(). 2681 2682 Collective on TS 2683 2684 Input Parameter: 2685 . ts - the TS context obtained from TSCreate() 2686 2687 Level: beginner 2688 2689 .seealso: `TSCreate()`, `TSSetUp()`, `TSSolve()` 2690 @*/ 2691 PetscErrorCode TSDestroy(TS *ts) 2692 { 2693 PetscFunctionBegin; 2694 if (!*ts) PetscFunctionReturn(0); 2695 PetscValidHeaderSpecific(*ts,TS_CLASSID,1); 2696 if (--((PetscObject)(*ts))->refct > 0) {*ts = NULL; PetscFunctionReturn(0);} 2697 2698 PetscCall(TSReset(*ts)); 2699 PetscCall(TSAdjointReset(*ts)); 2700 if ((*ts)->forward_solve) PetscCall(TSForwardReset(*ts)); 2701 2702 /* if memory was published with SAWs then destroy it */ 2703 PetscCall(PetscObjectSAWsViewOff((PetscObject)*ts)); 2704 PetscTryTypeMethod((*ts),destroy); 2705 2706 PetscCall(TSTrajectoryDestroy(&(*ts)->trajectory)); 2707 2708 PetscCall(TSAdaptDestroy(&(*ts)->adapt)); 2709 PetscCall(TSEventDestroy(&(*ts)->event)); 2710 2711 PetscCall(SNESDestroy(&(*ts)->snes)); 2712 PetscCall(DMDestroy(&(*ts)->dm)); 2713 PetscCall(TSMonitorCancel((*ts))); 2714 PetscCall(TSAdjointMonitorCancel((*ts))); 2715 2716 PetscCall(TSDestroy(&(*ts)->quadraturets)); 2717 PetscCall(PetscHeaderDestroy(ts)); 2718 PetscFunctionReturn(0); 2719 } 2720 2721 /*@ 2722 TSGetSNES - Returns the SNES (nonlinear solver) associated with 2723 a TS (timestepper) context. Valid only for nonlinear problems. 2724 2725 Not Collective, but SNES is parallel if TS is parallel 2726 2727 Input Parameter: 2728 . ts - the TS context obtained from TSCreate() 2729 2730 Output Parameter: 2731 . snes - the nonlinear solver context 2732 2733 Notes: 2734 The user can then directly manipulate the SNES context to set various 2735 options, etc. Likewise, the user can then extract and manipulate the 2736 KSP, KSP, and PC contexts as well. 2737 2738 TSGetSNES() does not work for integrators that do not use SNES; in 2739 this case TSGetSNES() returns NULL in snes. 2740 2741 Level: beginner 2742 2743 @*/ 2744 PetscErrorCode TSGetSNES(TS ts,SNES *snes) 2745 { 2746 PetscFunctionBegin; 2747 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2748 PetscValidPointer(snes,2); 2749 if (!ts->snes) { 2750 PetscCall(SNESCreate(PetscObjectComm((PetscObject)ts),&ts->snes)); 2751 PetscCall(PetscObjectSetOptions((PetscObject)ts->snes,((PetscObject)ts)->options)); 2752 PetscCall(SNESSetFunction(ts->snes,NULL,SNESTSFormFunction,ts)); 2753 PetscCall(PetscLogObjectParent((PetscObject)ts,(PetscObject)ts->snes)); 2754 PetscCall(PetscObjectIncrementTabLevel((PetscObject)ts->snes,(PetscObject)ts,1)); 2755 if (ts->dm) PetscCall(SNESSetDM(ts->snes,ts->dm)); 2756 if (ts->problem_type == TS_LINEAR) PetscCall(SNESSetType(ts->snes,SNESKSPONLY)); 2757 } 2758 *snes = ts->snes; 2759 PetscFunctionReturn(0); 2760 } 2761 2762 /*@ 2763 TSSetSNES - Set the SNES (nonlinear solver) to be used by the timestepping context 2764 2765 Collective 2766 2767 Input Parameters: 2768 + ts - the TS context obtained from TSCreate() 2769 - snes - the nonlinear solver context 2770 2771 Notes: 2772 Most users should have the TS created by calling TSGetSNES() 2773 2774 Level: developer 2775 2776 @*/ 2777 PetscErrorCode TSSetSNES(TS ts,SNES snes) 2778 { 2779 PetscErrorCode (*func)(SNES,Vec,Mat,Mat,void*); 2780 2781 PetscFunctionBegin; 2782 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2783 PetscValidHeaderSpecific(snes,SNES_CLASSID,2); 2784 PetscCall(PetscObjectReference((PetscObject)snes)); 2785 PetscCall(SNESDestroy(&ts->snes)); 2786 2787 ts->snes = snes; 2788 2789 PetscCall(SNESSetFunction(ts->snes,NULL,SNESTSFormFunction,ts)); 2790 PetscCall(SNESGetJacobian(ts->snes,NULL,NULL,&func,NULL)); 2791 if (func == SNESTSFormJacobian) PetscCall(SNESSetJacobian(ts->snes,NULL,NULL,SNESTSFormJacobian,ts)); 2792 PetscFunctionReturn(0); 2793 } 2794 2795 /*@ 2796 TSGetKSP - Returns the KSP (linear solver) associated with 2797 a TS (timestepper) context. 2798 2799 Not Collective, but KSP is parallel if TS is parallel 2800 2801 Input Parameter: 2802 . ts - the TS context obtained from TSCreate() 2803 2804 Output Parameter: 2805 . ksp - the nonlinear solver context 2806 2807 Notes: 2808 The user can then directly manipulate the KSP context to set various 2809 options, etc. Likewise, the user can then extract and manipulate the 2810 KSP and PC contexts as well. 2811 2812 TSGetKSP() does not work for integrators that do not use KSP; 2813 in this case TSGetKSP() returns NULL in ksp. 2814 2815 Level: beginner 2816 2817 @*/ 2818 PetscErrorCode TSGetKSP(TS ts,KSP *ksp) 2819 { 2820 SNES snes; 2821 2822 PetscFunctionBegin; 2823 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2824 PetscValidPointer(ksp,2); 2825 PetscCheck(((PetscObject)ts)->type_name,PETSC_COMM_SELF,PETSC_ERR_ARG_NULL,"KSP is not created yet. Call TSSetType() first"); 2826 PetscCheck(ts->problem_type == TS_LINEAR,PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Linear only; use TSGetSNES()"); 2827 PetscCall(TSGetSNES(ts,&snes)); 2828 PetscCall(SNESGetKSP(snes,ksp)); 2829 PetscFunctionReturn(0); 2830 } 2831 2832 /* ----------- Routines to set solver parameters ---------- */ 2833 2834 /*@ 2835 TSSetMaxSteps - Sets the maximum number of steps to use. 2836 2837 Logically Collective on TS 2838 2839 Input Parameters: 2840 + ts - the TS context obtained from TSCreate() 2841 - maxsteps - maximum number of steps to use 2842 2843 Options Database Keys: 2844 . -ts_max_steps <maxsteps> - Sets maxsteps 2845 2846 Notes: 2847 The default maximum number of steps is 5000 2848 2849 Level: intermediate 2850 2851 .seealso: `TSGetMaxSteps()`, `TSSetMaxTime()`, `TSSetExactFinalTime()` 2852 @*/ 2853 PetscErrorCode TSSetMaxSteps(TS ts,PetscInt maxsteps) 2854 { 2855 PetscFunctionBegin; 2856 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2857 PetscValidLogicalCollectiveInt(ts,maxsteps,2); 2858 PetscCheck(maxsteps >= 0,PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Maximum number of steps must be non-negative"); 2859 ts->max_steps = maxsteps; 2860 PetscFunctionReturn(0); 2861 } 2862 2863 /*@ 2864 TSGetMaxSteps - Gets the maximum number of steps to use. 2865 2866 Not Collective 2867 2868 Input Parameters: 2869 . ts - the TS context obtained from TSCreate() 2870 2871 Output Parameter: 2872 . maxsteps - maximum number of steps to use 2873 2874 Level: advanced 2875 2876 .seealso: `TSSetMaxSteps()`, `TSGetMaxTime()`, `TSSetMaxTime()` 2877 @*/ 2878 PetscErrorCode TSGetMaxSteps(TS ts,PetscInt *maxsteps) 2879 { 2880 PetscFunctionBegin; 2881 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2882 PetscValidIntPointer(maxsteps,2); 2883 *maxsteps = ts->max_steps; 2884 PetscFunctionReturn(0); 2885 } 2886 2887 /*@ 2888 TSSetMaxTime - Sets the maximum (or final) time for timestepping. 2889 2890 Logically Collective on TS 2891 2892 Input Parameters: 2893 + ts - the TS context obtained from TSCreate() 2894 - maxtime - final time to step to 2895 2896 Options Database Keys: 2897 . -ts_max_time <maxtime> - Sets maxtime 2898 2899 Notes: 2900 The default maximum time is 5.0 2901 2902 Level: intermediate 2903 2904 .seealso: `TSGetMaxTime()`, `TSSetMaxSteps()`, `TSSetExactFinalTime()` 2905 @*/ 2906 PetscErrorCode TSSetMaxTime(TS ts,PetscReal maxtime) 2907 { 2908 PetscFunctionBegin; 2909 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2910 PetscValidLogicalCollectiveReal(ts,maxtime,2); 2911 ts->max_time = maxtime; 2912 PetscFunctionReturn(0); 2913 } 2914 2915 /*@ 2916 TSGetMaxTime - Gets the maximum (or final) time for timestepping. 2917 2918 Not Collective 2919 2920 Input Parameters: 2921 . ts - the TS context obtained from TSCreate() 2922 2923 Output Parameter: 2924 . maxtime - final time to step to 2925 2926 Level: advanced 2927 2928 .seealso: `TSSetMaxTime()`, `TSGetMaxSteps()`, `TSSetMaxSteps()` 2929 @*/ 2930 PetscErrorCode TSGetMaxTime(TS ts,PetscReal *maxtime) 2931 { 2932 PetscFunctionBegin; 2933 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2934 PetscValidRealPointer(maxtime,2); 2935 *maxtime = ts->max_time; 2936 PetscFunctionReturn(0); 2937 } 2938 2939 /*@ 2940 TSSetInitialTimeStep - Deprecated, use TSSetTime() and TSSetTimeStep(). 2941 2942 Level: deprecated 2943 2944 @*/ 2945 PetscErrorCode TSSetInitialTimeStep(TS ts,PetscReal initial_time,PetscReal time_step) 2946 { 2947 PetscFunctionBegin; 2948 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2949 PetscCall(TSSetTime(ts,initial_time)); 2950 PetscCall(TSSetTimeStep(ts,time_step)); 2951 PetscFunctionReturn(0); 2952 } 2953 2954 /*@ 2955 TSGetDuration - Deprecated, use TSGetMaxSteps() and TSGetMaxTime(). 2956 2957 Level: deprecated 2958 2959 @*/ 2960 PetscErrorCode TSGetDuration(TS ts, PetscInt *maxsteps, PetscReal *maxtime) 2961 { 2962 PetscFunctionBegin; 2963 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 2964 if (maxsteps) { 2965 PetscValidIntPointer(maxsteps,2); 2966 *maxsteps = ts->max_steps; 2967 } 2968 if (maxtime) { 2969 PetscValidRealPointer(maxtime,3); 2970 *maxtime = ts->max_time; 2971 } 2972 PetscFunctionReturn(0); 2973 } 2974 2975 /*@ 2976 TSSetDuration - Deprecated, use TSSetMaxSteps() and TSSetMaxTime(). 2977 2978 Level: deprecated 2979 2980 @*/ 2981 PetscErrorCode TSSetDuration(TS ts,PetscInt maxsteps,PetscReal maxtime) 2982 { 2983 PetscFunctionBegin; 2984 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2985 PetscValidLogicalCollectiveInt(ts,maxsteps,2); 2986 PetscValidLogicalCollectiveReal(ts,maxtime,3); 2987 if (maxsteps >= 0) ts->max_steps = maxsteps; 2988 if (maxtime != PETSC_DEFAULT) ts->max_time = maxtime; 2989 PetscFunctionReturn(0); 2990 } 2991 2992 /*@ 2993 TSGetTimeStepNumber - Deprecated, use TSGetStepNumber(). 2994 2995 Level: deprecated 2996 2997 @*/ 2998 PetscErrorCode TSGetTimeStepNumber(TS ts,PetscInt *steps) { return TSGetStepNumber(ts,steps); } 2999 3000 /*@ 3001 TSGetTotalSteps - Deprecated, use TSGetStepNumber(). 3002 3003 Level: deprecated 3004 3005 @*/ 3006 PetscErrorCode TSGetTotalSteps(TS ts,PetscInt *steps) { return TSGetStepNumber(ts,steps); } 3007 3008 /*@ 3009 TSSetSolution - Sets the initial solution vector 3010 for use by the TS routines. 3011 3012 Logically Collective on TS 3013 3014 Input Parameters: 3015 + ts - the TS context obtained from TSCreate() 3016 - u - the solution vector 3017 3018 Level: beginner 3019 3020 .seealso: `TSSetSolutionFunction()`, `TSGetSolution()`, `TSCreate()` 3021 @*/ 3022 PetscErrorCode TSSetSolution(TS ts,Vec u) 3023 { 3024 DM dm; 3025 3026 PetscFunctionBegin; 3027 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3028 PetscValidHeaderSpecific(u,VEC_CLASSID,2); 3029 PetscCall(PetscObjectReference((PetscObject)u)); 3030 PetscCall(VecDestroy(&ts->vec_sol)); 3031 ts->vec_sol = u; 3032 3033 PetscCall(TSGetDM(ts,&dm)); 3034 PetscCall(DMShellSetGlobalVector(dm,u)); 3035 PetscFunctionReturn(0); 3036 } 3037 3038 /*@C 3039 TSSetPreStep - Sets the general-purpose function 3040 called once at the beginning of each time step. 3041 3042 Logically Collective on TS 3043 3044 Input Parameters: 3045 + ts - The TS context obtained from TSCreate() 3046 - func - The function 3047 3048 Calling sequence of func: 3049 .vb 3050 PetscErrorCode func (TS ts); 3051 .ve 3052 3053 Level: intermediate 3054 3055 .seealso: `TSSetPreStage()`, `TSSetPostStage()`, `TSSetPostStep()`, `TSStep()`, `TSRestartStep()` 3056 @*/ 3057 PetscErrorCode TSSetPreStep(TS ts, PetscErrorCode (*func)(TS)) 3058 { 3059 PetscFunctionBegin; 3060 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3061 ts->prestep = func; 3062 PetscFunctionReturn(0); 3063 } 3064 3065 /*@ 3066 TSPreStep - Runs the user-defined pre-step function. 3067 3068 Collective on TS 3069 3070 Input Parameters: 3071 . ts - The TS context obtained from TSCreate() 3072 3073 Notes: 3074 TSPreStep() is typically used within time stepping implementations, 3075 so most users would not generally call this routine themselves. 3076 3077 Level: developer 3078 3079 .seealso: `TSSetPreStep()`, `TSPreStage()`, `TSPostStage()`, `TSPostStep()` 3080 @*/ 3081 PetscErrorCode TSPreStep(TS ts) 3082 { 3083 PetscFunctionBegin; 3084 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3085 if (ts->prestep) { 3086 Vec U; 3087 PetscObjectId idprev; 3088 PetscBool sameObject; 3089 PetscObjectState sprev,spost; 3090 3091 PetscCall(TSGetSolution(ts,&U)); 3092 PetscCall(PetscObjectGetId((PetscObject)U,&idprev)); 3093 PetscCall(PetscObjectStateGet((PetscObject)U,&sprev)); 3094 PetscCallBack("TS callback preset",(*ts->prestep)(ts)); 3095 PetscCall(TSGetSolution(ts,&U)); 3096 PetscCall(PetscObjectCompareId((PetscObject)U,idprev,&sameObject)); 3097 PetscCall(PetscObjectStateGet((PetscObject)U,&spost)); 3098 if (!sameObject || sprev != spost) PetscCall(TSRestartStep(ts)); 3099 } 3100 PetscFunctionReturn(0); 3101 } 3102 3103 /*@C 3104 TSSetPreStage - Sets the general-purpose function 3105 called once at the beginning of each stage. 3106 3107 Logically Collective on TS 3108 3109 Input Parameters: 3110 + ts - The TS context obtained from TSCreate() 3111 - func - The function 3112 3113 Calling sequence of func: 3114 .vb 3115 PetscErrorCode func(TS ts, PetscReal stagetime); 3116 .ve 3117 3118 Level: intermediate 3119 3120 Note: 3121 There may be several stages per time step. If the solve for a given stage fails, the step may be rejected and retried. 3122 The time step number being computed can be queried using TSGetStepNumber() and the total size of the step being 3123 attempted can be obtained using TSGetTimeStep(). The time at the start of the step is available via TSGetTime(). 3124 3125 .seealso: `TSSetPostStage()`, `TSSetPreStep()`, `TSSetPostStep()`, `TSGetApplicationContext()` 3126 @*/ 3127 PetscErrorCode TSSetPreStage(TS ts, PetscErrorCode (*func)(TS,PetscReal)) 3128 { 3129 PetscFunctionBegin; 3130 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3131 ts->prestage = func; 3132 PetscFunctionReturn(0); 3133 } 3134 3135 /*@C 3136 TSSetPostStage - Sets the general-purpose function 3137 called once at the end of each stage. 3138 3139 Logically Collective on TS 3140 3141 Input Parameters: 3142 + ts - The TS context obtained from TSCreate() 3143 - func - The function 3144 3145 Calling sequence of func: 3146 .vb 3147 PetscErrorCode func(TS ts, PetscReal stagetime, PetscInt stageindex, Vec* Y); 3148 .ve 3149 3150 Level: intermediate 3151 3152 Note: 3153 There may be several stages per time step. If the solve for a given stage fails, the step may be rejected and retried. 3154 The time step number being computed can be queried using TSGetStepNumber() and the total size of the step being 3155 attempted can be obtained using TSGetTimeStep(). The time at the start of the step is available via TSGetTime(). 3156 3157 .seealso: `TSSetPreStage()`, `TSSetPreStep()`, `TSSetPostStep()`, `TSGetApplicationContext()` 3158 @*/ 3159 PetscErrorCode TSSetPostStage(TS ts, PetscErrorCode (*func)(TS,PetscReal,PetscInt,Vec*)) 3160 { 3161 PetscFunctionBegin; 3162 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3163 ts->poststage = func; 3164 PetscFunctionReturn(0); 3165 } 3166 3167 /*@C 3168 TSSetPostEvaluate - Sets the general-purpose function 3169 called once at the end of each step evaluation. 3170 3171 Logically Collective on TS 3172 3173 Input Parameters: 3174 + ts - The TS context obtained from TSCreate() 3175 - func - The function 3176 3177 Calling sequence of func: 3178 .vb 3179 PetscErrorCode func(TS ts); 3180 .ve 3181 3182 Level: intermediate 3183 3184 Note: 3185 Semantically, TSSetPostEvaluate() differs from TSSetPostStep() since the function it sets is called before event-handling 3186 thus guaranteeing the same solution (computed by the time-stepper) will be passed to it. On the other hand, TSPostStep() 3187 may be passed a different solution, possibly changed by the event handler. TSPostEvaluate() is called after the next step 3188 solution is evaluated allowing to modify it, if need be. The solution can be obtained with TSGetSolution(), the time step 3189 with TSGetTimeStep(), and the time at the start of the step is available via TSGetTime() 3190 3191 .seealso: `TSSetPreStage()`, `TSSetPreStep()`, `TSSetPostStep()`, `TSGetApplicationContext()` 3192 @*/ 3193 PetscErrorCode TSSetPostEvaluate(TS ts, PetscErrorCode (*func)(TS)) 3194 { 3195 PetscFunctionBegin; 3196 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3197 ts->postevaluate = func; 3198 PetscFunctionReturn(0); 3199 } 3200 3201 /*@ 3202 TSPreStage - Runs the user-defined pre-stage function set using TSSetPreStage() 3203 3204 Collective on TS 3205 3206 Input Parameters: 3207 . ts - The TS context obtained from TSCreate() 3208 stagetime - The absolute time of the current stage 3209 3210 Notes: 3211 TSPreStage() is typically used within time stepping implementations, 3212 most users would not generally call this routine themselves. 3213 3214 Level: developer 3215 3216 .seealso: `TSPostStage()`, `TSSetPreStep()`, `TSPreStep()`, `TSPostStep()` 3217 @*/ 3218 PetscErrorCode TSPreStage(TS ts, PetscReal stagetime) 3219 { 3220 PetscFunctionBegin; 3221 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3222 if (ts->prestage) PetscCallBack("TS callback prestage",(*ts->prestage)(ts,stagetime)); 3223 PetscFunctionReturn(0); 3224 } 3225 3226 /*@ 3227 TSPostStage - Runs the user-defined post-stage function set using TSSetPostStage() 3228 3229 Collective on TS 3230 3231 Input Parameters: 3232 . ts - The TS context obtained from TSCreate() 3233 stagetime - The absolute time of the current stage 3234 stageindex - Stage number 3235 Y - Array of vectors (of size = total number 3236 of stages) with the stage solutions 3237 3238 Notes: 3239 TSPostStage() is typically used within time stepping implementations, 3240 most users would not generally call this routine themselves. 3241 3242 Level: developer 3243 3244 .seealso: `TSPreStage()`, `TSSetPreStep()`, `TSPreStep()`, `TSPostStep()` 3245 @*/ 3246 PetscErrorCode TSPostStage(TS ts, PetscReal stagetime, PetscInt stageindex, Vec *Y) 3247 { 3248 PetscFunctionBegin; 3249 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3250 if (ts->poststage) PetscCallBack("TS callback poststage",(*ts->poststage)(ts,stagetime,stageindex,Y)); 3251 PetscFunctionReturn(0); 3252 } 3253 3254 /*@ 3255 TSPostEvaluate - Runs the user-defined post-evaluate function set using TSSetPostEvaluate() 3256 3257 Collective on TS 3258 3259 Input Parameters: 3260 . ts - The TS context obtained from TSCreate() 3261 3262 Notes: 3263 TSPostEvaluate() is typically used within time stepping implementations, 3264 most users would not generally call this routine themselves. 3265 3266 Level: developer 3267 3268 .seealso: `TSSetPostEvaluate()`, `TSSetPreStep()`, `TSPreStep()`, `TSPostStep()` 3269 @*/ 3270 PetscErrorCode TSPostEvaluate(TS ts) 3271 { 3272 PetscFunctionBegin; 3273 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3274 if (ts->postevaluate) { 3275 Vec U; 3276 PetscObjectState sprev,spost; 3277 3278 PetscCall(TSGetSolution(ts,&U)); 3279 PetscCall(PetscObjectStateGet((PetscObject)U,&sprev)); 3280 PetscCallBack("TS callback postevaluate",(*ts->postevaluate)(ts)); 3281 PetscCall(PetscObjectStateGet((PetscObject)U,&spost)); 3282 if (sprev != spost) PetscCall(TSRestartStep(ts)); 3283 } 3284 PetscFunctionReturn(0); 3285 } 3286 3287 /*@C 3288 TSSetPostStep - Sets the general-purpose function 3289 called once at the end of each time step. 3290 3291 Logically Collective on TS 3292 3293 Input Parameters: 3294 + ts - The TS context obtained from TSCreate() 3295 - func - The function 3296 3297 Calling sequence of func: 3298 $ func (TS ts); 3299 3300 Notes: 3301 The function set by TSSetPostStep() is called after each successful step. The solution vector X 3302 obtained by TSGetSolution() may be different than that computed at the step end if the event handler 3303 locates an event and TSPostEvent() modifies it. Use TSSetPostEvaluate() if an unmodified solution is needed instead. 3304 3305 Level: intermediate 3306 3307 .seealso: `TSSetPreStep()`, `TSSetPreStage()`, `TSSetPostEvaluate()`, `TSGetTimeStep()`, `TSGetStepNumber()`, `TSGetTime()`, `TSRestartStep()` 3308 @*/ 3309 PetscErrorCode TSSetPostStep(TS ts, PetscErrorCode (*func)(TS)) 3310 { 3311 PetscFunctionBegin; 3312 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3313 ts->poststep = func; 3314 PetscFunctionReturn(0); 3315 } 3316 3317 /*@ 3318 TSPostStep - Runs the user-defined post-step function. 3319 3320 Collective on TS 3321 3322 Input Parameters: 3323 . ts - The TS context obtained from TSCreate() 3324 3325 Notes: 3326 TSPostStep() is typically used within time stepping implementations, 3327 so most users would not generally call this routine themselves. 3328 3329 Level: developer 3330 3331 @*/ 3332 PetscErrorCode TSPostStep(TS ts) 3333 { 3334 PetscFunctionBegin; 3335 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3336 if (ts->poststep) { 3337 Vec U; 3338 PetscObjectId idprev; 3339 PetscBool sameObject; 3340 PetscObjectState sprev,spost; 3341 3342 PetscCall(TSGetSolution(ts,&U)); 3343 PetscCall(PetscObjectGetId((PetscObject)U,&idprev)); 3344 PetscCall(PetscObjectStateGet((PetscObject)U,&sprev)); 3345 PetscCallBack("TS callback poststep",(*ts->poststep)(ts)); 3346 PetscCall(TSGetSolution(ts,&U)); 3347 PetscCall(PetscObjectCompareId((PetscObject)U,idprev,&sameObject)); 3348 PetscCall(PetscObjectStateGet((PetscObject)U,&spost)); 3349 if (!sameObject || sprev != spost) PetscCall(TSRestartStep(ts)); 3350 } 3351 PetscFunctionReturn(0); 3352 } 3353 3354 /*@ 3355 TSInterpolate - Interpolate the solution computed during the previous step to an arbitrary location in the interval 3356 3357 Collective on TS 3358 3359 Input Parameters: 3360 + ts - time stepping context 3361 - t - time to interpolate to 3362 3363 Output Parameter: 3364 . U - state at given time 3365 3366 Level: intermediate 3367 3368 Developer Notes: 3369 TSInterpolate() and the storing of previous steps/stages should be generalized to support delay differential equations and continuous adjoints. 3370 3371 .seealso: `TSSetExactFinalTime()`, `TSSolve()` 3372 @*/ 3373 PetscErrorCode TSInterpolate(TS ts,PetscReal t,Vec U) 3374 { 3375 PetscFunctionBegin; 3376 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3377 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 3378 PetscCheck(t >= ts->ptime_prev && t <= ts->ptime,PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Requested time %g not in last time steps [%g,%g]",(double)t,(double)ts->ptime_prev,(double)ts->ptime); 3379 PetscUseTypeMethod(ts,interpolate ,t,U); 3380 PetscFunctionReturn(0); 3381 } 3382 3383 /*@ 3384 TSStep - Steps one time step 3385 3386 Collective on TS 3387 3388 Input Parameter: 3389 . ts - the TS context obtained from TSCreate() 3390 3391 Level: developer 3392 3393 Notes: 3394 The public interface for the ODE/DAE solvers is TSSolve(), you should almost for sure be using that routine and not this routine. 3395 3396 The hook set using TSSetPreStep() is called before each attempt to take the step. In general, the time step size may 3397 be changed due to adaptive error controller or solve failures. Note that steps may contain multiple stages. 3398 3399 This may over-step the final time provided in TSSetMaxTime() depending on the time-step used. TSSolve() interpolates to exactly the 3400 time provided in TSSetMaxTime(). One can use TSInterpolate() to determine an interpolated solution within the final timestep. 3401 3402 .seealso: `TSCreate()`, `TSSetUp()`, `TSDestroy()`, `TSSolve()`, `TSSetPreStep()`, `TSSetPreStage()`, `TSSetPostStage()`, `TSInterpolate()` 3403 @*/ 3404 PetscErrorCode TSStep(TS ts) 3405 { 3406 static PetscBool cite = PETSC_FALSE; 3407 PetscReal ptime; 3408 3409 PetscFunctionBegin; 3410 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3411 PetscCall(PetscCitationsRegister("@article{tspaper,\n" 3412 " title = {{PETSc/TS}: A Modern Scalable {DAE/ODE} Solver Library},\n" 3413 " author = {Abhyankar, Shrirang and Brown, Jed and Constantinescu, Emil and Ghosh, Debojyoti and Smith, Barry F. and Zhang, Hong},\n" 3414 " journal = {arXiv e-preprints},\n" 3415 " eprint = {1806.01437},\n" 3416 " archivePrefix = {arXiv},\n" 3417 " year = {2018}\n}\n",&cite)); 3418 PetscCall(TSSetUp(ts)); 3419 PetscCall(TSTrajectorySetUp(ts->trajectory,ts)); 3420 3421 PetscCheck(ts->max_time < PETSC_MAX_REAL || ts->max_steps != PETSC_MAX_INT,PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"You must call TSSetMaxTime() or TSSetMaxSteps(), or use -ts_max_time <time> or -ts_max_steps <steps>"); 3422 PetscCheck(ts->exact_final_time != TS_EXACTFINALTIME_UNSPECIFIED,PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"You must call TSSetExactFinalTime() or use -ts_exact_final_time <stepover,interpolate,matchstep> before calling TSStep()"); 3423 PetscCheck(ts->exact_final_time != TS_EXACTFINALTIME_MATCHSTEP || ts->adapt,PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Since TS is not adaptive you cannot use TS_EXACTFINALTIME_MATCHSTEP, suggest TS_EXACTFINALTIME_INTERPOLATE"); 3424 3425 if (!ts->steps) ts->ptime_prev = ts->ptime; 3426 ptime = ts->ptime; ts->ptime_prev_rollback = ts->ptime_prev; 3427 ts->reason = TS_CONVERGED_ITERATING; 3428 3429 PetscCall(PetscLogEventBegin(TS_Step,ts,0,0,0)); 3430 PetscUseTypeMethod(ts,step); 3431 PetscCall(PetscLogEventEnd(TS_Step,ts,0,0,0)); 3432 3433 if (ts->reason >= 0) { 3434 ts->ptime_prev = ptime; 3435 ts->steps++; 3436 ts->steprollback = PETSC_FALSE; 3437 ts->steprestart = PETSC_FALSE; 3438 if (ts->tspan && PetscIsCloseAtTol(ts->ptime,ts->tspan->span_times[ts->tspan->spanctr],ts->tspan->reltol*ts->time_step+ts->tspan->abstol,0) && ts->tspan->spanctr < ts->tspan->num_span_times) PetscCall(VecCopy(ts->vec_sol,ts->tspan->vecs_sol[ts->tspan->spanctr++])); 3439 } 3440 3441 if (!ts->reason) { 3442 if (ts->steps >= ts->max_steps) ts->reason = TS_CONVERGED_ITS; 3443 else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME; 3444 } 3445 3446 PetscCheck(ts->reason >= 0 || !ts->errorifstepfailed || ts->reason != TS_DIVERGED_NONLINEAR_SOLVE,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]); 3447 PetscCheck(ts->reason >= 0 || !ts->errorifstepfailed,PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s",TSConvergedReasons[ts->reason]); 3448 PetscFunctionReturn(0); 3449 } 3450 3451 /*@ 3452 TSEvaluateWLTE - Evaluate the weighted local truncation error norm 3453 at the end of a time step with a given order of accuracy. 3454 3455 Collective on TS 3456 3457 Input Parameters: 3458 + ts - time stepping context 3459 - wnormtype - norm type, either NORM_2 or NORM_INFINITY 3460 3461 Input/Output Parameter: 3462 . order - optional, desired order for the error evaluation or PETSC_DECIDE; 3463 on output, the actual order of the error evaluation 3464 3465 Output Parameter: 3466 . wlte - the weighted local truncation error norm 3467 3468 Level: advanced 3469 3470 Notes: 3471 If the timestepper cannot evaluate the error in a particular step 3472 (eg. in the first step or restart steps after event handling), 3473 this routine returns wlte=-1.0 . 3474 3475 .seealso: `TSStep()`, `TSAdapt`, `TSErrorWeightedNorm()` 3476 @*/ 3477 PetscErrorCode TSEvaluateWLTE(TS ts,NormType wnormtype,PetscInt *order,PetscReal *wlte) 3478 { 3479 PetscFunctionBegin; 3480 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3481 PetscValidType(ts,1); 3482 PetscValidLogicalCollectiveEnum(ts,wnormtype,2); 3483 if (order) PetscValidIntPointer(order,3); 3484 if (order) PetscValidLogicalCollectiveInt(ts,*order,3); 3485 PetscValidRealPointer(wlte,4); 3486 PetscCheck(wnormtype == NORM_2 || wnormtype == NORM_INFINITY,PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]); 3487 PetscUseTypeMethod(ts,evaluatewlte ,wnormtype,order,wlte); 3488 PetscFunctionReturn(0); 3489 } 3490 3491 /*@ 3492 TSEvaluateStep - Evaluate the solution at the end of a time step with a given order of accuracy. 3493 3494 Collective on TS 3495 3496 Input Parameters: 3497 + ts - time stepping context 3498 . order - desired order of accuracy 3499 - done - whether the step was evaluated at this order (pass NULL to generate an error if not available) 3500 3501 Output Parameter: 3502 . U - state at the end of the current step 3503 3504 Level: advanced 3505 3506 Notes: 3507 This function cannot be called until all stages have been evaluated. 3508 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. 3509 3510 .seealso: `TSStep()`, `TSAdapt` 3511 @*/ 3512 PetscErrorCode TSEvaluateStep(TS ts,PetscInt order,Vec U,PetscBool *done) 3513 { 3514 PetscFunctionBegin; 3515 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3516 PetscValidType(ts,1); 3517 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 3518 PetscUseTypeMethod(ts,evaluatestep ,order,U,done); 3519 PetscFunctionReturn(0); 3520 } 3521 3522 /*@C 3523 TSGetComputeInitialCondition - Get the function used to automatically compute an initial condition for the timestepping. 3524 3525 Not collective 3526 3527 Input Parameter: 3528 . ts - time stepping context 3529 3530 Output Parameter: 3531 . initConditions - The function which computes an initial condition 3532 3533 Level: advanced 3534 3535 Notes: 3536 The calling sequence for the function is 3537 $ initCondition(TS ts, Vec u) 3538 $ ts - The timestepping context 3539 $ u - The input vector in which the initial condition is stored 3540 3541 .seealso: `TSSetComputeInitialCondition()`, `TSComputeInitialCondition()` 3542 @*/ 3543 PetscErrorCode TSGetComputeInitialCondition(TS ts, PetscErrorCode (**initCondition)(TS, Vec)) 3544 { 3545 PetscFunctionBegin; 3546 PetscValidHeaderSpecific(ts, TS_CLASSID, 1); 3547 PetscValidPointer(initCondition, 2); 3548 *initCondition = ts->ops->initcondition; 3549 PetscFunctionReturn(0); 3550 } 3551 3552 /*@C 3553 TSSetComputeInitialCondition - Set the function used to automatically compute an initial condition for the timestepping. 3554 3555 Logically collective on ts 3556 3557 Input Parameters: 3558 + ts - time stepping context 3559 - initCondition - The function which computes an initial condition 3560 3561 Level: advanced 3562 3563 Calling sequence for initCondition: 3564 $ PetscErrorCode initCondition(TS ts, Vec u) 3565 3566 + ts - The timestepping context 3567 - u - The input vector in which the initial condition is to be stored 3568 3569 .seealso: `TSGetComputeInitialCondition()`, `TSComputeInitialCondition()` 3570 @*/ 3571 PetscErrorCode TSSetComputeInitialCondition(TS ts, PetscErrorCode (*initCondition)(TS, Vec)) 3572 { 3573 PetscFunctionBegin; 3574 PetscValidHeaderSpecific(ts, TS_CLASSID, 1); 3575 PetscValidFunction(initCondition, 2); 3576 ts->ops->initcondition = initCondition; 3577 PetscFunctionReturn(0); 3578 } 3579 3580 /*@ 3581 TSComputeInitialCondition - Compute an initial condition for the timestepping using the function previously set. 3582 3583 Collective on ts 3584 3585 Input Parameters: 3586 + ts - time stepping context 3587 - u - The Vec to store the condition in which will be used in TSSolve() 3588 3589 Level: advanced 3590 3591 .seealso: `TSGetComputeInitialCondition()`, `TSSetComputeInitialCondition()`, `TSSolve()` 3592 @*/ 3593 PetscErrorCode TSComputeInitialCondition(TS ts, Vec u) 3594 { 3595 PetscFunctionBegin; 3596 PetscValidHeaderSpecific(ts, TS_CLASSID, 1); 3597 PetscValidHeaderSpecific(u, VEC_CLASSID, 2); 3598 PetscTryTypeMethod(ts,initcondition, u); 3599 PetscFunctionReturn(0); 3600 } 3601 3602 /*@C 3603 TSGetComputeExactError - Get the function used to automatically compute the exact error for the timestepping. 3604 3605 Not collective 3606 3607 Input Parameter: 3608 . ts - time stepping context 3609 3610 Output Parameter: 3611 . exactError - The function which computes the solution error 3612 3613 Level: advanced 3614 3615 Calling sequence for exactError: 3616 $ PetscErrorCode exactError(TS ts, Vec u) 3617 3618 + ts - The timestepping context 3619 . u - The approximate solution vector 3620 - e - The input vector in which the error is stored 3621 3622 .seealso: `TSGetComputeExactError()`, `TSComputeExactError()` 3623 @*/ 3624 PetscErrorCode TSGetComputeExactError(TS ts, PetscErrorCode (**exactError)(TS, Vec, Vec)) 3625 { 3626 PetscFunctionBegin; 3627 PetscValidHeaderSpecific(ts, TS_CLASSID, 1); 3628 PetscValidPointer(exactError, 2); 3629 *exactError = ts->ops->exacterror; 3630 PetscFunctionReturn(0); 3631 } 3632 3633 /*@C 3634 TSSetComputeExactError - Set the function used to automatically compute the exact error for the timestepping. 3635 3636 Logically collective on ts 3637 3638 Input Parameters: 3639 + ts - time stepping context 3640 - exactError - The function which computes the solution error 3641 3642 Level: advanced 3643 3644 Calling sequence for exactError: 3645 $ PetscErrorCode exactError(TS ts, Vec u) 3646 3647 + ts - The timestepping context 3648 . u - The approximate solution vector 3649 - e - The input vector in which the error is stored 3650 3651 .seealso: `TSGetComputeExactError()`, `TSComputeExactError()` 3652 @*/ 3653 PetscErrorCode TSSetComputeExactError(TS ts, PetscErrorCode (*exactError)(TS, Vec, Vec)) 3654 { 3655 PetscFunctionBegin; 3656 PetscValidHeaderSpecific(ts, TS_CLASSID, 1); 3657 PetscValidFunction(exactError, 2); 3658 ts->ops->exacterror = exactError; 3659 PetscFunctionReturn(0); 3660 } 3661 3662 /*@ 3663 TSComputeExactError - Compute the solution error for the timestepping using the function previously set. 3664 3665 Collective on ts 3666 3667 Input Parameters: 3668 + ts - time stepping context 3669 . u - The approximate solution 3670 - e - The Vec used to store the error 3671 3672 Level: advanced 3673 3674 .seealso: `TSGetComputeInitialCondition()`, `TSSetComputeInitialCondition()`, `TSSolve()` 3675 @*/ 3676 PetscErrorCode TSComputeExactError(TS ts, Vec u, Vec e) 3677 { 3678 PetscFunctionBegin; 3679 PetscValidHeaderSpecific(ts, TS_CLASSID, 1); 3680 PetscValidHeaderSpecific(u, VEC_CLASSID, 2); 3681 PetscValidHeaderSpecific(e, VEC_CLASSID, 3); 3682 PetscTryTypeMethod(ts,exacterror, u, e); 3683 PetscFunctionReturn(0); 3684 } 3685 3686 /*@ 3687 TSSolve - Steps the requested number of timesteps. 3688 3689 Collective on TS 3690 3691 Input Parameters: 3692 + ts - the TS context obtained from TSCreate() 3693 - u - the solution vector (can be null if TSSetSolution() was used and TSSetExactFinalTime(ts,TS_EXACTFINALTIME_MATCHSTEP) was not used, 3694 otherwise must contain the initial conditions and will contain the solution at the final requested time 3695 3696 Level: beginner 3697 3698 Notes: 3699 The final time returned by this function may be different from the time of the internally 3700 held state accessible by TSGetSolution() and TSGetTime() because the method may have 3701 stepped over the final time. 3702 3703 .seealso: `TSCreate()`, `TSSetSolution()`, `TSStep()`, `TSGetTime()`, `TSGetSolveTime()` 3704 @*/ 3705 PetscErrorCode TSSolve(TS ts,Vec u) 3706 { 3707 Vec solution; 3708 3709 PetscFunctionBegin; 3710 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3711 if (u) PetscValidHeaderSpecific(u,VEC_CLASSID,2); 3712 3713 PetscCall(TSSetExactFinalTimeDefault(ts)); 3714 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 */ 3715 if (!ts->vec_sol || u == ts->vec_sol) { 3716 PetscCall(VecDuplicate(u,&solution)); 3717 PetscCall(TSSetSolution(ts,solution)); 3718 PetscCall(VecDestroy(&solution)); /* grant ownership */ 3719 } 3720 PetscCall(VecCopy(u,ts->vec_sol)); 3721 PetscCheck(!ts->forward_solve,PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Sensitivity analysis does not support the mode TS_EXACTFINALTIME_INTERPOLATE"); 3722 } else if (u) PetscCall(TSSetSolution(ts,u)); 3723 PetscCall(TSSetUp(ts)); 3724 PetscCall(TSTrajectorySetUp(ts->trajectory,ts)); 3725 3726 PetscCheck(ts->max_time < PETSC_MAX_REAL || ts->max_steps != PETSC_MAX_INT,PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"You must call TSSetMaxTime() or TSSetMaxSteps(), or use -ts_max_time <time> or -ts_max_steps <steps>"); 3727 PetscCheck(ts->exact_final_time != TS_EXACTFINALTIME_UNSPECIFIED,PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"You must call TSSetExactFinalTime() or use -ts_exact_final_time <stepover,interpolate,matchstep> before calling TSSolve()"); 3728 PetscCheck(ts->exact_final_time != TS_EXACTFINALTIME_MATCHSTEP || ts->adapt,PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Since TS is not adaptive you cannot use TS_EXACTFINALTIME_MATCHSTEP, suggest TS_EXACTFINALTIME_INTERPOLATE"); 3729 PetscCheck(!(ts->tspan && ts->exact_final_time != TS_EXACTFINALTIME_MATCHSTEP),PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"You must use TS_EXACTFINALTIME_MATCHSTEP when using time span"); 3730 3731 if (ts->tspan && PetscIsCloseAtTol(ts->ptime,ts->tspan->span_times[0],ts->tspan->reltol*ts->time_step+ts->tspan->abstol,0)) { /* starting point in time span */ 3732 PetscCall(VecCopy(ts->vec_sol,ts->tspan->vecs_sol[0])); 3733 ts->tspan->spanctr = 1; 3734 } 3735 3736 if (ts->forward_solve) PetscCall(TSForwardSetUp(ts)); 3737 3738 /* reset number of steps only when the step is not restarted. ARKIMEX 3739 restarts the step after an event. Resetting these counters in such case causes 3740 TSTrajectory to incorrectly save the output files 3741 */ 3742 /* reset time step and iteration counters */ 3743 if (!ts->steps) { 3744 ts->ksp_its = 0; 3745 ts->snes_its = 0; 3746 ts->num_snes_failures = 0; 3747 ts->reject = 0; 3748 ts->steprestart = PETSC_TRUE; 3749 ts->steprollback = PETSC_FALSE; 3750 ts->rhsjacobian.time = PETSC_MIN_REAL; 3751 } 3752 3753 /* make sure initial time step does not overshoot final time or the next point in tspan */ 3754 if (ts->exact_final_time == TS_EXACTFINALTIME_MATCHSTEP) { 3755 PetscReal maxdt; 3756 PetscReal dt = ts->time_step; 3757 3758 if (ts->tspan) maxdt = ts->tspan->span_times[ts->tspan->spanctr] - ts->ptime; 3759 else maxdt = ts->max_time - ts->ptime; 3760 ts->time_step = dt >= maxdt ? maxdt : (PetscIsCloseAtTol(dt,maxdt,10*PETSC_MACHINE_EPSILON,0) ? maxdt : dt); 3761 } 3762 ts->reason = TS_CONVERGED_ITERATING; 3763 3764 { 3765 PetscViewer viewer; 3766 PetscViewerFormat format; 3767 PetscBool flg; 3768 static PetscBool incall = PETSC_FALSE; 3769 3770 if (!incall) { 3771 /* Estimate the convergence rate of the time discretization */ 3772 PetscCall(PetscOptionsGetViewer(PetscObjectComm((PetscObject) ts),((PetscObject)ts)->options, ((PetscObject) ts)->prefix, "-ts_convergence_estimate", &viewer, &format, &flg)); 3773 if (flg) { 3774 PetscConvEst conv; 3775 DM dm; 3776 PetscReal *alpha; /* Convergence rate of the solution error for each field in the L_2 norm */ 3777 PetscInt Nf; 3778 PetscBool checkTemporal = PETSC_TRUE; 3779 3780 incall = PETSC_TRUE; 3781 PetscCall(PetscOptionsGetBool(((PetscObject)ts)->options, ((PetscObject) ts)->prefix, "-ts_convergence_temporal", &checkTemporal, &flg)); 3782 PetscCall(TSGetDM(ts, &dm)); 3783 PetscCall(DMGetNumFields(dm, &Nf)); 3784 PetscCall(PetscCalloc1(PetscMax(Nf, 1), &alpha)); 3785 PetscCall(PetscConvEstCreate(PetscObjectComm((PetscObject) ts), &conv)); 3786 PetscCall(PetscConvEstUseTS(conv, checkTemporal)); 3787 PetscCall(PetscConvEstSetSolver(conv, (PetscObject) ts)); 3788 PetscCall(PetscConvEstSetFromOptions(conv)); 3789 PetscCall(PetscConvEstSetUp(conv)); 3790 PetscCall(PetscConvEstGetConvRate(conv, alpha)); 3791 PetscCall(PetscViewerPushFormat(viewer, format)); 3792 PetscCall(PetscConvEstRateView(conv, alpha, viewer)); 3793 PetscCall(PetscViewerPopFormat(viewer)); 3794 PetscCall(PetscViewerDestroy(&viewer)); 3795 PetscCall(PetscConvEstDestroy(&conv)); 3796 PetscCall(PetscFree(alpha)); 3797 incall = PETSC_FALSE; 3798 } 3799 } 3800 } 3801 3802 PetscCall(TSViewFromOptions(ts,NULL,"-ts_view_pre")); 3803 3804 if (ts->ops->solve) { /* This private interface is transitional and should be removed when all implementations are updated. */ 3805 PetscUseTypeMethod(ts,solve); 3806 if (u) PetscCall(VecCopy(ts->vec_sol,u)); 3807 ts->solvetime = ts->ptime; 3808 solution = ts->vec_sol; 3809 } else { /* Step the requested number of timesteps. */ 3810 if (ts->steps >= ts->max_steps) ts->reason = TS_CONVERGED_ITS; 3811 else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME; 3812 3813 if (!ts->steps) { 3814 PetscCall(TSTrajectorySet(ts->trajectory,ts,ts->steps,ts->ptime,ts->vec_sol)); 3815 PetscCall(TSEventInitialize(ts->event,ts,ts->ptime,ts->vec_sol)); 3816 } 3817 3818 while (!ts->reason) { 3819 PetscCall(TSMonitor(ts,ts->steps,ts->ptime,ts->vec_sol)); 3820 if (!ts->steprollback) PetscCall(TSPreStep(ts)); 3821 PetscCall(TSStep(ts)); 3822 if (ts->testjacobian) PetscCall(TSRHSJacobianTest(ts,NULL)); 3823 if (ts->testjacobiantranspose) PetscCall(TSRHSJacobianTestTranspose(ts,NULL)); 3824 if (ts->quadraturets && ts->costintegralfwd) { /* Must evaluate the cost integral before event is handled. The cost integral value can also be rolled back. */ 3825 if (ts->reason >= 0) ts->steps--; /* Revert the step number changed by TSStep() */ 3826 PetscCall(TSForwardCostIntegral(ts)); 3827 if (ts->reason >= 0) ts->steps++; 3828 } 3829 if (ts->forward_solve) { /* compute forward sensitivities before event handling because postevent() may change RHS and jump conditions may have to be applied */ 3830 if (ts->reason >= 0) ts->steps--; /* Revert the step number changed by TSStep() */ 3831 PetscCall(TSForwardStep(ts)); 3832 if (ts->reason >= 0) ts->steps++; 3833 } 3834 PetscCall(TSPostEvaluate(ts)); 3835 PetscCall(TSEventHandler(ts)); /* The right-hand side may be changed due to event. Be careful with Any computation using the RHS information after this point. */ 3836 if (ts->steprollback) PetscCall(TSPostEvaluate(ts)); 3837 if (!ts->steprollback) { 3838 PetscCall(TSTrajectorySet(ts->trajectory,ts,ts->steps,ts->ptime,ts->vec_sol)); 3839 PetscCall(TSPostStep(ts)); 3840 } 3841 } 3842 PetscCall(TSMonitor(ts,ts->steps,ts->ptime,ts->vec_sol)); 3843 3844 if (ts->exact_final_time == TS_EXACTFINALTIME_INTERPOLATE && ts->ptime > ts->max_time) { 3845 PetscCall(TSInterpolate(ts,ts->max_time,u)); 3846 ts->solvetime = ts->max_time; 3847 solution = u; 3848 PetscCall(TSMonitor(ts,-1,ts->solvetime,solution)); 3849 } else { 3850 if (u) PetscCall(VecCopy(ts->vec_sol,u)); 3851 ts->solvetime = ts->ptime; 3852 solution = ts->vec_sol; 3853 } 3854 } 3855 3856 PetscCall(TSViewFromOptions(ts,NULL,"-ts_view")); 3857 PetscCall(VecViewFromOptions(solution,(PetscObject)ts,"-ts_view_solution")); 3858 PetscCall(PetscObjectSAWsBlock((PetscObject)ts)); 3859 if (ts->adjoint_solve) PetscCall(TSAdjointSolve(ts)); 3860 PetscFunctionReturn(0); 3861 } 3862 3863 /*@ 3864 TSGetTime - Gets the time of the most recently completed step. 3865 3866 Not Collective 3867 3868 Input Parameter: 3869 . ts - the TS context obtained from TSCreate() 3870 3871 Output Parameter: 3872 . t - the current time. This time may not corresponds to the final time set with TSSetMaxTime(), use TSGetSolveTime(). 3873 3874 Level: beginner 3875 3876 Note: 3877 When called during time step evaluation (e.g. during residual evaluation or via hooks set using TSSetPreStep(), 3878 TSSetPreStage(), TSSetPostStage(), or TSSetPostStep()), the time is the time at the start of the step being evaluated. 3879 3880 .seealso: `TSGetSolveTime()`, `TSSetTime()`, `TSGetTimeStep()`, `TSGetStepNumber()` 3881 3882 @*/ 3883 PetscErrorCode TSGetTime(TS ts,PetscReal *t) 3884 { 3885 PetscFunctionBegin; 3886 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3887 PetscValidRealPointer(t,2); 3888 *t = ts->ptime; 3889 PetscFunctionReturn(0); 3890 } 3891 3892 /*@ 3893 TSGetPrevTime - Gets the starting time of the previously completed step. 3894 3895 Not Collective 3896 3897 Input Parameter: 3898 . ts - the TS context obtained from TSCreate() 3899 3900 Output Parameter: 3901 . t - the previous time 3902 3903 Level: beginner 3904 3905 .seealso: `TSGetTime()`, `TSGetSolveTime()`, `TSGetTimeStep()` 3906 3907 @*/ 3908 PetscErrorCode TSGetPrevTime(TS ts,PetscReal *t) 3909 { 3910 PetscFunctionBegin; 3911 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3912 PetscValidRealPointer(t,2); 3913 *t = ts->ptime_prev; 3914 PetscFunctionReturn(0); 3915 } 3916 3917 /*@ 3918 TSSetTime - Allows one to reset the time. 3919 3920 Logically Collective on TS 3921 3922 Input Parameters: 3923 + ts - the TS context obtained from TSCreate() 3924 - time - the time 3925 3926 Level: intermediate 3927 3928 .seealso: `TSGetTime()`, `TSSetMaxSteps()` 3929 3930 @*/ 3931 PetscErrorCode TSSetTime(TS ts, PetscReal t) 3932 { 3933 PetscFunctionBegin; 3934 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3935 PetscValidLogicalCollectiveReal(ts,t,2); 3936 ts->ptime = t; 3937 PetscFunctionReturn(0); 3938 } 3939 3940 /*@C 3941 TSSetOptionsPrefix - Sets the prefix used for searching for all 3942 TS options in the database. 3943 3944 Logically Collective on TS 3945 3946 Input Parameters: 3947 + ts - The TS context 3948 - prefix - The prefix to prepend to all option names 3949 3950 Notes: 3951 A hyphen (-) must NOT be given at the beginning of the prefix name. 3952 The first character of all runtime options is AUTOMATICALLY the 3953 hyphen. 3954 3955 Level: advanced 3956 3957 .seealso: `TSSetFromOptions()` 3958 3959 @*/ 3960 PetscErrorCode TSSetOptionsPrefix(TS ts,const char prefix[]) 3961 { 3962 SNES snes; 3963 3964 PetscFunctionBegin; 3965 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3966 PetscCall(PetscObjectSetOptionsPrefix((PetscObject)ts,prefix)); 3967 PetscCall(TSGetSNES(ts,&snes)); 3968 PetscCall(SNESSetOptionsPrefix(snes,prefix)); 3969 PetscFunctionReturn(0); 3970 } 3971 3972 /*@C 3973 TSAppendOptionsPrefix - Appends to the prefix used for searching for all 3974 TS options in the database. 3975 3976 Logically Collective on TS 3977 3978 Input Parameters: 3979 + ts - The TS context 3980 - prefix - The prefix to prepend to all option names 3981 3982 Notes: 3983 A hyphen (-) must NOT be given at the beginning of the prefix name. 3984 The first character of all runtime options is AUTOMATICALLY the 3985 hyphen. 3986 3987 Level: advanced 3988 3989 .seealso: `TSGetOptionsPrefix()` 3990 3991 @*/ 3992 PetscErrorCode TSAppendOptionsPrefix(TS ts,const char prefix[]) 3993 { 3994 SNES snes; 3995 3996 PetscFunctionBegin; 3997 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3998 PetscCall(PetscObjectAppendOptionsPrefix((PetscObject)ts,prefix)); 3999 PetscCall(TSGetSNES(ts,&snes)); 4000 PetscCall(SNESAppendOptionsPrefix(snes,prefix)); 4001 PetscFunctionReturn(0); 4002 } 4003 4004 /*@C 4005 TSGetOptionsPrefix - Sets the prefix used for searching for all 4006 TS options in the database. 4007 4008 Not Collective 4009 4010 Input Parameter: 4011 . ts - The TS context 4012 4013 Output Parameter: 4014 . prefix - A pointer to the prefix string used 4015 4016 Notes: 4017 On the fortran side, the user should pass in a string 'prifix' of 4018 sufficient length to hold the prefix. 4019 4020 Level: intermediate 4021 4022 .seealso: `TSAppendOptionsPrefix()` 4023 @*/ 4024 PetscErrorCode TSGetOptionsPrefix(TS ts,const char *prefix[]) 4025 { 4026 PetscFunctionBegin; 4027 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4028 PetscValidPointer(prefix,2); 4029 PetscCall(PetscObjectGetOptionsPrefix((PetscObject)ts,prefix)); 4030 PetscFunctionReturn(0); 4031 } 4032 4033 /*@C 4034 TSGetRHSJacobian - Returns the Jacobian J at the present timestep. 4035 4036 Not Collective, but parallel objects are returned if TS is parallel 4037 4038 Input Parameter: 4039 . ts - The TS context obtained from TSCreate() 4040 4041 Output Parameters: 4042 + Amat - The (approximate) Jacobian J of G, where U_t = G(U,t) (or NULL) 4043 . Pmat - The matrix from which the preconditioner is constructed, usually the same as Amat (or NULL) 4044 . func - Function to compute the Jacobian of the RHS (or NULL) 4045 - ctx - User-defined context for Jacobian evaluation routine (or NULL) 4046 4047 Notes: 4048 You can pass in NULL for any return argument you do not need. 4049 4050 Level: intermediate 4051 4052 .seealso: `TSGetTimeStep()`, `TSGetMatrices()`, `TSGetTime()`, `TSGetStepNumber()` 4053 4054 @*/ 4055 PetscErrorCode TSGetRHSJacobian(TS ts,Mat *Amat,Mat *Pmat,TSRHSJacobian *func,void **ctx) 4056 { 4057 DM dm; 4058 4059 PetscFunctionBegin; 4060 if (Amat || Pmat) { 4061 SNES snes; 4062 PetscCall(TSGetSNES(ts,&snes)); 4063 PetscCall(SNESSetUpMatrices(snes)); 4064 PetscCall(SNESGetJacobian(snes,Amat,Pmat,NULL,NULL)); 4065 } 4066 PetscCall(TSGetDM(ts,&dm)); 4067 PetscCall(DMTSGetRHSJacobian(dm,func,ctx)); 4068 PetscFunctionReturn(0); 4069 } 4070 4071 /*@C 4072 TSGetIJacobian - Returns the implicit Jacobian at the present timestep. 4073 4074 Not Collective, but parallel objects are returned if TS is parallel 4075 4076 Input Parameter: 4077 . ts - The TS context obtained from TSCreate() 4078 4079 Output Parameters: 4080 + Amat - The (approximate) Jacobian of F(t,U,U_t) 4081 . Pmat - The matrix from which the preconditioner is constructed, often the same as Amat 4082 . f - The function to compute the matrices 4083 - ctx - User-defined context for Jacobian evaluation routine 4084 4085 Notes: 4086 You can pass in NULL for any return argument you do not need. 4087 4088 Level: advanced 4089 4090 .seealso: `TSGetTimeStep()`, `TSGetRHSJacobian()`, `TSGetMatrices()`, `TSGetTime()`, `TSGetStepNumber()` 4091 4092 @*/ 4093 PetscErrorCode TSGetIJacobian(TS ts,Mat *Amat,Mat *Pmat,TSIJacobian *f,void **ctx) 4094 { 4095 DM dm; 4096 4097 PetscFunctionBegin; 4098 if (Amat || Pmat) { 4099 SNES snes; 4100 PetscCall(TSGetSNES(ts,&snes)); 4101 PetscCall(SNESSetUpMatrices(snes)); 4102 PetscCall(SNESGetJacobian(snes,Amat,Pmat,NULL,NULL)); 4103 } 4104 PetscCall(TSGetDM(ts,&dm)); 4105 PetscCall(DMTSGetIJacobian(dm,f,ctx)); 4106 PetscFunctionReturn(0); 4107 } 4108 4109 #include <petsc/private/dmimpl.h> 4110 /*@ 4111 TSSetDM - Sets the DM that may be used by some nonlinear solvers or preconditioners under the TS 4112 4113 Logically Collective on ts 4114 4115 Input Parameters: 4116 + ts - the ODE integrator object 4117 - dm - the dm, cannot be NULL 4118 4119 Notes: 4120 A DM can only be used for solving one problem at a time because information about the problem is stored on the DM, 4121 even when not using interfaces like DMTSSetIFunction(). Use DMClone() to get a distinct DM when solving 4122 different problems using the same function space. 4123 4124 Level: intermediate 4125 4126 .seealso: `TSGetDM()`, `SNESSetDM()`, `SNESGetDM()` 4127 @*/ 4128 PetscErrorCode TSSetDM(TS ts,DM dm) 4129 { 4130 SNES snes; 4131 DMTS tsdm; 4132 4133 PetscFunctionBegin; 4134 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4135 PetscValidHeaderSpecific(dm,DM_CLASSID,2); 4136 PetscCall(PetscObjectReference((PetscObject)dm)); 4137 if (ts->dm) { /* Move the DMTS context over to the new DM unless the new DM already has one */ 4138 if (ts->dm->dmts && !dm->dmts) { 4139 PetscCall(DMCopyDMTS(ts->dm,dm)); 4140 PetscCall(DMGetDMTS(ts->dm,&tsdm)); 4141 /* Grant write privileges to the replacement DM */ 4142 if (tsdm->originaldm == ts->dm) tsdm->originaldm = dm; 4143 } 4144 PetscCall(DMDestroy(&ts->dm)); 4145 } 4146 ts->dm = dm; 4147 4148 PetscCall(TSGetSNES(ts,&snes)); 4149 PetscCall(SNESSetDM(snes,dm)); 4150 PetscFunctionReturn(0); 4151 } 4152 4153 /*@ 4154 TSGetDM - Gets the DM that may be used by some preconditioners 4155 4156 Not Collective 4157 4158 Input Parameter: 4159 . ts - the preconditioner context 4160 4161 Output Parameter: 4162 . dm - the dm 4163 4164 Level: intermediate 4165 4166 .seealso: `TSSetDM()`, `SNESSetDM()`, `SNESGetDM()` 4167 @*/ 4168 PetscErrorCode TSGetDM(TS ts,DM *dm) 4169 { 4170 PetscFunctionBegin; 4171 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4172 if (!ts->dm) { 4173 PetscCall(DMShellCreate(PetscObjectComm((PetscObject)ts),&ts->dm)); 4174 if (ts->snes) PetscCall(SNESSetDM(ts->snes,ts->dm)); 4175 } 4176 *dm = ts->dm; 4177 PetscFunctionReturn(0); 4178 } 4179 4180 /*@ 4181 SNESTSFormFunction - Function to evaluate nonlinear residual 4182 4183 Logically Collective on SNES 4184 4185 Input Parameters: 4186 + snes - nonlinear solver 4187 . U - the current state at which to evaluate the residual 4188 - ctx - user context, must be a TS 4189 4190 Output Parameter: 4191 . F - the nonlinear residual 4192 4193 Notes: 4194 This function is not normally called by users and is automatically registered with the SNES used by TS. 4195 It is most frequently passed to MatFDColoringSetFunction(). 4196 4197 Level: advanced 4198 4199 .seealso: `SNESSetFunction()`, `MatFDColoringSetFunction()` 4200 @*/ 4201 PetscErrorCode SNESTSFormFunction(SNES snes,Vec U,Vec F,void *ctx) 4202 { 4203 TS ts = (TS)ctx; 4204 4205 PetscFunctionBegin; 4206 PetscValidHeaderSpecific(snes,SNES_CLASSID,1); 4207 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 4208 PetscValidHeaderSpecific(F,VEC_CLASSID,3); 4209 PetscValidHeaderSpecific(ts,TS_CLASSID,4); 4210 PetscCall((ts->ops->snesfunction)(snes,U,F,ts)); 4211 PetscFunctionReturn(0); 4212 } 4213 4214 /*@ 4215 SNESTSFormJacobian - Function to evaluate the Jacobian 4216 4217 Collective on SNES 4218 4219 Input Parameters: 4220 + snes - nonlinear solver 4221 . U - the current state at which to evaluate the residual 4222 - ctx - user context, must be a TS 4223 4224 Output Parameters: 4225 + A - the Jacobian 4226 - B - the preconditioning matrix (may be the same as A) 4227 4228 Notes: 4229 This function is not normally called by users and is automatically registered with the SNES used by TS. 4230 4231 Level: developer 4232 4233 .seealso: `SNESSetJacobian()` 4234 @*/ 4235 PetscErrorCode SNESTSFormJacobian(SNES snes,Vec U,Mat A,Mat B,void *ctx) 4236 { 4237 TS ts = (TS)ctx; 4238 4239 PetscFunctionBegin; 4240 PetscValidHeaderSpecific(snes,SNES_CLASSID,1); 4241 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 4242 PetscValidPointer(A,3); 4243 PetscValidHeaderSpecific(A,MAT_CLASSID,3); 4244 PetscValidPointer(B,4); 4245 PetscValidHeaderSpecific(B,MAT_CLASSID,4); 4246 PetscValidHeaderSpecific(ts,TS_CLASSID,5); 4247 PetscCall((ts->ops->snesjacobian)(snes,U,A,B,ts)); 4248 PetscFunctionReturn(0); 4249 } 4250 4251 /*@C 4252 TSComputeRHSFunctionLinear - Evaluate the right hand side via the user-provided Jacobian, for linear problems Udot = A U only 4253 4254 Collective on TS 4255 4256 Input Parameters: 4257 + ts - time stepping context 4258 . t - time at which to evaluate 4259 . U - state at which to evaluate 4260 - ctx - context 4261 4262 Output Parameter: 4263 . F - right hand side 4264 4265 Level: intermediate 4266 4267 Notes: 4268 This function is intended to be passed to TSSetRHSFunction() to evaluate the right hand side for linear problems. 4269 The matrix (and optionally the evaluation context) should be passed to TSSetRHSJacobian(). 4270 4271 .seealso: `TSSetRHSFunction()`, `TSSetRHSJacobian()`, `TSComputeRHSJacobianConstant()` 4272 @*/ 4273 PetscErrorCode TSComputeRHSFunctionLinear(TS ts,PetscReal t,Vec U,Vec F,void *ctx) 4274 { 4275 Mat Arhs,Brhs; 4276 4277 PetscFunctionBegin; 4278 PetscCall(TSGetRHSMats_Private(ts,&Arhs,&Brhs)); 4279 /* undo the damage caused by shifting */ 4280 PetscCall(TSRecoverRHSJacobian(ts,Arhs,Brhs)); 4281 PetscCall(TSComputeRHSJacobian(ts,t,U,Arhs,Brhs)); 4282 PetscCall(MatMult(Arhs,U,F)); 4283 PetscFunctionReturn(0); 4284 } 4285 4286 /*@C 4287 TSComputeRHSJacobianConstant - Reuses a Jacobian that is time-independent. 4288 4289 Collective on TS 4290 4291 Input Parameters: 4292 + ts - time stepping context 4293 . t - time at which to evaluate 4294 . U - state at which to evaluate 4295 - ctx - context 4296 4297 Output Parameters: 4298 + A - pointer to operator 4299 - B - pointer to preconditioning matrix 4300 4301 Level: intermediate 4302 4303 Notes: 4304 This function is intended to be passed to TSSetRHSJacobian() to evaluate the Jacobian for linear time-independent problems. 4305 4306 .seealso: `TSSetRHSFunction()`, `TSSetRHSJacobian()`, `TSComputeRHSFunctionLinear()` 4307 @*/ 4308 PetscErrorCode TSComputeRHSJacobianConstant(TS ts,PetscReal t,Vec U,Mat A,Mat B,void *ctx) 4309 { 4310 PetscFunctionBegin; 4311 PetscFunctionReturn(0); 4312 } 4313 4314 /*@C 4315 TSComputeIFunctionLinear - Evaluate the left hand side via the user-provided Jacobian, for linear problems only 4316 4317 Collective on TS 4318 4319 Input Parameters: 4320 + ts - time stepping context 4321 . t - time at which to evaluate 4322 . U - state at which to evaluate 4323 . Udot - time derivative of state vector 4324 - ctx - context 4325 4326 Output Parameter: 4327 . F - left hand side 4328 4329 Level: intermediate 4330 4331 Notes: 4332 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 4333 user is required to write their own TSComputeIFunction. 4334 This function is intended to be passed to TSSetIFunction() to evaluate the left hand side for linear problems. 4335 The matrix (and optionally the evaluation context) should be passed to TSSetIJacobian(). 4336 4337 Note that using this function is NOT equivalent to using TSComputeRHSFunctionLinear() since that solves Udot = A U 4338 4339 .seealso: `TSSetIFunction()`, `TSSetIJacobian()`, `TSComputeIJacobianConstant()`, `TSComputeRHSFunctionLinear()` 4340 @*/ 4341 PetscErrorCode TSComputeIFunctionLinear(TS ts,PetscReal t,Vec U,Vec Udot,Vec F,void *ctx) 4342 { 4343 Mat A,B; 4344 4345 PetscFunctionBegin; 4346 PetscCall(TSGetIJacobian(ts,&A,&B,NULL,NULL)); 4347 PetscCall(TSComputeIJacobian(ts,t,U,Udot,1.0,A,B,PETSC_TRUE)); 4348 PetscCall(MatMult(A,Udot,F)); 4349 PetscFunctionReturn(0); 4350 } 4351 4352 /*@C 4353 TSComputeIJacobianConstant - Reuses a time-independent for a semi-implicit DAE or ODE 4354 4355 Collective on TS 4356 4357 Input Parameters: 4358 + ts - time stepping context 4359 . t - time at which to evaluate 4360 . U - state at which to evaluate 4361 . Udot - time derivative of state vector 4362 . shift - shift to apply 4363 - ctx - context 4364 4365 Output Parameters: 4366 + A - pointer to operator 4367 - B - pointer to preconditioning matrix 4368 4369 Level: advanced 4370 4371 Notes: 4372 This function is intended to be passed to TSSetIJacobian() to evaluate the Jacobian for linear time-independent problems. 4373 4374 It is only appropriate for problems of the form 4375 4376 $ M Udot = F(U,t) 4377 4378 where M is constant and F is non-stiff. The user must pass M to TSSetIJacobian(). The current implementation only 4379 works with IMEX time integration methods such as TSROSW and TSARKIMEX, since there is no support for de-constructing 4380 an implicit operator of the form 4381 4382 $ shift*M + J 4383 4384 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 4385 a copy of M or reassemble it when requested. 4386 4387 .seealso: `TSSetIFunction()`, `TSSetIJacobian()`, `TSComputeIFunctionLinear()` 4388 @*/ 4389 PetscErrorCode TSComputeIJacobianConstant(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat A,Mat B,void *ctx) 4390 { 4391 PetscFunctionBegin; 4392 PetscCall(MatScale(A, shift / ts->ijacobian.shift)); 4393 ts->ijacobian.shift = shift; 4394 PetscFunctionReturn(0); 4395 } 4396 4397 /*@ 4398 TSGetEquationType - Gets the type of the equation that TS is solving. 4399 4400 Not Collective 4401 4402 Input Parameter: 4403 . ts - the TS context 4404 4405 Output Parameter: 4406 . equation_type - see TSEquationType 4407 4408 Level: beginner 4409 4410 .seealso: `TSSetEquationType()`, `TSEquationType` 4411 @*/ 4412 PetscErrorCode TSGetEquationType(TS ts,TSEquationType *equation_type) 4413 { 4414 PetscFunctionBegin; 4415 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4416 PetscValidPointer(equation_type,2); 4417 *equation_type = ts->equation_type; 4418 PetscFunctionReturn(0); 4419 } 4420 4421 /*@ 4422 TSSetEquationType - Sets the type of the equation that TS is solving. 4423 4424 Not Collective 4425 4426 Input Parameters: 4427 + ts - the TS context 4428 - equation_type - see TSEquationType 4429 4430 Level: advanced 4431 4432 .seealso: `TSGetEquationType()`, `TSEquationType` 4433 @*/ 4434 PetscErrorCode TSSetEquationType(TS ts,TSEquationType equation_type) 4435 { 4436 PetscFunctionBegin; 4437 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4438 ts->equation_type = equation_type; 4439 PetscFunctionReturn(0); 4440 } 4441 4442 /*@ 4443 TSGetConvergedReason - Gets the reason the TS iteration was stopped. 4444 4445 Not Collective 4446 4447 Input Parameter: 4448 . ts - the TS context 4449 4450 Output Parameter: 4451 . reason - negative value indicates diverged, positive value converged, see TSConvergedReason or the 4452 manual pages for the individual convergence tests for complete lists 4453 4454 Level: beginner 4455 4456 Notes: 4457 Can only be called after the call to TSSolve() is complete. 4458 4459 .seealso: `TSSetConvergenceTest()`, `TSConvergedReason` 4460 @*/ 4461 PetscErrorCode TSGetConvergedReason(TS ts,TSConvergedReason *reason) 4462 { 4463 PetscFunctionBegin; 4464 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4465 PetscValidPointer(reason,2); 4466 *reason = ts->reason; 4467 PetscFunctionReturn(0); 4468 } 4469 4470 /*@ 4471 TSSetConvergedReason - Sets the reason for handling the convergence of TSSolve. 4472 4473 Logically Collective; reason must contain common value 4474 4475 Input Parameters: 4476 + ts - the TS context 4477 - reason - negative value indicates diverged, positive value converged, see TSConvergedReason or the 4478 manual pages for the individual convergence tests for complete lists 4479 4480 Level: advanced 4481 4482 Notes: 4483 Can only be called while TSSolve() is active. 4484 4485 .seealso: `TSConvergedReason` 4486 @*/ 4487 PetscErrorCode TSSetConvergedReason(TS ts,TSConvergedReason reason) 4488 { 4489 PetscFunctionBegin; 4490 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4491 ts->reason = reason; 4492 PetscFunctionReturn(0); 4493 } 4494 4495 /*@ 4496 TSGetSolveTime - Gets the time after a call to TSSolve() 4497 4498 Not Collective 4499 4500 Input Parameter: 4501 . ts - the TS context 4502 4503 Output Parameter: 4504 . ftime - the final time. This time corresponds to the final time set with TSSetMaxTime() 4505 4506 Level: beginner 4507 4508 Notes: 4509 Can only be called after the call to TSSolve() is complete. 4510 4511 .seealso: `TSSetConvergenceTest()`, `TSConvergedReason` 4512 @*/ 4513 PetscErrorCode TSGetSolveTime(TS ts,PetscReal *ftime) 4514 { 4515 PetscFunctionBegin; 4516 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4517 PetscValidRealPointer(ftime,2); 4518 *ftime = ts->solvetime; 4519 PetscFunctionReturn(0); 4520 } 4521 4522 /*@ 4523 TSGetSNESIterations - Gets the total number of nonlinear iterations 4524 used by the time integrator. 4525 4526 Not Collective 4527 4528 Input Parameter: 4529 . ts - TS context 4530 4531 Output Parameter: 4532 . nits - number of nonlinear iterations 4533 4534 Notes: 4535 This counter is reset to zero for each successive call to TSSolve(). 4536 4537 Level: intermediate 4538 4539 .seealso: `TSGetKSPIterations()` 4540 @*/ 4541 PetscErrorCode TSGetSNESIterations(TS ts,PetscInt *nits) 4542 { 4543 PetscFunctionBegin; 4544 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4545 PetscValidIntPointer(nits,2); 4546 *nits = ts->snes_its; 4547 PetscFunctionReturn(0); 4548 } 4549 4550 /*@ 4551 TSGetKSPIterations - Gets the total number of linear iterations 4552 used by the time integrator. 4553 4554 Not Collective 4555 4556 Input Parameter: 4557 . ts - TS context 4558 4559 Output Parameter: 4560 . lits - number of linear iterations 4561 4562 Notes: 4563 This counter is reset to zero for each successive call to TSSolve(). 4564 4565 Level: intermediate 4566 4567 .seealso: `TSGetSNESIterations()`, `SNESGetKSPIterations()` 4568 @*/ 4569 PetscErrorCode TSGetKSPIterations(TS ts,PetscInt *lits) 4570 { 4571 PetscFunctionBegin; 4572 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4573 PetscValidIntPointer(lits,2); 4574 *lits = ts->ksp_its; 4575 PetscFunctionReturn(0); 4576 } 4577 4578 /*@ 4579 TSGetStepRejections - Gets the total number of rejected steps. 4580 4581 Not Collective 4582 4583 Input Parameter: 4584 . ts - TS context 4585 4586 Output Parameter: 4587 . rejects - number of steps rejected 4588 4589 Notes: 4590 This counter is reset to zero for each successive call to TSSolve(). 4591 4592 Level: intermediate 4593 4594 .seealso: `TSGetSNESIterations()`, `TSGetKSPIterations()`, `TSSetMaxStepRejections()`, `TSGetSNESFailures()`, `TSSetMaxSNESFailures()`, `TSSetErrorIfStepFails()` 4595 @*/ 4596 PetscErrorCode TSGetStepRejections(TS ts,PetscInt *rejects) 4597 { 4598 PetscFunctionBegin; 4599 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4600 PetscValidIntPointer(rejects,2); 4601 *rejects = ts->reject; 4602 PetscFunctionReturn(0); 4603 } 4604 4605 /*@ 4606 TSGetSNESFailures - Gets the total number of failed SNES solves 4607 4608 Not Collective 4609 4610 Input Parameter: 4611 . ts - TS context 4612 4613 Output Parameter: 4614 . fails - number of failed nonlinear solves 4615 4616 Notes: 4617 This counter is reset to zero for each successive call to TSSolve(). 4618 4619 Level: intermediate 4620 4621 .seealso: `TSGetSNESIterations()`, `TSGetKSPIterations()`, `TSSetMaxStepRejections()`, `TSGetStepRejections()`, `TSSetMaxSNESFailures()` 4622 @*/ 4623 PetscErrorCode TSGetSNESFailures(TS ts,PetscInt *fails) 4624 { 4625 PetscFunctionBegin; 4626 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4627 PetscValidIntPointer(fails,2); 4628 *fails = ts->num_snes_failures; 4629 PetscFunctionReturn(0); 4630 } 4631 4632 /*@ 4633 TSSetMaxStepRejections - Sets the maximum number of step rejections before a step fails 4634 4635 Not Collective 4636 4637 Input Parameters: 4638 + ts - TS context 4639 - rejects - maximum number of rejected steps, pass -1 for unlimited 4640 4641 Notes: 4642 The counter is reset to zero for each step 4643 4644 Options Database Key: 4645 . -ts_max_reject - Maximum number of step rejections before a step fails 4646 4647 Level: intermediate 4648 4649 .seealso: `TSGetSNESIterations()`, `TSGetKSPIterations()`, `TSSetMaxSNESFailures()`, `TSGetStepRejections()`, `TSGetSNESFailures()`, `TSSetErrorIfStepFails()`, `TSGetConvergedReason()` 4650 @*/ 4651 PetscErrorCode TSSetMaxStepRejections(TS ts,PetscInt rejects) 4652 { 4653 PetscFunctionBegin; 4654 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4655 ts->max_reject = rejects; 4656 PetscFunctionReturn(0); 4657 } 4658 4659 /*@ 4660 TSSetMaxSNESFailures - Sets the maximum number of failed SNES solves 4661 4662 Not Collective 4663 4664 Input Parameters: 4665 + ts - TS context 4666 - fails - maximum number of failed nonlinear solves, pass -1 for unlimited 4667 4668 Notes: 4669 The counter is reset to zero for each successive call to TSSolve(). 4670 4671 Options Database Key: 4672 . -ts_max_snes_failures - Maximum number of nonlinear solve failures 4673 4674 Level: intermediate 4675 4676 .seealso: `TSGetSNESIterations()`, `TSGetKSPIterations()`, `TSSetMaxStepRejections()`, `TSGetStepRejections()`, `TSGetSNESFailures()`, `SNESGetConvergedReason()`, `TSGetConvergedReason()` 4677 @*/ 4678 PetscErrorCode TSSetMaxSNESFailures(TS ts,PetscInt fails) 4679 { 4680 PetscFunctionBegin; 4681 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4682 ts->max_snes_failures = fails; 4683 PetscFunctionReturn(0); 4684 } 4685 4686 /*@ 4687 TSSetErrorIfStepFails - Error if no step succeeds 4688 4689 Not Collective 4690 4691 Input Parameters: 4692 + ts - TS context 4693 - err - PETSC_TRUE to error if no step succeeds, PETSC_FALSE to return without failure 4694 4695 Options Database Key: 4696 . -ts_error_if_step_fails - Error if no step succeeds 4697 4698 Level: intermediate 4699 4700 .seealso: `TSGetSNESIterations()`, `TSGetKSPIterations()`, `TSSetMaxStepRejections()`, `TSGetStepRejections()`, `TSGetSNESFailures()`, `TSSetErrorIfStepFails()`, `TSGetConvergedReason()` 4701 @*/ 4702 PetscErrorCode TSSetErrorIfStepFails(TS ts,PetscBool err) 4703 { 4704 PetscFunctionBegin; 4705 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4706 ts->errorifstepfailed = err; 4707 PetscFunctionReturn(0); 4708 } 4709 4710 /*@ 4711 TSGetAdapt - Get the adaptive controller context for the current method 4712 4713 Collective on TS if controller has not been created yet 4714 4715 Input Parameter: 4716 . ts - time stepping context 4717 4718 Output Parameter: 4719 . adapt - adaptive controller 4720 4721 Level: intermediate 4722 4723 .seealso: `TSAdapt`, `TSAdaptSetType()`, `TSAdaptChoose()` 4724 @*/ 4725 PetscErrorCode TSGetAdapt(TS ts,TSAdapt *adapt) 4726 { 4727 PetscFunctionBegin; 4728 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4729 PetscValidPointer(adapt,2); 4730 if (!ts->adapt) { 4731 PetscCall(TSAdaptCreate(PetscObjectComm((PetscObject)ts),&ts->adapt)); 4732 PetscCall(PetscLogObjectParent((PetscObject)ts,(PetscObject)ts->adapt)); 4733 PetscCall(PetscObjectIncrementTabLevel((PetscObject)ts->adapt,(PetscObject)ts,1)); 4734 } 4735 *adapt = ts->adapt; 4736 PetscFunctionReturn(0); 4737 } 4738 4739 /*@ 4740 TSSetTolerances - Set tolerances for local truncation error when using adaptive controller 4741 4742 Logically Collective 4743 4744 Input Parameters: 4745 + ts - time integration context 4746 . atol - scalar absolute tolerances, PETSC_DECIDE to leave current value 4747 . vatol - vector of absolute tolerances or NULL, used in preference to atol if present 4748 . rtol - scalar relative tolerances, PETSC_DECIDE to leave current value 4749 - vrtol - vector of relative tolerances or NULL, used in preference to atol if present 4750 4751 Options Database keys: 4752 + -ts_rtol <rtol> - relative tolerance for local truncation error 4753 - -ts_atol <atol> - Absolute tolerance for local truncation error 4754 4755 Notes: 4756 With PETSc's implicit schemes for DAE problems, the calculation of the local truncation error 4757 (LTE) includes both the differential and the algebraic variables. If one wants the LTE to be 4758 computed only for the differential or the algebraic part then this can be done using the vector of 4759 tolerances vatol. For example, by setting the tolerance vector with the desired tolerance for the 4760 differential part and infinity for the algebraic part, the LTE calculation will include only the 4761 differential variables. 4762 4763 Level: beginner 4764 4765 .seealso: `TS`, `TSAdapt`, `TSErrorWeightedNorm()`, `TSGetTolerances()` 4766 @*/ 4767 PetscErrorCode TSSetTolerances(TS ts,PetscReal atol,Vec vatol,PetscReal rtol,Vec vrtol) 4768 { 4769 PetscFunctionBegin; 4770 if (atol != PETSC_DECIDE && atol != PETSC_DEFAULT) ts->atol = atol; 4771 if (vatol) { 4772 PetscCall(PetscObjectReference((PetscObject)vatol)); 4773 PetscCall(VecDestroy(&ts->vatol)); 4774 ts->vatol = vatol; 4775 } 4776 if (rtol != PETSC_DECIDE && rtol != PETSC_DEFAULT) ts->rtol = rtol; 4777 if (vrtol) { 4778 PetscCall(PetscObjectReference((PetscObject)vrtol)); 4779 PetscCall(VecDestroy(&ts->vrtol)); 4780 ts->vrtol = vrtol; 4781 } 4782 PetscFunctionReturn(0); 4783 } 4784 4785 /*@ 4786 TSGetTolerances - Get tolerances for local truncation error when using adaptive controller 4787 4788 Logically Collective 4789 4790 Input Parameter: 4791 . ts - time integration context 4792 4793 Output Parameters: 4794 + atol - scalar absolute tolerances, NULL to ignore 4795 . vatol - vector of absolute tolerances, NULL to ignore 4796 . rtol - scalar relative tolerances, NULL to ignore 4797 - vrtol - vector of relative tolerances, NULL to ignore 4798 4799 Level: beginner 4800 4801 .seealso: `TS`, `TSAdapt`, `TSErrorWeightedNorm()`, `TSSetTolerances()` 4802 @*/ 4803 PetscErrorCode TSGetTolerances(TS ts,PetscReal *atol,Vec *vatol,PetscReal *rtol,Vec *vrtol) 4804 { 4805 PetscFunctionBegin; 4806 if (atol) *atol = ts->atol; 4807 if (vatol) *vatol = ts->vatol; 4808 if (rtol) *rtol = ts->rtol; 4809 if (vrtol) *vrtol = ts->vrtol; 4810 PetscFunctionReturn(0); 4811 } 4812 4813 /*@ 4814 TSErrorWeightedNorm2 - compute a weighted 2-norm of the difference between two state vectors 4815 4816 Collective on TS 4817 4818 Input Parameters: 4819 + ts - time stepping context 4820 . U - state vector, usually ts->vec_sol 4821 - Y - state vector to be compared to U 4822 4823 Output Parameters: 4824 + norm - weighted norm, a value of 1.0 means that the error matches the tolerances 4825 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 4826 - normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 4827 4828 Level: developer 4829 4830 .seealso: `TSErrorWeightedNorm()`, `TSErrorWeightedNormInfinity()` 4831 @*/ 4832 PetscErrorCode TSErrorWeightedNorm2(TS ts,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 4833 { 4834 PetscInt i,n,N,rstart; 4835 PetscInt n_loc,na_loc,nr_loc; 4836 PetscReal n_glb,na_glb,nr_glb; 4837 const PetscScalar *u,*y; 4838 PetscReal sum,suma,sumr,gsum,gsuma,gsumr,diff; 4839 PetscReal tol,tola,tolr; 4840 PetscReal err_loc[6],err_glb[6]; 4841 4842 PetscFunctionBegin; 4843 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4844 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 4845 PetscValidHeaderSpecific(Y,VEC_CLASSID,3); 4846 PetscValidType(U,2); 4847 PetscValidType(Y,3); 4848 PetscCheckSameComm(U,2,Y,3); 4849 PetscValidRealPointer(norm,4); 4850 PetscValidRealPointer(norma,5); 4851 PetscValidRealPointer(normr,6); 4852 PetscCheck(U != Y,PetscObjectComm((PetscObject)U),PETSC_ERR_ARG_IDN,"U and Y cannot be the same vector"); 4853 4854 PetscCall(VecGetSize(U,&N)); 4855 PetscCall(VecGetLocalSize(U,&n)); 4856 PetscCall(VecGetOwnershipRange(U,&rstart,NULL)); 4857 PetscCall(VecGetArrayRead(U,&u)); 4858 PetscCall(VecGetArrayRead(Y,&y)); 4859 sum = 0.; n_loc = 0; 4860 suma = 0.; na_loc = 0; 4861 sumr = 0.; nr_loc = 0; 4862 if (ts->vatol && ts->vrtol) { 4863 const PetscScalar *atol,*rtol; 4864 PetscCall(VecGetArrayRead(ts->vatol,&atol)); 4865 PetscCall(VecGetArrayRead(ts->vrtol,&rtol)); 4866 for (i=0; i<n; i++) { 4867 SkipSmallValue(y[i],u[i],ts->adapt->ignore_max); 4868 diff = PetscAbsScalar(y[i] - u[i]); 4869 tola = PetscRealPart(atol[i]); 4870 if (tola>0.) { 4871 suma += PetscSqr(diff/tola); 4872 na_loc++; 4873 } 4874 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 4875 if (tolr>0.) { 4876 sumr += PetscSqr(diff/tolr); 4877 nr_loc++; 4878 } 4879 tol=tola+tolr; 4880 if (tol>0.) { 4881 sum += PetscSqr(diff/tol); 4882 n_loc++; 4883 } 4884 } 4885 PetscCall(VecRestoreArrayRead(ts->vatol,&atol)); 4886 PetscCall(VecRestoreArrayRead(ts->vrtol,&rtol)); 4887 } else if (ts->vatol) { /* vector atol, scalar rtol */ 4888 const PetscScalar *atol; 4889 PetscCall(VecGetArrayRead(ts->vatol,&atol)); 4890 for (i=0; i<n; i++) { 4891 SkipSmallValue(y[i],u[i],ts->adapt->ignore_max); 4892 diff = PetscAbsScalar(y[i] - u[i]); 4893 tola = PetscRealPart(atol[i]); 4894 if (tola>0.) { 4895 suma += PetscSqr(diff/tola); 4896 na_loc++; 4897 } 4898 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 4899 if (tolr>0.) { 4900 sumr += PetscSqr(diff/tolr); 4901 nr_loc++; 4902 } 4903 tol=tola+tolr; 4904 if (tol>0.) { 4905 sum += PetscSqr(diff/tol); 4906 n_loc++; 4907 } 4908 } 4909 PetscCall(VecRestoreArrayRead(ts->vatol,&atol)); 4910 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 4911 const PetscScalar *rtol; 4912 PetscCall(VecGetArrayRead(ts->vrtol,&rtol)); 4913 for (i=0; i<n; i++) { 4914 SkipSmallValue(y[i],u[i],ts->adapt->ignore_max); 4915 diff = PetscAbsScalar(y[i] - u[i]); 4916 tola = ts->atol; 4917 if (tola>0.) { 4918 suma += PetscSqr(diff/tola); 4919 na_loc++; 4920 } 4921 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 4922 if (tolr>0.) { 4923 sumr += PetscSqr(diff/tolr); 4924 nr_loc++; 4925 } 4926 tol=tola+tolr; 4927 if (tol>0.) { 4928 sum += PetscSqr(diff/tol); 4929 n_loc++; 4930 } 4931 } 4932 PetscCall(VecRestoreArrayRead(ts->vrtol,&rtol)); 4933 } else { /* scalar atol, scalar rtol */ 4934 for (i=0; i<n; i++) { 4935 SkipSmallValue(y[i],u[i],ts->adapt->ignore_max); 4936 diff = PetscAbsScalar(y[i] - u[i]); 4937 tola = ts->atol; 4938 if (tola>0.) { 4939 suma += PetscSqr(diff/tola); 4940 na_loc++; 4941 } 4942 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 4943 if (tolr>0.) { 4944 sumr += PetscSqr(diff/tolr); 4945 nr_loc++; 4946 } 4947 tol=tola+tolr; 4948 if (tol>0.) { 4949 sum += PetscSqr(diff/tol); 4950 n_loc++; 4951 } 4952 } 4953 } 4954 PetscCall(VecRestoreArrayRead(U,&u)); 4955 PetscCall(VecRestoreArrayRead(Y,&y)); 4956 4957 err_loc[0] = sum; 4958 err_loc[1] = suma; 4959 err_loc[2] = sumr; 4960 err_loc[3] = (PetscReal)n_loc; 4961 err_loc[4] = (PetscReal)na_loc; 4962 err_loc[5] = (PetscReal)nr_loc; 4963 4964 PetscCall(MPIU_Allreduce(err_loc,err_glb,6,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)ts))); 4965 4966 gsum = err_glb[0]; 4967 gsuma = err_glb[1]; 4968 gsumr = err_glb[2]; 4969 n_glb = err_glb[3]; 4970 na_glb = err_glb[4]; 4971 nr_glb = err_glb[5]; 4972 4973 *norm = 0.; 4974 if (n_glb>0.) *norm = PetscSqrtReal(gsum / n_glb); 4975 *norma = 0.; 4976 if (na_glb>0.) *norma = PetscSqrtReal(gsuma / na_glb); 4977 *normr = 0.; 4978 if (nr_glb>0.) *normr = PetscSqrtReal(gsumr / nr_glb); 4979 4980 PetscCheck(!PetscIsInfOrNanScalar(*norm),PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 4981 PetscCheck(!PetscIsInfOrNanScalar(*norma),PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 4982 PetscCheck(!PetscIsInfOrNanScalar(*normr),PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 4983 PetscFunctionReturn(0); 4984 } 4985 4986 /*@ 4987 TSErrorWeightedNormInfinity - compute a weighted infinity-norm of the difference between two state vectors 4988 4989 Collective on TS 4990 4991 Input Parameters: 4992 + ts - time stepping context 4993 . U - state vector, usually ts->vec_sol 4994 - Y - state vector to be compared to U 4995 4996 Output Parameters: 4997 + norm - weighted norm, a value of 1.0 means that the error matches the tolerances 4998 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 4999 - normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 5000 5001 Level: developer 5002 5003 .seealso: `TSErrorWeightedNorm()`, `TSErrorWeightedNorm2()` 5004 @*/ 5005 PetscErrorCode TSErrorWeightedNormInfinity(TS ts,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 5006 { 5007 PetscInt i,n,N,rstart; 5008 const PetscScalar *u,*y; 5009 PetscReal max,gmax,maxa,gmaxa,maxr,gmaxr; 5010 PetscReal tol,tola,tolr,diff; 5011 PetscReal err_loc[3],err_glb[3]; 5012 5013 PetscFunctionBegin; 5014 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5015 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 5016 PetscValidHeaderSpecific(Y,VEC_CLASSID,3); 5017 PetscValidType(U,2); 5018 PetscValidType(Y,3); 5019 PetscCheckSameComm(U,2,Y,3); 5020 PetscValidRealPointer(norm,4); 5021 PetscValidRealPointer(norma,5); 5022 PetscValidRealPointer(normr,6); 5023 PetscCheck(U != Y,PetscObjectComm((PetscObject)U),PETSC_ERR_ARG_IDN,"U and Y cannot be the same vector"); 5024 5025 PetscCall(VecGetSize(U,&N)); 5026 PetscCall(VecGetLocalSize(U,&n)); 5027 PetscCall(VecGetOwnershipRange(U,&rstart,NULL)); 5028 PetscCall(VecGetArrayRead(U,&u)); 5029 PetscCall(VecGetArrayRead(Y,&y)); 5030 5031 max=0.; 5032 maxa=0.; 5033 maxr=0.; 5034 5035 if (ts->vatol && ts->vrtol) { /* vector atol, vector rtol */ 5036 const PetscScalar *atol,*rtol; 5037 PetscCall(VecGetArrayRead(ts->vatol,&atol)); 5038 PetscCall(VecGetArrayRead(ts->vrtol,&rtol)); 5039 5040 for (i=0; i<n; i++) { 5041 SkipSmallValue(y[i],u[i],ts->adapt->ignore_max); 5042 diff = PetscAbsScalar(y[i] - u[i]); 5043 tola = PetscRealPart(atol[i]); 5044 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5045 tol = tola+tolr; 5046 if (tola>0.) maxa = PetscMax(maxa,diff / tola); 5047 if (tolr>0.) maxr = PetscMax(maxr,diff / tolr); 5048 if (tol>0.) max = PetscMax(max,diff / tol); 5049 } 5050 PetscCall(VecRestoreArrayRead(ts->vatol,&atol)); 5051 PetscCall(VecRestoreArrayRead(ts->vrtol,&rtol)); 5052 } else if (ts->vatol) { /* vector atol, scalar rtol */ 5053 const PetscScalar *atol; 5054 PetscCall(VecGetArrayRead(ts->vatol,&atol)); 5055 for (i=0; i<n; i++) { 5056 SkipSmallValue(y[i],u[i],ts->adapt->ignore_max); 5057 diff = PetscAbsScalar(y[i] - u[i]); 5058 tola = PetscRealPart(atol[i]); 5059 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5060 tol = tola+tolr; 5061 if (tola>0.) maxa = PetscMax(maxa,diff / tola); 5062 if (tolr>0.) maxr = PetscMax(maxr,diff / tolr); 5063 if (tol>0.) max = PetscMax(max,diff / tol); 5064 } 5065 PetscCall(VecRestoreArrayRead(ts->vatol,&atol)); 5066 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 5067 const PetscScalar *rtol; 5068 PetscCall(VecGetArrayRead(ts->vrtol,&rtol)); 5069 5070 for (i=0; i<n; i++) { 5071 SkipSmallValue(y[i],u[i],ts->adapt->ignore_max); 5072 diff = PetscAbsScalar(y[i] - u[i]); 5073 tola = ts->atol; 5074 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5075 tol = tola+tolr; 5076 if (tola>0.) maxa = PetscMax(maxa,diff / tola); 5077 if (tolr>0.) maxr = PetscMax(maxr,diff / tolr); 5078 if (tol>0.) max = PetscMax(max,diff / tol); 5079 } 5080 PetscCall(VecRestoreArrayRead(ts->vrtol,&rtol)); 5081 } else { /* scalar atol, scalar rtol */ 5082 5083 for (i=0; i<n; i++) { 5084 SkipSmallValue(y[i],u[i],ts->adapt->ignore_max); 5085 diff = PetscAbsScalar(y[i] - u[i]); 5086 tola = ts->atol; 5087 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5088 tol = tola+tolr; 5089 if (tola>0.) maxa = PetscMax(maxa,diff / tola); 5090 if (tolr>0.) maxr = PetscMax(maxr,diff / tolr); 5091 if (tol>0.) max = PetscMax(max,diff / tol); 5092 } 5093 } 5094 PetscCall(VecRestoreArrayRead(U,&u)); 5095 PetscCall(VecRestoreArrayRead(Y,&y)); 5096 err_loc[0] = max; 5097 err_loc[1] = maxa; 5098 err_loc[2] = maxr; 5099 PetscCall(MPIU_Allreduce(err_loc,err_glb,3,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)ts))); 5100 gmax = err_glb[0]; 5101 gmaxa = err_glb[1]; 5102 gmaxr = err_glb[2]; 5103 5104 *norm = gmax; 5105 *norma = gmaxa; 5106 *normr = gmaxr; 5107 PetscCheck(!PetscIsInfOrNanScalar(*norm),PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 5108 PetscCheck(!PetscIsInfOrNanScalar(*norma),PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 5109 PetscCheck(!PetscIsInfOrNanScalar(*normr),PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 5110 PetscFunctionReturn(0); 5111 } 5112 5113 /*@ 5114 TSErrorWeightedNorm - compute a weighted norm of the difference between two state vectors based on supplied absolute and relative tolerances 5115 5116 Collective on TS 5117 5118 Input Parameters: 5119 + ts - time stepping context 5120 . U - state vector, usually ts->vec_sol 5121 . Y - state vector to be compared to U 5122 - wnormtype - norm type, either NORM_2 or NORM_INFINITY 5123 5124 Output Parameters: 5125 + norm - weighted norm, a value of 1.0 achieves a balance between absolute and relative tolerances 5126 . norma - weighted norm, a value of 1.0 means that the error meets the absolute tolerance set by the user 5127 - normr - weighted norm, a value of 1.0 means that the error meets the relative tolerance set by the user 5128 5129 Options Database Keys: 5130 . -ts_adapt_wnormtype <wnormtype> - 2, INFINITY 5131 5132 Level: developer 5133 5134 .seealso: `TSErrorWeightedNormInfinity()`, `TSErrorWeightedNorm2()`, `TSErrorWeightedENorm` 5135 @*/ 5136 PetscErrorCode TSErrorWeightedNorm(TS ts,Vec U,Vec Y,NormType wnormtype,PetscReal *norm,PetscReal *norma,PetscReal *normr) 5137 { 5138 PetscFunctionBegin; 5139 if (wnormtype == NORM_2) PetscCall(TSErrorWeightedNorm2(ts,U,Y,norm,norma,normr)); 5140 else if (wnormtype == NORM_INFINITY) PetscCall(TSErrorWeightedNormInfinity(ts,U,Y,norm,norma,normr)); 5141 else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]); 5142 PetscFunctionReturn(0); 5143 } 5144 5145 /*@ 5146 TSErrorWeightedENorm2 - compute a weighted 2 error norm based on supplied absolute and relative tolerances 5147 5148 Collective on TS 5149 5150 Input Parameters: 5151 + ts - time stepping context 5152 . E - error vector 5153 . U - state vector, usually ts->vec_sol 5154 - Y - state vector, previous time step 5155 5156 Output Parameters: 5157 + norm - weighted norm, a value of 1.0 means that the error matches the tolerances 5158 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 5159 - normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 5160 5161 Level: developer 5162 5163 .seealso: `TSErrorWeightedENorm()`, `TSErrorWeightedENormInfinity()` 5164 @*/ 5165 PetscErrorCode TSErrorWeightedENorm2(TS ts,Vec E,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 5166 { 5167 PetscInt i,n,N,rstart; 5168 PetscInt n_loc,na_loc,nr_loc; 5169 PetscReal n_glb,na_glb,nr_glb; 5170 const PetscScalar *e,*u,*y; 5171 PetscReal err,sum,suma,sumr,gsum,gsuma,gsumr; 5172 PetscReal tol,tola,tolr; 5173 PetscReal err_loc[6],err_glb[6]; 5174 5175 PetscFunctionBegin; 5176 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5177 PetscValidHeaderSpecific(E,VEC_CLASSID,2); 5178 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 5179 PetscValidHeaderSpecific(Y,VEC_CLASSID,4); 5180 PetscValidType(E,2); 5181 PetscValidType(U,3); 5182 PetscValidType(Y,4); 5183 PetscCheckSameComm(E,2,U,3); 5184 PetscCheckSameComm(U,3,Y,4); 5185 PetscValidRealPointer(norm,5); 5186 PetscValidRealPointer(norma,6); 5187 PetscValidRealPointer(normr,7); 5188 5189 PetscCall(VecGetSize(E,&N)); 5190 PetscCall(VecGetLocalSize(E,&n)); 5191 PetscCall(VecGetOwnershipRange(E,&rstart,NULL)); 5192 PetscCall(VecGetArrayRead(E,&e)); 5193 PetscCall(VecGetArrayRead(U,&u)); 5194 PetscCall(VecGetArrayRead(Y,&y)); 5195 sum = 0.; n_loc = 0; 5196 suma = 0.; na_loc = 0; 5197 sumr = 0.; nr_loc = 0; 5198 if (ts->vatol && ts->vrtol) { 5199 const PetscScalar *atol,*rtol; 5200 PetscCall(VecGetArrayRead(ts->vatol,&atol)); 5201 PetscCall(VecGetArrayRead(ts->vrtol,&rtol)); 5202 for (i=0; i<n; i++) { 5203 SkipSmallValue(y[i],u[i],ts->adapt->ignore_max); 5204 err = PetscAbsScalar(e[i]); 5205 tola = PetscRealPart(atol[i]); 5206 if (tola>0.) { 5207 suma += PetscSqr(err/tola); 5208 na_loc++; 5209 } 5210 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5211 if (tolr>0.) { 5212 sumr += PetscSqr(err/tolr); 5213 nr_loc++; 5214 } 5215 tol=tola+tolr; 5216 if (tol>0.) { 5217 sum += PetscSqr(err/tol); 5218 n_loc++; 5219 } 5220 } 5221 PetscCall(VecRestoreArrayRead(ts->vatol,&atol)); 5222 PetscCall(VecRestoreArrayRead(ts->vrtol,&rtol)); 5223 } else if (ts->vatol) { /* vector atol, scalar rtol */ 5224 const PetscScalar *atol; 5225 PetscCall(VecGetArrayRead(ts->vatol,&atol)); 5226 for (i=0; i<n; i++) { 5227 SkipSmallValue(y[i],u[i],ts->adapt->ignore_max); 5228 err = PetscAbsScalar(e[i]); 5229 tola = PetscRealPart(atol[i]); 5230 if (tola>0.) { 5231 suma += PetscSqr(err/tola); 5232 na_loc++; 5233 } 5234 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5235 if (tolr>0.) { 5236 sumr += PetscSqr(err/tolr); 5237 nr_loc++; 5238 } 5239 tol=tola+tolr; 5240 if (tol>0.) { 5241 sum += PetscSqr(err/tol); 5242 n_loc++; 5243 } 5244 } 5245 PetscCall(VecRestoreArrayRead(ts->vatol,&atol)); 5246 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 5247 const PetscScalar *rtol; 5248 PetscCall(VecGetArrayRead(ts->vrtol,&rtol)); 5249 for (i=0; i<n; i++) { 5250 SkipSmallValue(y[i],u[i],ts->adapt->ignore_max); 5251 err = PetscAbsScalar(e[i]); 5252 tola = ts->atol; 5253 if (tola>0.) { 5254 suma += PetscSqr(err/tola); 5255 na_loc++; 5256 } 5257 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5258 if (tolr>0.) { 5259 sumr += PetscSqr(err/tolr); 5260 nr_loc++; 5261 } 5262 tol=tola+tolr; 5263 if (tol>0.) { 5264 sum += PetscSqr(err/tol); 5265 n_loc++; 5266 } 5267 } 5268 PetscCall(VecRestoreArrayRead(ts->vrtol,&rtol)); 5269 } else { /* scalar atol, scalar rtol */ 5270 for (i=0; i<n; i++) { 5271 SkipSmallValue(y[i],u[i],ts->adapt->ignore_max); 5272 err = PetscAbsScalar(e[i]); 5273 tola = ts->atol; 5274 if (tola>0.) { 5275 suma += PetscSqr(err/tola); 5276 na_loc++; 5277 } 5278 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5279 if (tolr>0.) { 5280 sumr += PetscSqr(err/tolr); 5281 nr_loc++; 5282 } 5283 tol=tola+tolr; 5284 if (tol>0.) { 5285 sum += PetscSqr(err/tol); 5286 n_loc++; 5287 } 5288 } 5289 } 5290 PetscCall(VecRestoreArrayRead(E,&e)); 5291 PetscCall(VecRestoreArrayRead(U,&u)); 5292 PetscCall(VecRestoreArrayRead(Y,&y)); 5293 5294 err_loc[0] = sum; 5295 err_loc[1] = suma; 5296 err_loc[2] = sumr; 5297 err_loc[3] = (PetscReal)n_loc; 5298 err_loc[4] = (PetscReal)na_loc; 5299 err_loc[5] = (PetscReal)nr_loc; 5300 5301 PetscCall(MPIU_Allreduce(err_loc,err_glb,6,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)ts))); 5302 5303 gsum = err_glb[0]; 5304 gsuma = err_glb[1]; 5305 gsumr = err_glb[2]; 5306 n_glb = err_glb[3]; 5307 na_glb = err_glb[4]; 5308 nr_glb = err_glb[5]; 5309 5310 *norm = 0.; 5311 if (n_glb>0.) *norm = PetscSqrtReal(gsum / n_glb); 5312 *norma = 0.; 5313 if (na_glb>0.) *norma = PetscSqrtReal(gsuma / na_glb); 5314 *normr = 0.; 5315 if (nr_glb>0.) *normr = PetscSqrtReal(gsumr / nr_glb); 5316 5317 PetscCheck(!PetscIsInfOrNanScalar(*norm),PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 5318 PetscCheck(!PetscIsInfOrNanScalar(*norma),PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 5319 PetscCheck(!PetscIsInfOrNanScalar(*normr),PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 5320 PetscFunctionReturn(0); 5321 } 5322 5323 /*@ 5324 TSErrorWeightedENormInfinity - compute a weighted infinity error norm based on supplied absolute and relative tolerances 5325 Collective on TS 5326 5327 Input Parameters: 5328 + ts - time stepping context 5329 . E - error vector 5330 . U - state vector, usually ts->vec_sol 5331 - Y - state vector, previous time step 5332 5333 Output Parameters: 5334 + norm - weighted norm, a value of 1.0 means that the error matches the tolerances 5335 . norma - weighted norm based on the absolute tolerance, a value of 1.0 means that the error matches the tolerances 5336 - normr - weighted norm based on the relative tolerance, a value of 1.0 means that the error matches the tolerances 5337 5338 Level: developer 5339 5340 .seealso: `TSErrorWeightedENorm()`, `TSErrorWeightedENorm2()` 5341 @*/ 5342 PetscErrorCode TSErrorWeightedENormInfinity(TS ts,Vec E,Vec U,Vec Y,PetscReal *norm,PetscReal *norma,PetscReal *normr) 5343 { 5344 PetscInt i,n,N,rstart; 5345 const PetscScalar *e,*u,*y; 5346 PetscReal err,max,gmax,maxa,gmaxa,maxr,gmaxr; 5347 PetscReal tol,tola,tolr; 5348 PetscReal err_loc[3],err_glb[3]; 5349 5350 PetscFunctionBegin; 5351 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5352 PetscValidHeaderSpecific(E,VEC_CLASSID,2); 5353 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 5354 PetscValidHeaderSpecific(Y,VEC_CLASSID,4); 5355 PetscValidType(E,2); 5356 PetscValidType(U,3); 5357 PetscValidType(Y,4); 5358 PetscCheckSameComm(E,2,U,3); 5359 PetscCheckSameComm(U,3,Y,4); 5360 PetscValidRealPointer(norm,5); 5361 PetscValidRealPointer(norma,6); 5362 PetscValidRealPointer(normr,7); 5363 5364 PetscCall(VecGetSize(E,&N)); 5365 PetscCall(VecGetLocalSize(E,&n)); 5366 PetscCall(VecGetOwnershipRange(E,&rstart,NULL)); 5367 PetscCall(VecGetArrayRead(E,&e)); 5368 PetscCall(VecGetArrayRead(U,&u)); 5369 PetscCall(VecGetArrayRead(Y,&y)); 5370 5371 max=0.; 5372 maxa=0.; 5373 maxr=0.; 5374 5375 if (ts->vatol && ts->vrtol) { /* vector atol, vector rtol */ 5376 const PetscScalar *atol,*rtol; 5377 PetscCall(VecGetArrayRead(ts->vatol,&atol)); 5378 PetscCall(VecGetArrayRead(ts->vrtol,&rtol)); 5379 5380 for (i=0; i<n; i++) { 5381 SkipSmallValue(y[i],u[i],ts->adapt->ignore_max); 5382 err = PetscAbsScalar(e[i]); 5383 tola = PetscRealPart(atol[i]); 5384 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5385 tol = tola+tolr; 5386 if (tola>0.) maxa = PetscMax(maxa,err / tola); 5387 if (tolr>0.) maxr = PetscMax(maxr,err / tolr); 5388 if (tol>0.) max = PetscMax(max,err / tol); 5389 } 5390 PetscCall(VecRestoreArrayRead(ts->vatol,&atol)); 5391 PetscCall(VecRestoreArrayRead(ts->vrtol,&rtol)); 5392 } else if (ts->vatol) { /* vector atol, scalar rtol */ 5393 const PetscScalar *atol; 5394 PetscCall(VecGetArrayRead(ts->vatol,&atol)); 5395 for (i=0; i<n; i++) { 5396 SkipSmallValue(y[i],u[i],ts->adapt->ignore_max); 5397 err = PetscAbsScalar(e[i]); 5398 tola = PetscRealPart(atol[i]); 5399 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5400 tol = tola+tolr; 5401 if (tola>0.) maxa = PetscMax(maxa,err / tola); 5402 if (tolr>0.) maxr = PetscMax(maxr,err / tolr); 5403 if (tol>0.) max = PetscMax(max,err / tol); 5404 } 5405 PetscCall(VecRestoreArrayRead(ts->vatol,&atol)); 5406 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 5407 const PetscScalar *rtol; 5408 PetscCall(VecGetArrayRead(ts->vrtol,&rtol)); 5409 5410 for (i=0; i<n; i++) { 5411 SkipSmallValue(y[i],u[i],ts->adapt->ignore_max); 5412 err = PetscAbsScalar(e[i]); 5413 tola = ts->atol; 5414 tolr = PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5415 tol = tola+tolr; 5416 if (tola>0.) maxa = PetscMax(maxa,err / tola); 5417 if (tolr>0.) maxr = PetscMax(maxr,err / tolr); 5418 if (tol>0.) max = PetscMax(max,err / tol); 5419 } 5420 PetscCall(VecRestoreArrayRead(ts->vrtol,&rtol)); 5421 } else { /* scalar atol, scalar rtol */ 5422 5423 for (i=0; i<n; i++) { 5424 SkipSmallValue(y[i],u[i],ts->adapt->ignore_max); 5425 err = PetscAbsScalar(e[i]); 5426 tola = ts->atol; 5427 tolr = ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5428 tol = tola+tolr; 5429 if (tola>0.) maxa = PetscMax(maxa,err / tola); 5430 if (tolr>0.) maxr = PetscMax(maxr,err / tolr); 5431 if (tol>0.) max = PetscMax(max,err / tol); 5432 } 5433 } 5434 PetscCall(VecRestoreArrayRead(E,&e)); 5435 PetscCall(VecRestoreArrayRead(U,&u)); 5436 PetscCall(VecRestoreArrayRead(Y,&y)); 5437 err_loc[0] = max; 5438 err_loc[1] = maxa; 5439 err_loc[2] = maxr; 5440 PetscCall(MPIU_Allreduce(err_loc,err_glb,3,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)ts))); 5441 gmax = err_glb[0]; 5442 gmaxa = err_glb[1]; 5443 gmaxr = err_glb[2]; 5444 5445 *norm = gmax; 5446 *norma = gmaxa; 5447 *normr = gmaxr; 5448 PetscCheck(!PetscIsInfOrNanScalar(*norm),PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 5449 PetscCheck(!PetscIsInfOrNanScalar(*norma),PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norma"); 5450 PetscCheck(!PetscIsInfOrNanScalar(*normr),PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in normr"); 5451 PetscFunctionReturn(0); 5452 } 5453 5454 /*@ 5455 TSErrorWeightedENorm - compute a weighted error norm based on supplied absolute and relative tolerances 5456 5457 Collective on TS 5458 5459 Input Parameters: 5460 + ts - time stepping context 5461 . E - error vector 5462 . U - state vector, usually ts->vec_sol 5463 . Y - state vector, previous time step 5464 - wnormtype - norm type, either NORM_2 or NORM_INFINITY 5465 5466 Output Parameters: 5467 + norm - weighted norm, a value of 1.0 achieves a balance between absolute and relative tolerances 5468 . norma - weighted norm, a value of 1.0 means that the error meets the absolute tolerance set by the user 5469 - normr - weighted norm, a value of 1.0 means that the error meets the relative tolerance set by the user 5470 5471 Options Database Keys: 5472 . -ts_adapt_wnormtype <wnormtype> - 2, INFINITY 5473 5474 Level: developer 5475 5476 .seealso: `TSErrorWeightedENormInfinity()`, `TSErrorWeightedENorm2()`, `TSErrorWeightedNormInfinity()`, `TSErrorWeightedNorm2()` 5477 @*/ 5478 PetscErrorCode TSErrorWeightedENorm(TS ts,Vec E,Vec U,Vec Y,NormType wnormtype,PetscReal *norm,PetscReal *norma,PetscReal *normr) 5479 { 5480 PetscFunctionBegin; 5481 if (wnormtype == NORM_2)PetscCall(TSErrorWeightedENorm2(ts,E,U,Y,norm,norma,normr)); 5482 else if (wnormtype == NORM_INFINITY) PetscCall(TSErrorWeightedENormInfinity(ts,E,U,Y,norm,norma,normr)); 5483 else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]); 5484 PetscFunctionReturn(0); 5485 } 5486 5487 /*@ 5488 TSSetCFLTimeLocal - Set the local CFL constraint relative to forward Euler 5489 5490 Logically Collective on TS 5491 5492 Input Parameters: 5493 + ts - time stepping context 5494 - cfltime - maximum stable time step if using forward Euler (value can be different on each process) 5495 5496 Note: 5497 After calling this function, the global CFL time can be obtained by calling TSGetCFLTime() 5498 5499 Level: intermediate 5500 5501 .seealso: `TSGetCFLTime()`, `TSADAPTCFL` 5502 @*/ 5503 PetscErrorCode TSSetCFLTimeLocal(TS ts,PetscReal cfltime) 5504 { 5505 PetscFunctionBegin; 5506 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5507 ts->cfltime_local = cfltime; 5508 ts->cfltime = -1.; 5509 PetscFunctionReturn(0); 5510 } 5511 5512 /*@ 5513 TSGetCFLTime - Get the maximum stable time step according to CFL criteria applied to forward Euler 5514 5515 Collective on TS 5516 5517 Input Parameter: 5518 . ts - time stepping context 5519 5520 Output Parameter: 5521 . cfltime - maximum stable time step for forward Euler 5522 5523 Level: advanced 5524 5525 .seealso: `TSSetCFLTimeLocal()` 5526 @*/ 5527 PetscErrorCode TSGetCFLTime(TS ts,PetscReal *cfltime) 5528 { 5529 PetscFunctionBegin; 5530 if (ts->cfltime < 0) PetscCall(MPIU_Allreduce(&ts->cfltime_local,&ts->cfltime,1,MPIU_REAL,MPIU_MIN,PetscObjectComm((PetscObject)ts))); 5531 *cfltime = ts->cfltime; 5532 PetscFunctionReturn(0); 5533 } 5534 5535 /*@ 5536 TSVISetVariableBounds - Sets the lower and upper bounds for the solution vector. xl <= x <= xu 5537 5538 Input Parameters: 5539 + ts - the TS context. 5540 . xl - lower bound. 5541 - xu - upper bound. 5542 5543 Notes: 5544 If this routine is not called then the lower and upper bounds are set to 5545 PETSC_NINFINITY and PETSC_INFINITY respectively during SNESSetUp(). 5546 5547 Level: advanced 5548 5549 @*/ 5550 PetscErrorCode TSVISetVariableBounds(TS ts, Vec xl, Vec xu) 5551 { 5552 SNES snes; 5553 5554 PetscFunctionBegin; 5555 PetscCall(TSGetSNES(ts,&snes)); 5556 PetscCall(SNESVISetVariableBounds(snes,xl,xu)); 5557 PetscFunctionReturn(0); 5558 } 5559 5560 /*@ 5561 TSComputeLinearStability - computes the linear stability function at a point 5562 5563 Collective on TS 5564 5565 Input Parameters: 5566 + ts - the TS context 5567 - xr,xi - real and imaginary part of input arguments 5568 5569 Output Parameters: 5570 . yr,yi - real and imaginary part of function value 5571 5572 Level: developer 5573 5574 .seealso: `TSSetRHSFunction()`, `TSComputeIFunction()` 5575 @*/ 5576 PetscErrorCode TSComputeLinearStability(TS ts,PetscReal xr,PetscReal xi,PetscReal *yr,PetscReal *yi) 5577 { 5578 PetscFunctionBegin; 5579 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5580 PetscUseTypeMethod(ts,linearstability ,xr,xi,yr,yi); 5581 PetscFunctionReturn(0); 5582 } 5583 5584 /*@ 5585 TSRestartStep - Flags the solver to restart the next step 5586 5587 Collective on TS 5588 5589 Input Parameter: 5590 . ts - the TS context obtained from TSCreate() 5591 5592 Level: advanced 5593 5594 Notes: 5595 Multistep methods like BDF or Runge-Kutta methods with FSAL property require restarting the solver in the event of 5596 discontinuities. These discontinuities may be introduced as a consequence of explicitly modifications to the solution 5597 vector (which PETSc attempts to detect and handle) or problem coefficients (which PETSc is not able to detect). For 5598 the sake of correctness and maximum safety, users are expected to call TSRestart() whenever they introduce 5599 discontinuities in callback routines (e.g. prestep and poststep routines, or implicit/rhs function routines with 5600 discontinuous source terms). 5601 5602 .seealso: `TSSolve()`, `TSSetPreStep()`, `TSSetPostStep()` 5603 @*/ 5604 PetscErrorCode TSRestartStep(TS ts) 5605 { 5606 PetscFunctionBegin; 5607 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5608 ts->steprestart = PETSC_TRUE; 5609 PetscFunctionReturn(0); 5610 } 5611 5612 /*@ 5613 TSRollBack - Rolls back one time step 5614 5615 Collective on TS 5616 5617 Input Parameter: 5618 . ts - the TS context obtained from TSCreate() 5619 5620 Level: advanced 5621 5622 .seealso: `TSCreate()`, `TSSetUp()`, `TSDestroy()`, `TSSolve()`, `TSSetPreStep()`, `TSSetPreStage()`, `TSInterpolate()` 5623 @*/ 5624 PetscErrorCode TSRollBack(TS ts) 5625 { 5626 PetscFunctionBegin; 5627 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 5628 PetscCheck(!ts->steprollback,PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONGSTATE,"TSRollBack already called"); 5629 PetscUseTypeMethod(ts,rollback); 5630 ts->time_step = ts->ptime - ts->ptime_prev; 5631 ts->ptime = ts->ptime_prev; 5632 ts->ptime_prev = ts->ptime_prev_rollback; 5633 ts->steps--; 5634 ts->steprollback = PETSC_TRUE; 5635 PetscFunctionReturn(0); 5636 } 5637 5638 /*@ 5639 TSGetStages - Get the number of stages and stage values 5640 5641 Input Parameter: 5642 . ts - the TS context obtained from TSCreate() 5643 5644 Output Parameters: 5645 + ns - the number of stages 5646 - Y - the current stage vectors 5647 5648 Level: advanced 5649 5650 Notes: Both ns and Y can be NULL. 5651 5652 .seealso: `TSCreate()` 5653 @*/ 5654 PetscErrorCode TSGetStages(TS ts,PetscInt *ns,Vec **Y) 5655 { 5656 PetscFunctionBegin; 5657 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 5658 if (ns) PetscValidIntPointer(ns,2); 5659 if (Y) PetscValidPointer(Y,3); 5660 if (!ts->ops->getstages) { 5661 if (ns) *ns = 0; 5662 if (Y) *Y = NULL; 5663 } else PetscUseTypeMethod(ts,getstages ,ns,Y); 5664 PetscFunctionReturn(0); 5665 } 5666 5667 /*@C 5668 TSComputeIJacobianDefaultColor - Computes the Jacobian using finite differences and coloring to exploit matrix sparsity. 5669 5670 Collective on SNES 5671 5672 Input Parameters: 5673 + ts - the TS context 5674 . t - current timestep 5675 . U - state vector 5676 . Udot - time derivative of state vector 5677 . shift - shift to apply, see note below 5678 - ctx - an optional user context 5679 5680 Output Parameters: 5681 + J - Jacobian matrix (not altered in this routine) 5682 - B - newly computed Jacobian matrix to use with preconditioner (generally the same as J) 5683 5684 Level: intermediate 5685 5686 Notes: 5687 If F(t,U,Udot)=0 is the DAE, the required Jacobian is 5688 5689 dF/dU + shift*dF/dUdot 5690 5691 Most users should not need to explicitly call this routine, as it 5692 is used internally within the nonlinear solvers. 5693 5694 This will first try to get the coloring from the DM. If the DM type has no coloring 5695 routine, then it will try to get the coloring from the matrix. This requires that the 5696 matrix have nonzero entries precomputed. 5697 5698 .seealso: `TSSetIJacobian()`, `MatFDColoringCreate()`, `MatFDColoringSetFunction()` 5699 @*/ 5700 PetscErrorCode TSComputeIJacobianDefaultColor(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat J,Mat B,void *ctx) 5701 { 5702 SNES snes; 5703 MatFDColoring color; 5704 PetscBool hascolor, matcolor = PETSC_FALSE; 5705 5706 PetscFunctionBegin; 5707 PetscCall(PetscOptionsGetBool(((PetscObject)ts)->options,((PetscObject) ts)->prefix, "-ts_fd_color_use_mat", &matcolor, NULL)); 5708 PetscCall(PetscObjectQuery((PetscObject) B, "TSMatFDColoring", (PetscObject *) &color)); 5709 if (!color) { 5710 DM dm; 5711 ISColoring iscoloring; 5712 5713 PetscCall(TSGetDM(ts, &dm)); 5714 PetscCall(DMHasColoring(dm, &hascolor)); 5715 if (hascolor && !matcolor) { 5716 PetscCall(DMCreateColoring(dm, IS_COLORING_GLOBAL, &iscoloring)); 5717 PetscCall(MatFDColoringCreate(B, iscoloring, &color)); 5718 PetscCall(MatFDColoringSetFunction(color, (PetscErrorCode (*)(void)) SNESTSFormFunction, (void *) ts)); 5719 PetscCall(MatFDColoringSetFromOptions(color)); 5720 PetscCall(MatFDColoringSetUp(B, iscoloring, color)); 5721 PetscCall(ISColoringDestroy(&iscoloring)); 5722 } else { 5723 MatColoring mc; 5724 5725 PetscCall(MatColoringCreate(B, &mc)); 5726 PetscCall(MatColoringSetDistance(mc, 2)); 5727 PetscCall(MatColoringSetType(mc, MATCOLORINGSL)); 5728 PetscCall(MatColoringSetFromOptions(mc)); 5729 PetscCall(MatColoringApply(mc, &iscoloring)); 5730 PetscCall(MatColoringDestroy(&mc)); 5731 PetscCall(MatFDColoringCreate(B, iscoloring, &color)); 5732 PetscCall(MatFDColoringSetFunction(color, (PetscErrorCode (*)(void)) SNESTSFormFunction, (void *) ts)); 5733 PetscCall(MatFDColoringSetFromOptions(color)); 5734 PetscCall(MatFDColoringSetUp(B, iscoloring, color)); 5735 PetscCall(ISColoringDestroy(&iscoloring)); 5736 } 5737 PetscCall(PetscObjectCompose((PetscObject) B, "TSMatFDColoring", (PetscObject) color)); 5738 PetscCall(PetscObjectDereference((PetscObject) color)); 5739 } 5740 PetscCall(TSGetSNES(ts, &snes)); 5741 PetscCall(MatFDColoringApply(B, color, U, snes)); 5742 if (J != B) { 5743 PetscCall(MatAssemblyBegin(J, MAT_FINAL_ASSEMBLY)); 5744 PetscCall(MatAssemblyEnd(J, MAT_FINAL_ASSEMBLY)); 5745 } 5746 PetscFunctionReturn(0); 5747 } 5748 5749 /*@ 5750 TSSetFunctionDomainError - Set a function that tests if the current state vector is valid 5751 5752 Input Parameters: 5753 + ts - the TS context 5754 - func - function called within TSFunctionDomainError 5755 5756 Calling sequence of func: 5757 $ PetscErrorCode func(TS ts,PetscReal time,Vec state,PetscBool reject) 5758 5759 + ts - the TS context 5760 . time - the current time (of the stage) 5761 . state - the state to check if it is valid 5762 - reject - (output parameter) PETSC_FALSE if the state is acceptable, PETSC_TRUE if not acceptable 5763 5764 Level: intermediate 5765 5766 Notes: 5767 If an implicit ODE solver is being used then, in addition to providing this routine, the 5768 user's code should call SNESSetFunctionDomainError() when domain errors occur during 5769 function evaluations where the functions are provided by TSSetIFunction() or TSSetRHSFunction(). 5770 Use TSGetSNES() to obtain the SNES object 5771 5772 Developer Notes: 5773 The naming of this function is inconsistent with the SNESSetFunctionDomainError() 5774 since one takes a function pointer and the other does not. 5775 5776 .seealso: `TSAdaptCheckStage()`, `TSFunctionDomainError()`, `SNESSetFunctionDomainError()`, `TSGetSNES()` 5777 @*/ 5778 5779 PetscErrorCode TSSetFunctionDomainError(TS ts, PetscErrorCode (*func)(TS,PetscReal,Vec,PetscBool*)) 5780 { 5781 PetscFunctionBegin; 5782 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 5783 ts->functiondomainerror = func; 5784 PetscFunctionReturn(0); 5785 } 5786 5787 /*@ 5788 TSFunctionDomainError - Checks if the current state is valid 5789 5790 Input Parameters: 5791 + ts - the TS context 5792 . stagetime - time of the simulation 5793 - Y - state vector to check. 5794 5795 Output Parameter: 5796 . accept - Set to PETSC_FALSE if the current state vector is valid. 5797 5798 Note: 5799 This function is called by the TS integration routines and calls the user provided function (set with TSSetFunctionDomainError()) 5800 to check if the current state is valid. 5801 5802 Level: developer 5803 5804 .seealso: `TSSetFunctionDomainError()` 5805 @*/ 5806 PetscErrorCode TSFunctionDomainError(TS ts,PetscReal stagetime,Vec Y,PetscBool* accept) 5807 { 5808 PetscFunctionBegin; 5809 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5810 *accept = PETSC_TRUE; 5811 if (ts->functiondomainerror) PetscCall((*ts->functiondomainerror)(ts,stagetime,Y,accept)); 5812 PetscFunctionReturn(0); 5813 } 5814 5815 /*@C 5816 TSClone - This function clones a time step object. 5817 5818 Collective 5819 5820 Input Parameter: 5821 . tsin - The input TS 5822 5823 Output Parameter: 5824 . tsout - The output TS (cloned) 5825 5826 Notes: 5827 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. 5828 5829 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); 5830 5831 Level: developer 5832 5833 .seealso: `TSCreate()`, `TSSetType()`, `TSSetUp()`, `TSDestroy()`, `TSSetProblemType()` 5834 @*/ 5835 PetscErrorCode TSClone(TS tsin, TS *tsout) 5836 { 5837 TS t; 5838 SNES snes_start; 5839 DM dm; 5840 TSType type; 5841 5842 PetscFunctionBegin; 5843 PetscValidPointer(tsin,1); 5844 *tsout = NULL; 5845 5846 PetscCall(PetscHeaderCreate(t, TS_CLASSID, "TS", "Time stepping", "TS", PetscObjectComm((PetscObject)tsin), TSDestroy, TSView)); 5847 5848 /* General TS description */ 5849 t->numbermonitors = 0; 5850 t->monitorFrequency = 1; 5851 t->setupcalled = 0; 5852 t->ksp_its = 0; 5853 t->snes_its = 0; 5854 t->nwork = 0; 5855 t->rhsjacobian.time = PETSC_MIN_REAL; 5856 t->rhsjacobian.scale = 1.; 5857 t->ijacobian.shift = 1.; 5858 5859 PetscCall(TSGetSNES(tsin,&snes_start)); 5860 PetscCall(TSSetSNES(t,snes_start)); 5861 5862 PetscCall(TSGetDM(tsin,&dm)); 5863 PetscCall(TSSetDM(t,dm)); 5864 5865 t->adapt = tsin->adapt; 5866 PetscCall(PetscObjectReference((PetscObject)t->adapt)); 5867 5868 t->trajectory = tsin->trajectory; 5869 PetscCall(PetscObjectReference((PetscObject)t->trajectory)); 5870 5871 t->event = tsin->event; 5872 if (t->event) t->event->refct++; 5873 5874 t->problem_type = tsin->problem_type; 5875 t->ptime = tsin->ptime; 5876 t->ptime_prev = tsin->ptime_prev; 5877 t->time_step = tsin->time_step; 5878 t->max_time = tsin->max_time; 5879 t->steps = tsin->steps; 5880 t->max_steps = tsin->max_steps; 5881 t->equation_type = tsin->equation_type; 5882 t->atol = tsin->atol; 5883 t->rtol = tsin->rtol; 5884 t->max_snes_failures = tsin->max_snes_failures; 5885 t->max_reject = tsin->max_reject; 5886 t->errorifstepfailed = tsin->errorifstepfailed; 5887 5888 PetscCall(TSGetType(tsin,&type)); 5889 PetscCall(TSSetType(t,type)); 5890 5891 t->vec_sol = NULL; 5892 5893 t->cfltime = tsin->cfltime; 5894 t->cfltime_local = tsin->cfltime_local; 5895 t->exact_final_time = tsin->exact_final_time; 5896 5897 PetscCall(PetscMemcpy(t->ops,tsin->ops,sizeof(struct _TSOps))); 5898 5899 if (((PetscObject)tsin)->fortran_func_pointers) { 5900 PetscInt i; 5901 PetscCall(PetscMalloc((10)*sizeof(void(*)(void)),&((PetscObject)t)->fortran_func_pointers)); 5902 for (i=0; i<10; i++) { 5903 ((PetscObject)t)->fortran_func_pointers[i] = ((PetscObject)tsin)->fortran_func_pointers[i]; 5904 } 5905 } 5906 *tsout = t; 5907 PetscFunctionReturn(0); 5908 } 5909 5910 static PetscErrorCode RHSWrapperFunction_TSRHSJacobianTest(void* ctx,Vec x,Vec y) 5911 { 5912 TS ts = (TS) ctx; 5913 5914 PetscFunctionBegin; 5915 PetscCall(TSComputeRHSFunction(ts,0,x,y)); 5916 PetscFunctionReturn(0); 5917 } 5918 5919 /*@ 5920 TSRHSJacobianTest - Compares the multiply routine provided to the MATSHELL with differencing on the TS given RHS function. 5921 5922 Logically Collective on TS 5923 5924 Input Parameters: 5925 TS - the time stepping routine 5926 5927 Output Parameter: 5928 . flg - PETSC_TRUE if the multiply is likely correct 5929 5930 Options Database: 5931 . -ts_rhs_jacobian_test_mult -mat_shell_test_mult_view - run the test at each timestep of the integrator 5932 5933 Level: advanced 5934 5935 Notes: 5936 This only works for problems defined only the RHS function and Jacobian NOT IFunction and IJacobian 5937 5938 .seealso: `MatCreateShell()`, `MatShellGetContext()`, `MatShellGetOperation()`, `MatShellTestMultTranspose()`, `TSRHSJacobianTestTranspose()` 5939 @*/ 5940 PetscErrorCode TSRHSJacobianTest(TS ts,PetscBool *flg) 5941 { 5942 Mat J,B; 5943 TSRHSJacobian func; 5944 void* ctx; 5945 5946 PetscFunctionBegin; 5947 PetscCall(TSGetRHSJacobian(ts,&J,&B,&func,&ctx)); 5948 PetscCall((*func)(ts,0.0,ts->vec_sol,J,B,ctx)); 5949 PetscCall(MatShellTestMult(J,RHSWrapperFunction_TSRHSJacobianTest,ts->vec_sol,ts,flg)); 5950 PetscFunctionReturn(0); 5951 } 5952 5953 /*@C 5954 TSRHSJacobianTestTranspose - Compares the multiply transpose routine provided to the MATSHELL with differencing on the TS given RHS function. 5955 5956 Logically Collective on TS 5957 5958 Input Parameters: 5959 TS - the time stepping routine 5960 5961 Output Parameter: 5962 . flg - PETSC_TRUE if the multiply is likely correct 5963 5964 Options Database: 5965 . -ts_rhs_jacobian_test_mult_transpose -mat_shell_test_mult_transpose_view - run the test at each timestep of the integrator 5966 5967 Notes: 5968 This only works for problems defined only the RHS function and Jacobian NOT IFunction and IJacobian 5969 5970 Level: advanced 5971 5972 .seealso: `MatCreateShell()`, `MatShellGetContext()`, `MatShellGetOperation()`, `MatShellTestMultTranspose()`, `TSRHSJacobianTest()` 5973 @*/ 5974 PetscErrorCode TSRHSJacobianTestTranspose(TS ts,PetscBool *flg) 5975 { 5976 Mat J,B; 5977 void *ctx; 5978 TSRHSJacobian func; 5979 5980 PetscFunctionBegin; 5981 PetscCall(TSGetRHSJacobian(ts,&J,&B,&func,&ctx)); 5982 PetscCall((*func)(ts,0.0,ts->vec_sol,J,B,ctx)); 5983 PetscCall(MatShellTestMultTranspose(J,RHSWrapperFunction_TSRHSJacobianTest,ts->vec_sol,ts,flg)); 5984 PetscFunctionReturn(0); 5985 } 5986 5987 /*@ 5988 TSSetUseSplitRHSFunction - Use the split RHSFunction when a multirate method is used. 5989 5990 Logically collective 5991 5992 Input Parameters: 5993 + ts - timestepping context 5994 - use_splitrhsfunction - PETSC_TRUE indicates that the split RHSFunction will be used 5995 5996 Options Database: 5997 . -ts_use_splitrhsfunction - <true,false> 5998 5999 Notes: 6000 This is only useful for multirate methods 6001 6002 Level: intermediate 6003 6004 .seealso: `TSGetUseSplitRHSFunction()` 6005 @*/ 6006 PetscErrorCode TSSetUseSplitRHSFunction(TS ts, PetscBool use_splitrhsfunction) 6007 { 6008 PetscFunctionBegin; 6009 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6010 ts->use_splitrhsfunction = use_splitrhsfunction; 6011 PetscFunctionReturn(0); 6012 } 6013 6014 /*@ 6015 TSGetUseSplitRHSFunction - Gets whether to use the split RHSFunction when a multirate method is used. 6016 6017 Not collective 6018 6019 Input Parameter: 6020 . ts - timestepping context 6021 6022 Output Parameter: 6023 . use_splitrhsfunction - PETSC_TRUE indicates that the split RHSFunction will be used 6024 6025 Level: intermediate 6026 6027 .seealso: `TSSetUseSplitRHSFunction()` 6028 @*/ 6029 PetscErrorCode TSGetUseSplitRHSFunction(TS ts, PetscBool *use_splitrhsfunction) 6030 { 6031 PetscFunctionBegin; 6032 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6033 *use_splitrhsfunction = ts->use_splitrhsfunction; 6034 PetscFunctionReturn(0); 6035 } 6036 6037 /*@ 6038 TSSetMatStructure - sets the relationship between the nonzero structure of the RHS Jacobian matrix to the IJacobian matrix. 6039 6040 Logically Collective on ts 6041 6042 Input Parameters: 6043 + ts - the time-stepper 6044 - str - the structure (the default is UNKNOWN_NONZERO_PATTERN) 6045 6046 Level: intermediate 6047 6048 Notes: 6049 When the relationship between the nonzero structures is known and supplied the solution process can be much faster 6050 6051 .seealso: `MatAXPY()`, `MatStructure` 6052 @*/ 6053 PetscErrorCode TSSetMatStructure(TS ts,MatStructure str) 6054 { 6055 PetscFunctionBegin; 6056 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6057 ts->axpy_pattern = str; 6058 PetscFunctionReturn(0); 6059 } 6060 6061 /*@ 6062 TSSetTimeSpan - sets the time span. The solution will be computed and stored for each time requested. 6063 6064 Collective on ts 6065 6066 Input Parameters: 6067 + ts - the time-stepper 6068 . n - number of the time points (>=2) 6069 - span_times - array of the time points. The first element and the last element are the initial time and the final time respectively. 6070 6071 Options Database Keys: 6072 . -ts_time_span <t0,...tf> - Sets the time span 6073 6074 Level: beginner 6075 6076 Notes: 6077 The elements in tspan must be all increasing. They correspond to the intermediate points for time integration. 6078 TS_EXACTFINALTIME_MATCHSTEP must be used to make the last time step in each sub-interval match the intermediate points specified. 6079 The intermediate solutions are saved in a vector array that can be accessed with TSGetSolutions(). Thus using time span may 6080 pressure the memory system when using a large number of span points. 6081 6082 .seealso: `TSGetTimeSpan()`, `TSGetSolutions()` 6083 @*/ 6084 PetscErrorCode TSSetTimeSpan(TS ts,PetscInt n,PetscReal *span_times) 6085 { 6086 PetscFunctionBegin; 6087 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6088 PetscCheck(n >= 2,PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Minimum time span size is 2 but %" PetscInt_FMT " is provided",n); 6089 if (ts->tspan && n != ts->tspan->num_span_times) { 6090 PetscCall(PetscFree(ts->tspan->span_times)); 6091 PetscCall(VecDestroyVecs(ts->tspan->num_span_times,&ts->tspan->vecs_sol)); 6092 PetscCall(PetscMalloc1(n,&ts->tspan->span_times)); 6093 } 6094 if (!ts->tspan) { 6095 TSTimeSpan tspan; 6096 PetscCall(PetscNew(&tspan)); 6097 PetscCall(PetscMalloc1(n,&tspan->span_times)); 6098 tspan->reltol = 1e-6; 6099 tspan->abstol = 10*PETSC_MACHINE_EPSILON; 6100 ts->tspan = tspan; 6101 } 6102 ts->tspan->num_span_times = n; 6103 PetscCall(PetscArraycpy(ts->tspan->span_times,span_times,n)); 6104 PetscCall(TSSetTime(ts,ts->tspan->span_times[0])); 6105 PetscCall(TSSetMaxTime(ts,ts->tspan->span_times[n-1])); 6106 PetscFunctionReturn(0); 6107 } 6108 6109 /*@C 6110 TSGetTimeSpan - gets the time span. 6111 6112 Not Collective 6113 6114 Input Parameter: 6115 . ts - the time-stepper 6116 6117 Output Parameters: 6118 + n - number of the time points (>=2) 6119 - span_times - array of the time points. The first element and the last element are the initial time and the final time respectively. The values are valid until the TS object is destroyed. 6120 6121 Level: beginner 6122 Notes: Both n and span_times can be NULL. 6123 6124 .seealso: `TSSetTimeSpan()`, `TSGetSolutions()` 6125 @*/ 6126 PetscErrorCode TSGetTimeSpan(TS ts,PetscInt *n,const PetscReal **span_times) 6127 { 6128 PetscFunctionBegin; 6129 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6130 if (n) PetscValidIntPointer(n,2); 6131 if (span_times) PetscValidPointer(span_times,3); 6132 if (!ts->tspan) { 6133 if (n) *n = 0; 6134 if (span_times) *span_times = NULL; 6135 } else { 6136 if (n) *n = ts->tspan->num_span_times; 6137 if (span_times) *span_times = ts->tspan->span_times; 6138 } 6139 PetscFunctionReturn(0); 6140 } 6141 6142 /*@ 6143 TSGetTimeSpanSolutions - Get the number of solutions and the solutions at the time points specified by the time span. 6144 6145 Input Parameter: 6146 . ts - the TS context obtained from TSCreate() 6147 6148 Output Parameters: 6149 + nsol - the number of solutions 6150 - Sols - the solution vectors 6151 6152 Level: beginner 6153 6154 Notes: 6155 Both nsol and Sols can be NULL. 6156 Some time points in the time span may be skipped by TS so that nsol is less than the number of points specified by TSSetTimeSpan(). For example, manipulating the step size, especially with a reduced precision, may cause TS to step over certain points in the span. 6157 6158 .seealso: `TSSetTimeSpan()` 6159 @*/ 6160 PetscErrorCode TSGetTimeSpanSolutions(TS ts,PetscInt *nsol,Vec **Sols) 6161 { 6162 PetscFunctionBegin; 6163 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 6164 if (nsol) PetscValidIntPointer(nsol,2); 6165 if (Sols) PetscValidPointer(Sols,3); 6166 if (!ts->tspan) { 6167 if (nsol) *nsol = 0; 6168 if (Sols) *Sols = NULL; 6169 } else { 6170 if (nsol) *nsol = ts->tspan->spanctr; 6171 if (Sols) *Sols = ts->tspan->vecs_sol; 6172 } 6173 PetscFunctionReturn(0); 6174 } 6175