1 2 #include <petsc-private/tsimpl.h> /*I "petscts.h" I*/ 3 #include <petscdmshell.h> 4 5 /* Logging support */ 6 PetscClassId TS_CLASSID; 7 PetscLogEvent TS_Step, TS_PseudoComputeTimeStep, TS_FunctionEval, TS_JacobianEval; 8 9 #undef __FUNCT__ 10 #define __FUNCT__ "TSSetTypeFromOptions" 11 /* 12 TSSetTypeFromOptions - Sets the type of ts from user options. 13 14 Collective on TS 15 16 Input Parameter: 17 . ts - The ts 18 19 Level: intermediate 20 21 .keywords: TS, set, options, database, type 22 .seealso: TSSetFromOptions(), TSSetType() 23 */ 24 static PetscErrorCode TSSetTypeFromOptions(TS ts) 25 { 26 PetscBool opt; 27 const char *defaultType; 28 char typeName[256]; 29 PetscErrorCode ierr; 30 31 PetscFunctionBegin; 32 if (((PetscObject)ts)->type_name) { 33 defaultType = ((PetscObject)ts)->type_name; 34 } else { 35 defaultType = TSEULER; 36 } 37 38 if (!TSRegisterAllCalled) {ierr = TSRegisterAll(PETSC_NULL);CHKERRQ(ierr);} 39 ierr = PetscOptionsList("-ts_type", "TS method"," TSSetType", TSList, defaultType, typeName, 256, &opt);CHKERRQ(ierr); 40 if (opt) { 41 ierr = TSSetType(ts, typeName);CHKERRQ(ierr); 42 } else { 43 ierr = TSSetType(ts, defaultType);CHKERRQ(ierr); 44 } 45 PetscFunctionReturn(0); 46 } 47 48 #undef __FUNCT__ 49 #define __FUNCT__ "TSSetFromOptions" 50 /*@ 51 TSSetFromOptions - Sets various TS parameters from user options. 52 53 Collective on TS 54 55 Input Parameter: 56 . ts - the TS context obtained from TSCreate() 57 58 Options Database Keys: 59 + -ts_type <type> - TSEULER, TSBEULER, TSSUNDIALS, TSPSEUDO, TSCN, TSRK, TSTHETA, TSGL, TSSSP 60 . -ts_max_steps maxsteps - maximum number of time-steps to take 61 . -ts_final_time time - maximum time to compute to 62 . -ts_dt dt - initial time step 63 . -ts_monitor - print information at each timestep 64 . -ts_monitor_lg_timestep - Monitor timestep size graphically 65 . -ts_monitor_lg_solution - Monitor solution graphically 66 . -ts_monitor_lg_error - Monitor error graphically 67 . -ts_monitor_lg_snes_iterations - Monitor number nonlinear iterations for each timestep graphically 68 . -ts_monitor_lg_ksp_iterations - Monitor number nonlinear iterations for each timestep graphically 69 . -ts_monitor_sp_eig - Monitor eigenvalues of linearized operator graphically 70 . -ts_monitor_draw_solution - Monitor solution graphically 71 . -ts_monitor_draw_solution - Monitor solution graphically 72 . -ts_monitor_draw_error - Monitor error graphically 73 . -ts_monitor_draw_solution_binary <filename> - Save each solution to a binary file 74 - -ts_monitor_draw_solution_vtk <filename.vts> - Save each time step to a binary file, use filename-%%03D.vts 75 76 Level: beginner 77 78 .keywords: TS, timestep, set, options, database 79 80 .seealso: TSGetType() 81 @*/ 82 PetscErrorCode TSSetFromOptions(TS ts) 83 { 84 PetscBool opt,flg; 85 PetscErrorCode ierr; 86 PetscViewer monviewer; 87 char monfilename[PETSC_MAX_PATH_LEN]; 88 SNES snes; 89 TSAdapt adapt; 90 PetscReal time_step; 91 92 PetscFunctionBegin; 93 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 94 ierr = PetscObjectOptionsBegin((PetscObject)ts);CHKERRQ(ierr); 95 /* Handle TS type options */ 96 ierr = TSSetTypeFromOptions(ts);CHKERRQ(ierr); 97 98 /* Handle generic TS options */ 99 ierr = PetscOptionsInt("-ts_max_steps","Maximum number of time steps","TSSetDuration",ts->max_steps,&ts->max_steps,PETSC_NULL);CHKERRQ(ierr); 100 ierr = PetscOptionsReal("-ts_final_time","Time to run to","TSSetDuration",ts->max_time,&ts->max_time,PETSC_NULL);CHKERRQ(ierr); 101 ierr = PetscOptionsReal("-ts_init_time","Initial time","TSSetTime",ts->ptime,&ts->ptime,PETSC_NULL);CHKERRQ(ierr); 102 ierr = PetscOptionsReal("-ts_dt","Initial time step","TSSetTimeStep",ts->time_step,&time_step,&flg);CHKERRQ(ierr); 103 if (flg) { 104 ierr = TSSetTimeStep(ts,time_step);CHKERRQ(ierr); 105 } 106 opt = ts->exact_final_time == PETSC_DECIDE ? PETSC_FALSE : (PetscBool)ts->exact_final_time; 107 ierr = PetscOptionsBool("-ts_exact_final_time","Interpolate output to stop exactly at the final time","TSSetExactFinalTime",opt,&opt,&flg);CHKERRQ(ierr); 108 if (flg) {ierr = TSSetExactFinalTime(ts,opt);CHKERRQ(ierr);} 109 ierr = PetscOptionsInt("-ts_max_snes_failures","Maximum number of nonlinear solve failures","TSSetMaxSNESFailures",ts->max_snes_failures,&ts->max_snes_failures,PETSC_NULL);CHKERRQ(ierr); 110 ierr = PetscOptionsInt("-ts_max_reject","Maximum number of step rejections before step fails","TSSetMaxStepRejections",ts->max_reject,&ts->max_reject,PETSC_NULL);CHKERRQ(ierr); 111 ierr = PetscOptionsBool("-ts_error_if_step_fails","Error if no step succeeds","TSSetErrorIfStepFails",ts->errorifstepfailed,&ts->errorifstepfailed,PETSC_NULL);CHKERRQ(ierr); 112 ierr = PetscOptionsReal("-ts_rtol","Relative tolerance for local truncation error","TSSetTolerances",ts->rtol,&ts->rtol,PETSC_NULL);CHKERRQ(ierr); 113 ierr = PetscOptionsReal("-ts_atol","Absolute tolerance for local truncation error","TSSetTolerances",ts->atol,&ts->atol,PETSC_NULL);CHKERRQ(ierr); 114 115 /* Monitor options */ 116 ierr = PetscOptionsString("-ts_monitor","Monitor timestep size","TSMonitorDefault","stdout",monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr); 117 if (flg) { 118 ierr = PetscViewerASCIIOpen(((PetscObject)ts)->comm,monfilename,&monviewer);CHKERRQ(ierr); 119 ierr = TSMonitorSet(ts,TSMonitorDefault,monviewer,(PetscErrorCode (*)(void**))PetscViewerDestroy);CHKERRQ(ierr); 120 } 121 ierr = PetscOptionsString("-ts_monitor_python","Use Python function","TSMonitorSet",0,monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr); 122 if (flg) {ierr = PetscPythonMonitorSet((PetscObject)ts,monfilename);CHKERRQ(ierr);} 123 124 ierr = PetscOptionsName("-ts_monitor_lg_timestep","Monitor timestep size graphically","TSMonitorLGTimeStep",&opt);CHKERRQ(ierr); 125 if (opt) { 126 TSMonitorLGCtx ctx; 127 PetscInt howoften = 1; 128 129 ierr = PetscOptionsInt("-ts_monitor_lg_timestep","Monitor timestep size graphically","TSMonitorLGTimeStep",howoften,&howoften,PETSC_NULL);CHKERRQ(ierr); 130 ierr = TSMonitorLGCtxCreate(((PetscObject)ts)->comm,0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);CHKERRQ(ierr); 131 ierr = TSMonitorSet(ts,TSMonitorLGTimeStep,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 132 } 133 ierr = PetscOptionsName("-ts_monitor_lg_solution","Monitor solution graphically","TSMonitorLGSolution",&opt);CHKERRQ(ierr); 134 if (opt) { 135 TSMonitorLGCtx ctx; 136 PetscInt howoften = 1; 137 138 ierr = PetscOptionsInt("-ts_monitor_lg_solution","Monitor solution graphically","TSMonitorLGSolution",howoften,&howoften,PETSC_NULL);CHKERRQ(ierr); 139 ierr = TSMonitorLGCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,600,400,howoften,&ctx); 140 ierr = TSMonitorSet(ts,TSMonitorLGSolution,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 141 } 142 ierr = PetscOptionsName("-ts_monitor_lg_error","Monitor error graphically","TSMonitorLGError",&opt);CHKERRQ(ierr); 143 if (opt) { 144 TSMonitorLGCtx ctx; 145 PetscInt howoften = 1; 146 147 ierr = PetscOptionsInt("-ts_monitor_lg_error","Monitor error graphically","TSMonitorLGError",howoften,&howoften,PETSC_NULL);CHKERRQ(ierr); 148 ierr = TSMonitorLGCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,600,400,howoften,&ctx); 149 ierr = TSMonitorSet(ts,TSMonitorLGError,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 150 } 151 ierr = PetscOptionsName("-ts_monitor_lg_snes_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGSNESIterations",&opt);CHKERRQ(ierr); 152 if (opt) { 153 TSMonitorLGCtx ctx; 154 PetscInt howoften = 1; 155 156 ierr = PetscOptionsInt("-ts_monitor_lg_snes_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGSNESIterations",howoften,&howoften,PETSC_NULL);CHKERRQ(ierr); 157 ierr = TSMonitorLGCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx); 158 ierr = TSMonitorSet(ts,TSMonitorLGSNESIterations,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 159 } 160 ierr = PetscOptionsName("-ts_monitor_lg_ksp_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGKSPIterations",&opt);CHKERRQ(ierr); 161 if (opt) { 162 TSMonitorLGCtx ctx; 163 PetscInt howoften = 1; 164 165 ierr = PetscOptionsInt("-ts_monitor_lg_ksp_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGKSPIterations",howoften,&howoften,PETSC_NULL);CHKERRQ(ierr); 166 ierr = TSMonitorLGCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx); 167 ierr = TSMonitorSet(ts,TSMonitorLGKSPIterations,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 168 } 169 ierr = PetscOptionsName("-ts_monitor_sp_eig","Monitor eigenvalues of linearized operator graphically","TSMonitorSPEig",&opt);CHKERRQ(ierr); 170 if (opt) { 171 TSMonitorSPEigCtx ctx; 172 PetscInt howoften = 1; 173 174 ierr = PetscOptionsInt("-ts_monitor_sp_eig","Monitor eigenvalues of linearized operator graphically","TSMonitorSPEig",howoften,&howoften,PETSC_NULL);CHKERRQ(ierr); 175 ierr = TSMonitorSPEigCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,600,400,howoften,&ctx); 176 ierr = TSMonitorSet(ts,TSMonitorSPEig,ctx,(PetscErrorCode (*)(void**))TSMonitorSPEigCtxDestroy);CHKERRQ(ierr); 177 } 178 opt = PETSC_FALSE; 179 ierr = PetscOptionsName("-ts_monitor_draw_solution","Monitor solution graphically","TSMonitorDrawSolution",&opt);CHKERRQ(ierr); 180 if (opt) { 181 TSMonitorDrawCtx ctx; 182 PetscInt howoften = 1; 183 184 ierr = PetscOptionsInt("-ts_monitor_draw_solution","Monitor solution graphically","TSMonitorDrawSolution",howoften,&howoften,PETSC_NULL);CHKERRQ(ierr); 185 ierr = TSMonitorDrawCtxCreate(((PetscObject)ts)->comm,0,0,PETSC_DECIDE,PETSC_DECIDE,600,400,howoften,&ctx); 186 ierr = TSMonitorSet(ts,TSMonitorDrawSolution,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);CHKERRQ(ierr); 187 } 188 opt = PETSC_FALSE; 189 ierr = PetscOptionsName("-ts_monitor_draw_error","Monitor error graphically","TSMonitorDrawError",&opt);CHKERRQ(ierr); 190 if (opt) { 191 TSMonitorDrawCtx ctx; 192 PetscInt howoften = 1; 193 194 ierr = PetscOptionsInt("-ts_monitor_draw_error","Monitor error graphically","TSMonitorDrawError",howoften,&howoften,PETSC_NULL);CHKERRQ(ierr); 195 ierr = TSMonitorDrawCtxCreate(((PetscObject)ts)->comm,0,0,PETSC_DECIDE,PETSC_DECIDE,600,400,howoften,&ctx); 196 ierr = TSMonitorSet(ts,TSMonitorDrawError,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);CHKERRQ(ierr); 197 } 198 opt = PETSC_FALSE; 199 ierr = PetscOptionsString("-ts_monitor_draw_solution_binary","Save each solution to a binary file","TSMonitorSolutionBinary",0,monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr); 200 if (flg) { 201 PetscViewer ctx; 202 if (monfilename[0]) { 203 ierr = PetscViewerBinaryOpen(((PetscObject)ts)->comm,monfilename,FILE_MODE_WRITE,&ctx);CHKERRQ(ierr); 204 } else { 205 ctx = PETSC_VIEWER_BINARY_(((PetscObject)ts)->comm); 206 } 207 ierr = TSMonitorSet(ts,TSMonitorSolutionBinary,ctx,(PetscErrorCode (*)(void**))PetscViewerDestroy);CHKERRQ(ierr); 208 } 209 opt = PETSC_FALSE; 210 ierr = PetscOptionsString("-ts_monitor_draw_solution_vtk","Save each time step to a binary file, use filename-%%03D.vts","TSMonitorSolutionVTK",0,monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr); 211 if (flg) { 212 const char *ptr,*ptr2; 213 char *filetemplate; 214 if (!monfilename[0]) SETERRQ(((PetscObject)ts)->comm,PETSC_ERR_USER,"-ts_monitor_draw_solution_vtk requires a file template, e.g. filename-%%03D.vts"); 215 /* Do some cursory validation of the input. */ 216 ierr = PetscStrstr(monfilename,"%",(char**)&ptr);CHKERRQ(ierr); 217 if (!ptr) SETERRQ(((PetscObject)ts)->comm,PETSC_ERR_USER,"-ts_monitor_draw_solution_vtk requires a file template, e.g. filename-%%03D.vts"); 218 for (ptr++ ; ptr && *ptr; ptr++) { 219 ierr = PetscStrchr("DdiouxX",*ptr,(char**)&ptr2);CHKERRQ(ierr); 220 if (!ptr2 && (*ptr < '0' || '9' < *ptr)) SETERRQ(((PetscObject)ts)->comm,PETSC_ERR_USER,"Invalid file template argument to -ts_monitor_draw_solution_vtk, should look like filename-%%03D.vts"); 221 if (ptr2) break; 222 } 223 ierr = PetscStrallocpy(monfilename,&filetemplate);CHKERRQ(ierr); 224 ierr = TSMonitorSet(ts,TSMonitorSolutionVTK,filetemplate,(PetscErrorCode (*)(void**))TSMonitorSolutionVTKDestroy);CHKERRQ(ierr); 225 } 226 227 ierr = TSGetAdapt(ts,&adapt);CHKERRQ(ierr); 228 ierr = TSAdaptSetFromOptions(adapt);CHKERRQ(ierr); 229 230 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 231 if (ts->problem_type == TS_LINEAR) {ierr = SNESSetType(snes,SNESKSPONLY);CHKERRQ(ierr);} 232 233 /* Handle specific TS options */ 234 if (ts->ops->setfromoptions) { 235 ierr = (*ts->ops->setfromoptions)(ts);CHKERRQ(ierr); 236 } 237 238 /* process any options handlers added with PetscObjectAddOptionsHandler() */ 239 ierr = PetscObjectProcessOptionsHandlers((PetscObject)ts);CHKERRQ(ierr); 240 ierr = PetscOptionsEnd();CHKERRQ(ierr); 241 PetscFunctionReturn(0); 242 } 243 244 #undef __FUNCT__ 245 #undef __FUNCT__ 246 #define __FUNCT__ "TSComputeRHSJacobian" 247 /*@ 248 TSComputeRHSJacobian - Computes the Jacobian matrix that has been 249 set with TSSetRHSJacobian(). 250 251 Collective on TS and Vec 252 253 Input Parameters: 254 + ts - the TS context 255 . t - current timestep 256 - U - input vector 257 258 Output Parameters: 259 + A - Jacobian matrix 260 . B - optional preconditioning matrix 261 - flag - flag indicating matrix structure 262 263 Notes: 264 Most users should not need to explicitly call this routine, as it 265 is used internally within the nonlinear solvers. 266 267 See KSPSetOperators() for important information about setting the 268 flag parameter. 269 270 Level: developer 271 272 .keywords: SNES, compute, Jacobian, matrix 273 274 .seealso: TSSetRHSJacobian(), KSPSetOperators() 275 @*/ 276 PetscErrorCode TSComputeRHSJacobian(TS ts,PetscReal t,Vec U,Mat *A,Mat *B,MatStructure *flg) 277 { 278 PetscErrorCode ierr; 279 PetscInt Ustate; 280 DM dm; 281 TSDM tsdm; 282 TSRHSJacobian rhsjacobianfunc; 283 void *ctx; 284 TSIJacobian ijacobianfunc; 285 286 PetscFunctionBegin; 287 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 288 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 289 PetscCheckSameComm(ts,1,U,3); 290 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 291 ierr = DMTSGetContext(dm,&tsdm);CHKERRQ(ierr); 292 ierr = DMTSGetRHSJacobian(dm,&rhsjacobianfunc,&ctx);CHKERRQ(ierr); 293 ierr = DMTSGetIJacobian(dm,&ijacobianfunc,PETSC_NULL);CHKERRQ(ierr); 294 ierr = PetscObjectStateQuery((PetscObject)U,&Ustate);CHKERRQ(ierr); 295 if (ts->rhsjacobian.time == t && (ts->problem_type == TS_LINEAR || (ts->rhsjacobian.X == U && ts->rhsjacobian.Xstate == Ustate))) { 296 *flg = ts->rhsjacobian.mstructure; 297 PetscFunctionReturn(0); 298 } 299 300 if (!rhsjacobianfunc && !ijacobianfunc) SETERRQ(((PetscObject)ts)->comm,PETSC_ERR_USER,"Must call TSSetRHSJacobian() and / or TSSetIJacobian()"); 301 302 if (rhsjacobianfunc) { 303 ierr = PetscLogEventBegin(TS_JacobianEval,ts,U,*A,*B);CHKERRQ(ierr); 304 *flg = DIFFERENT_NONZERO_PATTERN; 305 PetscStackPush("TS user Jacobian function"); 306 ierr = (*rhsjacobianfunc)(ts,t,U,A,B,flg,ctx);CHKERRQ(ierr); 307 PetscStackPop; 308 ierr = PetscLogEventEnd(TS_JacobianEval,ts,U,*A,*B);CHKERRQ(ierr); 309 /* make sure user returned a correct Jacobian and preconditioner */ 310 PetscValidHeaderSpecific(*A,MAT_CLASSID,4); 311 PetscValidHeaderSpecific(*B,MAT_CLASSID,5); 312 } else { 313 ierr = MatZeroEntries(*A);CHKERRQ(ierr); 314 if (*A != *B) {ierr = MatZeroEntries(*B);CHKERRQ(ierr);} 315 *flg = SAME_NONZERO_PATTERN; 316 } 317 ts->rhsjacobian.time = t; 318 ts->rhsjacobian.X = U; 319 ierr = PetscObjectStateQuery((PetscObject)U,&ts->rhsjacobian.Xstate);CHKERRQ(ierr); 320 ts->rhsjacobian.mstructure = *flg; 321 PetscFunctionReturn(0); 322 } 323 324 #undef __FUNCT__ 325 #define __FUNCT__ "TSComputeRHSFunction" 326 /*@ 327 TSComputeRHSFunction - Evaluates the right-hand-side function. 328 329 Collective on TS and Vec 330 331 Input Parameters: 332 + ts - the TS context 333 . t - current time 334 - U - state vector 335 336 Output Parameter: 337 . y - right hand side 338 339 Note: 340 Most users should not need to explicitly call this routine, as it 341 is used internally within the nonlinear solvers. 342 343 Level: developer 344 345 .keywords: TS, compute 346 347 .seealso: TSSetRHSFunction(), TSComputeIFunction() 348 @*/ 349 PetscErrorCode TSComputeRHSFunction(TS ts,PetscReal t,Vec U,Vec y) 350 { 351 PetscErrorCode ierr; 352 TSRHSFunction rhsfunction; 353 TSIFunction ifunction; 354 void *ctx; 355 DM dm; 356 357 PetscFunctionBegin; 358 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 359 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 360 PetscValidHeaderSpecific(y,VEC_CLASSID,4); 361 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 362 ierr = DMTSGetRHSFunction(dm,&rhsfunction,&ctx);CHKERRQ(ierr); 363 ierr = DMTSGetIFunction(dm,&ifunction,PETSC_NULL);CHKERRQ(ierr); 364 365 if (!rhsfunction && !ifunction) SETERRQ(((PetscObject)ts)->comm,PETSC_ERR_USER,"Must call TSSetRHSFunction() and / or TSSetIFunction()"); 366 367 ierr = PetscLogEventBegin(TS_FunctionEval,ts,U,y,0);CHKERRQ(ierr); 368 if (rhsfunction) { 369 PetscStackPush("TS user right-hand-side function"); 370 ierr = (*rhsfunction)(ts,t,U,y,ctx);CHKERRQ(ierr); 371 PetscStackPop; 372 } else { 373 ierr = VecZeroEntries(y);CHKERRQ(ierr); 374 } 375 376 ierr = PetscLogEventEnd(TS_FunctionEval,ts,U,y,0);CHKERRQ(ierr); 377 PetscFunctionReturn(0); 378 } 379 380 #undef __FUNCT__ 381 #define __FUNCT__ "TSComputeSolutionFunction" 382 /*@ 383 TSComputeSolutionFunction - Evaluates the solution function. 384 385 Collective on TS and Vec 386 387 Input Parameters: 388 + ts - the TS context 389 - t - current time 390 391 Output Parameter: 392 . U - the solution 393 394 Note: 395 Most users should not need to explicitly call this routine, as it 396 is used internally within the nonlinear solvers. 397 398 Level: developer 399 400 .keywords: TS, compute 401 402 .seealso: TSSetSolutionFunction(), TSSetRHSFunction(), TSComputeIFunction() 403 @*/ 404 PetscErrorCode TSComputeSolutionFunction(TS ts,PetscReal t,Vec U) 405 { 406 PetscErrorCode ierr; 407 TSSolutionFunction solutionfunction; 408 void *ctx; 409 DM dm; 410 411 PetscFunctionBegin; 412 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 413 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 414 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 415 ierr = DMTSGetSolutionFunction(dm,&solutionfunction,&ctx);CHKERRQ(ierr); 416 417 if (solutionfunction) { 418 PetscStackPush("TS user right-hand-side function"); 419 ierr = (*solutionfunction)(ts,t,U,ctx);CHKERRQ(ierr); 420 PetscStackPop; 421 } 422 PetscFunctionReturn(0); 423 } 424 425 #undef __FUNCT__ 426 #define __FUNCT__ "TSGetRHSVec_Private" 427 static PetscErrorCode TSGetRHSVec_Private(TS ts,Vec *Frhs) 428 { 429 Vec F; 430 PetscErrorCode ierr; 431 432 PetscFunctionBegin; 433 *Frhs = PETSC_NULL; 434 ierr = TSGetIFunction(ts,&F,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); 435 if (!ts->Frhs) { 436 ierr = VecDuplicate(F,&ts->Frhs);CHKERRQ(ierr); 437 } 438 *Frhs = ts->Frhs; 439 PetscFunctionReturn(0); 440 } 441 442 #undef __FUNCT__ 443 #define __FUNCT__ "TSGetRHSMats_Private" 444 static PetscErrorCode TSGetRHSMats_Private(TS ts,Mat *Arhs,Mat *Brhs) 445 { 446 Mat A,B; 447 PetscErrorCode ierr; 448 449 PetscFunctionBegin; 450 ierr = TSGetIJacobian(ts,&A,&B,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); 451 if (Arhs) { 452 if (!ts->Arhs) { 453 ierr = MatDuplicate(A,MAT_DO_NOT_COPY_VALUES,&ts->Arhs);CHKERRQ(ierr); 454 } 455 *Arhs = ts->Arhs; 456 } 457 if (Brhs) { 458 if (!ts->Brhs) { 459 ierr = MatDuplicate(B,MAT_DO_NOT_COPY_VALUES,&ts->Brhs);CHKERRQ(ierr); 460 } 461 *Brhs = ts->Brhs; 462 } 463 PetscFunctionReturn(0); 464 } 465 466 #undef __FUNCT__ 467 #define __FUNCT__ "TSComputeIFunction" 468 /*@ 469 TSComputeIFunction - Evaluates the DAE residual written in implicit form F(t,U,Udot)=0 470 471 Collective on TS and Vec 472 473 Input Parameters: 474 + ts - the TS context 475 . t - current time 476 . U - state vector 477 . Udot - time derivative of state vector 478 - imex - flag indicates if the method is IMEX so that the RHSFunction should be kept separate 479 480 Output Parameter: 481 . Y - right hand side 482 483 Note: 484 Most users should not need to explicitly call this routine, as it 485 is used internally within the nonlinear solvers. 486 487 If the user did did not write their equations in implicit form, this 488 function recasts them in implicit form. 489 490 Level: developer 491 492 .keywords: TS, compute 493 494 .seealso: TSSetIFunction(), TSComputeRHSFunction() 495 @*/ 496 PetscErrorCode TSComputeIFunction(TS ts,PetscReal t,Vec U,Vec Udot,Vec Y,PetscBool imex) 497 { 498 PetscErrorCode ierr; 499 TSIFunction ifunction; 500 TSRHSFunction rhsfunction; 501 void *ctx; 502 DM dm; 503 504 PetscFunctionBegin; 505 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 506 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 507 PetscValidHeaderSpecific(Udot,VEC_CLASSID,4); 508 PetscValidHeaderSpecific(Y,VEC_CLASSID,5); 509 510 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 511 ierr = DMTSGetIFunction(dm,&ifunction,&ctx);CHKERRQ(ierr); 512 ierr = DMTSGetRHSFunction(dm,&rhsfunction,PETSC_NULL);CHKERRQ(ierr); 513 514 if (!rhsfunction && !ifunction) SETERRQ(((PetscObject)ts)->comm,PETSC_ERR_USER,"Must call TSSetRHSFunction() and / or TSSetIFunction()"); 515 516 ierr = PetscLogEventBegin(TS_FunctionEval,ts,U,Udot,Y);CHKERRQ(ierr); 517 if (ifunction) { 518 PetscStackPush("TS user implicit function"); 519 ierr = (*ifunction)(ts,t,U,Udot,Y,ctx);CHKERRQ(ierr); 520 PetscStackPop; 521 } 522 if (imex) { 523 if (!ifunction) { 524 ierr = VecCopy(Udot,Y);CHKERRQ(ierr); 525 } 526 } else if (rhsfunction) { 527 if (ifunction) { 528 Vec Frhs; 529 ierr = TSGetRHSVec_Private(ts,&Frhs);CHKERRQ(ierr); 530 ierr = TSComputeRHSFunction(ts,t,U,Frhs);CHKERRQ(ierr); 531 ierr = VecAXPY(Y,-1,Frhs);CHKERRQ(ierr); 532 } else { 533 ierr = TSComputeRHSFunction(ts,t,U,Y);CHKERRQ(ierr); 534 ierr = VecAYPX(Y,-1,Udot);CHKERRQ(ierr); 535 } 536 } 537 ierr = PetscLogEventEnd(TS_FunctionEval,ts,U,Udot,Y);CHKERRQ(ierr); 538 PetscFunctionReturn(0); 539 } 540 541 #undef __FUNCT__ 542 #define __FUNCT__ "TSComputeIJacobian" 543 /*@ 544 TSComputeIJacobian - Evaluates the Jacobian of the DAE 545 546 Collective on TS and Vec 547 548 Input 549 Input Parameters: 550 + ts - the TS context 551 . t - current timestep 552 . U - state vector 553 . Udot - time derivative of state vector 554 . shift - shift to apply, see note below 555 - imex - flag indicates if the method is IMEX so that the RHSJacobian should be kept separate 556 557 Output Parameters: 558 + A - Jacobian matrix 559 . B - optional preconditioning matrix 560 - flag - flag indicating matrix structure 561 562 Notes: 563 If F(t,U,Udot)=0 is the DAE, the required Jacobian is 564 565 dF/dU + shift*dF/dUdot 566 567 Most users should not need to explicitly call this routine, as it 568 is used internally within the nonlinear solvers. 569 570 Level: developer 571 572 .keywords: TS, compute, Jacobian, matrix 573 574 .seealso: TSSetIJacobian() 575 @*/ 576 PetscErrorCode TSComputeIJacobian(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat *A,Mat *B,MatStructure *flg,PetscBool imex) 577 { 578 PetscInt Ustate, Udotstate; 579 PetscErrorCode ierr; 580 TSIJacobian ijacobian; 581 TSRHSJacobian rhsjacobian; 582 DM dm; 583 void *ctx; 584 585 PetscFunctionBegin; 586 587 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 588 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 589 PetscValidHeaderSpecific(Udot,VEC_CLASSID,4); 590 PetscValidPointer(A,6); 591 PetscValidHeaderSpecific(*A,MAT_CLASSID,6); 592 PetscValidPointer(B,7); 593 PetscValidHeaderSpecific(*B,MAT_CLASSID,7); 594 PetscValidPointer(flg,8); 595 596 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 597 ierr = DMTSGetIJacobian(dm,&ijacobian,&ctx);CHKERRQ(ierr); 598 ierr = DMTSGetRHSJacobian(dm,&rhsjacobian,PETSC_NULL);CHKERRQ(ierr); 599 600 ierr = PetscObjectStateQuery((PetscObject)U,&Ustate);CHKERRQ(ierr); 601 ierr = PetscObjectStateQuery((PetscObject)Udot,&Udotstate);CHKERRQ(ierr); 602 if (ts->ijacobian.time == t && (ts->problem_type == TS_LINEAR || (ts->ijacobian.X == U && ts->ijacobian.Xstate == Ustate && ts->ijacobian.Xdot == Udot && ts->ijacobian.Xdotstate == Udotstate && ts->ijacobian.imex == imex))) { 603 *flg = ts->ijacobian.mstructure; 604 ierr = MatScale(*A, shift / ts->ijacobian.shift);CHKERRQ(ierr); 605 PetscFunctionReturn(0); 606 } 607 608 if (!rhsjacobian && !ijacobian) SETERRQ(((PetscObject)ts)->comm,PETSC_ERR_USER,"Must call TSSetRHSJacobian() and / or TSSetIJacobian()"); 609 610 *flg = SAME_NONZERO_PATTERN; /* In case we're solving a linear problem in which case it wouldn't get initialized below. */ 611 ierr = PetscLogEventBegin(TS_JacobianEval,ts,U,*A,*B);CHKERRQ(ierr); 612 if (ijacobian) { 613 *flg = DIFFERENT_NONZERO_PATTERN; 614 PetscStackPush("TS user implicit Jacobian"); 615 ierr = (*ijacobian)(ts,t,U,Udot,shift,A,B,flg,ctx);CHKERRQ(ierr); 616 PetscStackPop; 617 /* make sure user returned a correct Jacobian and preconditioner */ 618 PetscValidHeaderSpecific(*A,MAT_CLASSID,4); 619 PetscValidHeaderSpecific(*B,MAT_CLASSID,5); 620 } 621 if (imex) { 622 if (!ijacobian) { /* system was written as Udot = G(t,U) */ 623 ierr = MatZeroEntries(*A);CHKERRQ(ierr); 624 ierr = MatShift(*A,shift);CHKERRQ(ierr); 625 if (*A != *B) { 626 ierr = MatZeroEntries(*B);CHKERRQ(ierr); 627 ierr = MatShift(*B,shift);CHKERRQ(ierr); 628 } 629 *flg = SAME_PRECONDITIONER; 630 } 631 } else { 632 if (!ijacobian) { 633 ierr = TSComputeRHSJacobian(ts,t,U,A,B,flg);CHKERRQ(ierr); 634 ierr = MatScale(*A,-1);CHKERRQ(ierr); 635 ierr = MatShift(*A,shift);CHKERRQ(ierr); 636 if (*A != *B) { 637 ierr = MatScale(*B,-1);CHKERRQ(ierr); 638 ierr = MatShift(*B,shift);CHKERRQ(ierr); 639 } 640 } else if (rhsjacobian) { 641 Mat Arhs,Brhs; 642 MatStructure axpy,flg2 = DIFFERENT_NONZERO_PATTERN; 643 ierr = TSGetRHSMats_Private(ts,&Arhs,&Brhs);CHKERRQ(ierr); 644 ierr = TSComputeRHSJacobian(ts,t,U,&Arhs,&Brhs,&flg2);CHKERRQ(ierr); 645 axpy = (*flg == flg2) ? SAME_NONZERO_PATTERN : DIFFERENT_NONZERO_PATTERN; 646 ierr = MatAXPY(*A,-1,Arhs,axpy);CHKERRQ(ierr); 647 if (*A != *B) { 648 ierr = MatAXPY(*B,-1,Brhs,axpy);CHKERRQ(ierr); 649 } 650 *flg = PetscMin(*flg,flg2); 651 } 652 } 653 654 ts->ijacobian.time = t; 655 ts->ijacobian.X = U; 656 ts->ijacobian.Xdot = Udot; 657 ierr = PetscObjectStateQuery((PetscObject)U,&ts->ijacobian.Xstate);CHKERRQ(ierr); 658 ierr = PetscObjectStateQuery((PetscObject)Udot,&ts->ijacobian.Xdotstate);CHKERRQ(ierr); 659 ts->ijacobian.shift = shift; 660 ts->ijacobian.imex = imex; 661 ts->ijacobian.mstructure = *flg; 662 ierr = PetscLogEventEnd(TS_JacobianEval,ts,U,*A,*B);CHKERRQ(ierr); 663 PetscFunctionReturn(0); 664 } 665 666 #undef __FUNCT__ 667 #define __FUNCT__ "TSSetRHSFunction" 668 /*@C 669 TSSetRHSFunction - Sets the routine for evaluating the function, 670 where U_t = G(t,u). 671 672 Logically Collective on TS 673 674 Input Parameters: 675 + ts - the TS context obtained from TSCreate() 676 . r - vector to put the computed right hand side (or PETSC_NULL to have it created) 677 . f - routine for evaluating the right-hand-side function 678 - ctx - [optional] user-defined context for private data for the 679 function evaluation routine (may be PETSC_NULL) 680 681 Calling sequence of func: 682 $ func (TS ts,PetscReal t,Vec u,Vec F,void *ctx); 683 684 + t - current timestep 685 . u - input vector 686 . F - function vector 687 - ctx - [optional] user-defined function context 688 689 Level: beginner 690 691 .keywords: TS, timestep, set, right-hand-side, function 692 693 .seealso: TSSetRHSJacobian(), TSSetIJacobian() 694 @*/ 695 PetscErrorCode TSSetRHSFunction(TS ts,Vec r,PetscErrorCode (*f)(TS,PetscReal,Vec,Vec,void*),void *ctx) 696 { 697 PetscErrorCode ierr; 698 SNES snes; 699 Vec ralloc = PETSC_NULL; 700 DM dm; 701 702 PetscFunctionBegin; 703 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 704 if (r) PetscValidHeaderSpecific(r,VEC_CLASSID,2); 705 706 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 707 ierr = DMTSSetRHSFunction(dm,f,ctx);CHKERRQ(ierr); 708 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 709 if (!r && !ts->dm && ts->vec_sol) { 710 ierr = VecDuplicate(ts->vec_sol,&ralloc);CHKERRQ(ierr); 711 r = ralloc; 712 } 713 ierr = SNESSetFunction(snes,r,SNESTSFormFunction,ts);CHKERRQ(ierr); 714 ierr = VecDestroy(&ralloc);CHKERRQ(ierr); 715 PetscFunctionReturn(0); 716 } 717 718 #undef __FUNCT__ 719 #define __FUNCT__ "TSSetSolutionFunction" 720 /*@C 721 TSSetSolutionFunction - Provide a function that computes the solution of the ODE or DAE 722 723 Logically Collective on TS 724 725 Input Parameters: 726 + ts - the TS context obtained from TSCreate() 727 . f - routine for evaluating the solution 728 - ctx - [optional] user-defined context for private data for the 729 function evaluation routine (may be PETSC_NULL) 730 731 Calling sequence of func: 732 $ func (TS ts,PetscReal t,Vec u,void *ctx); 733 734 + t - current timestep 735 . u - output vector 736 - ctx - [optional] user-defined function context 737 738 Notes: 739 This routine is used for testing accuracy of time integration schemes when you already know the solution. 740 If analytic solutions are not known for your system, consider using the Method of Manufactured Solutions to 741 create closed-form solutions with non-physical forcing terms. 742 743 For low-dimensional problems solved in serial, such as small discrete systems, TSMonitorLGError() can be used to monitor the error history. 744 745 Level: beginner 746 747 .keywords: TS, timestep, set, right-hand-side, function 748 749 .seealso: TSSetRHSJacobian(), TSSetIJacobian(), TSComputeSolutionFunction() 750 @*/ 751 PetscErrorCode TSSetSolutionFunction(TS ts,PetscErrorCode (*f)(TS,PetscReal,Vec,void*),void *ctx) 752 { 753 PetscErrorCode ierr; 754 DM dm; 755 756 PetscFunctionBegin; 757 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 758 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 759 ierr = DMTSSetSolutionFunction(dm,f,ctx);CHKERRQ(ierr); 760 PetscFunctionReturn(0); 761 } 762 763 #undef __FUNCT__ 764 #define __FUNCT__ "TSSetRHSJacobian" 765 /*@C 766 TSSetRHSJacobian - Sets the function to compute the Jacobian of F, 767 where U_t = G(U,t), as well as the location to store the matrix. 768 769 Logically Collective on TS 770 771 Input Parameters: 772 + ts - the TS context obtained from TSCreate() 773 . A - Jacobian matrix 774 . B - preconditioner matrix (usually same as A) 775 . f - the Jacobian evaluation routine 776 - ctx - [optional] user-defined context for private data for the 777 Jacobian evaluation routine (may be PETSC_NULL) 778 779 Calling sequence of func: 780 $ func (TS ts,PetscReal t,Vec u,Mat *A,Mat *B,MatStructure *flag,void *ctx); 781 782 + t - current timestep 783 . u - input vector 784 . A - matrix A, where U_t = A(t)u 785 . B - preconditioner matrix, usually the same as A 786 . flag - flag indicating information about the preconditioner matrix 787 structure (same as flag in KSPSetOperators()) 788 - ctx - [optional] user-defined context for matrix evaluation routine 789 790 Notes: 791 See KSPSetOperators() for important information about setting the flag 792 output parameter in the routine func(). Be sure to read this information! 793 794 The routine func() takes Mat * as the matrix arguments rather than Mat. 795 This allows the matrix evaluation routine to replace A and/or B with a 796 completely new matrix structure (not just different matrix elements) 797 when appropriate, for instance, if the nonzero structure is changing 798 throughout the global iterations. 799 800 Level: beginner 801 802 .keywords: TS, timestep, set, right-hand-side, Jacobian 803 804 .seealso: SNESDefaultComputeJacobianColor(), TSSetRHSFunction() 805 806 @*/ 807 PetscErrorCode TSSetRHSJacobian(TS ts,Mat A,Mat B,TSRHSJacobian f,void *ctx) 808 { 809 PetscErrorCode ierr; 810 SNES snes; 811 DM dm; 812 TSIJacobian ijacobian; 813 814 PetscFunctionBegin; 815 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 816 if (A) PetscValidHeaderSpecific(A,MAT_CLASSID,2); 817 if (B) PetscValidHeaderSpecific(B,MAT_CLASSID,3); 818 if (A) PetscCheckSameComm(ts,1,A,2); 819 if (B) PetscCheckSameComm(ts,1,B,3); 820 821 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 822 ierr = DMTSSetRHSJacobian(dm,f,ctx);CHKERRQ(ierr); 823 ierr = DMTSGetIJacobian(dm,&ijacobian,PETSC_NULL);CHKERRQ(ierr); 824 825 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 826 if (!ijacobian) { 827 ierr = SNESSetJacobian(snes,A,B,SNESTSFormJacobian,ts);CHKERRQ(ierr); 828 } 829 if (A) { 830 ierr = PetscObjectReference((PetscObject)A);CHKERRQ(ierr); 831 ierr = MatDestroy(&ts->Arhs);CHKERRQ(ierr); 832 ts->Arhs = A; 833 } 834 if (B) { 835 ierr = PetscObjectReference((PetscObject)B);CHKERRQ(ierr); 836 ierr = MatDestroy(&ts->Brhs);CHKERRQ(ierr); 837 ts->Brhs = B; 838 } 839 PetscFunctionReturn(0); 840 } 841 842 843 #undef __FUNCT__ 844 #define __FUNCT__ "TSSetIFunction" 845 /*@C 846 TSSetIFunction - Set the function to compute F(t,U,U_t) where F() = 0 is the DAE to be solved. 847 848 Logically Collective on TS 849 850 Input Parameters: 851 + ts - the TS context obtained from TSCreate() 852 . r - vector to hold the residual (or PETSC_NULL to have it created internally) 853 . f - the function evaluation routine 854 - ctx - user-defined context for private data for the function evaluation routine (may be PETSC_NULL) 855 856 Calling sequence of f: 857 $ f(TS ts,PetscReal t,Vec u,Vec u_t,Vec F,ctx); 858 859 + t - time at step/stage being solved 860 . u - state vector 861 . u_t - time derivative of state vector 862 . F - function vector 863 - ctx - [optional] user-defined context for matrix evaluation routine 864 865 Important: 866 The user MUST call either this routine, TSSetRHSFunction(). This routine must be used when not solving an ODE, for example a DAE. 867 868 Level: beginner 869 870 .keywords: TS, timestep, set, DAE, Jacobian 871 872 .seealso: TSSetRHSJacobian(), TSSetRHSFunction(), TSSetIJacobian() 873 @*/ 874 PetscErrorCode TSSetIFunction(TS ts,Vec res,TSIFunction f,void *ctx) 875 { 876 PetscErrorCode ierr; 877 SNES snes; 878 Vec resalloc = PETSC_NULL; 879 DM dm; 880 881 PetscFunctionBegin; 882 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 883 if (res) PetscValidHeaderSpecific(res,VEC_CLASSID,2); 884 885 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 886 ierr = DMTSSetIFunction(dm,f,ctx);CHKERRQ(ierr); 887 888 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 889 if (!res && !ts->dm && ts->vec_sol) { 890 ierr = VecDuplicate(ts->vec_sol,&resalloc);CHKERRQ(ierr); 891 res = resalloc; 892 } 893 ierr = SNESSetFunction(snes,res,SNESTSFormFunction,ts);CHKERRQ(ierr); 894 ierr = VecDestroy(&resalloc);CHKERRQ(ierr); 895 896 PetscFunctionReturn(0); 897 } 898 899 #undef __FUNCT__ 900 #define __FUNCT__ "TSGetIFunction" 901 /*@C 902 TSGetIFunction - Returns the vector where the implicit residual is stored and the function/contex to compute it. 903 904 Not Collective 905 906 Input Parameter: 907 . ts - the TS context 908 909 Output Parameter: 910 + r - vector to hold residual (or PETSC_NULL) 911 . func - the function to compute residual (or PETSC_NULL) 912 - ctx - the function context (or PETSC_NULL) 913 914 Level: advanced 915 916 .keywords: TS, nonlinear, get, function 917 918 .seealso: TSSetIFunction(), SNESGetFunction() 919 @*/ 920 PetscErrorCode TSGetIFunction(TS ts,Vec *r,TSIFunction *func,void **ctx) 921 { 922 PetscErrorCode ierr; 923 SNES snes; 924 DM dm; 925 926 PetscFunctionBegin; 927 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 928 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 929 ierr = SNESGetFunction(snes,r,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); 930 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 931 ierr = DMTSGetIFunction(dm,func,ctx);CHKERRQ(ierr); 932 PetscFunctionReturn(0); 933 } 934 935 #undef __FUNCT__ 936 #define __FUNCT__ "TSGetRHSFunction" 937 /*@C 938 TSGetRHSFunction - Returns the vector where the right hand side is stored and the function/context to compute it. 939 940 Not Collective 941 942 Input Parameter: 943 . ts - the TS context 944 945 Output Parameter: 946 + r - vector to hold computed right hand side (or PETSC_NULL) 947 . func - the function to compute right hand side (or PETSC_NULL) 948 - ctx - the function context (or PETSC_NULL) 949 950 Level: advanced 951 952 .keywords: TS, nonlinear, get, function 953 954 .seealso: TSSetRhsfunction(), SNESGetFunction() 955 @*/ 956 PetscErrorCode TSGetRHSFunction(TS ts,Vec *r,TSRHSFunction *func,void **ctx) 957 { 958 PetscErrorCode ierr; 959 SNES snes; 960 DM dm; 961 962 PetscFunctionBegin; 963 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 964 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 965 ierr = SNESGetFunction(snes,r,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); 966 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 967 ierr = DMTSGetRHSFunction(dm,func,ctx);CHKERRQ(ierr); 968 PetscFunctionReturn(0); 969 } 970 971 #undef __FUNCT__ 972 #define __FUNCT__ "TSSetIJacobian" 973 /*@C 974 TSSetIJacobian - Set the function to compute the matrix dF/dU + a*dF/dU_t where F(t,U,U_t) is the function 975 you provided with TSSetIFunction(). 976 977 Logically Collective on TS 978 979 Input Parameters: 980 + ts - the TS context obtained from TSCreate() 981 . A - Jacobian matrix 982 . B - preconditioning matrix for A (may be same as A) 983 . f - the Jacobian evaluation routine 984 - ctx - user-defined context for private data for the Jacobian evaluation routine (may be PETSC_NULL) 985 986 Calling sequence of f: 987 $ f(TS ts,PetscReal t,Vec U,Vec U_t,PetscReal a,Mat *A,Mat *B,MatStructure *flag,void *ctx); 988 989 + t - time at step/stage being solved 990 . U - state vector 991 . U_t - time derivative of state vector 992 . a - shift 993 . A - Jacobian of F(t,U,W+a*U), equivalent to dF/dU + a*dF/dU_t 994 . B - preconditioning matrix for A, may be same as A 995 . flag - flag indicating information about the preconditioner matrix 996 structure (same as flag in KSPSetOperators()) 997 - ctx - [optional] user-defined context for matrix evaluation routine 998 999 Notes: 1000 The matrices A and B are exactly the matrices that are used by SNES for the nonlinear solve. 1001 1002 The matrix dF/dU + a*dF/dU_t you provide turns out to be 1003 the Jacobian of F(t,U,W+a*U) where F(t,U,U_t) = 0 is the DAE to be solved. 1004 The time integrator internally approximates U_t by W+a*U where the positive "shift" 1005 a and vector W depend on the integration method, step size, and past states. For example with 1006 the backward Euler method a = 1/dt and W = -a*U(previous timestep) so 1007 W + a*U = a*(U - U(previous timestep)) = (U - U(previous timestep))/dt 1008 1009 Level: beginner 1010 1011 .keywords: TS, timestep, DAE, Jacobian 1012 1013 .seealso: TSSetIFunction(), TSSetRHSJacobian(), SNESDefaultComputeJacobianColor(), SNESDefaultComputeJacobian() 1014 1015 @*/ 1016 PetscErrorCode TSSetIJacobian(TS ts,Mat A,Mat B,TSIJacobian f,void *ctx) 1017 { 1018 PetscErrorCode ierr; 1019 SNES snes; 1020 DM dm; 1021 1022 PetscFunctionBegin; 1023 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1024 if (A) PetscValidHeaderSpecific(A,MAT_CLASSID,2); 1025 if (B) PetscValidHeaderSpecific(B,MAT_CLASSID,3); 1026 if (A) PetscCheckSameComm(ts,1,A,2); 1027 if (B) PetscCheckSameComm(ts,1,B,3); 1028 1029 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1030 ierr = DMTSSetIJacobian(dm,f,ctx);CHKERRQ(ierr); 1031 1032 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1033 ierr = SNESSetJacobian(snes,A,B,SNESTSFormJacobian,ts);CHKERRQ(ierr); 1034 PetscFunctionReturn(0); 1035 } 1036 1037 #undef __FUNCT__ 1038 #define __FUNCT__ "TSView" 1039 /*@C 1040 TSView - Prints the TS data structure. 1041 1042 Collective on TS 1043 1044 Input Parameters: 1045 + ts - the TS context obtained from TSCreate() 1046 - viewer - visualization context 1047 1048 Options Database Key: 1049 . -ts_view - calls TSView() at end of TSStep() 1050 1051 Notes: 1052 The available visualization contexts include 1053 + PETSC_VIEWER_STDOUT_SELF - standard output (default) 1054 - PETSC_VIEWER_STDOUT_WORLD - synchronized standard 1055 output where only the first processor opens 1056 the file. All other processors send their 1057 data to the first processor to print. 1058 1059 The user can open an alternative visualization context with 1060 PetscViewerASCIIOpen() - output to a specified file. 1061 1062 Level: beginner 1063 1064 .keywords: TS, timestep, view 1065 1066 .seealso: PetscViewerASCIIOpen() 1067 @*/ 1068 PetscErrorCode TSView(TS ts,PetscViewer viewer) 1069 { 1070 PetscErrorCode ierr; 1071 TSType type; 1072 PetscBool iascii,isstring,isundials; 1073 1074 PetscFunctionBegin; 1075 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1076 if (!viewer) { 1077 ierr = PetscViewerASCIIGetStdout(((PetscObject)ts)->comm,&viewer);CHKERRQ(ierr); 1078 } 1079 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,2); 1080 PetscCheckSameComm(ts,1,viewer,2); 1081 1082 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1083 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSTRING,&isstring);CHKERRQ(ierr); 1084 if (iascii) { 1085 ierr = PetscObjectPrintClassNamePrefixType((PetscObject)ts,viewer,"TS Object");CHKERRQ(ierr); 1086 ierr = PetscViewerASCIIPrintf(viewer," maximum steps=%D\n",ts->max_steps);CHKERRQ(ierr); 1087 ierr = PetscViewerASCIIPrintf(viewer," maximum time=%G\n",ts->max_time);CHKERRQ(ierr); 1088 if (ts->problem_type == TS_NONLINEAR) { 1089 ierr = PetscViewerASCIIPrintf(viewer," total number of nonlinear solver iterations=%D\n",ts->snes_its);CHKERRQ(ierr); 1090 ierr = PetscViewerASCIIPrintf(viewer," total number of nonlinear solve failures=%D\n",ts->num_snes_failures);CHKERRQ(ierr); 1091 } 1092 ierr = PetscViewerASCIIPrintf(viewer," total number of linear solver iterations=%D\n",ts->ksp_its);CHKERRQ(ierr); 1093 ierr = PetscViewerASCIIPrintf(viewer," total number of rejected steps=%D\n",ts->reject);CHKERRQ(ierr); 1094 if (ts->ops->view) { 1095 ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr); 1096 ierr = (*ts->ops->view)(ts,viewer);CHKERRQ(ierr); 1097 ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr); 1098 } 1099 } else if (isstring) { 1100 ierr = TSGetType(ts,&type);CHKERRQ(ierr); 1101 ierr = PetscViewerStringSPrintf(viewer," %-7.7s",type);CHKERRQ(ierr); 1102 } 1103 ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr); 1104 ierr = PetscObjectTypeCompare((PetscObject)ts,TSSUNDIALS,&isundials);CHKERRQ(ierr); 1105 ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr); 1106 PetscFunctionReturn(0); 1107 } 1108 1109 1110 #undef __FUNCT__ 1111 #define __FUNCT__ "TSSetApplicationContext" 1112 /*@ 1113 TSSetApplicationContext - Sets an optional user-defined context for 1114 the timesteppers. 1115 1116 Logically Collective on TS 1117 1118 Input Parameters: 1119 + ts - the TS context obtained from TSCreate() 1120 - usrP - optional user context 1121 1122 Level: intermediate 1123 1124 .keywords: TS, timestep, set, application, context 1125 1126 .seealso: TSGetApplicationContext() 1127 @*/ 1128 PetscErrorCode TSSetApplicationContext(TS ts,void *usrP) 1129 { 1130 PetscFunctionBegin; 1131 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1132 ts->user = usrP; 1133 PetscFunctionReturn(0); 1134 } 1135 1136 #undef __FUNCT__ 1137 #define __FUNCT__ "TSGetApplicationContext" 1138 /*@ 1139 TSGetApplicationContext - Gets the user-defined context for the 1140 timestepper. 1141 1142 Not Collective 1143 1144 Input Parameter: 1145 . ts - the TS context obtained from TSCreate() 1146 1147 Output Parameter: 1148 . usrP - user context 1149 1150 Level: intermediate 1151 1152 .keywords: TS, timestep, get, application, context 1153 1154 .seealso: TSSetApplicationContext() 1155 @*/ 1156 PetscErrorCode TSGetApplicationContext(TS ts,void *usrP) 1157 { 1158 PetscFunctionBegin; 1159 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1160 *(void**)usrP = ts->user; 1161 PetscFunctionReturn(0); 1162 } 1163 1164 #undef __FUNCT__ 1165 #define __FUNCT__ "TSGetTimeStepNumber" 1166 /*@ 1167 TSGetTimeStepNumber - Gets the number of time steps completed. 1168 1169 Not Collective 1170 1171 Input Parameter: 1172 . ts - the TS context obtained from TSCreate() 1173 1174 Output Parameter: 1175 . iter - number of steps completed so far 1176 1177 Level: intermediate 1178 1179 .keywords: TS, timestep, get, iteration, number 1180 .seealso: TSGetTime(), TSGetTimeStep(), TSSetPreStep(), TSSetPreStage(), TSSetPostStep() 1181 @*/ 1182 PetscErrorCode TSGetTimeStepNumber(TS ts,PetscInt* iter) 1183 { 1184 PetscFunctionBegin; 1185 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1186 PetscValidIntPointer(iter,2); 1187 *iter = ts->steps; 1188 PetscFunctionReturn(0); 1189 } 1190 1191 #undef __FUNCT__ 1192 #define __FUNCT__ "TSSetInitialTimeStep" 1193 /*@ 1194 TSSetInitialTimeStep - Sets the initial timestep to be used, 1195 as well as the initial time. 1196 1197 Logically Collective on TS 1198 1199 Input Parameters: 1200 + ts - the TS context obtained from TSCreate() 1201 . initial_time - the initial time 1202 - time_step - the size of the timestep 1203 1204 Level: intermediate 1205 1206 .seealso: TSSetTimeStep(), TSGetTimeStep() 1207 1208 .keywords: TS, set, initial, timestep 1209 @*/ 1210 PetscErrorCode TSSetInitialTimeStep(TS ts,PetscReal initial_time,PetscReal time_step) 1211 { 1212 PetscErrorCode ierr; 1213 1214 PetscFunctionBegin; 1215 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1216 ierr = TSSetTimeStep(ts,time_step);CHKERRQ(ierr); 1217 ierr = TSSetTime(ts,initial_time);CHKERRQ(ierr); 1218 PetscFunctionReturn(0); 1219 } 1220 1221 #undef __FUNCT__ 1222 #define __FUNCT__ "TSSetTimeStep" 1223 /*@ 1224 TSSetTimeStep - Allows one to reset the timestep at any time, 1225 useful for simple pseudo-timestepping codes. 1226 1227 Logically Collective on TS 1228 1229 Input Parameters: 1230 + ts - the TS context obtained from TSCreate() 1231 - time_step - the size of the timestep 1232 1233 Level: intermediate 1234 1235 .seealso: TSSetInitialTimeStep(), TSGetTimeStep() 1236 1237 .keywords: TS, set, timestep 1238 @*/ 1239 PetscErrorCode TSSetTimeStep(TS ts,PetscReal time_step) 1240 { 1241 PetscFunctionBegin; 1242 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1243 PetscValidLogicalCollectiveReal(ts,time_step,2); 1244 ts->time_step = time_step; 1245 ts->time_step_orig = time_step; 1246 PetscFunctionReturn(0); 1247 } 1248 1249 #undef __FUNCT__ 1250 #define __FUNCT__ "TSSetExactFinalTime" 1251 /*@ 1252 TSSetExactFinalTime - Determines whether to interpolate solution to the 1253 exact final time requested by the user or just returns it at the final time 1254 it computed. 1255 1256 Logically Collective on TS 1257 1258 Input Parameter: 1259 + ts - the time-step context 1260 - ft - PETSC_TRUE if interpolates, else PETSC_FALSE 1261 1262 Level: beginner 1263 1264 .seealso: TSSetDuration() 1265 @*/ 1266 PetscErrorCode TSSetExactFinalTime(TS ts,PetscBool flg) 1267 { 1268 PetscFunctionBegin; 1269 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1270 PetscValidLogicalCollectiveBool(ts,flg,2); 1271 ts->exact_final_time = flg; 1272 PetscFunctionReturn(0); 1273 } 1274 1275 #undef __FUNCT__ 1276 #define __FUNCT__ "TSGetTimeStep" 1277 /*@ 1278 TSGetTimeStep - Gets the current timestep size. 1279 1280 Not Collective 1281 1282 Input Parameter: 1283 . ts - the TS context obtained from TSCreate() 1284 1285 Output Parameter: 1286 . dt - the current timestep size 1287 1288 Level: intermediate 1289 1290 .seealso: TSSetInitialTimeStep(), TSGetTimeStep() 1291 1292 .keywords: TS, get, timestep 1293 @*/ 1294 PetscErrorCode TSGetTimeStep(TS ts,PetscReal* dt) 1295 { 1296 PetscFunctionBegin; 1297 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1298 PetscValidRealPointer(dt,2); 1299 *dt = ts->time_step; 1300 PetscFunctionReturn(0); 1301 } 1302 1303 #undef __FUNCT__ 1304 #define __FUNCT__ "TSGetSolution" 1305 /*@ 1306 TSGetSolution - Returns the solution at the present timestep. It 1307 is valid to call this routine inside the function that you are evaluating 1308 in order to move to the new timestep. This vector not changed until 1309 the solution at the next timestep has been calculated. 1310 1311 Not Collective, but Vec returned is parallel if TS is parallel 1312 1313 Input Parameter: 1314 . ts - the TS context obtained from TSCreate() 1315 1316 Output Parameter: 1317 . v - the vector containing the solution 1318 1319 Level: intermediate 1320 1321 .seealso: TSGetTimeStep() 1322 1323 .keywords: TS, timestep, get, solution 1324 @*/ 1325 PetscErrorCode TSGetSolution(TS ts,Vec *v) 1326 { 1327 PetscFunctionBegin; 1328 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1329 PetscValidPointer(v,2); 1330 *v = ts->vec_sol; 1331 PetscFunctionReturn(0); 1332 } 1333 1334 /* ----- Routines to initialize and destroy a timestepper ---- */ 1335 #undef __FUNCT__ 1336 #define __FUNCT__ "TSSetProblemType" 1337 /*@ 1338 TSSetProblemType - Sets the type of problem to be solved. 1339 1340 Not collective 1341 1342 Input Parameters: 1343 + ts - The TS 1344 - type - One of TS_LINEAR, TS_NONLINEAR where these types refer to problems of the forms 1345 .vb 1346 U_t - A U = 0 (linear) 1347 U_t - A(t) U = 0 (linear) 1348 F(t,U,U_t) = 0 (nonlinear) 1349 .ve 1350 1351 Level: beginner 1352 1353 .keywords: TS, problem type 1354 .seealso: TSSetUp(), TSProblemType, TS 1355 @*/ 1356 PetscErrorCode TSSetProblemType(TS ts, TSProblemType type) 1357 { 1358 PetscErrorCode ierr; 1359 1360 PetscFunctionBegin; 1361 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 1362 ts->problem_type = type; 1363 if (type == TS_LINEAR) { 1364 SNES snes; 1365 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1366 ierr = SNESSetType(snes,SNESKSPONLY);CHKERRQ(ierr); 1367 } 1368 PetscFunctionReturn(0); 1369 } 1370 1371 #undef __FUNCT__ 1372 #define __FUNCT__ "TSGetProblemType" 1373 /*@C 1374 TSGetProblemType - Gets the type of problem to be solved. 1375 1376 Not collective 1377 1378 Input Parameter: 1379 . ts - The TS 1380 1381 Output Parameter: 1382 . type - One of TS_LINEAR, TS_NONLINEAR where these types refer to problems of the forms 1383 .vb 1384 M U_t = A U 1385 M(t) U_t = A(t) U 1386 F(t,U,U_t) 1387 .ve 1388 1389 Level: beginner 1390 1391 .keywords: TS, problem type 1392 .seealso: TSSetUp(), TSProblemType, TS 1393 @*/ 1394 PetscErrorCode TSGetProblemType(TS ts, TSProblemType *type) 1395 { 1396 PetscFunctionBegin; 1397 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 1398 PetscValidIntPointer(type,2); 1399 *type = ts->problem_type; 1400 PetscFunctionReturn(0); 1401 } 1402 1403 #undef __FUNCT__ 1404 #define __FUNCT__ "TSSetUp" 1405 /*@ 1406 TSSetUp - Sets up the internal data structures for the later use 1407 of a timestepper. 1408 1409 Collective on TS 1410 1411 Input Parameter: 1412 . ts - the TS context obtained from TSCreate() 1413 1414 Notes: 1415 For basic use of the TS solvers the user need not explicitly call 1416 TSSetUp(), since these actions will automatically occur during 1417 the call to TSStep(). However, if one wishes to control this 1418 phase separately, TSSetUp() should be called after TSCreate() 1419 and optional routines of the form TSSetXXX(), but before TSStep(). 1420 1421 Level: advanced 1422 1423 .keywords: TS, timestep, setup 1424 1425 .seealso: TSCreate(), TSStep(), TSDestroy() 1426 @*/ 1427 PetscErrorCode TSSetUp(TS ts) 1428 { 1429 PetscErrorCode ierr; 1430 DM dm; 1431 PetscErrorCode (*func)(SNES,Vec,Vec,void*); 1432 PetscErrorCode (*jac)(SNES,Vec,Mat*,Mat*,MatStructure*,void*); 1433 TSIJacobian ijac; 1434 TSRHSJacobian rhsjac; 1435 1436 PetscFunctionBegin; 1437 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1438 if (ts->setupcalled) PetscFunctionReturn(0); 1439 1440 if (!((PetscObject)ts)->type_name) { 1441 ierr = TSSetType(ts,TSEULER);CHKERRQ(ierr); 1442 } 1443 if (ts->exact_final_time == PETSC_DECIDE) ts->exact_final_time = PETSC_FALSE; 1444 1445 if (!ts->vec_sol) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call TSSetSolution() first"); 1446 1447 ierr = TSGetAdapt(ts,&ts->adapt);CHKERRQ(ierr); 1448 1449 if (ts->ops->setup) { 1450 ierr = (*ts->ops->setup)(ts);CHKERRQ(ierr); 1451 } 1452 1453 /* in the case where we've set a DMTSFunction or what have you, we need the default SNESFunction 1454 to be set right but can't do it elsewhere due to the overreliance on ctx=ts. 1455 */ 1456 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1457 ierr = DMSNESGetFunction(dm,&func,PETSC_NULL);CHKERRQ(ierr); 1458 if (!func) { 1459 ierr =DMSNESSetFunction(dm,SNESTSFormFunction,ts);CHKERRQ(ierr); 1460 } 1461 /* if the SNES doesn't have a jacobian set and the TS has an ijacobian or rhsjacobian set, set the SNES to use it. 1462 Otherwise, the SNES will use coloring internally to form the Jacobian. 1463 */ 1464 ierr = DMSNESGetJacobian(dm,&jac,PETSC_NULL);CHKERRQ(ierr); 1465 ierr = DMTSGetIJacobian(dm,&ijac,PETSC_NULL);CHKERRQ(ierr); 1466 ierr = DMTSGetRHSJacobian(dm,&rhsjac,PETSC_NULL);CHKERRQ(ierr); 1467 if (!jac && (ijac || rhsjac)) { 1468 ierr = DMSNESSetJacobian(dm,SNESTSFormJacobian,ts);CHKERRQ(ierr); 1469 } 1470 ts->setupcalled = PETSC_TRUE; 1471 PetscFunctionReturn(0); 1472 } 1473 1474 #undef __FUNCT__ 1475 #define __FUNCT__ "TSReset" 1476 /*@ 1477 TSReset - Resets a TS context and removes any allocated Vecs and Mats. 1478 1479 Collective on TS 1480 1481 Input Parameter: 1482 . ts - the TS context obtained from TSCreate() 1483 1484 Level: beginner 1485 1486 .keywords: TS, timestep, reset 1487 1488 .seealso: TSCreate(), TSSetup(), TSDestroy() 1489 @*/ 1490 PetscErrorCode TSReset(TS ts) 1491 { 1492 PetscErrorCode ierr; 1493 1494 PetscFunctionBegin; 1495 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1496 if (ts->ops->reset) { 1497 ierr = (*ts->ops->reset)(ts);CHKERRQ(ierr); 1498 } 1499 if (ts->snes) {ierr = SNESReset(ts->snes);CHKERRQ(ierr);} 1500 ierr = MatDestroy(&ts->Arhs);CHKERRQ(ierr); 1501 ierr = MatDestroy(&ts->Brhs);CHKERRQ(ierr); 1502 ierr = VecDestroy(&ts->Frhs);CHKERRQ(ierr); 1503 ierr = VecDestroy(&ts->vec_sol);CHKERRQ(ierr); 1504 ierr = VecDestroy(&ts->vatol);CHKERRQ(ierr); 1505 ierr = VecDestroy(&ts->vrtol);CHKERRQ(ierr); 1506 ierr = VecDestroyVecs(ts->nwork,&ts->work);CHKERRQ(ierr); 1507 ts->setupcalled = PETSC_FALSE; 1508 PetscFunctionReturn(0); 1509 } 1510 1511 #undef __FUNCT__ 1512 #define __FUNCT__ "TSDestroy" 1513 /*@ 1514 TSDestroy - Destroys the timestepper context that was created 1515 with TSCreate(). 1516 1517 Collective on TS 1518 1519 Input Parameter: 1520 . ts - the TS context obtained from TSCreate() 1521 1522 Level: beginner 1523 1524 .keywords: TS, timestepper, destroy 1525 1526 .seealso: TSCreate(), TSSetUp(), TSSolve() 1527 @*/ 1528 PetscErrorCode TSDestroy(TS *ts) 1529 { 1530 PetscErrorCode ierr; 1531 1532 PetscFunctionBegin; 1533 if (!*ts) PetscFunctionReturn(0); 1534 PetscValidHeaderSpecific((*ts),TS_CLASSID,1); 1535 if (--((PetscObject)(*ts))->refct > 0) {*ts = 0; PetscFunctionReturn(0);} 1536 1537 ierr = TSReset((*ts));CHKERRQ(ierr); 1538 1539 /* if memory was published with AMS then destroy it */ 1540 ierr = PetscObjectDepublish((*ts));CHKERRQ(ierr); 1541 if ((*ts)->ops->destroy) {ierr = (*(*ts)->ops->destroy)((*ts));CHKERRQ(ierr);} 1542 1543 ierr = TSAdaptDestroy(&(*ts)->adapt);CHKERRQ(ierr); 1544 ierr = SNESDestroy(&(*ts)->snes);CHKERRQ(ierr); 1545 ierr = DMDestroy(&(*ts)->dm);CHKERRQ(ierr); 1546 ierr = TSMonitorCancel((*ts));CHKERRQ(ierr); 1547 1548 ierr = PetscHeaderDestroy(ts);CHKERRQ(ierr); 1549 PetscFunctionReturn(0); 1550 } 1551 1552 #undef __FUNCT__ 1553 #define __FUNCT__ "TSGetSNES" 1554 /*@ 1555 TSGetSNES - Returns the SNES (nonlinear solver) associated with 1556 a TS (timestepper) context. Valid only for nonlinear problems. 1557 1558 Not Collective, but SNES is parallel if TS is parallel 1559 1560 Input Parameter: 1561 . ts - the TS context obtained from TSCreate() 1562 1563 Output Parameter: 1564 . snes - the nonlinear solver context 1565 1566 Notes: 1567 The user can then directly manipulate the SNES context to set various 1568 options, etc. Likewise, the user can then extract and manipulate the 1569 KSP, KSP, and PC contexts as well. 1570 1571 TSGetSNES() does not work for integrators that do not use SNES; in 1572 this case TSGetSNES() returns PETSC_NULL in snes. 1573 1574 Level: beginner 1575 1576 .keywords: timestep, get, SNES 1577 @*/ 1578 PetscErrorCode TSGetSNES(TS ts,SNES *snes) 1579 { 1580 PetscErrorCode ierr; 1581 1582 PetscFunctionBegin; 1583 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1584 PetscValidPointer(snes,2); 1585 if (!ts->snes) { 1586 ierr = SNESCreate(((PetscObject)ts)->comm,&ts->snes);CHKERRQ(ierr); 1587 ierr = SNESSetFunction(ts->snes,PETSC_NULL,SNESTSFormFunction,ts);CHKERRQ(ierr); 1588 ierr = PetscLogObjectParent(ts,ts->snes);CHKERRQ(ierr); 1589 ierr = PetscObjectIncrementTabLevel((PetscObject)ts->snes,(PetscObject)ts,1);CHKERRQ(ierr); 1590 if (ts->dm) {ierr = SNESSetDM(ts->snes,ts->dm);CHKERRQ(ierr);} 1591 if (ts->problem_type == TS_LINEAR) { 1592 ierr = SNESSetType(ts->snes,SNESKSPONLY);CHKERRQ(ierr); 1593 } 1594 } 1595 *snes = ts->snes; 1596 PetscFunctionReturn(0); 1597 } 1598 1599 #undef __FUNCT__ 1600 #define __FUNCT__ "TSGetKSP" 1601 /*@ 1602 TSGetKSP - Returns the KSP (linear solver) associated with 1603 a TS (timestepper) context. 1604 1605 Not Collective, but KSP is parallel if TS is parallel 1606 1607 Input Parameter: 1608 . ts - the TS context obtained from TSCreate() 1609 1610 Output Parameter: 1611 . ksp - the nonlinear solver context 1612 1613 Notes: 1614 The user can then directly manipulate the KSP context to set various 1615 options, etc. Likewise, the user can then extract and manipulate the 1616 KSP and PC contexts as well. 1617 1618 TSGetKSP() does not work for integrators that do not use KSP; 1619 in this case TSGetKSP() returns PETSC_NULL in ksp. 1620 1621 Level: beginner 1622 1623 .keywords: timestep, get, KSP 1624 @*/ 1625 PetscErrorCode TSGetKSP(TS ts,KSP *ksp) 1626 { 1627 PetscErrorCode ierr; 1628 SNES snes; 1629 1630 PetscFunctionBegin; 1631 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1632 PetscValidPointer(ksp,2); 1633 if (!((PetscObject)ts)->type_name) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_NULL,"KSP is not created yet. Call TSSetType() first"); 1634 if (ts->problem_type != TS_LINEAR) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Linear only; use TSGetSNES()"); 1635 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1636 ierr = SNESGetKSP(snes,ksp);CHKERRQ(ierr); 1637 PetscFunctionReturn(0); 1638 } 1639 1640 /* ----------- Routines to set solver parameters ---------- */ 1641 1642 #undef __FUNCT__ 1643 #define __FUNCT__ "TSGetDuration" 1644 /*@ 1645 TSGetDuration - Gets the maximum number of timesteps to use and 1646 maximum time for iteration. 1647 1648 Not Collective 1649 1650 Input Parameters: 1651 + ts - the TS context obtained from TSCreate() 1652 . maxsteps - maximum number of iterations to use, or PETSC_NULL 1653 - maxtime - final time to iterate to, or PETSC_NULL 1654 1655 Level: intermediate 1656 1657 .keywords: TS, timestep, get, maximum, iterations, time 1658 @*/ 1659 PetscErrorCode TSGetDuration(TS ts, PetscInt *maxsteps, PetscReal *maxtime) 1660 { 1661 PetscFunctionBegin; 1662 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 1663 if (maxsteps) { 1664 PetscValidIntPointer(maxsteps,2); 1665 *maxsteps = ts->max_steps; 1666 } 1667 if (maxtime) { 1668 PetscValidScalarPointer(maxtime,3); 1669 *maxtime = ts->max_time; 1670 } 1671 PetscFunctionReturn(0); 1672 } 1673 1674 #undef __FUNCT__ 1675 #define __FUNCT__ "TSSetDuration" 1676 /*@ 1677 TSSetDuration - Sets the maximum number of timesteps to use and 1678 maximum time for iteration. 1679 1680 Logically Collective on TS 1681 1682 Input Parameters: 1683 + ts - the TS context obtained from TSCreate() 1684 . maxsteps - maximum number of iterations to use 1685 - maxtime - final time to iterate to 1686 1687 Options Database Keys: 1688 . -ts_max_steps <maxsteps> - Sets maxsteps 1689 . -ts_final_time <maxtime> - Sets maxtime 1690 1691 Notes: 1692 The default maximum number of iterations is 5000. Default time is 5.0 1693 1694 Level: intermediate 1695 1696 .keywords: TS, timestep, set, maximum, iterations 1697 1698 .seealso: TSSetExactFinalTime() 1699 @*/ 1700 PetscErrorCode TSSetDuration(TS ts,PetscInt maxsteps,PetscReal maxtime) 1701 { 1702 PetscFunctionBegin; 1703 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1704 PetscValidLogicalCollectiveInt(ts,maxsteps,2); 1705 PetscValidLogicalCollectiveReal(ts,maxtime,2); 1706 if (maxsteps >= 0) ts->max_steps = maxsteps; 1707 if (maxtime != PETSC_DEFAULT) ts->max_time = maxtime; 1708 PetscFunctionReturn(0); 1709 } 1710 1711 #undef __FUNCT__ 1712 #define __FUNCT__ "TSSetSolution" 1713 /*@ 1714 TSSetSolution - Sets the initial solution vector 1715 for use by the TS routines. 1716 1717 Logically Collective on TS and Vec 1718 1719 Input Parameters: 1720 + ts - the TS context obtained from TSCreate() 1721 - u - the solution vector 1722 1723 Level: beginner 1724 1725 .keywords: TS, timestep, set, solution, initial conditions 1726 @*/ 1727 PetscErrorCode TSSetSolution(TS ts,Vec u) 1728 { 1729 PetscErrorCode ierr; 1730 DM dm; 1731 1732 PetscFunctionBegin; 1733 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1734 PetscValidHeaderSpecific(u,VEC_CLASSID,2); 1735 ierr = PetscObjectReference((PetscObject)u);CHKERRQ(ierr); 1736 ierr = VecDestroy(&ts->vec_sol);CHKERRQ(ierr); 1737 ts->vec_sol = u; 1738 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1739 ierr = DMShellSetGlobalVector(dm,u);CHKERRQ(ierr); 1740 PetscFunctionReturn(0); 1741 } 1742 1743 #undef __FUNCT__ 1744 #define __FUNCT__ "TSSetPreStep" 1745 /*@C 1746 TSSetPreStep - Sets the general-purpose function 1747 called once at the beginning of each time step. 1748 1749 Logically Collective on TS 1750 1751 Input Parameters: 1752 + ts - The TS context obtained from TSCreate() 1753 - func - The function 1754 1755 Calling sequence of func: 1756 . func (TS ts); 1757 1758 Level: intermediate 1759 1760 Note: 1761 If a step is rejected, TSStep() will call this routine again before each attempt. 1762 The last completed time step number can be queried using TSGetTimeStepNumber(), the 1763 size of the step being attempted can be obtained using TSGetTimeStep(). 1764 1765 .keywords: TS, timestep 1766 .seealso: TSSetPreStage(), TSSetPostStep(), TSStep() 1767 @*/ 1768 PetscErrorCode TSSetPreStep(TS ts, PetscErrorCode (*func)(TS)) 1769 { 1770 PetscFunctionBegin; 1771 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 1772 ts->ops->prestep = func; 1773 PetscFunctionReturn(0); 1774 } 1775 1776 #undef __FUNCT__ 1777 #define __FUNCT__ "TSPreStep" 1778 /*@ 1779 TSPreStep - Runs the user-defined pre-step function. 1780 1781 Collective on TS 1782 1783 Input Parameters: 1784 . ts - The TS context obtained from TSCreate() 1785 1786 Notes: 1787 TSPreStep() is typically used within time stepping implementations, 1788 so most users would not generally call this routine themselves. 1789 1790 Level: developer 1791 1792 .keywords: TS, timestep 1793 .seealso: TSSetPreStep(), TSPreStage(), TSPostStep() 1794 @*/ 1795 PetscErrorCode TSPreStep(TS ts) 1796 { 1797 PetscErrorCode ierr; 1798 1799 PetscFunctionBegin; 1800 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1801 if (ts->ops->prestep) { 1802 PetscStackPush("TS PreStep function"); 1803 ierr = (*ts->ops->prestep)(ts);CHKERRQ(ierr); 1804 PetscStackPop; 1805 } 1806 PetscFunctionReturn(0); 1807 } 1808 1809 #undef __FUNCT__ 1810 #define __FUNCT__ "TSSetPreStage" 1811 /*@C 1812 TSSetPreStage - Sets the general-purpose function 1813 called once at the beginning of each stage. 1814 1815 Logically Collective on TS 1816 1817 Input Parameters: 1818 + ts - The TS context obtained from TSCreate() 1819 - func - The function 1820 1821 Calling sequence of func: 1822 . PetscErrorCode func(TS ts, PetscReal stagetime); 1823 1824 Level: intermediate 1825 1826 Note: 1827 There may be several stages per time step. If the solve for a given stage fails, the step may be rejected and retried. 1828 The time step number being computed can be queried using TSGetTimeStepNumber() and the total size of the step being 1829 attempted can be obtained using TSGetTimeStep(). The time at the start of the step is available via TSGetTime(). 1830 1831 .keywords: TS, timestep 1832 .seealso: TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext() 1833 @*/ 1834 PetscErrorCode TSSetPreStage(TS ts, PetscErrorCode (*func)(TS,PetscReal)) 1835 { 1836 PetscFunctionBegin; 1837 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 1838 ts->ops->prestage = func; 1839 PetscFunctionReturn(0); 1840 } 1841 1842 #undef __FUNCT__ 1843 #define __FUNCT__ "TSPreStage" 1844 /*@ 1845 TSPreStage - Runs the user-defined pre-stage function set using TSSetPreStage() 1846 1847 Collective on TS 1848 1849 Input Parameters: 1850 . ts - The TS context obtained from TSCreate() 1851 1852 Notes: 1853 TSPreStage() is typically used within time stepping implementations, 1854 most users would not generally call this routine themselves. 1855 1856 Level: developer 1857 1858 .keywords: TS, timestep 1859 .seealso: TSSetPreStep(), TSPreStep(), TSPostStep() 1860 @*/ 1861 PetscErrorCode TSPreStage(TS ts, PetscReal stagetime) 1862 { 1863 PetscErrorCode ierr; 1864 1865 PetscFunctionBegin; 1866 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1867 if (ts->ops->prestage) { 1868 PetscStackPush("TS PreStage function"); 1869 ierr = (*ts->ops->prestage)(ts,stagetime);CHKERRQ(ierr); 1870 PetscStackPop; 1871 } 1872 PetscFunctionReturn(0); 1873 } 1874 1875 #undef __FUNCT__ 1876 #define __FUNCT__ "TSSetPostStep" 1877 /*@C 1878 TSSetPostStep - Sets the general-purpose function 1879 called once at the end of each time step. 1880 1881 Logically Collective on TS 1882 1883 Input Parameters: 1884 + ts - The TS context obtained from TSCreate() 1885 - func - The function 1886 1887 Calling sequence of func: 1888 $ func (TS ts); 1889 1890 Level: intermediate 1891 1892 .keywords: TS, timestep 1893 .seealso: TSSetPreStep(), TSSetPreStage(), TSGetTimeStep(), TSGetTimeStepNumber(), TSGetTime() 1894 @*/ 1895 PetscErrorCode TSSetPostStep(TS ts, PetscErrorCode (*func)(TS)) 1896 { 1897 PetscFunctionBegin; 1898 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 1899 ts->ops->poststep = func; 1900 PetscFunctionReturn(0); 1901 } 1902 1903 #undef __FUNCT__ 1904 #define __FUNCT__ "TSPostStep" 1905 /*@ 1906 TSPostStep - Runs the user-defined post-step function. 1907 1908 Collective on TS 1909 1910 Input Parameters: 1911 . ts - The TS context obtained from TSCreate() 1912 1913 Notes: 1914 TSPostStep() is typically used within time stepping implementations, 1915 so most users would not generally call this routine themselves. 1916 1917 Level: developer 1918 1919 .keywords: TS, timestep 1920 @*/ 1921 PetscErrorCode TSPostStep(TS ts) 1922 { 1923 PetscErrorCode ierr; 1924 1925 PetscFunctionBegin; 1926 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1927 if (ts->ops->poststep) { 1928 PetscStackPush("TS PostStep function"); 1929 ierr = (*ts->ops->poststep)(ts);CHKERRQ(ierr); 1930 PetscStackPop; 1931 } 1932 PetscFunctionReturn(0); 1933 } 1934 1935 /* ------------ Routines to set performance monitoring options ----------- */ 1936 1937 #undef __FUNCT__ 1938 #define __FUNCT__ "TSMonitorSet" 1939 /*@C 1940 TSMonitorSet - Sets an ADDITIONAL function that is to be used at every 1941 timestep to display the iteration's progress. 1942 1943 Logically Collective on TS 1944 1945 Input Parameters: 1946 + ts - the TS context obtained from TSCreate() 1947 . monitor - monitoring routine 1948 . mctx - [optional] user-defined context for private data for the 1949 monitor routine (use PETSC_NULL if no context is desired) 1950 - monitordestroy - [optional] routine that frees monitor context 1951 (may be PETSC_NULL) 1952 1953 Calling sequence of monitor: 1954 $ int monitor(TS ts,PetscInt steps,PetscReal time,Vec u,void *mctx) 1955 1956 + ts - the TS context 1957 . steps - iteration number (after the final time step the monitor routine is called with a step of -1, this is at the final time which may have 1958 been interpolated to) 1959 . time - current time 1960 . u - current iterate 1961 - mctx - [optional] monitoring context 1962 1963 Notes: 1964 This routine adds an additional monitor to the list of monitors that 1965 already has been loaded. 1966 1967 Fortran notes: Only a single monitor function can be set for each TS object 1968 1969 Level: intermediate 1970 1971 .keywords: TS, timestep, set, monitor 1972 1973 .seealso: TSMonitorDefault(), TSMonitorCancel() 1974 @*/ 1975 PetscErrorCode TSMonitorSet(TS ts,PetscErrorCode (*monitor)(TS,PetscInt,PetscReal,Vec,void*),void *mctx,PetscErrorCode (*mdestroy)(void**)) 1976 { 1977 PetscFunctionBegin; 1978 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1979 if (ts->numbermonitors >= MAXTSMONITORS) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Too many monitors set"); 1980 ts->monitor[ts->numbermonitors] = monitor; 1981 ts->monitordestroy[ts->numbermonitors] = mdestroy; 1982 ts->monitorcontext[ts->numbermonitors++] = (void*)mctx; 1983 PetscFunctionReturn(0); 1984 } 1985 1986 #undef __FUNCT__ 1987 #define __FUNCT__ "TSMonitorCancel" 1988 /*@C 1989 TSMonitorCancel - Clears all the monitors that have been set on a time-step object. 1990 1991 Logically Collective on TS 1992 1993 Input Parameters: 1994 . ts - the TS context obtained from TSCreate() 1995 1996 Notes: 1997 There is no way to remove a single, specific monitor. 1998 1999 Level: intermediate 2000 2001 .keywords: TS, timestep, set, monitor 2002 2003 .seealso: TSMonitorDefault(), TSMonitorSet() 2004 @*/ 2005 PetscErrorCode TSMonitorCancel(TS ts) 2006 { 2007 PetscErrorCode ierr; 2008 PetscInt i; 2009 2010 PetscFunctionBegin; 2011 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2012 for (i=0; i<ts->numbermonitors; i++) { 2013 if (ts->monitordestroy[i]) { 2014 ierr = (*ts->monitordestroy[i])(&ts->monitorcontext[i]);CHKERRQ(ierr); 2015 } 2016 } 2017 ts->numbermonitors = 0; 2018 PetscFunctionReturn(0); 2019 } 2020 2021 #undef __FUNCT__ 2022 #define __FUNCT__ "TSMonitorDefault" 2023 /*@ 2024 TSMonitorDefault - Sets the Default monitor 2025 2026 Level: intermediate 2027 2028 .keywords: TS, set, monitor 2029 2030 .seealso: TSMonitorDefault(), TSMonitorSet() 2031 @*/ 2032 PetscErrorCode TSMonitorDefault(TS ts,PetscInt step,PetscReal ptime,Vec v,void *dummy) 2033 { 2034 PetscErrorCode ierr; 2035 PetscViewer viewer = dummy ? (PetscViewer) dummy : PETSC_VIEWER_STDOUT_(((PetscObject)ts)->comm); 2036 2037 PetscFunctionBegin; 2038 ierr = PetscViewerASCIIAddTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 2039 ierr = PetscViewerASCIIPrintf(viewer,"%D TS dt %g time %g\n",step,(double)ts->time_step,(double)ptime);CHKERRQ(ierr); 2040 ierr = PetscViewerASCIISubtractTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 2041 PetscFunctionReturn(0); 2042 } 2043 2044 #undef __FUNCT__ 2045 #define __FUNCT__ "TSSetRetainStages" 2046 /*@ 2047 TSSetRetainStages - Request that all stages in the upcoming step be stored so that interpolation will be available. 2048 2049 Logically Collective on TS 2050 2051 Input Argument: 2052 . ts - time stepping context 2053 2054 Output Argument: 2055 . flg - PETSC_TRUE or PETSC_FALSE 2056 2057 Level: intermediate 2058 2059 .keywords: TS, set 2060 2061 .seealso: TSInterpolate(), TSSetPostStep() 2062 @*/ 2063 PetscErrorCode TSSetRetainStages(TS ts,PetscBool flg) 2064 { 2065 PetscFunctionBegin; 2066 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2067 ts->retain_stages = flg; 2068 PetscFunctionReturn(0); 2069 } 2070 2071 #undef __FUNCT__ 2072 #define __FUNCT__ "TSInterpolate" 2073 /*@ 2074 TSInterpolate - Interpolate the solution computed during the previous step to an arbitrary location in the interval 2075 2076 Collective on TS 2077 2078 Input Argument: 2079 + ts - time stepping context 2080 - t - time to interpolate to 2081 2082 Output Argument: 2083 . U - state at given time 2084 2085 Notes: 2086 The user should call TSSetRetainStages() before taking a step in which interpolation will be requested. 2087 2088 Level: intermediate 2089 2090 Developer Notes: 2091 TSInterpolate() and the storing of previous steps/stages should be generalized to support delay differential equations and continuous adjoints. 2092 2093 .keywords: TS, set 2094 2095 .seealso: TSSetRetainStages(), TSSetPostStep() 2096 @*/ 2097 PetscErrorCode TSInterpolate(TS ts,PetscReal t,Vec U) 2098 { 2099 PetscErrorCode ierr; 2100 2101 PetscFunctionBegin; 2102 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2103 if (t < ts->ptime - ts->time_step_prev || t > ts->ptime) SETERRQ3(((PetscObject)ts)->comm,PETSC_ERR_ARG_OUTOFRANGE,"Requested time %G not in last time steps [%G,%G]",t,ts->ptime-ts->time_step_prev,ts->ptime); 2104 if (!ts->ops->interpolate) SETERRQ1(((PetscObject)ts)->comm,PETSC_ERR_SUP,"%s does not provide interpolation",((PetscObject)ts)->type_name); 2105 ierr = (*ts->ops->interpolate)(ts,t,U);CHKERRQ(ierr); 2106 PetscFunctionReturn(0); 2107 } 2108 2109 #undef __FUNCT__ 2110 #define __FUNCT__ "TSStep" 2111 /*@ 2112 TSStep - Steps one time step 2113 2114 Collective on TS 2115 2116 Input Parameter: 2117 . ts - the TS context obtained from TSCreate() 2118 2119 Level: intermediate 2120 2121 Notes: 2122 The hook set using TSSetPreStep() is called before each attempt to take the step. In general, the time step size may 2123 be changed due to adaptive error controller or solve failures. Note that steps may contain multiple stages. 2124 2125 .keywords: TS, timestep, solve 2126 2127 .seealso: TSCreate(), TSSetUp(), TSDestroy(), TSSolve(), TSSetPreStep(), TSSetPreStage() 2128 @*/ 2129 PetscErrorCode TSStep(TS ts) 2130 { 2131 PetscReal ptime_prev; 2132 PetscErrorCode ierr; 2133 2134 PetscFunctionBegin; 2135 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 2136 ierr = TSSetUp(ts);CHKERRQ(ierr); 2137 2138 ts->reason = TS_CONVERGED_ITERATING; 2139 2140 ptime_prev = ts->ptime; 2141 ierr = PetscLogEventBegin(TS_Step,ts,0,0,0);CHKERRQ(ierr); 2142 ierr = (*ts->ops->step)(ts);CHKERRQ(ierr); 2143 ierr = PetscLogEventEnd(TS_Step,ts,0,0,0);CHKERRQ(ierr); 2144 ts->time_step_prev = ts->ptime - ptime_prev; 2145 2146 if (ts->reason < 0) { 2147 if (ts->errorifstepfailed) { 2148 if (ts->reason == TS_DIVERGED_NONLINEAR_SOLVE) { 2149 SETERRQ1(((PetscObject)ts)->comm,PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s, increase -ts_max_snes_failures or make negative to attempt recovery",TSConvergedReasons[ts->reason]); 2150 } else SETERRQ1(((PetscObject)ts)->comm,PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s",TSConvergedReasons[ts->reason]); 2151 } 2152 } else if (!ts->reason) { 2153 if (ts->steps >= ts->max_steps) 2154 ts->reason = TS_CONVERGED_ITS; 2155 else if (ts->ptime >= ts->max_time) 2156 ts->reason = TS_CONVERGED_TIME; 2157 } 2158 2159 PetscFunctionReturn(0); 2160 } 2161 2162 #undef __FUNCT__ 2163 #define __FUNCT__ "TSEvaluateStep" 2164 /*@ 2165 TSEvaluateStep - Evaluate the solution at the end of a time step with a given order of accuracy. 2166 2167 Collective on TS 2168 2169 Input Arguments: 2170 + ts - time stepping context 2171 . order - desired order of accuracy 2172 - done - whether the step was evaluated at this order (pass PETSC_NULL to generate an error if not available) 2173 2174 Output Arguments: 2175 . U - state at the end of the current step 2176 2177 Level: advanced 2178 2179 Notes: 2180 This function cannot be called until all stages have been evaluated. 2181 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. 2182 2183 .seealso: TSStep(), TSAdapt 2184 @*/ 2185 PetscErrorCode TSEvaluateStep(TS ts,PetscInt order,Vec U,PetscBool *done) 2186 { 2187 PetscErrorCode ierr; 2188 2189 PetscFunctionBegin; 2190 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2191 PetscValidType(ts,1); 2192 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 2193 if (!ts->ops->evaluatestep) SETERRQ1(((PetscObject)ts)->comm,PETSC_ERR_SUP,"TSEvaluateStep not implemented for type '%s'",((PetscObject)ts)->type_name); 2194 ierr = (*ts->ops->evaluatestep)(ts,order,U,done);CHKERRQ(ierr); 2195 PetscFunctionReturn(0); 2196 } 2197 2198 #undef __FUNCT__ 2199 #define __FUNCT__ "TSSolve" 2200 /*@ 2201 TSSolve - Steps the requested number of timesteps. 2202 2203 Collective on TS 2204 2205 Input Parameter: 2206 + ts - the TS context obtained from TSCreate() 2207 - u - the solution vector 2208 2209 Output Parameter: 2210 . ftime - time of the state vector u upon completion 2211 2212 Level: beginner 2213 2214 Notes: 2215 The final time returned by this function may be different from the time of the internally 2216 held state accessible by TSGetSolution() and TSGetTime() because the method may have 2217 stepped over the final time. 2218 2219 .keywords: TS, timestep, solve 2220 2221 .seealso: TSCreate(), TSSetSolution(), TSStep() 2222 @*/ 2223 PetscErrorCode TSSolve(TS ts,Vec u,PetscReal *ftime) 2224 { 2225 PetscBool flg; 2226 char filename[PETSC_MAX_PATH_LEN]; 2227 PetscViewer viewer; 2228 PetscErrorCode ierr; 2229 2230 PetscFunctionBegin; 2231 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2232 PetscValidHeaderSpecific(u,VEC_CLASSID,2); 2233 if (ts->exact_final_time) { /* Need ts->vec_sol to be distinct so it is not overwritten when we interpolate at the end */ 2234 if (!ts->vec_sol || u == ts->vec_sol) { 2235 Vec y; 2236 ierr = VecDuplicate(u,&y);CHKERRQ(ierr); 2237 ierr = TSSetSolution(ts,y);CHKERRQ(ierr); 2238 ierr = VecDestroy(&y);CHKERRQ(ierr); /* grant ownership */ 2239 } 2240 ierr = VecCopy(u,ts->vec_sol);CHKERRQ(ierr); 2241 } else { 2242 ierr = TSSetSolution(ts,u);CHKERRQ(ierr); 2243 } 2244 ierr = TSSetUp(ts);CHKERRQ(ierr); 2245 /* reset time step and iteration counters */ 2246 ts->steps = 0; 2247 ts->ksp_its = 0; 2248 ts->snes_its = 0; 2249 ts->num_snes_failures = 0; 2250 ts->reject = 0; 2251 ts->reason = TS_CONVERGED_ITERATING; 2252 2253 if (ts->ops->solve) { /* This private interface is transitional and should be removed when all implementations are updated. */ 2254 ierr = (*ts->ops->solve)(ts);CHKERRQ(ierr); 2255 ierr = VecCopy(ts->vec_sol,u);CHKERRQ(ierr); 2256 if (ftime) *ftime = ts->ptime; 2257 } else { 2258 /* steps the requested number of timesteps. */ 2259 ierr = TSMonitor(ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 2260 if (ts->steps >= ts->max_steps) 2261 ts->reason = TS_CONVERGED_ITS; 2262 else if (ts->ptime >= ts->max_time) 2263 ts->reason = TS_CONVERGED_TIME; 2264 while (!ts->reason) { 2265 ierr = TSStep(ts);CHKERRQ(ierr); 2266 ierr = TSPostStep(ts);CHKERRQ(ierr); 2267 ierr = TSMonitor(ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 2268 } 2269 if (ts->exact_final_time && ts->ptime > ts->max_time) { 2270 ierr = TSInterpolate(ts,ts->max_time,u);CHKERRQ(ierr); 2271 if (ftime) *ftime = ts->max_time; 2272 } else { 2273 ierr = VecCopy(ts->vec_sol,u);CHKERRQ(ierr); 2274 if (ftime) *ftime = ts->ptime; 2275 } 2276 } 2277 ierr = TSMonitor(ts,-1,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 2278 ierr = PetscOptionsGetString(((PetscObject)ts)->prefix,"-ts_view",filename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr); 2279 if (flg && !PetscPreLoadingOn) { 2280 ierr = PetscViewerASCIIOpen(((PetscObject)ts)->comm,filename,&viewer);CHKERRQ(ierr); 2281 ierr = TSView(ts,viewer);CHKERRQ(ierr); 2282 ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr); 2283 } 2284 PetscFunctionReturn(0); 2285 } 2286 2287 #undef __FUNCT__ 2288 #define __FUNCT__ "TSMonitor" 2289 /*@ 2290 TSMonitor - Runs all user-provided monitor routines set using TSMonitorSet() 2291 2292 Collective on TS 2293 2294 Input Parameters: 2295 + ts - time stepping context obtained from TSCreate() 2296 . step - step number that has just completed 2297 . ptime - model time of the state 2298 - u - state at the current model time 2299 2300 Notes: 2301 TSMonitor() is typically used within the time stepping implementations. 2302 Users might call this function when using the TSStep() interface instead of TSSolve(). 2303 2304 Level: advanced 2305 2306 .keywords: TS, timestep 2307 @*/ 2308 PetscErrorCode TSMonitor(TS ts,PetscInt step,PetscReal ptime,Vec u) 2309 { 2310 PetscErrorCode ierr; 2311 PetscInt i,n = ts->numbermonitors; 2312 2313 PetscFunctionBegin; 2314 for (i=0; i<n; i++) { 2315 ierr = (*ts->monitor[i])(ts,step,ptime,u,ts->monitorcontext[i]);CHKERRQ(ierr); 2316 } 2317 PetscFunctionReturn(0); 2318 } 2319 2320 /* ------------------------------------------------------------------------*/ 2321 struct _n_TSMonitorLGCtx { 2322 PetscDrawLG lg; 2323 PetscInt howoften; /* when > 0 uses step % howoften, when negative only final solution plotted */ 2324 PetscInt ksp_its,snes_its; 2325 }; 2326 2327 2328 #undef __FUNCT__ 2329 #define __FUNCT__ "TSMonitorLGCtxCreate" 2330 /*@C 2331 TSMonitorLGCtxCreate - Creates a line graph context for use with 2332 TS to monitor the solution process graphically in various ways 2333 2334 Collective on TS 2335 2336 Input Parameters: 2337 + host - the X display to open, or null for the local machine 2338 . label - the title to put in the title bar 2339 . x, y - the screen coordinates of the upper left coordinate of the window 2340 . m, n - the screen width and height in pixels 2341 - howoften - if positive then determines the frequency of the plotting, if -1 then only at the final time 2342 2343 Output Parameter: 2344 . ctx - the context 2345 2346 Options Database Key: 2347 + -ts_monitor_lg_timestep - automatically sets line graph monitor 2348 . -ts_monitor_lg_solution - 2349 . -ts_monitor_lg_error - 2350 . -ts_monitor_lg_ksp_iterations - 2351 . -ts_monitor_lg_snes_iterations - 2352 - -lg_indicate_data_points <true,false> - indicate the data points (at each time step) on the plot; default is true 2353 2354 Notes: 2355 Use TSMonitorLGCtxDestroy() to destroy. 2356 2357 Level: intermediate 2358 2359 .keywords: TS, monitor, line graph, residual, seealso 2360 2361 .seealso: TSMonitorLGTimeStep(), TSMonitorSet(), TSMonitorLGSolution(), TSMonitorLGError() 2362 2363 @*/ 2364 PetscErrorCode TSMonitorLGCtxCreate(MPI_Comm comm,const char host[],const char label[],int x,int y,int m,int n,PetscInt howoften,TSMonitorLGCtx *ctx) 2365 { 2366 PetscDraw win; 2367 PetscErrorCode ierr; 2368 PetscBool flg = PETSC_TRUE; 2369 2370 PetscFunctionBegin; 2371 ierr = PetscNew(struct _n_TSMonitorLGCtx,ctx);CHKERRQ(ierr); 2372 ierr = PetscDrawCreate(comm,host,label,x,y,m,n,&win);CHKERRQ(ierr); 2373 ierr = PetscDrawSetFromOptions(win);CHKERRQ(ierr); 2374 ierr = PetscDrawLGCreate(win,1,&(*ctx)->lg);CHKERRQ(ierr); 2375 ierr = PetscOptionsGetBool(PETSC_NULL,"-lg_indicate_data_points",&flg,PETSC_NULL);CHKERRQ(ierr); 2376 if (flg) { 2377 ierr = PetscDrawLGIndicateDataPoints((*ctx)->lg);CHKERRQ(ierr); 2378 } 2379 ierr = PetscLogObjectParent((*ctx)->lg,win);CHKERRQ(ierr); 2380 (*ctx)->howoften = howoften; 2381 PetscFunctionReturn(0); 2382 } 2383 2384 #undef __FUNCT__ 2385 #define __FUNCT__ "TSMonitorLGTimeStep" 2386 PetscErrorCode TSMonitorLGTimeStep(TS ts,PetscInt n,PetscReal ptime,Vec v,void *monctx) 2387 { 2388 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 2389 PetscReal x = ptime,y; 2390 PetscErrorCode ierr; 2391 2392 PetscFunctionBegin; 2393 if (!n) { 2394 PetscDrawAxis axis; 2395 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 2396 ierr = PetscDrawAxisSetLabels(axis,"Timestep as function of time","Time","Time step");CHKERRQ(ierr); 2397 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 2398 } 2399 ierr = TSGetTimeStep(ts,&y);CHKERRQ(ierr); 2400 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 2401 if (((ctx->howoften > 0) && (!(n % ctx->howoften))) || ((ctx->howoften == -1) && (n == -1))){ 2402 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 2403 } 2404 PetscFunctionReturn(0); 2405 } 2406 2407 #undef __FUNCT__ 2408 #define __FUNCT__ "TSMonitorLGCtxDestroy" 2409 /*@C 2410 TSMonitorLGCtxDestroy - Destroys a line graph context that was created 2411 with TSMonitorLGCtxCreate(). 2412 2413 Collective on TSMonitorLGCtx 2414 2415 Input Parameter: 2416 . ctx - the monitor context 2417 2418 Level: intermediate 2419 2420 .keywords: TS, monitor, line graph, destroy 2421 2422 .seealso: TSMonitorLGCtxCreate(), TSMonitorSet(), TSMonitorLGTimeStep(); 2423 @*/ 2424 PetscErrorCode TSMonitorLGCtxDestroy(TSMonitorLGCtx *ctx) 2425 { 2426 PetscDraw draw; 2427 PetscErrorCode ierr; 2428 2429 PetscFunctionBegin; 2430 ierr = PetscDrawLGGetDraw((*ctx)->lg,&draw);CHKERRQ(ierr); 2431 ierr = PetscDrawDestroy(&draw);CHKERRQ(ierr); 2432 ierr = PetscDrawLGDestroy(&(*ctx)->lg);CHKERRQ(ierr); 2433 ierr = PetscFree(*ctx);CHKERRQ(ierr); 2434 PetscFunctionReturn(0); 2435 } 2436 2437 #undef __FUNCT__ 2438 #define __FUNCT__ "TSGetTime" 2439 /*@ 2440 TSGetTime - Gets the time of the most recently completed step. 2441 2442 Not Collective 2443 2444 Input Parameter: 2445 . ts - the TS context obtained from TSCreate() 2446 2447 Output Parameter: 2448 . t - the current time 2449 2450 Level: beginner 2451 2452 Note: 2453 When called during time step evaluation (e.g. during residual evaluation or via hooks set using TSSetPreStep(), 2454 TSSetPreStage(), or TSSetPostStep()), the time is the time at the start of the step being evaluated. 2455 2456 .seealso: TSSetInitialTimeStep(), TSGetTimeStep() 2457 2458 .keywords: TS, get, time 2459 @*/ 2460 PetscErrorCode TSGetTime(TS ts,PetscReal* t) 2461 { 2462 PetscFunctionBegin; 2463 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2464 PetscValidRealPointer(t,2); 2465 *t = ts->ptime; 2466 PetscFunctionReturn(0); 2467 } 2468 2469 #undef __FUNCT__ 2470 #define __FUNCT__ "TSSetTime" 2471 /*@ 2472 TSSetTime - Allows one to reset the time. 2473 2474 Logically Collective on TS 2475 2476 Input Parameters: 2477 + ts - the TS context obtained from TSCreate() 2478 - time - the time 2479 2480 Level: intermediate 2481 2482 .seealso: TSGetTime(), TSSetDuration() 2483 2484 .keywords: TS, set, time 2485 @*/ 2486 PetscErrorCode TSSetTime(TS ts, PetscReal t) 2487 { 2488 PetscFunctionBegin; 2489 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2490 PetscValidLogicalCollectiveReal(ts,t,2); 2491 ts->ptime = t; 2492 PetscFunctionReturn(0); 2493 } 2494 2495 #undef __FUNCT__ 2496 #define __FUNCT__ "TSSetOptionsPrefix" 2497 /*@C 2498 TSSetOptionsPrefix - Sets the prefix used for searching for all 2499 TS options in the database. 2500 2501 Logically Collective on TS 2502 2503 Input Parameter: 2504 + ts - The TS context 2505 - prefix - The prefix to prepend to all option names 2506 2507 Notes: 2508 A hyphen (-) must NOT be given at the beginning of the prefix name. 2509 The first character of all runtime options is AUTOMATICALLY the 2510 hyphen. 2511 2512 Level: advanced 2513 2514 .keywords: TS, set, options, prefix, database 2515 2516 .seealso: TSSetFromOptions() 2517 2518 @*/ 2519 PetscErrorCode TSSetOptionsPrefix(TS ts,const char prefix[]) 2520 { 2521 PetscErrorCode ierr; 2522 SNES snes; 2523 2524 PetscFunctionBegin; 2525 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2526 ierr = PetscObjectSetOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 2527 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 2528 ierr = SNESSetOptionsPrefix(snes,prefix);CHKERRQ(ierr); 2529 PetscFunctionReturn(0); 2530 } 2531 2532 2533 #undef __FUNCT__ 2534 #define __FUNCT__ "TSAppendOptionsPrefix" 2535 /*@C 2536 TSAppendOptionsPrefix - Appends to the prefix used for searching for all 2537 TS options in the database. 2538 2539 Logically Collective on TS 2540 2541 Input Parameter: 2542 + ts - The TS context 2543 - prefix - The prefix to prepend to all option names 2544 2545 Notes: 2546 A hyphen (-) must NOT be given at the beginning of the prefix name. 2547 The first character of all runtime options is AUTOMATICALLY the 2548 hyphen. 2549 2550 Level: advanced 2551 2552 .keywords: TS, append, options, prefix, database 2553 2554 .seealso: TSGetOptionsPrefix() 2555 2556 @*/ 2557 PetscErrorCode TSAppendOptionsPrefix(TS ts,const char prefix[]) 2558 { 2559 PetscErrorCode ierr; 2560 SNES snes; 2561 2562 PetscFunctionBegin; 2563 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2564 ierr = PetscObjectAppendOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 2565 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 2566 ierr = SNESAppendOptionsPrefix(snes,prefix);CHKERRQ(ierr); 2567 PetscFunctionReturn(0); 2568 } 2569 2570 #undef __FUNCT__ 2571 #define __FUNCT__ "TSGetOptionsPrefix" 2572 /*@C 2573 TSGetOptionsPrefix - Sets the prefix used for searching for all 2574 TS options in the database. 2575 2576 Not Collective 2577 2578 Input Parameter: 2579 . ts - The TS context 2580 2581 Output Parameter: 2582 . prefix - A pointer to the prefix string used 2583 2584 Notes: On the fortran side, the user should pass in a string 'prifix' of 2585 sufficient length to hold the prefix. 2586 2587 Level: intermediate 2588 2589 .keywords: TS, get, options, prefix, database 2590 2591 .seealso: TSAppendOptionsPrefix() 2592 @*/ 2593 PetscErrorCode TSGetOptionsPrefix(TS ts,const char *prefix[]) 2594 { 2595 PetscErrorCode ierr; 2596 2597 PetscFunctionBegin; 2598 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2599 PetscValidPointer(prefix,2); 2600 ierr = PetscObjectGetOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 2601 PetscFunctionReturn(0); 2602 } 2603 2604 #undef __FUNCT__ 2605 #define __FUNCT__ "TSGetRHSJacobian" 2606 /*@C 2607 TSGetRHSJacobian - Returns the Jacobian J at the present timestep. 2608 2609 Not Collective, but parallel objects are returned if TS is parallel 2610 2611 Input Parameter: 2612 . ts - The TS context obtained from TSCreate() 2613 2614 Output Parameters: 2615 + J - The Jacobian J of F, where U_t = G(U,t) 2616 . M - The preconditioner matrix, usually the same as J 2617 . func - Function to compute the Jacobian of the RHS 2618 - ctx - User-defined context for Jacobian evaluation routine 2619 2620 Notes: You can pass in PETSC_NULL for any return argument you do not need. 2621 2622 Level: intermediate 2623 2624 .seealso: TSGetTimeStep(), TSGetMatrices(), TSGetTime(), TSGetTimeStepNumber() 2625 2626 .keywords: TS, timestep, get, matrix, Jacobian 2627 @*/ 2628 PetscErrorCode TSGetRHSJacobian(TS ts,Mat *J,Mat *M,TSRHSJacobian *func,void **ctx) 2629 { 2630 PetscErrorCode ierr; 2631 SNES snes; 2632 DM dm; 2633 2634 PetscFunctionBegin; 2635 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 2636 ierr = SNESGetJacobian(snes,J,M,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); 2637 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 2638 ierr = DMTSGetRHSJacobian(dm,func,ctx);CHKERRQ(ierr); 2639 PetscFunctionReturn(0); 2640 } 2641 2642 #undef __FUNCT__ 2643 #define __FUNCT__ "TSGetIJacobian" 2644 /*@C 2645 TSGetIJacobian - Returns the implicit Jacobian at the present timestep. 2646 2647 Not Collective, but parallel objects are returned if TS is parallel 2648 2649 Input Parameter: 2650 . ts - The TS context obtained from TSCreate() 2651 2652 Output Parameters: 2653 + A - The Jacobian of F(t,U,U_t) 2654 . B - The preconditioner matrix, often the same as A 2655 . f - The function to compute the matrices 2656 - ctx - User-defined context for Jacobian evaluation routine 2657 2658 Notes: You can pass in PETSC_NULL for any return argument you do not need. 2659 2660 Level: advanced 2661 2662 .seealso: TSGetTimeStep(), TSGetRHSJacobian(), TSGetMatrices(), TSGetTime(), TSGetTimeStepNumber() 2663 2664 .keywords: TS, timestep, get, matrix, Jacobian 2665 @*/ 2666 PetscErrorCode TSGetIJacobian(TS ts,Mat *A,Mat *B,TSIJacobian *f,void **ctx) 2667 { 2668 PetscErrorCode ierr; 2669 SNES snes; 2670 DM dm; 2671 2672 PetscFunctionBegin; 2673 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 2674 ierr = SNESGetJacobian(snes,A,B,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); 2675 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 2676 ierr = DMTSGetIJacobian(dm,f,ctx);CHKERRQ(ierr); 2677 PetscFunctionReturn(0); 2678 } 2679 2680 struct _n_TSMonitorDrawCtx { 2681 PetscViewer viewer; 2682 Vec initialsolution; 2683 PetscBool showinitial; 2684 PetscInt howoften; /* when > 0 uses step % howoften, when negative only final solution plotted */ 2685 }; 2686 2687 #undef __FUNCT__ 2688 #define __FUNCT__ "TSMonitorDrawSolution" 2689 /*@C 2690 TSMonitorDrawSolution - Monitors progress of the TS solvers by calling 2691 VecView() for the solution at each timestep 2692 2693 Collective on TS 2694 2695 Input Parameters: 2696 + ts - the TS context 2697 . step - current time-step 2698 . ptime - current time 2699 - dummy - either a viewer or PETSC_NULL 2700 2701 Options Database: 2702 . -ts_monitor_draw_solution_initial - show initial solution as well as current solution 2703 2704 Notes: the initial solution and current solution are not displayed with a common axis scaling so generally the option -ts_monitor_draw_solution_initial 2705 will look bad 2706 2707 Level: intermediate 2708 2709 .keywords: TS, vector, monitor, view 2710 2711 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 2712 @*/ 2713 PetscErrorCode TSMonitorDrawSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 2714 { 2715 PetscErrorCode ierr; 2716 TSMonitorDrawCtx ictx = (TSMonitorDrawCtx)dummy; 2717 2718 PetscFunctionBegin; 2719 if (!step && ictx->showinitial) { 2720 if (!ictx->initialsolution) { 2721 ierr = VecDuplicate(u,&ictx->initialsolution);CHKERRQ(ierr); 2722 } 2723 ierr = VecCopy(u,ictx->initialsolution);CHKERRQ(ierr); 2724 } 2725 if (!(((ictx->howoften > 0) && (!(step % ictx->howoften)) && (step > -1)) || ((ictx->howoften == -1) && (step == -1)))) PetscFunctionReturn(0); 2726 2727 if (ictx->showinitial) { 2728 PetscReal pause; 2729 ierr = PetscViewerDrawGetPause(ictx->viewer,&pause);CHKERRQ(ierr); 2730 ierr = PetscViewerDrawSetPause(ictx->viewer,0.0);CHKERRQ(ierr); 2731 ierr = VecView(ictx->initialsolution,ictx->viewer);CHKERRQ(ierr); 2732 ierr = PetscViewerDrawSetPause(ictx->viewer,pause);CHKERRQ(ierr); 2733 ierr = PetscViewerDrawSetHold(ictx->viewer,PETSC_TRUE);CHKERRQ(ierr); 2734 } 2735 ierr = VecView(u,ictx->viewer);CHKERRQ(ierr); 2736 if (ictx->showinitial) { 2737 ierr = PetscViewerDrawSetHold(ictx->viewer,PETSC_FALSE);CHKERRQ(ierr); 2738 } 2739 PetscFunctionReturn(0); 2740 } 2741 2742 2743 #undef __FUNCT__ 2744 #define __FUNCT__ "TSMonitorDrawCtxDestroy" 2745 /*@C 2746 TSMonitorDrawCtxDestroy - Destroys the monitor context for TSMonitorDrawSolution() 2747 2748 Collective on TS 2749 2750 Input Parameters: 2751 . ctx - the monitor context 2752 2753 Level: intermediate 2754 2755 .keywords: TS, vector, monitor, view 2756 2757 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorDrawSolution(), TSMonitorDrawError() 2758 @*/ 2759 PetscErrorCode TSMonitorDrawCtxDestroy(TSMonitorDrawCtx *ictx) 2760 { 2761 PetscErrorCode ierr; 2762 2763 PetscFunctionBegin; 2764 ierr = PetscViewerDestroy(&(*ictx)->viewer);CHKERRQ(ierr); 2765 ierr = VecDestroy(&(*ictx)->initialsolution);CHKERRQ(ierr); 2766 ierr = PetscFree(*ictx);CHKERRQ(ierr); 2767 PetscFunctionReturn(0); 2768 } 2769 2770 #undef __FUNCT__ 2771 #define __FUNCT__ "TSMonitorDrawCtxCreate" 2772 /*@C 2773 TSMonitorDrawCtxCreate - Creates the monitor context for TSMonitorDrawCtx 2774 2775 Collective on TS 2776 2777 Input Parameter: 2778 . ts - time-step context 2779 2780 Output Patameter: 2781 . ctx - the monitor context 2782 2783 Options Database: 2784 . -ts_monitor_draw_solution_initial - show initial solution as well as current solution 2785 2786 Level: intermediate 2787 2788 .keywords: TS, vector, monitor, view 2789 2790 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorDrawCtx() 2791 @*/ 2792 PetscErrorCode TSMonitorDrawCtxCreate(MPI_Comm comm,const char host[],const char label[],int x,int y,int m,int n,PetscInt howoften,TSMonitorDrawCtx *ctx) 2793 { 2794 PetscErrorCode ierr; 2795 2796 PetscFunctionBegin; 2797 ierr = PetscNew(struct _n_TSMonitorDrawCtx,ctx);CHKERRQ(ierr); 2798 ierr = PetscViewerDrawOpen(comm,host,label,x,y,m,n,&(*ctx)->viewer);CHKERRQ(ierr); 2799 (*ctx)->showinitial = PETSC_FALSE; 2800 (*ctx)->howoften = howoften; 2801 ierr = PetscOptionsGetBool(PETSC_NULL,"-ts_monitor_draw_solution_initial",&(*ctx)->showinitial,PETSC_NULL);CHKERRQ(ierr); 2802 PetscFunctionReturn(0); 2803 } 2804 2805 #undef __FUNCT__ 2806 #define __FUNCT__ "TSMonitorDrawError" 2807 /*@C 2808 TSMonitorDrawError - Monitors progress of the TS solvers by calling 2809 VecView() for the error at each timestep 2810 2811 Collective on TS 2812 2813 Input Parameters: 2814 + ts - the TS context 2815 . step - current time-step 2816 . ptime - current time 2817 - dummy - either a viewer or PETSC_NULL 2818 2819 Level: intermediate 2820 2821 .keywords: TS, vector, monitor, view 2822 2823 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 2824 @*/ 2825 PetscErrorCode TSMonitorDrawError(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 2826 { 2827 PetscErrorCode ierr; 2828 TSMonitorDrawCtx ctx = (TSMonitorDrawCtx)dummy; 2829 PetscViewer viewer = ctx->viewer; 2830 Vec work; 2831 2832 PetscFunctionBegin; 2833 if (!(((ctx->howoften > 0) && (!(step % ctx->howoften)) && (step > -1)) || ((ctx->howoften == -1) && (step == -1)))) PetscFunctionReturn(0); 2834 ierr = VecDuplicate(u,&work);CHKERRQ(ierr); 2835 ierr = TSComputeSolutionFunction(ts,ptime,work);CHKERRQ(ierr); 2836 ierr = VecAXPY(work,-1.0,u);CHKERRQ(ierr); 2837 ierr = VecView(work,viewer);CHKERRQ(ierr); 2838 ierr = VecDestroy(&work);CHKERRQ(ierr); 2839 PetscFunctionReturn(0); 2840 } 2841 2842 #undef __FUNCT__ 2843 #define __FUNCT__ "TSSetDM" 2844 /*@ 2845 TSSetDM - Sets the DM that may be used by some preconditioners 2846 2847 Logically Collective on TS and DM 2848 2849 Input Parameters: 2850 + ts - the preconditioner context 2851 - dm - the dm 2852 2853 Level: intermediate 2854 2855 2856 .seealso: TSGetDM(), SNESSetDM(), SNESGetDM() 2857 @*/ 2858 PetscErrorCode TSSetDM(TS ts,DM dm) 2859 { 2860 PetscErrorCode ierr; 2861 SNES snes; 2862 TSDM tsdm; 2863 2864 PetscFunctionBegin; 2865 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2866 ierr = PetscObjectReference((PetscObject)dm);CHKERRQ(ierr); 2867 if (ts->dm) { /* Move the TSDM context over to the new DM unless the new DM already has one */ 2868 PetscContainer oldcontainer,container; 2869 ierr = PetscObjectQuery((PetscObject)ts->dm,"TSDM",(PetscObject*)&oldcontainer);CHKERRQ(ierr); 2870 ierr = PetscObjectQuery((PetscObject)dm,"TSDM",(PetscObject*)&container);CHKERRQ(ierr); 2871 if (oldcontainer && !container) { 2872 ierr = DMTSCopyContext(ts->dm,dm);CHKERRQ(ierr); 2873 ierr = DMTSGetContext(ts->dm,&tsdm);CHKERRQ(ierr); 2874 if (tsdm->originaldm == ts->dm) { /* Grant write privileges to the replacement DM */ 2875 tsdm->originaldm = dm; 2876 } 2877 } 2878 ierr = DMDestroy(&ts->dm);CHKERRQ(ierr); 2879 } 2880 ts->dm = dm; 2881 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 2882 ierr = SNESSetDM(snes,dm);CHKERRQ(ierr); 2883 PetscFunctionReturn(0); 2884 } 2885 2886 #undef __FUNCT__ 2887 #define __FUNCT__ "TSGetDM" 2888 /*@ 2889 TSGetDM - Gets the DM that may be used by some preconditioners 2890 2891 Not Collective 2892 2893 Input Parameter: 2894 . ts - the preconditioner context 2895 2896 Output Parameter: 2897 . dm - the dm 2898 2899 Level: intermediate 2900 2901 2902 .seealso: TSSetDM(), SNESSetDM(), SNESGetDM() 2903 @*/ 2904 PetscErrorCode TSGetDM(TS ts,DM *dm) 2905 { 2906 PetscErrorCode ierr; 2907 2908 PetscFunctionBegin; 2909 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2910 if (!ts->dm) { 2911 ierr = DMShellCreate(((PetscObject)ts)->comm,&ts->dm);CHKERRQ(ierr); 2912 if (ts->snes) {ierr = SNESSetDM(ts->snes,ts->dm);CHKERRQ(ierr);} 2913 } 2914 *dm = ts->dm; 2915 PetscFunctionReturn(0); 2916 } 2917 2918 #undef __FUNCT__ 2919 #define __FUNCT__ "SNESTSFormFunction" 2920 /*@ 2921 SNESTSFormFunction - Function to evaluate nonlinear residual 2922 2923 Logically Collective on SNES 2924 2925 Input Parameter: 2926 + snes - nonlinear solver 2927 . U - the current state at which to evaluate the residual 2928 - ctx - user context, must be a TS 2929 2930 Output Parameter: 2931 . F - the nonlinear residual 2932 2933 Notes: 2934 This function is not normally called by users and is automatically registered with the SNES used by TS. 2935 It is most frequently passed to MatFDColoringSetFunction(). 2936 2937 Level: advanced 2938 2939 .seealso: SNESSetFunction(), MatFDColoringSetFunction() 2940 @*/ 2941 PetscErrorCode SNESTSFormFunction(SNES snes,Vec U,Vec F,void *ctx) 2942 { 2943 TS ts = (TS)ctx; 2944 PetscErrorCode ierr; 2945 2946 PetscFunctionBegin; 2947 PetscValidHeaderSpecific(snes,SNES_CLASSID,1); 2948 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 2949 PetscValidHeaderSpecific(F,VEC_CLASSID,3); 2950 PetscValidHeaderSpecific(ts,TS_CLASSID,4); 2951 ierr = (ts->ops->snesfunction)(snes,U,F,ts);CHKERRQ(ierr); 2952 PetscFunctionReturn(0); 2953 } 2954 2955 #undef __FUNCT__ 2956 #define __FUNCT__ "SNESTSFormJacobian" 2957 /*@ 2958 SNESTSFormJacobian - Function to evaluate the Jacobian 2959 2960 Collective on SNES 2961 2962 Input Parameter: 2963 + snes - nonlinear solver 2964 . U - the current state at which to evaluate the residual 2965 - ctx - user context, must be a TS 2966 2967 Output Parameter: 2968 + A - the Jacobian 2969 . B - the preconditioning matrix (may be the same as A) 2970 - flag - indicates any structure change in the matrix 2971 2972 Notes: 2973 This function is not normally called by users and is automatically registered with the SNES used by TS. 2974 2975 Level: developer 2976 2977 .seealso: SNESSetJacobian() 2978 @*/ 2979 PetscErrorCode SNESTSFormJacobian(SNES snes,Vec U,Mat *A,Mat *B,MatStructure *flag,void *ctx) 2980 { 2981 TS ts = (TS)ctx; 2982 PetscErrorCode ierr; 2983 2984 PetscFunctionBegin; 2985 PetscValidHeaderSpecific(snes,SNES_CLASSID,1); 2986 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 2987 PetscValidPointer(A,3); 2988 PetscValidHeaderSpecific(*A,MAT_CLASSID,3); 2989 PetscValidPointer(B,4); 2990 PetscValidHeaderSpecific(*B,MAT_CLASSID,4); 2991 PetscValidPointer(flag,5); 2992 PetscValidHeaderSpecific(ts,TS_CLASSID,6); 2993 ierr = (ts->ops->snesjacobian)(snes,U,A,B,flag,ts);CHKERRQ(ierr); 2994 PetscFunctionReturn(0); 2995 } 2996 2997 #undef __FUNCT__ 2998 #define __FUNCT__ "TSComputeRHSFunctionLinear" 2999 /*@C 3000 TSComputeRHSFunctionLinear - Evaluate the right hand side via the user-provided Jacobian, for linear problems only 3001 3002 Collective on TS 3003 3004 Input Arguments: 3005 + ts - time stepping context 3006 . t - time at which to evaluate 3007 . U - state at which to evaluate 3008 - ctx - context 3009 3010 Output Arguments: 3011 . F - right hand side 3012 3013 Level: intermediate 3014 3015 Notes: 3016 This function is intended to be passed to TSSetRHSFunction() to evaluate the right hand side for linear problems. 3017 The matrix (and optionally the evaluation context) should be passed to TSSetRHSJacobian(). 3018 3019 .seealso: TSSetRHSFunction(), TSSetRHSJacobian(), TSComputeRHSJacobianConstant() 3020 @*/ 3021 PetscErrorCode TSComputeRHSFunctionLinear(TS ts,PetscReal t,Vec U,Vec F,void *ctx) 3022 { 3023 PetscErrorCode ierr; 3024 Mat Arhs,Brhs; 3025 MatStructure flg2; 3026 3027 PetscFunctionBegin; 3028 ierr = TSGetRHSMats_Private(ts,&Arhs,&Brhs);CHKERRQ(ierr); 3029 ierr = TSComputeRHSJacobian(ts,t,U,&Arhs,&Brhs,&flg2);CHKERRQ(ierr); 3030 ierr = MatMult(Arhs,U,F);CHKERRQ(ierr); 3031 PetscFunctionReturn(0); 3032 } 3033 3034 #undef __FUNCT__ 3035 #define __FUNCT__ "TSComputeRHSJacobianConstant" 3036 /*@C 3037 TSComputeRHSJacobianConstant - Reuses a Jacobian that is time-independent. 3038 3039 Collective on TS 3040 3041 Input Arguments: 3042 + ts - time stepping context 3043 . t - time at which to evaluate 3044 . U - state at which to evaluate 3045 - ctx - context 3046 3047 Output Arguments: 3048 + A - pointer to operator 3049 . B - pointer to preconditioning matrix 3050 - flg - matrix structure flag 3051 3052 Level: intermediate 3053 3054 Notes: 3055 This function is intended to be passed to TSSetRHSJacobian() to evaluate the Jacobian for linear time-independent problems. 3056 3057 .seealso: TSSetRHSFunction(), TSSetRHSJacobian(), TSComputeRHSFunctionLinear() 3058 @*/ 3059 PetscErrorCode TSComputeRHSJacobianConstant(TS ts,PetscReal t,Vec U,Mat *A,Mat *B,MatStructure *flg,void *ctx) 3060 { 3061 PetscFunctionBegin; 3062 *flg = SAME_PRECONDITIONER; 3063 PetscFunctionReturn(0); 3064 } 3065 3066 #undef __FUNCT__ 3067 #define __FUNCT__ "TSComputeIFunctionLinear" 3068 /*@C 3069 TSComputeIFunctionLinear - Evaluate the left hand side via the user-provided Jacobian, for linear problems only 3070 3071 Collective on TS 3072 3073 Input Arguments: 3074 + ts - time stepping context 3075 . t - time at which to evaluate 3076 . U - state at which to evaluate 3077 . Udot - time derivative of state vector 3078 - ctx - context 3079 3080 Output Arguments: 3081 . F - left hand side 3082 3083 Level: intermediate 3084 3085 Notes: 3086 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 3087 user is required to write their own TSComputeIFunction. 3088 This function is intended to be passed to TSSetIFunction() to evaluate the left hand side for linear problems. 3089 The matrix (and optionally the evaluation context) should be passed to TSSetIJacobian(). 3090 3091 .seealso: TSSetIFunction(), TSSetIJacobian(), TSComputeIJacobianConstant() 3092 @*/ 3093 PetscErrorCode TSComputeIFunctionLinear(TS ts,PetscReal t,Vec U,Vec Udot,Vec F,void *ctx) 3094 { 3095 PetscErrorCode ierr; 3096 Mat A,B; 3097 MatStructure flg2; 3098 3099 PetscFunctionBegin; 3100 ierr = TSGetIJacobian(ts,&A,&B,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); 3101 ierr = TSComputeIJacobian(ts,t,U,Udot,1.0,&A,&B,&flg2,PETSC_TRUE);CHKERRQ(ierr); 3102 ierr = MatMult(A,Udot,F);CHKERRQ(ierr); 3103 PetscFunctionReturn(0); 3104 } 3105 3106 #undef __FUNCT__ 3107 #define __FUNCT__ "TSComputeIJacobianConstant" 3108 /*@C 3109 TSComputeIJacobianConstant - Reuses a Jacobian that is time-independent. 3110 3111 Collective on TS 3112 3113 Input Arguments: 3114 + ts - time stepping context 3115 . t - time at which to evaluate 3116 . U - state at which to evaluate 3117 . Udot - time derivative of state vector 3118 . shift - shift to apply 3119 - ctx - context 3120 3121 Output Arguments: 3122 + A - pointer to operator 3123 . B - pointer to preconditioning matrix 3124 - flg - matrix structure flag 3125 3126 Level: intermediate 3127 3128 Notes: 3129 This function is intended to be passed to TSSetIJacobian() to evaluate the Jacobian for linear time-independent problems. 3130 3131 .seealso: TSSetIFunction(), TSSetIJacobian(), TSComputeIFunctionLinear() 3132 @*/ 3133 PetscErrorCode TSComputeIJacobianConstant(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat *A,Mat *B,MatStructure *flg,void *ctx) 3134 { 3135 PetscFunctionBegin; 3136 *flg = SAME_PRECONDITIONER; 3137 PetscFunctionReturn(0); 3138 } 3139 3140 3141 #undef __FUNCT__ 3142 #define __FUNCT__ "TSGetConvergedReason" 3143 /*@ 3144 TSGetConvergedReason - Gets the reason the TS iteration was stopped. 3145 3146 Not Collective 3147 3148 Input Parameter: 3149 . ts - the TS context 3150 3151 Output Parameter: 3152 . reason - negative value indicates diverged, positive value converged, see TSConvergedReason or the 3153 manual pages for the individual convergence tests for complete lists 3154 3155 Level: intermediate 3156 3157 Notes: 3158 Can only be called after the call to TSSolve() is complete. 3159 3160 .keywords: TS, nonlinear, set, convergence, test 3161 3162 .seealso: TSSetConvergenceTest(), TSConvergedReason 3163 @*/ 3164 PetscErrorCode TSGetConvergedReason(TS ts,TSConvergedReason *reason) 3165 { 3166 PetscFunctionBegin; 3167 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3168 PetscValidPointer(reason,2); 3169 *reason = ts->reason; 3170 PetscFunctionReturn(0); 3171 } 3172 3173 #undef __FUNCT__ 3174 #define __FUNCT__ "TSGetSNESIterations" 3175 /*@ 3176 TSGetSNESIterations - Gets the total number of nonlinear iterations 3177 used by the time integrator. 3178 3179 Not Collective 3180 3181 Input Parameter: 3182 . ts - TS context 3183 3184 Output Parameter: 3185 . nits - number of nonlinear iterations 3186 3187 Notes: 3188 This counter is reset to zero for each successive call to TSSolve(). 3189 3190 Level: intermediate 3191 3192 .keywords: TS, get, number, nonlinear, iterations 3193 3194 .seealso: TSGetKSPIterations() 3195 @*/ 3196 PetscErrorCode TSGetSNESIterations(TS ts,PetscInt *nits) 3197 { 3198 PetscFunctionBegin; 3199 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3200 PetscValidIntPointer(nits,2); 3201 *nits = ts->snes_its; 3202 PetscFunctionReturn(0); 3203 } 3204 3205 #undef __FUNCT__ 3206 #define __FUNCT__ "TSGetKSPIterations" 3207 /*@ 3208 TSGetKSPIterations - Gets the total number of linear iterations 3209 used by the time integrator. 3210 3211 Not Collective 3212 3213 Input Parameter: 3214 . ts - TS context 3215 3216 Output Parameter: 3217 . lits - number of linear iterations 3218 3219 Notes: 3220 This counter is reset to zero for each successive call to TSSolve(). 3221 3222 Level: intermediate 3223 3224 .keywords: TS, get, number, linear, iterations 3225 3226 .seealso: TSGetSNESIterations(), SNESGetKSPIterations() 3227 @*/ 3228 PetscErrorCode TSGetKSPIterations(TS ts,PetscInt *lits) 3229 { 3230 PetscFunctionBegin; 3231 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3232 PetscValidIntPointer(lits,2); 3233 *lits = ts->ksp_its; 3234 PetscFunctionReturn(0); 3235 } 3236 3237 #undef __FUNCT__ 3238 #define __FUNCT__ "TSGetStepRejections" 3239 /*@ 3240 TSGetStepRejections - Gets the total number of rejected steps. 3241 3242 Not Collective 3243 3244 Input Parameter: 3245 . ts - TS context 3246 3247 Output Parameter: 3248 . rejects - number of steps rejected 3249 3250 Notes: 3251 This counter is reset to zero for each successive call to TSSolve(). 3252 3253 Level: intermediate 3254 3255 .keywords: TS, get, number 3256 3257 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetSNESFailures(), TSSetMaxSNESFailures(), TSSetErrorIfStepFails() 3258 @*/ 3259 PetscErrorCode TSGetStepRejections(TS ts,PetscInt *rejects) 3260 { 3261 PetscFunctionBegin; 3262 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3263 PetscValidIntPointer(rejects,2); 3264 *rejects = ts->reject; 3265 PetscFunctionReturn(0); 3266 } 3267 3268 #undef __FUNCT__ 3269 #define __FUNCT__ "TSGetSNESFailures" 3270 /*@ 3271 TSGetSNESFailures - Gets the total number of failed SNES solves 3272 3273 Not Collective 3274 3275 Input Parameter: 3276 . ts - TS context 3277 3278 Output Parameter: 3279 . fails - number of failed nonlinear solves 3280 3281 Notes: 3282 This counter is reset to zero for each successive call to TSSolve(). 3283 3284 Level: intermediate 3285 3286 .keywords: TS, get, number 3287 3288 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSSetMaxSNESFailures() 3289 @*/ 3290 PetscErrorCode TSGetSNESFailures(TS ts,PetscInt *fails) 3291 { 3292 PetscFunctionBegin; 3293 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3294 PetscValidIntPointer(fails,2); 3295 *fails = ts->num_snes_failures; 3296 PetscFunctionReturn(0); 3297 } 3298 3299 #undef __FUNCT__ 3300 #define __FUNCT__ "TSSetMaxStepRejections" 3301 /*@ 3302 TSSetMaxStepRejections - Sets the maximum number of step rejections before a step fails 3303 3304 Not Collective 3305 3306 Input Parameter: 3307 + ts - TS context 3308 - rejects - maximum number of rejected steps, pass -1 for unlimited 3309 3310 Notes: 3311 The counter is reset to zero for each step 3312 3313 Options Database Key: 3314 . -ts_max_reject - Maximum number of step rejections before a step fails 3315 3316 Level: intermediate 3317 3318 .keywords: TS, set, maximum, number 3319 3320 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxSNESFailures(), TSGetStepRejections(), TSGetSNESFailures(), TSSetErrorIfStepFails(), TSGetConvergedReason() 3321 @*/ 3322 PetscErrorCode TSSetMaxStepRejections(TS ts,PetscInt rejects) 3323 { 3324 PetscFunctionBegin; 3325 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3326 ts->max_reject = rejects; 3327 PetscFunctionReturn(0); 3328 } 3329 3330 #undef __FUNCT__ 3331 #define __FUNCT__ "TSSetMaxSNESFailures" 3332 /*@ 3333 TSSetMaxSNESFailures - Sets the maximum number of failed SNES solves 3334 3335 Not Collective 3336 3337 Input Parameter: 3338 + ts - TS context 3339 - fails - maximum number of failed nonlinear solves, pass -1 for unlimited 3340 3341 Notes: 3342 The counter is reset to zero for each successive call to TSSolve(). 3343 3344 Options Database Key: 3345 . -ts_max_snes_failures - Maximum number of nonlinear solve failures 3346 3347 Level: intermediate 3348 3349 .keywords: TS, set, maximum, number 3350 3351 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSGetSNESFailures(), SNESGetConvergedReason(), TSGetConvergedReason() 3352 @*/ 3353 PetscErrorCode TSSetMaxSNESFailures(TS ts,PetscInt fails) 3354 { 3355 PetscFunctionBegin; 3356 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3357 ts->max_snes_failures = fails; 3358 PetscFunctionReturn(0); 3359 } 3360 3361 #undef __FUNCT__ 3362 #define __FUNCT__ "TSSetErrorIfStepFails()" 3363 /*@ 3364 TSSetErrorIfStepFails - Error if no step succeeds 3365 3366 Not Collective 3367 3368 Input Parameter: 3369 + ts - TS context 3370 - err - PETSC_TRUE to error if no step succeeds, PETSC_FALSE to return without failure 3371 3372 Options Database Key: 3373 . -ts_error_if_step_fails - Error if no step succeeds 3374 3375 Level: intermediate 3376 3377 .keywords: TS, set, error 3378 3379 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSGetSNESFailures(), TSSetErrorIfStepFails(), TSGetConvergedReason() 3380 @*/ 3381 PetscErrorCode TSSetErrorIfStepFails(TS ts,PetscBool err) 3382 { 3383 PetscFunctionBegin; 3384 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3385 ts->errorifstepfailed = err; 3386 PetscFunctionReturn(0); 3387 } 3388 3389 #undef __FUNCT__ 3390 #define __FUNCT__ "TSMonitorSolutionBinary" 3391 /*@C 3392 TSMonitorSolutionBinary - Monitors progress of the TS solvers by VecView() for the solution at each timestep. Normally the viewer is a binary file 3393 3394 Collective on TS 3395 3396 Input Parameters: 3397 + ts - the TS context 3398 . step - current time-step 3399 . ptime - current time 3400 . u - current state 3401 - viewer - binary viewer 3402 3403 Level: intermediate 3404 3405 .keywords: TS, vector, monitor, view 3406 3407 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 3408 @*/ 3409 PetscErrorCode TSMonitorSolutionBinary(TS ts,PetscInt step,PetscReal ptime,Vec u,void *viewer) 3410 { 3411 PetscErrorCode ierr; 3412 PetscViewer v = (PetscViewer)viewer; 3413 3414 PetscFunctionBegin; 3415 ierr = VecView(u,v);CHKERRQ(ierr); 3416 PetscFunctionReturn(0); 3417 } 3418 3419 #undef __FUNCT__ 3420 #define __FUNCT__ "TSMonitorSolutionVTK" 3421 /*@C 3422 TSMonitorSolutionVTK - Monitors progress of the TS solvers by VecView() for the solution at each timestep. 3423 3424 Collective on TS 3425 3426 Input Parameters: 3427 + ts - the TS context 3428 . step - current time-step 3429 . ptime - current time 3430 . u - current state 3431 - filenametemplate - string containing a format specifier for the integer time step (e.g. %03D) 3432 3433 Level: intermediate 3434 3435 Notes: 3436 The VTK format does not allow writing multiple time steps in the same file, therefore a different file will be written for each time step. 3437 These are named according to the file name template. 3438 3439 This function is normally passed as an argument to TSMonitorSet() along with TSMonitorSolutionVTKDestroy(). 3440 3441 .keywords: TS, vector, monitor, view 3442 3443 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 3444 @*/ 3445 PetscErrorCode TSMonitorSolutionVTK(TS ts,PetscInt step,PetscReal ptime,Vec u,void *filenametemplate) 3446 { 3447 PetscErrorCode ierr; 3448 char filename[PETSC_MAX_PATH_LEN]; 3449 PetscViewer viewer; 3450 3451 PetscFunctionBegin; 3452 ierr = PetscSNPrintf(filename,sizeof(filename),(const char*)filenametemplate,step);CHKERRQ(ierr); 3453 ierr = PetscViewerVTKOpen(((PetscObject)ts)->comm,filename,FILE_MODE_WRITE,&viewer);CHKERRQ(ierr); 3454 ierr = VecView(u,viewer);CHKERRQ(ierr); 3455 ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr); 3456 PetscFunctionReturn(0); 3457 } 3458 3459 #undef __FUNCT__ 3460 #define __FUNCT__ "TSMonitorSolutionVTKDestroy" 3461 /*@C 3462 TSMonitorSolutionVTKDestroy - Destroy context for monitoring 3463 3464 Collective on TS 3465 3466 Input Parameters: 3467 . filenametemplate - string containing a format specifier for the integer time step (e.g. %03D) 3468 3469 Level: intermediate 3470 3471 Note: 3472 This function is normally passed to TSMonitorSet() along with TSMonitorSolutionVTK(). 3473 3474 .keywords: TS, vector, monitor, view 3475 3476 .seealso: TSMonitorSet(), TSMonitorSolutionVTK() 3477 @*/ 3478 PetscErrorCode TSMonitorSolutionVTKDestroy(void *filenametemplate) 3479 { 3480 PetscErrorCode ierr; 3481 3482 PetscFunctionBegin; 3483 ierr = PetscFree(*(char**)filenametemplate);CHKERRQ(ierr); 3484 PetscFunctionReturn(0); 3485 } 3486 3487 #undef __FUNCT__ 3488 #define __FUNCT__ "TSGetAdapt" 3489 /*@ 3490 TSGetAdapt - Get the adaptive controller context for the current method 3491 3492 Collective on TS if controller has not been created yet 3493 3494 Input Arguments: 3495 . ts - time stepping context 3496 3497 Output Arguments: 3498 . adapt - adaptive controller 3499 3500 Level: intermediate 3501 3502 .seealso: TSAdapt, TSAdaptSetType(), TSAdaptChoose() 3503 @*/ 3504 PetscErrorCode TSGetAdapt(TS ts,TSAdapt *adapt) 3505 { 3506 PetscErrorCode ierr; 3507 3508 PetscFunctionBegin; 3509 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3510 PetscValidPointer(adapt,2); 3511 if (!ts->adapt) { 3512 ierr = TSAdaptCreate(((PetscObject)ts)->comm,&ts->adapt);CHKERRQ(ierr); 3513 ierr = PetscLogObjectParent(ts,ts->adapt);CHKERRQ(ierr); 3514 ierr = PetscObjectIncrementTabLevel((PetscObject)ts->adapt,(PetscObject)ts,1);CHKERRQ(ierr); 3515 } 3516 *adapt = ts->adapt; 3517 PetscFunctionReturn(0); 3518 } 3519 3520 #undef __FUNCT__ 3521 #define __FUNCT__ "TSSetTolerances" 3522 /*@ 3523 TSSetTolerances - Set tolerances for local truncation error when using adaptive controller 3524 3525 Logically Collective 3526 3527 Input Arguments: 3528 + ts - time integration context 3529 . atol - scalar absolute tolerances, PETSC_DECIDE to leave current value 3530 . vatol - vector of absolute tolerances or PETSC_NULL, used in preference to atol if present 3531 . rtol - scalar relative tolerances, PETSC_DECIDE to leave current value 3532 - vrtol - vector of relative tolerances or PETSC_NULL, used in preference to atol if present 3533 3534 Level: beginner 3535 3536 .seealso: TS, TSAdapt, TSVecNormWRMS(), TSGetTolerances() 3537 @*/ 3538 PetscErrorCode TSSetTolerances(TS ts,PetscReal atol,Vec vatol,PetscReal rtol,Vec vrtol) 3539 { 3540 PetscErrorCode ierr; 3541 3542 PetscFunctionBegin; 3543 if (atol != PETSC_DECIDE && atol != PETSC_DEFAULT) ts->atol = atol; 3544 if (vatol) { 3545 ierr = PetscObjectReference((PetscObject)vatol);CHKERRQ(ierr); 3546 ierr = VecDestroy(&ts->vatol);CHKERRQ(ierr); 3547 ts->vatol = vatol; 3548 } 3549 if (rtol != PETSC_DECIDE && rtol != PETSC_DEFAULT) ts->rtol = rtol; 3550 if (vrtol) { 3551 ierr = PetscObjectReference((PetscObject)vrtol);CHKERRQ(ierr); 3552 ierr = VecDestroy(&ts->vrtol);CHKERRQ(ierr); 3553 ts->vrtol = vrtol; 3554 } 3555 PetscFunctionReturn(0); 3556 } 3557 3558 #undef __FUNCT__ 3559 #define __FUNCT__ "TSGetTolerances" 3560 /*@ 3561 TSGetTolerances - Get tolerances for local truncation error when using adaptive controller 3562 3563 Logically Collective 3564 3565 Input Arguments: 3566 . ts - time integration context 3567 3568 Output Arguments: 3569 + atol - scalar absolute tolerances, PETSC_NULL to ignore 3570 . vatol - vector of absolute tolerances, PETSC_NULL to ignore 3571 . rtol - scalar relative tolerances, PETSC_NULL to ignore 3572 - vrtol - vector of relative tolerances, PETSC_NULL to ignore 3573 3574 Level: beginner 3575 3576 .seealso: TS, TSAdapt, TSVecNormWRMS(), TSSetTolerances() 3577 @*/ 3578 PetscErrorCode TSGetTolerances(TS ts,PetscReal *atol,Vec *vatol,PetscReal *rtol,Vec *vrtol) 3579 { 3580 PetscFunctionBegin; 3581 if (atol) *atol = ts->atol; 3582 if (vatol) *vatol = ts->vatol; 3583 if (rtol) *rtol = ts->rtol; 3584 if (vrtol) *vrtol = ts->vrtol; 3585 PetscFunctionReturn(0); 3586 } 3587 3588 #undef __FUNCT__ 3589 #define __FUNCT__ "TSErrorNormWRMS" 3590 /*@ 3591 TSErrorNormWRMS - compute a weighted norm of the difference between a vector and the current state 3592 3593 Collective on TS 3594 3595 Input Arguments: 3596 + ts - time stepping context 3597 - Y - state vector to be compared to ts->vec_sol 3598 3599 Output Arguments: 3600 . norm - weighted norm, a value of 1.0 is considered small 3601 3602 Level: developer 3603 3604 .seealso: TSSetTolerances() 3605 @*/ 3606 PetscErrorCode TSErrorNormWRMS(TS ts,Vec Y,PetscReal *norm) 3607 { 3608 PetscErrorCode ierr; 3609 PetscInt i,n,N; 3610 const PetscScalar *u,*y; 3611 Vec U; 3612 PetscReal sum,gsum; 3613 3614 PetscFunctionBegin; 3615 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3616 PetscValidHeaderSpecific(Y,VEC_CLASSID,2); 3617 PetscValidPointer(norm,3); 3618 U = ts->vec_sol; 3619 PetscCheckSameTypeAndComm(U,1,Y,2); 3620 if (U == Y) SETERRQ(((PetscObject)U)->comm,PETSC_ERR_ARG_IDN,"Y cannot be the TS solution vector"); 3621 3622 ierr = VecGetSize(U,&N);CHKERRQ(ierr); 3623 ierr = VecGetLocalSize(U,&n);CHKERRQ(ierr); 3624 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 3625 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 3626 sum = 0.; 3627 if (ts->vatol && ts->vrtol) { 3628 const PetscScalar *atol,*rtol; 3629 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 3630 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 3631 for (i=0; i<n; i++) { 3632 PetscReal tol = PetscRealPart(atol[i]) + PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 3633 sum += PetscSqr(PetscAbsScalar(y[i] - u[i]) / tol); 3634 } 3635 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 3636 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 3637 } else if (ts->vatol) { /* vector atol, scalar rtol */ 3638 const PetscScalar *atol; 3639 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 3640 for (i=0; i<n; i++) { 3641 PetscReal tol = PetscRealPart(atol[i]) + ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 3642 sum += PetscSqr(PetscAbsScalar(y[i] - u[i]) / tol); 3643 } 3644 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 3645 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 3646 const PetscScalar *rtol; 3647 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 3648 for (i=0; i<n; i++) { 3649 PetscReal tol = ts->atol + PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 3650 sum += PetscSqr(PetscAbsScalar(y[i] - u[i]) / tol); 3651 } 3652 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 3653 } else { /* scalar atol, scalar rtol */ 3654 for (i=0; i<n; i++) { 3655 PetscReal tol = ts->atol + ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 3656 sum += PetscSqr(PetscAbsScalar(y[i] - u[i]) / tol); 3657 } 3658 } 3659 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 3660 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 3661 3662 ierr = MPI_Allreduce(&sum,&gsum,1,MPIU_REAL,MPIU_SUM,((PetscObject)ts)->comm);CHKERRQ(ierr); 3663 *norm = PetscSqrtReal(gsum / N); 3664 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(((PetscObject)ts)->comm,PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 3665 PetscFunctionReturn(0); 3666 } 3667 3668 #undef __FUNCT__ 3669 #define __FUNCT__ "TSSetCFLTimeLocal" 3670 /*@ 3671 TSSetCFLTimeLocal - Set the local CFL constraint relative to forward Euler 3672 3673 Logically Collective on TS 3674 3675 Input Arguments: 3676 + ts - time stepping context 3677 - cfltime - maximum stable time step if using forward Euler (value can be different on each process) 3678 3679 Note: 3680 After calling this function, the global CFL time can be obtained by calling TSGetCFLTime() 3681 3682 Level: intermediate 3683 3684 .seealso: TSGetCFLTime(), TSADAPTCFL 3685 @*/ 3686 PetscErrorCode TSSetCFLTimeLocal(TS ts,PetscReal cfltime) 3687 { 3688 PetscFunctionBegin; 3689 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3690 ts->cfltime_local = cfltime; 3691 ts->cfltime = -1.; 3692 PetscFunctionReturn(0); 3693 } 3694 3695 #undef __FUNCT__ 3696 #define __FUNCT__ "TSGetCFLTime" 3697 /*@ 3698 TSGetCFLTime - Get the maximum stable time step according to CFL criteria applied to forward Euler 3699 3700 Collective on TS 3701 3702 Input Arguments: 3703 . ts - time stepping context 3704 3705 Output Arguments: 3706 . cfltime - maximum stable time step for forward Euler 3707 3708 Level: advanced 3709 3710 .seealso: TSSetCFLTimeLocal() 3711 @*/ 3712 PetscErrorCode TSGetCFLTime(TS ts,PetscReal *cfltime) 3713 { 3714 PetscErrorCode ierr; 3715 3716 PetscFunctionBegin; 3717 if (ts->cfltime < 0) { 3718 ierr = MPI_Allreduce(&ts->cfltime_local,&ts->cfltime,1,MPIU_REAL,MPIU_MIN,((PetscObject)ts)->comm);CHKERRQ(ierr); 3719 } 3720 *cfltime = ts->cfltime; 3721 PetscFunctionReturn(0); 3722 } 3723 3724 #undef __FUNCT__ 3725 #define __FUNCT__ "TSVISetVariableBounds" 3726 /*@ 3727 TSVISetVariableBounds - Sets the lower and upper bounds for the solution vector. xl <= x <= xu 3728 3729 Input Parameters: 3730 . ts - the TS context. 3731 . xl - lower bound. 3732 . xu - upper bound. 3733 3734 Notes: 3735 If this routine is not called then the lower and upper bounds are set to 3736 SNES_VI_NINF and SNES_VI_INF respectively during SNESSetUp(). 3737 3738 Level: advanced 3739 3740 @*/ 3741 PetscErrorCode TSVISetVariableBounds(TS ts, Vec xl, Vec xu) 3742 { 3743 PetscErrorCode ierr; 3744 SNES snes; 3745 3746 PetscFunctionBegin; 3747 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 3748 ierr = SNESVISetVariableBounds(snes,xl,xu);CHKERRQ(ierr); 3749 PetscFunctionReturn(0); 3750 } 3751 3752 #if defined(PETSC_HAVE_MATLAB_ENGINE) 3753 #include <mex.h> 3754 3755 typedef struct {char *funcname; mxArray *ctx;} TSMatlabContext; 3756 3757 #undef __FUNCT__ 3758 #define __FUNCT__ "TSComputeFunction_Matlab" 3759 /* 3760 TSComputeFunction_Matlab - Calls the function that has been set with 3761 TSSetFunctionMatlab(). 3762 3763 Collective on TS 3764 3765 Input Parameters: 3766 + snes - the TS context 3767 - u - input vector 3768 3769 Output Parameter: 3770 . y - function vector, as set by TSSetFunction() 3771 3772 Notes: 3773 TSComputeFunction() is typically used within nonlinear solvers 3774 implementations, so most users would not generally call this routine 3775 themselves. 3776 3777 Level: developer 3778 3779 .keywords: TS, nonlinear, compute, function 3780 3781 .seealso: TSSetFunction(), TSGetFunction() 3782 */ 3783 PetscErrorCode TSComputeFunction_Matlab(TS snes,PetscReal time,Vec u,Vec udot,Vec y, void *ctx) 3784 { 3785 PetscErrorCode ierr; 3786 TSMatlabContext *sctx = (TSMatlabContext *)ctx; 3787 int nlhs = 1,nrhs = 7; 3788 mxArray *plhs[1],*prhs[7]; 3789 long long int lx = 0,lxdot = 0,ly = 0,ls = 0; 3790 3791 PetscFunctionBegin; 3792 PetscValidHeaderSpecific(snes,TS_CLASSID,1); 3793 PetscValidHeaderSpecific(u,VEC_CLASSID,3); 3794 PetscValidHeaderSpecific(udot,VEC_CLASSID,4); 3795 PetscValidHeaderSpecific(y,VEC_CLASSID,5); 3796 PetscCheckSameComm(snes,1,u,3); 3797 PetscCheckSameComm(snes,1,y,5); 3798 3799 ierr = PetscMemcpy(&ls,&snes,sizeof(snes));CHKERRQ(ierr); 3800 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 3801 ierr = PetscMemcpy(&lxdot,&udot,sizeof(udot));CHKERRQ(ierr); 3802 ierr = PetscMemcpy(&ly,&y,sizeof(u));CHKERRQ(ierr); 3803 prhs[0] = mxCreateDoubleScalar((double)ls); 3804 prhs[1] = mxCreateDoubleScalar(time); 3805 prhs[2] = mxCreateDoubleScalar((double)lx); 3806 prhs[3] = mxCreateDoubleScalar((double)lxdot); 3807 prhs[4] = mxCreateDoubleScalar((double)ly); 3808 prhs[5] = mxCreateString(sctx->funcname); 3809 prhs[6] = sctx->ctx; 3810 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSComputeFunctionInternal");CHKERRQ(ierr); 3811 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 3812 mxDestroyArray(prhs[0]); 3813 mxDestroyArray(prhs[1]); 3814 mxDestroyArray(prhs[2]); 3815 mxDestroyArray(prhs[3]); 3816 mxDestroyArray(prhs[4]); 3817 mxDestroyArray(prhs[5]); 3818 mxDestroyArray(plhs[0]); 3819 PetscFunctionReturn(0); 3820 } 3821 3822 3823 #undef __FUNCT__ 3824 #define __FUNCT__ "TSSetFunctionMatlab" 3825 /* 3826 TSSetFunctionMatlab - Sets the function evaluation routine and function 3827 vector for use by the TS routines in solving ODEs 3828 equations from MATLAB. Here the function is a string containing the name of a MATLAB function 3829 3830 Logically Collective on TS 3831 3832 Input Parameters: 3833 + ts - the TS context 3834 - func - function evaluation routine 3835 3836 Calling sequence of func: 3837 $ func (TS ts,PetscReal time,Vec u,Vec udot,Vec f,void *ctx); 3838 3839 Level: beginner 3840 3841 .keywords: TS, nonlinear, set, function 3842 3843 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 3844 */ 3845 PetscErrorCode TSSetFunctionMatlab(TS ts,const char *func,mxArray *ctx) 3846 { 3847 PetscErrorCode ierr; 3848 TSMatlabContext *sctx; 3849 3850 PetscFunctionBegin; 3851 /* currently sctx is memory bleed */ 3852 ierr = PetscMalloc(sizeof(TSMatlabContext),&sctx);CHKERRQ(ierr); 3853 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 3854 /* 3855 This should work, but it doesn't 3856 sctx->ctx = ctx; 3857 mexMakeArrayPersistent(sctx->ctx); 3858 */ 3859 sctx->ctx = mxDuplicateArray(ctx); 3860 ierr = TSSetIFunction(ts,PETSC_NULL,TSComputeFunction_Matlab,sctx);CHKERRQ(ierr); 3861 PetscFunctionReturn(0); 3862 } 3863 3864 #undef __FUNCT__ 3865 #define __FUNCT__ "TSComputeJacobian_Matlab" 3866 /* 3867 TSComputeJacobian_Matlab - Calls the function that has been set with 3868 TSSetJacobianMatlab(). 3869 3870 Collective on TS 3871 3872 Input Parameters: 3873 + ts - the TS context 3874 . u - input vector 3875 . A, B - the matrices 3876 - ctx - user context 3877 3878 Output Parameter: 3879 . flag - structure of the matrix 3880 3881 Level: developer 3882 3883 .keywords: TS, nonlinear, compute, function 3884 3885 .seealso: TSSetFunction(), TSGetFunction() 3886 @*/ 3887 PetscErrorCode TSComputeJacobian_Matlab(TS ts,PetscReal time,Vec u,Vec udot,PetscReal shift,Mat *A,Mat *B,MatStructure *flag, void *ctx) 3888 { 3889 PetscErrorCode ierr; 3890 TSMatlabContext *sctx = (TSMatlabContext *)ctx; 3891 int nlhs = 2,nrhs = 9; 3892 mxArray *plhs[2],*prhs[9]; 3893 long long int lx = 0,lxdot = 0,lA = 0,ls = 0, lB = 0; 3894 3895 PetscFunctionBegin; 3896 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3897 PetscValidHeaderSpecific(u,VEC_CLASSID,3); 3898 3899 /* call Matlab function in ctx with arguments u and y */ 3900 3901 ierr = PetscMemcpy(&ls,&ts,sizeof(ts));CHKERRQ(ierr); 3902 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 3903 ierr = PetscMemcpy(&lxdot,&udot,sizeof(u));CHKERRQ(ierr); 3904 ierr = PetscMemcpy(&lA,A,sizeof(u));CHKERRQ(ierr); 3905 ierr = PetscMemcpy(&lB,B,sizeof(u));CHKERRQ(ierr); 3906 prhs[0] = mxCreateDoubleScalar((double)ls); 3907 prhs[1] = mxCreateDoubleScalar((double)time); 3908 prhs[2] = mxCreateDoubleScalar((double)lx); 3909 prhs[3] = mxCreateDoubleScalar((double)lxdot); 3910 prhs[4] = mxCreateDoubleScalar((double)shift); 3911 prhs[5] = mxCreateDoubleScalar((double)lA); 3912 prhs[6] = mxCreateDoubleScalar((double)lB); 3913 prhs[7] = mxCreateString(sctx->funcname); 3914 prhs[8] = sctx->ctx; 3915 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSComputeJacobianInternal");CHKERRQ(ierr); 3916 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 3917 *flag = (MatStructure) mxGetScalar(plhs[1]);CHKERRQ(ierr); 3918 mxDestroyArray(prhs[0]); 3919 mxDestroyArray(prhs[1]); 3920 mxDestroyArray(prhs[2]); 3921 mxDestroyArray(prhs[3]); 3922 mxDestroyArray(prhs[4]); 3923 mxDestroyArray(prhs[5]); 3924 mxDestroyArray(prhs[6]); 3925 mxDestroyArray(prhs[7]); 3926 mxDestroyArray(plhs[0]); 3927 mxDestroyArray(plhs[1]); 3928 PetscFunctionReturn(0); 3929 } 3930 3931 3932 #undef __FUNCT__ 3933 #define __FUNCT__ "TSSetJacobianMatlab" 3934 /* 3935 TSSetJacobianMatlab - Sets the Jacobian function evaluation routine and two empty Jacobian matrices 3936 vector for use by the TS routines in solving ODEs from MATLAB. Here the function is a string containing the name of a MATLAB function 3937 3938 Logically Collective on TS 3939 3940 Input Parameters: 3941 + ts - the TS context 3942 . A,B - Jacobian matrices 3943 . func - function evaluation routine 3944 - ctx - user context 3945 3946 Calling sequence of func: 3947 $ flag = func (TS ts,PetscReal time,Vec u,Vec udot,Mat A,Mat B,void *ctx); 3948 3949 3950 Level: developer 3951 3952 .keywords: TS, nonlinear, set, function 3953 3954 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 3955 */ 3956 PetscErrorCode TSSetJacobianMatlab(TS ts,Mat A,Mat B,const char *func,mxArray *ctx) 3957 { 3958 PetscErrorCode ierr; 3959 TSMatlabContext *sctx; 3960 3961 PetscFunctionBegin; 3962 /* currently sctx is memory bleed */ 3963 ierr = PetscMalloc(sizeof(TSMatlabContext),&sctx);CHKERRQ(ierr); 3964 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 3965 /* 3966 This should work, but it doesn't 3967 sctx->ctx = ctx; 3968 mexMakeArrayPersistent(sctx->ctx); 3969 */ 3970 sctx->ctx = mxDuplicateArray(ctx); 3971 ierr = TSSetIJacobian(ts,A,B,TSComputeJacobian_Matlab,sctx);CHKERRQ(ierr); 3972 PetscFunctionReturn(0); 3973 } 3974 3975 #undef __FUNCT__ 3976 #define __FUNCT__ "TSMonitor_Matlab" 3977 /* 3978 TSMonitor_Matlab - Calls the function that has been set with TSMonitorSetMatlab(). 3979 3980 Collective on TS 3981 3982 .seealso: TSSetFunction(), TSGetFunction() 3983 @*/ 3984 PetscErrorCode TSMonitor_Matlab(TS ts,PetscInt it, PetscReal time,Vec u, void *ctx) 3985 { 3986 PetscErrorCode ierr; 3987 TSMatlabContext *sctx = (TSMatlabContext *)ctx; 3988 int nlhs = 1,nrhs = 6; 3989 mxArray *plhs[1],*prhs[6]; 3990 long long int lx = 0,ls = 0; 3991 3992 PetscFunctionBegin; 3993 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3994 PetscValidHeaderSpecific(u,VEC_CLASSID,4); 3995 3996 ierr = PetscMemcpy(&ls,&ts,sizeof(ts));CHKERRQ(ierr); 3997 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 3998 prhs[0] = mxCreateDoubleScalar((double)ls); 3999 prhs[1] = mxCreateDoubleScalar((double)it); 4000 prhs[2] = mxCreateDoubleScalar((double)time); 4001 prhs[3] = mxCreateDoubleScalar((double)lx); 4002 prhs[4] = mxCreateString(sctx->funcname); 4003 prhs[5] = sctx->ctx; 4004 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSMonitorInternal");CHKERRQ(ierr); 4005 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 4006 mxDestroyArray(prhs[0]); 4007 mxDestroyArray(prhs[1]); 4008 mxDestroyArray(prhs[2]); 4009 mxDestroyArray(prhs[3]); 4010 mxDestroyArray(prhs[4]); 4011 mxDestroyArray(plhs[0]); 4012 PetscFunctionReturn(0); 4013 } 4014 4015 4016 #undef __FUNCT__ 4017 #define __FUNCT__ "TSMonitorSetMatlab" 4018 /* 4019 TSMonitorSetMatlab - Sets the monitor function from Matlab 4020 4021 Level: developer 4022 4023 .keywords: TS, nonlinear, set, function 4024 4025 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 4026 */ 4027 PetscErrorCode TSMonitorSetMatlab(TS ts,const char *func,mxArray *ctx) 4028 { 4029 PetscErrorCode ierr; 4030 TSMatlabContext *sctx; 4031 4032 PetscFunctionBegin; 4033 /* currently sctx is memory bleed */ 4034 ierr = PetscMalloc(sizeof(TSMatlabContext),&sctx);CHKERRQ(ierr); 4035 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 4036 /* 4037 This should work, but it doesn't 4038 sctx->ctx = ctx; 4039 mexMakeArrayPersistent(sctx->ctx); 4040 */ 4041 sctx->ctx = mxDuplicateArray(ctx); 4042 ierr = TSMonitorSet(ts,TSMonitor_Matlab,sctx,PETSC_NULL);CHKERRQ(ierr); 4043 PetscFunctionReturn(0); 4044 } 4045 #endif 4046 4047 4048 4049 #undef __FUNCT__ 4050 #define __FUNCT__ "TSMonitorLGSolution" 4051 /*@C 4052 TSMonitorLGSolution - Monitors progress of the TS solvers by plotting each component of the solution vector 4053 in a time based line graph 4054 4055 Collective on TS 4056 4057 Input Parameters: 4058 + ts - the TS context 4059 . step - current time-step 4060 . ptime - current time 4061 - lg - a line graph object 4062 4063 Level: intermediate 4064 4065 Notes: each process in a parallel run displays its component solutions in a separate window 4066 4067 .keywords: TS, vector, monitor, view 4068 4069 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 4070 @*/ 4071 PetscErrorCode TSMonitorLGSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 4072 { 4073 PetscErrorCode ierr; 4074 TSMonitorLGCtx ctx = (TSMonitorLGCtx)dummy; 4075 const PetscScalar *yy; 4076 PetscInt dim; 4077 4078 PetscFunctionBegin; 4079 if (!step) { 4080 PetscDrawAxis axis; 4081 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 4082 ierr = PetscDrawAxisSetLabels(axis,"Solution as function of time","Time","Solution");CHKERRQ(ierr); 4083 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 4084 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 4085 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 4086 } 4087 ierr = VecGetArrayRead(u,&yy);CHKERRQ(ierr); 4088 #if defined(PETSC_USE_COMPLEX) 4089 { 4090 PetscReal *yreal; 4091 PetscInt i,n; 4092 ierr = VecGetLocalSize(u,&n);CHKERRQ(ierr); 4093 ierr = PetscMalloc(n*sizeof(PetscReal),&yreal);CHKERRQ(ierr); 4094 for (i=0; i<n; i++) yreal[i] = PetscRealPart(yy[i]); 4095 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yreal);CHKERRQ(ierr); 4096 ierr = PetscFree(yreal);CHKERRQ(ierr); 4097 } 4098 #else 4099 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yy);CHKERRQ(ierr); 4100 #endif 4101 ierr = VecRestoreArrayRead(u,&yy);CHKERRQ(ierr); 4102 if (((ctx->howoften > 0) && (!(step % ctx->howoften)) && (step > -1)) || ((ctx->howoften == -1) && (step == -1))){ 4103 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 4104 } 4105 PetscFunctionReturn(0); 4106 } 4107 4108 #undef __FUNCT__ 4109 #define __FUNCT__ "TSMonitorLGError" 4110 /*@C 4111 TSMonitorLGError - Monitors progress of the TS solvers by plotting each component of the solution vector 4112 in a time based line graph 4113 4114 Collective on TS 4115 4116 Input Parameters: 4117 + ts - the TS context 4118 . step - current time-step 4119 . ptime - current time 4120 - lg - a line graph object 4121 4122 Level: intermediate 4123 4124 Notes: 4125 Only for sequential solves. 4126 4127 The user must provide the solution using TSSetSolutionFunction() to use this monitor. 4128 4129 Options Database Keys: 4130 . -ts_monitor_lg_error - create a graphical monitor of error history 4131 4132 .keywords: TS, vector, monitor, view 4133 4134 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSSetSolutionFunction() 4135 @*/ 4136 PetscErrorCode TSMonitorLGError(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 4137 { 4138 PetscErrorCode ierr; 4139 TSMonitorLGCtx ctx = (TSMonitorLGCtx)dummy; 4140 const PetscScalar *yy; 4141 Vec y; 4142 PetscInt dim; 4143 4144 PetscFunctionBegin; 4145 if (!step) { 4146 PetscDrawAxis axis; 4147 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 4148 ierr = PetscDrawAxisSetLabels(axis,"Error in solution as function of time","Time","Solution");CHKERRQ(ierr); 4149 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 4150 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 4151 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 4152 } 4153 ierr = VecDuplicate(u,&y);CHKERRQ(ierr); 4154 ierr = TSComputeSolutionFunction(ts,ptime,y);CHKERRQ(ierr); 4155 ierr = VecAXPY(y,-1.0,u);CHKERRQ(ierr); 4156 ierr = VecGetArrayRead(y,&yy);CHKERRQ(ierr); 4157 #if defined(PETSC_USE_COMPLEX) 4158 { 4159 PetscReal *yreal; 4160 PetscInt i,n; 4161 ierr = VecGetLocalSize(y,&n);CHKERRQ(ierr); 4162 ierr = PetscMalloc(n*sizeof(PetscReal),&yreal);CHKERRQ(ierr); 4163 for (i=0; i<n; i++) yreal[i] = PetscRealPart(yy[i]); 4164 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yreal);CHKERRQ(ierr); 4165 ierr = PetscFree(yreal);CHKERRQ(ierr); 4166 } 4167 #else 4168 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yy);CHKERRQ(ierr); 4169 #endif 4170 ierr = VecRestoreArrayRead(y,&yy);CHKERRQ(ierr); 4171 ierr = VecDestroy(&y);CHKERRQ(ierr); 4172 if (((ctx->howoften > 0) && (!(step % ctx->howoften)) && (step > -1)) || ((ctx->howoften == -1) && (step == -1))){ 4173 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 4174 } 4175 PetscFunctionReturn(0); 4176 } 4177 4178 #undef __FUNCT__ 4179 #define __FUNCT__ "TSMonitorLGSNESIterations" 4180 PetscErrorCode TSMonitorLGSNESIterations(TS ts,PetscInt n,PetscReal ptime,Vec v,void *monctx) 4181 { 4182 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 4183 PetscReal x = ptime,y; 4184 PetscErrorCode ierr; 4185 PetscInt its; 4186 4187 PetscFunctionBegin; 4188 if (!n) { 4189 PetscDrawAxis axis; 4190 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 4191 ierr = PetscDrawAxisSetLabels(axis,"Nonlinear iterations as function of time","Time","SNES Iterations");CHKERRQ(ierr); 4192 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 4193 ctx->snes_its = 0; 4194 } 4195 ierr = TSGetSNESIterations(ts,&its);CHKERRQ(ierr); 4196 y = its - ctx->snes_its; 4197 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 4198 if (((ctx->howoften > 0) && (!(n % ctx->howoften)) && (n > -1)) || ((ctx->howoften == -1) && (n == -1))){ 4199 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 4200 } 4201 ctx->snes_its = its; 4202 PetscFunctionReturn(0); 4203 } 4204 4205 #undef __FUNCT__ 4206 #define __FUNCT__ "TSMonitorLGKSPIterations" 4207 PetscErrorCode TSMonitorLGKSPIterations(TS ts,PetscInt n,PetscReal ptime,Vec v,void *monctx) 4208 { 4209 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 4210 PetscReal x = ptime,y; 4211 PetscErrorCode ierr; 4212 PetscInt its; 4213 4214 PetscFunctionBegin; 4215 if (!n) { 4216 PetscDrawAxis axis; 4217 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 4218 ierr = PetscDrawAxisSetLabels(axis,"Linear iterations as function of time","Time","KSP Iterations");CHKERRQ(ierr); 4219 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 4220 ctx->ksp_its = 0; 4221 } 4222 ierr = TSGetKSPIterations(ts,&its);CHKERRQ(ierr); 4223 y = its - ctx->ksp_its; 4224 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 4225 if (((ctx->howoften > 0) && (!(n % ctx->howoften)) && (n > -1)) || ((ctx->howoften == -1) && (n == -1))){ 4226 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 4227 } 4228 ctx->ksp_its = its; 4229 PetscFunctionReturn(0); 4230 } 4231 4232 #undef __FUNCT__ 4233 #define __FUNCT__ "TSComputeLinearStability" 4234 /*@ 4235 TSComputeLinearStability - computes the linear stability function at a point 4236 4237 Collective on TS and Vec 4238 4239 Input Parameters: 4240 + ts - the TS context 4241 - xr,xi - real and imaginary part of input arguments 4242 4243 Output Parameters: 4244 . yr,yi - real and imaginary part of function value 4245 4246 Level: developer 4247 4248 .keywords: TS, compute 4249 4250 .seealso: TSSetRHSFunction(), TSComputeIFunction() 4251 @*/ 4252 PetscErrorCode TSComputeLinearStability(TS ts,PetscReal xr,PetscReal xi,PetscReal *yr,PetscReal *yi) 4253 { 4254 PetscErrorCode ierr; 4255 4256 PetscFunctionBegin; 4257 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4258 if (!ts->ops->linearstability) SETERRQ(((PetscObject)ts)->comm,PETSC_ERR_SUP,"Linearized stability function not provided for this method"); 4259 ierr = (*ts->ops->linearstability)(ts,xr,xi,yr,yi);CHKERRQ(ierr); 4260 PetscFunctionReturn(0); 4261 } 4262