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