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 1958 . time - current time 1959 . u - current iterate 1960 - mctx - [optional] monitoring context 1961 1962 Notes: 1963 This routine adds an additional monitor to the list of monitors that 1964 already has been loaded. 1965 1966 Fortran notes: Only a single monitor function can be set for each TS object 1967 1968 Level: intermediate 1969 1970 .keywords: TS, timestep, set, monitor 1971 1972 .seealso: TSMonitorDefault(), TSMonitorCancel() 1973 @*/ 1974 PetscErrorCode TSMonitorSet(TS ts,PetscErrorCode (*monitor)(TS,PetscInt,PetscReal,Vec,void*),void *mctx,PetscErrorCode (*mdestroy)(void**)) 1975 { 1976 PetscFunctionBegin; 1977 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1978 if (ts->numbermonitors >= MAXTSMONITORS) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Too many monitors set"); 1979 ts->monitor[ts->numbermonitors] = monitor; 1980 ts->monitordestroy[ts->numbermonitors] = mdestroy; 1981 ts->monitorcontext[ts->numbermonitors++] = (void*)mctx; 1982 PetscFunctionReturn(0); 1983 } 1984 1985 #undef __FUNCT__ 1986 #define __FUNCT__ "TSMonitorCancel" 1987 /*@C 1988 TSMonitorCancel - Clears all the monitors that have been set on a time-step object. 1989 1990 Logically Collective on TS 1991 1992 Input Parameters: 1993 . ts - the TS context obtained from TSCreate() 1994 1995 Notes: 1996 There is no way to remove a single, specific monitor. 1997 1998 Level: intermediate 1999 2000 .keywords: TS, timestep, set, monitor 2001 2002 .seealso: TSMonitorDefault(), TSMonitorSet() 2003 @*/ 2004 PetscErrorCode TSMonitorCancel(TS ts) 2005 { 2006 PetscErrorCode ierr; 2007 PetscInt i; 2008 2009 PetscFunctionBegin; 2010 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2011 for (i=0; i<ts->numbermonitors; i++) { 2012 if (ts->monitordestroy[i]) { 2013 ierr = (*ts->monitordestroy[i])(&ts->monitorcontext[i]);CHKERRQ(ierr); 2014 } 2015 } 2016 ts->numbermonitors = 0; 2017 PetscFunctionReturn(0); 2018 } 2019 2020 #undef __FUNCT__ 2021 #define __FUNCT__ "TSMonitorDefault" 2022 /*@ 2023 TSMonitorDefault - Sets the Default monitor 2024 2025 Level: intermediate 2026 2027 .keywords: TS, set, monitor 2028 2029 .seealso: TSMonitorDefault(), TSMonitorSet() 2030 @*/ 2031 PetscErrorCode TSMonitorDefault(TS ts,PetscInt step,PetscReal ptime,Vec v,void *dummy) 2032 { 2033 PetscErrorCode ierr; 2034 PetscViewer viewer = dummy ? (PetscViewer) dummy : PETSC_VIEWER_STDOUT_(((PetscObject)ts)->comm); 2035 2036 PetscFunctionBegin; 2037 ierr = PetscViewerASCIIAddTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 2038 ierr = PetscViewerASCIIPrintf(viewer,"%D TS dt %g time %g\n",step,(double)ts->time_step,(double)ptime);CHKERRQ(ierr); 2039 ierr = PetscViewerASCIISubtractTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 2040 PetscFunctionReturn(0); 2041 } 2042 2043 #undef __FUNCT__ 2044 #define __FUNCT__ "TSSetRetainStages" 2045 /*@ 2046 TSSetRetainStages - Request that all stages in the upcoming step be stored so that interpolation will be available. 2047 2048 Logically Collective on TS 2049 2050 Input Argument: 2051 . ts - time stepping context 2052 2053 Output Argument: 2054 . flg - PETSC_TRUE or PETSC_FALSE 2055 2056 Level: intermediate 2057 2058 .keywords: TS, set 2059 2060 .seealso: TSInterpolate(), TSSetPostStep() 2061 @*/ 2062 PetscErrorCode TSSetRetainStages(TS ts,PetscBool flg) 2063 { 2064 PetscFunctionBegin; 2065 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2066 ts->retain_stages = flg; 2067 PetscFunctionReturn(0); 2068 } 2069 2070 #undef __FUNCT__ 2071 #define __FUNCT__ "TSInterpolate" 2072 /*@ 2073 TSInterpolate - Interpolate the solution computed during the previous step to an arbitrary location in the interval 2074 2075 Collective on TS 2076 2077 Input Argument: 2078 + ts - time stepping context 2079 - t - time to interpolate to 2080 2081 Output Argument: 2082 . U - state at given time 2083 2084 Notes: 2085 The user should call TSSetRetainStages() before taking a step in which interpolation will be requested. 2086 2087 Level: intermediate 2088 2089 Developer Notes: 2090 TSInterpolate() and the storing of previous steps/stages should be generalized to support delay differential equations and continuous adjoints. 2091 2092 .keywords: TS, set 2093 2094 .seealso: TSSetRetainStages(), TSSetPostStep() 2095 @*/ 2096 PetscErrorCode TSInterpolate(TS ts,PetscReal t,Vec U) 2097 { 2098 PetscErrorCode ierr; 2099 2100 PetscFunctionBegin; 2101 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2102 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); 2103 if (!ts->ops->interpolate) SETERRQ1(((PetscObject)ts)->comm,PETSC_ERR_SUP,"%s does not provide interpolation",((PetscObject)ts)->type_name); 2104 ierr = (*ts->ops->interpolate)(ts,t,U);CHKERRQ(ierr); 2105 PetscFunctionReturn(0); 2106 } 2107 2108 #undef __FUNCT__ 2109 #define __FUNCT__ "TSStep" 2110 /*@ 2111 TSStep - Steps one time step 2112 2113 Collective on TS 2114 2115 Input Parameter: 2116 . ts - the TS context obtained from TSCreate() 2117 2118 Level: intermediate 2119 2120 Notes: 2121 The hook set using TSSetPreStep() is called before each attempt to take the step. In general, the time step size may 2122 be changed due to adaptive error controller or solve failures. Note that steps may contain multiple stages. 2123 2124 .keywords: TS, timestep, solve 2125 2126 .seealso: TSCreate(), TSSetUp(), TSDestroy(), TSSolve(), TSSetPreStep(), TSSetPreStage() 2127 @*/ 2128 PetscErrorCode TSStep(TS ts) 2129 { 2130 PetscReal ptime_prev; 2131 PetscErrorCode ierr; 2132 2133 PetscFunctionBegin; 2134 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 2135 ierr = TSSetUp(ts);CHKERRQ(ierr); 2136 2137 ts->reason = TS_CONVERGED_ITERATING; 2138 2139 ptime_prev = ts->ptime; 2140 ierr = PetscLogEventBegin(TS_Step,ts,0,0,0);CHKERRQ(ierr); 2141 ierr = (*ts->ops->step)(ts);CHKERRQ(ierr); 2142 ierr = PetscLogEventEnd(TS_Step,ts,0,0,0);CHKERRQ(ierr); 2143 ts->time_step_prev = ts->ptime - ptime_prev; 2144 2145 if (ts->reason < 0) { 2146 if (ts->errorifstepfailed) { 2147 if (ts->reason == TS_DIVERGED_NONLINEAR_SOLVE) { 2148 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]); 2149 } else SETERRQ1(((PetscObject)ts)->comm,PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s",TSConvergedReasons[ts->reason]); 2150 } 2151 } else if (!ts->reason) { 2152 if (ts->steps >= ts->max_steps) 2153 ts->reason = TS_CONVERGED_ITS; 2154 else if (ts->ptime >= ts->max_time) 2155 ts->reason = TS_CONVERGED_TIME; 2156 } 2157 2158 PetscFunctionReturn(0); 2159 } 2160 2161 #undef __FUNCT__ 2162 #define __FUNCT__ "TSEvaluateStep" 2163 /*@ 2164 TSEvaluateStep - Evaluate the solution at the end of a time step with a given order of accuracy. 2165 2166 Collective on TS 2167 2168 Input Arguments: 2169 + ts - time stepping context 2170 . order - desired order of accuracy 2171 - done - whether the step was evaluated at this order (pass PETSC_NULL to generate an error if not available) 2172 2173 Output Arguments: 2174 . U - state at the end of the current step 2175 2176 Level: advanced 2177 2178 Notes: 2179 This function cannot be called until all stages have been evaluated. 2180 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. 2181 2182 .seealso: TSStep(), TSAdapt 2183 @*/ 2184 PetscErrorCode TSEvaluateStep(TS ts,PetscInt order,Vec U,PetscBool *done) 2185 { 2186 PetscErrorCode ierr; 2187 2188 PetscFunctionBegin; 2189 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2190 PetscValidType(ts,1); 2191 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 2192 if (!ts->ops->evaluatestep) SETERRQ1(((PetscObject)ts)->comm,PETSC_ERR_SUP,"TSEvaluateStep not implemented for type '%s'",((PetscObject)ts)->type_name); 2193 ierr = (*ts->ops->evaluatestep)(ts,order,U,done);CHKERRQ(ierr); 2194 PetscFunctionReturn(0); 2195 } 2196 2197 #undef __FUNCT__ 2198 #define __FUNCT__ "TSSolve" 2199 /*@ 2200 TSSolve - Steps the requested number of timesteps. 2201 2202 Collective on TS 2203 2204 Input Parameter: 2205 + ts - the TS context obtained from TSCreate() 2206 - u - the solution vector 2207 2208 Output Parameter: 2209 . ftime - time of the state vector u upon completion 2210 2211 Level: beginner 2212 2213 Notes: 2214 The final time returned by this function may be different from the time of the internally 2215 held state accessible by TSGetSolution() and TSGetTime() because the method may have 2216 stepped over the final time. 2217 2218 .keywords: TS, timestep, solve 2219 2220 .seealso: TSCreate(), TSSetSolution(), TSStep() 2221 @*/ 2222 PetscErrorCode TSSolve(TS ts,Vec u,PetscReal *ftime) 2223 { 2224 PetscBool flg; 2225 char filename[PETSC_MAX_PATH_LEN]; 2226 PetscViewer viewer; 2227 PetscErrorCode ierr; 2228 2229 PetscFunctionBegin; 2230 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2231 PetscValidHeaderSpecific(u,VEC_CLASSID,2); 2232 if (ts->exact_final_time) { /* Need ts->vec_sol to be distinct so it is not overwritten when we interpolate at the end */ 2233 if (!ts->vec_sol || u == ts->vec_sol) { 2234 Vec y; 2235 ierr = VecDuplicate(u,&y);CHKERRQ(ierr); 2236 ierr = TSSetSolution(ts,y);CHKERRQ(ierr); 2237 ierr = VecDestroy(&y);CHKERRQ(ierr); /* grant ownership */ 2238 } 2239 ierr = VecCopy(u,ts->vec_sol);CHKERRQ(ierr); 2240 } else { 2241 ierr = TSSetSolution(ts,u);CHKERRQ(ierr); 2242 } 2243 ierr = TSSetUp(ts);CHKERRQ(ierr); 2244 /* reset time step and iteration counters */ 2245 ts->steps = 0; 2246 ts->ksp_its = 0; 2247 ts->snes_its = 0; 2248 ts->num_snes_failures = 0; 2249 ts->reject = 0; 2250 ts->reason = TS_CONVERGED_ITERATING; 2251 2252 if (ts->ops->solve) { /* This private interface is transitional and should be removed when all implementations are updated. */ 2253 ierr = (*ts->ops->solve)(ts);CHKERRQ(ierr); 2254 ierr = VecCopy(ts->vec_sol,u);CHKERRQ(ierr); 2255 if (ftime) *ftime = ts->ptime; 2256 } else { 2257 /* steps the requested number of timesteps. */ 2258 ierr = TSMonitor(ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 2259 if (ts->steps >= ts->max_steps) 2260 ts->reason = TS_CONVERGED_ITS; 2261 else if (ts->ptime >= ts->max_time) 2262 ts->reason = TS_CONVERGED_TIME; 2263 while (!ts->reason) { 2264 ierr = TSStep(ts);CHKERRQ(ierr); 2265 ierr = TSPostStep(ts);CHKERRQ(ierr); 2266 ierr = TSMonitor(ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 2267 } 2268 if (ts->exact_final_time && ts->ptime > ts->max_time) { 2269 ierr = TSInterpolate(ts,ts->max_time,u);CHKERRQ(ierr); 2270 if (ftime) *ftime = ts->max_time; 2271 } else { 2272 ierr = VecCopy(ts->vec_sol,u);CHKERRQ(ierr); 2273 if (ftime) *ftime = ts->ptime; 2274 } 2275 } 2276 ierr = TSMonitor(ts,-1,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 2277 ierr = PetscOptionsGetString(((PetscObject)ts)->prefix,"-ts_view",filename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr); 2278 if (flg && !PetscPreLoadingOn) { 2279 ierr = PetscViewerASCIIOpen(((PetscObject)ts)->comm,filename,&viewer);CHKERRQ(ierr); 2280 ierr = TSView(ts,viewer);CHKERRQ(ierr); 2281 ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr); 2282 } 2283 PetscFunctionReturn(0); 2284 } 2285 2286 #undef __FUNCT__ 2287 #define __FUNCT__ "TSMonitor" 2288 /*@ 2289 TSMonitor - Runs all user-provided monitor routines set using TSMonitorSet() 2290 2291 Collective on TS 2292 2293 Input Parameters: 2294 + ts - time stepping context obtained from TSCreate() 2295 . step - step number that has just completed 2296 . ptime - model time of the state 2297 - u - state at the current model time 2298 2299 Notes: 2300 TSMonitor() is typically used within the time stepping implementations. 2301 Users might call this function when using the TSStep() interface instead of TSSolve(). 2302 2303 Level: advanced 2304 2305 .keywords: TS, timestep 2306 @*/ 2307 PetscErrorCode TSMonitor(TS ts,PetscInt step,PetscReal ptime,Vec u) 2308 { 2309 PetscErrorCode ierr; 2310 PetscInt i,n = ts->numbermonitors; 2311 2312 PetscFunctionBegin; 2313 for (i=0; i<n; i++) { 2314 ierr = (*ts->monitor[i])(ts,step,ptime,u,ts->monitorcontext[i]);CHKERRQ(ierr); 2315 } 2316 PetscFunctionReturn(0); 2317 } 2318 2319 /* ------------------------------------------------------------------------*/ 2320 struct _n_TSMonitorLGCtx { 2321 PetscDrawLG lg; 2322 PetscInt howoften; /* when > 0 uses step % howoften, when negative only final solution plotted */ 2323 PetscInt ksp_its,snes_its; 2324 }; 2325 2326 2327 #undef __FUNCT__ 2328 #define __FUNCT__ "TSMonitorLGCtxCreate" 2329 /*@C 2330 TSMonitorLGCtxCreate - Creates a line graph context for use with 2331 TS to monitor the solution process graphically in various ways 2332 2333 Collective on TS 2334 2335 Input Parameters: 2336 + host - the X display to open, or null for the local machine 2337 . label - the title to put in the title bar 2338 . x, y - the screen coordinates of the upper left coordinate of the window 2339 . m, n - the screen width and height in pixels 2340 - howoften - if positive then determines the frequency of the plotting, if -1 then only at the final time 2341 2342 Output Parameter: 2343 . ctx - the context 2344 2345 Options Database Key: 2346 + -ts_monitor_lg_timestep - automatically sets line graph monitor 2347 . -ts_monitor_lg_solution - 2348 . -ts_monitor_lg_error - 2349 . -ts_monitor_lg_ksp_iterations - 2350 . -ts_monitor_lg_snes_iterations - 2351 - -lg_indicate_data_points <true,false> - indicate the data points (at each time step) on the plot; default is true 2352 2353 Notes: 2354 Use TSMonitorLGCtxDestroy() to destroy. 2355 2356 Level: intermediate 2357 2358 .keywords: TS, monitor, line graph, residual, seealso 2359 2360 .seealso: TSMonitorLGTimeStep(), TSMonitorSet(), TSMonitorLGSolution(), TSMonitorLGError() 2361 2362 @*/ 2363 PetscErrorCode TSMonitorLGCtxCreate(MPI_Comm comm,const char host[],const char label[],int x,int y,int m,int n,PetscInt howoften,TSMonitorLGCtx *ctx) 2364 { 2365 PetscDraw win; 2366 PetscErrorCode ierr; 2367 PetscBool flg = PETSC_TRUE; 2368 2369 PetscFunctionBegin; 2370 ierr = PetscNew(struct _n_TSMonitorLGCtx,ctx);CHKERRQ(ierr); 2371 ierr = PetscDrawCreate(comm,host,label,x,y,m,n,&win);CHKERRQ(ierr); 2372 ierr = PetscDrawSetFromOptions(win);CHKERRQ(ierr); 2373 ierr = PetscDrawLGCreate(win,1,&(*ctx)->lg);CHKERRQ(ierr); 2374 ierr = PetscOptionsGetBool(PETSC_NULL,"-lg_indicate_data_points",&flg,PETSC_NULL);CHKERRQ(ierr); 2375 if (flg) { 2376 ierr = PetscDrawLGIndicateDataPoints((*ctx)->lg);CHKERRQ(ierr); 2377 } 2378 ierr = PetscLogObjectParent((*ctx)->lg,win);CHKERRQ(ierr); 2379 (*ctx)->howoften = howoften; 2380 PetscFunctionReturn(0); 2381 } 2382 2383 #undef __FUNCT__ 2384 #define __FUNCT__ "TSMonitorLGTimeStep" 2385 PetscErrorCode TSMonitorLGTimeStep(TS ts,PetscInt n,PetscReal ptime,Vec v,void *monctx) 2386 { 2387 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 2388 PetscReal x = ptime,y; 2389 PetscErrorCode ierr; 2390 2391 PetscFunctionBegin; 2392 if (!n) { 2393 PetscDrawAxis axis; 2394 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 2395 ierr = PetscDrawAxisSetLabels(axis,"Timestep as function of time","Time","Time step");CHKERRQ(ierr); 2396 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 2397 } 2398 ierr = TSGetTimeStep(ts,&y);CHKERRQ(ierr); 2399 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 2400 if (((ctx->howoften > 0) && (!(n % ctx->howoften))) || ((ctx->howoften == -1) && (n == -1))){ 2401 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 2402 } 2403 PetscFunctionReturn(0); 2404 } 2405 2406 #undef __FUNCT__ 2407 #define __FUNCT__ "TSMonitorLGCtxDestroy" 2408 /*@C 2409 TSMonitorLGCtxDestroy - Destroys a line graph context that was created 2410 with TSMonitorLGCtxCreate(). 2411 2412 Collective on TSMonitorLGCtx 2413 2414 Input Parameter: 2415 . ctx - the monitor context 2416 2417 Level: intermediate 2418 2419 .keywords: TS, monitor, line graph, destroy 2420 2421 .seealso: TSMonitorLGCtxCreate(), TSMonitorSet(), TSMonitorLGTimeStep(); 2422 @*/ 2423 PetscErrorCode TSMonitorLGCtxDestroy(TSMonitorLGCtx *ctx) 2424 { 2425 PetscDraw draw; 2426 PetscErrorCode ierr; 2427 2428 PetscFunctionBegin; 2429 ierr = PetscDrawLGGetDraw((*ctx)->lg,&draw);CHKERRQ(ierr); 2430 ierr = PetscDrawDestroy(&draw);CHKERRQ(ierr); 2431 ierr = PetscDrawLGDestroy(&(*ctx)->lg);CHKERRQ(ierr); 2432 ierr = PetscFree(*ctx);CHKERRQ(ierr); 2433 PetscFunctionReturn(0); 2434 } 2435 2436 #undef __FUNCT__ 2437 #define __FUNCT__ "TSGetTime" 2438 /*@ 2439 TSGetTime - Gets the time of the most recently completed step. 2440 2441 Not Collective 2442 2443 Input Parameter: 2444 . ts - the TS context obtained from TSCreate() 2445 2446 Output Parameter: 2447 . t - the current time 2448 2449 Level: beginner 2450 2451 Note: 2452 When called during time step evaluation (e.g. during residual evaluation or via hooks set using TSSetPreStep(), 2453 TSSetPreStage(), or TSSetPostStep()), the time is the time at the start of the step being evaluated. 2454 2455 .seealso: TSSetInitialTimeStep(), TSGetTimeStep() 2456 2457 .keywords: TS, get, time 2458 @*/ 2459 PetscErrorCode TSGetTime(TS ts,PetscReal* t) 2460 { 2461 PetscFunctionBegin; 2462 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2463 PetscValidRealPointer(t,2); 2464 *t = ts->ptime; 2465 PetscFunctionReturn(0); 2466 } 2467 2468 #undef __FUNCT__ 2469 #define __FUNCT__ "TSSetTime" 2470 /*@ 2471 TSSetTime - Allows one to reset the time. 2472 2473 Logically Collective on TS 2474 2475 Input Parameters: 2476 + ts - the TS context obtained from TSCreate() 2477 - time - the time 2478 2479 Level: intermediate 2480 2481 .seealso: TSGetTime(), TSSetDuration() 2482 2483 .keywords: TS, set, time 2484 @*/ 2485 PetscErrorCode TSSetTime(TS ts, PetscReal t) 2486 { 2487 PetscFunctionBegin; 2488 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2489 PetscValidLogicalCollectiveReal(ts,t,2); 2490 ts->ptime = t; 2491 PetscFunctionReturn(0); 2492 } 2493 2494 #undef __FUNCT__ 2495 #define __FUNCT__ "TSSetOptionsPrefix" 2496 /*@C 2497 TSSetOptionsPrefix - Sets the prefix used for searching for all 2498 TS options in the database. 2499 2500 Logically Collective on TS 2501 2502 Input Parameter: 2503 + ts - The TS context 2504 - prefix - The prefix to prepend to all option names 2505 2506 Notes: 2507 A hyphen (-) must NOT be given at the beginning of the prefix name. 2508 The first character of all runtime options is AUTOMATICALLY the 2509 hyphen. 2510 2511 Level: advanced 2512 2513 .keywords: TS, set, options, prefix, database 2514 2515 .seealso: TSSetFromOptions() 2516 2517 @*/ 2518 PetscErrorCode TSSetOptionsPrefix(TS ts,const char prefix[]) 2519 { 2520 PetscErrorCode ierr; 2521 SNES snes; 2522 2523 PetscFunctionBegin; 2524 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2525 ierr = PetscObjectSetOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 2526 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 2527 ierr = SNESSetOptionsPrefix(snes,prefix);CHKERRQ(ierr); 2528 PetscFunctionReturn(0); 2529 } 2530 2531 2532 #undef __FUNCT__ 2533 #define __FUNCT__ "TSAppendOptionsPrefix" 2534 /*@C 2535 TSAppendOptionsPrefix - Appends to the prefix used for searching for all 2536 TS options in the database. 2537 2538 Logically Collective on TS 2539 2540 Input Parameter: 2541 + ts - The TS context 2542 - prefix - The prefix to prepend to all option names 2543 2544 Notes: 2545 A hyphen (-) must NOT be given at the beginning of the prefix name. 2546 The first character of all runtime options is AUTOMATICALLY the 2547 hyphen. 2548 2549 Level: advanced 2550 2551 .keywords: TS, append, options, prefix, database 2552 2553 .seealso: TSGetOptionsPrefix() 2554 2555 @*/ 2556 PetscErrorCode TSAppendOptionsPrefix(TS ts,const char prefix[]) 2557 { 2558 PetscErrorCode ierr; 2559 SNES snes; 2560 2561 PetscFunctionBegin; 2562 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2563 ierr = PetscObjectAppendOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 2564 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 2565 ierr = SNESAppendOptionsPrefix(snes,prefix);CHKERRQ(ierr); 2566 PetscFunctionReturn(0); 2567 } 2568 2569 #undef __FUNCT__ 2570 #define __FUNCT__ "TSGetOptionsPrefix" 2571 /*@C 2572 TSGetOptionsPrefix - Sets the prefix used for searching for all 2573 TS options in the database. 2574 2575 Not Collective 2576 2577 Input Parameter: 2578 . ts - The TS context 2579 2580 Output Parameter: 2581 . prefix - A pointer to the prefix string used 2582 2583 Notes: On the fortran side, the user should pass in a string 'prifix' of 2584 sufficient length to hold the prefix. 2585 2586 Level: intermediate 2587 2588 .keywords: TS, get, options, prefix, database 2589 2590 .seealso: TSAppendOptionsPrefix() 2591 @*/ 2592 PetscErrorCode TSGetOptionsPrefix(TS ts,const char *prefix[]) 2593 { 2594 PetscErrorCode ierr; 2595 2596 PetscFunctionBegin; 2597 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2598 PetscValidPointer(prefix,2); 2599 ierr = PetscObjectGetOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 2600 PetscFunctionReturn(0); 2601 } 2602 2603 #undef __FUNCT__ 2604 #define __FUNCT__ "TSGetRHSJacobian" 2605 /*@C 2606 TSGetRHSJacobian - Returns the Jacobian J at the present timestep. 2607 2608 Not Collective, but parallel objects are returned if TS is parallel 2609 2610 Input Parameter: 2611 . ts - The TS context obtained from TSCreate() 2612 2613 Output Parameters: 2614 + J - The Jacobian J of F, where U_t = G(U,t) 2615 . M - The preconditioner matrix, usually the same as J 2616 . func - Function to compute the Jacobian of the RHS 2617 - ctx - User-defined context for Jacobian evaluation routine 2618 2619 Notes: You can pass in PETSC_NULL for any return argument you do not need. 2620 2621 Level: intermediate 2622 2623 .seealso: TSGetTimeStep(), TSGetMatrices(), TSGetTime(), TSGetTimeStepNumber() 2624 2625 .keywords: TS, timestep, get, matrix, Jacobian 2626 @*/ 2627 PetscErrorCode TSGetRHSJacobian(TS ts,Mat *J,Mat *M,TSRHSJacobian *func,void **ctx) 2628 { 2629 PetscErrorCode ierr; 2630 SNES snes; 2631 DM dm; 2632 2633 PetscFunctionBegin; 2634 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 2635 ierr = SNESGetJacobian(snes,J,M,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); 2636 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 2637 ierr = DMTSGetRHSJacobian(dm,func,ctx);CHKERRQ(ierr); 2638 PetscFunctionReturn(0); 2639 } 2640 2641 #undef __FUNCT__ 2642 #define __FUNCT__ "TSGetIJacobian" 2643 /*@C 2644 TSGetIJacobian - Returns the implicit Jacobian at the present timestep. 2645 2646 Not Collective, but parallel objects are returned if TS is parallel 2647 2648 Input Parameter: 2649 . ts - The TS context obtained from TSCreate() 2650 2651 Output Parameters: 2652 + A - The Jacobian of F(t,U,U_t) 2653 . B - The preconditioner matrix, often the same as A 2654 . f - The function to compute the matrices 2655 - ctx - User-defined context for Jacobian evaluation routine 2656 2657 Notes: You can pass in PETSC_NULL for any return argument you do not need. 2658 2659 Level: advanced 2660 2661 .seealso: TSGetTimeStep(), TSGetRHSJacobian(), TSGetMatrices(), TSGetTime(), TSGetTimeStepNumber() 2662 2663 .keywords: TS, timestep, get, matrix, Jacobian 2664 @*/ 2665 PetscErrorCode TSGetIJacobian(TS ts,Mat *A,Mat *B,TSIJacobian *f,void **ctx) 2666 { 2667 PetscErrorCode ierr; 2668 SNES snes; 2669 DM dm; 2670 2671 PetscFunctionBegin; 2672 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 2673 ierr = SNESGetJacobian(snes,A,B,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); 2674 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 2675 ierr = DMTSGetIJacobian(dm,f,ctx);CHKERRQ(ierr); 2676 PetscFunctionReturn(0); 2677 } 2678 2679 struct _n_TSMonitorDrawCtx { 2680 PetscViewer viewer; 2681 Vec initialsolution; 2682 PetscBool showinitial; 2683 PetscInt howoften; /* when > 0 uses step % howoften, when negative only final solution plotted */ 2684 }; 2685 2686 #undef __FUNCT__ 2687 #define __FUNCT__ "TSMonitorDrawSolution" 2688 /*@C 2689 TSMonitorDrawSolution - Monitors progress of the TS solvers by calling 2690 VecView() for the solution at each timestep 2691 2692 Collective on TS 2693 2694 Input Parameters: 2695 + ts - the TS context 2696 . step - current time-step 2697 . ptime - current time 2698 - dummy - either a viewer or PETSC_NULL 2699 2700 Options Database: 2701 . -ts_monitor_draw_solution_initial - show initial solution as well as current solution 2702 2703 Notes: the initial solution and current solution are not displayed with a common axis scaling so generally the option -ts_monitor_draw_solution_initial 2704 will look bad 2705 2706 Level: intermediate 2707 2708 .keywords: TS, vector, monitor, view 2709 2710 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 2711 @*/ 2712 PetscErrorCode TSMonitorDrawSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 2713 { 2714 PetscErrorCode ierr; 2715 TSMonitorDrawCtx ictx = (TSMonitorDrawCtx)dummy; 2716 2717 PetscFunctionBegin; 2718 if (!step && ictx->showinitial) { 2719 if (!ictx->initialsolution) { 2720 ierr = VecDuplicate(u,&ictx->initialsolution);CHKERRQ(ierr); 2721 } 2722 ierr = VecCopy(u,ictx->initialsolution);CHKERRQ(ierr); 2723 } 2724 if (!(((ictx->howoften > 0) && (!(step % ictx->howoften)) && (step > -1)) || ((ictx->howoften == -1) && (step == -1)))) PetscFunctionReturn(0); 2725 2726 if (ictx->showinitial) { 2727 PetscReal pause; 2728 ierr = PetscViewerDrawGetPause(ictx->viewer,&pause);CHKERRQ(ierr); 2729 ierr = PetscViewerDrawSetPause(ictx->viewer,0.0);CHKERRQ(ierr); 2730 ierr = VecView(ictx->initialsolution,ictx->viewer);CHKERRQ(ierr); 2731 ierr = PetscViewerDrawSetPause(ictx->viewer,pause);CHKERRQ(ierr); 2732 ierr = PetscViewerDrawSetHold(ictx->viewer,PETSC_TRUE);CHKERRQ(ierr); 2733 } 2734 ierr = VecView(u,ictx->viewer);CHKERRQ(ierr); 2735 if (ictx->showinitial) { 2736 ierr = PetscViewerDrawSetHold(ictx->viewer,PETSC_FALSE);CHKERRQ(ierr); 2737 } 2738 PetscFunctionReturn(0); 2739 } 2740 2741 2742 #undef __FUNCT__ 2743 #define __FUNCT__ "TSMonitorDrawCtxDestroy" 2744 /*@C 2745 TSMonitorDrawCtxDestroy - Destroys the monitor context for TSMonitorDrawSolution() 2746 2747 Collective on TS 2748 2749 Input Parameters: 2750 . ctx - the monitor context 2751 2752 Level: intermediate 2753 2754 .keywords: TS, vector, monitor, view 2755 2756 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorDrawSolution(), TSMonitorDrawError() 2757 @*/ 2758 PetscErrorCode TSMonitorDrawCtxDestroy(TSMonitorDrawCtx *ictx) 2759 { 2760 PetscErrorCode ierr; 2761 2762 PetscFunctionBegin; 2763 ierr = PetscViewerDestroy(&(*ictx)->viewer);CHKERRQ(ierr); 2764 ierr = VecDestroy(&(*ictx)->initialsolution);CHKERRQ(ierr); 2765 ierr = PetscFree(*ictx);CHKERRQ(ierr); 2766 PetscFunctionReturn(0); 2767 } 2768 2769 #undef __FUNCT__ 2770 #define __FUNCT__ "TSMonitorDrawCtxCreate" 2771 /*@C 2772 TSMonitorDrawCtxCreate - Creates the monitor context for TSMonitorDrawCtx 2773 2774 Collective on TS 2775 2776 Input Parameter: 2777 . ts - time-step context 2778 2779 Output Patameter: 2780 . ctx - the monitor context 2781 2782 Options Database: 2783 . -ts_monitor_draw_solution_initial - show initial solution as well as current solution 2784 2785 Level: intermediate 2786 2787 .keywords: TS, vector, monitor, view 2788 2789 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorDrawCtx() 2790 @*/ 2791 PetscErrorCode TSMonitorDrawCtxCreate(MPI_Comm comm,const char host[],const char label[],int x,int y,int m,int n,PetscInt howoften,TSMonitorDrawCtx *ctx) 2792 { 2793 PetscErrorCode ierr; 2794 2795 PetscFunctionBegin; 2796 ierr = PetscNew(struct _n_TSMonitorDrawCtx,ctx);CHKERRQ(ierr); 2797 ierr = PetscViewerDrawOpen(comm,host,label,x,y,m,n,&(*ctx)->viewer);CHKERRQ(ierr); 2798 (*ctx)->showinitial = PETSC_FALSE; 2799 (*ctx)->howoften = howoften; 2800 ierr = PetscOptionsGetBool(PETSC_NULL,"-ts_monitor_draw_solution_initial",&(*ctx)->showinitial,PETSC_NULL);CHKERRQ(ierr); 2801 PetscFunctionReturn(0); 2802 } 2803 2804 #undef __FUNCT__ 2805 #define __FUNCT__ "TSMonitorDrawError" 2806 /*@C 2807 TSMonitorDrawError - Monitors progress of the TS solvers by calling 2808 VecView() for the error at each timestep 2809 2810 Collective on TS 2811 2812 Input Parameters: 2813 + ts - the TS context 2814 . step - current time-step 2815 . ptime - current time 2816 - dummy - either a viewer or PETSC_NULL 2817 2818 Level: intermediate 2819 2820 .keywords: TS, vector, monitor, view 2821 2822 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 2823 @*/ 2824 PetscErrorCode TSMonitorDrawError(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 2825 { 2826 PetscErrorCode ierr; 2827 TSMonitorDrawCtx ctx = (TSMonitorDrawCtx)dummy; 2828 PetscViewer viewer = ctx->viewer; 2829 Vec work; 2830 2831 PetscFunctionBegin; 2832 if (!(((ctx->howoften > 0) && (!(step % ctx->howoften)) && (step > -1)) || ((ctx->howoften == -1) && (step == -1)))) PetscFunctionReturn(0); 2833 ierr = VecDuplicate(u,&work);CHKERRQ(ierr); 2834 ierr = TSComputeSolutionFunction(ts,ptime,work);CHKERRQ(ierr); 2835 ierr = VecAXPY(work,-1.0,u);CHKERRQ(ierr); 2836 ierr = VecView(work,viewer);CHKERRQ(ierr); 2837 ierr = VecDestroy(&work);CHKERRQ(ierr); 2838 PetscFunctionReturn(0); 2839 } 2840 2841 #undef __FUNCT__ 2842 #define __FUNCT__ "TSSetDM" 2843 /*@ 2844 TSSetDM - Sets the DM that may be used by some preconditioners 2845 2846 Logically Collective on TS and DM 2847 2848 Input Parameters: 2849 + ts - the preconditioner context 2850 - dm - the dm 2851 2852 Level: intermediate 2853 2854 2855 .seealso: TSGetDM(), SNESSetDM(), SNESGetDM() 2856 @*/ 2857 PetscErrorCode TSSetDM(TS ts,DM dm) 2858 { 2859 PetscErrorCode ierr; 2860 SNES snes; 2861 TSDM tsdm; 2862 2863 PetscFunctionBegin; 2864 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2865 ierr = PetscObjectReference((PetscObject)dm);CHKERRQ(ierr); 2866 if (ts->dm) { /* Move the TSDM context over to the new DM unless the new DM already has one */ 2867 PetscContainer oldcontainer,container; 2868 ierr = PetscObjectQuery((PetscObject)ts->dm,"TSDM",(PetscObject*)&oldcontainer);CHKERRQ(ierr); 2869 ierr = PetscObjectQuery((PetscObject)dm,"TSDM",(PetscObject*)&container);CHKERRQ(ierr); 2870 if (oldcontainer && !container) { 2871 ierr = DMTSCopyContext(ts->dm,dm);CHKERRQ(ierr); 2872 ierr = DMTSGetContext(ts->dm,&tsdm);CHKERRQ(ierr); 2873 if (tsdm->originaldm == ts->dm) { /* Grant write privileges to the replacement DM */ 2874 tsdm->originaldm = dm; 2875 } 2876 } 2877 ierr = DMDestroy(&ts->dm);CHKERRQ(ierr); 2878 } 2879 ts->dm = dm; 2880 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 2881 ierr = SNESSetDM(snes,dm);CHKERRQ(ierr); 2882 PetscFunctionReturn(0); 2883 } 2884 2885 #undef __FUNCT__ 2886 #define __FUNCT__ "TSGetDM" 2887 /*@ 2888 TSGetDM - Gets the DM that may be used by some preconditioners 2889 2890 Not Collective 2891 2892 Input Parameter: 2893 . ts - the preconditioner context 2894 2895 Output Parameter: 2896 . dm - the dm 2897 2898 Level: intermediate 2899 2900 2901 .seealso: TSSetDM(), SNESSetDM(), SNESGetDM() 2902 @*/ 2903 PetscErrorCode TSGetDM(TS ts,DM *dm) 2904 { 2905 PetscErrorCode ierr; 2906 2907 PetscFunctionBegin; 2908 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2909 if (!ts->dm) { 2910 ierr = DMShellCreate(((PetscObject)ts)->comm,&ts->dm);CHKERRQ(ierr); 2911 if (ts->snes) {ierr = SNESSetDM(ts->snes,ts->dm);CHKERRQ(ierr);} 2912 } 2913 *dm = ts->dm; 2914 PetscFunctionReturn(0); 2915 } 2916 2917 #undef __FUNCT__ 2918 #define __FUNCT__ "SNESTSFormFunction" 2919 /*@ 2920 SNESTSFormFunction - Function to evaluate nonlinear residual 2921 2922 Logically Collective on SNES 2923 2924 Input Parameter: 2925 + snes - nonlinear solver 2926 . U - the current state at which to evaluate the residual 2927 - ctx - user context, must be a TS 2928 2929 Output Parameter: 2930 . F - the nonlinear residual 2931 2932 Notes: 2933 This function is not normally called by users and is automatically registered with the SNES used by TS. 2934 It is most frequently passed to MatFDColoringSetFunction(). 2935 2936 Level: advanced 2937 2938 .seealso: SNESSetFunction(), MatFDColoringSetFunction() 2939 @*/ 2940 PetscErrorCode SNESTSFormFunction(SNES snes,Vec U,Vec F,void *ctx) 2941 { 2942 TS ts = (TS)ctx; 2943 PetscErrorCode ierr; 2944 2945 PetscFunctionBegin; 2946 PetscValidHeaderSpecific(snes,SNES_CLASSID,1); 2947 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 2948 PetscValidHeaderSpecific(F,VEC_CLASSID,3); 2949 PetscValidHeaderSpecific(ts,TS_CLASSID,4); 2950 ierr = (ts->ops->snesfunction)(snes,U,F,ts);CHKERRQ(ierr); 2951 PetscFunctionReturn(0); 2952 } 2953 2954 #undef __FUNCT__ 2955 #define __FUNCT__ "SNESTSFormJacobian" 2956 /*@ 2957 SNESTSFormJacobian - Function to evaluate the Jacobian 2958 2959 Collective on SNES 2960 2961 Input Parameter: 2962 + snes - nonlinear solver 2963 . U - the current state at which to evaluate the residual 2964 - ctx - user context, must be a TS 2965 2966 Output Parameter: 2967 + A - the Jacobian 2968 . B - the preconditioning matrix (may be the same as A) 2969 - flag - indicates any structure change in the matrix 2970 2971 Notes: 2972 This function is not normally called by users and is automatically registered with the SNES used by TS. 2973 2974 Level: developer 2975 2976 .seealso: SNESSetJacobian() 2977 @*/ 2978 PetscErrorCode SNESTSFormJacobian(SNES snes,Vec U,Mat *A,Mat *B,MatStructure *flag,void *ctx) 2979 { 2980 TS ts = (TS)ctx; 2981 PetscErrorCode ierr; 2982 2983 PetscFunctionBegin; 2984 PetscValidHeaderSpecific(snes,SNES_CLASSID,1); 2985 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 2986 PetscValidPointer(A,3); 2987 PetscValidHeaderSpecific(*A,MAT_CLASSID,3); 2988 PetscValidPointer(B,4); 2989 PetscValidHeaderSpecific(*B,MAT_CLASSID,4); 2990 PetscValidPointer(flag,5); 2991 PetscValidHeaderSpecific(ts,TS_CLASSID,6); 2992 ierr = (ts->ops->snesjacobian)(snes,U,A,B,flag,ts);CHKERRQ(ierr); 2993 PetscFunctionReturn(0); 2994 } 2995 2996 #undef __FUNCT__ 2997 #define __FUNCT__ "TSComputeRHSFunctionLinear" 2998 /*@C 2999 TSComputeRHSFunctionLinear - Evaluate the right hand side via the user-provided Jacobian, for linear problems only 3000 3001 Collective on TS 3002 3003 Input Arguments: 3004 + ts - time stepping context 3005 . t - time at which to evaluate 3006 . U - state at which to evaluate 3007 - ctx - context 3008 3009 Output Arguments: 3010 . F - right hand side 3011 3012 Level: intermediate 3013 3014 Notes: 3015 This function is intended to be passed to TSSetRHSFunction() to evaluate the right hand side for linear problems. 3016 The matrix (and optionally the evaluation context) should be passed to TSSetRHSJacobian(). 3017 3018 .seealso: TSSetRHSFunction(), TSSetRHSJacobian(), TSComputeRHSJacobianConstant() 3019 @*/ 3020 PetscErrorCode TSComputeRHSFunctionLinear(TS ts,PetscReal t,Vec U,Vec F,void *ctx) 3021 { 3022 PetscErrorCode ierr; 3023 Mat Arhs,Brhs; 3024 MatStructure flg2; 3025 3026 PetscFunctionBegin; 3027 ierr = TSGetRHSMats_Private(ts,&Arhs,&Brhs);CHKERRQ(ierr); 3028 ierr = TSComputeRHSJacobian(ts,t,U,&Arhs,&Brhs,&flg2);CHKERRQ(ierr); 3029 ierr = MatMult(Arhs,U,F);CHKERRQ(ierr); 3030 PetscFunctionReturn(0); 3031 } 3032 3033 #undef __FUNCT__ 3034 #define __FUNCT__ "TSComputeRHSJacobianConstant" 3035 /*@C 3036 TSComputeRHSJacobianConstant - Reuses a Jacobian that is time-independent. 3037 3038 Collective on TS 3039 3040 Input Arguments: 3041 + ts - time stepping context 3042 . t - time at which to evaluate 3043 . U - state at which to evaluate 3044 - ctx - context 3045 3046 Output Arguments: 3047 + A - pointer to operator 3048 . B - pointer to preconditioning matrix 3049 - flg - matrix structure flag 3050 3051 Level: intermediate 3052 3053 Notes: 3054 This function is intended to be passed to TSSetRHSJacobian() to evaluate the Jacobian for linear time-independent problems. 3055 3056 .seealso: TSSetRHSFunction(), TSSetRHSJacobian(), TSComputeRHSFunctionLinear() 3057 @*/ 3058 PetscErrorCode TSComputeRHSJacobianConstant(TS ts,PetscReal t,Vec U,Mat *A,Mat *B,MatStructure *flg,void *ctx) 3059 { 3060 PetscFunctionBegin; 3061 *flg = SAME_PRECONDITIONER; 3062 PetscFunctionReturn(0); 3063 } 3064 3065 #undef __FUNCT__ 3066 #define __FUNCT__ "TSComputeIFunctionLinear" 3067 /*@C 3068 TSComputeIFunctionLinear - Evaluate the left hand side via the user-provided Jacobian, for linear problems only 3069 3070 Collective on TS 3071 3072 Input Arguments: 3073 + ts - time stepping context 3074 . t - time at which to evaluate 3075 . U - state at which to evaluate 3076 . Udot - time derivative of state vector 3077 - ctx - context 3078 3079 Output Arguments: 3080 . F - left hand side 3081 3082 Level: intermediate 3083 3084 Notes: 3085 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 3086 user is required to write their own TSComputeIFunction. 3087 This function is intended to be passed to TSSetIFunction() to evaluate the left hand side for linear problems. 3088 The matrix (and optionally the evaluation context) should be passed to TSSetIJacobian(). 3089 3090 .seealso: TSSetIFunction(), TSSetIJacobian(), TSComputeIJacobianConstant() 3091 @*/ 3092 PetscErrorCode TSComputeIFunctionLinear(TS ts,PetscReal t,Vec U,Vec Udot,Vec F,void *ctx) 3093 { 3094 PetscErrorCode ierr; 3095 Mat A,B; 3096 MatStructure flg2; 3097 3098 PetscFunctionBegin; 3099 ierr = TSGetIJacobian(ts,&A,&B,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); 3100 ierr = TSComputeIJacobian(ts,t,U,Udot,1.0,&A,&B,&flg2,PETSC_TRUE);CHKERRQ(ierr); 3101 ierr = MatMult(A,Udot,F);CHKERRQ(ierr); 3102 PetscFunctionReturn(0); 3103 } 3104 3105 #undef __FUNCT__ 3106 #define __FUNCT__ "TSComputeIJacobianConstant" 3107 /*@C 3108 TSComputeIJacobianConstant - Reuses a Jacobian that is time-independent. 3109 3110 Collective on TS 3111 3112 Input Arguments: 3113 + ts - time stepping context 3114 . t - time at which to evaluate 3115 . U - state at which to evaluate 3116 . Udot - time derivative of state vector 3117 . shift - shift to apply 3118 - ctx - context 3119 3120 Output Arguments: 3121 + A - pointer to operator 3122 . B - pointer to preconditioning matrix 3123 - flg - matrix structure flag 3124 3125 Level: intermediate 3126 3127 Notes: 3128 This function is intended to be passed to TSSetIJacobian() to evaluate the Jacobian for linear time-independent problems. 3129 3130 .seealso: TSSetIFunction(), TSSetIJacobian(), TSComputeIFunctionLinear() 3131 @*/ 3132 PetscErrorCode TSComputeIJacobianConstant(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat *A,Mat *B,MatStructure *flg,void *ctx) 3133 { 3134 PetscFunctionBegin; 3135 *flg = SAME_PRECONDITIONER; 3136 PetscFunctionReturn(0); 3137 } 3138 3139 3140 #undef __FUNCT__ 3141 #define __FUNCT__ "TSGetConvergedReason" 3142 /*@ 3143 TSGetConvergedReason - Gets the reason the TS iteration was stopped. 3144 3145 Not Collective 3146 3147 Input Parameter: 3148 . ts - the TS context 3149 3150 Output Parameter: 3151 . reason - negative value indicates diverged, positive value converged, see TSConvergedReason or the 3152 manual pages for the individual convergence tests for complete lists 3153 3154 Level: intermediate 3155 3156 Notes: 3157 Can only be called after the call to TSSolve() is complete. 3158 3159 .keywords: TS, nonlinear, set, convergence, test 3160 3161 .seealso: TSSetConvergenceTest(), TSConvergedReason 3162 @*/ 3163 PetscErrorCode TSGetConvergedReason(TS ts,TSConvergedReason *reason) 3164 { 3165 PetscFunctionBegin; 3166 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3167 PetscValidPointer(reason,2); 3168 *reason = ts->reason; 3169 PetscFunctionReturn(0); 3170 } 3171 3172 #undef __FUNCT__ 3173 #define __FUNCT__ "TSGetSNESIterations" 3174 /*@ 3175 TSGetSNESIterations - Gets the total number of nonlinear iterations 3176 used by the time integrator. 3177 3178 Not Collective 3179 3180 Input Parameter: 3181 . ts - TS context 3182 3183 Output Parameter: 3184 . nits - number of nonlinear iterations 3185 3186 Notes: 3187 This counter is reset to zero for each successive call to TSSolve(). 3188 3189 Level: intermediate 3190 3191 .keywords: TS, get, number, nonlinear, iterations 3192 3193 .seealso: TSGetKSPIterations() 3194 @*/ 3195 PetscErrorCode TSGetSNESIterations(TS ts,PetscInt *nits) 3196 { 3197 PetscFunctionBegin; 3198 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3199 PetscValidIntPointer(nits,2); 3200 *nits = ts->snes_its; 3201 PetscFunctionReturn(0); 3202 } 3203 3204 #undef __FUNCT__ 3205 #define __FUNCT__ "TSGetKSPIterations" 3206 /*@ 3207 TSGetKSPIterations - Gets the total number of linear iterations 3208 used by the time integrator. 3209 3210 Not Collective 3211 3212 Input Parameter: 3213 . ts - TS context 3214 3215 Output Parameter: 3216 . lits - number of linear iterations 3217 3218 Notes: 3219 This counter is reset to zero for each successive call to TSSolve(). 3220 3221 Level: intermediate 3222 3223 .keywords: TS, get, number, linear, iterations 3224 3225 .seealso: TSGetSNESIterations(), SNESGetKSPIterations() 3226 @*/ 3227 PetscErrorCode TSGetKSPIterations(TS ts,PetscInt *lits) 3228 { 3229 PetscFunctionBegin; 3230 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3231 PetscValidIntPointer(lits,2); 3232 *lits = ts->ksp_its; 3233 PetscFunctionReturn(0); 3234 } 3235 3236 #undef __FUNCT__ 3237 #define __FUNCT__ "TSGetStepRejections" 3238 /*@ 3239 TSGetStepRejections - Gets the total number of rejected steps. 3240 3241 Not Collective 3242 3243 Input Parameter: 3244 . ts - TS context 3245 3246 Output Parameter: 3247 . rejects - number of steps rejected 3248 3249 Notes: 3250 This counter is reset to zero for each successive call to TSSolve(). 3251 3252 Level: intermediate 3253 3254 .keywords: TS, get, number 3255 3256 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetSNESFailures(), TSSetMaxSNESFailures(), TSSetErrorIfStepFails() 3257 @*/ 3258 PetscErrorCode TSGetStepRejections(TS ts,PetscInt *rejects) 3259 { 3260 PetscFunctionBegin; 3261 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3262 PetscValidIntPointer(rejects,2); 3263 *rejects = ts->reject; 3264 PetscFunctionReturn(0); 3265 } 3266 3267 #undef __FUNCT__ 3268 #define __FUNCT__ "TSGetSNESFailures" 3269 /*@ 3270 TSGetSNESFailures - Gets the total number of failed SNES solves 3271 3272 Not Collective 3273 3274 Input Parameter: 3275 . ts - TS context 3276 3277 Output Parameter: 3278 . fails - number of failed nonlinear solves 3279 3280 Notes: 3281 This counter is reset to zero for each successive call to TSSolve(). 3282 3283 Level: intermediate 3284 3285 .keywords: TS, get, number 3286 3287 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSSetMaxSNESFailures() 3288 @*/ 3289 PetscErrorCode TSGetSNESFailures(TS ts,PetscInt *fails) 3290 { 3291 PetscFunctionBegin; 3292 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3293 PetscValidIntPointer(fails,2); 3294 *fails = ts->num_snes_failures; 3295 PetscFunctionReturn(0); 3296 } 3297 3298 #undef __FUNCT__ 3299 #define __FUNCT__ "TSSetMaxStepRejections" 3300 /*@ 3301 TSSetMaxStepRejections - Sets the maximum number of step rejections before a step fails 3302 3303 Not Collective 3304 3305 Input Parameter: 3306 + ts - TS context 3307 - rejects - maximum number of rejected steps, pass -1 for unlimited 3308 3309 Notes: 3310 The counter is reset to zero for each step 3311 3312 Options Database Key: 3313 . -ts_max_reject - Maximum number of step rejections before a step fails 3314 3315 Level: intermediate 3316 3317 .keywords: TS, set, maximum, number 3318 3319 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxSNESFailures(), TSGetStepRejections(), TSGetSNESFailures(), TSSetErrorIfStepFails(), TSGetConvergedReason() 3320 @*/ 3321 PetscErrorCode TSSetMaxStepRejections(TS ts,PetscInt rejects) 3322 { 3323 PetscFunctionBegin; 3324 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3325 ts->max_reject = rejects; 3326 PetscFunctionReturn(0); 3327 } 3328 3329 #undef __FUNCT__ 3330 #define __FUNCT__ "TSSetMaxSNESFailures" 3331 /*@ 3332 TSSetMaxSNESFailures - Sets the maximum number of failed SNES solves 3333 3334 Not Collective 3335 3336 Input Parameter: 3337 + ts - TS context 3338 - fails - maximum number of failed nonlinear solves, pass -1 for unlimited 3339 3340 Notes: 3341 The counter is reset to zero for each successive call to TSSolve(). 3342 3343 Options Database Key: 3344 . -ts_max_snes_failures - Maximum number of nonlinear solve failures 3345 3346 Level: intermediate 3347 3348 .keywords: TS, set, maximum, number 3349 3350 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSGetSNESFailures(), SNESGetConvergedReason(), TSGetConvergedReason() 3351 @*/ 3352 PetscErrorCode TSSetMaxSNESFailures(TS ts,PetscInt fails) 3353 { 3354 PetscFunctionBegin; 3355 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3356 ts->max_snes_failures = fails; 3357 PetscFunctionReturn(0); 3358 } 3359 3360 #undef __FUNCT__ 3361 #define __FUNCT__ "TSSetErrorIfStepFails()" 3362 /*@ 3363 TSSetErrorIfStepFails - Error if no step succeeds 3364 3365 Not Collective 3366 3367 Input Parameter: 3368 + ts - TS context 3369 - err - PETSC_TRUE to error if no step succeeds, PETSC_FALSE to return without failure 3370 3371 Options Database Key: 3372 . -ts_error_if_step_fails - Error if no step succeeds 3373 3374 Level: intermediate 3375 3376 .keywords: TS, set, error 3377 3378 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSGetSNESFailures(), TSSetErrorIfStepFails(), TSGetConvergedReason() 3379 @*/ 3380 PetscErrorCode TSSetErrorIfStepFails(TS ts,PetscBool err) 3381 { 3382 PetscFunctionBegin; 3383 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3384 ts->errorifstepfailed = err; 3385 PetscFunctionReturn(0); 3386 } 3387 3388 #undef __FUNCT__ 3389 #define __FUNCT__ "TSMonitorSolutionBinary" 3390 /*@C 3391 TSMonitorSolutionBinary - Monitors progress of the TS solvers by VecView() for the solution at each timestep. Normally the viewer is a binary file 3392 3393 Collective on TS 3394 3395 Input Parameters: 3396 + ts - the TS context 3397 . step - current time-step 3398 . ptime - current time 3399 . u - current state 3400 - viewer - binary viewer 3401 3402 Level: intermediate 3403 3404 .keywords: TS, vector, monitor, view 3405 3406 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 3407 @*/ 3408 PetscErrorCode TSMonitorSolutionBinary(TS ts,PetscInt step,PetscReal ptime,Vec u,void *viewer) 3409 { 3410 PetscErrorCode ierr; 3411 PetscViewer v = (PetscViewer)viewer; 3412 3413 PetscFunctionBegin; 3414 ierr = VecView(u,v);CHKERRQ(ierr); 3415 PetscFunctionReturn(0); 3416 } 3417 3418 #undef __FUNCT__ 3419 #define __FUNCT__ "TSMonitorSolutionVTK" 3420 /*@C 3421 TSMonitorSolutionVTK - Monitors progress of the TS solvers by VecView() for the solution at each timestep. 3422 3423 Collective on TS 3424 3425 Input Parameters: 3426 + ts - the TS context 3427 . step - current time-step 3428 . ptime - current time 3429 . u - current state 3430 - filenametemplate - string containing a format specifier for the integer time step (e.g. %03D) 3431 3432 Level: intermediate 3433 3434 Notes: 3435 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. 3436 These are named according to the file name template. 3437 3438 This function is normally passed as an argument to TSMonitorSet() along with TSMonitorSolutionVTKDestroy(). 3439 3440 .keywords: TS, vector, monitor, view 3441 3442 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 3443 @*/ 3444 PetscErrorCode TSMonitorSolutionVTK(TS ts,PetscInt step,PetscReal ptime,Vec u,void *filenametemplate) 3445 { 3446 PetscErrorCode ierr; 3447 char filename[PETSC_MAX_PATH_LEN]; 3448 PetscViewer viewer; 3449 3450 PetscFunctionBegin; 3451 ierr = PetscSNPrintf(filename,sizeof(filename),(const char*)filenametemplate,step);CHKERRQ(ierr); 3452 ierr = PetscViewerVTKOpen(((PetscObject)ts)->comm,filename,FILE_MODE_WRITE,&viewer);CHKERRQ(ierr); 3453 ierr = VecView(u,viewer);CHKERRQ(ierr); 3454 ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr); 3455 PetscFunctionReturn(0); 3456 } 3457 3458 #undef __FUNCT__ 3459 #define __FUNCT__ "TSMonitorSolutionVTKDestroy" 3460 /*@C 3461 TSMonitorSolutionVTKDestroy - Destroy context for monitoring 3462 3463 Collective on TS 3464 3465 Input Parameters: 3466 . filenametemplate - string containing a format specifier for the integer time step (e.g. %03D) 3467 3468 Level: intermediate 3469 3470 Note: 3471 This function is normally passed to TSMonitorSet() along with TSMonitorSolutionVTK(). 3472 3473 .keywords: TS, vector, monitor, view 3474 3475 .seealso: TSMonitorSet(), TSMonitorSolutionVTK() 3476 @*/ 3477 PetscErrorCode TSMonitorSolutionVTKDestroy(void *filenametemplate) 3478 { 3479 PetscErrorCode ierr; 3480 3481 PetscFunctionBegin; 3482 ierr = PetscFree(*(char**)filenametemplate);CHKERRQ(ierr); 3483 PetscFunctionReturn(0); 3484 } 3485 3486 #undef __FUNCT__ 3487 #define __FUNCT__ "TSGetAdapt" 3488 /*@ 3489 TSGetAdapt - Get the adaptive controller context for the current method 3490 3491 Collective on TS if controller has not been created yet 3492 3493 Input Arguments: 3494 . ts - time stepping context 3495 3496 Output Arguments: 3497 . adapt - adaptive controller 3498 3499 Level: intermediate 3500 3501 .seealso: TSAdapt, TSAdaptSetType(), TSAdaptChoose() 3502 @*/ 3503 PetscErrorCode TSGetAdapt(TS ts,TSAdapt *adapt) 3504 { 3505 PetscErrorCode ierr; 3506 3507 PetscFunctionBegin; 3508 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3509 PetscValidPointer(adapt,2); 3510 if (!ts->adapt) { 3511 ierr = TSAdaptCreate(((PetscObject)ts)->comm,&ts->adapt);CHKERRQ(ierr); 3512 ierr = PetscLogObjectParent(ts,ts->adapt);CHKERRQ(ierr); 3513 ierr = PetscObjectIncrementTabLevel((PetscObject)ts->adapt,(PetscObject)ts,1);CHKERRQ(ierr); 3514 } 3515 *adapt = ts->adapt; 3516 PetscFunctionReturn(0); 3517 } 3518 3519 #undef __FUNCT__ 3520 #define __FUNCT__ "TSSetTolerances" 3521 /*@ 3522 TSSetTolerances - Set tolerances for local truncation error when using adaptive controller 3523 3524 Logically Collective 3525 3526 Input Arguments: 3527 + ts - time integration context 3528 . atol - scalar absolute tolerances, PETSC_DECIDE to leave current value 3529 . vatol - vector of absolute tolerances or PETSC_NULL, used in preference to atol if present 3530 . rtol - scalar relative tolerances, PETSC_DECIDE to leave current value 3531 - vrtol - vector of relative tolerances or PETSC_NULL, used in preference to atol if present 3532 3533 Level: beginner 3534 3535 .seealso: TS, TSAdapt, TSVecNormWRMS(), TSGetTolerances() 3536 @*/ 3537 PetscErrorCode TSSetTolerances(TS ts,PetscReal atol,Vec vatol,PetscReal rtol,Vec vrtol) 3538 { 3539 PetscErrorCode ierr; 3540 3541 PetscFunctionBegin; 3542 if (atol != PETSC_DECIDE && atol != PETSC_DEFAULT) ts->atol = atol; 3543 if (vatol) { 3544 ierr = PetscObjectReference((PetscObject)vatol);CHKERRQ(ierr); 3545 ierr = VecDestroy(&ts->vatol);CHKERRQ(ierr); 3546 ts->vatol = vatol; 3547 } 3548 if (rtol != PETSC_DECIDE && rtol != PETSC_DEFAULT) ts->rtol = rtol; 3549 if (vrtol) { 3550 ierr = PetscObjectReference((PetscObject)vrtol);CHKERRQ(ierr); 3551 ierr = VecDestroy(&ts->vrtol);CHKERRQ(ierr); 3552 ts->vrtol = vrtol; 3553 } 3554 PetscFunctionReturn(0); 3555 } 3556 3557 #undef __FUNCT__ 3558 #define __FUNCT__ "TSGetTolerances" 3559 /*@ 3560 TSGetTolerances - Get tolerances for local truncation error when using adaptive controller 3561 3562 Logically Collective 3563 3564 Input Arguments: 3565 . ts - time integration context 3566 3567 Output Arguments: 3568 + atol - scalar absolute tolerances, PETSC_NULL to ignore 3569 . vatol - vector of absolute tolerances, PETSC_NULL to ignore 3570 . rtol - scalar relative tolerances, PETSC_NULL to ignore 3571 - vrtol - vector of relative tolerances, PETSC_NULL to ignore 3572 3573 Level: beginner 3574 3575 .seealso: TS, TSAdapt, TSVecNormWRMS(), TSSetTolerances() 3576 @*/ 3577 PetscErrorCode TSGetTolerances(TS ts,PetscReal *atol,Vec *vatol,PetscReal *rtol,Vec *vrtol) 3578 { 3579 PetscFunctionBegin; 3580 if (atol) *atol = ts->atol; 3581 if (vatol) *vatol = ts->vatol; 3582 if (rtol) *rtol = ts->rtol; 3583 if (vrtol) *vrtol = ts->vrtol; 3584 PetscFunctionReturn(0); 3585 } 3586 3587 #undef __FUNCT__ 3588 #define __FUNCT__ "TSErrorNormWRMS" 3589 /*@ 3590 TSErrorNormWRMS - compute a weighted norm of the difference between a vector and the current state 3591 3592 Collective on TS 3593 3594 Input Arguments: 3595 + ts - time stepping context 3596 - Y - state vector to be compared to ts->vec_sol 3597 3598 Output Arguments: 3599 . norm - weighted norm, a value of 1.0 is considered small 3600 3601 Level: developer 3602 3603 .seealso: TSSetTolerances() 3604 @*/ 3605 PetscErrorCode TSErrorNormWRMS(TS ts,Vec Y,PetscReal *norm) 3606 { 3607 PetscErrorCode ierr; 3608 PetscInt i,n,N; 3609 const PetscScalar *u,*y; 3610 Vec U; 3611 PetscReal sum,gsum; 3612 3613 PetscFunctionBegin; 3614 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3615 PetscValidHeaderSpecific(Y,VEC_CLASSID,2); 3616 PetscValidPointer(norm,3); 3617 U = ts->vec_sol; 3618 PetscCheckSameTypeAndComm(U,1,Y,2); 3619 if (U == Y) SETERRQ(((PetscObject)U)->comm,PETSC_ERR_ARG_IDN,"Y cannot be the TS solution vector"); 3620 3621 ierr = VecGetSize(U,&N);CHKERRQ(ierr); 3622 ierr = VecGetLocalSize(U,&n);CHKERRQ(ierr); 3623 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 3624 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 3625 sum = 0.; 3626 if (ts->vatol && ts->vrtol) { 3627 const PetscScalar *atol,*rtol; 3628 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 3629 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 3630 for (i=0; i<n; i++) { 3631 PetscReal tol = PetscRealPart(atol[i]) + PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 3632 sum += PetscSqr(PetscAbsScalar(y[i] - u[i]) / tol); 3633 } 3634 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 3635 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 3636 } else if (ts->vatol) { /* vector atol, scalar rtol */ 3637 const PetscScalar *atol; 3638 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 3639 for (i=0; i<n; i++) { 3640 PetscReal tol = PetscRealPart(atol[i]) + ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 3641 sum += PetscSqr(PetscAbsScalar(y[i] - u[i]) / tol); 3642 } 3643 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 3644 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 3645 const PetscScalar *rtol; 3646 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 3647 for (i=0; i<n; i++) { 3648 PetscReal tol = ts->atol + PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 3649 sum += PetscSqr(PetscAbsScalar(y[i] - u[i]) / tol); 3650 } 3651 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 3652 } else { /* scalar atol, scalar rtol */ 3653 for (i=0; i<n; i++) { 3654 PetscReal tol = ts->atol + ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 3655 sum += PetscSqr(PetscAbsScalar(y[i] - u[i]) / tol); 3656 } 3657 } 3658 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 3659 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 3660 3661 ierr = MPI_Allreduce(&sum,&gsum,1,MPIU_REAL,MPIU_SUM,((PetscObject)ts)->comm);CHKERRQ(ierr); 3662 *norm = PetscSqrtReal(gsum / N); 3663 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(((PetscObject)ts)->comm,PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 3664 PetscFunctionReturn(0); 3665 } 3666 3667 #undef __FUNCT__ 3668 #define __FUNCT__ "TSSetCFLTimeLocal" 3669 /*@ 3670 TSSetCFLTimeLocal - Set the local CFL constraint relative to forward Euler 3671 3672 Logically Collective on TS 3673 3674 Input Arguments: 3675 + ts - time stepping context 3676 - cfltime - maximum stable time step if using forward Euler (value can be different on each process) 3677 3678 Note: 3679 After calling this function, the global CFL time can be obtained by calling TSGetCFLTime() 3680 3681 Level: intermediate 3682 3683 .seealso: TSGetCFLTime(), TSADAPTCFL 3684 @*/ 3685 PetscErrorCode TSSetCFLTimeLocal(TS ts,PetscReal cfltime) 3686 { 3687 PetscFunctionBegin; 3688 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3689 ts->cfltime_local = cfltime; 3690 ts->cfltime = -1.; 3691 PetscFunctionReturn(0); 3692 } 3693 3694 #undef __FUNCT__ 3695 #define __FUNCT__ "TSGetCFLTime" 3696 /*@ 3697 TSGetCFLTime - Get the maximum stable time step according to CFL criteria applied to forward Euler 3698 3699 Collective on TS 3700 3701 Input Arguments: 3702 . ts - time stepping context 3703 3704 Output Arguments: 3705 . cfltime - maximum stable time step for forward Euler 3706 3707 Level: advanced 3708 3709 .seealso: TSSetCFLTimeLocal() 3710 @*/ 3711 PetscErrorCode TSGetCFLTime(TS ts,PetscReal *cfltime) 3712 { 3713 PetscErrorCode ierr; 3714 3715 PetscFunctionBegin; 3716 if (ts->cfltime < 0) { 3717 ierr = MPI_Allreduce(&ts->cfltime_local,&ts->cfltime,1,MPIU_REAL,MPIU_MIN,((PetscObject)ts)->comm);CHKERRQ(ierr); 3718 } 3719 *cfltime = ts->cfltime; 3720 PetscFunctionReturn(0); 3721 } 3722 3723 #undef __FUNCT__ 3724 #define __FUNCT__ "TSVISetVariableBounds" 3725 /*@ 3726 TSVISetVariableBounds - Sets the lower and upper bounds for the solution vector. xl <= x <= xu 3727 3728 Input Parameters: 3729 . ts - the TS context. 3730 . xl - lower bound. 3731 . xu - upper bound. 3732 3733 Notes: 3734 If this routine is not called then the lower and upper bounds are set to 3735 SNES_VI_NINF and SNES_VI_INF respectively during SNESSetUp(). 3736 3737 Level: advanced 3738 3739 @*/ 3740 PetscErrorCode TSVISetVariableBounds(TS ts, Vec xl, Vec xu) 3741 { 3742 PetscErrorCode ierr; 3743 SNES snes; 3744 3745 PetscFunctionBegin; 3746 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 3747 ierr = SNESVISetVariableBounds(snes,xl,xu);CHKERRQ(ierr); 3748 PetscFunctionReturn(0); 3749 } 3750 3751 #if defined(PETSC_HAVE_MATLAB_ENGINE) 3752 #include <mex.h> 3753 3754 typedef struct {char *funcname; mxArray *ctx;} TSMatlabContext; 3755 3756 #undef __FUNCT__ 3757 #define __FUNCT__ "TSComputeFunction_Matlab" 3758 /* 3759 TSComputeFunction_Matlab - Calls the function that has been set with 3760 TSSetFunctionMatlab(). 3761 3762 Collective on TS 3763 3764 Input Parameters: 3765 + snes - the TS context 3766 - u - input vector 3767 3768 Output Parameter: 3769 . y - function vector, as set by TSSetFunction() 3770 3771 Notes: 3772 TSComputeFunction() is typically used within nonlinear solvers 3773 implementations, so most users would not generally call this routine 3774 themselves. 3775 3776 Level: developer 3777 3778 .keywords: TS, nonlinear, compute, function 3779 3780 .seealso: TSSetFunction(), TSGetFunction() 3781 */ 3782 PetscErrorCode TSComputeFunction_Matlab(TS snes,PetscReal time,Vec u,Vec udot,Vec y, void *ctx) 3783 { 3784 PetscErrorCode ierr; 3785 TSMatlabContext *sctx = (TSMatlabContext *)ctx; 3786 int nlhs = 1,nrhs = 7; 3787 mxArray *plhs[1],*prhs[7]; 3788 long long int lx = 0,lxdot = 0,ly = 0,ls = 0; 3789 3790 PetscFunctionBegin; 3791 PetscValidHeaderSpecific(snes,TS_CLASSID,1); 3792 PetscValidHeaderSpecific(u,VEC_CLASSID,3); 3793 PetscValidHeaderSpecific(udot,VEC_CLASSID,4); 3794 PetscValidHeaderSpecific(y,VEC_CLASSID,5); 3795 PetscCheckSameComm(snes,1,u,3); 3796 PetscCheckSameComm(snes,1,y,5); 3797 3798 ierr = PetscMemcpy(&ls,&snes,sizeof(snes));CHKERRQ(ierr); 3799 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 3800 ierr = PetscMemcpy(&lxdot,&udot,sizeof(udot));CHKERRQ(ierr); 3801 ierr = PetscMemcpy(&ly,&y,sizeof(u));CHKERRQ(ierr); 3802 prhs[0] = mxCreateDoubleScalar((double)ls); 3803 prhs[1] = mxCreateDoubleScalar(time); 3804 prhs[2] = mxCreateDoubleScalar((double)lx); 3805 prhs[3] = mxCreateDoubleScalar((double)lxdot); 3806 prhs[4] = mxCreateDoubleScalar((double)ly); 3807 prhs[5] = mxCreateString(sctx->funcname); 3808 prhs[6] = sctx->ctx; 3809 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSComputeFunctionInternal");CHKERRQ(ierr); 3810 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 3811 mxDestroyArray(prhs[0]); 3812 mxDestroyArray(prhs[1]); 3813 mxDestroyArray(prhs[2]); 3814 mxDestroyArray(prhs[3]); 3815 mxDestroyArray(prhs[4]); 3816 mxDestroyArray(prhs[5]); 3817 mxDestroyArray(plhs[0]); 3818 PetscFunctionReturn(0); 3819 } 3820 3821 3822 #undef __FUNCT__ 3823 #define __FUNCT__ "TSSetFunctionMatlab" 3824 /* 3825 TSSetFunctionMatlab - Sets the function evaluation routine and function 3826 vector for use by the TS routines in solving ODEs 3827 equations from MATLAB. Here the function is a string containing the name of a MATLAB function 3828 3829 Logically Collective on TS 3830 3831 Input Parameters: 3832 + ts - the TS context 3833 - func - function evaluation routine 3834 3835 Calling sequence of func: 3836 $ func (TS ts,PetscReal time,Vec u,Vec udot,Vec f,void *ctx); 3837 3838 Level: beginner 3839 3840 .keywords: TS, nonlinear, set, function 3841 3842 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 3843 */ 3844 PetscErrorCode TSSetFunctionMatlab(TS ts,const char *func,mxArray *ctx) 3845 { 3846 PetscErrorCode ierr; 3847 TSMatlabContext *sctx; 3848 3849 PetscFunctionBegin; 3850 /* currently sctx is memory bleed */ 3851 ierr = PetscMalloc(sizeof(TSMatlabContext),&sctx);CHKERRQ(ierr); 3852 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 3853 /* 3854 This should work, but it doesn't 3855 sctx->ctx = ctx; 3856 mexMakeArrayPersistent(sctx->ctx); 3857 */ 3858 sctx->ctx = mxDuplicateArray(ctx); 3859 ierr = TSSetIFunction(ts,PETSC_NULL,TSComputeFunction_Matlab,sctx);CHKERRQ(ierr); 3860 PetscFunctionReturn(0); 3861 } 3862 3863 #undef __FUNCT__ 3864 #define __FUNCT__ "TSComputeJacobian_Matlab" 3865 /* 3866 TSComputeJacobian_Matlab - Calls the function that has been set with 3867 TSSetJacobianMatlab(). 3868 3869 Collective on TS 3870 3871 Input Parameters: 3872 + ts - the TS context 3873 . u - input vector 3874 . A, B - the matrices 3875 - ctx - user context 3876 3877 Output Parameter: 3878 . flag - structure of the matrix 3879 3880 Level: developer 3881 3882 .keywords: TS, nonlinear, compute, function 3883 3884 .seealso: TSSetFunction(), TSGetFunction() 3885 @*/ 3886 PetscErrorCode TSComputeJacobian_Matlab(TS ts,PetscReal time,Vec u,Vec udot,PetscReal shift,Mat *A,Mat *B,MatStructure *flag, void *ctx) 3887 { 3888 PetscErrorCode ierr; 3889 TSMatlabContext *sctx = (TSMatlabContext *)ctx; 3890 int nlhs = 2,nrhs = 9; 3891 mxArray *plhs[2],*prhs[9]; 3892 long long int lx = 0,lxdot = 0,lA = 0,ls = 0, lB = 0; 3893 3894 PetscFunctionBegin; 3895 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3896 PetscValidHeaderSpecific(u,VEC_CLASSID,3); 3897 3898 /* call Matlab function in ctx with arguments u and y */ 3899 3900 ierr = PetscMemcpy(&ls,&ts,sizeof(ts));CHKERRQ(ierr); 3901 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 3902 ierr = PetscMemcpy(&lxdot,&udot,sizeof(u));CHKERRQ(ierr); 3903 ierr = PetscMemcpy(&lA,A,sizeof(u));CHKERRQ(ierr); 3904 ierr = PetscMemcpy(&lB,B,sizeof(u));CHKERRQ(ierr); 3905 prhs[0] = mxCreateDoubleScalar((double)ls); 3906 prhs[1] = mxCreateDoubleScalar((double)time); 3907 prhs[2] = mxCreateDoubleScalar((double)lx); 3908 prhs[3] = mxCreateDoubleScalar((double)lxdot); 3909 prhs[4] = mxCreateDoubleScalar((double)shift); 3910 prhs[5] = mxCreateDoubleScalar((double)lA); 3911 prhs[6] = mxCreateDoubleScalar((double)lB); 3912 prhs[7] = mxCreateString(sctx->funcname); 3913 prhs[8] = sctx->ctx; 3914 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSComputeJacobianInternal");CHKERRQ(ierr); 3915 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 3916 *flag = (MatStructure) mxGetScalar(plhs[1]);CHKERRQ(ierr); 3917 mxDestroyArray(prhs[0]); 3918 mxDestroyArray(prhs[1]); 3919 mxDestroyArray(prhs[2]); 3920 mxDestroyArray(prhs[3]); 3921 mxDestroyArray(prhs[4]); 3922 mxDestroyArray(prhs[5]); 3923 mxDestroyArray(prhs[6]); 3924 mxDestroyArray(prhs[7]); 3925 mxDestroyArray(plhs[0]); 3926 mxDestroyArray(plhs[1]); 3927 PetscFunctionReturn(0); 3928 } 3929 3930 3931 #undef __FUNCT__ 3932 #define __FUNCT__ "TSSetJacobianMatlab" 3933 /* 3934 TSSetJacobianMatlab - Sets the Jacobian function evaluation routine and two empty Jacobian matrices 3935 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 3936 3937 Logically Collective on TS 3938 3939 Input Parameters: 3940 + ts - the TS context 3941 . A,B - Jacobian matrices 3942 . func - function evaluation routine 3943 - ctx - user context 3944 3945 Calling sequence of func: 3946 $ flag = func (TS ts,PetscReal time,Vec u,Vec udot,Mat A,Mat B,void *ctx); 3947 3948 3949 Level: developer 3950 3951 .keywords: TS, nonlinear, set, function 3952 3953 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 3954 */ 3955 PetscErrorCode TSSetJacobianMatlab(TS ts,Mat A,Mat B,const char *func,mxArray *ctx) 3956 { 3957 PetscErrorCode ierr; 3958 TSMatlabContext *sctx; 3959 3960 PetscFunctionBegin; 3961 /* currently sctx is memory bleed */ 3962 ierr = PetscMalloc(sizeof(TSMatlabContext),&sctx);CHKERRQ(ierr); 3963 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 3964 /* 3965 This should work, but it doesn't 3966 sctx->ctx = ctx; 3967 mexMakeArrayPersistent(sctx->ctx); 3968 */ 3969 sctx->ctx = mxDuplicateArray(ctx); 3970 ierr = TSSetIJacobian(ts,A,B,TSComputeJacobian_Matlab,sctx);CHKERRQ(ierr); 3971 PetscFunctionReturn(0); 3972 } 3973 3974 #undef __FUNCT__ 3975 #define __FUNCT__ "TSMonitor_Matlab" 3976 /* 3977 TSMonitor_Matlab - Calls the function that has been set with TSMonitorSetMatlab(). 3978 3979 Collective on TS 3980 3981 .seealso: TSSetFunction(), TSGetFunction() 3982 @*/ 3983 PetscErrorCode TSMonitor_Matlab(TS ts,PetscInt it, PetscReal time,Vec u, void *ctx) 3984 { 3985 PetscErrorCode ierr; 3986 TSMatlabContext *sctx = (TSMatlabContext *)ctx; 3987 int nlhs = 1,nrhs = 6; 3988 mxArray *plhs[1],*prhs[6]; 3989 long long int lx = 0,ls = 0; 3990 3991 PetscFunctionBegin; 3992 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3993 PetscValidHeaderSpecific(u,VEC_CLASSID,4); 3994 3995 ierr = PetscMemcpy(&ls,&ts,sizeof(ts));CHKERRQ(ierr); 3996 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 3997 prhs[0] = mxCreateDoubleScalar((double)ls); 3998 prhs[1] = mxCreateDoubleScalar((double)it); 3999 prhs[2] = mxCreateDoubleScalar((double)time); 4000 prhs[3] = mxCreateDoubleScalar((double)lx); 4001 prhs[4] = mxCreateString(sctx->funcname); 4002 prhs[5] = sctx->ctx; 4003 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSMonitorInternal");CHKERRQ(ierr); 4004 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 4005 mxDestroyArray(prhs[0]); 4006 mxDestroyArray(prhs[1]); 4007 mxDestroyArray(prhs[2]); 4008 mxDestroyArray(prhs[3]); 4009 mxDestroyArray(prhs[4]); 4010 mxDestroyArray(plhs[0]); 4011 PetscFunctionReturn(0); 4012 } 4013 4014 4015 #undef __FUNCT__ 4016 #define __FUNCT__ "TSMonitorSetMatlab" 4017 /* 4018 TSMonitorSetMatlab - Sets the monitor function from Matlab 4019 4020 Level: developer 4021 4022 .keywords: TS, nonlinear, set, function 4023 4024 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 4025 */ 4026 PetscErrorCode TSMonitorSetMatlab(TS ts,const char *func,mxArray *ctx) 4027 { 4028 PetscErrorCode ierr; 4029 TSMatlabContext *sctx; 4030 4031 PetscFunctionBegin; 4032 /* currently sctx is memory bleed */ 4033 ierr = PetscMalloc(sizeof(TSMatlabContext),&sctx);CHKERRQ(ierr); 4034 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 4035 /* 4036 This should work, but it doesn't 4037 sctx->ctx = ctx; 4038 mexMakeArrayPersistent(sctx->ctx); 4039 */ 4040 sctx->ctx = mxDuplicateArray(ctx); 4041 ierr = TSMonitorSet(ts,TSMonitor_Matlab,sctx,PETSC_NULL);CHKERRQ(ierr); 4042 PetscFunctionReturn(0); 4043 } 4044 #endif 4045 4046 4047 4048 #undef __FUNCT__ 4049 #define __FUNCT__ "TSMonitorLGSolution" 4050 /*@C 4051 TSMonitorLGSolution - Monitors progress of the TS solvers by plotting each component of the solution vector 4052 in a time based line graph 4053 4054 Collective on TS 4055 4056 Input Parameters: 4057 + ts - the TS context 4058 . step - current time-step 4059 . ptime - current time 4060 - lg - a line graph object 4061 4062 Level: intermediate 4063 4064 Notes: each process in a parallel run displays its component solutions in a separate window 4065 4066 .keywords: TS, vector, monitor, view 4067 4068 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 4069 @*/ 4070 PetscErrorCode TSMonitorLGSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 4071 { 4072 PetscErrorCode ierr; 4073 TSMonitorLGCtx ctx = (TSMonitorLGCtx)dummy; 4074 const PetscScalar *yy; 4075 PetscInt dim; 4076 4077 PetscFunctionBegin; 4078 if (!step) { 4079 PetscDrawAxis axis; 4080 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 4081 ierr = PetscDrawAxisSetLabels(axis,"Solution as function of time","Time","Solution");CHKERRQ(ierr); 4082 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 4083 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 4084 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 4085 } 4086 ierr = VecGetArrayRead(u,&yy);CHKERRQ(ierr); 4087 #if defined(PETSC_USE_COMPLEX) 4088 { 4089 PetscReal *yreal; 4090 PetscInt i,n; 4091 ierr = VecGetLocalSize(u,&n);CHKERRQ(ierr); 4092 ierr = PetscMalloc(n*sizeof(PetscReal),&yreal);CHKERRQ(ierr); 4093 for (i=0; i<n; i++) yreal[i] = PetscRealPart(yy[i]); 4094 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yreal);CHKERRQ(ierr); 4095 ierr = PetscFree(yreal);CHKERRQ(ierr); 4096 } 4097 #else 4098 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yy);CHKERRQ(ierr); 4099 #endif 4100 ierr = VecRestoreArrayRead(u,&yy);CHKERRQ(ierr); 4101 if (((ctx->howoften > 0) && (!(step % ctx->howoften)) && (step > -1)) || ((ctx->howoften == -1) && (step == -1))){ 4102 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 4103 } 4104 PetscFunctionReturn(0); 4105 } 4106 4107 #undef __FUNCT__ 4108 #define __FUNCT__ "TSMonitorLGError" 4109 /*@C 4110 TSMonitorLGError - Monitors progress of the TS solvers by plotting each component of the solution vector 4111 in a time based line graph 4112 4113 Collective on TS 4114 4115 Input Parameters: 4116 + ts - the TS context 4117 . step - current time-step 4118 . ptime - current time 4119 - lg - a line graph object 4120 4121 Level: intermediate 4122 4123 Notes: 4124 Only for sequential solves. 4125 4126 The user must provide the solution using TSSetSolutionFunction() to use this monitor. 4127 4128 Options Database Keys: 4129 . -ts_monitor_lg_error - create a graphical monitor of error history 4130 4131 .keywords: TS, vector, monitor, view 4132 4133 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSSetSolutionFunction() 4134 @*/ 4135 PetscErrorCode TSMonitorLGError(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 4136 { 4137 PetscErrorCode ierr; 4138 TSMonitorLGCtx ctx = (TSMonitorLGCtx)dummy; 4139 const PetscScalar *yy; 4140 Vec y; 4141 PetscInt dim; 4142 4143 PetscFunctionBegin; 4144 if (!step) { 4145 PetscDrawAxis axis; 4146 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 4147 ierr = PetscDrawAxisSetLabels(axis,"Error in solution as function of time","Time","Solution");CHKERRQ(ierr); 4148 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 4149 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 4150 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 4151 } 4152 ierr = VecDuplicate(u,&y);CHKERRQ(ierr); 4153 ierr = TSComputeSolutionFunction(ts,ptime,y);CHKERRQ(ierr); 4154 ierr = VecAXPY(y,-1.0,u);CHKERRQ(ierr); 4155 ierr = VecGetArrayRead(y,&yy);CHKERRQ(ierr); 4156 #if defined(PETSC_USE_COMPLEX) 4157 { 4158 PetscReal *yreal; 4159 PetscInt i,n; 4160 ierr = VecGetLocalSize(y,&n);CHKERRQ(ierr); 4161 ierr = PetscMalloc(n*sizeof(PetscReal),&yreal);CHKERRQ(ierr); 4162 for (i=0; i<n; i++) yreal[i] = PetscRealPart(yy[i]); 4163 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yreal);CHKERRQ(ierr); 4164 ierr = PetscFree(yreal);CHKERRQ(ierr); 4165 } 4166 #else 4167 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yy);CHKERRQ(ierr); 4168 #endif 4169 ierr = VecRestoreArrayRead(y,&yy);CHKERRQ(ierr); 4170 ierr = VecDestroy(&y);CHKERRQ(ierr); 4171 if (((ctx->howoften > 0) && (!(step % ctx->howoften)) && (step > -1)) || ((ctx->howoften == -1) && (step == -1))){ 4172 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 4173 } 4174 PetscFunctionReturn(0); 4175 } 4176 4177 #undef __FUNCT__ 4178 #define __FUNCT__ "TSMonitorLGSNESIterations" 4179 PetscErrorCode TSMonitorLGSNESIterations(TS ts,PetscInt n,PetscReal ptime,Vec v,void *monctx) 4180 { 4181 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 4182 PetscReal x = ptime,y; 4183 PetscErrorCode ierr; 4184 PetscInt its; 4185 4186 PetscFunctionBegin; 4187 if (!n) { 4188 PetscDrawAxis axis; 4189 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 4190 ierr = PetscDrawAxisSetLabels(axis,"Nonlinear iterations as function of time","Time","SNES Iterations");CHKERRQ(ierr); 4191 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 4192 ctx->snes_its = 0; 4193 } 4194 ierr = TSGetSNESIterations(ts,&its);CHKERRQ(ierr); 4195 y = its - ctx->snes_its; 4196 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 4197 if (((ctx->howoften > 0) && (!(n % ctx->howoften)) && (n > -1)) || ((ctx->howoften == -1) && (n == -1))){ 4198 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 4199 } 4200 ctx->snes_its = its; 4201 PetscFunctionReturn(0); 4202 } 4203 4204 #undef __FUNCT__ 4205 #define __FUNCT__ "TSMonitorLGKSPIterations" 4206 PetscErrorCode TSMonitorLGKSPIterations(TS ts,PetscInt n,PetscReal ptime,Vec v,void *monctx) 4207 { 4208 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 4209 PetscReal x = ptime,y; 4210 PetscErrorCode ierr; 4211 PetscInt its; 4212 4213 PetscFunctionBegin; 4214 if (!n) { 4215 PetscDrawAxis axis; 4216 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 4217 ierr = PetscDrawAxisSetLabels(axis,"Linear iterations as function of time","Time","KSP Iterations");CHKERRQ(ierr); 4218 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 4219 ctx->ksp_its = 0; 4220 } 4221 ierr = TSGetKSPIterations(ts,&its);CHKERRQ(ierr); 4222 y = its - ctx->ksp_its; 4223 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 4224 if (((ctx->howoften > 0) && (!(n % ctx->howoften)) && (n > -1)) || ((ctx->howoften == -1) && (n == -1))){ 4225 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 4226 } 4227 ctx->ksp_its = its; 4228 PetscFunctionReturn(0); 4229 } 4230 4231 #undef __FUNCT__ 4232 #define __FUNCT__ "TSComputeLinearStability" 4233 /*@ 4234 TSComputeLinearStability - computes the linear stability function at a point 4235 4236 Collective on TS and Vec 4237 4238 Input Parameters: 4239 + ts - the TS context 4240 - xr,xi - real and imaginary part of input arguments 4241 4242 Output Parameters: 4243 . yr,yi - real and imaginary part of function value 4244 4245 Level: developer 4246 4247 .keywords: TS, compute 4248 4249 .seealso: TSSetRHSFunction(), TSComputeIFunction() 4250 @*/ 4251 PetscErrorCode TSComputeLinearStability(TS ts,PetscReal xr,PetscReal xi,PetscReal *yr,PetscReal *yi) 4252 { 4253 PetscErrorCode ierr; 4254 4255 PetscFunctionBegin; 4256 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4257 if (!ts->ops->linearstability) SETERRQ(((PetscObject)ts)->comm,PETSC_ERR_SUP,"Linearized stability function not provided for this method"); 4258 ierr = (*ts->ops->linearstability)(ts,xr,xi,yr,yi);CHKERRQ(ierr); 4259 PetscFunctionReturn(0); 4260 } 4261