1 2 #include <petsc/private/tsimpl.h> /*I "petscts.h" I*/ 3 #include <petscdmshell.h> 4 #include <petscdmda.h> 5 #include <petscviewer.h> 6 #include <petscdraw.h> 7 8 /* Logging support */ 9 PetscClassId TS_CLASSID, DMTS_CLASSID; 10 PetscLogEvent TS_Step, TS_PseudoComputeTimeStep, TS_FunctionEval, TS_JacobianEval; 11 12 const char *const TSExactFinalTimeOptions[] = {"STEPOVER","INTERPOLATE","MATCHSTEP","TSExactFinalTimeOption","TS_EXACTFINALTIME_",0}; 13 14 struct _n_TSMonitorDrawCtx { 15 PetscViewer viewer; 16 PetscDrawAxis axis; 17 Vec initialsolution; 18 PetscBool showinitial; 19 PetscInt howoften; /* when > 0 uses step % howoften, when negative only final solution plotted */ 20 PetscBool showtimestepandtime; 21 int color; 22 }; 23 24 #undef __FUNCT__ 25 #define __FUNCT__ "TSSetFromOptions" 26 /*@ 27 TSSetFromOptions - Sets various TS parameters from user options. 28 29 Collective on TS 30 31 Input Parameter: 32 . ts - the TS context obtained from TSCreate() 33 34 Options Database Keys: 35 + -ts_type <type> - TSEULER, TSBEULER, TSSUNDIALS, TSPSEUDO, TSCN, TSRK, TSTHETA, TSGL, TSSSP 36 . -ts_save_trajectory - checkpoint the solution at each time-step 37 . -ts_max_steps <maxsteps> - maximum number of time-steps to take 38 . -ts_final_time <time> - maximum time to compute to 39 . -ts_dt <dt> - initial time step 40 . -ts_exact_final_time <stepover,interpolate,matchstep> whether to stop at the exact given final time and how to compute the solution at that ti,e 41 . -ts_max_snes_failures <maxfailures> - Maximum number of nonlinear solve failures allowed 42 . -ts_max_reject <maxrejects> - Maximum number of step rejections before step fails 43 . -ts_error_if_step_fails <true,false> - Error if no step succeeds 44 . -ts_rtol <rtol> - relative tolerance for local truncation error 45 . -ts_atol <atol> Absolute tolerance for local truncation error 46 . -ts_adjoint_solve <yes,no> After solving the ODE/DAE solve the adjoint problem (requires -ts_save_trajectory) 47 . -ts_fd_color - Use finite differences with coloring to compute IJacobian 48 . -ts_monitor - print information at each timestep 49 . -ts_monitor_lg_timestep - Monitor timestep size graphically 50 . -ts_monitor_lg_solution - Monitor solution graphically 51 . -ts_monitor_lg_error - Monitor error graphically 52 . -ts_monitor_lg_snes_iterations - Monitor number nonlinear iterations for each timestep graphically 53 . -ts_monitor_lg_ksp_iterations - Monitor number nonlinear iterations for each timestep graphically 54 . -ts_monitor_sp_eig - Monitor eigenvalues of linearized operator graphically 55 . -ts_monitor_draw_solution - Monitor solution graphically 56 . -ts_monitor_draw_solution_phase <xleft,yleft,xright,yright> - Monitor solution graphically with phase diagram, requires problem with exactly 2 degrees of freedom 57 . -ts_monitor_draw_error - Monitor error graphically, requires use to have provided TSSetSolutionFunction() 58 . -ts_monitor_solution_binary <filename> - Save each solution to a binary file 59 . -ts_monitor_solution_vtk <filename.vts> - Save each time step to a binary file, use filename-%%03D.vts 60 - -ts_monitor_envelope - determine maximum and minimum value of each component of the solution over the solution time 61 62 Developer Note: We should unify all the -ts_monitor options in the way that -xxx_view has been unified 63 64 Level: beginner 65 66 .keywords: TS, timestep, set, options, database 67 68 .seealso: TSGetType() 69 @*/ 70 PetscErrorCode TSSetFromOptions(TS ts) 71 { 72 PetscBool opt,flg,tflg; 73 PetscErrorCode ierr; 74 PetscViewer monviewer; 75 char monfilename[PETSC_MAX_PATH_LEN]; 76 SNES snes; 77 TSAdapt adapt; 78 PetscReal time_step; 79 TSExactFinalTimeOption eftopt; 80 char dir[16]; 81 const char *defaultType; 82 char typeName[256]; 83 84 PetscFunctionBegin; 85 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 86 ierr = PetscObjectOptionsBegin((PetscObject)ts);CHKERRQ(ierr); 87 if (((PetscObject)ts)->type_name) defaultType = ((PetscObject)ts)->type_name; 88 else defaultType = TSEULER; 89 90 ierr = TSRegisterAll();CHKERRQ(ierr); 91 ierr = PetscOptionsFList("-ts_type", "TS method"," TSSetType", TSList, defaultType, typeName, 256, &opt);CHKERRQ(ierr); 92 if (opt) { 93 ierr = TSSetType(ts, typeName);CHKERRQ(ierr); 94 } else { 95 ierr = TSSetType(ts, defaultType);CHKERRQ(ierr); 96 } 97 98 /* Handle generic TS options */ 99 if (ts->trajectory) tflg = PETSC_TRUE; 100 else tflg = PETSC_FALSE; 101 ierr = PetscOptionsBool("-ts_save_trajectory","Save the solution at each timestep","TSSetSaveTrajectory",tflg,&tflg,NULL);CHKERRQ(ierr); 102 if (tflg) {ierr = TSSetSaveTrajectory(ts);CHKERRQ(ierr);} 103 if (ts->adjoint_solve) tflg = PETSC_TRUE; 104 else tflg = PETSC_FALSE; 105 ierr = PetscOptionsBool("-ts_adjoint_solve","Solve the adjoint problem immediately after solving the forward problem","",tflg,&tflg,&flg);CHKERRQ(ierr); 106 if (flg) { 107 ierr = TSSetSaveTrajectory(ts);CHKERRQ(ierr); 108 ts->adjoint_solve = tflg; 109 } 110 ierr = PetscOptionsInt("-ts_max_steps","Maximum number of time steps","TSSetDuration",ts->max_steps,&ts->max_steps,NULL);CHKERRQ(ierr); 111 ierr = PetscOptionsReal("-ts_final_time","Time to run to","TSSetDuration",ts->max_time,&ts->max_time,NULL);CHKERRQ(ierr); 112 ierr = PetscOptionsReal("-ts_init_time","Initial time","TSSetTime",ts->ptime,&ts->ptime,NULL);CHKERRQ(ierr); 113 ierr = PetscOptionsReal("-ts_dt","Initial time step","TSSetTimeStep",ts->time_step,&time_step,&flg);CHKERRQ(ierr); 114 if (flg) { 115 ierr = TSSetTimeStep(ts,time_step);CHKERRQ(ierr); 116 } 117 ierr = PetscOptionsEnum("-ts_exact_final_time","Option for handling of final time step","TSSetExactFinalTime",TSExactFinalTimeOptions,(PetscEnum)ts->exact_final_time,(PetscEnum*)&eftopt,&flg);CHKERRQ(ierr); 118 if (flg) {ierr = TSSetExactFinalTime(ts,eftopt);CHKERRQ(ierr);} 119 ierr = PetscOptionsInt("-ts_max_snes_failures","Maximum number of nonlinear solve failures","TSSetMaxSNESFailures",ts->max_snes_failures,&ts->max_snes_failures,NULL);CHKERRQ(ierr); 120 ierr = PetscOptionsInt("-ts_max_reject","Maximum number of step rejections before step fails","TSSetMaxStepRejections",ts->max_reject,&ts->max_reject,NULL);CHKERRQ(ierr); 121 ierr = PetscOptionsBool("-ts_error_if_step_fails","Error if no step succeeds","TSSetErrorIfStepFails",ts->errorifstepfailed,&ts->errorifstepfailed,NULL);CHKERRQ(ierr); 122 ierr = PetscOptionsReal("-ts_rtol","Relative tolerance for local truncation error","TSSetTolerances",ts->rtol,&ts->rtol,NULL);CHKERRQ(ierr); 123 ierr = PetscOptionsReal("-ts_atol","Absolute tolerance for local truncation error","TSSetTolerances",ts->atol,&ts->atol,NULL);CHKERRQ(ierr); 124 125 #if defined(PETSC_HAVE_SAWS) 126 { 127 PetscBool set; 128 flg = PETSC_FALSE; 129 ierr = PetscOptionsBool("-ts_saws_block","Block for SAWs memory snooper at end of TSSolve","PetscObjectSAWsBlock",((PetscObject)ts)->amspublishblock,&flg,&set);CHKERRQ(ierr); 130 if (set) { 131 ierr = PetscObjectSAWsSetBlock((PetscObject)ts,flg);CHKERRQ(ierr); 132 } 133 } 134 #endif 135 136 /* Monitor options */ 137 ierr = PetscOptionsString("-ts_monitor","Monitor timestep size","TSMonitorDefault","stdout",monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr); 138 if (flg) { 139 ierr = PetscViewerASCIIOpen(PetscObjectComm((PetscObject)ts),monfilename,&monviewer);CHKERRQ(ierr); 140 ierr = TSMonitorSet(ts,TSMonitorDefault,monviewer,(PetscErrorCode (*)(void**))PetscViewerDestroy);CHKERRQ(ierr); 141 } 142 ierr = PetscOptionsString("-ts_monitor_python","Use Python function","TSMonitorSet",0,monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr); 143 if (flg) {ierr = PetscPythonMonitorSet((PetscObject)ts,monfilename);CHKERRQ(ierr);} 144 145 ierr = PetscOptionsName("-ts_monitor_lg_timestep","Monitor timestep size graphically","TSMonitorLGTimeStep",&opt);CHKERRQ(ierr); 146 if (opt) { 147 TSMonitorLGCtx ctx; 148 PetscInt howoften = 1; 149 150 ierr = PetscOptionsInt("-ts_monitor_lg_timestep","Monitor timestep size graphically","TSMonitorLGTimeStep",howoften,&howoften,NULL);CHKERRQ(ierr); 151 ierr = TSMonitorLGCtxCreate(PetscObjectComm((PetscObject)ts),0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);CHKERRQ(ierr); 152 ierr = TSMonitorSet(ts,TSMonitorLGTimeStep,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 153 } 154 ierr = PetscOptionsName("-ts_monitor_lg_solution","Monitor solution graphically","TSMonitorLGSolution",&opt);CHKERRQ(ierr); 155 if (opt) { 156 TSMonitorLGCtx ctx; 157 PetscInt howoften = 1; 158 159 ierr = PetscOptionsInt("-ts_monitor_lg_solution","Monitor solution graphically","TSMonitorLGSolution",howoften,&howoften,NULL);CHKERRQ(ierr); 160 ierr = TSMonitorLGCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,600,400,howoften,&ctx);CHKERRQ(ierr); 161 ierr = TSMonitorSet(ts,TSMonitorLGSolution,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 162 } 163 ierr = PetscOptionsName("-ts_monitor_lg_error","Monitor error graphically","TSMonitorLGError",&opt);CHKERRQ(ierr); 164 if (opt) { 165 TSMonitorLGCtx ctx; 166 PetscInt howoften = 1; 167 168 ierr = PetscOptionsInt("-ts_monitor_lg_error","Monitor error graphically","TSMonitorLGError",howoften,&howoften,NULL);CHKERRQ(ierr); 169 ierr = TSMonitorLGCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,600,400,howoften,&ctx);CHKERRQ(ierr); 170 ierr = TSMonitorSet(ts,TSMonitorLGError,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 171 } 172 ierr = PetscOptionsName("-ts_monitor_lg_snes_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGSNESIterations",&opt);CHKERRQ(ierr); 173 if (opt) { 174 TSMonitorLGCtx ctx; 175 PetscInt howoften = 1; 176 177 ierr = PetscOptionsInt("-ts_monitor_lg_snes_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGSNESIterations",howoften,&howoften,NULL);CHKERRQ(ierr); 178 ierr = TSMonitorLGCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);CHKERRQ(ierr); 179 ierr = TSMonitorSet(ts,TSMonitorLGSNESIterations,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 180 } 181 ierr = PetscOptionsName("-ts_monitor_lg_ksp_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGKSPIterations",&opt);CHKERRQ(ierr); 182 if (opt) { 183 TSMonitorLGCtx ctx; 184 PetscInt howoften = 1; 185 186 ierr = PetscOptionsInt("-ts_monitor_lg_ksp_iterations","Monitor number nonlinear iterations for each timestep graphically","TSMonitorLGKSPIterations",howoften,&howoften,NULL);CHKERRQ(ierr); 187 ierr = TSMonitorLGCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,howoften,&ctx);CHKERRQ(ierr); 188 ierr = TSMonitorSet(ts,TSMonitorLGKSPIterations,ctx,(PetscErrorCode (*)(void**))TSMonitorLGCtxDestroy);CHKERRQ(ierr); 189 } 190 ierr = PetscOptionsName("-ts_monitor_sp_eig","Monitor eigenvalues of linearized operator graphically","TSMonitorSPEig",&opt);CHKERRQ(ierr); 191 if (opt) { 192 TSMonitorSPEigCtx ctx; 193 PetscInt howoften = 1; 194 195 ierr = PetscOptionsInt("-ts_monitor_sp_eig","Monitor eigenvalues of linearized operator graphically","TSMonitorSPEig",howoften,&howoften,NULL);CHKERRQ(ierr); 196 ierr = TSMonitorSPEigCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,600,400,howoften,&ctx);CHKERRQ(ierr); 197 ierr = TSMonitorSet(ts,TSMonitorSPEig,ctx,(PetscErrorCode (*)(void**))TSMonitorSPEigCtxDestroy);CHKERRQ(ierr); 198 } 199 opt = PETSC_FALSE; 200 ierr = PetscOptionsName("-ts_monitor_draw_solution","Monitor solution graphically","TSMonitorDrawSolution",&opt);CHKERRQ(ierr); 201 if (opt) { 202 TSMonitorDrawCtx ctx; 203 PetscInt howoften = 1; 204 205 ierr = PetscOptionsInt("-ts_monitor_draw_solution","Monitor solution graphically","TSMonitorDrawSolution",howoften,&howoften,NULL);CHKERRQ(ierr); 206 ierr = TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),0,0,PETSC_DECIDE,PETSC_DECIDE,600,400,howoften,&ctx);CHKERRQ(ierr); 207 ierr = TSMonitorSet(ts,TSMonitorDrawSolution,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);CHKERRQ(ierr); 208 } 209 opt = PETSC_FALSE; 210 ierr = PetscOptionsName("-ts_monitor_draw_solution_phase","Monitor solution graphically","TSMonitorDrawSolutionPhase",&opt);CHKERRQ(ierr); 211 if (opt) { 212 TSMonitorDrawCtx ctx; 213 PetscReal bounds[4]; 214 PetscInt n = 4; 215 PetscDraw draw; 216 217 ierr = PetscOptionsRealArray("-ts_monitor_draw_solution_phase","Monitor solution graphically","TSMonitorDrawSolutionPhase",bounds,&n,NULL);CHKERRQ(ierr); 218 if (n != 4) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Must provide bounding box of phase field"); 219 ierr = TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),0,0,PETSC_DECIDE,PETSC_DECIDE,600,400,1,&ctx);CHKERRQ(ierr); 220 ierr = PetscViewerDrawGetDraw(ctx->viewer,0,&draw);CHKERRQ(ierr); 221 ierr = PetscDrawClear(draw);CHKERRQ(ierr); 222 ierr = PetscDrawAxisCreate(draw,&ctx->axis);CHKERRQ(ierr); 223 ierr = PetscDrawAxisSetLimits(ctx->axis,bounds[0],bounds[2],bounds[1],bounds[3]);CHKERRQ(ierr); 224 ierr = PetscDrawAxisSetLabels(ctx->axis,"Phase Diagram","Variable 1","Variable 2");CHKERRQ(ierr); 225 ierr = PetscDrawAxisDraw(ctx->axis);CHKERRQ(ierr); 226 /* ierr = PetscDrawSetCoordinates(draw,bounds[0],bounds[1],bounds[2],bounds[3]);CHKERRQ(ierr); */ 227 ierr = TSMonitorSet(ts,TSMonitorDrawSolutionPhase,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);CHKERRQ(ierr); 228 } 229 opt = PETSC_FALSE; 230 ierr = PetscOptionsName("-ts_monitor_draw_error","Monitor error graphically","TSMonitorDrawError",&opt);CHKERRQ(ierr); 231 if (opt) { 232 TSMonitorDrawCtx ctx; 233 PetscInt howoften = 1; 234 235 ierr = PetscOptionsInt("-ts_monitor_draw_error","Monitor error graphically","TSMonitorDrawError",howoften,&howoften,NULL);CHKERRQ(ierr); 236 ierr = TSMonitorDrawCtxCreate(PetscObjectComm((PetscObject)ts),0,0,PETSC_DECIDE,PETSC_DECIDE,600,400,howoften,&ctx);CHKERRQ(ierr); 237 ierr = TSMonitorSet(ts,TSMonitorDrawError,ctx,(PetscErrorCode (*)(void**))TSMonitorDrawCtxDestroy);CHKERRQ(ierr); 238 } 239 opt = PETSC_FALSE; 240 ierr = PetscOptionsString("-ts_monitor_solution_binary","Save each solution to a binary file","TSMonitorSolutionBinary",0,monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr); 241 if (flg) { 242 PetscViewer ctx; 243 if (monfilename[0]) { 244 ierr = PetscViewerBinaryOpen(PetscObjectComm((PetscObject)ts),monfilename,FILE_MODE_WRITE,&ctx);CHKERRQ(ierr); 245 ierr = TSMonitorSet(ts,TSMonitorSolutionBinary,ctx,(PetscErrorCode (*)(void**))PetscViewerDestroy);CHKERRQ(ierr); 246 } else { 247 ctx = PETSC_VIEWER_BINARY_(PetscObjectComm((PetscObject)ts)); 248 ierr = TSMonitorSet(ts,TSMonitorSolutionBinary,ctx,(PetscErrorCode (*)(void**))NULL);CHKERRQ(ierr); 249 } 250 } 251 opt = PETSC_FALSE; 252 ierr = PetscOptionsString("-ts_monitor_solution_vtk","Save each time step to a binary file, use filename-%%03D.vts","TSMonitorSolutionVTK",0,monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr); 253 if (flg) { 254 const char *ptr,*ptr2; 255 char *filetemplate; 256 if (!monfilename[0]) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"-ts_monitor_solution_vtk requires a file template, e.g. filename-%%03D.vts"); 257 /* Do some cursory validation of the input. */ 258 ierr = PetscStrstr(monfilename,"%",(char**)&ptr);CHKERRQ(ierr); 259 if (!ptr) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"-ts_monitor_solution_vtk requires a file template, e.g. filename-%%03D.vts"); 260 for (ptr++; ptr && *ptr; ptr++) { 261 ierr = PetscStrchr("DdiouxX",*ptr,(char**)&ptr2);CHKERRQ(ierr); 262 if (!ptr2 && (*ptr < '0' || '9' < *ptr)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Invalid file template argument to -ts_monitor_solution_vtk, should look like filename-%%03D.vts"); 263 if (ptr2) break; 264 } 265 ierr = PetscStrallocpy(monfilename,&filetemplate);CHKERRQ(ierr); 266 ierr = TSMonitorSet(ts,TSMonitorSolutionVTK,filetemplate,(PetscErrorCode (*)(void**))TSMonitorSolutionVTKDestroy);CHKERRQ(ierr); 267 } 268 269 ierr = PetscOptionsString("-ts_monitor_dmda_ray","Display a ray of the solution","None","y=0",dir,16,&flg);CHKERRQ(ierr); 270 if (flg) { 271 TSMonitorDMDARayCtx *rayctx; 272 int ray = 0; 273 DMDADirection ddir; 274 DM da; 275 PetscMPIInt rank; 276 277 if (dir[1] != '=') SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Unknown ray %s",dir); 278 if (dir[0] == 'x') ddir = DMDA_X; 279 else if (dir[0] == 'y') ddir = DMDA_Y; 280 else SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Unknown ray %s",dir); 281 sscanf(dir+2,"%d",&ray); 282 283 ierr = PetscInfo2(((PetscObject)ts),"Displaying DMDA ray %c = %D\n",dir[0],ray);CHKERRQ(ierr); 284 ierr = PetscNew(&rayctx);CHKERRQ(ierr); 285 ierr = TSGetDM(ts,&da);CHKERRQ(ierr); 286 ierr = DMDAGetRay(da,ddir,ray,&rayctx->ray,&rayctx->scatter);CHKERRQ(ierr); 287 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)ts),&rank);CHKERRQ(ierr); 288 if (!rank) { 289 ierr = PetscViewerDrawOpen(PETSC_COMM_SELF,0,0,0,0,600,300,&rayctx->viewer);CHKERRQ(ierr); 290 } 291 rayctx->lgctx = NULL; 292 ierr = TSMonitorSet(ts,TSMonitorDMDARay,rayctx,TSMonitorDMDARayDestroy);CHKERRQ(ierr); 293 } 294 ierr = PetscOptionsString("-ts_monitor_lg_dmda_ray","Display a ray of the solution","None","x=0",dir,16,&flg);CHKERRQ(ierr); 295 if (flg) { 296 TSMonitorDMDARayCtx *rayctx; 297 int ray = 0; 298 DMDADirection ddir; 299 DM da; 300 PetscInt howoften = 1; 301 302 if (dir[1] != '=') SETERRQ1(PetscObjectComm((PetscObject) ts), PETSC_ERR_ARG_WRONG, "Malformed ray %s", dir); 303 if (dir[0] == 'x') ddir = DMDA_X; 304 else if (dir[0] == 'y') ddir = DMDA_Y; 305 else SETERRQ1(PetscObjectComm((PetscObject) ts), PETSC_ERR_ARG_WRONG, "Unknown ray direction %s", dir); 306 sscanf(dir+2, "%d", &ray); 307 308 ierr = PetscInfo2(((PetscObject) ts),"Displaying LG DMDA ray %c = %D\n", dir[0], ray);CHKERRQ(ierr); 309 ierr = PetscNew(&rayctx);CHKERRQ(ierr); 310 ierr = TSGetDM(ts, &da);CHKERRQ(ierr); 311 ierr = DMDAGetRay(da, ddir, ray, &rayctx->ray, &rayctx->scatter);CHKERRQ(ierr); 312 ierr = TSMonitorLGCtxCreate(PETSC_COMM_SELF,0,0,PETSC_DECIDE,PETSC_DECIDE,600,400,howoften,&rayctx->lgctx);CHKERRQ(ierr); 313 ierr = TSMonitorSet(ts, TSMonitorLGDMDARay, rayctx, TSMonitorDMDARayDestroy);CHKERRQ(ierr); 314 } 315 316 ierr = PetscOptionsName("-ts_monitor_envelope","Monitor maximum and minimum value of each component of the solution","TSMonitorEnvelope",&opt);CHKERRQ(ierr); 317 if (opt) { 318 TSMonitorEnvelopeCtx ctx; 319 320 ierr = TSMonitorEnvelopeCtxCreate(ts,&ctx);CHKERRQ(ierr); 321 ierr = TSMonitorSet(ts,TSMonitorEnvelope,ctx,(PetscErrorCode (*)(void**))TSMonitorEnvelopeCtxDestroy);CHKERRQ(ierr); 322 } 323 324 flg = PETSC_FALSE; 325 ierr = PetscOptionsBool("-ts_fd_color", "Use finite differences with coloring to compute IJacobian", "TSComputeJacobianDefaultColor", flg, &flg, NULL);CHKERRQ(ierr); 326 if (flg) { 327 DM dm; 328 DMTS tdm; 329 330 ierr = TSGetDM(ts, &dm);CHKERRQ(ierr); 331 ierr = DMGetDMTS(dm, &tdm);CHKERRQ(ierr); 332 tdm->ijacobianctx = NULL; 333 ierr = TSSetIJacobian(ts, NULL, NULL, TSComputeIJacobianDefaultColor, 0);CHKERRQ(ierr); 334 ierr = PetscInfo(ts, "Setting default finite difference coloring Jacobian matrix\n");CHKERRQ(ierr); 335 } 336 337 /* 338 This code is all wrong. One is creating objects inside the TSSetFromOptions() so if run with the options gui 339 will bleed memory. Also one is using a PetscOptionsBegin() inside a PetscOptionsBegin() 340 */ 341 ierr = TSGetAdapt(ts,&adapt);CHKERRQ(ierr); 342 ierr = TSAdaptSetFromOptions(PetscOptionsObject,adapt);CHKERRQ(ierr); 343 344 /* Handle specific TS options */ 345 if (ts->ops->setfromoptions) { 346 ierr = (*ts->ops->setfromoptions)(PetscOptionsObject,ts);CHKERRQ(ierr); 347 } 348 ierr = PetscOptionsEnd();CHKERRQ(ierr); 349 350 /* process any options handlers added with PetscObjectAddOptionsHandler() */ 351 ierr = PetscObjectProcessOptionsHandlers((PetscObject)ts);CHKERRQ(ierr); 352 353 if (ts->trajectory) { 354 ierr = TSTrajectorySetFromOptions(ts->trajectory);CHKERRQ(ierr); 355 } 356 357 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 358 if (snes) { 359 if (ts->problem_type == TS_LINEAR) {ierr = SNESSetType(snes,SNESKSPONLY);CHKERRQ(ierr);} 360 ierr = SNESSetFromOptions(ts->snes);CHKERRQ(ierr); 361 } 362 PetscFunctionReturn(0); 363 } 364 365 #undef __FUNCT__ 366 #define __FUNCT__ "TSSetSaveTrajectory" 367 /*@ 368 TSSetSaveTrajectory - Causes the TS to save its solutions as it iterates forward in time in a TSTrajectory object 369 370 Collective on TS 371 372 Input Parameters: 373 . ts - the TS context obtained from TSCreate() 374 375 376 Level: intermediate 377 378 .seealso: TSGetTrajectory(), TSAdjointSolve() 379 380 .keywords: TS, set, checkpoint, 381 @*/ 382 PetscErrorCode TSSetSaveTrajectory(TS ts) 383 { 384 PetscErrorCode ierr; 385 386 PetscFunctionBegin; 387 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 388 if (!ts->trajectory) { 389 ierr = TSTrajectoryCreate(PetscObjectComm((PetscObject)ts),&ts->trajectory);CHKERRQ(ierr); 390 ierr = TSTrajectorySetType(ts->trajectory,TSTRAJECTORYBASIC);CHKERRQ(ierr); 391 } 392 PetscFunctionReturn(0); 393 } 394 395 #undef __FUNCT__ 396 #define __FUNCT__ "TSComputeRHSJacobian" 397 /*@ 398 TSComputeRHSJacobian - Computes the Jacobian matrix that has been 399 set with TSSetRHSJacobian(). 400 401 Collective on TS and Vec 402 403 Input Parameters: 404 + ts - the TS context 405 . t - current timestep 406 - U - input vector 407 408 Output Parameters: 409 + A - Jacobian matrix 410 . B - optional preconditioning matrix 411 - flag - flag indicating matrix structure 412 413 Notes: 414 Most users should not need to explicitly call this routine, as it 415 is used internally within the nonlinear solvers. 416 417 See KSPSetOperators() for important information about setting the 418 flag parameter. 419 420 Level: developer 421 422 .keywords: SNES, compute, Jacobian, matrix 423 424 .seealso: TSSetRHSJacobian(), KSPSetOperators() 425 @*/ 426 PetscErrorCode TSComputeRHSJacobian(TS ts,PetscReal t,Vec U,Mat A,Mat B) 427 { 428 PetscErrorCode ierr; 429 PetscObjectState Ustate; 430 DM dm; 431 DMTS tsdm; 432 TSRHSJacobian rhsjacobianfunc; 433 void *ctx; 434 TSIJacobian ijacobianfunc; 435 TSRHSFunction rhsfunction; 436 437 PetscFunctionBegin; 438 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 439 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 440 PetscCheckSameComm(ts,1,U,3); 441 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 442 ierr = DMGetDMTS(dm,&tsdm);CHKERRQ(ierr); 443 ierr = DMTSGetRHSJacobian(dm,&rhsjacobianfunc,&ctx);CHKERRQ(ierr); 444 ierr = DMTSGetIJacobian(dm,&ijacobianfunc,NULL);CHKERRQ(ierr); 445 ierr = DMTSGetRHSFunction(dm,&rhsfunction,&ctx);CHKERRQ(ierr); 446 ierr = PetscObjectStateGet((PetscObject)U,&Ustate);CHKERRQ(ierr); 447 if (ts->rhsjacobian.time == t && (ts->problem_type == TS_LINEAR || (ts->rhsjacobian.X == U && ts->rhsjacobian.Xstate == Ustate)) && (rhsfunction != TSComputeRHSFunctionLinear)) { 448 PetscFunctionReturn(0); 449 } 450 451 if (!rhsjacobianfunc && !ijacobianfunc) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSJacobian() and / or TSSetIJacobian()"); 452 453 if (ts->rhsjacobian.reuse) { 454 ierr = MatShift(A,-ts->rhsjacobian.shift);CHKERRQ(ierr); 455 ierr = MatScale(A,1./ts->rhsjacobian.scale);CHKERRQ(ierr); 456 if (A != B) { 457 ierr = MatShift(B,-ts->rhsjacobian.shift);CHKERRQ(ierr); 458 ierr = MatScale(B,1./ts->rhsjacobian.scale);CHKERRQ(ierr); 459 } 460 ts->rhsjacobian.shift = 0; 461 ts->rhsjacobian.scale = 1.; 462 } 463 464 if (rhsjacobianfunc) { 465 ierr = PetscLogEventBegin(TS_JacobianEval,ts,U,A,B);CHKERRQ(ierr); 466 PetscStackPush("TS user Jacobian function"); 467 ierr = (*rhsjacobianfunc)(ts,t,U,A,B,ctx);CHKERRQ(ierr); 468 PetscStackPop; 469 ierr = PetscLogEventEnd(TS_JacobianEval,ts,U,A,B);CHKERRQ(ierr); 470 /* make sure user returned a correct Jacobian and preconditioner */ 471 PetscValidHeaderSpecific(A,MAT_CLASSID,4); 472 PetscValidHeaderSpecific(B,MAT_CLASSID,5); 473 } else { 474 ierr = MatZeroEntries(A);CHKERRQ(ierr); 475 if (A != B) {ierr = MatZeroEntries(B);CHKERRQ(ierr);} 476 } 477 ts->rhsjacobian.time = t; 478 ts->rhsjacobian.X = U; 479 ierr = PetscObjectStateGet((PetscObject)U,&ts->rhsjacobian.Xstate);CHKERRQ(ierr); 480 PetscFunctionReturn(0); 481 } 482 483 #undef __FUNCT__ 484 #define __FUNCT__ "TSComputeRHSFunction" 485 /*@ 486 TSComputeRHSFunction - Evaluates the right-hand-side function. 487 488 Collective on TS and Vec 489 490 Input Parameters: 491 + ts - the TS context 492 . t - current time 493 - U - state vector 494 495 Output Parameter: 496 . y - right hand side 497 498 Note: 499 Most users should not need to explicitly call this routine, as it 500 is used internally within the nonlinear solvers. 501 502 Level: developer 503 504 .keywords: TS, compute 505 506 .seealso: TSSetRHSFunction(), TSComputeIFunction() 507 @*/ 508 PetscErrorCode TSComputeRHSFunction(TS ts,PetscReal t,Vec U,Vec y) 509 { 510 PetscErrorCode ierr; 511 TSRHSFunction rhsfunction; 512 TSIFunction ifunction; 513 void *ctx; 514 DM dm; 515 516 PetscFunctionBegin; 517 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 518 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 519 PetscValidHeaderSpecific(y,VEC_CLASSID,4); 520 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 521 ierr = DMTSGetRHSFunction(dm,&rhsfunction,&ctx);CHKERRQ(ierr); 522 ierr = DMTSGetIFunction(dm,&ifunction,NULL);CHKERRQ(ierr); 523 524 if (!rhsfunction && !ifunction) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSFunction() and / or TSSetIFunction()"); 525 526 ierr = PetscLogEventBegin(TS_FunctionEval,ts,U,y,0);CHKERRQ(ierr); 527 if (rhsfunction) { 528 PetscStackPush("TS user right-hand-side function"); 529 ierr = (*rhsfunction)(ts,t,U,y,ctx);CHKERRQ(ierr); 530 PetscStackPop; 531 } else { 532 ierr = VecZeroEntries(y);CHKERRQ(ierr); 533 } 534 535 ierr = PetscLogEventEnd(TS_FunctionEval,ts,U,y,0);CHKERRQ(ierr); 536 PetscFunctionReturn(0); 537 } 538 539 #undef __FUNCT__ 540 #define __FUNCT__ "TSComputeSolutionFunction" 541 /*@ 542 TSComputeSolutionFunction - Evaluates the solution function. 543 544 Collective on TS and Vec 545 546 Input Parameters: 547 + ts - the TS context 548 - t - current time 549 550 Output Parameter: 551 . U - the solution 552 553 Note: 554 Most users should not need to explicitly call this routine, as it 555 is used internally within the nonlinear solvers. 556 557 Level: developer 558 559 .keywords: TS, compute 560 561 .seealso: TSSetSolutionFunction(), TSSetRHSFunction(), TSComputeIFunction() 562 @*/ 563 PetscErrorCode TSComputeSolutionFunction(TS ts,PetscReal t,Vec U) 564 { 565 PetscErrorCode ierr; 566 TSSolutionFunction solutionfunction; 567 void *ctx; 568 DM dm; 569 570 PetscFunctionBegin; 571 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 572 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 573 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 574 ierr = DMTSGetSolutionFunction(dm,&solutionfunction,&ctx);CHKERRQ(ierr); 575 576 if (solutionfunction) { 577 PetscStackPush("TS user solution function"); 578 ierr = (*solutionfunction)(ts,t,U,ctx);CHKERRQ(ierr); 579 PetscStackPop; 580 } 581 PetscFunctionReturn(0); 582 } 583 #undef __FUNCT__ 584 #define __FUNCT__ "TSComputeForcingFunction" 585 /*@ 586 TSComputeForcingFunction - Evaluates the forcing function. 587 588 Collective on TS and Vec 589 590 Input Parameters: 591 + ts - the TS context 592 - t - current time 593 594 Output Parameter: 595 . U - the function value 596 597 Note: 598 Most users should not need to explicitly call this routine, as it 599 is used internally within the nonlinear solvers. 600 601 Level: developer 602 603 .keywords: TS, compute 604 605 .seealso: TSSetSolutionFunction(), TSSetRHSFunction(), TSComputeIFunction() 606 @*/ 607 PetscErrorCode TSComputeForcingFunction(TS ts,PetscReal t,Vec U) 608 { 609 PetscErrorCode ierr, (*forcing)(TS,PetscReal,Vec,void*); 610 void *ctx; 611 DM dm; 612 613 PetscFunctionBegin; 614 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 615 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 616 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 617 ierr = DMTSGetForcingFunction(dm,&forcing,&ctx);CHKERRQ(ierr); 618 619 if (forcing) { 620 PetscStackPush("TS user forcing function"); 621 ierr = (*forcing)(ts,t,U,ctx);CHKERRQ(ierr); 622 PetscStackPop; 623 } 624 PetscFunctionReturn(0); 625 } 626 627 #undef __FUNCT__ 628 #define __FUNCT__ "TSGetRHSVec_Private" 629 static PetscErrorCode TSGetRHSVec_Private(TS ts,Vec *Frhs) 630 { 631 Vec F; 632 PetscErrorCode ierr; 633 634 PetscFunctionBegin; 635 *Frhs = NULL; 636 ierr = TSGetIFunction(ts,&F,NULL,NULL);CHKERRQ(ierr); 637 if (!ts->Frhs) { 638 ierr = VecDuplicate(F,&ts->Frhs);CHKERRQ(ierr); 639 } 640 *Frhs = ts->Frhs; 641 PetscFunctionReturn(0); 642 } 643 644 #undef __FUNCT__ 645 #define __FUNCT__ "TSGetRHSMats_Private" 646 static PetscErrorCode TSGetRHSMats_Private(TS ts,Mat *Arhs,Mat *Brhs) 647 { 648 Mat A,B; 649 PetscErrorCode ierr; 650 651 PetscFunctionBegin; 652 if (Arhs) *Arhs = NULL; 653 if (Brhs) *Brhs = NULL; 654 ierr = TSGetIJacobian(ts,&A,&B,NULL,NULL);CHKERRQ(ierr); 655 if (Arhs) { 656 if (!ts->Arhs) { 657 ierr = MatDuplicate(A,MAT_DO_NOT_COPY_VALUES,&ts->Arhs);CHKERRQ(ierr); 658 } 659 *Arhs = ts->Arhs; 660 } 661 if (Brhs) { 662 if (!ts->Brhs) { 663 if (A != B) { 664 ierr = MatDuplicate(B,MAT_DO_NOT_COPY_VALUES,&ts->Brhs);CHKERRQ(ierr); 665 } else { 666 ts->Brhs = ts->Arhs; 667 ierr = PetscObjectReference((PetscObject)ts->Arhs);CHKERRQ(ierr); 668 } 669 } 670 *Brhs = ts->Brhs; 671 } 672 PetscFunctionReturn(0); 673 } 674 675 #undef __FUNCT__ 676 #define __FUNCT__ "TSComputeIFunction" 677 /*@ 678 TSComputeIFunction - Evaluates the DAE residual written in implicit form F(t,U,Udot)=0 679 680 Collective on TS and Vec 681 682 Input Parameters: 683 + ts - the TS context 684 . t - current time 685 . U - state vector 686 . Udot - time derivative of state vector 687 - imex - flag indicates if the method is IMEX so that the RHSFunction should be kept separate 688 689 Output Parameter: 690 . Y - right hand side 691 692 Note: 693 Most users should not need to explicitly call this routine, as it 694 is used internally within the nonlinear solvers. 695 696 If the user did did not write their equations in implicit form, this 697 function recasts them in implicit form. 698 699 Level: developer 700 701 .keywords: TS, compute 702 703 .seealso: TSSetIFunction(), TSComputeRHSFunction() 704 @*/ 705 PetscErrorCode TSComputeIFunction(TS ts,PetscReal t,Vec U,Vec Udot,Vec Y,PetscBool imex) 706 { 707 PetscErrorCode ierr; 708 TSIFunction ifunction; 709 TSRHSFunction rhsfunction; 710 void *ctx; 711 DM dm; 712 713 PetscFunctionBegin; 714 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 715 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 716 PetscValidHeaderSpecific(Udot,VEC_CLASSID,4); 717 PetscValidHeaderSpecific(Y,VEC_CLASSID,5); 718 719 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 720 ierr = DMTSGetIFunction(dm,&ifunction,&ctx);CHKERRQ(ierr); 721 ierr = DMTSGetRHSFunction(dm,&rhsfunction,NULL);CHKERRQ(ierr); 722 723 if (!rhsfunction && !ifunction) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSFunction() and / or TSSetIFunction()"); 724 725 ierr = PetscLogEventBegin(TS_FunctionEval,ts,U,Udot,Y);CHKERRQ(ierr); 726 if (ifunction) { 727 PetscStackPush("TS user implicit function"); 728 ierr = (*ifunction)(ts,t,U,Udot,Y,ctx);CHKERRQ(ierr); 729 PetscStackPop; 730 } 731 if (imex) { 732 if (!ifunction) { 733 ierr = VecCopy(Udot,Y);CHKERRQ(ierr); 734 } 735 } else if (rhsfunction) { 736 if (ifunction) { 737 Vec Frhs; 738 ierr = TSGetRHSVec_Private(ts,&Frhs);CHKERRQ(ierr); 739 ierr = TSComputeRHSFunction(ts,t,U,Frhs);CHKERRQ(ierr); 740 ierr = VecAXPY(Y,-1,Frhs);CHKERRQ(ierr); 741 } else { 742 ierr = TSComputeRHSFunction(ts,t,U,Y);CHKERRQ(ierr); 743 ierr = VecAYPX(Y,-1,Udot);CHKERRQ(ierr); 744 } 745 } 746 ierr = PetscLogEventEnd(TS_FunctionEval,ts,U,Udot,Y);CHKERRQ(ierr); 747 PetscFunctionReturn(0); 748 } 749 750 #undef __FUNCT__ 751 #define __FUNCT__ "TSComputeIJacobian" 752 /*@ 753 TSComputeIJacobian - Evaluates the Jacobian of the DAE 754 755 Collective on TS and Vec 756 757 Input 758 Input Parameters: 759 + ts - the TS context 760 . t - current timestep 761 . U - state vector 762 . Udot - time derivative of state vector 763 . shift - shift to apply, see note below 764 - imex - flag indicates if the method is IMEX so that the RHSJacobian should be kept separate 765 766 Output Parameters: 767 + A - Jacobian matrix 768 . B - optional preconditioning matrix 769 - flag - flag indicating matrix structure 770 771 Notes: 772 If F(t,U,Udot)=0 is the DAE, the required Jacobian is 773 774 dF/dU + shift*dF/dUdot 775 776 Most users should not need to explicitly call this routine, as it 777 is used internally within the nonlinear solvers. 778 779 Level: developer 780 781 .keywords: TS, compute, Jacobian, matrix 782 783 .seealso: TSSetIJacobian() 784 @*/ 785 PetscErrorCode TSComputeIJacobian(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat A,Mat B,PetscBool imex) 786 { 787 PetscErrorCode ierr; 788 TSIJacobian ijacobian; 789 TSRHSJacobian rhsjacobian; 790 DM dm; 791 void *ctx; 792 793 PetscFunctionBegin; 794 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 795 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 796 PetscValidHeaderSpecific(Udot,VEC_CLASSID,4); 797 PetscValidPointer(A,6); 798 PetscValidHeaderSpecific(A,MAT_CLASSID,6); 799 PetscValidPointer(B,7); 800 PetscValidHeaderSpecific(B,MAT_CLASSID,7); 801 802 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 803 ierr = DMTSGetIJacobian(dm,&ijacobian,&ctx);CHKERRQ(ierr); 804 ierr = DMTSGetRHSJacobian(dm,&rhsjacobian,NULL);CHKERRQ(ierr); 805 806 if (!rhsjacobian && !ijacobian) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Must call TSSetRHSJacobian() and / or TSSetIJacobian()"); 807 808 ierr = PetscLogEventBegin(TS_JacobianEval,ts,U,A,B);CHKERRQ(ierr); 809 if (ijacobian) { 810 PetscStackPush("TS user implicit Jacobian"); 811 ierr = (*ijacobian)(ts,t,U,Udot,shift,A,B,ctx);CHKERRQ(ierr); 812 PetscStackPop; 813 /* make sure user returned a correct Jacobian and preconditioner */ 814 PetscValidHeaderSpecific(A,MAT_CLASSID,4); 815 PetscValidHeaderSpecific(B,MAT_CLASSID,5); 816 } 817 if (imex) { 818 if (!ijacobian) { /* system was written as Udot = G(t,U) */ 819 ierr = MatZeroEntries(A);CHKERRQ(ierr); 820 ierr = MatShift(A,shift);CHKERRQ(ierr); 821 if (A != B) { 822 ierr = MatZeroEntries(B);CHKERRQ(ierr); 823 ierr = MatShift(B,shift);CHKERRQ(ierr); 824 } 825 } 826 } else { 827 Mat Arhs = NULL,Brhs = NULL; 828 if (rhsjacobian) { 829 if (ijacobian) { 830 ierr = TSGetRHSMats_Private(ts,&Arhs,&Brhs);CHKERRQ(ierr); 831 } else { 832 ierr = TSGetIJacobian(ts,&Arhs,&Brhs,NULL,NULL);CHKERRQ(ierr); 833 } 834 ierr = TSComputeRHSJacobian(ts,t,U,Arhs,Brhs);CHKERRQ(ierr); 835 } 836 if (Arhs == A) { /* No IJacobian, so we only have the RHS matrix */ 837 ts->rhsjacobian.scale = -1; 838 ts->rhsjacobian.shift = shift; 839 ierr = MatScale(A,-1);CHKERRQ(ierr); 840 ierr = MatShift(A,shift);CHKERRQ(ierr); 841 if (A != B) { 842 ierr = MatScale(B,-1);CHKERRQ(ierr); 843 ierr = MatShift(B,shift);CHKERRQ(ierr); 844 } 845 } else if (Arhs) { /* Both IJacobian and RHSJacobian */ 846 MatStructure axpy = DIFFERENT_NONZERO_PATTERN; 847 if (!ijacobian) { /* No IJacobian provided, but we have a separate RHS matrix */ 848 ierr = MatZeroEntries(A);CHKERRQ(ierr); 849 ierr = MatShift(A,shift);CHKERRQ(ierr); 850 if (A != B) { 851 ierr = MatZeroEntries(B);CHKERRQ(ierr); 852 ierr = MatShift(B,shift);CHKERRQ(ierr); 853 } 854 } 855 ierr = MatAXPY(A,-1,Arhs,axpy);CHKERRQ(ierr); 856 if (A != B) { 857 ierr = MatAXPY(B,-1,Brhs,axpy);CHKERRQ(ierr); 858 } 859 } 860 } 861 ierr = PetscLogEventEnd(TS_JacobianEval,ts,U,A,B);CHKERRQ(ierr); 862 PetscFunctionReturn(0); 863 } 864 865 #undef __FUNCT__ 866 #define __FUNCT__ "TSSetRHSFunction" 867 /*@C 868 TSSetRHSFunction - Sets the routine for evaluating the function, 869 where U_t = G(t,u). 870 871 Logically Collective on TS 872 873 Input Parameters: 874 + ts - the TS context obtained from TSCreate() 875 . r - vector to put the computed right hand side (or NULL to have it created) 876 . f - routine for evaluating the right-hand-side function 877 - ctx - [optional] user-defined context for private data for the 878 function evaluation routine (may be NULL) 879 880 Calling sequence of func: 881 $ func (TS ts,PetscReal t,Vec u,Vec F,void *ctx); 882 883 + t - current timestep 884 . u - input vector 885 . F - function vector 886 - ctx - [optional] user-defined function context 887 888 Level: beginner 889 890 Notes: You must call this function or TSSetIFunction() to define your ODE. You cannot use this function when solving a DAE. 891 892 .keywords: TS, timestep, set, right-hand-side, function 893 894 .seealso: TSSetRHSJacobian(), TSSetIJacobian(), TSSetIFunction() 895 @*/ 896 PetscErrorCode TSSetRHSFunction(TS ts,Vec r,PetscErrorCode (*f)(TS,PetscReal,Vec,Vec,void*),void *ctx) 897 { 898 PetscErrorCode ierr; 899 SNES snes; 900 Vec ralloc = NULL; 901 DM dm; 902 903 PetscFunctionBegin; 904 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 905 if (r) PetscValidHeaderSpecific(r,VEC_CLASSID,2); 906 907 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 908 ierr = DMTSSetRHSFunction(dm,f,ctx);CHKERRQ(ierr); 909 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 910 if (!r && !ts->dm && ts->vec_sol) { 911 ierr = VecDuplicate(ts->vec_sol,&ralloc);CHKERRQ(ierr); 912 r = ralloc; 913 } 914 ierr = SNESSetFunction(snes,r,SNESTSFormFunction,ts);CHKERRQ(ierr); 915 ierr = VecDestroy(&ralloc);CHKERRQ(ierr); 916 PetscFunctionReturn(0); 917 } 918 919 #undef __FUNCT__ 920 #define __FUNCT__ "TSSetSolutionFunction" 921 /*@C 922 TSSetSolutionFunction - Provide a function that computes the solution of the ODE or DAE 923 924 Logically Collective on TS 925 926 Input Parameters: 927 + ts - the TS context obtained from TSCreate() 928 . f - routine for evaluating the solution 929 - ctx - [optional] user-defined context for private data for the 930 function evaluation routine (may be NULL) 931 932 Calling sequence of func: 933 $ func (TS ts,PetscReal t,Vec u,void *ctx); 934 935 + t - current timestep 936 . u - output vector 937 - ctx - [optional] user-defined function context 938 939 Notes: 940 This routine is used for testing accuracy of time integration schemes when you already know the solution. 941 If analytic solutions are not known for your system, consider using the Method of Manufactured Solutions to 942 create closed-form solutions with non-physical forcing terms. 943 944 For low-dimensional problems solved in serial, such as small discrete systems, TSMonitorLGError() can be used to monitor the error history. 945 946 Level: beginner 947 948 .keywords: TS, timestep, set, right-hand-side, function 949 950 .seealso: TSSetRHSJacobian(), TSSetIJacobian(), TSComputeSolutionFunction(), TSSetForcingFunction() 951 @*/ 952 PetscErrorCode TSSetSolutionFunction(TS ts,PetscErrorCode (*f)(TS,PetscReal,Vec,void*),void *ctx) 953 { 954 PetscErrorCode ierr; 955 DM dm; 956 957 PetscFunctionBegin; 958 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 959 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 960 ierr = DMTSSetSolutionFunction(dm,f,ctx);CHKERRQ(ierr); 961 PetscFunctionReturn(0); 962 } 963 964 #undef __FUNCT__ 965 #define __FUNCT__ "TSSetForcingFunction" 966 /*@C 967 TSSetForcingFunction - Provide a function that computes a forcing term for a ODE or PDE 968 969 Logically Collective on TS 970 971 Input Parameters: 972 + ts - the TS context obtained from TSCreate() 973 . f - routine for evaluating the forcing function 974 - ctx - [optional] user-defined context for private data for the 975 function evaluation routine (may be NULL) 976 977 Calling sequence of func: 978 $ func (TS ts,PetscReal t,Vec u,void *ctx); 979 980 + t - current timestep 981 . u - output vector 982 - ctx - [optional] user-defined function context 983 984 Notes: 985 This routine is useful for testing accuracy of time integration schemes when using the Method of Manufactured Solutions to 986 create closed-form solutions with a non-physical forcing term. 987 988 For low-dimensional problems solved in serial, such as small discrete systems, TSMonitorLGError() can be used to monitor the error history. 989 990 Level: beginner 991 992 .keywords: TS, timestep, set, right-hand-side, function 993 994 .seealso: TSSetRHSJacobian(), TSSetIJacobian(), TSComputeSolutionFunction(), TSSetSolutionFunction() 995 @*/ 996 PetscErrorCode TSSetForcingFunction(TS ts,PetscErrorCode (*f)(TS,PetscReal,Vec,void*),void *ctx) 997 { 998 PetscErrorCode ierr; 999 DM dm; 1000 1001 PetscFunctionBegin; 1002 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1003 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1004 ierr = DMTSSetForcingFunction(dm,f,ctx);CHKERRQ(ierr); 1005 PetscFunctionReturn(0); 1006 } 1007 1008 #undef __FUNCT__ 1009 #define __FUNCT__ "TSSetRHSJacobian" 1010 /*@C 1011 TSSetRHSJacobian - Sets the function to compute the Jacobian of G, 1012 where U_t = G(U,t), as well as the location to store the matrix. 1013 1014 Logically Collective on TS 1015 1016 Input Parameters: 1017 + ts - the TS context obtained from TSCreate() 1018 . Amat - (approximate) Jacobian matrix 1019 . Pmat - matrix from which preconditioner is to be constructed (usually the same as Amat) 1020 . f - the Jacobian evaluation routine 1021 - ctx - [optional] user-defined context for private data for the 1022 Jacobian evaluation routine (may be NULL) 1023 1024 Calling sequence of f: 1025 $ func (TS ts,PetscReal t,Vec u,Mat A,Mat B,void *ctx); 1026 1027 + t - current timestep 1028 . u - input vector 1029 . Amat - (approximate) Jacobian matrix 1030 . Pmat - matrix from which preconditioner is to be constructed (usually the same as Amat) 1031 - ctx - [optional] user-defined context for matrix evaluation routine 1032 1033 1034 Level: beginner 1035 1036 .keywords: TS, timestep, set, right-hand-side, Jacobian 1037 1038 .seealso: SNESComputeJacobianDefaultColor(), TSSetRHSFunction(), TSRHSJacobianSetReuse(), TSSetIJacobian() 1039 1040 @*/ 1041 PetscErrorCode TSSetRHSJacobian(TS ts,Mat Amat,Mat Pmat,TSRHSJacobian f,void *ctx) 1042 { 1043 PetscErrorCode ierr; 1044 SNES snes; 1045 DM dm; 1046 TSIJacobian ijacobian; 1047 1048 PetscFunctionBegin; 1049 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1050 if (Amat) PetscValidHeaderSpecific(Amat,MAT_CLASSID,2); 1051 if (Pmat) PetscValidHeaderSpecific(Pmat,MAT_CLASSID,3); 1052 if (Amat) PetscCheckSameComm(ts,1,Amat,2); 1053 if (Pmat) PetscCheckSameComm(ts,1,Pmat,3); 1054 1055 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1056 ierr = DMTSSetRHSJacobian(dm,f,ctx);CHKERRQ(ierr); 1057 if (f == TSComputeRHSJacobianConstant) { 1058 /* Handle this case automatically for the user; otherwise user should call themselves. */ 1059 ierr = TSRHSJacobianSetReuse(ts,PETSC_TRUE);CHKERRQ(ierr); 1060 } 1061 ierr = DMTSGetIJacobian(dm,&ijacobian,NULL);CHKERRQ(ierr); 1062 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1063 if (!ijacobian) { 1064 ierr = SNESSetJacobian(snes,Amat,Pmat,SNESTSFormJacobian,ts);CHKERRQ(ierr); 1065 } 1066 if (Amat) { 1067 ierr = PetscObjectReference((PetscObject)Amat);CHKERRQ(ierr); 1068 ierr = MatDestroy(&ts->Arhs);CHKERRQ(ierr); 1069 1070 ts->Arhs = Amat; 1071 } 1072 if (Pmat) { 1073 ierr = PetscObjectReference((PetscObject)Pmat);CHKERRQ(ierr); 1074 ierr = MatDestroy(&ts->Brhs);CHKERRQ(ierr); 1075 1076 ts->Brhs = Pmat; 1077 } 1078 PetscFunctionReturn(0); 1079 } 1080 1081 1082 #undef __FUNCT__ 1083 #define __FUNCT__ "TSSetIFunction" 1084 /*@C 1085 TSSetIFunction - Set the function to compute F(t,U,U_t) where F() = 0 is the DAE to be solved. 1086 1087 Logically Collective on TS 1088 1089 Input Parameters: 1090 + ts - the TS context obtained from TSCreate() 1091 . r - vector to hold the residual (or NULL to have it created internally) 1092 . f - the function evaluation routine 1093 - ctx - user-defined context for private data for the function evaluation routine (may be NULL) 1094 1095 Calling sequence of f: 1096 $ f(TS ts,PetscReal t,Vec u,Vec u_t,Vec F,ctx); 1097 1098 + t - time at step/stage being solved 1099 . u - state vector 1100 . u_t - time derivative of state vector 1101 . F - function vector 1102 - ctx - [optional] user-defined context for matrix evaluation routine 1103 1104 Important: 1105 The user MUST call either this routine or TSSetRHSFunction() to define the ODE. When solving DAEs you must use this function. 1106 1107 Level: beginner 1108 1109 .keywords: TS, timestep, set, DAE, Jacobian 1110 1111 .seealso: TSSetRHSJacobian(), TSSetRHSFunction(), TSSetIJacobian() 1112 @*/ 1113 PetscErrorCode TSSetIFunction(TS ts,Vec res,TSIFunction f,void *ctx) 1114 { 1115 PetscErrorCode ierr; 1116 SNES snes; 1117 Vec resalloc = NULL; 1118 DM dm; 1119 1120 PetscFunctionBegin; 1121 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1122 if (res) PetscValidHeaderSpecific(res,VEC_CLASSID,2); 1123 1124 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1125 ierr = DMTSSetIFunction(dm,f,ctx);CHKERRQ(ierr); 1126 1127 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1128 if (!res && !ts->dm && ts->vec_sol) { 1129 ierr = VecDuplicate(ts->vec_sol,&resalloc);CHKERRQ(ierr); 1130 res = resalloc; 1131 } 1132 ierr = SNESSetFunction(snes,res,SNESTSFormFunction,ts);CHKERRQ(ierr); 1133 ierr = VecDestroy(&resalloc);CHKERRQ(ierr); 1134 PetscFunctionReturn(0); 1135 } 1136 1137 #undef __FUNCT__ 1138 #define __FUNCT__ "TSGetIFunction" 1139 /*@C 1140 TSGetIFunction - Returns the vector where the implicit residual is stored and the function/contex to compute it. 1141 1142 Not Collective 1143 1144 Input Parameter: 1145 . ts - the TS context 1146 1147 Output Parameter: 1148 + r - vector to hold residual (or NULL) 1149 . func - the function to compute residual (or NULL) 1150 - ctx - the function context (or NULL) 1151 1152 Level: advanced 1153 1154 .keywords: TS, nonlinear, get, function 1155 1156 .seealso: TSSetIFunction(), SNESGetFunction() 1157 @*/ 1158 PetscErrorCode TSGetIFunction(TS ts,Vec *r,TSIFunction *func,void **ctx) 1159 { 1160 PetscErrorCode ierr; 1161 SNES snes; 1162 DM dm; 1163 1164 PetscFunctionBegin; 1165 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1166 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1167 ierr = SNESGetFunction(snes,r,NULL,NULL);CHKERRQ(ierr); 1168 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1169 ierr = DMTSGetIFunction(dm,func,ctx);CHKERRQ(ierr); 1170 PetscFunctionReturn(0); 1171 } 1172 1173 #undef __FUNCT__ 1174 #define __FUNCT__ "TSGetRHSFunction" 1175 /*@C 1176 TSGetRHSFunction - Returns the vector where the right hand side is stored and the function/context to compute it. 1177 1178 Not Collective 1179 1180 Input Parameter: 1181 . ts - the TS context 1182 1183 Output Parameter: 1184 + r - vector to hold computed right hand side (or NULL) 1185 . func - the function to compute right hand side (or NULL) 1186 - ctx - the function context (or NULL) 1187 1188 Level: advanced 1189 1190 .keywords: TS, nonlinear, get, function 1191 1192 .seealso: TSSetRHSFunction(), SNESGetFunction() 1193 @*/ 1194 PetscErrorCode TSGetRHSFunction(TS ts,Vec *r,TSRHSFunction *func,void **ctx) 1195 { 1196 PetscErrorCode ierr; 1197 SNES snes; 1198 DM dm; 1199 1200 PetscFunctionBegin; 1201 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1202 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1203 ierr = SNESGetFunction(snes,r,NULL,NULL);CHKERRQ(ierr); 1204 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1205 ierr = DMTSGetRHSFunction(dm,func,ctx);CHKERRQ(ierr); 1206 PetscFunctionReturn(0); 1207 } 1208 1209 #undef __FUNCT__ 1210 #define __FUNCT__ "TSSetIJacobian" 1211 /*@C 1212 TSSetIJacobian - Set the function to compute the matrix dF/dU + a*dF/dU_t where F(t,U,U_t) is the function 1213 provided with TSSetIFunction(). 1214 1215 Logically Collective on TS 1216 1217 Input Parameters: 1218 + ts - the TS context obtained from TSCreate() 1219 . Amat - (approximate) Jacobian matrix 1220 . Pmat - matrix used to compute preconditioner (usually the same as Amat) 1221 . f - the Jacobian evaluation routine 1222 - ctx - user-defined context for private data for the Jacobian evaluation routine (may be NULL) 1223 1224 Calling sequence of f: 1225 $ f(TS ts,PetscReal t,Vec U,Vec U_t,PetscReal a,Mat Amat,Mat Pmat,void *ctx); 1226 1227 + t - time at step/stage being solved 1228 . U - state vector 1229 . U_t - time derivative of state vector 1230 . a - shift 1231 . Amat - (approximate) Jacobian of F(t,U,W+a*U), equivalent to dF/dU + a*dF/dU_t 1232 . Pmat - matrix used for constructing preconditioner, usually the same as Amat 1233 - ctx - [optional] user-defined context for matrix evaluation routine 1234 1235 Notes: 1236 The matrices Amat and Pmat are exactly the matrices that are used by SNES for the nonlinear solve. 1237 1238 The matrix dF/dU + a*dF/dU_t you provide turns out to be 1239 the Jacobian of F(t,U,W+a*U) where F(t,U,U_t) = 0 is the DAE to be solved. 1240 The time integrator internally approximates U_t by W+a*U where the positive "shift" 1241 a and vector W depend on the integration method, step size, and past states. For example with 1242 the backward Euler method a = 1/dt and W = -a*U(previous timestep) so 1243 W + a*U = a*(U - U(previous timestep)) = (U - U(previous timestep))/dt 1244 1245 Level: beginner 1246 1247 .keywords: TS, timestep, DAE, Jacobian 1248 1249 .seealso: TSSetIFunction(), TSSetRHSJacobian(), SNESComputeJacobianDefaultColor(), SNESComputeJacobianDefault(), TSSetRHSFunction() 1250 1251 @*/ 1252 PetscErrorCode TSSetIJacobian(TS ts,Mat Amat,Mat Pmat,TSIJacobian f,void *ctx) 1253 { 1254 PetscErrorCode ierr; 1255 SNES snes; 1256 DM dm; 1257 1258 PetscFunctionBegin; 1259 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1260 if (Amat) PetscValidHeaderSpecific(Amat,MAT_CLASSID,2); 1261 if (Pmat) PetscValidHeaderSpecific(Pmat,MAT_CLASSID,3); 1262 if (Amat) PetscCheckSameComm(ts,1,Amat,2); 1263 if (Pmat) PetscCheckSameComm(ts,1,Pmat,3); 1264 1265 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1266 ierr = DMTSSetIJacobian(dm,f,ctx);CHKERRQ(ierr); 1267 1268 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1269 ierr = SNESSetJacobian(snes,Amat,Pmat,SNESTSFormJacobian,ts);CHKERRQ(ierr); 1270 PetscFunctionReturn(0); 1271 } 1272 1273 #undef __FUNCT__ 1274 #define __FUNCT__ "TSRHSJacobianSetReuse" 1275 /*@ 1276 TSRHSJacobianSetReuse - restore RHS Jacobian before re-evaluating. Without this flag, TS will change the sign and 1277 shift the RHS Jacobian for a finite-time-step implicit solve, in which case the user function will need to recompute 1278 the entire Jacobian. The reuse flag must be set if the evaluation function will assume that the matrix entries have 1279 not been changed by the TS. 1280 1281 Logically Collective 1282 1283 Input Arguments: 1284 + ts - TS context obtained from TSCreate() 1285 - reuse - PETSC_TRUE if the RHS Jacobian 1286 1287 Level: intermediate 1288 1289 .seealso: TSSetRHSJacobian(), TSComputeRHSJacobianConstant() 1290 @*/ 1291 PetscErrorCode TSRHSJacobianSetReuse(TS ts,PetscBool reuse) 1292 { 1293 PetscFunctionBegin; 1294 ts->rhsjacobian.reuse = reuse; 1295 PetscFunctionReturn(0); 1296 } 1297 1298 #undef __FUNCT__ 1299 #define __FUNCT__ "TSLoad" 1300 /*@C 1301 TSLoad - Loads a KSP that has been stored in binary with KSPView(). 1302 1303 Collective on PetscViewer 1304 1305 Input Parameters: 1306 + newdm - the newly loaded TS, this needs to have been created with TSCreate() or 1307 some related function before a call to TSLoad(). 1308 - viewer - binary file viewer, obtained from PetscViewerBinaryOpen() 1309 1310 Level: intermediate 1311 1312 Notes: 1313 The type is determined by the data in the file, any type set into the TS before this call is ignored. 1314 1315 Notes for advanced users: 1316 Most users should not need to know the details of the binary storage 1317 format, since TSLoad() and TSView() completely hide these details. 1318 But for anyone who's interested, the standard binary matrix storage 1319 format is 1320 .vb 1321 has not yet been determined 1322 .ve 1323 1324 .seealso: PetscViewerBinaryOpen(), TSView(), MatLoad(), VecLoad() 1325 @*/ 1326 PetscErrorCode TSLoad(TS ts, PetscViewer viewer) 1327 { 1328 PetscErrorCode ierr; 1329 PetscBool isbinary; 1330 PetscInt classid; 1331 char type[256]; 1332 DMTS sdm; 1333 DM dm; 1334 1335 PetscFunctionBegin; 1336 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1337 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,2); 1338 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1339 if (!isbinary) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid viewer; open viewer with PetscViewerBinaryOpen()"); 1340 1341 ierr = PetscViewerBinaryRead(viewer,&classid,1,NULL,PETSC_INT);CHKERRQ(ierr); 1342 if (classid != TS_FILE_CLASSID) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_WRONG,"Not TS next in file"); 1343 ierr = PetscViewerBinaryRead(viewer,type,256,NULL,PETSC_CHAR);CHKERRQ(ierr); 1344 ierr = TSSetType(ts, type);CHKERRQ(ierr); 1345 if (ts->ops->load) { 1346 ierr = (*ts->ops->load)(ts,viewer);CHKERRQ(ierr); 1347 } 1348 ierr = DMCreate(PetscObjectComm((PetscObject)ts),&dm);CHKERRQ(ierr); 1349 ierr = DMLoad(dm,viewer);CHKERRQ(ierr); 1350 ierr = TSSetDM(ts,dm);CHKERRQ(ierr); 1351 ierr = DMCreateGlobalVector(ts->dm,&ts->vec_sol);CHKERRQ(ierr); 1352 ierr = VecLoad(ts->vec_sol,viewer);CHKERRQ(ierr); 1353 ierr = DMGetDMTS(ts->dm,&sdm);CHKERRQ(ierr); 1354 ierr = DMTSLoad(sdm,viewer);CHKERRQ(ierr); 1355 PetscFunctionReturn(0); 1356 } 1357 1358 #include <petscdraw.h> 1359 #if defined(PETSC_HAVE_SAWS) 1360 #include <petscviewersaws.h> 1361 #endif 1362 #undef __FUNCT__ 1363 #define __FUNCT__ "TSView" 1364 /*@C 1365 TSView - Prints the TS data structure. 1366 1367 Collective on TS 1368 1369 Input Parameters: 1370 + ts - the TS context obtained from TSCreate() 1371 - viewer - visualization context 1372 1373 Options Database Key: 1374 . -ts_view - calls TSView() at end of TSStep() 1375 1376 Notes: 1377 The available visualization contexts include 1378 + PETSC_VIEWER_STDOUT_SELF - standard output (default) 1379 - PETSC_VIEWER_STDOUT_WORLD - synchronized standard 1380 output where only the first processor opens 1381 the file. All other processors send their 1382 data to the first processor to print. 1383 1384 The user can open an alternative visualization context with 1385 PetscViewerASCIIOpen() - output to a specified file. 1386 1387 Level: beginner 1388 1389 .keywords: TS, timestep, view 1390 1391 .seealso: PetscViewerASCIIOpen() 1392 @*/ 1393 PetscErrorCode TSView(TS ts,PetscViewer viewer) 1394 { 1395 PetscErrorCode ierr; 1396 TSType type; 1397 PetscBool iascii,isstring,isundials,isbinary,isdraw; 1398 DMTS sdm; 1399 #if defined(PETSC_HAVE_SAWS) 1400 PetscBool issaws; 1401 #endif 1402 1403 PetscFunctionBegin; 1404 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1405 if (!viewer) { 1406 ierr = PetscViewerASCIIGetStdout(PetscObjectComm((PetscObject)ts),&viewer);CHKERRQ(ierr); 1407 } 1408 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,2); 1409 PetscCheckSameComm(ts,1,viewer,2); 1410 1411 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1412 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSTRING,&isstring);CHKERRQ(ierr); 1413 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1414 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1415 #if defined(PETSC_HAVE_SAWS) 1416 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSAWS,&issaws);CHKERRQ(ierr); 1417 #endif 1418 if (iascii) { 1419 ierr = PetscObjectPrintClassNamePrefixType((PetscObject)ts,viewer);CHKERRQ(ierr); 1420 ierr = PetscViewerASCIIPrintf(viewer," maximum steps=%D\n",ts->max_steps);CHKERRQ(ierr); 1421 ierr = PetscViewerASCIIPrintf(viewer," maximum time=%g\n",(double)ts->max_time);CHKERRQ(ierr); 1422 if (ts->problem_type == TS_NONLINEAR) { 1423 ierr = PetscViewerASCIIPrintf(viewer," total number of nonlinear solver iterations=%D\n",ts->snes_its);CHKERRQ(ierr); 1424 ierr = PetscViewerASCIIPrintf(viewer," total number of nonlinear solve failures=%D\n",ts->num_snes_failures);CHKERRQ(ierr); 1425 } 1426 ierr = PetscViewerASCIIPrintf(viewer," total number of linear solver iterations=%D\n",ts->ksp_its);CHKERRQ(ierr); 1427 ierr = PetscViewerASCIIPrintf(viewer," total number of rejected steps=%D\n",ts->reject);CHKERRQ(ierr); 1428 ierr = DMGetDMTS(ts->dm,&sdm);CHKERRQ(ierr); 1429 ierr = DMTSView(sdm,viewer);CHKERRQ(ierr); 1430 if (ts->ops->view) { 1431 ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr); 1432 ierr = (*ts->ops->view)(ts,viewer);CHKERRQ(ierr); 1433 ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr); 1434 } 1435 } else if (isstring) { 1436 ierr = TSGetType(ts,&type);CHKERRQ(ierr); 1437 ierr = PetscViewerStringSPrintf(viewer," %-7.7s",type);CHKERRQ(ierr); 1438 } else if (isbinary) { 1439 PetscInt classid = TS_FILE_CLASSID; 1440 MPI_Comm comm; 1441 PetscMPIInt rank; 1442 char type[256]; 1443 1444 ierr = PetscObjectGetComm((PetscObject)ts,&comm);CHKERRQ(ierr); 1445 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 1446 if (!rank) { 1447 ierr = PetscViewerBinaryWrite(viewer,&classid,1,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); 1448 ierr = PetscStrncpy(type,((PetscObject)ts)->type_name,256);CHKERRQ(ierr); 1449 ierr = PetscViewerBinaryWrite(viewer,type,256,PETSC_CHAR,PETSC_FALSE);CHKERRQ(ierr); 1450 } 1451 if (ts->ops->view) { 1452 ierr = (*ts->ops->view)(ts,viewer);CHKERRQ(ierr); 1453 } 1454 ierr = DMView(ts->dm,viewer);CHKERRQ(ierr); 1455 ierr = VecView(ts->vec_sol,viewer);CHKERRQ(ierr); 1456 ierr = DMGetDMTS(ts->dm,&sdm);CHKERRQ(ierr); 1457 ierr = DMTSView(sdm,viewer);CHKERRQ(ierr); 1458 } else if (isdraw) { 1459 PetscDraw draw; 1460 char str[36]; 1461 PetscReal x,y,bottom,h; 1462 1463 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1464 ierr = PetscDrawGetCurrentPoint(draw,&x,&y);CHKERRQ(ierr); 1465 ierr = PetscStrcpy(str,"TS: ");CHKERRQ(ierr); 1466 ierr = PetscStrcat(str,((PetscObject)ts)->type_name);CHKERRQ(ierr); 1467 ierr = PetscDrawStringBoxed(draw,x,y,PETSC_DRAW_BLACK,PETSC_DRAW_BLACK,str,NULL,&h);CHKERRQ(ierr); 1468 bottom = y - h; 1469 ierr = PetscDrawPushCurrentPoint(draw,x,bottom);CHKERRQ(ierr); 1470 if (ts->ops->view) { 1471 ierr = (*ts->ops->view)(ts,viewer);CHKERRQ(ierr); 1472 } 1473 ierr = PetscDrawPopCurrentPoint(draw);CHKERRQ(ierr); 1474 #if defined(PETSC_HAVE_SAWS) 1475 } else if (issaws) { 1476 PetscMPIInt rank; 1477 const char *name; 1478 1479 ierr = PetscObjectGetName((PetscObject)ts,&name);CHKERRQ(ierr); 1480 ierr = MPI_Comm_rank(PETSC_COMM_WORLD,&rank);CHKERRQ(ierr); 1481 if (!((PetscObject)ts)->amsmem && !rank) { 1482 char dir[1024]; 1483 1484 ierr = PetscObjectViewSAWs((PetscObject)ts,viewer);CHKERRQ(ierr); 1485 ierr = PetscSNPrintf(dir,1024,"/PETSc/Objects/%s/time_step",name);CHKERRQ(ierr); 1486 PetscStackCallSAWs(SAWs_Register,(dir,&ts->steps,1,SAWs_READ,SAWs_INT)); 1487 ierr = PetscSNPrintf(dir,1024,"/PETSc/Objects/%s/time",name);CHKERRQ(ierr); 1488 PetscStackCallSAWs(SAWs_Register,(dir,&ts->ptime,1,SAWs_READ,SAWs_DOUBLE)); 1489 } 1490 if (ts->ops->view) { 1491 ierr = (*ts->ops->view)(ts,viewer);CHKERRQ(ierr); 1492 } 1493 #endif 1494 } 1495 1496 ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr); 1497 ierr = PetscObjectTypeCompare((PetscObject)ts,TSSUNDIALS,&isundials);CHKERRQ(ierr); 1498 ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr); 1499 PetscFunctionReturn(0); 1500 } 1501 1502 1503 #undef __FUNCT__ 1504 #define __FUNCT__ "TSSetApplicationContext" 1505 /*@ 1506 TSSetApplicationContext - Sets an optional user-defined context for 1507 the timesteppers. 1508 1509 Logically Collective on TS 1510 1511 Input Parameters: 1512 + ts - the TS context obtained from TSCreate() 1513 - usrP - optional user context 1514 1515 Level: intermediate 1516 1517 .keywords: TS, timestep, set, application, context 1518 1519 .seealso: TSGetApplicationContext() 1520 @*/ 1521 PetscErrorCode TSSetApplicationContext(TS ts,void *usrP) 1522 { 1523 PetscFunctionBegin; 1524 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1525 ts->user = usrP; 1526 PetscFunctionReturn(0); 1527 } 1528 1529 #undef __FUNCT__ 1530 #define __FUNCT__ "TSGetApplicationContext" 1531 /*@ 1532 TSGetApplicationContext - Gets the user-defined context for the 1533 timestepper. 1534 1535 Not Collective 1536 1537 Input Parameter: 1538 . ts - the TS context obtained from TSCreate() 1539 1540 Output Parameter: 1541 . usrP - user context 1542 1543 Level: intermediate 1544 1545 .keywords: TS, timestep, get, application, context 1546 1547 .seealso: TSSetApplicationContext() 1548 @*/ 1549 PetscErrorCode TSGetApplicationContext(TS ts,void *usrP) 1550 { 1551 PetscFunctionBegin; 1552 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1553 *(void**)usrP = ts->user; 1554 PetscFunctionReturn(0); 1555 } 1556 1557 #undef __FUNCT__ 1558 #define __FUNCT__ "TSGetTimeStepNumber" 1559 /*@ 1560 TSGetTimeStepNumber - Gets the number of time steps completed. 1561 1562 Not Collective 1563 1564 Input Parameter: 1565 . ts - the TS context obtained from TSCreate() 1566 1567 Output Parameter: 1568 . iter - number of steps completed so far 1569 1570 Level: intermediate 1571 1572 .keywords: TS, timestep, get, iteration, number 1573 .seealso: TSGetTime(), TSGetTimeStep(), TSSetPreStep(), TSSetPreStage(), TSSetPostStage(), TSSetPostStep() 1574 @*/ 1575 PetscErrorCode TSGetTimeStepNumber(TS ts,PetscInt *iter) 1576 { 1577 PetscFunctionBegin; 1578 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1579 PetscValidIntPointer(iter,2); 1580 *iter = ts->steps; 1581 PetscFunctionReturn(0); 1582 } 1583 1584 #undef __FUNCT__ 1585 #define __FUNCT__ "TSSetInitialTimeStep" 1586 /*@ 1587 TSSetInitialTimeStep - Sets the initial timestep to be used, 1588 as well as the initial time. 1589 1590 Logically Collective on TS 1591 1592 Input Parameters: 1593 + ts - the TS context obtained from TSCreate() 1594 . initial_time - the initial time 1595 - time_step - the size of the timestep 1596 1597 Level: intermediate 1598 1599 .seealso: TSSetTimeStep(), TSGetTimeStep() 1600 1601 .keywords: TS, set, initial, timestep 1602 @*/ 1603 PetscErrorCode TSSetInitialTimeStep(TS ts,PetscReal initial_time,PetscReal time_step) 1604 { 1605 PetscErrorCode ierr; 1606 1607 PetscFunctionBegin; 1608 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1609 ierr = TSSetTimeStep(ts,time_step);CHKERRQ(ierr); 1610 ierr = TSSetTime(ts,initial_time);CHKERRQ(ierr); 1611 PetscFunctionReturn(0); 1612 } 1613 1614 #undef __FUNCT__ 1615 #define __FUNCT__ "TSSetTimeStep" 1616 /*@ 1617 TSSetTimeStep - Allows one to reset the timestep at any time, 1618 useful for simple pseudo-timestepping codes. 1619 1620 Logically Collective on TS 1621 1622 Input Parameters: 1623 + ts - the TS context obtained from TSCreate() 1624 - time_step - the size of the timestep 1625 1626 Level: intermediate 1627 1628 .seealso: TSSetInitialTimeStep(), TSGetTimeStep() 1629 1630 .keywords: TS, set, timestep 1631 @*/ 1632 PetscErrorCode TSSetTimeStep(TS ts,PetscReal time_step) 1633 { 1634 PetscFunctionBegin; 1635 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1636 PetscValidLogicalCollectiveReal(ts,time_step,2); 1637 ts->time_step = time_step; 1638 ts->time_step_orig = time_step; 1639 PetscFunctionReturn(0); 1640 } 1641 1642 #undef __FUNCT__ 1643 #define __FUNCT__ "TSSetExactFinalTime" 1644 /*@ 1645 TSSetExactFinalTime - Determines whether to adapt the final time step to 1646 match the exact final time, interpolate solution to the exact final time, 1647 or just return at the final time TS computed. 1648 1649 Logically Collective on TS 1650 1651 Input Parameter: 1652 + ts - the time-step context 1653 - eftopt - exact final time option 1654 1655 Level: beginner 1656 1657 .seealso: TSExactFinalTimeOption 1658 @*/ 1659 PetscErrorCode TSSetExactFinalTime(TS ts,TSExactFinalTimeOption eftopt) 1660 { 1661 PetscFunctionBegin; 1662 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1663 PetscValidLogicalCollectiveEnum(ts,eftopt,2); 1664 ts->exact_final_time = eftopt; 1665 PetscFunctionReturn(0); 1666 } 1667 1668 #undef __FUNCT__ 1669 #define __FUNCT__ "TSGetTimeStep" 1670 /*@ 1671 TSGetTimeStep - Gets the current timestep size. 1672 1673 Not Collective 1674 1675 Input Parameter: 1676 . ts - the TS context obtained from TSCreate() 1677 1678 Output Parameter: 1679 . dt - the current timestep size 1680 1681 Level: intermediate 1682 1683 .seealso: TSSetInitialTimeStep(), TSGetTimeStep() 1684 1685 .keywords: TS, get, timestep 1686 @*/ 1687 PetscErrorCode TSGetTimeStep(TS ts,PetscReal *dt) 1688 { 1689 PetscFunctionBegin; 1690 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1691 PetscValidRealPointer(dt,2); 1692 *dt = ts->time_step; 1693 PetscFunctionReturn(0); 1694 } 1695 1696 #undef __FUNCT__ 1697 #define __FUNCT__ "TSGetSolution" 1698 /*@ 1699 TSGetSolution - Returns the solution at the present timestep. It 1700 is valid to call this routine inside the function that you are evaluating 1701 in order to move to the new timestep. This vector not changed until 1702 the solution at the next timestep has been calculated. 1703 1704 Not Collective, but Vec returned is parallel if TS is parallel 1705 1706 Input Parameter: 1707 . ts - the TS context obtained from TSCreate() 1708 1709 Output Parameter: 1710 . v - the vector containing the solution 1711 1712 Level: intermediate 1713 1714 .seealso: TSGetTimeStep() 1715 1716 .keywords: TS, timestep, get, solution 1717 @*/ 1718 PetscErrorCode TSGetSolution(TS ts,Vec *v) 1719 { 1720 PetscFunctionBegin; 1721 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1722 PetscValidPointer(v,2); 1723 *v = ts->vec_sol; 1724 PetscFunctionReturn(0); 1725 } 1726 1727 #undef __FUNCT__ 1728 #define __FUNCT__ "TSGetCostGradients" 1729 /*@ 1730 TSGetCostGradients - Returns the gradients from the TSAdjointSolve() 1731 1732 Not Collective, but Vec returned is parallel if TS is parallel 1733 1734 Input Parameter: 1735 . ts - the TS context obtained from TSCreate() 1736 1737 Output Parameter: 1738 + lambda - vectors containing the gradients of the cost functions with respect to the ODE/DAE solution variables 1739 - mu - vectors containing the gradients of the cost functions with respect to the problem parameters 1740 1741 Level: intermediate 1742 1743 .seealso: TSGetTimeStep() 1744 1745 .keywords: TS, timestep, get, sensitivity 1746 @*/ 1747 PetscErrorCode TSGetCostGradients(TS ts,PetscInt *numcost,Vec **lambda,Vec **mu) 1748 { 1749 PetscFunctionBegin; 1750 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1751 if (numcost) *numcost = ts->numcost; 1752 if (lambda) *lambda = ts->vecs_sensi; 1753 if (mu) *mu = ts->vecs_sensip; 1754 PetscFunctionReturn(0); 1755 } 1756 1757 /* ----- Routines to initialize and destroy a timestepper ---- */ 1758 #undef __FUNCT__ 1759 #define __FUNCT__ "TSSetProblemType" 1760 /*@ 1761 TSSetProblemType - Sets the type of problem to be solved. 1762 1763 Not collective 1764 1765 Input Parameters: 1766 + ts - The TS 1767 - type - One of TS_LINEAR, TS_NONLINEAR where these types refer to problems of the forms 1768 .vb 1769 U_t - A U = 0 (linear) 1770 U_t - A(t) U = 0 (linear) 1771 F(t,U,U_t) = 0 (nonlinear) 1772 .ve 1773 1774 Level: beginner 1775 1776 .keywords: TS, problem type 1777 .seealso: TSSetUp(), TSProblemType, TS 1778 @*/ 1779 PetscErrorCode TSSetProblemType(TS ts, TSProblemType type) 1780 { 1781 PetscErrorCode ierr; 1782 1783 PetscFunctionBegin; 1784 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 1785 ts->problem_type = type; 1786 if (type == TS_LINEAR) { 1787 SNES snes; 1788 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1789 ierr = SNESSetType(snes,SNESKSPONLY);CHKERRQ(ierr); 1790 } 1791 PetscFunctionReturn(0); 1792 } 1793 1794 #undef __FUNCT__ 1795 #define __FUNCT__ "TSGetProblemType" 1796 /*@C 1797 TSGetProblemType - Gets the type of problem to be solved. 1798 1799 Not collective 1800 1801 Input Parameter: 1802 . ts - The TS 1803 1804 Output Parameter: 1805 . type - One of TS_LINEAR, TS_NONLINEAR where these types refer to problems of the forms 1806 .vb 1807 M U_t = A U 1808 M(t) U_t = A(t) U 1809 F(t,U,U_t) 1810 .ve 1811 1812 Level: beginner 1813 1814 .keywords: TS, problem type 1815 .seealso: TSSetUp(), TSProblemType, TS 1816 @*/ 1817 PetscErrorCode TSGetProblemType(TS ts, TSProblemType *type) 1818 { 1819 PetscFunctionBegin; 1820 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 1821 PetscValidIntPointer(type,2); 1822 *type = ts->problem_type; 1823 PetscFunctionReturn(0); 1824 } 1825 1826 #undef __FUNCT__ 1827 #define __FUNCT__ "TSSetUp" 1828 /*@ 1829 TSSetUp - Sets up the internal data structures for the later use 1830 of a timestepper. 1831 1832 Collective on TS 1833 1834 Input Parameter: 1835 . ts - the TS context obtained from TSCreate() 1836 1837 Notes: 1838 For basic use of the TS solvers the user need not explicitly call 1839 TSSetUp(), since these actions will automatically occur during 1840 the call to TSStep(). However, if one wishes to control this 1841 phase separately, TSSetUp() should be called after TSCreate() 1842 and optional routines of the form TSSetXXX(), but before TSStep(). 1843 1844 Level: advanced 1845 1846 .keywords: TS, timestep, setup 1847 1848 .seealso: TSCreate(), TSStep(), TSDestroy() 1849 @*/ 1850 PetscErrorCode TSSetUp(TS ts) 1851 { 1852 PetscErrorCode ierr; 1853 DM dm; 1854 PetscErrorCode (*func)(SNES,Vec,Vec,void*); 1855 PetscErrorCode (*jac)(SNES,Vec,Mat,Mat,void*); 1856 TSIJacobian ijac; 1857 TSRHSJacobian rhsjac; 1858 1859 PetscFunctionBegin; 1860 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1861 if (ts->setupcalled) PetscFunctionReturn(0); 1862 1863 ts->total_steps = 0; 1864 if (!((PetscObject)ts)->type_name) { 1865 ierr = TSSetType(ts,TSEULER);CHKERRQ(ierr); 1866 } 1867 1868 if (!ts->vec_sol) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call TSSetSolution() first"); 1869 1870 1871 ierr = TSGetAdapt(ts,&ts->adapt);CHKERRQ(ierr); 1872 1873 if (ts->rhsjacobian.reuse) { 1874 Mat Amat,Pmat; 1875 SNES snes; 1876 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 1877 ierr = SNESGetJacobian(snes,&Amat,&Pmat,NULL,NULL);CHKERRQ(ierr); 1878 /* Matching matrices implies that an IJacobian is NOT set, because if it had been set, the IJacobian's matrix would 1879 * have displaced the RHS matrix */ 1880 if (Amat == ts->Arhs) { 1881 ierr = MatDuplicate(ts->Arhs,MAT_DO_NOT_COPY_VALUES,&Amat);CHKERRQ(ierr); 1882 ierr = SNESSetJacobian(snes,Amat,NULL,NULL,NULL);CHKERRQ(ierr); 1883 ierr = MatDestroy(&Amat);CHKERRQ(ierr); 1884 } 1885 if (Pmat == ts->Brhs) { 1886 ierr = MatDuplicate(ts->Brhs,MAT_DO_NOT_COPY_VALUES,&Pmat);CHKERRQ(ierr); 1887 ierr = SNESSetJacobian(snes,NULL,Pmat,NULL,NULL);CHKERRQ(ierr); 1888 ierr = MatDestroy(&Pmat);CHKERRQ(ierr); 1889 } 1890 } 1891 if (ts->ops->setup) { 1892 ierr = (*ts->ops->setup)(ts);CHKERRQ(ierr); 1893 } 1894 1895 /* in the case where we've set a DMTSFunction or what have you, we need the default SNESFunction 1896 to be set right but can't do it elsewhere due to the overreliance on ctx=ts. 1897 */ 1898 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 1899 ierr = DMSNESGetFunction(dm,&func,NULL);CHKERRQ(ierr); 1900 if (!func) { 1901 ierr =DMSNESSetFunction(dm,SNESTSFormFunction,ts);CHKERRQ(ierr); 1902 } 1903 /* if the SNES doesn't have a jacobian set and the TS has an ijacobian or rhsjacobian set, set the SNES to use it. 1904 Otherwise, the SNES will use coloring internally to form the Jacobian. 1905 */ 1906 ierr = DMSNESGetJacobian(dm,&jac,NULL);CHKERRQ(ierr); 1907 ierr = DMTSGetIJacobian(dm,&ijac,NULL);CHKERRQ(ierr); 1908 ierr = DMTSGetRHSJacobian(dm,&rhsjac,NULL);CHKERRQ(ierr); 1909 if (!jac && (ijac || rhsjac)) { 1910 ierr = DMSNESSetJacobian(dm,SNESTSFormJacobian,ts);CHKERRQ(ierr); 1911 } 1912 ts->setupcalled = PETSC_TRUE; 1913 PetscFunctionReturn(0); 1914 } 1915 1916 #undef __FUNCT__ 1917 #define __FUNCT__ "TSAdjointSetUp" 1918 /*@ 1919 TSAdjointSetUp - Sets up the internal data structures for the later use 1920 of an adjoint solver 1921 1922 Collective on TS 1923 1924 Input Parameter: 1925 . ts - the TS context obtained from TSCreate() 1926 1927 Notes: 1928 For basic use of the TS solvers the user need not explicitly call 1929 TSSetUp(), since these actions will automatically occur during 1930 the call to TSStep(). However, if one wishes to control this 1931 phase separately, TSSetUp() should be called after TSCreate() 1932 and optional routines of the form TSSetXXX(), but before TSStep(). 1933 1934 Level: advanced 1935 1936 .keywords: TS, timestep, setup 1937 1938 .seealso: TSCreate(), TSStep(), TSDestroy() 1939 @*/ 1940 PetscErrorCode TSAdjointSetUp(TS ts) 1941 { 1942 PetscErrorCode ierr; 1943 1944 PetscFunctionBegin; 1945 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1946 if (ts->adjointsetupcalled) PetscFunctionReturn(0); 1947 if (!ts->vecs_sensi) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call TSSetCostGradients() first"); 1948 1949 ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&ts->vecs_drdy);CHKERRQ(ierr); 1950 if (ts->vecs_sensip){ 1951 ierr = VecDuplicateVecs(ts->vecs_sensip[0],ts->numcost,&ts->vecs_drdp);CHKERRQ(ierr); 1952 } 1953 1954 if (ts->ops->adjointsetup) { 1955 ierr = (*ts->ops->adjointsetup)(ts);CHKERRQ(ierr); 1956 } 1957 ts->adjointsetupcalled = PETSC_TRUE; 1958 PetscFunctionReturn(0); 1959 } 1960 1961 #undef __FUNCT__ 1962 #define __FUNCT__ "TSReset" 1963 /*@ 1964 TSReset - Resets a TS context and removes any allocated Vecs and Mats. 1965 1966 Collective on TS 1967 1968 Input Parameter: 1969 . ts - the TS context obtained from TSCreate() 1970 1971 Level: beginner 1972 1973 .keywords: TS, timestep, reset 1974 1975 .seealso: TSCreate(), TSSetup(), TSDestroy() 1976 @*/ 1977 PetscErrorCode TSReset(TS ts) 1978 { 1979 PetscErrorCode ierr; 1980 1981 PetscFunctionBegin; 1982 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1983 1984 if (ts->ops->reset) { 1985 ierr = (*ts->ops->reset)(ts);CHKERRQ(ierr); 1986 } 1987 if (ts->snes) {ierr = SNESReset(ts->snes);CHKERRQ(ierr);} 1988 if (ts->adapt) {ierr = TSAdaptReset(ts->adapt);CHKERRQ(ierr);} 1989 1990 ierr = MatDestroy(&ts->Arhs);CHKERRQ(ierr); 1991 ierr = MatDestroy(&ts->Brhs);CHKERRQ(ierr); 1992 ierr = VecDestroy(&ts->Frhs);CHKERRQ(ierr); 1993 ierr = VecDestroy(&ts->vec_sol);CHKERRQ(ierr); 1994 ierr = VecDestroy(&ts->vatol);CHKERRQ(ierr); 1995 ierr = VecDestroy(&ts->vrtol);CHKERRQ(ierr); 1996 ierr = VecDestroyVecs(ts->nwork,&ts->work);CHKERRQ(ierr); 1997 1998 ierr = VecDestroyVecs(ts->numcost,&ts->vecs_drdy);CHKERRQ(ierr); 1999 if (ts->vecs_drdp){ 2000 ierr = VecDestroyVecs(ts->numcost,&ts->vecs_drdp);CHKERRQ(ierr); 2001 } 2002 ts->vecs_sensi = NULL; 2003 ts->vecs_sensip = NULL; 2004 ierr = MatDestroy(&ts->Jacp);CHKERRQ(ierr); 2005 ierr = VecDestroy(&ts->vec_costintegral);CHKERRQ(ierr); 2006 ierr = VecDestroy(&ts->vec_costintegrand);CHKERRQ(ierr); 2007 ts->setupcalled = PETSC_FALSE; 2008 PetscFunctionReturn(0); 2009 } 2010 2011 #undef __FUNCT__ 2012 #define __FUNCT__ "TSDestroy" 2013 /*@ 2014 TSDestroy - Destroys the timestepper context that was created 2015 with TSCreate(). 2016 2017 Collective on TS 2018 2019 Input Parameter: 2020 . ts - the TS context obtained from TSCreate() 2021 2022 Level: beginner 2023 2024 .keywords: TS, timestepper, destroy 2025 2026 .seealso: TSCreate(), TSSetUp(), TSSolve() 2027 @*/ 2028 PetscErrorCode TSDestroy(TS *ts) 2029 { 2030 PetscErrorCode ierr; 2031 2032 PetscFunctionBegin; 2033 if (!*ts) PetscFunctionReturn(0); 2034 PetscValidHeaderSpecific((*ts),TS_CLASSID,1); 2035 if (--((PetscObject)(*ts))->refct > 0) {*ts = 0; PetscFunctionReturn(0);} 2036 2037 ierr = TSReset((*ts));CHKERRQ(ierr); 2038 2039 /* if memory was published with SAWs then destroy it */ 2040 ierr = PetscObjectSAWsViewOff((PetscObject)*ts);CHKERRQ(ierr); 2041 if ((*ts)->ops->destroy) {ierr = (*(*ts)->ops->destroy)((*ts));CHKERRQ(ierr);} 2042 2043 ierr = TSTrajectoryDestroy(&(*ts)->trajectory);CHKERRQ(ierr); 2044 2045 ierr = TSAdaptDestroy(&(*ts)->adapt);CHKERRQ(ierr); 2046 if ((*ts)->event) { 2047 ierr = TSEventMonitorDestroy(&(*ts)->event);CHKERRQ(ierr); 2048 } 2049 ierr = SNESDestroy(&(*ts)->snes);CHKERRQ(ierr); 2050 ierr = DMDestroy(&(*ts)->dm);CHKERRQ(ierr); 2051 ierr = TSMonitorCancel((*ts));CHKERRQ(ierr); 2052 2053 ierr = PetscHeaderDestroy(ts);CHKERRQ(ierr); 2054 PetscFunctionReturn(0); 2055 } 2056 2057 #undef __FUNCT__ 2058 #define __FUNCT__ "TSGetSNES" 2059 /*@ 2060 TSGetSNES - Returns the SNES (nonlinear solver) associated with 2061 a TS (timestepper) context. Valid only for nonlinear problems. 2062 2063 Not Collective, but SNES is parallel if TS is parallel 2064 2065 Input Parameter: 2066 . ts - the TS context obtained from TSCreate() 2067 2068 Output Parameter: 2069 . snes - the nonlinear solver context 2070 2071 Notes: 2072 The user can then directly manipulate the SNES context to set various 2073 options, etc. Likewise, the user can then extract and manipulate the 2074 KSP, KSP, and PC contexts as well. 2075 2076 TSGetSNES() does not work for integrators that do not use SNES; in 2077 this case TSGetSNES() returns NULL in snes. 2078 2079 Level: beginner 2080 2081 .keywords: timestep, get, SNES 2082 @*/ 2083 PetscErrorCode TSGetSNES(TS ts,SNES *snes) 2084 { 2085 PetscErrorCode ierr; 2086 2087 PetscFunctionBegin; 2088 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2089 PetscValidPointer(snes,2); 2090 if (!ts->snes) { 2091 ierr = SNESCreate(PetscObjectComm((PetscObject)ts),&ts->snes);CHKERRQ(ierr); 2092 ierr = SNESSetFunction(ts->snes,NULL,SNESTSFormFunction,ts);CHKERRQ(ierr); 2093 ierr = PetscLogObjectParent((PetscObject)ts,(PetscObject)ts->snes);CHKERRQ(ierr); 2094 ierr = PetscObjectIncrementTabLevel((PetscObject)ts->snes,(PetscObject)ts,1);CHKERRQ(ierr); 2095 if (ts->dm) {ierr = SNESSetDM(ts->snes,ts->dm);CHKERRQ(ierr);} 2096 if (ts->problem_type == TS_LINEAR) { 2097 ierr = SNESSetType(ts->snes,SNESKSPONLY);CHKERRQ(ierr); 2098 } 2099 } 2100 *snes = ts->snes; 2101 PetscFunctionReturn(0); 2102 } 2103 2104 #undef __FUNCT__ 2105 #define __FUNCT__ "TSSetSNES" 2106 /*@ 2107 TSSetSNES - Set the SNES (nonlinear solver) to be used by the timestepping context 2108 2109 Collective 2110 2111 Input Parameter: 2112 + ts - the TS context obtained from TSCreate() 2113 - snes - the nonlinear solver context 2114 2115 Notes: 2116 Most users should have the TS created by calling TSGetSNES() 2117 2118 Level: developer 2119 2120 .keywords: timestep, set, SNES 2121 @*/ 2122 PetscErrorCode TSSetSNES(TS ts,SNES snes) 2123 { 2124 PetscErrorCode ierr; 2125 PetscErrorCode (*func)(SNES,Vec,Mat,Mat,void*); 2126 2127 PetscFunctionBegin; 2128 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2129 PetscValidHeaderSpecific(snes,SNES_CLASSID,2); 2130 ierr = PetscObjectReference((PetscObject)snes);CHKERRQ(ierr); 2131 ierr = SNESDestroy(&ts->snes);CHKERRQ(ierr); 2132 2133 ts->snes = snes; 2134 2135 ierr = SNESSetFunction(ts->snes,NULL,SNESTSFormFunction,ts);CHKERRQ(ierr); 2136 ierr = SNESGetJacobian(ts->snes,NULL,NULL,&func,NULL);CHKERRQ(ierr); 2137 if (func == SNESTSFormJacobian) { 2138 ierr = SNESSetJacobian(ts->snes,NULL,NULL,SNESTSFormJacobian,ts);CHKERRQ(ierr); 2139 } 2140 PetscFunctionReturn(0); 2141 } 2142 2143 #undef __FUNCT__ 2144 #define __FUNCT__ "TSGetKSP" 2145 /*@ 2146 TSGetKSP - Returns the KSP (linear solver) associated with 2147 a TS (timestepper) context. 2148 2149 Not Collective, but KSP is parallel if TS is parallel 2150 2151 Input Parameter: 2152 . ts - the TS context obtained from TSCreate() 2153 2154 Output Parameter: 2155 . ksp - the nonlinear solver context 2156 2157 Notes: 2158 The user can then directly manipulate the KSP context to set various 2159 options, etc. Likewise, the user can then extract and manipulate the 2160 KSP and PC contexts as well. 2161 2162 TSGetKSP() does not work for integrators that do not use KSP; 2163 in this case TSGetKSP() returns NULL in ksp. 2164 2165 Level: beginner 2166 2167 .keywords: timestep, get, KSP 2168 @*/ 2169 PetscErrorCode TSGetKSP(TS ts,KSP *ksp) 2170 { 2171 PetscErrorCode ierr; 2172 SNES snes; 2173 2174 PetscFunctionBegin; 2175 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2176 PetscValidPointer(ksp,2); 2177 if (!((PetscObject)ts)->type_name) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_NULL,"KSP is not created yet. Call TSSetType() first"); 2178 if (ts->problem_type != TS_LINEAR) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Linear only; use TSGetSNES()"); 2179 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 2180 ierr = SNESGetKSP(snes,ksp);CHKERRQ(ierr); 2181 PetscFunctionReturn(0); 2182 } 2183 2184 /* ----------- Routines to set solver parameters ---------- */ 2185 2186 #undef __FUNCT__ 2187 #define __FUNCT__ "TSGetDuration" 2188 /*@ 2189 TSGetDuration - Gets the maximum number of timesteps to use and 2190 maximum time for iteration. 2191 2192 Not Collective 2193 2194 Input Parameters: 2195 + ts - the TS context obtained from TSCreate() 2196 . maxsteps - maximum number of iterations to use, or NULL 2197 - maxtime - final time to iterate to, or NULL 2198 2199 Level: intermediate 2200 2201 .keywords: TS, timestep, get, maximum, iterations, time 2202 @*/ 2203 PetscErrorCode TSGetDuration(TS ts, PetscInt *maxsteps, PetscReal *maxtime) 2204 { 2205 PetscFunctionBegin; 2206 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 2207 if (maxsteps) { 2208 PetscValidIntPointer(maxsteps,2); 2209 *maxsteps = ts->max_steps; 2210 } 2211 if (maxtime) { 2212 PetscValidScalarPointer(maxtime,3); 2213 *maxtime = ts->max_time; 2214 } 2215 PetscFunctionReturn(0); 2216 } 2217 2218 #undef __FUNCT__ 2219 #define __FUNCT__ "TSSetDuration" 2220 /*@ 2221 TSSetDuration - Sets the maximum number of timesteps to use and 2222 maximum time for iteration. 2223 2224 Logically Collective on TS 2225 2226 Input Parameters: 2227 + ts - the TS context obtained from TSCreate() 2228 . maxsteps - maximum number of iterations to use 2229 - maxtime - final time to iterate to 2230 2231 Options Database Keys: 2232 . -ts_max_steps <maxsteps> - Sets maxsteps 2233 . -ts_final_time <maxtime> - Sets maxtime 2234 2235 Notes: 2236 The default maximum number of iterations is 5000. Default time is 5.0 2237 2238 Level: intermediate 2239 2240 .keywords: TS, timestep, set, maximum, iterations 2241 2242 .seealso: TSSetExactFinalTime() 2243 @*/ 2244 PetscErrorCode TSSetDuration(TS ts,PetscInt maxsteps,PetscReal maxtime) 2245 { 2246 PetscFunctionBegin; 2247 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2248 PetscValidLogicalCollectiveInt(ts,maxsteps,2); 2249 PetscValidLogicalCollectiveReal(ts,maxtime,2); 2250 if (maxsteps >= 0) ts->max_steps = maxsteps; 2251 if (maxtime != PETSC_DEFAULT) ts->max_time = maxtime; 2252 PetscFunctionReturn(0); 2253 } 2254 2255 #undef __FUNCT__ 2256 #define __FUNCT__ "TSSetSolution" 2257 /*@ 2258 TSSetSolution - Sets the initial solution vector 2259 for use by the TS routines. 2260 2261 Logically Collective on TS and Vec 2262 2263 Input Parameters: 2264 + ts - the TS context obtained from TSCreate() 2265 - u - the solution vector 2266 2267 Level: beginner 2268 2269 .keywords: TS, timestep, set, solution, initial conditions 2270 @*/ 2271 PetscErrorCode TSSetSolution(TS ts,Vec u) 2272 { 2273 PetscErrorCode ierr; 2274 DM dm; 2275 2276 PetscFunctionBegin; 2277 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2278 PetscValidHeaderSpecific(u,VEC_CLASSID,2); 2279 ierr = PetscObjectReference((PetscObject)u);CHKERRQ(ierr); 2280 ierr = VecDestroy(&ts->vec_sol);CHKERRQ(ierr); 2281 2282 ts->vec_sol = u; 2283 2284 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 2285 ierr = DMShellSetGlobalVector(dm,u);CHKERRQ(ierr); 2286 PetscFunctionReturn(0); 2287 } 2288 2289 #undef __FUNCT__ 2290 #define __FUNCT__ "TSAdjointSetSteps" 2291 /*@ 2292 TSAdjointSetSteps - Sets the number of steps the adjoint solver should take backward in time 2293 2294 Logically Collective on TS 2295 2296 Input Parameters: 2297 + ts - the TS context obtained from TSCreate() 2298 . steps - number of steps to use 2299 2300 Level: intermediate 2301 2302 Notes: Normally one does not call this and TSAdjointSolve() integrates back to the original timestep. One can call this 2303 so as to integrate back to less than the original timestep 2304 2305 .keywords: TS, timestep, set, maximum, iterations 2306 2307 .seealso: TSSetExactFinalTime() 2308 @*/ 2309 PetscErrorCode TSAdjointSetSteps(TS ts,PetscInt steps) 2310 { 2311 PetscFunctionBegin; 2312 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2313 PetscValidLogicalCollectiveInt(ts,steps,2); 2314 if (steps < 0) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Cannot step back a negative number of steps"); 2315 if (steps > ts->total_steps) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Cannot step back more than the total number of forward steps"); 2316 ts->adjoint_max_steps = steps; 2317 PetscFunctionReturn(0); 2318 } 2319 2320 #undef __FUNCT__ 2321 #define __FUNCT__ "TSSetCostGradients" 2322 /*@ 2323 TSSetCostGradients - Sets the initial value of the gradients of the cost function w.r.t. initial conditions and w.r.t. the problem parameters 2324 for use by the TSAdjoint routines. 2325 2326 Logically Collective on TS and Vec 2327 2328 Input Parameters: 2329 + ts - the TS context obtained from TSCreate() 2330 . lambda - gradients with respect to the initial condition variables, the dimension and parallel layout of these vectors is the same as the ODE solution vector 2331 - mu - gradients with respect to the parameters, the number of entries in these vectors is the same as the number of parameters 2332 2333 Level: beginner 2334 2335 Notes: the entries in these vectors must be correctly initialized with the values lamda_i = df/dy|finaltime mu_i = df/dp|finaltime 2336 2337 .keywords: TS, timestep, set, sensitivity, initial conditions 2338 @*/ 2339 PetscErrorCode TSSetCostGradients(TS ts,PetscInt numcost,Vec *lambda,Vec *mu) 2340 { 2341 PetscFunctionBegin; 2342 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2343 PetscValidPointer(lambda,2); 2344 ts->vecs_sensi = lambda; 2345 ts->vecs_sensip = mu; 2346 if (ts->numcost && ts->numcost!=numcost) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"The number of cost functions (2rd parameter of TSSetCostIntegrand()) is inconsistent with the one set by TSSetCostIntegrand"); 2347 ts->numcost = numcost; 2348 PetscFunctionReturn(0); 2349 } 2350 2351 #undef __FUNCT__ 2352 #define __FUNCT__ "TSAdjointSetRHSJacobian" 2353 /*@C 2354 TSAdjointSetRHSJacobian - Sets the function that computes the Jacobian of G w.r.t. the parameters p where y_t = G(y,p,t), as well as the location to store the matrix. 2355 2356 Logically Collective on TS 2357 2358 Input Parameters: 2359 + ts - The TS context obtained from TSCreate() 2360 - func - The function 2361 2362 Calling sequence of func: 2363 $ func (TS ts,PetscReal t,Vec y,Mat A,void *ctx); 2364 + t - current timestep 2365 . y - input vector (current ODE solution) 2366 . A - output matrix 2367 - ctx - [optional] user-defined function context 2368 2369 Level: intermediate 2370 2371 Notes: Amat has the same number of rows and the same row parallel layout as u, Amat has the same number of columns and parallel layout as p 2372 2373 .keywords: TS, sensitivity 2374 .seealso: 2375 @*/ 2376 PetscErrorCode TSAdjointSetRHSJacobian(TS ts,Mat Amat,PetscErrorCode (*func)(TS,PetscReal,Vec,Mat,void*),void *ctx) 2377 { 2378 PetscErrorCode ierr; 2379 2380 PetscFunctionBegin; 2381 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 2382 if (Amat) PetscValidHeaderSpecific(Amat,MAT_CLASSID,2); 2383 2384 ts->rhsjacobianp = func; 2385 ts->rhsjacobianpctx = ctx; 2386 if(Amat) { 2387 ierr = PetscObjectReference((PetscObject)Amat);CHKERRQ(ierr); 2388 ierr = MatDestroy(&ts->Jacp);CHKERRQ(ierr); 2389 ts->Jacp = Amat; 2390 } 2391 PetscFunctionReturn(0); 2392 } 2393 2394 #undef __FUNCT__ 2395 #define __FUNCT__ "TSAdjointComputeRHSJacobian" 2396 /*@C 2397 TSAdjointComputeRHSJacobian - Runs the user-defined Jacobian function. 2398 2399 Collective on TS 2400 2401 Input Parameters: 2402 . ts - The TS context obtained from TSCreate() 2403 2404 Level: developer 2405 2406 .keywords: TS, sensitivity 2407 .seealso: TSAdjointSetRHSJacobian() 2408 @*/ 2409 PetscErrorCode TSAdjointComputeRHSJacobian(TS ts,PetscReal t,Vec X,Mat Amat) 2410 { 2411 PetscErrorCode ierr; 2412 2413 PetscFunctionBegin; 2414 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2415 PetscValidHeaderSpecific(X,VEC_CLASSID,3); 2416 PetscValidPointer(Amat,4); 2417 2418 PetscStackPush("TS user JacobianP function for sensitivity analysis"); 2419 ierr = (*ts->rhsjacobianp)(ts,t,X,Amat,ts->rhsjacobianpctx); CHKERRQ(ierr); 2420 PetscStackPop; 2421 PetscFunctionReturn(0); 2422 } 2423 2424 #undef __FUNCT__ 2425 #define __FUNCT__ "TSSetCostIntegrand" 2426 /*@C 2427 TSSetCostIntegrand - Sets the routine for evaluating the integral term in one or more cost functions 2428 2429 Logically Collective on TS 2430 2431 Input Parameters: 2432 + ts - the TS context obtained from TSCreate() 2433 . numcost - number of gradients to be computed, this is the number of cost functions 2434 . rf - routine for evaluating the integrand function 2435 . drdyf - function that computes the gradients of the r's with respect to y,NULL if not a function y 2436 . drdpf - function that computes the gradients of the r's with respect to p, NULL if not a function of p 2437 - ctx - [optional] user-defined context for private data for the function evaluation routine (may be NULL) 2438 2439 Calling sequence of rf: 2440 $ rf(TS ts,PetscReal t,Vec y,Vec f[],void *ctx); 2441 2442 + t - current timestep 2443 . y - input vector 2444 . f - function result; one vector entry for each cost function 2445 - ctx - [optional] user-defined function context 2446 2447 Calling sequence of drdyf: 2448 $ PetscErroCode drdyf(TS ts,PetscReal t,Vec y,Vec *drdy,void *ctx); 2449 2450 Calling sequence of drdpf: 2451 $ PetscErroCode drdpf(TS ts,PetscReal t,Vec y,Vec *drdp,void *ctx); 2452 2453 Level: intermediate 2454 2455 Notes: For optimization there is generally a single cost function, numcost = 1. For sensitivities there may be multiple cost functions 2456 2457 .keywords: TS, sensitivity analysis, timestep, set, quadrature, function 2458 2459 .seealso: TSAdjointSetRHSJacobian(),TSGetCostGradients(), TSSetCostGradients() 2460 @*/ 2461 PetscErrorCode TSSetCostIntegrand(TS ts,PetscInt numcost, PetscErrorCode (*rf)(TS,PetscReal,Vec,Vec,void*), 2462 PetscErrorCode (*drdyf)(TS,PetscReal,Vec,Vec*,void*), 2463 PetscErrorCode (*drdpf)(TS,PetscReal,Vec,Vec*,void*),void *ctx) 2464 { 2465 PetscErrorCode ierr; 2466 2467 PetscFunctionBegin; 2468 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2469 if (ts->numcost && ts->numcost!=numcost) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"The number of cost functions (2rd parameter of TSSetCostIntegrand()) is inconsistent with the one set by TSSetCostGradients()"); 2470 if (!ts->numcost) ts->numcost=numcost; 2471 2472 ierr = VecCreateSeq(PETSC_COMM_SELF,numcost,&ts->vec_costintegral);CHKERRQ(ierr); 2473 ierr = VecDuplicate(ts->vec_costintegral,&ts->vec_costintegrand);CHKERRQ(ierr); 2474 ts->costintegrand = rf; 2475 ts->costintegrandctx = ctx; 2476 ts->drdyfunction = drdyf; 2477 ts->drdpfunction = drdpf; 2478 PetscFunctionReturn(0); 2479 } 2480 2481 #undef __FUNCT__ 2482 #define __FUNCT__ "TSGetCostIntegral" 2483 /*@ 2484 TSGetCostIntegral - Returns the values of the integral term in the cost functions. 2485 It is valid to call the routine after a backward run. 2486 2487 Not Collective 2488 2489 Input Parameter: 2490 . ts - the TS context obtained from TSCreate() 2491 2492 Output Parameter: 2493 . v - the vector containing the integrals for each cost function 2494 2495 Level: intermediate 2496 2497 .seealso: TSSetCostIntegrand() 2498 2499 .keywords: TS, sensitivity analysis 2500 @*/ 2501 PetscErrorCode TSGetCostIntegral(TS ts,Vec *v) 2502 { 2503 PetscFunctionBegin; 2504 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2505 PetscValidPointer(v,2); 2506 *v = ts->vec_costintegral; 2507 PetscFunctionReturn(0); 2508 } 2509 2510 #undef __FUNCT__ 2511 #define __FUNCT__ "TSAdjointComputeCostIntegrand" 2512 /*@ 2513 TSAdjointComputeCostIntegrand - Evaluates the integral function in the cost functions. 2514 2515 Input Parameters: 2516 + ts - the TS context 2517 . t - current time 2518 - y - state vector, i.e. current solution 2519 2520 Output Parameter: 2521 . q - vector of size numcost to hold the outputs 2522 2523 Note: 2524 Most users should not need to explicitly call this routine, as it 2525 is used internally within the sensitivity analysis context. 2526 2527 Level: developer 2528 2529 .keywords: TS, compute 2530 2531 .seealso: TSSetCostIntegrand() 2532 @*/ 2533 PetscErrorCode TSAdjointComputeCostIntegrand(TS ts,PetscReal t,Vec y,Vec q) 2534 { 2535 PetscErrorCode ierr; 2536 2537 PetscFunctionBegin; 2538 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2539 PetscValidHeaderSpecific(y,VEC_CLASSID,3); 2540 PetscValidHeaderSpecific(q,VEC_CLASSID,4); 2541 2542 ierr = PetscLogEventBegin(TS_FunctionEval,ts,y,q,0);CHKERRQ(ierr); 2543 if (ts->costintegrand) { 2544 PetscStackPush("TS user integrand in the cost function"); 2545 ierr = (*ts->costintegrand)(ts,t,y,q,ts->costintegrandctx);CHKERRQ(ierr); 2546 PetscStackPop; 2547 } else { 2548 ierr = VecZeroEntries(q);CHKERRQ(ierr); 2549 } 2550 2551 ierr = PetscLogEventEnd(TS_FunctionEval,ts,y,q,0);CHKERRQ(ierr); 2552 PetscFunctionReturn(0); 2553 } 2554 2555 #undef __FUNCT__ 2556 #define __FUNCT__ "TSAdjointComputeDRDYFunction" 2557 /*@ 2558 TSAdjointComputeDRDYFunction - Runs the user-defined DRDY function. 2559 2560 Collective on TS 2561 2562 Input Parameters: 2563 . ts - The TS context obtained from TSCreate() 2564 2565 Notes: 2566 TSAdjointComputeDRDYFunction() is typically used for sensitivity implementation, 2567 so most users would not generally call this routine themselves. 2568 2569 Level: developer 2570 2571 .keywords: TS, sensitivity 2572 .seealso: TSAdjointComputeDRDYFunction() 2573 @*/ 2574 PetscErrorCode TSAdjointComputeDRDYFunction(TS ts,PetscReal t,Vec y,Vec *drdy) 2575 { 2576 PetscErrorCode ierr; 2577 2578 PetscFunctionBegin; 2579 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2580 PetscValidHeaderSpecific(y,VEC_CLASSID,3); 2581 2582 PetscStackPush("TS user DRDY function for sensitivity analysis"); 2583 ierr = (*ts->drdyfunction)(ts,t,y,drdy,ts->costintegrandctx); CHKERRQ(ierr); 2584 PetscStackPop; 2585 PetscFunctionReturn(0); 2586 } 2587 2588 #undef __FUNCT__ 2589 #define __FUNCT__ "TSAdjointComputeDRDPFunction" 2590 /*@ 2591 TSAdjointComputeDRDPFunction - Runs the user-defined DRDP function. 2592 2593 Collective on TS 2594 2595 Input Parameters: 2596 . ts - The TS context obtained from TSCreate() 2597 2598 Notes: 2599 TSDRDPFunction() is typically used for sensitivity implementation, 2600 so most users would not generally call this routine themselves. 2601 2602 Level: developer 2603 2604 .keywords: TS, sensitivity 2605 .seealso: TSAdjointSetDRDPFunction() 2606 @*/ 2607 PetscErrorCode TSAdjointComputeDRDPFunction(TS ts,PetscReal t,Vec y,Vec *drdp) 2608 { 2609 PetscErrorCode ierr; 2610 2611 PetscFunctionBegin; 2612 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2613 PetscValidHeaderSpecific(y,VEC_CLASSID,3); 2614 2615 PetscStackPush("TS user DRDP function for sensitivity analysis"); 2616 ierr = (*ts->drdpfunction)(ts,t,y,drdp,ts->costintegrandctx); CHKERRQ(ierr); 2617 PetscStackPop; 2618 PetscFunctionReturn(0); 2619 } 2620 2621 #undef __FUNCT__ 2622 #define __FUNCT__ "TSSetPreStep" 2623 /*@C 2624 TSSetPreStep - Sets the general-purpose function 2625 called once at the beginning of each time step. 2626 2627 Logically Collective on TS 2628 2629 Input Parameters: 2630 + ts - The TS context obtained from TSCreate() 2631 - func - The function 2632 2633 Calling sequence of func: 2634 . func (TS ts); 2635 2636 Level: intermediate 2637 2638 Note: 2639 If a step is rejected, TSStep() will call this routine again before each attempt. 2640 The last completed time step number can be queried using TSGetTimeStepNumber(), the 2641 size of the step being attempted can be obtained using TSGetTimeStep(). 2642 2643 .keywords: TS, timestep 2644 .seealso: TSSetPreStage(), TSSetPostStage(), TSSetPostStep(), TSStep() 2645 @*/ 2646 PetscErrorCode TSSetPreStep(TS ts, PetscErrorCode (*func)(TS)) 2647 { 2648 PetscFunctionBegin; 2649 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 2650 ts->prestep = func; 2651 PetscFunctionReturn(0); 2652 } 2653 2654 #undef __FUNCT__ 2655 #define __FUNCT__ "TSPreStep" 2656 /*@ 2657 TSPreStep - Runs the user-defined pre-step function. 2658 2659 Collective on TS 2660 2661 Input Parameters: 2662 . ts - The TS context obtained from TSCreate() 2663 2664 Notes: 2665 TSPreStep() is typically used within time stepping implementations, 2666 so most users would not generally call this routine themselves. 2667 2668 Level: developer 2669 2670 .keywords: TS, timestep 2671 .seealso: TSSetPreStep(), TSPreStage(), TSPostStage(), TSPostStep() 2672 @*/ 2673 PetscErrorCode TSPreStep(TS ts) 2674 { 2675 PetscErrorCode ierr; 2676 2677 PetscFunctionBegin; 2678 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2679 if (ts->prestep) { 2680 PetscStackCallStandard((*ts->prestep),(ts)); 2681 } 2682 PetscFunctionReturn(0); 2683 } 2684 2685 #undef __FUNCT__ 2686 #define __FUNCT__ "TSSetPreStage" 2687 /*@C 2688 TSSetPreStage - Sets the general-purpose function 2689 called once at the beginning of each stage. 2690 2691 Logically Collective on TS 2692 2693 Input Parameters: 2694 + ts - The TS context obtained from TSCreate() 2695 - func - The function 2696 2697 Calling sequence of func: 2698 . PetscErrorCode func(TS ts, PetscReal stagetime); 2699 2700 Level: intermediate 2701 2702 Note: 2703 There may be several stages per time step. If the solve for a given stage fails, the step may be rejected and retried. 2704 The time step number being computed can be queried using TSGetTimeStepNumber() and the total size of the step being 2705 attempted can be obtained using TSGetTimeStep(). The time at the start of the step is available via TSGetTime(). 2706 2707 .keywords: TS, timestep 2708 .seealso: TSSetPostStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext() 2709 @*/ 2710 PetscErrorCode TSSetPreStage(TS ts, PetscErrorCode (*func)(TS,PetscReal)) 2711 { 2712 PetscFunctionBegin; 2713 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 2714 ts->prestage = func; 2715 PetscFunctionReturn(0); 2716 } 2717 2718 #undef __FUNCT__ 2719 #define __FUNCT__ "TSSetPostStage" 2720 /*@C 2721 TSSetPostStage - Sets the general-purpose function 2722 called once at the end of each stage. 2723 2724 Logically Collective on TS 2725 2726 Input Parameters: 2727 + ts - The TS context obtained from TSCreate() 2728 - func - The function 2729 2730 Calling sequence of func: 2731 . PetscErrorCode func(TS ts, PetscReal stagetime, PetscInt stageindex, Vec* Y); 2732 2733 Level: intermediate 2734 2735 Note: 2736 There may be several stages per time step. If the solve for a given stage fails, the step may be rejected and retried. 2737 The time step number being computed can be queried using TSGetTimeStepNumber() and the total size of the step being 2738 attempted can be obtained using TSGetTimeStep(). The time at the start of the step is available via TSGetTime(). 2739 2740 .keywords: TS, timestep 2741 .seealso: TSSetPreStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext() 2742 @*/ 2743 PetscErrorCode TSSetPostStage(TS ts, PetscErrorCode (*func)(TS,PetscReal,PetscInt,Vec*)) 2744 { 2745 PetscFunctionBegin; 2746 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 2747 ts->poststage = func; 2748 PetscFunctionReturn(0); 2749 } 2750 2751 #undef __FUNCT__ 2752 #define __FUNCT__ "TSPreStage" 2753 /*@ 2754 TSPreStage - Runs the user-defined pre-stage function set using TSSetPreStage() 2755 2756 Collective on TS 2757 2758 Input Parameters: 2759 . ts - The TS context obtained from TSCreate() 2760 stagetime - The absolute time of the current stage 2761 2762 Notes: 2763 TSPreStage() is typically used within time stepping implementations, 2764 most users would not generally call this routine themselves. 2765 2766 Level: developer 2767 2768 .keywords: TS, timestep 2769 .seealso: TSPostStage(), TSSetPreStep(), TSPreStep(), TSPostStep() 2770 @*/ 2771 PetscErrorCode TSPreStage(TS ts, PetscReal stagetime) 2772 { 2773 PetscErrorCode ierr; 2774 2775 PetscFunctionBegin; 2776 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2777 if (ts->prestage) { 2778 PetscStackCallStandard((*ts->prestage),(ts,stagetime)); 2779 } 2780 PetscFunctionReturn(0); 2781 } 2782 2783 #undef __FUNCT__ 2784 #define __FUNCT__ "TSPostStage" 2785 /*@ 2786 TSPostStage - Runs the user-defined post-stage function set using TSSetPostStage() 2787 2788 Collective on TS 2789 2790 Input Parameters: 2791 . ts - The TS context obtained from TSCreate() 2792 stagetime - The absolute time of the current stage 2793 stageindex - Stage number 2794 Y - Array of vectors (of size = total number 2795 of stages) with the stage solutions 2796 2797 Notes: 2798 TSPostStage() is typically used within time stepping implementations, 2799 most users would not generally call this routine themselves. 2800 2801 Level: developer 2802 2803 .keywords: TS, timestep 2804 .seealso: TSPreStage(), TSSetPreStep(), TSPreStep(), TSPostStep() 2805 @*/ 2806 PetscErrorCode TSPostStage(TS ts, PetscReal stagetime, PetscInt stageindex, Vec *Y) 2807 { 2808 PetscErrorCode ierr; 2809 2810 PetscFunctionBegin; 2811 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2812 if (ts->poststage) { 2813 PetscStackCallStandard((*ts->poststage),(ts,stagetime,stageindex,Y)); 2814 } 2815 PetscFunctionReturn(0); 2816 } 2817 2818 #undef __FUNCT__ 2819 #define __FUNCT__ "TSSetPostStep" 2820 /*@C 2821 TSSetPostStep - Sets the general-purpose function 2822 called once at the end of each time step. 2823 2824 Logically Collective on TS 2825 2826 Input Parameters: 2827 + ts - The TS context obtained from TSCreate() 2828 - func - The function 2829 2830 Calling sequence of func: 2831 $ func (TS ts); 2832 2833 Level: intermediate 2834 2835 .keywords: TS, timestep 2836 .seealso: TSSetPreStep(), TSSetPreStage(), TSGetTimeStep(), TSGetTimeStepNumber(), TSGetTime() 2837 @*/ 2838 PetscErrorCode TSSetPostStep(TS ts, PetscErrorCode (*func)(TS)) 2839 { 2840 PetscFunctionBegin; 2841 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 2842 ts->poststep = func; 2843 PetscFunctionReturn(0); 2844 } 2845 2846 #undef __FUNCT__ 2847 #define __FUNCT__ "TSPostStep" 2848 /*@ 2849 TSPostStep - Runs the user-defined post-step function. 2850 2851 Collective on TS 2852 2853 Input Parameters: 2854 . ts - The TS context obtained from TSCreate() 2855 2856 Notes: 2857 TSPostStep() is typically used within time stepping implementations, 2858 so most users would not generally call this routine themselves. 2859 2860 Level: developer 2861 2862 .keywords: TS, timestep 2863 @*/ 2864 PetscErrorCode TSPostStep(TS ts) 2865 { 2866 PetscErrorCode ierr; 2867 2868 PetscFunctionBegin; 2869 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2870 if (ts->poststep) { 2871 PetscStackCallStandard((*ts->poststep),(ts)); 2872 } 2873 PetscFunctionReturn(0); 2874 } 2875 2876 /* ------------ Routines to set performance monitoring options ----------- */ 2877 2878 #undef __FUNCT__ 2879 #define __FUNCT__ "TSMonitorSet" 2880 /*@C 2881 TSMonitorSet - Sets an ADDITIONAL function that is to be used at every 2882 timestep to display the iteration's progress. 2883 2884 Logically Collective on TS 2885 2886 Input Parameters: 2887 + ts - the TS context obtained from TSCreate() 2888 . monitor - monitoring routine 2889 . mctx - [optional] user-defined context for private data for the 2890 monitor routine (use NULL if no context is desired) 2891 - monitordestroy - [optional] routine that frees monitor context 2892 (may be NULL) 2893 2894 Calling sequence of monitor: 2895 $ int monitor(TS ts,PetscInt steps,PetscReal time,Vec u,void *mctx) 2896 2897 + ts - the TS context 2898 . steps - iteration number (after the final time step the monitor routine is called with a step of -1, this is at the final time which may have 2899 been interpolated to) 2900 . time - current time 2901 . u - current iterate 2902 - mctx - [optional] monitoring context 2903 2904 Notes: 2905 This routine adds an additional monitor to the list of monitors that 2906 already has been loaded. 2907 2908 Fortran notes: Only a single monitor function can be set for each TS object 2909 2910 Level: intermediate 2911 2912 .keywords: TS, timestep, set, monitor 2913 2914 .seealso: TSMonitorDefault(), TSMonitorCancel() 2915 @*/ 2916 PetscErrorCode TSMonitorSet(TS ts,PetscErrorCode (*monitor)(TS,PetscInt,PetscReal,Vec,void*),void *mctx,PetscErrorCode (*mdestroy)(void**)) 2917 { 2918 PetscFunctionBegin; 2919 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2920 if (ts->numbermonitors >= MAXTSMONITORS) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Too many monitors set"); 2921 ts->monitor[ts->numbermonitors] = monitor; 2922 ts->monitordestroy[ts->numbermonitors] = mdestroy; 2923 ts->monitorcontext[ts->numbermonitors++] = (void*)mctx; 2924 PetscFunctionReturn(0); 2925 } 2926 2927 #undef __FUNCT__ 2928 #define __FUNCT__ "TSMonitorCancel" 2929 /*@C 2930 TSMonitorCancel - Clears all the monitors that have been set on a time-step object. 2931 2932 Logically Collective on TS 2933 2934 Input Parameters: 2935 . ts - the TS context obtained from TSCreate() 2936 2937 Notes: 2938 There is no way to remove a single, specific monitor. 2939 2940 Level: intermediate 2941 2942 .keywords: TS, timestep, set, monitor 2943 2944 .seealso: TSMonitorDefault(), TSMonitorSet() 2945 @*/ 2946 PetscErrorCode TSMonitorCancel(TS ts) 2947 { 2948 PetscErrorCode ierr; 2949 PetscInt i; 2950 2951 PetscFunctionBegin; 2952 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2953 for (i=0; i<ts->numbermonitors; i++) { 2954 if (ts->monitordestroy[i]) { 2955 ierr = (*ts->monitordestroy[i])(&ts->monitorcontext[i]);CHKERRQ(ierr); 2956 } 2957 } 2958 ts->numbermonitors = 0; 2959 PetscFunctionReturn(0); 2960 } 2961 2962 #undef __FUNCT__ 2963 #define __FUNCT__ "TSMonitorDefault" 2964 /*@ 2965 TSMonitorDefault - Sets the Default monitor 2966 2967 Level: intermediate 2968 2969 .keywords: TS, set, monitor 2970 2971 .seealso: TSMonitorDefault(), TSMonitorSet() 2972 @*/ 2973 PetscErrorCode TSMonitorDefault(TS ts,PetscInt step,PetscReal ptime,Vec v,void *dummy) 2974 { 2975 PetscErrorCode ierr; 2976 PetscViewer viewer = dummy ? (PetscViewer) dummy : PETSC_VIEWER_STDOUT_(PetscObjectComm((PetscObject)ts)); 2977 2978 PetscFunctionBegin; 2979 ierr = PetscViewerASCIIAddTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 2980 ierr = PetscViewerASCIIPrintf(viewer,"%D TS dt %g time %g%s",step,(double)ts->time_step,(double)ptime,ts->steprollback ? " (r)\n" : "\n");CHKERRQ(ierr); 2981 ierr = PetscViewerASCIISubtractTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 2982 PetscFunctionReturn(0); 2983 } 2984 2985 #undef __FUNCT__ 2986 #define __FUNCT__ "TSSetRetainStages" 2987 /*@ 2988 TSSetRetainStages - Request that all stages in the upcoming step be stored so that interpolation will be available. 2989 2990 Logically Collective on TS 2991 2992 Input Argument: 2993 . ts - time stepping context 2994 2995 Output Argument: 2996 . flg - PETSC_TRUE or PETSC_FALSE 2997 2998 Level: intermediate 2999 3000 .keywords: TS, set 3001 3002 .seealso: TSInterpolate(), TSSetPostStep() 3003 @*/ 3004 PetscErrorCode TSSetRetainStages(TS ts,PetscBool flg) 3005 { 3006 PetscFunctionBegin; 3007 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3008 ts->retain_stages = flg; 3009 PetscFunctionReturn(0); 3010 } 3011 3012 #undef __FUNCT__ 3013 #define __FUNCT__ "TSInterpolate" 3014 /*@ 3015 TSInterpolate - Interpolate the solution computed during the previous step to an arbitrary location in the interval 3016 3017 Collective on TS 3018 3019 Input Argument: 3020 + ts - time stepping context 3021 - t - time to interpolate to 3022 3023 Output Argument: 3024 . U - state at given time 3025 3026 Notes: 3027 The user should call TSSetRetainStages() before taking a step in which interpolation will be requested. 3028 3029 Level: intermediate 3030 3031 Developer Notes: 3032 TSInterpolate() and the storing of previous steps/stages should be generalized to support delay differential equations and continuous adjoints. 3033 3034 .keywords: TS, set 3035 3036 .seealso: TSSetRetainStages(), TSSetPostStep() 3037 @*/ 3038 PetscErrorCode TSInterpolate(TS ts,PetscReal t,Vec U) 3039 { 3040 PetscErrorCode ierr; 3041 3042 PetscFunctionBegin; 3043 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3044 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 3045 if (t < ts->ptime - ts->time_step_prev || t > ts->ptime) SETERRQ3(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Requested time %g not in last time steps [%g,%g]",t,(double)(ts->ptime-ts->time_step_prev),(double)ts->ptime); 3046 if (!ts->ops->interpolate) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"%s does not provide interpolation",((PetscObject)ts)->type_name); 3047 ierr = (*ts->ops->interpolate)(ts,t,U);CHKERRQ(ierr); 3048 PetscFunctionReturn(0); 3049 } 3050 3051 #undef __FUNCT__ 3052 #define __FUNCT__ "TSStep" 3053 /*@ 3054 TSStep - Steps one time step 3055 3056 Collective on TS 3057 3058 Input Parameter: 3059 . ts - the TS context obtained from TSCreate() 3060 3061 Level: developer 3062 3063 Notes: 3064 The public interface for the ODE/DAE solvers is TSSolve(), you should almost for sure be using that routine and not this routine. 3065 3066 The hook set using TSSetPreStep() is called before each attempt to take the step. In general, the time step size may 3067 be changed due to adaptive error controller or solve failures. Note that steps may contain multiple stages. 3068 3069 This may over-step the final time provided in TSSetDuration() depending on the time-step used. TSSolve() interpolates to exactly the 3070 time provided in TSSetDuration(). One can use TSInterpolate() to determine an interpolated solution within the final timestep. 3071 3072 .keywords: TS, timestep, solve 3073 3074 .seealso: TSCreate(), TSSetUp(), TSDestroy(), TSSolve(), TSSetPreStep(), TSSetPreStage(), TSSetPostStage(), TSInterpolate() 3075 @*/ 3076 PetscErrorCode TSStep(TS ts) 3077 { 3078 DM dm; 3079 PetscErrorCode ierr; 3080 static PetscBool cite = PETSC_FALSE; 3081 3082 PetscFunctionBegin; 3083 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3084 ierr = PetscCitationsRegister("@techreport{tspaper,\n" 3085 " title = {{PETSc/TS}: A Modern Scalable {DAE/ODE} Solver Library},\n" 3086 " author = {Shrirang Abhyankar and Jed Brown and Emil Constantinescu and Debojyoti Ghosh and Barry F. Smith},\n" 3087 " type = {Preprint},\n" 3088 " number = {ANL/MCS-P5061-0114},\n" 3089 " institution = {Argonne National Laboratory},\n" 3090 " year = {2014}\n}\n",&cite);CHKERRQ(ierr); 3091 3092 ierr = TSGetDM(ts, &dm);CHKERRQ(ierr); 3093 ierr = TSSetUp(ts);CHKERRQ(ierr); 3094 3095 ts->reason = TS_CONVERGED_ITERATING; 3096 ts->ptime_prev = ts->ptime; 3097 ierr = DMSetOutputSequenceNumber(dm, ts->steps, ts->ptime);CHKERRQ(ierr); 3098 3099 if (!ts->ops->step) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSStep not implemented for type '%s'",((PetscObject)ts)->type_name); 3100 ierr = PetscLogEventBegin(TS_Step,ts,0,0,0);CHKERRQ(ierr); 3101 ierr = (*ts->ops->step)(ts);CHKERRQ(ierr); 3102 ierr = PetscLogEventEnd(TS_Step,ts,0,0,0);CHKERRQ(ierr); 3103 3104 ts->time_step_prev = ts->ptime - ts->ptime_prev; 3105 ierr = DMSetOutputSequenceNumber(dm, ts->steps, ts->ptime);CHKERRQ(ierr); 3106 3107 if (ts->reason < 0) { 3108 if (ts->errorifstepfailed) { 3109 if (ts->reason == TS_DIVERGED_NONLINEAR_SOLVE) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s, increase -ts_max_snes_failures or make negative to attempt recovery",TSConvergedReasons[ts->reason]); 3110 else SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s",TSConvergedReasons[ts->reason]); 3111 } 3112 } else if (!ts->reason) { 3113 if (ts->steps >= ts->max_steps) ts->reason = TS_CONVERGED_ITS; 3114 else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME; 3115 } 3116 ts->total_steps++; 3117 ts->steprollback = PETSC_FALSE; 3118 PetscFunctionReturn(0); 3119 } 3120 3121 #undef __FUNCT__ 3122 #define __FUNCT__ "TSAdjointStep" 3123 /*@ 3124 TSAdjointStep - Steps one time step 3125 3126 Collective on TS 3127 3128 Input Parameter: 3129 . ts - the TS context obtained from TSCreate() 3130 3131 Level: intermediate 3132 3133 Notes: 3134 The hook set using TSSetPreStep() is called before each attempt to take the step. In general, the time step size may 3135 be changed due to adaptive error controller or solve failures. Note that steps may contain multiple stages. 3136 3137 This may over-step the final time provided in TSSetDuration() depending on the time-step used. TSSolve() interpolates to exactly the 3138 time provided in TSSetDuration(). One can use TSInterpolate() to determine an interpolated solution within the final timestep. 3139 3140 .keywords: TS, timestep, solve 3141 3142 .seealso: TSCreate(), TSSetUp(), TSDestroy(), TSSolve(), TSSetPreStep(), TSSetPreStage(), TSSetPostStage(), TSInterpolate() 3143 @*/ 3144 PetscErrorCode TSAdjointStep(TS ts) 3145 { 3146 DM dm; 3147 PetscErrorCode ierr; 3148 3149 PetscFunctionBegin; 3150 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3151 ierr = TSGetDM(ts, &dm);CHKERRQ(ierr); 3152 ierr = TSAdjointSetUp(ts);CHKERRQ(ierr); 3153 3154 ts->reason = TS_CONVERGED_ITERATING; 3155 ts->ptime_prev = ts->ptime; 3156 ierr = DMSetOutputSequenceNumber(dm, ts->steps, ts->ptime);CHKERRQ(ierr); 3157 ierr = VecViewFromOptions(ts->vec_sol, ((PetscObject) ts)->prefix, "-ts_view_solution");CHKERRQ(ierr); 3158 3159 ierr = PetscLogEventBegin(TS_Step,ts,0,0,0);CHKERRQ(ierr); 3160 if (!ts->ops->adjointstep) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed because the adjoint of %s has not been implemented, try other time stepping methods for adjoint sensitivity analysis",((PetscObject)ts)->type_name); 3161 ierr = (*ts->ops->adjointstep)(ts);CHKERRQ(ierr); 3162 ierr = PetscLogEventEnd(TS_Step,ts,0,0,0);CHKERRQ(ierr); 3163 3164 ts->time_step_prev = ts->ptime - ts->ptime_prev; 3165 ierr = DMSetOutputSequenceNumber(dm, ts->steps, ts->ptime);CHKERRQ(ierr); 3166 3167 if (ts->reason < 0) { 3168 if (ts->errorifstepfailed) { 3169 if (ts->reason == TS_DIVERGED_NONLINEAR_SOLVE) { 3170 SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s, increase -ts_max_snes_failures or make negative to attempt recovery",TSConvergedReasons[ts->reason]); 3171 } else if (ts->reason == TS_DIVERGED_STEP_REJECTED) { 3172 SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s, increase -ts_max_reject or make negative to attempt recovery",TSConvergedReasons[ts->reason]); 3173 } else SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s",TSConvergedReasons[ts->reason]); 3174 } 3175 } else if (!ts->reason) { 3176 if (ts->steps >= ts->adjoint_max_steps) ts->reason = TS_CONVERGED_ITS; 3177 else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME; 3178 } 3179 ts->total_steps--; 3180 PetscFunctionReturn(0); 3181 } 3182 3183 #undef __FUNCT__ 3184 #define __FUNCT__ "TSEvaluateStep" 3185 /*@ 3186 TSEvaluateStep - Evaluate the solution at the end of a time step with a given order of accuracy. 3187 3188 Collective on TS 3189 3190 Input Arguments: 3191 + ts - time stepping context 3192 . order - desired order of accuracy 3193 - done - whether the step was evaluated at this order (pass NULL to generate an error if not available) 3194 3195 Output Arguments: 3196 . U - state at the end of the current step 3197 3198 Level: advanced 3199 3200 Notes: 3201 This function cannot be called until all stages have been evaluated. 3202 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. 3203 3204 .seealso: TSStep(), TSAdapt 3205 @*/ 3206 PetscErrorCode TSEvaluateStep(TS ts,PetscInt order,Vec U,PetscBool *done) 3207 { 3208 PetscErrorCode ierr; 3209 3210 PetscFunctionBegin; 3211 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3212 PetscValidType(ts,1); 3213 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 3214 if (!ts->ops->evaluatestep) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSEvaluateStep not implemented for type '%s'",((PetscObject)ts)->type_name); 3215 ierr = (*ts->ops->evaluatestep)(ts,order,U,done);CHKERRQ(ierr); 3216 PetscFunctionReturn(0); 3217 } 3218 3219 3220 #undef __FUNCT__ 3221 #define __FUNCT__ "TSSolve" 3222 /*@ 3223 TSSolve - Steps the requested number of timesteps. 3224 3225 Collective on TS 3226 3227 Input Parameter: 3228 + ts - the TS context obtained from TSCreate() 3229 - u - the solution vector (can be null if TSSetSolution() was used, otherwise must contain the initial conditions) 3230 3231 Level: beginner 3232 3233 Notes: 3234 The final time returned by this function may be different from the time of the internally 3235 held state accessible by TSGetSolution() and TSGetTime() because the method may have 3236 stepped over the final time. 3237 3238 .keywords: TS, timestep, solve 3239 3240 .seealso: TSCreate(), TSSetSolution(), TSStep() 3241 @*/ 3242 PetscErrorCode TSSolve(TS ts,Vec u) 3243 { 3244 Vec solution; 3245 PetscErrorCode ierr; 3246 3247 PetscFunctionBegin; 3248 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3249 if (u) PetscValidHeaderSpecific(u,VEC_CLASSID,2); 3250 if (ts->exact_final_time == TS_EXACTFINALTIME_INTERPOLATE) { /* Need ts->vec_sol to be distinct so it is not overwritten when we interpolate at the end */ 3251 PetscValidHeaderSpecific(u,VEC_CLASSID,2); 3252 if (!ts->vec_sol || u == ts->vec_sol) { 3253 ierr = VecDuplicate(u,&solution);CHKERRQ(ierr); 3254 ierr = TSSetSolution(ts,solution);CHKERRQ(ierr); 3255 ierr = VecDestroy(&solution);CHKERRQ(ierr); /* grant ownership */ 3256 } 3257 ierr = VecCopy(u,ts->vec_sol);CHKERRQ(ierr); 3258 } else if (u) { 3259 ierr = TSSetSolution(ts,u);CHKERRQ(ierr); 3260 } 3261 ierr = TSSetUp(ts);CHKERRQ(ierr); 3262 /* reset time step and iteration counters */ 3263 ts->steps = 0; 3264 ts->ksp_its = 0; 3265 ts->snes_its = 0; 3266 ts->num_snes_failures = 0; 3267 ts->reject = 0; 3268 ts->reason = TS_CONVERGED_ITERATING; 3269 3270 ierr = TSViewFromOptions(ts,NULL,"-ts_view_pre");CHKERRQ(ierr); 3271 { 3272 DM dm; 3273 ierr = TSGetDM(ts, &dm);CHKERRQ(ierr); 3274 ierr = DMSetOutputSequenceNumber(dm, ts->steps, ts->ptime);CHKERRQ(ierr); 3275 } 3276 3277 if (ts->ops->solve) { /* This private interface is transitional and should be removed when all implementations are updated. */ 3278 ierr = (*ts->ops->solve)(ts);CHKERRQ(ierr); 3279 ierr = VecCopy(ts->vec_sol,u);CHKERRQ(ierr); 3280 ts->solvetime = ts->ptime; 3281 } else { 3282 /* steps the requested number of timesteps. */ 3283 if (ts->steps >= ts->max_steps) ts->reason = TS_CONVERGED_ITS; 3284 else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME; 3285 ierr = TSTrajectorySet(ts->trajectory,ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 3286 if (ts->vec_costintegral) ts->costintegralfwd=PETSC_TRUE; 3287 if(ts->event) { 3288 ierr = TSEventMonitorInitialize(ts);CHKERRQ(ierr); 3289 } 3290 while (!ts->reason) { 3291 ierr = TSMonitor(ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 3292 ierr = TSStep(ts);CHKERRQ(ierr); 3293 if (ts->event) { 3294 ierr = TSEventMonitor(ts);CHKERRQ(ierr); 3295 } 3296 if(!ts->steprollback) { 3297 ierr = TSTrajectorySet(ts->trajectory,ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 3298 ierr = TSPostStep(ts);CHKERRQ(ierr); 3299 } 3300 } 3301 if (ts->exact_final_time == TS_EXACTFINALTIME_INTERPOLATE && ts->ptime > ts->max_time) { 3302 ierr = TSInterpolate(ts,ts->max_time,u);CHKERRQ(ierr); 3303 ts->solvetime = ts->max_time; 3304 solution = u; 3305 } else { 3306 if (u) {ierr = VecCopy(ts->vec_sol,u);CHKERRQ(ierr);} 3307 ts->solvetime = ts->ptime; 3308 solution = ts->vec_sol; 3309 } 3310 ierr = TSMonitor(ts,ts->steps,ts->solvetime,solution);CHKERRQ(ierr); 3311 ierr = VecViewFromOptions(solution, ((PetscObject) ts)->prefix, "-ts_view_solution");CHKERRQ(ierr); 3312 } 3313 3314 ierr = TSViewFromOptions(ts,NULL,"-ts_view");CHKERRQ(ierr); 3315 ierr = VecViewFromOptions(ts->vec_sol,NULL,"-ts_view_solution");CHKERRQ(ierr); 3316 ierr = PetscObjectSAWsBlock((PetscObject)ts);CHKERRQ(ierr); 3317 if (ts->adjoint_solve) { 3318 ierr = TSAdjointSolve(ts);CHKERRQ(ierr); 3319 } 3320 PetscFunctionReturn(0); 3321 } 3322 3323 #undef __FUNCT__ 3324 #define __FUNCT__ "TSAdjointSolve" 3325 /*@ 3326 TSAdjointSolve - Solves the discrete ajoint problem for an ODE/DAE 3327 3328 Collective on TS 3329 3330 Input Parameter: 3331 . ts - the TS context obtained from TSCreate() 3332 3333 Options Database: 3334 . -ts_adjoint_view_solution <viewerinfo> - views the first gradient with respect to the initial conditions 3335 3336 Level: intermediate 3337 3338 Notes: 3339 This must be called after a call to TSSolve() that solves the forward problem 3340 3341 By default this will integrate back to the initial time, one can use TSAdjointSetSteps() to step back to a later time 3342 3343 .keywords: TS, timestep, solve 3344 3345 .seealso: TSCreate(), TSSetSolution(), TSStep() 3346 @*/ 3347 PetscErrorCode TSAdjointSolve(TS ts) 3348 { 3349 PetscErrorCode ierr; 3350 3351 PetscFunctionBegin; 3352 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3353 ierr = TSAdjointSetUp(ts);CHKERRQ(ierr); 3354 /* reset time step and iteration counters */ 3355 ts->steps = 0; 3356 ts->ksp_its = 0; 3357 ts->snes_its = 0; 3358 ts->num_snes_failures = 0; 3359 ts->reject = 0; 3360 ts->reason = TS_CONVERGED_ITERATING; 3361 3362 if (!ts->adjoint_max_steps) ts->adjoint_max_steps = ts->total_steps; 3363 3364 if (ts->steps >= ts->adjoint_max_steps) ts->reason = TS_CONVERGED_ITS; 3365 while (!ts->reason) { 3366 ierr = TSTrajectoryGet(ts->trajectory,ts,ts->adjoint_max_steps-ts->steps,ts->ptime);CHKERRQ(ierr); 3367 ierr = TSMonitor(ts,ts->adjoint_max_steps-ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 3368 ierr = TSAdjointStep(ts);CHKERRQ(ierr); 3369 if (ts->event) { 3370 ierr = TSAdjointEventMonitor(ts);CHKERRQ(ierr); 3371 } 3372 3373 #if 0 /* I don't think PostStep is needed in AdjointSolve */ 3374 if (ts->event->status != TSEVENT_PROCESSING) { 3375 ierr = TSPostStep(ts);CHKERRQ(ierr); 3376 } 3377 } else { 3378 ierr = TSPostStep(ts);CHKERRQ(ierr); 3379 } 3380 #endif 3381 } 3382 ts->solvetime = ts->ptime; 3383 ierr = VecViewFromOptions(ts->vecs_sensi[0], ((PetscObject) ts)->prefix, "-ts_adjoint_view_solution");CHKERRQ(ierr); 3384 PetscFunctionReturn(0); 3385 } 3386 3387 #undef __FUNCT__ 3388 #define __FUNCT__ "TSMonitor" 3389 /*@ 3390 TSMonitor - Runs all user-provided monitor routines set using TSMonitorSet() 3391 3392 Collective on TS 3393 3394 Input Parameters: 3395 + ts - time stepping context obtained from TSCreate() 3396 . step - step number that has just completed 3397 . ptime - model time of the state 3398 - u - state at the current model time 3399 3400 Notes: 3401 TSMonitor() is typically used within the time stepping implementations. 3402 Users might call this function when using the TSStep() interface instead of TSSolve(). 3403 3404 Level: advanced 3405 3406 .keywords: TS, timestep 3407 @*/ 3408 PetscErrorCode TSMonitor(TS ts,PetscInt step,PetscReal ptime,Vec u) 3409 { 3410 PetscErrorCode ierr; 3411 PetscInt i,n = ts->numbermonitors; 3412 3413 PetscFunctionBegin; 3414 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3415 PetscValidHeaderSpecific(u,VEC_CLASSID,4); 3416 ierr = VecLockPush(u);CHKERRQ(ierr); 3417 for (i=0; i<n; i++) { 3418 ierr = (*ts->monitor[i])(ts,step,ptime,u,ts->monitorcontext[i]);CHKERRQ(ierr); 3419 } 3420 ierr = VecLockPop(u);CHKERRQ(ierr); 3421 PetscFunctionReturn(0); 3422 } 3423 3424 /* ------------------------------------------------------------------------*/ 3425 #undef __FUNCT__ 3426 #define __FUNCT__ "TSMonitorLGCtxCreate" 3427 /*@C 3428 TSMonitorLGCtxCreate - Creates a line graph context for use with 3429 TS to monitor the solution process graphically in various ways 3430 3431 Collective on TS 3432 3433 Input Parameters: 3434 + host - the X display to open, or null for the local machine 3435 . label - the title to put in the title bar 3436 . x, y - the screen coordinates of the upper left coordinate of the window 3437 . m, n - the screen width and height in pixels 3438 - howoften - if positive then determines the frequency of the plotting, if -1 then only at the final time 3439 3440 Output Parameter: 3441 . ctx - the context 3442 3443 Options Database Key: 3444 + -ts_monitor_lg_timestep - automatically sets line graph monitor 3445 . -ts_monitor_lg_solution - 3446 . -ts_monitor_lg_error - 3447 . -ts_monitor_lg_ksp_iterations - 3448 . -ts_monitor_lg_snes_iterations - 3449 - -lg_use_markers <true,false> - mark the data points (at each time step) on the plot; default is true 3450 3451 Notes: 3452 Use TSMonitorLGCtxDestroy() to destroy. 3453 3454 Level: intermediate 3455 3456 .keywords: TS, monitor, line graph, residual, seealso 3457 3458 .seealso: TSMonitorLGTimeStep(), TSMonitorSet(), TSMonitorLGSolution(), TSMonitorLGError() 3459 3460 @*/ 3461 PetscErrorCode TSMonitorLGCtxCreate(MPI_Comm comm,const char host[],const char label[],int x,int y,int m,int n,PetscInt howoften,TSMonitorLGCtx *ctx) 3462 { 3463 PetscDraw win; 3464 PetscErrorCode ierr; 3465 3466 PetscFunctionBegin; 3467 ierr = PetscNew(ctx);CHKERRQ(ierr); 3468 ierr = PetscDrawCreate(comm,host,label,x,y,m,n,&win);CHKERRQ(ierr); 3469 ierr = PetscDrawSetFromOptions(win);CHKERRQ(ierr); 3470 ierr = PetscDrawLGCreate(win,1,&(*ctx)->lg);CHKERRQ(ierr); 3471 ierr = PetscLogObjectParent((PetscObject)(*ctx)->lg,(PetscObject)win);CHKERRQ(ierr); 3472 ierr = PetscDrawLGSetUseMarkers((*ctx)->lg,PETSC_TRUE);CHKERRQ(ierr); 3473 ierr = PetscDrawLGSetFromOptions((*ctx)->lg);CHKERRQ(ierr); 3474 (*ctx)->howoften = howoften; 3475 PetscFunctionReturn(0); 3476 } 3477 3478 #undef __FUNCT__ 3479 #define __FUNCT__ "TSMonitorLGTimeStep" 3480 PetscErrorCode TSMonitorLGTimeStep(TS ts,PetscInt step,PetscReal ptime,Vec v,void *monctx) 3481 { 3482 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 3483 PetscReal x = ptime,y; 3484 PetscErrorCode ierr; 3485 3486 PetscFunctionBegin; 3487 if (!step) { 3488 PetscDrawAxis axis; 3489 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 3490 ierr = PetscDrawAxisSetLabels(axis,"Timestep as function of time","Time","Time step");CHKERRQ(ierr); 3491 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 3492 } 3493 ierr = TSGetTimeStep(ts,&y);CHKERRQ(ierr); 3494 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 3495 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 3496 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 3497 } 3498 PetscFunctionReturn(0); 3499 } 3500 3501 #undef __FUNCT__ 3502 #define __FUNCT__ "TSMonitorLGCtxDestroy" 3503 /*@C 3504 TSMonitorLGCtxDestroy - Destroys a line graph context that was created 3505 with TSMonitorLGCtxCreate(). 3506 3507 Collective on TSMonitorLGCtx 3508 3509 Input Parameter: 3510 . ctx - the monitor context 3511 3512 Level: intermediate 3513 3514 .keywords: TS, monitor, line graph, destroy 3515 3516 .seealso: TSMonitorLGCtxCreate(), TSMonitorSet(), TSMonitorLGTimeStep(); 3517 @*/ 3518 PetscErrorCode TSMonitorLGCtxDestroy(TSMonitorLGCtx *ctx) 3519 { 3520 PetscDraw draw; 3521 PetscErrorCode ierr; 3522 3523 PetscFunctionBegin; 3524 if ((*ctx)->transformdestroy) { 3525 ierr = ((*ctx)->transformdestroy)((*ctx)->transformctx);CHKERRQ(ierr); 3526 } 3527 ierr = PetscDrawLGGetDraw((*ctx)->lg,&draw);CHKERRQ(ierr); 3528 ierr = PetscDrawDestroy(&draw);CHKERRQ(ierr); 3529 ierr = PetscDrawLGDestroy(&(*ctx)->lg);CHKERRQ(ierr); 3530 ierr = PetscStrArrayDestroy(&(*ctx)->names);CHKERRQ(ierr); 3531 ierr = PetscStrArrayDestroy(&(*ctx)->displaynames);CHKERRQ(ierr); 3532 ierr = PetscFree((*ctx)->displayvariables);CHKERRQ(ierr); 3533 ierr = PetscFree((*ctx)->displayvalues);CHKERRQ(ierr); 3534 ierr = PetscFree(*ctx);CHKERRQ(ierr); 3535 PetscFunctionReturn(0); 3536 } 3537 3538 #undef __FUNCT__ 3539 #define __FUNCT__ "TSGetTime" 3540 /*@ 3541 TSGetTime - Gets the time of the most recently completed step. 3542 3543 Not Collective 3544 3545 Input Parameter: 3546 . ts - the TS context obtained from TSCreate() 3547 3548 Output Parameter: 3549 . t - the current time 3550 3551 Level: beginner 3552 3553 Note: 3554 When called during time step evaluation (e.g. during residual evaluation or via hooks set using TSSetPreStep(), 3555 TSSetPreStage(), TSSetPostStage(), or TSSetPostStep()), the time is the time at the start of the step being evaluated. 3556 3557 .seealso: TSSetInitialTimeStep(), TSGetTimeStep() 3558 3559 .keywords: TS, get, time 3560 @*/ 3561 PetscErrorCode TSGetTime(TS ts,PetscReal *t) 3562 { 3563 PetscFunctionBegin; 3564 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3565 PetscValidRealPointer(t,2); 3566 *t = ts->ptime; 3567 PetscFunctionReturn(0); 3568 } 3569 3570 #undef __FUNCT__ 3571 #define __FUNCT__ "TSGetPrevTime" 3572 /*@ 3573 TSGetPrevTime - Gets the starting time of the previously completed step. 3574 3575 Not Collective 3576 3577 Input Parameter: 3578 . ts - the TS context obtained from TSCreate() 3579 3580 Output Parameter: 3581 . t - the previous time 3582 3583 Level: beginner 3584 3585 .seealso: TSSetInitialTimeStep(), TSGetTimeStep() 3586 3587 .keywords: TS, get, time 3588 @*/ 3589 PetscErrorCode TSGetPrevTime(TS ts,PetscReal *t) 3590 { 3591 PetscFunctionBegin; 3592 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3593 PetscValidRealPointer(t,2); 3594 *t = ts->ptime_prev; 3595 PetscFunctionReturn(0); 3596 } 3597 3598 #undef __FUNCT__ 3599 #define __FUNCT__ "TSSetTime" 3600 /*@ 3601 TSSetTime - Allows one to reset the time. 3602 3603 Logically Collective on TS 3604 3605 Input Parameters: 3606 + ts - the TS context obtained from TSCreate() 3607 - time - the time 3608 3609 Level: intermediate 3610 3611 .seealso: TSGetTime(), TSSetDuration() 3612 3613 .keywords: TS, set, time 3614 @*/ 3615 PetscErrorCode TSSetTime(TS ts, PetscReal t) 3616 { 3617 PetscFunctionBegin; 3618 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3619 PetscValidLogicalCollectiveReal(ts,t,2); 3620 ts->ptime = t; 3621 PetscFunctionReturn(0); 3622 } 3623 3624 #undef __FUNCT__ 3625 #define __FUNCT__ "TSSetOptionsPrefix" 3626 /*@C 3627 TSSetOptionsPrefix - Sets the prefix used for searching for all 3628 TS options in the database. 3629 3630 Logically Collective on TS 3631 3632 Input Parameter: 3633 + ts - The TS context 3634 - prefix - The prefix to prepend to all option names 3635 3636 Notes: 3637 A hyphen (-) must NOT be given at the beginning of the prefix name. 3638 The first character of all runtime options is AUTOMATICALLY the 3639 hyphen. 3640 3641 Level: advanced 3642 3643 .keywords: TS, set, options, prefix, database 3644 3645 .seealso: TSSetFromOptions() 3646 3647 @*/ 3648 PetscErrorCode TSSetOptionsPrefix(TS ts,const char prefix[]) 3649 { 3650 PetscErrorCode ierr; 3651 SNES snes; 3652 3653 PetscFunctionBegin; 3654 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3655 ierr = PetscObjectSetOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 3656 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 3657 ierr = SNESSetOptionsPrefix(snes,prefix);CHKERRQ(ierr); 3658 PetscFunctionReturn(0); 3659 } 3660 3661 3662 #undef __FUNCT__ 3663 #define __FUNCT__ "TSAppendOptionsPrefix" 3664 /*@C 3665 TSAppendOptionsPrefix - Appends to the prefix used for searching for all 3666 TS options in the database. 3667 3668 Logically Collective on TS 3669 3670 Input Parameter: 3671 + ts - The TS context 3672 - prefix - The prefix to prepend to all option names 3673 3674 Notes: 3675 A hyphen (-) must NOT be given at the beginning of the prefix name. 3676 The first character of all runtime options is AUTOMATICALLY the 3677 hyphen. 3678 3679 Level: advanced 3680 3681 .keywords: TS, append, options, prefix, database 3682 3683 .seealso: TSGetOptionsPrefix() 3684 3685 @*/ 3686 PetscErrorCode TSAppendOptionsPrefix(TS ts,const char prefix[]) 3687 { 3688 PetscErrorCode ierr; 3689 SNES snes; 3690 3691 PetscFunctionBegin; 3692 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3693 ierr = PetscObjectAppendOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 3694 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 3695 ierr = SNESAppendOptionsPrefix(snes,prefix);CHKERRQ(ierr); 3696 PetscFunctionReturn(0); 3697 } 3698 3699 #undef __FUNCT__ 3700 #define __FUNCT__ "TSGetOptionsPrefix" 3701 /*@C 3702 TSGetOptionsPrefix - Sets the prefix used for searching for all 3703 TS options in the database. 3704 3705 Not Collective 3706 3707 Input Parameter: 3708 . ts - The TS context 3709 3710 Output Parameter: 3711 . prefix - A pointer to the prefix string used 3712 3713 Notes: On the fortran side, the user should pass in a string 'prifix' of 3714 sufficient length to hold the prefix. 3715 3716 Level: intermediate 3717 3718 .keywords: TS, get, options, prefix, database 3719 3720 .seealso: TSAppendOptionsPrefix() 3721 @*/ 3722 PetscErrorCode TSGetOptionsPrefix(TS ts,const char *prefix[]) 3723 { 3724 PetscErrorCode ierr; 3725 3726 PetscFunctionBegin; 3727 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3728 PetscValidPointer(prefix,2); 3729 ierr = PetscObjectGetOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 3730 PetscFunctionReturn(0); 3731 } 3732 3733 #undef __FUNCT__ 3734 #define __FUNCT__ "TSGetRHSJacobian" 3735 /*@C 3736 TSGetRHSJacobian - Returns the Jacobian J at the present timestep. 3737 3738 Not Collective, but parallel objects are returned if TS is parallel 3739 3740 Input Parameter: 3741 . ts - The TS context obtained from TSCreate() 3742 3743 Output Parameters: 3744 + Amat - The (approximate) Jacobian J of G, where U_t = G(U,t) (or NULL) 3745 . Pmat - The matrix from which the preconditioner is constructed, usually the same as Amat (or NULL) 3746 . func - Function to compute the Jacobian of the RHS (or NULL) 3747 - ctx - User-defined context for Jacobian evaluation routine (or NULL) 3748 3749 Notes: You can pass in NULL for any return argument you do not need. 3750 3751 Level: intermediate 3752 3753 .seealso: TSGetTimeStep(), TSGetMatrices(), TSGetTime(), TSGetTimeStepNumber() 3754 3755 .keywords: TS, timestep, get, matrix, Jacobian 3756 @*/ 3757 PetscErrorCode TSGetRHSJacobian(TS ts,Mat *Amat,Mat *Pmat,TSRHSJacobian *func,void **ctx) 3758 { 3759 PetscErrorCode ierr; 3760 SNES snes; 3761 DM dm; 3762 3763 PetscFunctionBegin; 3764 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 3765 ierr = SNESGetJacobian(snes,Amat,Pmat,NULL,NULL);CHKERRQ(ierr); 3766 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 3767 ierr = DMTSGetRHSJacobian(dm,func,ctx);CHKERRQ(ierr); 3768 PetscFunctionReturn(0); 3769 } 3770 3771 #undef __FUNCT__ 3772 #define __FUNCT__ "TSGetIJacobian" 3773 /*@C 3774 TSGetIJacobian - Returns the implicit Jacobian at the present timestep. 3775 3776 Not Collective, but parallel objects are returned if TS is parallel 3777 3778 Input Parameter: 3779 . ts - The TS context obtained from TSCreate() 3780 3781 Output Parameters: 3782 + Amat - The (approximate) Jacobian of F(t,U,U_t) 3783 . Pmat - The matrix from which the preconditioner is constructed, often the same as Amat 3784 . f - The function to compute the matrices 3785 - ctx - User-defined context for Jacobian evaluation routine 3786 3787 Notes: You can pass in NULL for any return argument you do not need. 3788 3789 Level: advanced 3790 3791 .seealso: TSGetTimeStep(), TSGetRHSJacobian(), TSGetMatrices(), TSGetTime(), TSGetTimeStepNumber() 3792 3793 .keywords: TS, timestep, get, matrix, Jacobian 3794 @*/ 3795 PetscErrorCode TSGetIJacobian(TS ts,Mat *Amat,Mat *Pmat,TSIJacobian *f,void **ctx) 3796 { 3797 PetscErrorCode ierr; 3798 SNES snes; 3799 DM dm; 3800 3801 PetscFunctionBegin; 3802 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 3803 ierr = SNESSetUpMatrices(snes);CHKERRQ(ierr); 3804 ierr = SNESGetJacobian(snes,Amat,Pmat,NULL,NULL);CHKERRQ(ierr); 3805 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 3806 ierr = DMTSGetIJacobian(dm,f,ctx);CHKERRQ(ierr); 3807 PetscFunctionReturn(0); 3808 } 3809 3810 3811 #undef __FUNCT__ 3812 #define __FUNCT__ "TSMonitorDrawSolution" 3813 /*@C 3814 TSMonitorDrawSolution - Monitors progress of the TS solvers by calling 3815 VecView() for the solution at each timestep 3816 3817 Collective on TS 3818 3819 Input Parameters: 3820 + ts - the TS context 3821 . step - current time-step 3822 . ptime - current time 3823 - dummy - either a viewer or NULL 3824 3825 Options Database: 3826 . -ts_monitor_draw_solution_initial - show initial solution as well as current solution 3827 3828 Notes: the initial solution and current solution are not display with a common axis scaling so generally the option -ts_monitor_draw_solution_initial 3829 will look bad 3830 3831 Level: intermediate 3832 3833 .keywords: TS, vector, monitor, view 3834 3835 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 3836 @*/ 3837 PetscErrorCode TSMonitorDrawSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 3838 { 3839 PetscErrorCode ierr; 3840 TSMonitorDrawCtx ictx = (TSMonitorDrawCtx)dummy; 3841 PetscDraw draw; 3842 3843 PetscFunctionBegin; 3844 if (!step && ictx->showinitial) { 3845 if (!ictx->initialsolution) { 3846 ierr = VecDuplicate(u,&ictx->initialsolution);CHKERRQ(ierr); 3847 } 3848 ierr = VecCopy(u,ictx->initialsolution);CHKERRQ(ierr); 3849 } 3850 if (!(((ictx->howoften > 0) && (!(step % ictx->howoften))) || ((ictx->howoften == -1) && ts->reason))) PetscFunctionReturn(0); 3851 3852 if (ictx->showinitial) { 3853 PetscReal pause; 3854 ierr = PetscViewerDrawGetPause(ictx->viewer,&pause);CHKERRQ(ierr); 3855 ierr = PetscViewerDrawSetPause(ictx->viewer,0.0);CHKERRQ(ierr); 3856 ierr = VecView(ictx->initialsolution,ictx->viewer);CHKERRQ(ierr); 3857 ierr = PetscViewerDrawSetPause(ictx->viewer,pause);CHKERRQ(ierr); 3858 ierr = PetscViewerDrawSetHold(ictx->viewer,PETSC_TRUE);CHKERRQ(ierr); 3859 } 3860 ierr = VecView(u,ictx->viewer);CHKERRQ(ierr); 3861 if (ictx->showtimestepandtime) { 3862 PetscReal xl,yl,xr,yr,h; 3863 char time[32]; 3864 3865 ierr = PetscViewerDrawGetDraw(ictx->viewer,0,&draw);CHKERRQ(ierr); 3866 ierr = PetscSNPrintf(time,32,"Timestep %d Time %g",(int)step,(double)ptime);CHKERRQ(ierr); 3867 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 3868 h = yl + .95*(yr - yl); 3869 ierr = PetscDrawStringCentered(draw,.5*(xl+xr),h,PETSC_DRAW_BLACK,time);CHKERRQ(ierr); 3870 ierr = PetscDrawFlush(draw);CHKERRQ(ierr); 3871 } 3872 3873 if (ictx->showinitial) { 3874 ierr = PetscViewerDrawSetHold(ictx->viewer,PETSC_FALSE);CHKERRQ(ierr); 3875 } 3876 PetscFunctionReturn(0); 3877 } 3878 3879 #undef __FUNCT__ 3880 #define __FUNCT__ "TSMonitorDrawSolutionPhase" 3881 /*@C 3882 TSMonitorDrawSolutionPhase - Monitors progress of the TS solvers by plotting the solution as a phase diagram 3883 3884 Collective on TS 3885 3886 Input Parameters: 3887 + ts - the TS context 3888 . step - current time-step 3889 . ptime - current time 3890 - dummy - either a viewer or NULL 3891 3892 Level: intermediate 3893 3894 .keywords: TS, vector, monitor, view 3895 3896 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 3897 @*/ 3898 PetscErrorCode TSMonitorDrawSolutionPhase(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 3899 { 3900 PetscErrorCode ierr; 3901 TSMonitorDrawCtx ictx = (TSMonitorDrawCtx)dummy; 3902 PetscDraw draw; 3903 MPI_Comm comm; 3904 PetscInt n; 3905 PetscMPIInt size; 3906 PetscReal xl,yl,xr,yr,h; 3907 char time[32]; 3908 const PetscScalar *U; 3909 3910 PetscFunctionBegin; 3911 ierr = PetscObjectGetComm((PetscObject)ts,&comm);CHKERRQ(ierr); 3912 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3913 if (size != 1) SETERRQ(comm,PETSC_ERR_SUP,"Only allowed for sequential runs"); 3914 ierr = VecGetSize(u,&n);CHKERRQ(ierr); 3915 if (n != 2) SETERRQ(comm,PETSC_ERR_SUP,"Only for ODEs with two unknowns"); 3916 3917 ierr = PetscViewerDrawGetDraw(ictx->viewer,0,&draw);CHKERRQ(ierr); 3918 3919 ierr = VecGetArrayRead(u,&U);CHKERRQ(ierr); 3920 ierr = PetscDrawAxisGetLimits(ictx->axis,&xl,&xr,&yl,&yr);CHKERRQ(ierr); 3921 if ((PetscRealPart(U[0]) < xl) || (PetscRealPart(U[1]) < yl) || (PetscRealPart(U[0]) > xr) || (PetscRealPart(U[1]) > yr)) { 3922 ierr = VecRestoreArrayRead(u,&U);CHKERRQ(ierr); 3923 PetscFunctionReturn(0); 3924 } 3925 if (!step) ictx->color++; 3926 ierr = PetscDrawPoint(draw,PetscRealPart(U[0]),PetscRealPart(U[1]),ictx->color);CHKERRQ(ierr); 3927 ierr = VecRestoreArrayRead(u,&U);CHKERRQ(ierr); 3928 3929 if (ictx->showtimestepandtime) { 3930 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 3931 ierr = PetscSNPrintf(time,32,"Timestep %d Time %g",(int)step,(double)ptime);CHKERRQ(ierr); 3932 h = yl + .95*(yr - yl); 3933 ierr = PetscDrawStringCentered(draw,.5*(xl+xr),h,PETSC_DRAW_BLACK,time);CHKERRQ(ierr); 3934 } 3935 ierr = PetscDrawFlush(draw);CHKERRQ(ierr); 3936 PetscFunctionReturn(0); 3937 } 3938 3939 3940 #undef __FUNCT__ 3941 #define __FUNCT__ "TSMonitorDrawCtxDestroy" 3942 /*@C 3943 TSMonitorDrawCtxDestroy - Destroys the monitor context for TSMonitorDrawSolution() 3944 3945 Collective on TS 3946 3947 Input Parameters: 3948 . ctx - the monitor context 3949 3950 Level: intermediate 3951 3952 .keywords: TS, vector, monitor, view 3953 3954 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorDrawSolution(), TSMonitorDrawError() 3955 @*/ 3956 PetscErrorCode TSMonitorDrawCtxDestroy(TSMonitorDrawCtx *ictx) 3957 { 3958 PetscErrorCode ierr; 3959 3960 PetscFunctionBegin; 3961 ierr = PetscDrawAxisDestroy(&(*ictx)->axis);CHKERRQ(ierr); 3962 ierr = PetscViewerDestroy(&(*ictx)->viewer);CHKERRQ(ierr); 3963 ierr = VecDestroy(&(*ictx)->initialsolution);CHKERRQ(ierr); 3964 ierr = PetscFree(*ictx);CHKERRQ(ierr); 3965 PetscFunctionReturn(0); 3966 } 3967 3968 #undef __FUNCT__ 3969 #define __FUNCT__ "TSMonitorDrawCtxCreate" 3970 /*@C 3971 TSMonitorDrawCtxCreate - Creates the monitor context for TSMonitorDrawCtx 3972 3973 Collective on TS 3974 3975 Input Parameter: 3976 . ts - time-step context 3977 3978 Output Patameter: 3979 . ctx - the monitor context 3980 3981 Options Database: 3982 . -ts_monitor_draw_solution_initial - show initial solution as well as current solution 3983 3984 Level: intermediate 3985 3986 .keywords: TS, vector, monitor, view 3987 3988 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorDrawCtx() 3989 @*/ 3990 PetscErrorCode TSMonitorDrawCtxCreate(MPI_Comm comm,const char host[],const char label[],int x,int y,int m,int n,PetscInt howoften,TSMonitorDrawCtx *ctx) 3991 { 3992 PetscErrorCode ierr; 3993 3994 PetscFunctionBegin; 3995 ierr = PetscNew(ctx);CHKERRQ(ierr); 3996 ierr = PetscViewerDrawOpen(comm,host,label,x,y,m,n,&(*ctx)->viewer);CHKERRQ(ierr); 3997 ierr = PetscViewerSetFromOptions((*ctx)->viewer);CHKERRQ(ierr); 3998 3999 (*ctx)->howoften = howoften; 4000 (*ctx)->showinitial = PETSC_FALSE; 4001 ierr = PetscOptionsGetBool(NULL,"-ts_monitor_draw_solution_initial",&(*ctx)->showinitial,NULL);CHKERRQ(ierr); 4002 4003 (*ctx)->showtimestepandtime = PETSC_FALSE; 4004 ierr = PetscOptionsGetBool(NULL,"-ts_monitor_draw_solution_show_time",&(*ctx)->showtimestepandtime,NULL);CHKERRQ(ierr); 4005 (*ctx)->color = PETSC_DRAW_WHITE; 4006 PetscFunctionReturn(0); 4007 } 4008 4009 #undef __FUNCT__ 4010 #define __FUNCT__ "TSMonitorDrawError" 4011 /*@C 4012 TSMonitorDrawError - Monitors progress of the TS solvers by calling 4013 VecView() for the error at each timestep 4014 4015 Collective on TS 4016 4017 Input Parameters: 4018 + ts - the TS context 4019 . step - current time-step 4020 . ptime - current time 4021 - dummy - either a viewer or NULL 4022 4023 Level: intermediate 4024 4025 .keywords: TS, vector, monitor, view 4026 4027 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 4028 @*/ 4029 PetscErrorCode TSMonitorDrawError(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 4030 { 4031 PetscErrorCode ierr; 4032 TSMonitorDrawCtx ctx = (TSMonitorDrawCtx)dummy; 4033 PetscViewer viewer = ctx->viewer; 4034 Vec work; 4035 4036 PetscFunctionBegin; 4037 if (!(((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason))) PetscFunctionReturn(0); 4038 ierr = VecDuplicate(u,&work);CHKERRQ(ierr); 4039 ierr = TSComputeSolutionFunction(ts,ptime,work);CHKERRQ(ierr); 4040 ierr = VecAXPY(work,-1.0,u);CHKERRQ(ierr); 4041 ierr = VecView(work,viewer);CHKERRQ(ierr); 4042 ierr = VecDestroy(&work);CHKERRQ(ierr); 4043 PetscFunctionReturn(0); 4044 } 4045 4046 #include <petsc/private/dmimpl.h> 4047 #undef __FUNCT__ 4048 #define __FUNCT__ "TSSetDM" 4049 /*@ 4050 TSSetDM - Sets the DM that may be used by some preconditioners 4051 4052 Logically Collective on TS and DM 4053 4054 Input Parameters: 4055 + ts - the preconditioner context 4056 - dm - the dm 4057 4058 Level: intermediate 4059 4060 4061 .seealso: TSGetDM(), SNESSetDM(), SNESGetDM() 4062 @*/ 4063 PetscErrorCode TSSetDM(TS ts,DM dm) 4064 { 4065 PetscErrorCode ierr; 4066 SNES snes; 4067 DMTS tsdm; 4068 4069 PetscFunctionBegin; 4070 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4071 ierr = PetscObjectReference((PetscObject)dm);CHKERRQ(ierr); 4072 if (ts->dm) { /* Move the DMTS context over to the new DM unless the new DM already has one */ 4073 if (ts->dm->dmts && !dm->dmts) { 4074 ierr = DMCopyDMTS(ts->dm,dm);CHKERRQ(ierr); 4075 ierr = DMGetDMTS(ts->dm,&tsdm);CHKERRQ(ierr); 4076 if (tsdm->originaldm == ts->dm) { /* Grant write privileges to the replacement DM */ 4077 tsdm->originaldm = dm; 4078 } 4079 } 4080 ierr = DMDestroy(&ts->dm);CHKERRQ(ierr); 4081 } 4082 ts->dm = dm; 4083 4084 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4085 ierr = SNESSetDM(snes,dm);CHKERRQ(ierr); 4086 PetscFunctionReturn(0); 4087 } 4088 4089 #undef __FUNCT__ 4090 #define __FUNCT__ "TSGetDM" 4091 /*@ 4092 TSGetDM - Gets the DM that may be used by some preconditioners 4093 4094 Not Collective 4095 4096 Input Parameter: 4097 . ts - the preconditioner context 4098 4099 Output Parameter: 4100 . dm - the dm 4101 4102 Level: intermediate 4103 4104 4105 .seealso: TSSetDM(), SNESSetDM(), SNESGetDM() 4106 @*/ 4107 PetscErrorCode TSGetDM(TS ts,DM *dm) 4108 { 4109 PetscErrorCode ierr; 4110 4111 PetscFunctionBegin; 4112 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4113 if (!ts->dm) { 4114 ierr = DMShellCreate(PetscObjectComm((PetscObject)ts),&ts->dm);CHKERRQ(ierr); 4115 if (ts->snes) {ierr = SNESSetDM(ts->snes,ts->dm);CHKERRQ(ierr);} 4116 } 4117 *dm = ts->dm; 4118 PetscFunctionReturn(0); 4119 } 4120 4121 #undef __FUNCT__ 4122 #define __FUNCT__ "SNESTSFormFunction" 4123 /*@ 4124 SNESTSFormFunction - Function to evaluate nonlinear residual 4125 4126 Logically Collective on SNES 4127 4128 Input Parameter: 4129 + snes - nonlinear solver 4130 . U - the current state at which to evaluate the residual 4131 - ctx - user context, must be a TS 4132 4133 Output Parameter: 4134 . F - the nonlinear residual 4135 4136 Notes: 4137 This function is not normally called by users and is automatically registered with the SNES used by TS. 4138 It is most frequently passed to MatFDColoringSetFunction(). 4139 4140 Level: advanced 4141 4142 .seealso: SNESSetFunction(), MatFDColoringSetFunction() 4143 @*/ 4144 PetscErrorCode SNESTSFormFunction(SNES snes,Vec U,Vec F,void *ctx) 4145 { 4146 TS ts = (TS)ctx; 4147 PetscErrorCode ierr; 4148 4149 PetscFunctionBegin; 4150 PetscValidHeaderSpecific(snes,SNES_CLASSID,1); 4151 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 4152 PetscValidHeaderSpecific(F,VEC_CLASSID,3); 4153 PetscValidHeaderSpecific(ts,TS_CLASSID,4); 4154 ierr = (ts->ops->snesfunction)(snes,U,F,ts);CHKERRQ(ierr); 4155 PetscFunctionReturn(0); 4156 } 4157 4158 #undef __FUNCT__ 4159 #define __FUNCT__ "SNESTSFormJacobian" 4160 /*@ 4161 SNESTSFormJacobian - Function to evaluate the Jacobian 4162 4163 Collective on SNES 4164 4165 Input Parameter: 4166 + snes - nonlinear solver 4167 . U - the current state at which to evaluate the residual 4168 - ctx - user context, must be a TS 4169 4170 Output Parameter: 4171 + A - the Jacobian 4172 . B - the preconditioning matrix (may be the same as A) 4173 - flag - indicates any structure change in the matrix 4174 4175 Notes: 4176 This function is not normally called by users and is automatically registered with the SNES used by TS. 4177 4178 Level: developer 4179 4180 .seealso: SNESSetJacobian() 4181 @*/ 4182 PetscErrorCode SNESTSFormJacobian(SNES snes,Vec U,Mat A,Mat B,void *ctx) 4183 { 4184 TS ts = (TS)ctx; 4185 PetscErrorCode ierr; 4186 4187 PetscFunctionBegin; 4188 PetscValidHeaderSpecific(snes,SNES_CLASSID,1); 4189 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 4190 PetscValidPointer(A,3); 4191 PetscValidHeaderSpecific(A,MAT_CLASSID,3); 4192 PetscValidPointer(B,4); 4193 PetscValidHeaderSpecific(B,MAT_CLASSID,4); 4194 PetscValidHeaderSpecific(ts,TS_CLASSID,6); 4195 ierr = (ts->ops->snesjacobian)(snes,U,A,B,ts);CHKERRQ(ierr); 4196 PetscFunctionReturn(0); 4197 } 4198 4199 #undef __FUNCT__ 4200 #define __FUNCT__ "TSComputeRHSFunctionLinear" 4201 /*@C 4202 TSComputeRHSFunctionLinear - Evaluate the right hand side via the user-provided Jacobian, for linear problems only 4203 4204 Collective on TS 4205 4206 Input Arguments: 4207 + ts - time stepping context 4208 . t - time at which to evaluate 4209 . U - state at which to evaluate 4210 - ctx - context 4211 4212 Output Arguments: 4213 . F - right hand side 4214 4215 Level: intermediate 4216 4217 Notes: 4218 This function is intended to be passed to TSSetRHSFunction() to evaluate the right hand side for linear problems. 4219 The matrix (and optionally the evaluation context) should be passed to TSSetRHSJacobian(). 4220 4221 .seealso: TSSetRHSFunction(), TSSetRHSJacobian(), TSComputeRHSJacobianConstant() 4222 @*/ 4223 PetscErrorCode TSComputeRHSFunctionLinear(TS ts,PetscReal t,Vec U,Vec F,void *ctx) 4224 { 4225 PetscErrorCode ierr; 4226 Mat Arhs,Brhs; 4227 4228 PetscFunctionBegin; 4229 ierr = TSGetRHSMats_Private(ts,&Arhs,&Brhs);CHKERRQ(ierr); 4230 ierr = TSComputeRHSJacobian(ts,t,U,Arhs,Brhs);CHKERRQ(ierr); 4231 ierr = MatMult(Arhs,U,F);CHKERRQ(ierr); 4232 PetscFunctionReturn(0); 4233 } 4234 4235 #undef __FUNCT__ 4236 #define __FUNCT__ "TSComputeRHSJacobianConstant" 4237 /*@C 4238 TSComputeRHSJacobianConstant - Reuses a Jacobian that is time-independent. 4239 4240 Collective on TS 4241 4242 Input Arguments: 4243 + ts - time stepping context 4244 . t - time at which to evaluate 4245 . U - state at which to evaluate 4246 - ctx - context 4247 4248 Output Arguments: 4249 + A - pointer to operator 4250 . B - pointer to preconditioning matrix 4251 - flg - matrix structure flag 4252 4253 Level: intermediate 4254 4255 Notes: 4256 This function is intended to be passed to TSSetRHSJacobian() to evaluate the Jacobian for linear time-independent problems. 4257 4258 .seealso: TSSetRHSFunction(), TSSetRHSJacobian(), TSComputeRHSFunctionLinear() 4259 @*/ 4260 PetscErrorCode TSComputeRHSJacobianConstant(TS ts,PetscReal t,Vec U,Mat A,Mat B,void *ctx) 4261 { 4262 PetscFunctionBegin; 4263 PetscFunctionReturn(0); 4264 } 4265 4266 #undef __FUNCT__ 4267 #define __FUNCT__ "TSComputeIFunctionLinear" 4268 /*@C 4269 TSComputeIFunctionLinear - Evaluate the left hand side via the user-provided Jacobian, for linear problems only 4270 4271 Collective on TS 4272 4273 Input Arguments: 4274 + ts - time stepping context 4275 . t - time at which to evaluate 4276 . U - state at which to evaluate 4277 . Udot - time derivative of state vector 4278 - ctx - context 4279 4280 Output Arguments: 4281 . F - left hand side 4282 4283 Level: intermediate 4284 4285 Notes: 4286 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 4287 user is required to write their own TSComputeIFunction. 4288 This function is intended to be passed to TSSetIFunction() to evaluate the left hand side for linear problems. 4289 The matrix (and optionally the evaluation context) should be passed to TSSetIJacobian(). 4290 4291 .seealso: TSSetIFunction(), TSSetIJacobian(), TSComputeIJacobianConstant() 4292 @*/ 4293 PetscErrorCode TSComputeIFunctionLinear(TS ts,PetscReal t,Vec U,Vec Udot,Vec F,void *ctx) 4294 { 4295 PetscErrorCode ierr; 4296 Mat A,B; 4297 4298 PetscFunctionBegin; 4299 ierr = TSGetIJacobian(ts,&A,&B,NULL,NULL);CHKERRQ(ierr); 4300 ierr = TSComputeIJacobian(ts,t,U,Udot,1.0,A,B,PETSC_TRUE);CHKERRQ(ierr); 4301 ierr = MatMult(A,Udot,F);CHKERRQ(ierr); 4302 PetscFunctionReturn(0); 4303 } 4304 4305 #undef __FUNCT__ 4306 #define __FUNCT__ "TSComputeIJacobianConstant" 4307 /*@C 4308 TSComputeIJacobianConstant - Reuses a time-independent for a semi-implicit DAE or ODE 4309 4310 Collective on TS 4311 4312 Input Arguments: 4313 + ts - time stepping context 4314 . t - time at which to evaluate 4315 . U - state at which to evaluate 4316 . Udot - time derivative of state vector 4317 . shift - shift to apply 4318 - ctx - context 4319 4320 Output Arguments: 4321 + A - pointer to operator 4322 . B - pointer to preconditioning matrix 4323 - flg - matrix structure flag 4324 4325 Level: advanced 4326 4327 Notes: 4328 This function is intended to be passed to TSSetIJacobian() to evaluate the Jacobian for linear time-independent problems. 4329 4330 It is only appropriate for problems of the form 4331 4332 $ M Udot = F(U,t) 4333 4334 where M is constant and F is non-stiff. The user must pass M to TSSetIJacobian(). The current implementation only 4335 works with IMEX time integration methods such as TSROSW and TSARKIMEX, since there is no support for de-constructing 4336 an implicit operator of the form 4337 4338 $ shift*M + J 4339 4340 where J is the Jacobian of -F(U). Support may be added in a future version of PETSc, but for now, the user must store 4341 a copy of M or reassemble it when requested. 4342 4343 .seealso: TSSetIFunction(), TSSetIJacobian(), TSComputeIFunctionLinear() 4344 @*/ 4345 PetscErrorCode TSComputeIJacobianConstant(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat A,Mat B,void *ctx) 4346 { 4347 PetscErrorCode ierr; 4348 4349 PetscFunctionBegin; 4350 ierr = MatScale(A, shift / ts->ijacobian.shift);CHKERRQ(ierr); 4351 ts->ijacobian.shift = shift; 4352 PetscFunctionReturn(0); 4353 } 4354 4355 #undef __FUNCT__ 4356 #define __FUNCT__ "TSGetEquationType" 4357 /*@ 4358 TSGetEquationType - Gets the type of the equation that TS is solving. 4359 4360 Not Collective 4361 4362 Input Parameter: 4363 . ts - the TS context 4364 4365 Output Parameter: 4366 . equation_type - see TSEquationType 4367 4368 Level: beginner 4369 4370 .keywords: TS, equation type 4371 4372 .seealso: TSSetEquationType(), TSEquationType 4373 @*/ 4374 PetscErrorCode TSGetEquationType(TS ts,TSEquationType *equation_type) 4375 { 4376 PetscFunctionBegin; 4377 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4378 PetscValidPointer(equation_type,2); 4379 *equation_type = ts->equation_type; 4380 PetscFunctionReturn(0); 4381 } 4382 4383 #undef __FUNCT__ 4384 #define __FUNCT__ "TSSetEquationType" 4385 /*@ 4386 TSSetEquationType - Sets the type of the equation that TS is solving. 4387 4388 Not Collective 4389 4390 Input Parameter: 4391 + ts - the TS context 4392 - equation_type - see TSEquationType 4393 4394 Level: advanced 4395 4396 .keywords: TS, equation type 4397 4398 .seealso: TSGetEquationType(), TSEquationType 4399 @*/ 4400 PetscErrorCode TSSetEquationType(TS ts,TSEquationType equation_type) 4401 { 4402 PetscFunctionBegin; 4403 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4404 ts->equation_type = equation_type; 4405 PetscFunctionReturn(0); 4406 } 4407 4408 #undef __FUNCT__ 4409 #define __FUNCT__ "TSGetConvergedReason" 4410 /*@ 4411 TSGetConvergedReason - Gets the reason the TS iteration was stopped. 4412 4413 Not Collective 4414 4415 Input Parameter: 4416 . ts - the TS context 4417 4418 Output Parameter: 4419 . reason - negative value indicates diverged, positive value converged, see TSConvergedReason or the 4420 manual pages for the individual convergence tests for complete lists 4421 4422 Level: beginner 4423 4424 Notes: 4425 Can only be called after the call to TSSolve() is complete. 4426 4427 .keywords: TS, nonlinear, set, convergence, test 4428 4429 .seealso: TSSetConvergenceTest(), TSConvergedReason 4430 @*/ 4431 PetscErrorCode TSGetConvergedReason(TS ts,TSConvergedReason *reason) 4432 { 4433 PetscFunctionBegin; 4434 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4435 PetscValidPointer(reason,2); 4436 *reason = ts->reason; 4437 PetscFunctionReturn(0); 4438 } 4439 4440 #undef __FUNCT__ 4441 #define __FUNCT__ "TSSetConvergedReason" 4442 /*@ 4443 TSSetConvergedReason - Sets the reason for handling the convergence of TSSolve. 4444 4445 Not Collective 4446 4447 Input Parameter: 4448 + ts - the TS context 4449 . reason - negative value indicates diverged, positive value converged, see TSConvergedReason or the 4450 manual pages for the individual convergence tests for complete lists 4451 4452 Level: advanced 4453 4454 Notes: 4455 Can only be called during TSSolve() is active. 4456 4457 .keywords: TS, nonlinear, set, convergence, test 4458 4459 .seealso: TSConvergedReason 4460 @*/ 4461 PetscErrorCode TSSetConvergedReason(TS ts,TSConvergedReason reason) 4462 { 4463 PetscFunctionBegin; 4464 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4465 ts->reason = reason; 4466 PetscFunctionReturn(0); 4467 } 4468 4469 #undef __FUNCT__ 4470 #define __FUNCT__ "TSGetSolveTime" 4471 /*@ 4472 TSGetSolveTime - Gets the time after a call to TSSolve() 4473 4474 Not Collective 4475 4476 Input Parameter: 4477 . ts - the TS context 4478 4479 Output Parameter: 4480 . ftime - the final time. This time should correspond to the final time set with TSSetDuration() 4481 4482 Level: beginner 4483 4484 Notes: 4485 Can only be called after the call to TSSolve() is complete. 4486 4487 .keywords: TS, nonlinear, set, convergence, test 4488 4489 .seealso: TSSetConvergenceTest(), TSConvergedReason 4490 @*/ 4491 PetscErrorCode TSGetSolveTime(TS ts,PetscReal *ftime) 4492 { 4493 PetscFunctionBegin; 4494 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4495 PetscValidPointer(ftime,2); 4496 *ftime = ts->solvetime; 4497 PetscFunctionReturn(0); 4498 } 4499 4500 #undef __FUNCT__ 4501 #define __FUNCT__ "TSGetTotalSteps" 4502 /*@ 4503 TSGetTotalSteps - Gets the total number of steps done since the last call to TSSetUp() or TSCreate() 4504 4505 Not Collective 4506 4507 Input Parameter: 4508 . ts - the TS context 4509 4510 Output Parameter: 4511 . steps - the number of steps 4512 4513 Level: beginner 4514 4515 Notes: 4516 Includes the number of steps for all calls to TSSolve() since TSSetUp() was called 4517 4518 .keywords: TS, nonlinear, set, convergence, test 4519 4520 .seealso: TSSetConvergenceTest(), TSConvergedReason 4521 @*/ 4522 PetscErrorCode TSGetTotalSteps(TS ts,PetscInt *steps) 4523 { 4524 PetscFunctionBegin; 4525 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4526 PetscValidPointer(steps,2); 4527 *steps = ts->total_steps; 4528 PetscFunctionReturn(0); 4529 } 4530 4531 #undef __FUNCT__ 4532 #define __FUNCT__ "TSGetSNESIterations" 4533 /*@ 4534 TSGetSNESIterations - Gets the total number of nonlinear iterations 4535 used by the time integrator. 4536 4537 Not Collective 4538 4539 Input Parameter: 4540 . ts - TS context 4541 4542 Output Parameter: 4543 . nits - number of nonlinear iterations 4544 4545 Notes: 4546 This counter is reset to zero for each successive call to TSSolve(). 4547 4548 Level: intermediate 4549 4550 .keywords: TS, get, number, nonlinear, iterations 4551 4552 .seealso: TSGetKSPIterations() 4553 @*/ 4554 PetscErrorCode TSGetSNESIterations(TS ts,PetscInt *nits) 4555 { 4556 PetscFunctionBegin; 4557 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4558 PetscValidIntPointer(nits,2); 4559 *nits = ts->snes_its; 4560 PetscFunctionReturn(0); 4561 } 4562 4563 #undef __FUNCT__ 4564 #define __FUNCT__ "TSGetKSPIterations" 4565 /*@ 4566 TSGetKSPIterations - Gets the total number of linear iterations 4567 used by the time integrator. 4568 4569 Not Collective 4570 4571 Input Parameter: 4572 . ts - TS context 4573 4574 Output Parameter: 4575 . lits - number of linear iterations 4576 4577 Notes: 4578 This counter is reset to zero for each successive call to TSSolve(). 4579 4580 Level: intermediate 4581 4582 .keywords: TS, get, number, linear, iterations 4583 4584 .seealso: TSGetSNESIterations(), SNESGetKSPIterations() 4585 @*/ 4586 PetscErrorCode TSGetKSPIterations(TS ts,PetscInt *lits) 4587 { 4588 PetscFunctionBegin; 4589 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4590 PetscValidIntPointer(lits,2); 4591 *lits = ts->ksp_its; 4592 PetscFunctionReturn(0); 4593 } 4594 4595 #undef __FUNCT__ 4596 #define __FUNCT__ "TSGetStepRejections" 4597 /*@ 4598 TSGetStepRejections - Gets the total number of rejected steps. 4599 4600 Not Collective 4601 4602 Input Parameter: 4603 . ts - TS context 4604 4605 Output Parameter: 4606 . rejects - number of steps rejected 4607 4608 Notes: 4609 This counter is reset to zero for each successive call to TSSolve(). 4610 4611 Level: intermediate 4612 4613 .keywords: TS, get, number 4614 4615 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetSNESFailures(), TSSetMaxSNESFailures(), TSSetErrorIfStepFails() 4616 @*/ 4617 PetscErrorCode TSGetStepRejections(TS ts,PetscInt *rejects) 4618 { 4619 PetscFunctionBegin; 4620 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4621 PetscValidIntPointer(rejects,2); 4622 *rejects = ts->reject; 4623 PetscFunctionReturn(0); 4624 } 4625 4626 #undef __FUNCT__ 4627 #define __FUNCT__ "TSGetSNESFailures" 4628 /*@ 4629 TSGetSNESFailures - Gets the total number of failed SNES solves 4630 4631 Not Collective 4632 4633 Input Parameter: 4634 . ts - TS context 4635 4636 Output Parameter: 4637 . fails - number of failed nonlinear solves 4638 4639 Notes: 4640 This counter is reset to zero for each successive call to TSSolve(). 4641 4642 Level: intermediate 4643 4644 .keywords: TS, get, number 4645 4646 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSSetMaxSNESFailures() 4647 @*/ 4648 PetscErrorCode TSGetSNESFailures(TS ts,PetscInt *fails) 4649 { 4650 PetscFunctionBegin; 4651 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4652 PetscValidIntPointer(fails,2); 4653 *fails = ts->num_snes_failures; 4654 PetscFunctionReturn(0); 4655 } 4656 4657 #undef __FUNCT__ 4658 #define __FUNCT__ "TSSetMaxStepRejections" 4659 /*@ 4660 TSSetMaxStepRejections - Sets the maximum number of step rejections before a step fails 4661 4662 Not Collective 4663 4664 Input Parameter: 4665 + ts - TS context 4666 - rejects - maximum number of rejected steps, pass -1 for unlimited 4667 4668 Notes: 4669 The counter is reset to zero for each step 4670 4671 Options Database Key: 4672 . -ts_max_reject - Maximum number of step rejections before a step fails 4673 4674 Level: intermediate 4675 4676 .keywords: TS, set, maximum, number 4677 4678 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxSNESFailures(), TSGetStepRejections(), TSGetSNESFailures(), TSSetErrorIfStepFails(), TSGetConvergedReason() 4679 @*/ 4680 PetscErrorCode TSSetMaxStepRejections(TS ts,PetscInt rejects) 4681 { 4682 PetscFunctionBegin; 4683 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4684 ts->max_reject = rejects; 4685 PetscFunctionReturn(0); 4686 } 4687 4688 #undef __FUNCT__ 4689 #define __FUNCT__ "TSSetMaxSNESFailures" 4690 /*@ 4691 TSSetMaxSNESFailures - Sets the maximum number of failed SNES solves 4692 4693 Not Collective 4694 4695 Input Parameter: 4696 + ts - TS context 4697 - fails - maximum number of failed nonlinear solves, pass -1 for unlimited 4698 4699 Notes: 4700 The counter is reset to zero for each successive call to TSSolve(). 4701 4702 Options Database Key: 4703 . -ts_max_snes_failures - Maximum number of nonlinear solve failures 4704 4705 Level: intermediate 4706 4707 .keywords: TS, set, maximum, number 4708 4709 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSGetSNESFailures(), SNESGetConvergedReason(), TSGetConvergedReason() 4710 @*/ 4711 PetscErrorCode TSSetMaxSNESFailures(TS ts,PetscInt fails) 4712 { 4713 PetscFunctionBegin; 4714 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4715 ts->max_snes_failures = fails; 4716 PetscFunctionReturn(0); 4717 } 4718 4719 #undef __FUNCT__ 4720 #define __FUNCT__ "TSSetErrorIfStepFails" 4721 /*@ 4722 TSSetErrorIfStepFails - Error if no step succeeds 4723 4724 Not Collective 4725 4726 Input Parameter: 4727 + ts - TS context 4728 - err - PETSC_TRUE to error if no step succeeds, PETSC_FALSE to return without failure 4729 4730 Options Database Key: 4731 . -ts_error_if_step_fails - Error if no step succeeds 4732 4733 Level: intermediate 4734 4735 .keywords: TS, set, error 4736 4737 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSGetSNESFailures(), TSSetErrorIfStepFails(), TSGetConvergedReason() 4738 @*/ 4739 PetscErrorCode TSSetErrorIfStepFails(TS ts,PetscBool err) 4740 { 4741 PetscFunctionBegin; 4742 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4743 ts->errorifstepfailed = err; 4744 PetscFunctionReturn(0); 4745 } 4746 4747 #undef __FUNCT__ 4748 #define __FUNCT__ "TSMonitorSolutionBinary" 4749 /*@C 4750 TSMonitorSolutionBinary - Monitors progress of the TS solvers by VecView() for the solution at each timestep. Normally the viewer is a binary file 4751 4752 Collective on TS 4753 4754 Input Parameters: 4755 + ts - the TS context 4756 . step - current time-step 4757 . ptime - current time 4758 . u - current state 4759 - viewer - binary viewer 4760 4761 Level: intermediate 4762 4763 .keywords: TS, vector, monitor, view 4764 4765 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 4766 @*/ 4767 PetscErrorCode TSMonitorSolutionBinary(TS ts,PetscInt step,PetscReal ptime,Vec u,void *viewer) 4768 { 4769 PetscErrorCode ierr; 4770 PetscViewer v = (PetscViewer)viewer; 4771 4772 PetscFunctionBegin; 4773 ierr = VecView(u,v);CHKERRQ(ierr); 4774 PetscFunctionReturn(0); 4775 } 4776 4777 #undef __FUNCT__ 4778 #define __FUNCT__ "TSMonitorSolutionVTK" 4779 /*@C 4780 TSMonitorSolutionVTK - Monitors progress of the TS solvers by VecView() for the solution at each timestep. 4781 4782 Collective on TS 4783 4784 Input Parameters: 4785 + ts - the TS context 4786 . step - current time-step 4787 . ptime - current time 4788 . u - current state 4789 - filenametemplate - string containing a format specifier for the integer time step (e.g. %03D) 4790 4791 Level: intermediate 4792 4793 Notes: 4794 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. 4795 These are named according to the file name template. 4796 4797 This function is normally passed as an argument to TSMonitorSet() along with TSMonitorSolutionVTKDestroy(). 4798 4799 .keywords: TS, vector, monitor, view 4800 4801 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 4802 @*/ 4803 PetscErrorCode TSMonitorSolutionVTK(TS ts,PetscInt step,PetscReal ptime,Vec u,void *filenametemplate) 4804 { 4805 PetscErrorCode ierr; 4806 char filename[PETSC_MAX_PATH_LEN]; 4807 PetscViewer viewer; 4808 4809 PetscFunctionBegin; 4810 ierr = PetscSNPrintf(filename,sizeof(filename),(const char*)filenametemplate,step);CHKERRQ(ierr); 4811 ierr = PetscViewerVTKOpen(PetscObjectComm((PetscObject)ts),filename,FILE_MODE_WRITE,&viewer);CHKERRQ(ierr); 4812 ierr = VecView(u,viewer);CHKERRQ(ierr); 4813 ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr); 4814 PetscFunctionReturn(0); 4815 } 4816 4817 #undef __FUNCT__ 4818 #define __FUNCT__ "TSMonitorSolutionVTKDestroy" 4819 /*@C 4820 TSMonitorSolutionVTKDestroy - Destroy context for monitoring 4821 4822 Collective on TS 4823 4824 Input Parameters: 4825 . filenametemplate - string containing a format specifier for the integer time step (e.g. %03D) 4826 4827 Level: intermediate 4828 4829 Note: 4830 This function is normally passed to TSMonitorSet() along with TSMonitorSolutionVTK(). 4831 4832 .keywords: TS, vector, monitor, view 4833 4834 .seealso: TSMonitorSet(), TSMonitorSolutionVTK() 4835 @*/ 4836 PetscErrorCode TSMonitorSolutionVTKDestroy(void *filenametemplate) 4837 { 4838 PetscErrorCode ierr; 4839 4840 PetscFunctionBegin; 4841 ierr = PetscFree(*(char**)filenametemplate);CHKERRQ(ierr); 4842 PetscFunctionReturn(0); 4843 } 4844 4845 #undef __FUNCT__ 4846 #define __FUNCT__ "TSGetAdapt" 4847 /*@ 4848 TSGetAdapt - Get the adaptive controller context for the current method 4849 4850 Collective on TS if controller has not been created yet 4851 4852 Input Arguments: 4853 . ts - time stepping context 4854 4855 Output Arguments: 4856 . adapt - adaptive controller 4857 4858 Level: intermediate 4859 4860 .seealso: TSAdapt, TSAdaptSetType(), TSAdaptChoose() 4861 @*/ 4862 PetscErrorCode TSGetAdapt(TS ts,TSAdapt *adapt) 4863 { 4864 PetscErrorCode ierr; 4865 4866 PetscFunctionBegin; 4867 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4868 PetscValidPointer(adapt,2); 4869 if (!ts->adapt) { 4870 ierr = TSAdaptCreate(PetscObjectComm((PetscObject)ts),&ts->adapt);CHKERRQ(ierr); 4871 ierr = PetscLogObjectParent((PetscObject)ts,(PetscObject)ts->adapt);CHKERRQ(ierr); 4872 ierr = PetscObjectIncrementTabLevel((PetscObject)ts->adapt,(PetscObject)ts,1);CHKERRQ(ierr); 4873 } 4874 *adapt = ts->adapt; 4875 PetscFunctionReturn(0); 4876 } 4877 4878 #undef __FUNCT__ 4879 #define __FUNCT__ "TSSetTolerances" 4880 /*@ 4881 TSSetTolerances - Set tolerances for local truncation error when using adaptive controller 4882 4883 Logically Collective 4884 4885 Input Arguments: 4886 + ts - time integration context 4887 . atol - scalar absolute tolerances, PETSC_DECIDE to leave current value 4888 . vatol - vector of absolute tolerances or NULL, used in preference to atol if present 4889 . rtol - scalar relative tolerances, PETSC_DECIDE to leave current value 4890 - vrtol - vector of relative tolerances or NULL, used in preference to atol if present 4891 4892 Options Database keys: 4893 + -ts_rtol <rtol> - relative tolerance for local truncation error 4894 - -ts_atol <atol> Absolute tolerance for local truncation error 4895 4896 Notes: 4897 With PETSc's implicit schemes for DAE problems, the calculation of the local truncation error 4898 (LTE) includes both the differential and the algebraic variables. If one wants the LTE to be 4899 computed only for the differential or the algebraic part then this can be done using the vector of 4900 tolerances vatol. For example, by setting the tolerance vector with the desired tolerance for the 4901 differential part and infinity for the algebraic part, the LTE calculation will include only the 4902 differential variables. 4903 4904 Level: beginner 4905 4906 .seealso: TS, TSAdapt, TSVecNormWRMS(), TSGetTolerances() 4907 @*/ 4908 PetscErrorCode TSSetTolerances(TS ts,PetscReal atol,Vec vatol,PetscReal rtol,Vec vrtol) 4909 { 4910 PetscErrorCode ierr; 4911 4912 PetscFunctionBegin; 4913 if (atol != PETSC_DECIDE && atol != PETSC_DEFAULT) ts->atol = atol; 4914 if (vatol) { 4915 ierr = PetscObjectReference((PetscObject)vatol);CHKERRQ(ierr); 4916 ierr = VecDestroy(&ts->vatol);CHKERRQ(ierr); 4917 4918 ts->vatol = vatol; 4919 } 4920 if (rtol != PETSC_DECIDE && rtol != PETSC_DEFAULT) ts->rtol = rtol; 4921 if (vrtol) { 4922 ierr = PetscObjectReference((PetscObject)vrtol);CHKERRQ(ierr); 4923 ierr = VecDestroy(&ts->vrtol);CHKERRQ(ierr); 4924 4925 ts->vrtol = vrtol; 4926 } 4927 PetscFunctionReturn(0); 4928 } 4929 4930 #undef __FUNCT__ 4931 #define __FUNCT__ "TSGetTolerances" 4932 /*@ 4933 TSGetTolerances - Get tolerances for local truncation error when using adaptive controller 4934 4935 Logically Collective 4936 4937 Input Arguments: 4938 . ts - time integration context 4939 4940 Output Arguments: 4941 + atol - scalar absolute tolerances, NULL to ignore 4942 . vatol - vector of absolute tolerances, NULL to ignore 4943 . rtol - scalar relative tolerances, NULL to ignore 4944 - vrtol - vector of relative tolerances, NULL to ignore 4945 4946 Level: beginner 4947 4948 .seealso: TS, TSAdapt, TSVecNormWRMS(), TSSetTolerances() 4949 @*/ 4950 PetscErrorCode TSGetTolerances(TS ts,PetscReal *atol,Vec *vatol,PetscReal *rtol,Vec *vrtol) 4951 { 4952 PetscFunctionBegin; 4953 if (atol) *atol = ts->atol; 4954 if (vatol) *vatol = ts->vatol; 4955 if (rtol) *rtol = ts->rtol; 4956 if (vrtol) *vrtol = ts->vrtol; 4957 PetscFunctionReturn(0); 4958 } 4959 4960 #undef __FUNCT__ 4961 #define __FUNCT__ "TSErrorWeightedNorm2" 4962 /*@ 4963 TSErrorWeightedNorm2 - compute a weighted 2-norm of the difference between two state vectors 4964 4965 Collective on TS 4966 4967 Input Arguments: 4968 + ts - time stepping context 4969 . U - state vector, usually ts->vec_sol 4970 - Y - state vector to be compared to U 4971 4972 Output Arguments: 4973 . norm - weighted norm, a value of 1.0 is considered small 4974 4975 Level: developer 4976 4977 .seealso: TSErrorWeightedNorm(), TSErrorWeightedNormInfinity() 4978 @*/ 4979 PetscErrorCode TSErrorWeightedNorm2(TS ts,Vec U,Vec Y,PetscReal *norm) 4980 { 4981 PetscErrorCode ierr; 4982 PetscInt i,n,N,rstart; 4983 const PetscScalar *u,*y; 4984 PetscReal sum,gsum; 4985 PetscReal tol; 4986 4987 PetscFunctionBegin; 4988 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4989 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 4990 PetscValidHeaderSpecific(Y,VEC_CLASSID,3); 4991 PetscValidType(U,2); 4992 PetscValidType(Y,3); 4993 PetscCheckSameComm(U,2,Y,3); 4994 PetscValidPointer(norm,4); 4995 if (U == Y) SETERRQ(PetscObjectComm((PetscObject)U),PETSC_ERR_ARG_IDN,"U and Y cannot be the same vector"); 4996 4997 ierr = VecGetSize(U,&N);CHKERRQ(ierr); 4998 ierr = VecGetLocalSize(U,&n);CHKERRQ(ierr); 4999 ierr = VecGetOwnershipRange(U,&rstart,NULL);CHKERRQ(ierr); 5000 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 5001 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 5002 sum = 0.; 5003 if (ts->vatol && ts->vrtol) { 5004 const PetscScalar *atol,*rtol; 5005 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5006 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5007 for (i=0; i<n; i++) { 5008 tol = PetscRealPart(atol[i]) + PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5009 sum += PetscSqr(PetscAbsScalar(y[i] - u[i]) / tol); 5010 } 5011 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5012 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5013 } else if (ts->vatol) { /* vector atol, scalar rtol */ 5014 const PetscScalar *atol; 5015 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5016 for (i=0; i<n; i++) { 5017 tol = PetscRealPart(atol[i]) + ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5018 sum += PetscSqr(PetscAbsScalar(y[i] - u[i]) / tol); 5019 } 5020 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5021 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 5022 const PetscScalar *rtol; 5023 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5024 for (i=0; i<n; i++) { 5025 tol = ts->atol + PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5026 sum += PetscSqr(PetscAbsScalar(y[i] - u[i]) / tol); 5027 } 5028 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5029 } else { /* scalar atol, scalar rtol */ 5030 for (i=0; i<n; i++) { 5031 tol = ts->atol + ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5032 sum += PetscSqr(PetscAbsScalar(y[i] - u[i]) / tol); 5033 } 5034 } 5035 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 5036 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 5037 5038 ierr = MPI_Allreduce(&sum,&gsum,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 5039 *norm = PetscSqrtReal(gsum / N); 5040 5041 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 5042 PetscFunctionReturn(0); 5043 } 5044 5045 #undef __FUNCT__ 5046 #define __FUNCT__ "TSErrorWeightedNormInfinity" 5047 /*@ 5048 TSErrorWeightedNormInfinity - compute a weighted infinity-norm of the difference between two state vectors 5049 5050 Collective on TS 5051 5052 Input Arguments: 5053 + ts - time stepping context 5054 . U - state vector, usually ts->vec_sol 5055 - Y - state vector to be compared to U 5056 5057 Output Arguments: 5058 . norm - weighted norm, a value of 1.0 is considered small 5059 5060 Level: developer 5061 5062 .seealso: TSErrorWeightedNorm(), TSErrorWeightedNorm2() 5063 @*/ 5064 PetscErrorCode TSErrorWeightedNormInfinity(TS ts,Vec U,Vec Y,PetscReal *norm) 5065 { 5066 PetscErrorCode ierr; 5067 PetscInt i,n,N,rstart,k; 5068 const PetscScalar *u,*y; 5069 PetscReal max,gmax; 5070 PetscReal tol; 5071 5072 PetscFunctionBegin; 5073 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5074 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 5075 PetscValidHeaderSpecific(Y,VEC_CLASSID,3); 5076 PetscValidType(U,2); 5077 PetscValidType(Y,3); 5078 PetscCheckSameComm(U,2,Y,3); 5079 PetscValidPointer(norm,4); 5080 if (U == Y) SETERRQ(PetscObjectComm((PetscObject)U),PETSC_ERR_ARG_IDN,"U and Y cannot be the same vector"); 5081 5082 ierr = VecGetSize(U,&N);CHKERRQ(ierr); 5083 ierr = VecGetLocalSize(U,&n);CHKERRQ(ierr); 5084 ierr = VecGetOwnershipRange(U,&rstart,NULL);CHKERRQ(ierr); 5085 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 5086 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 5087 if (ts->vatol && ts->vrtol) { 5088 const PetscScalar *atol,*rtol; 5089 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5090 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5091 k = 0; 5092 tol = PetscRealPart(atol[k]) + PetscRealPart(rtol[k]) * PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5093 max = PetscAbsScalar(y[k] - u[k]) / tol; 5094 for (i=1; i<n; i++) { 5095 tol = PetscRealPart(atol[i]) + PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5096 max = PetscMax(max,PetscAbsScalar(y[i] - u[i]) / tol); 5097 } 5098 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5099 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5100 } else if (ts->vatol) { /* vector atol, scalar rtol */ 5101 const PetscScalar *atol; 5102 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5103 k = 0; 5104 tol = PetscRealPart(atol[k]) + ts->rtol * PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5105 max = PetscAbsScalar(y[k] - u[k]) / tol; 5106 for (i=1; i<n; i++) { 5107 tol = PetscRealPart(atol[i]) + ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5108 max = PetscMax(max,PetscAbsScalar(y[i] - u[i]) / tol); 5109 } 5110 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5111 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 5112 const PetscScalar *rtol; 5113 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5114 k = 0; 5115 tol = ts->atol + PetscRealPart(rtol[k]) * PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5116 max = PetscAbsScalar(y[k] - u[k]) / tol; 5117 for (i=1; i<n; i++) { 5118 tol = ts->atol + PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5119 max = PetscMax(max,PetscAbsScalar(y[i] - u[i]) / tol); 5120 } 5121 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5122 } else { /* scalar atol, scalar rtol */ 5123 k = 0; 5124 tol = ts->atol + ts->rtol * PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5125 max = PetscAbsScalar(y[k] - u[k]) / tol; 5126 for (i=1; i<n; i++) { 5127 tol = ts->atol + ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5128 max = PetscMax(max,PetscAbsScalar(y[i] - u[i]) / tol); 5129 } 5130 } 5131 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 5132 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 5133 5134 ierr = MPI_Allreduce(&max,&gmax,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 5135 *norm = gmax; 5136 5137 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 5138 PetscFunctionReturn(0); 5139 } 5140 5141 #undef __FUNCT__ 5142 #define __FUNCT__ "TSErrorWeightedNorm" 5143 /*@ 5144 TSErrorWeightedNorm - compute a weighted norm of the difference between two state vectors 5145 5146 Collective on TS 5147 5148 Input Arguments: 5149 + ts - time stepping context 5150 . U - state vector, usually ts->vec_sol 5151 . Y - state vector to be compared to U 5152 - wnormtype - norm type, either NORM_2 or NORM_INFINITY 5153 5154 Output Arguments: 5155 . norm - weighted norm, a value of 1.0 is considered small 5156 5157 5158 Options Database Keys: 5159 . -ts_adapt_wnormtype <wnormtype> - 2, INFINITY 5160 5161 Level: developer 5162 5163 .seealso: TSErrorWeightedNormInfinity(), TSErrorWeightedNorm2() 5164 @*/ 5165 PetscErrorCode TSErrorWeightedNorm(TS ts,Vec U,Vec Y,NormType wnormtype,PetscReal *norm) 5166 { 5167 PetscErrorCode ierr; 5168 5169 PetscFunctionBegin; 5170 if (wnormtype == NORM_2) { 5171 ierr = TSErrorWeightedNorm2(ts,U,Y,norm);CHKERRQ(ierr); 5172 } else if(wnormtype == NORM_INFINITY) { 5173 ierr = TSErrorWeightedNormInfinity(ts,U,Y,norm);CHKERRQ(ierr); 5174 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for norm type %s",NormTypes[wnormtype]); 5175 PetscFunctionReturn(0); 5176 } 5177 5178 #undef __FUNCT__ 5179 #define __FUNCT__ "TSSetCFLTimeLocal" 5180 /*@ 5181 TSSetCFLTimeLocal - Set the local CFL constraint relative to forward Euler 5182 5183 Logically Collective on TS 5184 5185 Input Arguments: 5186 + ts - time stepping context 5187 - cfltime - maximum stable time step if using forward Euler (value can be different on each process) 5188 5189 Note: 5190 After calling this function, the global CFL time can be obtained by calling TSGetCFLTime() 5191 5192 Level: intermediate 5193 5194 .seealso: TSGetCFLTime(), TSADAPTCFL 5195 @*/ 5196 PetscErrorCode TSSetCFLTimeLocal(TS ts,PetscReal cfltime) 5197 { 5198 PetscFunctionBegin; 5199 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5200 ts->cfltime_local = cfltime; 5201 ts->cfltime = -1.; 5202 PetscFunctionReturn(0); 5203 } 5204 5205 #undef __FUNCT__ 5206 #define __FUNCT__ "TSGetCFLTime" 5207 /*@ 5208 TSGetCFLTime - Get the maximum stable time step according to CFL criteria applied to forward Euler 5209 5210 Collective on TS 5211 5212 Input Arguments: 5213 . ts - time stepping context 5214 5215 Output Arguments: 5216 . cfltime - maximum stable time step for forward Euler 5217 5218 Level: advanced 5219 5220 .seealso: TSSetCFLTimeLocal() 5221 @*/ 5222 PetscErrorCode TSGetCFLTime(TS ts,PetscReal *cfltime) 5223 { 5224 PetscErrorCode ierr; 5225 5226 PetscFunctionBegin; 5227 if (ts->cfltime < 0) { 5228 ierr = MPI_Allreduce(&ts->cfltime_local,&ts->cfltime,1,MPIU_REAL,MPIU_MIN,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 5229 } 5230 *cfltime = ts->cfltime; 5231 PetscFunctionReturn(0); 5232 } 5233 5234 #undef __FUNCT__ 5235 #define __FUNCT__ "TSVISetVariableBounds" 5236 /*@ 5237 TSVISetVariableBounds - Sets the lower and upper bounds for the solution vector. xl <= x <= xu 5238 5239 Input Parameters: 5240 . ts - the TS context. 5241 . xl - lower bound. 5242 . xu - upper bound. 5243 5244 Notes: 5245 If this routine is not called then the lower and upper bounds are set to 5246 PETSC_NINFINITY and PETSC_INFINITY respectively during SNESSetUp(). 5247 5248 Level: advanced 5249 5250 @*/ 5251 PetscErrorCode TSVISetVariableBounds(TS ts, Vec xl, Vec xu) 5252 { 5253 PetscErrorCode ierr; 5254 SNES snes; 5255 5256 PetscFunctionBegin; 5257 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 5258 ierr = SNESVISetVariableBounds(snes,xl,xu);CHKERRQ(ierr); 5259 PetscFunctionReturn(0); 5260 } 5261 5262 #if defined(PETSC_HAVE_MATLAB_ENGINE) 5263 #include <mex.h> 5264 5265 typedef struct {char *funcname; mxArray *ctx;} TSMatlabContext; 5266 5267 #undef __FUNCT__ 5268 #define __FUNCT__ "TSComputeFunction_Matlab" 5269 /* 5270 TSComputeFunction_Matlab - Calls the function that has been set with 5271 TSSetFunctionMatlab(). 5272 5273 Collective on TS 5274 5275 Input Parameters: 5276 + snes - the TS context 5277 - u - input vector 5278 5279 Output Parameter: 5280 . y - function vector, as set by TSSetFunction() 5281 5282 Notes: 5283 TSComputeFunction() is typically used within nonlinear solvers 5284 implementations, so most users would not generally call this routine 5285 themselves. 5286 5287 Level: developer 5288 5289 .keywords: TS, nonlinear, compute, function 5290 5291 .seealso: TSSetFunction(), TSGetFunction() 5292 */ 5293 PetscErrorCode TSComputeFunction_Matlab(TS snes,PetscReal time,Vec u,Vec udot,Vec y, void *ctx) 5294 { 5295 PetscErrorCode ierr; 5296 TSMatlabContext *sctx = (TSMatlabContext*)ctx; 5297 int nlhs = 1,nrhs = 7; 5298 mxArray *plhs[1],*prhs[7]; 5299 long long int lx = 0,lxdot = 0,ly = 0,ls = 0; 5300 5301 PetscFunctionBegin; 5302 PetscValidHeaderSpecific(snes,TS_CLASSID,1); 5303 PetscValidHeaderSpecific(u,VEC_CLASSID,3); 5304 PetscValidHeaderSpecific(udot,VEC_CLASSID,4); 5305 PetscValidHeaderSpecific(y,VEC_CLASSID,5); 5306 PetscCheckSameComm(snes,1,u,3); 5307 PetscCheckSameComm(snes,1,y,5); 5308 5309 ierr = PetscMemcpy(&ls,&snes,sizeof(snes));CHKERRQ(ierr); 5310 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 5311 ierr = PetscMemcpy(&lxdot,&udot,sizeof(udot));CHKERRQ(ierr); 5312 ierr = PetscMemcpy(&ly,&y,sizeof(u));CHKERRQ(ierr); 5313 5314 prhs[0] = mxCreateDoubleScalar((double)ls); 5315 prhs[1] = mxCreateDoubleScalar(time); 5316 prhs[2] = mxCreateDoubleScalar((double)lx); 5317 prhs[3] = mxCreateDoubleScalar((double)lxdot); 5318 prhs[4] = mxCreateDoubleScalar((double)ly); 5319 prhs[5] = mxCreateString(sctx->funcname); 5320 prhs[6] = sctx->ctx; 5321 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSComputeFunctionInternal");CHKERRQ(ierr); 5322 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 5323 mxDestroyArray(prhs[0]); 5324 mxDestroyArray(prhs[1]); 5325 mxDestroyArray(prhs[2]); 5326 mxDestroyArray(prhs[3]); 5327 mxDestroyArray(prhs[4]); 5328 mxDestroyArray(prhs[5]); 5329 mxDestroyArray(plhs[0]); 5330 PetscFunctionReturn(0); 5331 } 5332 5333 5334 #undef __FUNCT__ 5335 #define __FUNCT__ "TSSetFunctionMatlab" 5336 /* 5337 TSSetFunctionMatlab - Sets the function evaluation routine and function 5338 vector for use by the TS routines in solving ODEs 5339 equations from MATLAB. Here the function is a string containing the name of a MATLAB function 5340 5341 Logically Collective on TS 5342 5343 Input Parameters: 5344 + ts - the TS context 5345 - func - function evaluation routine 5346 5347 Calling sequence of func: 5348 $ func (TS ts,PetscReal time,Vec u,Vec udot,Vec f,void *ctx); 5349 5350 Level: beginner 5351 5352 .keywords: TS, nonlinear, set, function 5353 5354 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 5355 */ 5356 PetscErrorCode TSSetFunctionMatlab(TS ts,const char *func,mxArray *ctx) 5357 { 5358 PetscErrorCode ierr; 5359 TSMatlabContext *sctx; 5360 5361 PetscFunctionBegin; 5362 /* currently sctx is memory bleed */ 5363 ierr = PetscMalloc(sizeof(TSMatlabContext),&sctx);CHKERRQ(ierr); 5364 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 5365 /* 5366 This should work, but it doesn't 5367 sctx->ctx = ctx; 5368 mexMakeArrayPersistent(sctx->ctx); 5369 */ 5370 sctx->ctx = mxDuplicateArray(ctx); 5371 5372 ierr = TSSetIFunction(ts,NULL,TSComputeFunction_Matlab,sctx);CHKERRQ(ierr); 5373 PetscFunctionReturn(0); 5374 } 5375 5376 #undef __FUNCT__ 5377 #define __FUNCT__ "TSComputeJacobian_Matlab" 5378 /* 5379 TSComputeJacobian_Matlab - Calls the function that has been set with 5380 TSSetJacobianMatlab(). 5381 5382 Collective on TS 5383 5384 Input Parameters: 5385 + ts - the TS context 5386 . u - input vector 5387 . A, B - the matrices 5388 - ctx - user context 5389 5390 Level: developer 5391 5392 .keywords: TS, nonlinear, compute, function 5393 5394 .seealso: TSSetFunction(), TSGetFunction() 5395 @*/ 5396 PetscErrorCode TSComputeJacobian_Matlab(TS ts,PetscReal time,Vec u,Vec udot,PetscReal shift,Mat A,Mat B,void *ctx) 5397 { 5398 PetscErrorCode ierr; 5399 TSMatlabContext *sctx = (TSMatlabContext*)ctx; 5400 int nlhs = 2,nrhs = 9; 5401 mxArray *plhs[2],*prhs[9]; 5402 long long int lx = 0,lxdot = 0,lA = 0,ls = 0, lB = 0; 5403 5404 PetscFunctionBegin; 5405 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5406 PetscValidHeaderSpecific(u,VEC_CLASSID,3); 5407 5408 /* call Matlab function in ctx with arguments u and y */ 5409 5410 ierr = PetscMemcpy(&ls,&ts,sizeof(ts));CHKERRQ(ierr); 5411 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 5412 ierr = PetscMemcpy(&lxdot,&udot,sizeof(u));CHKERRQ(ierr); 5413 ierr = PetscMemcpy(&lA,A,sizeof(u));CHKERRQ(ierr); 5414 ierr = PetscMemcpy(&lB,B,sizeof(u));CHKERRQ(ierr); 5415 5416 prhs[0] = mxCreateDoubleScalar((double)ls); 5417 prhs[1] = mxCreateDoubleScalar((double)time); 5418 prhs[2] = mxCreateDoubleScalar((double)lx); 5419 prhs[3] = mxCreateDoubleScalar((double)lxdot); 5420 prhs[4] = mxCreateDoubleScalar((double)shift); 5421 prhs[5] = mxCreateDoubleScalar((double)lA); 5422 prhs[6] = mxCreateDoubleScalar((double)lB); 5423 prhs[7] = mxCreateString(sctx->funcname); 5424 prhs[8] = sctx->ctx; 5425 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSComputeJacobianInternal");CHKERRQ(ierr); 5426 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 5427 mxDestroyArray(prhs[0]); 5428 mxDestroyArray(prhs[1]); 5429 mxDestroyArray(prhs[2]); 5430 mxDestroyArray(prhs[3]); 5431 mxDestroyArray(prhs[4]); 5432 mxDestroyArray(prhs[5]); 5433 mxDestroyArray(prhs[6]); 5434 mxDestroyArray(prhs[7]); 5435 mxDestroyArray(plhs[0]); 5436 mxDestroyArray(plhs[1]); 5437 PetscFunctionReturn(0); 5438 } 5439 5440 5441 #undef __FUNCT__ 5442 #define __FUNCT__ "TSSetJacobianMatlab" 5443 /* 5444 TSSetJacobianMatlab - Sets the Jacobian function evaluation routine and two empty Jacobian matrices 5445 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 5446 5447 Logically Collective on TS 5448 5449 Input Parameters: 5450 + ts - the TS context 5451 . A,B - Jacobian matrices 5452 . func - function evaluation routine 5453 - ctx - user context 5454 5455 Calling sequence of func: 5456 $ flag = func (TS ts,PetscReal time,Vec u,Vec udot,Mat A,Mat B,void *ctx); 5457 5458 5459 Level: developer 5460 5461 .keywords: TS, nonlinear, set, function 5462 5463 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 5464 */ 5465 PetscErrorCode TSSetJacobianMatlab(TS ts,Mat A,Mat B,const char *func,mxArray *ctx) 5466 { 5467 PetscErrorCode ierr; 5468 TSMatlabContext *sctx; 5469 5470 PetscFunctionBegin; 5471 /* currently sctx is memory bleed */ 5472 ierr = PetscMalloc(sizeof(TSMatlabContext),&sctx);CHKERRQ(ierr); 5473 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 5474 /* 5475 This should work, but it doesn't 5476 sctx->ctx = ctx; 5477 mexMakeArrayPersistent(sctx->ctx); 5478 */ 5479 sctx->ctx = mxDuplicateArray(ctx); 5480 5481 ierr = TSSetIJacobian(ts,A,B,TSComputeJacobian_Matlab,sctx);CHKERRQ(ierr); 5482 PetscFunctionReturn(0); 5483 } 5484 5485 #undef __FUNCT__ 5486 #define __FUNCT__ "TSMonitor_Matlab" 5487 /* 5488 TSMonitor_Matlab - Calls the function that has been set with TSMonitorSetMatlab(). 5489 5490 Collective on TS 5491 5492 .seealso: TSSetFunction(), TSGetFunction() 5493 @*/ 5494 PetscErrorCode TSMonitor_Matlab(TS ts,PetscInt it, PetscReal time,Vec u, void *ctx) 5495 { 5496 PetscErrorCode ierr; 5497 TSMatlabContext *sctx = (TSMatlabContext*)ctx; 5498 int nlhs = 1,nrhs = 6; 5499 mxArray *plhs[1],*prhs[6]; 5500 long long int lx = 0,ls = 0; 5501 5502 PetscFunctionBegin; 5503 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5504 PetscValidHeaderSpecific(u,VEC_CLASSID,4); 5505 5506 ierr = PetscMemcpy(&ls,&ts,sizeof(ts));CHKERRQ(ierr); 5507 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 5508 5509 prhs[0] = mxCreateDoubleScalar((double)ls); 5510 prhs[1] = mxCreateDoubleScalar((double)it); 5511 prhs[2] = mxCreateDoubleScalar((double)time); 5512 prhs[3] = mxCreateDoubleScalar((double)lx); 5513 prhs[4] = mxCreateString(sctx->funcname); 5514 prhs[5] = sctx->ctx; 5515 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSMonitorInternal");CHKERRQ(ierr); 5516 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 5517 mxDestroyArray(prhs[0]); 5518 mxDestroyArray(prhs[1]); 5519 mxDestroyArray(prhs[2]); 5520 mxDestroyArray(prhs[3]); 5521 mxDestroyArray(prhs[4]); 5522 mxDestroyArray(plhs[0]); 5523 PetscFunctionReturn(0); 5524 } 5525 5526 5527 #undef __FUNCT__ 5528 #define __FUNCT__ "TSMonitorSetMatlab" 5529 /* 5530 TSMonitorSetMatlab - Sets the monitor function from Matlab 5531 5532 Level: developer 5533 5534 .keywords: TS, nonlinear, set, function 5535 5536 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 5537 */ 5538 PetscErrorCode TSMonitorSetMatlab(TS ts,const char *func,mxArray *ctx) 5539 { 5540 PetscErrorCode ierr; 5541 TSMatlabContext *sctx; 5542 5543 PetscFunctionBegin; 5544 /* currently sctx is memory bleed */ 5545 ierr = PetscMalloc(sizeof(TSMatlabContext),&sctx);CHKERRQ(ierr); 5546 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 5547 /* 5548 This should work, but it doesn't 5549 sctx->ctx = ctx; 5550 mexMakeArrayPersistent(sctx->ctx); 5551 */ 5552 sctx->ctx = mxDuplicateArray(ctx); 5553 5554 ierr = TSMonitorSet(ts,TSMonitor_Matlab,sctx,NULL);CHKERRQ(ierr); 5555 PetscFunctionReturn(0); 5556 } 5557 #endif 5558 5559 #undef __FUNCT__ 5560 #define __FUNCT__ "TSMonitorLGSolution" 5561 /*@C 5562 TSMonitorLGSolution - Monitors progress of the TS solvers by plotting each component of the solution vector 5563 in a time based line graph 5564 5565 Collective on TS 5566 5567 Input Parameters: 5568 + ts - the TS context 5569 . step - current time-step 5570 . ptime - current time 5571 - lg - a line graph object 5572 5573 Options Database: 5574 . -ts_monitor_lg_solution_variables 5575 5576 Level: intermediate 5577 5578 Notes: each process in a parallel run displays its component solutions in a separate window 5579 5580 .keywords: TS, vector, monitor, view 5581 5582 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 5583 @*/ 5584 PetscErrorCode TSMonitorLGSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 5585 { 5586 PetscErrorCode ierr; 5587 TSMonitorLGCtx ctx = (TSMonitorLGCtx)dummy; 5588 const PetscScalar *yy; 5589 PetscInt dim; 5590 Vec v; 5591 5592 PetscFunctionBegin; 5593 if (!step) { 5594 PetscDrawAxis axis; 5595 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 5596 ierr = PetscDrawAxisSetLabels(axis,"Solution as function of time","Time","Solution");CHKERRQ(ierr); 5597 if (ctx->names && !ctx->displaynames) { 5598 char **displaynames; 5599 PetscBool flg; 5600 5601 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 5602 ierr = PetscMalloc((dim+1)*sizeof(char*),&displaynames);CHKERRQ(ierr); 5603 ierr = PetscMemzero(displaynames,(dim+1)*sizeof(char*));CHKERRQ(ierr); 5604 ierr = PetscOptionsGetStringArray(((PetscObject)ts)->prefix,"-ts_monitor_lg_solution_variables",displaynames,&dim,&flg);CHKERRQ(ierr); 5605 if (flg) { 5606 ierr = TSMonitorLGCtxSetDisplayVariables(ctx,(const char *const *)displaynames);CHKERRQ(ierr); 5607 } 5608 ierr = PetscStrArrayDestroy(&displaynames);CHKERRQ(ierr); 5609 } 5610 if (ctx->displaynames) { 5611 ierr = PetscDrawLGSetDimension(ctx->lg,ctx->ndisplayvariables);CHKERRQ(ierr); 5612 ierr = PetscDrawLGSetLegend(ctx->lg,(const char *const *)ctx->displaynames);CHKERRQ(ierr); 5613 } else if (ctx->names) { 5614 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 5615 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 5616 ierr = PetscDrawLGSetLegend(ctx->lg,(const char *const *)ctx->names);CHKERRQ(ierr); 5617 } 5618 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 5619 } 5620 if (ctx->transform) { 5621 ierr = (*ctx->transform)(ctx->transformctx,u,&v);CHKERRQ(ierr); 5622 } else { 5623 v = u; 5624 } 5625 ierr = VecGetArrayRead(v,&yy);CHKERRQ(ierr); 5626 #if defined(PETSC_USE_COMPLEX) 5627 { 5628 PetscReal *yreal; 5629 PetscInt i,n; 5630 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 5631 ierr = PetscMalloc1(n,&yreal);CHKERRQ(ierr); 5632 for (i=0; i<n; i++) yreal[i] = PetscRealPart(yy[i]); 5633 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yreal);CHKERRQ(ierr); 5634 ierr = PetscFree(yreal);CHKERRQ(ierr); 5635 } 5636 #else 5637 if (ctx->displaynames) { 5638 PetscInt i; 5639 for (i=0; i<ctx->ndisplayvariables; i++) { 5640 ctx->displayvalues[i] = yy[ctx->displayvariables[i]]; 5641 } 5642 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,ctx->displayvalues);CHKERRQ(ierr); 5643 } else { 5644 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yy);CHKERRQ(ierr); 5645 } 5646 #endif 5647 ierr = VecRestoreArrayRead(v,&yy);CHKERRQ(ierr); 5648 if (ctx->transform) { 5649 ierr = VecDestroy(&v);CHKERRQ(ierr); 5650 } 5651 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 5652 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 5653 } 5654 PetscFunctionReturn(0); 5655 } 5656 5657 5658 #undef __FUNCT__ 5659 #define __FUNCT__ "TSMonitorLGSetVariableNames" 5660 /*@C 5661 TSMonitorLGSetVariableNames - Sets the name of each component in the solution vector so that it may be displayed in the plot 5662 5663 Collective on TS 5664 5665 Input Parameters: 5666 + ts - the TS context 5667 - names - the names of the components, final string must be NULL 5668 5669 Level: intermediate 5670 5671 .keywords: TS, vector, monitor, view 5672 5673 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables(), TSMonitorLGCtxSetVariableNames() 5674 @*/ 5675 PetscErrorCode TSMonitorLGSetVariableNames(TS ts,const char * const *names) 5676 { 5677 PetscErrorCode ierr; 5678 PetscInt i; 5679 5680 PetscFunctionBegin; 5681 for (i=0; i<ts->numbermonitors; i++) { 5682 if (ts->monitor[i] == TSMonitorLGSolution) { 5683 ierr = TSMonitorLGCtxSetVariableNames((TSMonitorLGCtx)ts->monitorcontext[i],names);CHKERRQ(ierr); 5684 break; 5685 } 5686 } 5687 PetscFunctionReturn(0); 5688 } 5689 5690 #undef __FUNCT__ 5691 #define __FUNCT__ "TSMonitorLGCtxSetVariableNames" 5692 /*@C 5693 TSMonitorLGCtxSetVariableNames - Sets the name of each component in the solution vector so that it may be displayed in the plot 5694 5695 Collective on TS 5696 5697 Input Parameters: 5698 + ts - the TS context 5699 - names - the names of the components, final string must be NULL 5700 5701 Level: intermediate 5702 5703 .keywords: TS, vector, monitor, view 5704 5705 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables(), TSMonitorLGSetVariableNames() 5706 @*/ 5707 PetscErrorCode TSMonitorLGCtxSetVariableNames(TSMonitorLGCtx ctx,const char * const *names) 5708 { 5709 PetscErrorCode ierr; 5710 5711 PetscFunctionBegin; 5712 ierr = PetscStrArrayDestroy(&ctx->names);CHKERRQ(ierr); 5713 ierr = PetscStrArrayallocpy(names,&ctx->names);CHKERRQ(ierr); 5714 PetscFunctionReturn(0); 5715 } 5716 5717 #undef __FUNCT__ 5718 #define __FUNCT__ "TSMonitorLGGetVariableNames" 5719 /*@C 5720 TSMonitorLGGetVariableNames - Gets the name of each component in the solution vector so that it may be displayed in the plot 5721 5722 Collective on TS 5723 5724 Input Parameter: 5725 . ts - the TS context 5726 5727 Output Parameter: 5728 . names - the names of the components, final string must be NULL 5729 5730 Level: intermediate 5731 5732 .keywords: TS, vector, monitor, view 5733 5734 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables() 5735 @*/ 5736 PetscErrorCode TSMonitorLGGetVariableNames(TS ts,const char *const **names) 5737 { 5738 PetscInt i; 5739 5740 PetscFunctionBegin; 5741 *names = NULL; 5742 for (i=0; i<ts->numbermonitors; i++) { 5743 if (ts->monitor[i] == TSMonitorLGSolution) { 5744 TSMonitorLGCtx ctx = (TSMonitorLGCtx) ts->monitorcontext[i]; 5745 *names = (const char *const *)ctx->names; 5746 break; 5747 } 5748 } 5749 PetscFunctionReturn(0); 5750 } 5751 5752 #undef __FUNCT__ 5753 #define __FUNCT__ "TSMonitorLGCtxSetDisplayVariables" 5754 /*@C 5755 TSMonitorLGCtxSetDisplayVariables - Sets the variables that are to be display in the monitor 5756 5757 Collective on TS 5758 5759 Input Parameters: 5760 + ctx - the TSMonitorLG context 5761 . displaynames - the names of the components, final string must be NULL 5762 5763 Level: intermediate 5764 5765 .keywords: TS, vector, monitor, view 5766 5767 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames() 5768 @*/ 5769 PetscErrorCode TSMonitorLGCtxSetDisplayVariables(TSMonitorLGCtx ctx,const char * const *displaynames) 5770 { 5771 PetscInt j = 0,k; 5772 PetscErrorCode ierr; 5773 5774 PetscFunctionBegin; 5775 if (!ctx->names) PetscFunctionReturn(0); 5776 ierr = PetscStrArrayDestroy(&ctx->displaynames);CHKERRQ(ierr); 5777 ierr = PetscStrArrayallocpy(displaynames,&ctx->displaynames);CHKERRQ(ierr); 5778 while (displaynames[j]) j++; 5779 ctx->ndisplayvariables = j; 5780 ierr = PetscMalloc1(ctx->ndisplayvariables,&ctx->displayvariables);CHKERRQ(ierr); 5781 ierr = PetscMalloc1(ctx->ndisplayvariables,&ctx->displayvalues);CHKERRQ(ierr); 5782 j = 0; 5783 while (displaynames[j]) { 5784 k = 0; 5785 while (ctx->names[k]) { 5786 PetscBool flg; 5787 ierr = PetscStrcmp(displaynames[j],ctx->names[k],&flg);CHKERRQ(ierr); 5788 if (flg) { 5789 ctx->displayvariables[j] = k; 5790 break; 5791 } 5792 k++; 5793 } 5794 j++; 5795 } 5796 PetscFunctionReturn(0); 5797 } 5798 5799 5800 #undef __FUNCT__ 5801 #define __FUNCT__ "TSMonitorLGSetDisplayVariables" 5802 /*@C 5803 TSMonitorLGSetDisplayVariables - Sets the variables that are to be display in the monitor 5804 5805 Collective on TS 5806 5807 Input Parameters: 5808 + ts - the TS context 5809 . displaynames - the names of the components, final string must be NULL 5810 5811 Level: intermediate 5812 5813 .keywords: TS, vector, monitor, view 5814 5815 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames() 5816 @*/ 5817 PetscErrorCode TSMonitorLGSetDisplayVariables(TS ts,const char * const *displaynames) 5818 { 5819 PetscInt i; 5820 PetscErrorCode ierr; 5821 5822 PetscFunctionBegin; 5823 for (i=0; i<ts->numbermonitors; i++) { 5824 if (ts->monitor[i] == TSMonitorLGSolution) { 5825 ierr = TSMonitorLGCtxSetDisplayVariables((TSMonitorLGCtx)ts->monitorcontext[i],displaynames);CHKERRQ(ierr); 5826 break; 5827 } 5828 } 5829 PetscFunctionReturn(0); 5830 } 5831 5832 #undef __FUNCT__ 5833 #define __FUNCT__ "TSMonitorLGSetTransform" 5834 /*@C 5835 TSMonitorLGSetTransform - Solution vector will be transformed by provided function before being displayed 5836 5837 Collective on TS 5838 5839 Input Parameters: 5840 + ts - the TS context 5841 . transform - the transform function 5842 . destroy - function to destroy the optional context 5843 - ctx - optional context used by transform function 5844 5845 Level: intermediate 5846 5847 .keywords: TS, vector, monitor, view 5848 5849 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames(), TSMonitorLGCtxSetTransform() 5850 @*/ 5851 PetscErrorCode TSMonitorLGSetTransform(TS ts,PetscErrorCode (*transform)(void*,Vec,Vec*),PetscErrorCode (*destroy)(void*),void *tctx) 5852 { 5853 PetscInt i; 5854 PetscErrorCode ierr; 5855 5856 PetscFunctionBegin; 5857 for (i=0; i<ts->numbermonitors; i++) { 5858 if (ts->monitor[i] == TSMonitorLGSolution) { 5859 ierr = TSMonitorLGCtxSetTransform((TSMonitorLGCtx)ts->monitorcontext[i],transform,destroy,tctx);CHKERRQ(ierr); 5860 } 5861 } 5862 PetscFunctionReturn(0); 5863 } 5864 5865 #undef __FUNCT__ 5866 #define __FUNCT__ "TSMonitorLGCtxSetTransform" 5867 /*@C 5868 TSMonitorLGCtxSetTransform - Solution vector will be transformed by provided function before being displayed 5869 5870 Collective on TSLGCtx 5871 5872 Input Parameters: 5873 + ts - the TS context 5874 . transform - the transform function 5875 . destroy - function to destroy the optional context 5876 - ctx - optional context used by transform function 5877 5878 Level: intermediate 5879 5880 .keywords: TS, vector, monitor, view 5881 5882 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames(), TSMonitorLGSetTransform() 5883 @*/ 5884 PetscErrorCode TSMonitorLGCtxSetTransform(TSMonitorLGCtx ctx,PetscErrorCode (*transform)(void*,Vec,Vec*),PetscErrorCode (*destroy)(void*),void *tctx) 5885 { 5886 PetscFunctionBegin; 5887 ctx->transform = transform; 5888 ctx->transformdestroy = destroy; 5889 ctx->transformctx = tctx; 5890 PetscFunctionReturn(0); 5891 } 5892 5893 #undef __FUNCT__ 5894 #define __FUNCT__ "TSMonitorLGError" 5895 /*@C 5896 TSMonitorLGError - Monitors progress of the TS solvers by plotting each component of the solution vector 5897 in a time based line graph 5898 5899 Collective on TS 5900 5901 Input Parameters: 5902 + ts - the TS context 5903 . step - current time-step 5904 . ptime - current time 5905 - lg - a line graph object 5906 5907 Level: intermediate 5908 5909 Notes: 5910 Only for sequential solves. 5911 5912 The user must provide the solution using TSSetSolutionFunction() to use this monitor. 5913 5914 Options Database Keys: 5915 . -ts_monitor_lg_error - create a graphical monitor of error history 5916 5917 .keywords: TS, vector, monitor, view 5918 5919 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSSetSolutionFunction() 5920 @*/ 5921 PetscErrorCode TSMonitorLGError(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 5922 { 5923 PetscErrorCode ierr; 5924 TSMonitorLGCtx ctx = (TSMonitorLGCtx)dummy; 5925 const PetscScalar *yy; 5926 Vec y; 5927 PetscInt dim; 5928 5929 PetscFunctionBegin; 5930 if (!step) { 5931 PetscDrawAxis axis; 5932 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 5933 ierr = PetscDrawAxisSetLabels(axis,"Error in solution as function of time","Time","Solution");CHKERRQ(ierr); 5934 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 5935 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 5936 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 5937 } 5938 ierr = VecDuplicate(u,&y);CHKERRQ(ierr); 5939 ierr = TSComputeSolutionFunction(ts,ptime,y);CHKERRQ(ierr); 5940 ierr = VecAXPY(y,-1.0,u);CHKERRQ(ierr); 5941 ierr = VecGetArrayRead(y,&yy);CHKERRQ(ierr); 5942 #if defined(PETSC_USE_COMPLEX) 5943 { 5944 PetscReal *yreal; 5945 PetscInt i,n; 5946 ierr = VecGetLocalSize(y,&n);CHKERRQ(ierr); 5947 ierr = PetscMalloc1(n,&yreal);CHKERRQ(ierr); 5948 for (i=0; i<n; i++) yreal[i] = PetscRealPart(yy[i]); 5949 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yreal);CHKERRQ(ierr); 5950 ierr = PetscFree(yreal);CHKERRQ(ierr); 5951 } 5952 #else 5953 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yy);CHKERRQ(ierr); 5954 #endif 5955 ierr = VecRestoreArrayRead(y,&yy);CHKERRQ(ierr); 5956 ierr = VecDestroy(&y);CHKERRQ(ierr); 5957 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 5958 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 5959 } 5960 PetscFunctionReturn(0); 5961 } 5962 5963 #undef __FUNCT__ 5964 #define __FUNCT__ "TSMonitorLGSNESIterations" 5965 PetscErrorCode TSMonitorLGSNESIterations(TS ts,PetscInt n,PetscReal ptime,Vec v,void *monctx) 5966 { 5967 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 5968 PetscReal x = ptime,y; 5969 PetscErrorCode ierr; 5970 PetscInt its; 5971 5972 PetscFunctionBegin; 5973 if (!n) { 5974 PetscDrawAxis axis; 5975 5976 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 5977 ierr = PetscDrawAxisSetLabels(axis,"Nonlinear iterations as function of time","Time","SNES Iterations");CHKERRQ(ierr); 5978 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 5979 5980 ctx->snes_its = 0; 5981 } 5982 ierr = TSGetSNESIterations(ts,&its);CHKERRQ(ierr); 5983 y = its - ctx->snes_its; 5984 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 5985 if (((ctx->howoften > 0) && (!(n % ctx->howoften)) && (n > -1)) || ((ctx->howoften == -1) && (n == -1))) { 5986 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 5987 } 5988 ctx->snes_its = its; 5989 PetscFunctionReturn(0); 5990 } 5991 5992 #undef __FUNCT__ 5993 #define __FUNCT__ "TSMonitorLGKSPIterations" 5994 PetscErrorCode TSMonitorLGKSPIterations(TS ts,PetscInt n,PetscReal ptime,Vec v,void *monctx) 5995 { 5996 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 5997 PetscReal x = ptime,y; 5998 PetscErrorCode ierr; 5999 PetscInt its; 6000 6001 PetscFunctionBegin; 6002 if (!n) { 6003 PetscDrawAxis axis; 6004 6005 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 6006 ierr = PetscDrawAxisSetLabels(axis,"Linear iterations as function of time","Time","KSP Iterations");CHKERRQ(ierr); 6007 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 6008 6009 ctx->ksp_its = 0; 6010 } 6011 ierr = TSGetKSPIterations(ts,&its);CHKERRQ(ierr); 6012 y = its - ctx->ksp_its; 6013 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 6014 if (((ctx->howoften > 0) && (!(n % ctx->howoften)) && (n > -1)) || ((ctx->howoften == -1) && (n == -1))) { 6015 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 6016 } 6017 ctx->ksp_its = its; 6018 PetscFunctionReturn(0); 6019 } 6020 6021 #undef __FUNCT__ 6022 #define __FUNCT__ "TSComputeLinearStability" 6023 /*@ 6024 TSComputeLinearStability - computes the linear stability function at a point 6025 6026 Collective on TS and Vec 6027 6028 Input Parameters: 6029 + ts - the TS context 6030 - xr,xi - real and imaginary part of input arguments 6031 6032 Output Parameters: 6033 . yr,yi - real and imaginary part of function value 6034 6035 Level: developer 6036 6037 .keywords: TS, compute 6038 6039 .seealso: TSSetRHSFunction(), TSComputeIFunction() 6040 @*/ 6041 PetscErrorCode TSComputeLinearStability(TS ts,PetscReal xr,PetscReal xi,PetscReal *yr,PetscReal *yi) 6042 { 6043 PetscErrorCode ierr; 6044 6045 PetscFunctionBegin; 6046 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6047 if (!ts->ops->linearstability) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Linearized stability function not provided for this method"); 6048 ierr = (*ts->ops->linearstability)(ts,xr,xi,yr,yi);CHKERRQ(ierr); 6049 PetscFunctionReturn(0); 6050 } 6051 6052 /* ------------------------------------------------------------------------*/ 6053 #undef __FUNCT__ 6054 #define __FUNCT__ "TSMonitorEnvelopeCtxCreate" 6055 /*@C 6056 TSMonitorEnvelopeCtxCreate - Creates a context for use with TSMonitorEnvelope() 6057 6058 Collective on TS 6059 6060 Input Parameters: 6061 . ts - the ODE solver object 6062 6063 Output Parameter: 6064 . ctx - the context 6065 6066 Level: intermediate 6067 6068 .keywords: TS, monitor, line graph, residual, seealso 6069 6070 .seealso: TSMonitorLGTimeStep(), TSMonitorSet(), TSMonitorLGSolution(), TSMonitorLGError() 6071 6072 @*/ 6073 PetscErrorCode TSMonitorEnvelopeCtxCreate(TS ts,TSMonitorEnvelopeCtx *ctx) 6074 { 6075 PetscErrorCode ierr; 6076 6077 PetscFunctionBegin; 6078 ierr = PetscNew(ctx);CHKERRQ(ierr); 6079 PetscFunctionReturn(0); 6080 } 6081 6082 #undef __FUNCT__ 6083 #define __FUNCT__ "TSMonitorEnvelope" 6084 /*@C 6085 TSMonitorEnvelope - Monitors the maximum and minimum value of each component of the solution 6086 6087 Collective on TS 6088 6089 Input Parameters: 6090 + ts - the TS context 6091 . step - current time-step 6092 . ptime - current time 6093 - ctx - the envelope context 6094 6095 Options Database: 6096 . -ts_monitor_envelope 6097 6098 Level: intermediate 6099 6100 Notes: after a solve you can use TSMonitorEnvelopeGetBounds() to access the envelope 6101 6102 .keywords: TS, vector, monitor, view 6103 6104 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorEnvelopeGetBounds() 6105 @*/ 6106 PetscErrorCode TSMonitorEnvelope(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 6107 { 6108 PetscErrorCode ierr; 6109 TSMonitorEnvelopeCtx ctx = (TSMonitorEnvelopeCtx)dummy; 6110 6111 PetscFunctionBegin; 6112 if (!ctx->max) { 6113 ierr = VecDuplicate(u,&ctx->max);CHKERRQ(ierr); 6114 ierr = VecDuplicate(u,&ctx->min);CHKERRQ(ierr); 6115 ierr = VecCopy(u,ctx->max);CHKERRQ(ierr); 6116 ierr = VecCopy(u,ctx->min);CHKERRQ(ierr); 6117 } else { 6118 ierr = VecPointwiseMax(ctx->max,u,ctx->max);CHKERRQ(ierr); 6119 ierr = VecPointwiseMin(ctx->min,u,ctx->min);CHKERRQ(ierr); 6120 } 6121 PetscFunctionReturn(0); 6122 } 6123 6124 6125 #undef __FUNCT__ 6126 #define __FUNCT__ "TSMonitorEnvelopeGetBounds" 6127 /*@C 6128 TSMonitorEnvelopeGetBounds - Gets the bounds for the components of the solution 6129 6130 Collective on TS 6131 6132 Input Parameter: 6133 . ts - the TS context 6134 6135 Output Parameter: 6136 + max - the maximum values 6137 - min - the minimum values 6138 6139 Level: intermediate 6140 6141 .keywords: TS, vector, monitor, view 6142 6143 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables() 6144 @*/ 6145 PetscErrorCode TSMonitorEnvelopeGetBounds(TS ts,Vec *max,Vec *min) 6146 { 6147 PetscInt i; 6148 6149 PetscFunctionBegin; 6150 if (max) *max = NULL; 6151 if (min) *min = NULL; 6152 for (i=0; i<ts->numbermonitors; i++) { 6153 if (ts->monitor[i] == TSMonitorEnvelope) { 6154 TSMonitorEnvelopeCtx ctx = (TSMonitorEnvelopeCtx) ts->monitorcontext[i]; 6155 if (max) *max = ctx->max; 6156 if (min) *min = ctx->min; 6157 break; 6158 } 6159 } 6160 PetscFunctionReturn(0); 6161 } 6162 6163 #undef __FUNCT__ 6164 #define __FUNCT__ "TSMonitorEnvelopeCtxDestroy" 6165 /*@C 6166 TSMonitorEnvelopeCtxDestroy - Destroys a context that was created with TSMonitorEnvelopeCtxCreate(). 6167 6168 Collective on TSMonitorEnvelopeCtx 6169 6170 Input Parameter: 6171 . ctx - the monitor context 6172 6173 Level: intermediate 6174 6175 .keywords: TS, monitor, line graph, destroy 6176 6177 .seealso: TSMonitorLGCtxCreate(), TSMonitorSet(), TSMonitorLGTimeStep(); 6178 @*/ 6179 PetscErrorCode TSMonitorEnvelopeCtxDestroy(TSMonitorEnvelopeCtx *ctx) 6180 { 6181 PetscErrorCode ierr; 6182 6183 PetscFunctionBegin; 6184 ierr = VecDestroy(&(*ctx)->min);CHKERRQ(ierr); 6185 ierr = VecDestroy(&(*ctx)->max);CHKERRQ(ierr); 6186 ierr = PetscFree(*ctx);CHKERRQ(ierr); 6187 PetscFunctionReturn(0); 6188 } 6189 6190 #undef __FUNCT__ 6191 #define __FUNCT__ "TSRollBack" 6192 /*@ 6193 TSRollBack - Rolls back one time step 6194 6195 Collective on TS 6196 6197 Input Parameter: 6198 . ts - the TS context obtained from TSCreate() 6199 6200 Level: advanced 6201 6202 .keywords: TS, timestep, rollback 6203 6204 .seealso: TSCreate(), TSSetUp(), TSDestroy(), TSSolve(), TSSetPreStep(), TSSetPreStage(), TSInterpolate() 6205 @*/ 6206 PetscErrorCode TSRollBack(TS ts) 6207 { 6208 PetscErrorCode ierr; 6209 6210 PetscFunctionBegin; 6211 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 6212 6213 if (!ts->ops->rollback) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSRollBack not implemented for type '%s'",((PetscObject)ts)->type_name); 6214 ierr = (*ts->ops->rollback)(ts);CHKERRQ(ierr); 6215 ts->time_step = ts->ptime - ts->ptime_prev; 6216 ts->ptime = ts->ptime_prev; 6217 ts->steprollback = PETSC_TRUE; /* Flag to indicate that the step is rollbacked */ 6218 PetscFunctionReturn(0); 6219 } 6220 6221 #undef __FUNCT__ 6222 #define __FUNCT__ "TSGetStages" 6223 /*@ 6224 TSGetStages - Get the number of stages and stage values 6225 6226 Input Parameter: 6227 . ts - the TS context obtained from TSCreate() 6228 6229 Level: advanced 6230 6231 .keywords: TS, getstages 6232 6233 .seealso: TSCreate() 6234 @*/ 6235 PetscErrorCode TSGetStages(TS ts,PetscInt *ns, Vec **Y) 6236 { 6237 PetscErrorCode ierr; 6238 6239 PetscFunctionBegin; 6240 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 6241 PetscValidPointer(ns,2); 6242 6243 if (!ts->ops->getstages) *ns=0; 6244 else { 6245 ierr = (*ts->ops->getstages)(ts,ns,Y);CHKERRQ(ierr); 6246 } 6247 PetscFunctionReturn(0); 6248 } 6249 6250 #undef __FUNCT__ 6251 #define __FUNCT__ "TSComputeIJacobianDefaultColor" 6252 /*@C 6253 TSComputeIJacobianDefaultColor - Computes the Jacobian using finite differences and coloring to exploit matrix sparsity. 6254 6255 Collective on SNES 6256 6257 Input Parameters: 6258 + ts - the TS context 6259 . t - current timestep 6260 . U - state vector 6261 . Udot - time derivative of state vector 6262 . shift - shift to apply, see note below 6263 - ctx - an optional user context 6264 6265 Output Parameters: 6266 + J - Jacobian matrix (not altered in this routine) 6267 - B - newly computed Jacobian matrix to use with preconditioner (generally the same as J) 6268 6269 Level: intermediate 6270 6271 Notes: 6272 If F(t,U,Udot)=0 is the DAE, the required Jacobian is 6273 6274 dF/dU + shift*dF/dUdot 6275 6276 Most users should not need to explicitly call this routine, as it 6277 is used internally within the nonlinear solvers. 6278 6279 This will first try to get the coloring from the DM. If the DM type has no coloring 6280 routine, then it will try to get the coloring from the matrix. This requires that the 6281 matrix have nonzero entries precomputed. 6282 6283 .keywords: TS, finite differences, Jacobian, coloring, sparse 6284 .seealso: TSSetIJacobian(), MatFDColoringCreate(), MatFDColoringSetFunction() 6285 @*/ 6286 PetscErrorCode TSComputeIJacobianDefaultColor(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat J,Mat B,void *ctx) 6287 { 6288 SNES snes; 6289 MatFDColoring color; 6290 PetscBool hascolor, matcolor = PETSC_FALSE; 6291 PetscErrorCode ierr; 6292 6293 PetscFunctionBegin; 6294 ierr = PetscOptionsGetBool(((PetscObject) ts)->prefix, "-ts_fd_color_use_mat", &matcolor, NULL);CHKERRQ(ierr); 6295 ierr = PetscObjectQuery((PetscObject) B, "TSMatFDColoring", (PetscObject *) &color);CHKERRQ(ierr); 6296 if (!color) { 6297 DM dm; 6298 ISColoring iscoloring; 6299 6300 ierr = TSGetDM(ts, &dm);CHKERRQ(ierr); 6301 ierr = DMHasColoring(dm, &hascolor);CHKERRQ(ierr); 6302 if (hascolor && !matcolor) { 6303 ierr = DMCreateColoring(dm, IS_COLORING_GLOBAL, &iscoloring);CHKERRQ(ierr); 6304 ierr = MatFDColoringCreate(B, iscoloring, &color);CHKERRQ(ierr); 6305 ierr = MatFDColoringSetFunction(color, (PetscErrorCode (*)(void)) SNESTSFormFunction, (void *) ts);CHKERRQ(ierr); 6306 ierr = MatFDColoringSetFromOptions(color);CHKERRQ(ierr); 6307 ierr = MatFDColoringSetUp(B, iscoloring, color);CHKERRQ(ierr); 6308 ierr = ISColoringDestroy(&iscoloring);CHKERRQ(ierr); 6309 } else { 6310 MatColoring mc; 6311 6312 ierr = MatColoringCreate(B, &mc);CHKERRQ(ierr); 6313 ierr = MatColoringSetDistance(mc, 2);CHKERRQ(ierr); 6314 ierr = MatColoringSetType(mc, MATCOLORINGSL);CHKERRQ(ierr); 6315 ierr = MatColoringSetFromOptions(mc);CHKERRQ(ierr); 6316 ierr = MatColoringApply(mc, &iscoloring);CHKERRQ(ierr); 6317 ierr = MatColoringDestroy(&mc);CHKERRQ(ierr); 6318 ierr = MatFDColoringCreate(B, iscoloring, &color);CHKERRQ(ierr); 6319 ierr = MatFDColoringSetFunction(color, (PetscErrorCode (*)(void)) SNESTSFormFunction, (void *) ts);CHKERRQ(ierr); 6320 ierr = MatFDColoringSetFromOptions(color);CHKERRQ(ierr); 6321 ierr = MatFDColoringSetUp(B, iscoloring, color);CHKERRQ(ierr); 6322 ierr = ISColoringDestroy(&iscoloring);CHKERRQ(ierr); 6323 } 6324 ierr = PetscObjectCompose((PetscObject) B, "TSMatFDColoring", (PetscObject) color);CHKERRQ(ierr); 6325 ierr = PetscObjectDereference((PetscObject) color);CHKERRQ(ierr); 6326 } 6327 ierr = TSGetSNES(ts, &snes);CHKERRQ(ierr); 6328 ierr = MatFDColoringApply(B, color, U, snes);CHKERRQ(ierr); 6329 if (J != B) { 6330 ierr = MatAssemblyBegin(J, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 6331 ierr = MatAssemblyEnd(J, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 6332 } 6333 PetscFunctionReturn(0); 6334 } 6335 6336 #undef __FUNCT__ 6337 #define __FUNCT__ "TSClone" 6338 /*@C 6339 TSClone - This function clones a time step object. 6340 6341 Collective on MPI_Comm 6342 6343 Input Parameter: 6344 . tsin - The input TS 6345 6346 Output Parameter: 6347 . tsout - The output TS (cloned) 6348 6349 Notes: 6350 This function is used to create a clone of a TS object. It is used in ARKIMEX for initializing the slope for first stage explicit methods. It will likely be replaced in the future with a mechanism of switching methods on the fly. 6351 6352 When using TSDestroy() on a clone the user has to first reset the correct TS reference in the embedded SNES object: e.g.: by running SNES snes_dup=NULL; TSGetSNES(ts,&snes_dup); ierr = TSSetSNES(ts,snes_dup); 6353 6354 Level: developer 6355 6356 .keywords: TS, clone 6357 .seealso: TSCreate(), TSSetType(), TSSetUp(), TSDestroy(), TSSetProblemType() 6358 @*/ 6359 PetscErrorCode TSClone(TS tsin, TS *tsout) 6360 { 6361 TS t; 6362 PetscErrorCode ierr; 6363 SNES snes_start; 6364 DM dm; 6365 TSType type; 6366 6367 PetscFunctionBegin; 6368 PetscValidPointer(tsin,1); 6369 *tsout = NULL; 6370 6371 ierr = PetscHeaderCreate(t, TS_CLASSID, "TS", "Time stepping", "TS", PetscObjectComm((PetscObject)tsin), TSDestroy, TSView);CHKERRQ(ierr); 6372 6373 /* General TS description */ 6374 t->numbermonitors = 0; 6375 t->setupcalled = 0; 6376 t->ksp_its = 0; 6377 t->snes_its = 0; 6378 t->nwork = 0; 6379 t->rhsjacobian.time = -1e20; 6380 t->rhsjacobian.scale = 1.; 6381 t->ijacobian.shift = 1.; 6382 6383 ierr = TSGetSNES(tsin,&snes_start); CHKERRQ(ierr); 6384 ierr = TSSetSNES(t,snes_start); CHKERRQ(ierr); 6385 6386 ierr = TSGetDM(tsin,&dm); CHKERRQ(ierr); 6387 ierr = TSSetDM(t,dm); CHKERRQ(ierr); 6388 6389 t->adapt=tsin->adapt; 6390 PetscObjectReference((PetscObject)t->adapt); 6391 6392 t->problem_type = tsin->problem_type; 6393 t->ptime = tsin->ptime; 6394 t->time_step = tsin->time_step; 6395 t->time_step_orig = tsin->time_step_orig; 6396 t->max_time = tsin->max_time; 6397 t->steps = tsin->steps; 6398 t->max_steps = tsin->max_steps; 6399 t->equation_type = tsin->equation_type; 6400 t->atol = tsin->atol; 6401 t->rtol = tsin->rtol; 6402 t->max_snes_failures = tsin->max_snes_failures; 6403 t->max_reject = tsin->max_reject; 6404 t->errorifstepfailed = tsin->errorifstepfailed; 6405 6406 ierr = TSGetType(tsin,&type); CHKERRQ(ierr); 6407 ierr = TSSetType(t,type); CHKERRQ(ierr); 6408 6409 t->vec_sol = NULL; 6410 6411 t->cfltime = tsin->cfltime; 6412 t->cfltime_local = tsin->cfltime_local; 6413 t->exact_final_time = tsin->exact_final_time; 6414 6415 ierr = PetscMemcpy(t->ops,tsin->ops,sizeof(struct _TSOps));CHKERRQ(ierr); 6416 6417 *tsout = t; 6418 PetscFunctionReturn(0); 6419 } 6420