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,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,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 = PetscDrawBoxedString(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 1987 ierr = MatDestroy(&ts->Arhs);CHKERRQ(ierr); 1988 ierr = MatDestroy(&ts->Brhs);CHKERRQ(ierr); 1989 ierr = VecDestroy(&ts->Frhs);CHKERRQ(ierr); 1990 ierr = VecDestroy(&ts->vec_sol);CHKERRQ(ierr); 1991 ierr = VecDestroy(&ts->vatol);CHKERRQ(ierr); 1992 ierr = VecDestroy(&ts->vrtol);CHKERRQ(ierr); 1993 ierr = VecDestroyVecs(ts->nwork,&ts->work);CHKERRQ(ierr); 1994 ierr = ISDestroy(&ts->is_diff);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); 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->event) { 3285 ierr = TSEventMonitorInitialize(ts);CHKERRQ(ierr); 3286 } 3287 while (!ts->reason) { 3288 ierr = TSMonitor(ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 3289 ierr = TSStep(ts);CHKERRQ(ierr); 3290 if (ts->event) { 3291 ierr = TSEventMonitor(ts);CHKERRQ(ierr); 3292 } 3293 if(!ts->steprollback) { 3294 ierr = TSTrajectorySet(ts->trajectory,ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 3295 ierr = TSPostStep(ts);CHKERRQ(ierr); 3296 } 3297 } 3298 if (ts->exact_final_time == TS_EXACTFINALTIME_INTERPOLATE && ts->ptime > ts->max_time) { 3299 ierr = TSInterpolate(ts,ts->max_time,u);CHKERRQ(ierr); 3300 ts->solvetime = ts->max_time; 3301 solution = u; 3302 } else { 3303 if (u) {ierr = VecCopy(ts->vec_sol,u);CHKERRQ(ierr);} 3304 ts->solvetime = ts->ptime; 3305 solution = ts->vec_sol; 3306 } 3307 ierr = TSMonitor(ts,ts->steps,ts->solvetime,solution);CHKERRQ(ierr); 3308 ierr = VecViewFromOptions(solution, ((PetscObject) ts)->prefix, "-ts_view_solution");CHKERRQ(ierr); 3309 } 3310 3311 ierr = TSViewFromOptions(ts,NULL,"-ts_view");CHKERRQ(ierr); 3312 ierr = PetscObjectSAWsBlock((PetscObject)ts);CHKERRQ(ierr); 3313 if (ts->vec_costintegral) ts->costintegralfwd=PETSC_TRUE; 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_indicate_data_points <true,false> - indicate 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 = PetscDrawLGIndicateDataPoints((*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 ierr = PetscDrawLGIndicateDataPoints(ctx->lg,PETSC_TRUE);CHKERRQ(ierr); 3490 } 3491 ierr = TSGetTimeStep(ts,&y);CHKERRQ(ierr); 3492 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 3493 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 3494 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 3495 } 3496 PetscFunctionReturn(0); 3497 } 3498 3499 #undef __FUNCT__ 3500 #define __FUNCT__ "TSMonitorLGCtxDestroy" 3501 /*@C 3502 TSMonitorLGCtxDestroy - Destroys a line graph context that was created 3503 with TSMonitorLGCtxCreate(). 3504 3505 Collective on TSMonitorLGCtx 3506 3507 Input Parameter: 3508 . ctx - the monitor context 3509 3510 Level: intermediate 3511 3512 .keywords: TS, monitor, line graph, destroy 3513 3514 .seealso: TSMonitorLGCtxCreate(), TSMonitorSet(), TSMonitorLGTimeStep(); 3515 @*/ 3516 PetscErrorCode TSMonitorLGCtxDestroy(TSMonitorLGCtx *ctx) 3517 { 3518 PetscDraw draw; 3519 PetscErrorCode ierr; 3520 3521 PetscFunctionBegin; 3522 if ((*ctx)->transformdestroy) { 3523 ierr = ((*ctx)->transformdestroy)((*ctx)->transformctx);CHKERRQ(ierr); 3524 } 3525 ierr = PetscDrawLGGetDraw((*ctx)->lg,&draw);CHKERRQ(ierr); 3526 ierr = PetscDrawDestroy(&draw);CHKERRQ(ierr); 3527 ierr = PetscDrawLGDestroy(&(*ctx)->lg);CHKERRQ(ierr); 3528 ierr = PetscStrArrayDestroy(&(*ctx)->names);CHKERRQ(ierr); 3529 ierr = PetscStrArrayDestroy(&(*ctx)->displaynames);CHKERRQ(ierr); 3530 ierr = PetscFree((*ctx)->displayvariables);CHKERRQ(ierr); 3531 ierr = PetscFree((*ctx)->displayvalues);CHKERRQ(ierr); 3532 ierr = PetscFree(*ctx);CHKERRQ(ierr); 3533 PetscFunctionReturn(0); 3534 } 3535 3536 #undef __FUNCT__ 3537 #define __FUNCT__ "TSGetTime" 3538 /*@ 3539 TSGetTime - Gets the time of the most recently completed step. 3540 3541 Not Collective 3542 3543 Input Parameter: 3544 . ts - the TS context obtained from TSCreate() 3545 3546 Output Parameter: 3547 . t - the current time 3548 3549 Level: beginner 3550 3551 Note: 3552 When called during time step evaluation (e.g. during residual evaluation or via hooks set using TSSetPreStep(), 3553 TSSetPreStage(), TSSetPostStage(), or TSSetPostStep()), the time is the time at the start of the step being evaluated. 3554 3555 .seealso: TSSetInitialTimeStep(), TSGetTimeStep() 3556 3557 .keywords: TS, get, time 3558 @*/ 3559 PetscErrorCode TSGetTime(TS ts,PetscReal *t) 3560 { 3561 PetscFunctionBegin; 3562 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3563 PetscValidRealPointer(t,2); 3564 *t = ts->ptime; 3565 PetscFunctionReturn(0); 3566 } 3567 3568 #undef __FUNCT__ 3569 #define __FUNCT__ "TSGetPrevTime" 3570 /*@ 3571 TSGetPrevTime - Gets the starting time of the previously completed step. 3572 3573 Not Collective 3574 3575 Input Parameter: 3576 . ts - the TS context obtained from TSCreate() 3577 3578 Output Parameter: 3579 . t - the previous time 3580 3581 Level: beginner 3582 3583 .seealso: TSSetInitialTimeStep(), TSGetTimeStep() 3584 3585 .keywords: TS, get, time 3586 @*/ 3587 PetscErrorCode TSGetPrevTime(TS ts,PetscReal *t) 3588 { 3589 PetscFunctionBegin; 3590 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3591 PetscValidRealPointer(t,2); 3592 *t = ts->ptime_prev; 3593 PetscFunctionReturn(0); 3594 } 3595 3596 #undef __FUNCT__ 3597 #define __FUNCT__ "TSSetTime" 3598 /*@ 3599 TSSetTime - Allows one to reset the time. 3600 3601 Logically Collective on TS 3602 3603 Input Parameters: 3604 + ts - the TS context obtained from TSCreate() 3605 - time - the time 3606 3607 Level: intermediate 3608 3609 .seealso: TSGetTime(), TSSetDuration() 3610 3611 .keywords: TS, set, time 3612 @*/ 3613 PetscErrorCode TSSetTime(TS ts, PetscReal t) 3614 { 3615 PetscFunctionBegin; 3616 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3617 PetscValidLogicalCollectiveReal(ts,t,2); 3618 ts->ptime = t; 3619 PetscFunctionReturn(0); 3620 } 3621 3622 #undef __FUNCT__ 3623 #define __FUNCT__ "TSSetOptionsPrefix" 3624 /*@C 3625 TSSetOptionsPrefix - Sets the prefix used for searching for all 3626 TS options in the database. 3627 3628 Logically Collective on TS 3629 3630 Input Parameter: 3631 + ts - The TS context 3632 - prefix - The prefix to prepend to all option names 3633 3634 Notes: 3635 A hyphen (-) must NOT be given at the beginning of the prefix name. 3636 The first character of all runtime options is AUTOMATICALLY the 3637 hyphen. 3638 3639 Level: advanced 3640 3641 .keywords: TS, set, options, prefix, database 3642 3643 .seealso: TSSetFromOptions() 3644 3645 @*/ 3646 PetscErrorCode TSSetOptionsPrefix(TS ts,const char prefix[]) 3647 { 3648 PetscErrorCode ierr; 3649 SNES snes; 3650 3651 PetscFunctionBegin; 3652 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3653 ierr = PetscObjectSetOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 3654 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 3655 ierr = SNESSetOptionsPrefix(snes,prefix);CHKERRQ(ierr); 3656 PetscFunctionReturn(0); 3657 } 3658 3659 3660 #undef __FUNCT__ 3661 #define __FUNCT__ "TSAppendOptionsPrefix" 3662 /*@C 3663 TSAppendOptionsPrefix - Appends to the prefix used for searching for all 3664 TS options in the database. 3665 3666 Logically Collective on TS 3667 3668 Input Parameter: 3669 + ts - The TS context 3670 - prefix - The prefix to prepend to all option names 3671 3672 Notes: 3673 A hyphen (-) must NOT be given at the beginning of the prefix name. 3674 The first character of all runtime options is AUTOMATICALLY the 3675 hyphen. 3676 3677 Level: advanced 3678 3679 .keywords: TS, append, options, prefix, database 3680 3681 .seealso: TSGetOptionsPrefix() 3682 3683 @*/ 3684 PetscErrorCode TSAppendOptionsPrefix(TS ts,const char prefix[]) 3685 { 3686 PetscErrorCode ierr; 3687 SNES snes; 3688 3689 PetscFunctionBegin; 3690 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3691 ierr = PetscObjectAppendOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 3692 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 3693 ierr = SNESAppendOptionsPrefix(snes,prefix);CHKERRQ(ierr); 3694 PetscFunctionReturn(0); 3695 } 3696 3697 #undef __FUNCT__ 3698 #define __FUNCT__ "TSGetOptionsPrefix" 3699 /*@C 3700 TSGetOptionsPrefix - Sets the prefix used for searching for all 3701 TS options in the database. 3702 3703 Not Collective 3704 3705 Input Parameter: 3706 . ts - The TS context 3707 3708 Output Parameter: 3709 . prefix - A pointer to the prefix string used 3710 3711 Notes: On the fortran side, the user should pass in a string 'prifix' of 3712 sufficient length to hold the prefix. 3713 3714 Level: intermediate 3715 3716 .keywords: TS, get, options, prefix, database 3717 3718 .seealso: TSAppendOptionsPrefix() 3719 @*/ 3720 PetscErrorCode TSGetOptionsPrefix(TS ts,const char *prefix[]) 3721 { 3722 PetscErrorCode ierr; 3723 3724 PetscFunctionBegin; 3725 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3726 PetscValidPointer(prefix,2); 3727 ierr = PetscObjectGetOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 3728 PetscFunctionReturn(0); 3729 } 3730 3731 #undef __FUNCT__ 3732 #define __FUNCT__ "TSGetRHSJacobian" 3733 /*@C 3734 TSGetRHSJacobian - Returns the Jacobian J at the present timestep. 3735 3736 Not Collective, but parallel objects are returned if TS is parallel 3737 3738 Input Parameter: 3739 . ts - The TS context obtained from TSCreate() 3740 3741 Output Parameters: 3742 + Amat - The (approximate) Jacobian J of G, where U_t = G(U,t) (or NULL) 3743 . Pmat - The matrix from which the preconditioner is constructed, usually the same as Amat (or NULL) 3744 . func - Function to compute the Jacobian of the RHS (or NULL) 3745 - ctx - User-defined context for Jacobian evaluation routine (or NULL) 3746 3747 Notes: You can pass in NULL for any return argument you do not need. 3748 3749 Level: intermediate 3750 3751 .seealso: TSGetTimeStep(), TSGetMatrices(), TSGetTime(), TSGetTimeStepNumber() 3752 3753 .keywords: TS, timestep, get, matrix, Jacobian 3754 @*/ 3755 PetscErrorCode TSGetRHSJacobian(TS ts,Mat *Amat,Mat *Pmat,TSRHSJacobian *func,void **ctx) 3756 { 3757 PetscErrorCode ierr; 3758 SNES snes; 3759 DM dm; 3760 3761 PetscFunctionBegin; 3762 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 3763 ierr = SNESGetJacobian(snes,Amat,Pmat,NULL,NULL);CHKERRQ(ierr); 3764 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 3765 ierr = DMTSGetRHSJacobian(dm,func,ctx);CHKERRQ(ierr); 3766 PetscFunctionReturn(0); 3767 } 3768 3769 #undef __FUNCT__ 3770 #define __FUNCT__ "TSGetIJacobian" 3771 /*@C 3772 TSGetIJacobian - Returns the implicit Jacobian at the present timestep. 3773 3774 Not Collective, but parallel objects are returned if TS is parallel 3775 3776 Input Parameter: 3777 . ts - The TS context obtained from TSCreate() 3778 3779 Output Parameters: 3780 + Amat - The (approximate) Jacobian of F(t,U,U_t) 3781 . Pmat - The matrix from which the preconditioner is constructed, often the same as Amat 3782 . f - The function to compute the matrices 3783 - ctx - User-defined context for Jacobian evaluation routine 3784 3785 Notes: You can pass in NULL for any return argument you do not need. 3786 3787 Level: advanced 3788 3789 .seealso: TSGetTimeStep(), TSGetRHSJacobian(), TSGetMatrices(), TSGetTime(), TSGetTimeStepNumber() 3790 3791 .keywords: TS, timestep, get, matrix, Jacobian 3792 @*/ 3793 PetscErrorCode TSGetIJacobian(TS ts,Mat *Amat,Mat *Pmat,TSIJacobian *f,void **ctx) 3794 { 3795 PetscErrorCode ierr; 3796 SNES snes; 3797 DM dm; 3798 3799 PetscFunctionBegin; 3800 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 3801 ierr = SNESSetUpMatrices(snes);CHKERRQ(ierr); 3802 ierr = SNESGetJacobian(snes,Amat,Pmat,NULL,NULL);CHKERRQ(ierr); 3803 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 3804 ierr = DMTSGetIJacobian(dm,f,ctx);CHKERRQ(ierr); 3805 PetscFunctionReturn(0); 3806 } 3807 3808 3809 #undef __FUNCT__ 3810 #define __FUNCT__ "TSMonitorDrawSolution" 3811 /*@C 3812 TSMonitorDrawSolution - Monitors progress of the TS solvers by calling 3813 VecView() for the solution at each timestep 3814 3815 Collective on TS 3816 3817 Input Parameters: 3818 + ts - the TS context 3819 . step - current time-step 3820 . ptime - current time 3821 - dummy - either a viewer or NULL 3822 3823 Options Database: 3824 . -ts_monitor_draw_solution_initial - show initial solution as well as current solution 3825 3826 Notes: the initial solution and current solution are not display with a common axis scaling so generally the option -ts_monitor_draw_solution_initial 3827 will look bad 3828 3829 Level: intermediate 3830 3831 .keywords: TS, vector, monitor, view 3832 3833 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 3834 @*/ 3835 PetscErrorCode TSMonitorDrawSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 3836 { 3837 PetscErrorCode ierr; 3838 TSMonitorDrawCtx ictx = (TSMonitorDrawCtx)dummy; 3839 PetscDraw draw; 3840 3841 PetscFunctionBegin; 3842 if (!step && ictx->showinitial) { 3843 if (!ictx->initialsolution) { 3844 ierr = VecDuplicate(u,&ictx->initialsolution);CHKERRQ(ierr); 3845 } 3846 ierr = VecCopy(u,ictx->initialsolution);CHKERRQ(ierr); 3847 } 3848 if (!(((ictx->howoften > 0) && (!(step % ictx->howoften))) || ((ictx->howoften == -1) && ts->reason))) PetscFunctionReturn(0); 3849 3850 if (ictx->showinitial) { 3851 PetscReal pause; 3852 ierr = PetscViewerDrawGetPause(ictx->viewer,&pause);CHKERRQ(ierr); 3853 ierr = PetscViewerDrawSetPause(ictx->viewer,0.0);CHKERRQ(ierr); 3854 ierr = VecView(ictx->initialsolution,ictx->viewer);CHKERRQ(ierr); 3855 ierr = PetscViewerDrawSetPause(ictx->viewer,pause);CHKERRQ(ierr); 3856 ierr = PetscViewerDrawSetHold(ictx->viewer,PETSC_TRUE);CHKERRQ(ierr); 3857 } 3858 ierr = VecView(u,ictx->viewer);CHKERRQ(ierr); 3859 if (ictx->showtimestepandtime) { 3860 PetscReal xl,yl,xr,yr,tw,w,h; 3861 char time[32]; 3862 size_t len; 3863 3864 ierr = PetscViewerDrawGetDraw(ictx->viewer,0,&draw);CHKERRQ(ierr); 3865 ierr = PetscSNPrintf(time,32,"Timestep %d Time %g",(int)step,(double)ptime);CHKERRQ(ierr); 3866 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 3867 ierr = PetscStrlen(time,&len);CHKERRQ(ierr); 3868 ierr = PetscDrawStringGetSize(draw,&tw,NULL);CHKERRQ(ierr); 3869 w = xl + .5*(xr - xl) - .5*len*tw; 3870 h = yl + .95*(yr - yl); 3871 ierr = PetscDrawString(draw,w,h,PETSC_DRAW_BLACK,time);CHKERRQ(ierr); 3872 ierr = PetscDrawFlush(draw);CHKERRQ(ierr); 3873 } 3874 3875 if (ictx->showinitial) { 3876 ierr = PetscViewerDrawSetHold(ictx->viewer,PETSC_FALSE);CHKERRQ(ierr); 3877 } 3878 PetscFunctionReturn(0); 3879 } 3880 3881 #undef __FUNCT__ 3882 #define __FUNCT__ "TSMonitorDrawSolutionPhase" 3883 /*@C 3884 TSMonitorDrawSolutionPhase - Monitors progress of the TS solvers by plotting the solution as a phase diagram 3885 3886 Collective on TS 3887 3888 Input Parameters: 3889 + ts - the TS context 3890 . step - current time-step 3891 . ptime - current time 3892 - dummy - either a viewer or NULL 3893 3894 Level: intermediate 3895 3896 .keywords: TS, vector, monitor, view 3897 3898 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 3899 @*/ 3900 PetscErrorCode TSMonitorDrawSolutionPhase(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 3901 { 3902 PetscErrorCode ierr; 3903 TSMonitorDrawCtx ictx = (TSMonitorDrawCtx)dummy; 3904 PetscDraw draw; 3905 MPI_Comm comm; 3906 PetscInt n; 3907 PetscMPIInt size; 3908 PetscReal xl,yl,xr,yr,tw,w,h; 3909 char time[32]; 3910 size_t len; 3911 const PetscScalar *U; 3912 3913 PetscFunctionBegin; 3914 ierr = PetscObjectGetComm((PetscObject)ts,&comm);CHKERRQ(ierr); 3915 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3916 if (size != 1) SETERRQ(comm,PETSC_ERR_SUP,"Only allowed for sequential runs"); 3917 ierr = VecGetSize(u,&n);CHKERRQ(ierr); 3918 if (n != 2) SETERRQ(comm,PETSC_ERR_SUP,"Only for ODEs with two unknowns"); 3919 3920 ierr = PetscViewerDrawGetDraw(ictx->viewer,0,&draw);CHKERRQ(ierr); 3921 3922 ierr = VecGetArrayRead(u,&U);CHKERRQ(ierr); 3923 ierr = PetscDrawAxisGetLimits(ictx->axis,&xl,&xr,&yl,&yr);CHKERRQ(ierr); 3924 if ((PetscRealPart(U[0]) < xl) || (PetscRealPart(U[1]) < yl) || (PetscRealPart(U[0]) > xr) || (PetscRealPart(U[1]) > yr)) { 3925 ierr = VecRestoreArrayRead(u,&U);CHKERRQ(ierr); 3926 PetscFunctionReturn(0); 3927 } 3928 if (!step) ictx->color++; 3929 ierr = PetscDrawPoint(draw,PetscRealPart(U[0]),PetscRealPart(U[1]),ictx->color);CHKERRQ(ierr); 3930 ierr = VecRestoreArrayRead(u,&U);CHKERRQ(ierr); 3931 3932 if (ictx->showtimestepandtime) { 3933 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 3934 ierr = PetscSNPrintf(time,32,"Timestep %d Time %g",(int)step,(double)ptime);CHKERRQ(ierr); 3935 ierr = PetscStrlen(time,&len);CHKERRQ(ierr); 3936 ierr = PetscDrawStringGetSize(draw,&tw,NULL);CHKERRQ(ierr); 3937 w = xl + .5*(xr - xl) - .5*len*tw; 3938 h = yl + .95*(yr - yl); 3939 ierr = PetscDrawString(draw,w,h,PETSC_DRAW_BLACK,time);CHKERRQ(ierr); 3940 } 3941 ierr = PetscDrawFlush(draw);CHKERRQ(ierr); 3942 PetscFunctionReturn(0); 3943 } 3944 3945 3946 #undef __FUNCT__ 3947 #define __FUNCT__ "TSMonitorDrawCtxDestroy" 3948 /*@C 3949 TSMonitorDrawCtxDestroy - Destroys the monitor context for TSMonitorDrawSolution() 3950 3951 Collective on TS 3952 3953 Input Parameters: 3954 . ctx - the monitor context 3955 3956 Level: intermediate 3957 3958 .keywords: TS, vector, monitor, view 3959 3960 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorDrawSolution(), TSMonitorDrawError() 3961 @*/ 3962 PetscErrorCode TSMonitorDrawCtxDestroy(TSMonitorDrawCtx *ictx) 3963 { 3964 PetscErrorCode ierr; 3965 3966 PetscFunctionBegin; 3967 ierr = PetscDrawAxisDestroy(&(*ictx)->axis);CHKERRQ(ierr); 3968 ierr = PetscViewerDestroy(&(*ictx)->viewer);CHKERRQ(ierr); 3969 ierr = VecDestroy(&(*ictx)->initialsolution);CHKERRQ(ierr); 3970 ierr = PetscFree(*ictx);CHKERRQ(ierr); 3971 PetscFunctionReturn(0); 3972 } 3973 3974 #undef __FUNCT__ 3975 #define __FUNCT__ "TSMonitorDrawCtxCreate" 3976 /*@C 3977 TSMonitorDrawCtxCreate - Creates the monitor context for TSMonitorDrawCtx 3978 3979 Collective on TS 3980 3981 Input Parameter: 3982 . ts - time-step context 3983 3984 Output Patameter: 3985 . ctx - the monitor context 3986 3987 Options Database: 3988 . -ts_monitor_draw_solution_initial - show initial solution as well as current solution 3989 3990 Level: intermediate 3991 3992 .keywords: TS, vector, monitor, view 3993 3994 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorDrawCtx() 3995 @*/ 3996 PetscErrorCode TSMonitorDrawCtxCreate(MPI_Comm comm,const char host[],const char label[],int x,int y,int m,int n,PetscInt howoften,TSMonitorDrawCtx *ctx) 3997 { 3998 PetscErrorCode ierr; 3999 4000 PetscFunctionBegin; 4001 ierr = PetscNew(ctx);CHKERRQ(ierr); 4002 ierr = PetscViewerDrawOpen(comm,host,label,x,y,m,n,&(*ctx)->viewer);CHKERRQ(ierr); 4003 ierr = PetscViewerSetFromOptions((*ctx)->viewer);CHKERRQ(ierr); 4004 4005 (*ctx)->howoften = howoften; 4006 (*ctx)->showinitial = PETSC_FALSE; 4007 ierr = PetscOptionsGetBool(NULL,"-ts_monitor_draw_solution_initial",&(*ctx)->showinitial,NULL);CHKERRQ(ierr); 4008 4009 (*ctx)->showtimestepandtime = PETSC_FALSE; 4010 ierr = PetscOptionsGetBool(NULL,"-ts_monitor_draw_solution_show_time",&(*ctx)->showtimestepandtime,NULL);CHKERRQ(ierr); 4011 (*ctx)->color = PETSC_DRAW_WHITE; 4012 PetscFunctionReturn(0); 4013 } 4014 4015 #undef __FUNCT__ 4016 #define __FUNCT__ "TSMonitorDrawError" 4017 /*@C 4018 TSMonitorDrawError - Monitors progress of the TS solvers by calling 4019 VecView() for the error at each timestep 4020 4021 Collective on TS 4022 4023 Input Parameters: 4024 + ts - the TS context 4025 . step - current time-step 4026 . ptime - current time 4027 - dummy - either a viewer or NULL 4028 4029 Level: intermediate 4030 4031 .keywords: TS, vector, monitor, view 4032 4033 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 4034 @*/ 4035 PetscErrorCode TSMonitorDrawError(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 4036 { 4037 PetscErrorCode ierr; 4038 TSMonitorDrawCtx ctx = (TSMonitorDrawCtx)dummy; 4039 PetscViewer viewer = ctx->viewer; 4040 Vec work; 4041 4042 PetscFunctionBegin; 4043 if (!(((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason))) PetscFunctionReturn(0); 4044 ierr = VecDuplicate(u,&work);CHKERRQ(ierr); 4045 ierr = TSComputeSolutionFunction(ts,ptime,work);CHKERRQ(ierr); 4046 ierr = VecAXPY(work,-1.0,u);CHKERRQ(ierr); 4047 ierr = VecView(work,viewer);CHKERRQ(ierr); 4048 ierr = VecDestroy(&work);CHKERRQ(ierr); 4049 PetscFunctionReturn(0); 4050 } 4051 4052 #include <petsc-private/dmimpl.h> 4053 #undef __FUNCT__ 4054 #define __FUNCT__ "TSSetDM" 4055 /*@ 4056 TSSetDM - Sets the DM that may be used by some preconditioners 4057 4058 Logically Collective on TS and DM 4059 4060 Input Parameters: 4061 + ts - the preconditioner context 4062 - dm - the dm 4063 4064 Level: intermediate 4065 4066 4067 .seealso: TSGetDM(), SNESSetDM(), SNESGetDM() 4068 @*/ 4069 PetscErrorCode TSSetDM(TS ts,DM dm) 4070 { 4071 PetscErrorCode ierr; 4072 SNES snes; 4073 DMTS tsdm; 4074 4075 PetscFunctionBegin; 4076 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4077 ierr = PetscObjectReference((PetscObject)dm);CHKERRQ(ierr); 4078 if (ts->dm) { /* Move the DMTS context over to the new DM unless the new DM already has one */ 4079 if (ts->dm->dmts && !dm->dmts) { 4080 ierr = DMCopyDMTS(ts->dm,dm);CHKERRQ(ierr); 4081 ierr = DMGetDMTS(ts->dm,&tsdm);CHKERRQ(ierr); 4082 if (tsdm->originaldm == ts->dm) { /* Grant write privileges to the replacement DM */ 4083 tsdm->originaldm = dm; 4084 } 4085 } 4086 ierr = DMDestroy(&ts->dm);CHKERRQ(ierr); 4087 } 4088 ts->dm = dm; 4089 4090 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4091 ierr = SNESSetDM(snes,dm);CHKERRQ(ierr); 4092 PetscFunctionReturn(0); 4093 } 4094 4095 #undef __FUNCT__ 4096 #define __FUNCT__ "TSGetDM" 4097 /*@ 4098 TSGetDM - Gets the DM that may be used by some preconditioners 4099 4100 Not Collective 4101 4102 Input Parameter: 4103 . ts - the preconditioner context 4104 4105 Output Parameter: 4106 . dm - the dm 4107 4108 Level: intermediate 4109 4110 4111 .seealso: TSSetDM(), SNESSetDM(), SNESGetDM() 4112 @*/ 4113 PetscErrorCode TSGetDM(TS ts,DM *dm) 4114 { 4115 PetscErrorCode ierr; 4116 4117 PetscFunctionBegin; 4118 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4119 if (!ts->dm) { 4120 ierr = DMShellCreate(PetscObjectComm((PetscObject)ts),&ts->dm);CHKERRQ(ierr); 4121 if (ts->snes) {ierr = SNESSetDM(ts->snes,ts->dm);CHKERRQ(ierr);} 4122 } 4123 *dm = ts->dm; 4124 PetscFunctionReturn(0); 4125 } 4126 4127 #undef __FUNCT__ 4128 #define __FUNCT__ "SNESTSFormFunction" 4129 /*@ 4130 SNESTSFormFunction - Function to evaluate nonlinear residual 4131 4132 Logically Collective on SNES 4133 4134 Input Parameter: 4135 + snes - nonlinear solver 4136 . U - the current state at which to evaluate the residual 4137 - ctx - user context, must be a TS 4138 4139 Output Parameter: 4140 . F - the nonlinear residual 4141 4142 Notes: 4143 This function is not normally called by users and is automatically registered with the SNES used by TS. 4144 It is most frequently passed to MatFDColoringSetFunction(). 4145 4146 Level: advanced 4147 4148 .seealso: SNESSetFunction(), MatFDColoringSetFunction() 4149 @*/ 4150 PetscErrorCode SNESTSFormFunction(SNES snes,Vec U,Vec F,void *ctx) 4151 { 4152 TS ts = (TS)ctx; 4153 PetscErrorCode ierr; 4154 4155 PetscFunctionBegin; 4156 PetscValidHeaderSpecific(snes,SNES_CLASSID,1); 4157 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 4158 PetscValidHeaderSpecific(F,VEC_CLASSID,3); 4159 PetscValidHeaderSpecific(ts,TS_CLASSID,4); 4160 ierr = (ts->ops->snesfunction)(snes,U,F,ts);CHKERRQ(ierr); 4161 PetscFunctionReturn(0); 4162 } 4163 4164 #undef __FUNCT__ 4165 #define __FUNCT__ "SNESTSFormJacobian" 4166 /*@ 4167 SNESTSFormJacobian - Function to evaluate the Jacobian 4168 4169 Collective on SNES 4170 4171 Input Parameter: 4172 + snes - nonlinear solver 4173 . U - the current state at which to evaluate the residual 4174 - ctx - user context, must be a TS 4175 4176 Output Parameter: 4177 + A - the Jacobian 4178 . B - the preconditioning matrix (may be the same as A) 4179 - flag - indicates any structure change in the matrix 4180 4181 Notes: 4182 This function is not normally called by users and is automatically registered with the SNES used by TS. 4183 4184 Level: developer 4185 4186 .seealso: SNESSetJacobian() 4187 @*/ 4188 PetscErrorCode SNESTSFormJacobian(SNES snes,Vec U,Mat A,Mat B,void *ctx) 4189 { 4190 TS ts = (TS)ctx; 4191 PetscErrorCode ierr; 4192 4193 PetscFunctionBegin; 4194 PetscValidHeaderSpecific(snes,SNES_CLASSID,1); 4195 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 4196 PetscValidPointer(A,3); 4197 PetscValidHeaderSpecific(A,MAT_CLASSID,3); 4198 PetscValidPointer(B,4); 4199 PetscValidHeaderSpecific(B,MAT_CLASSID,4); 4200 PetscValidHeaderSpecific(ts,TS_CLASSID,6); 4201 ierr = (ts->ops->snesjacobian)(snes,U,A,B,ts);CHKERRQ(ierr); 4202 PetscFunctionReturn(0); 4203 } 4204 4205 #undef __FUNCT__ 4206 #define __FUNCT__ "TSComputeRHSFunctionLinear" 4207 /*@C 4208 TSComputeRHSFunctionLinear - Evaluate the right hand side via the user-provided Jacobian, for linear problems only 4209 4210 Collective on TS 4211 4212 Input Arguments: 4213 + ts - time stepping context 4214 . t - time at which to evaluate 4215 . U - state at which to evaluate 4216 - ctx - context 4217 4218 Output Arguments: 4219 . F - right hand side 4220 4221 Level: intermediate 4222 4223 Notes: 4224 This function is intended to be passed to TSSetRHSFunction() to evaluate the right hand side for linear problems. 4225 The matrix (and optionally the evaluation context) should be passed to TSSetRHSJacobian(). 4226 4227 .seealso: TSSetRHSFunction(), TSSetRHSJacobian(), TSComputeRHSJacobianConstant() 4228 @*/ 4229 PetscErrorCode TSComputeRHSFunctionLinear(TS ts,PetscReal t,Vec U,Vec F,void *ctx) 4230 { 4231 PetscErrorCode ierr; 4232 Mat Arhs,Brhs; 4233 4234 PetscFunctionBegin; 4235 ierr = TSGetRHSMats_Private(ts,&Arhs,&Brhs);CHKERRQ(ierr); 4236 ierr = TSComputeRHSJacobian(ts,t,U,Arhs,Brhs);CHKERRQ(ierr); 4237 ierr = MatMult(Arhs,U,F);CHKERRQ(ierr); 4238 PetscFunctionReturn(0); 4239 } 4240 4241 #undef __FUNCT__ 4242 #define __FUNCT__ "TSComputeRHSJacobianConstant" 4243 /*@C 4244 TSComputeRHSJacobianConstant - Reuses a Jacobian that is time-independent. 4245 4246 Collective on TS 4247 4248 Input Arguments: 4249 + ts - time stepping context 4250 . t - time at which to evaluate 4251 . U - state at which to evaluate 4252 - ctx - context 4253 4254 Output Arguments: 4255 + A - pointer to operator 4256 . B - pointer to preconditioning matrix 4257 - flg - matrix structure flag 4258 4259 Level: intermediate 4260 4261 Notes: 4262 This function is intended to be passed to TSSetRHSJacobian() to evaluate the Jacobian for linear time-independent problems. 4263 4264 .seealso: TSSetRHSFunction(), TSSetRHSJacobian(), TSComputeRHSFunctionLinear() 4265 @*/ 4266 PetscErrorCode TSComputeRHSJacobianConstant(TS ts,PetscReal t,Vec U,Mat A,Mat B,void *ctx) 4267 { 4268 PetscFunctionBegin; 4269 PetscFunctionReturn(0); 4270 } 4271 4272 #undef __FUNCT__ 4273 #define __FUNCT__ "TSComputeIFunctionLinear" 4274 /*@C 4275 TSComputeIFunctionLinear - Evaluate the left hand side via the user-provided Jacobian, for linear problems only 4276 4277 Collective on TS 4278 4279 Input Arguments: 4280 + ts - time stepping context 4281 . t - time at which to evaluate 4282 . U - state at which to evaluate 4283 . Udot - time derivative of state vector 4284 - ctx - context 4285 4286 Output Arguments: 4287 . F - left hand side 4288 4289 Level: intermediate 4290 4291 Notes: 4292 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 4293 user is required to write their own TSComputeIFunction. 4294 This function is intended to be passed to TSSetIFunction() to evaluate the left hand side for linear problems. 4295 The matrix (and optionally the evaluation context) should be passed to TSSetIJacobian(). 4296 4297 .seealso: TSSetIFunction(), TSSetIJacobian(), TSComputeIJacobianConstant() 4298 @*/ 4299 PetscErrorCode TSComputeIFunctionLinear(TS ts,PetscReal t,Vec U,Vec Udot,Vec F,void *ctx) 4300 { 4301 PetscErrorCode ierr; 4302 Mat A,B; 4303 4304 PetscFunctionBegin; 4305 ierr = TSGetIJacobian(ts,&A,&B,NULL,NULL);CHKERRQ(ierr); 4306 ierr = TSComputeIJacobian(ts,t,U,Udot,1.0,A,B,PETSC_TRUE);CHKERRQ(ierr); 4307 ierr = MatMult(A,Udot,F);CHKERRQ(ierr); 4308 PetscFunctionReturn(0); 4309 } 4310 4311 #undef __FUNCT__ 4312 #define __FUNCT__ "TSComputeIJacobianConstant" 4313 /*@C 4314 TSComputeIJacobianConstant - Reuses a time-independent for a semi-implicit DAE or ODE 4315 4316 Collective on TS 4317 4318 Input Arguments: 4319 + ts - time stepping context 4320 . t - time at which to evaluate 4321 . U - state at which to evaluate 4322 . Udot - time derivative of state vector 4323 . shift - shift to apply 4324 - ctx - context 4325 4326 Output Arguments: 4327 + A - pointer to operator 4328 . B - pointer to preconditioning matrix 4329 - flg - matrix structure flag 4330 4331 Level: advanced 4332 4333 Notes: 4334 This function is intended to be passed to TSSetIJacobian() to evaluate the Jacobian for linear time-independent problems. 4335 4336 It is only appropriate for problems of the form 4337 4338 $ M Udot = F(U,t) 4339 4340 where M is constant and F is non-stiff. The user must pass M to TSSetIJacobian(). The current implementation only 4341 works with IMEX time integration methods such as TSROSW and TSARKIMEX, since there is no support for de-constructing 4342 an implicit operator of the form 4343 4344 $ shift*M + J 4345 4346 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 4347 a copy of M or reassemble it when requested. 4348 4349 .seealso: TSSetIFunction(), TSSetIJacobian(), TSComputeIFunctionLinear() 4350 @*/ 4351 PetscErrorCode TSComputeIJacobianConstant(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat A,Mat B,void *ctx) 4352 { 4353 PetscErrorCode ierr; 4354 4355 PetscFunctionBegin; 4356 ierr = MatScale(A, shift / ts->ijacobian.shift);CHKERRQ(ierr); 4357 ts->ijacobian.shift = shift; 4358 PetscFunctionReturn(0); 4359 } 4360 4361 #undef __FUNCT__ 4362 #define __FUNCT__ "TSGetEquationType" 4363 /*@ 4364 TSGetEquationType - Gets the type of the equation that TS is solving. 4365 4366 Not Collective 4367 4368 Input Parameter: 4369 . ts - the TS context 4370 4371 Output Parameter: 4372 . equation_type - see TSEquationType 4373 4374 Level: beginner 4375 4376 .keywords: TS, equation type 4377 4378 .seealso: TSSetEquationType(), TSEquationType 4379 @*/ 4380 PetscErrorCode TSGetEquationType(TS ts,TSEquationType *equation_type) 4381 { 4382 PetscFunctionBegin; 4383 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4384 PetscValidPointer(equation_type,2); 4385 *equation_type = ts->equation_type; 4386 PetscFunctionReturn(0); 4387 } 4388 4389 #undef __FUNCT__ 4390 #define __FUNCT__ "TSSetEquationType" 4391 /*@ 4392 TSSetEquationType - Sets the type of the equation that TS is solving. 4393 4394 Not Collective 4395 4396 Input Parameter: 4397 + ts - the TS context 4398 . equation_type - see TSEquationType 4399 4400 Level: advanced 4401 4402 .keywords: TS, equation type 4403 4404 .seealso: TSGetEquationType(), TSEquationType 4405 @*/ 4406 PetscErrorCode TSSetEquationType(TS ts,TSEquationType equation_type) 4407 { 4408 PetscFunctionBegin; 4409 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4410 ts->equation_type = equation_type; 4411 PetscFunctionReturn(0); 4412 } 4413 4414 #undef __FUNCT__ 4415 #define __FUNCT__ "TSGetConvergedReason" 4416 /*@ 4417 TSGetConvergedReason - Gets the reason the TS iteration was stopped. 4418 4419 Not Collective 4420 4421 Input Parameter: 4422 . ts - the TS context 4423 4424 Output Parameter: 4425 . reason - negative value indicates diverged, positive value converged, see TSConvergedReason or the 4426 manual pages for the individual convergence tests for complete lists 4427 4428 Level: beginner 4429 4430 Notes: 4431 Can only be called after the call to TSSolve() is complete. 4432 4433 .keywords: TS, nonlinear, set, convergence, test 4434 4435 .seealso: TSSetConvergenceTest(), TSConvergedReason 4436 @*/ 4437 PetscErrorCode TSGetConvergedReason(TS ts,TSConvergedReason *reason) 4438 { 4439 PetscFunctionBegin; 4440 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4441 PetscValidPointer(reason,2); 4442 *reason = ts->reason; 4443 PetscFunctionReturn(0); 4444 } 4445 4446 #undef __FUNCT__ 4447 #define __FUNCT__ "TSSetConvergedReason" 4448 /*@ 4449 TSSetConvergedReason - Sets the reason for handling the convergence of TSSolve. 4450 4451 Not Collective 4452 4453 Input Parameter: 4454 + ts - the TS context 4455 . reason - negative value indicates diverged, positive value converged, see TSConvergedReason or the 4456 manual pages for the individual convergence tests for complete lists 4457 4458 Level: advanced 4459 4460 Notes: 4461 Can only be called during TSSolve() is active. 4462 4463 .keywords: TS, nonlinear, set, convergence, test 4464 4465 .seealso: TSConvergedReason 4466 @*/ 4467 PetscErrorCode TSSetConvergedReason(TS ts,TSConvergedReason reason) 4468 { 4469 PetscFunctionBegin; 4470 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4471 ts->reason = reason; 4472 PetscFunctionReturn(0); 4473 } 4474 4475 #undef __FUNCT__ 4476 #define __FUNCT__ "TSGetSolveTime" 4477 /*@ 4478 TSGetSolveTime - Gets the time after a call to TSSolve() 4479 4480 Not Collective 4481 4482 Input Parameter: 4483 . ts - the TS context 4484 4485 Output Parameter: 4486 . ftime - the final time. This time should correspond to the final time set with TSSetDuration() 4487 4488 Level: beginner 4489 4490 Notes: 4491 Can only be called after the call to TSSolve() is complete. 4492 4493 .keywords: TS, nonlinear, set, convergence, test 4494 4495 .seealso: TSSetConvergenceTest(), TSConvergedReason 4496 @*/ 4497 PetscErrorCode TSGetSolveTime(TS ts,PetscReal *ftime) 4498 { 4499 PetscFunctionBegin; 4500 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4501 PetscValidPointer(ftime,2); 4502 *ftime = ts->solvetime; 4503 PetscFunctionReturn(0); 4504 } 4505 4506 #undef __FUNCT__ 4507 #define __FUNCT__ "TSGetTotalSteps" 4508 /*@ 4509 TSGetTotalSteps - Gets the total number of steps done since the last call to TSSetUp() or TSCreate() 4510 4511 Not Collective 4512 4513 Input Parameter: 4514 . ts - the TS context 4515 4516 Output Parameter: 4517 . steps - the number of steps 4518 4519 Level: beginner 4520 4521 Notes: 4522 Includes the number of steps for all calls to TSSolve() since TSSetUp() was called 4523 4524 .keywords: TS, nonlinear, set, convergence, test 4525 4526 .seealso: TSSetConvergenceTest(), TSConvergedReason 4527 @*/ 4528 PetscErrorCode TSGetTotalSteps(TS ts,PetscInt *steps) 4529 { 4530 PetscFunctionBegin; 4531 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4532 PetscValidPointer(steps,2); 4533 *steps = ts->total_steps; 4534 PetscFunctionReturn(0); 4535 } 4536 4537 #undef __FUNCT__ 4538 #define __FUNCT__ "TSGetSNESIterations" 4539 /*@ 4540 TSGetSNESIterations - Gets the total number of nonlinear iterations 4541 used by the time integrator. 4542 4543 Not Collective 4544 4545 Input Parameter: 4546 . ts - TS context 4547 4548 Output Parameter: 4549 . nits - number of nonlinear iterations 4550 4551 Notes: 4552 This counter is reset to zero for each successive call to TSSolve(). 4553 4554 Level: intermediate 4555 4556 .keywords: TS, get, number, nonlinear, iterations 4557 4558 .seealso: TSGetKSPIterations() 4559 @*/ 4560 PetscErrorCode TSGetSNESIterations(TS ts,PetscInt *nits) 4561 { 4562 PetscFunctionBegin; 4563 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4564 PetscValidIntPointer(nits,2); 4565 *nits = ts->snes_its; 4566 PetscFunctionReturn(0); 4567 } 4568 4569 #undef __FUNCT__ 4570 #define __FUNCT__ "TSGetKSPIterations" 4571 /*@ 4572 TSGetKSPIterations - Gets the total number of linear iterations 4573 used by the time integrator. 4574 4575 Not Collective 4576 4577 Input Parameter: 4578 . ts - TS context 4579 4580 Output Parameter: 4581 . lits - number of linear iterations 4582 4583 Notes: 4584 This counter is reset to zero for each successive call to TSSolve(). 4585 4586 Level: intermediate 4587 4588 .keywords: TS, get, number, linear, iterations 4589 4590 .seealso: TSGetSNESIterations(), SNESGetKSPIterations() 4591 @*/ 4592 PetscErrorCode TSGetKSPIterations(TS ts,PetscInt *lits) 4593 { 4594 PetscFunctionBegin; 4595 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4596 PetscValidIntPointer(lits,2); 4597 *lits = ts->ksp_its; 4598 PetscFunctionReturn(0); 4599 } 4600 4601 #undef __FUNCT__ 4602 #define __FUNCT__ "TSGetStepRejections" 4603 /*@ 4604 TSGetStepRejections - Gets the total number of rejected steps. 4605 4606 Not Collective 4607 4608 Input Parameter: 4609 . ts - TS context 4610 4611 Output Parameter: 4612 . rejects - number of steps rejected 4613 4614 Notes: 4615 This counter is reset to zero for each successive call to TSSolve(). 4616 4617 Level: intermediate 4618 4619 .keywords: TS, get, number 4620 4621 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetSNESFailures(), TSSetMaxSNESFailures(), TSSetErrorIfStepFails() 4622 @*/ 4623 PetscErrorCode TSGetStepRejections(TS ts,PetscInt *rejects) 4624 { 4625 PetscFunctionBegin; 4626 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4627 PetscValidIntPointer(rejects,2); 4628 *rejects = ts->reject; 4629 PetscFunctionReturn(0); 4630 } 4631 4632 #undef __FUNCT__ 4633 #define __FUNCT__ "TSGetSNESFailures" 4634 /*@ 4635 TSGetSNESFailures - Gets the total number of failed SNES solves 4636 4637 Not Collective 4638 4639 Input Parameter: 4640 . ts - TS context 4641 4642 Output Parameter: 4643 . fails - number of failed nonlinear solves 4644 4645 Notes: 4646 This counter is reset to zero for each successive call to TSSolve(). 4647 4648 Level: intermediate 4649 4650 .keywords: TS, get, number 4651 4652 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSSetMaxSNESFailures() 4653 @*/ 4654 PetscErrorCode TSGetSNESFailures(TS ts,PetscInt *fails) 4655 { 4656 PetscFunctionBegin; 4657 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4658 PetscValidIntPointer(fails,2); 4659 *fails = ts->num_snes_failures; 4660 PetscFunctionReturn(0); 4661 } 4662 4663 #undef __FUNCT__ 4664 #define __FUNCT__ "TSSetMaxStepRejections" 4665 /*@ 4666 TSSetMaxStepRejections - Sets the maximum number of step rejections before a step fails 4667 4668 Not Collective 4669 4670 Input Parameter: 4671 + ts - TS context 4672 - rejects - maximum number of rejected steps, pass -1 for unlimited 4673 4674 Notes: 4675 The counter is reset to zero for each step 4676 4677 Options Database Key: 4678 . -ts_max_reject - Maximum number of step rejections before a step fails 4679 4680 Level: intermediate 4681 4682 .keywords: TS, set, maximum, number 4683 4684 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxSNESFailures(), TSGetStepRejections(), TSGetSNESFailures(), TSSetErrorIfStepFails(), TSGetConvergedReason() 4685 @*/ 4686 PetscErrorCode TSSetMaxStepRejections(TS ts,PetscInt rejects) 4687 { 4688 PetscFunctionBegin; 4689 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4690 ts->max_reject = rejects; 4691 PetscFunctionReturn(0); 4692 } 4693 4694 #undef __FUNCT__ 4695 #define __FUNCT__ "TSSetMaxSNESFailures" 4696 /*@ 4697 TSSetMaxSNESFailures - Sets the maximum number of failed SNES solves 4698 4699 Not Collective 4700 4701 Input Parameter: 4702 + ts - TS context 4703 - fails - maximum number of failed nonlinear solves, pass -1 for unlimited 4704 4705 Notes: 4706 The counter is reset to zero for each successive call to TSSolve(). 4707 4708 Options Database Key: 4709 . -ts_max_snes_failures - Maximum number of nonlinear solve failures 4710 4711 Level: intermediate 4712 4713 .keywords: TS, set, maximum, number 4714 4715 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSGetSNESFailures(), SNESGetConvergedReason(), TSGetConvergedReason() 4716 @*/ 4717 PetscErrorCode TSSetMaxSNESFailures(TS ts,PetscInt fails) 4718 { 4719 PetscFunctionBegin; 4720 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4721 ts->max_snes_failures = fails; 4722 PetscFunctionReturn(0); 4723 } 4724 4725 #undef __FUNCT__ 4726 #define __FUNCT__ "TSSetErrorIfStepFails" 4727 /*@ 4728 TSSetErrorIfStepFails - Error if no step succeeds 4729 4730 Not Collective 4731 4732 Input Parameter: 4733 + ts - TS context 4734 - err - PETSC_TRUE to error if no step succeeds, PETSC_FALSE to return without failure 4735 4736 Options Database Key: 4737 . -ts_error_if_step_fails - Error if no step succeeds 4738 4739 Level: intermediate 4740 4741 .keywords: TS, set, error 4742 4743 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSGetSNESFailures(), TSSetErrorIfStepFails(), TSGetConvergedReason() 4744 @*/ 4745 PetscErrorCode TSSetErrorIfStepFails(TS ts,PetscBool err) 4746 { 4747 PetscFunctionBegin; 4748 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4749 ts->errorifstepfailed = err; 4750 PetscFunctionReturn(0); 4751 } 4752 4753 #undef __FUNCT__ 4754 #define __FUNCT__ "TSMonitorSolutionBinary" 4755 /*@C 4756 TSMonitorSolutionBinary - Monitors progress of the TS solvers by VecView() for the solution at each timestep. Normally the viewer is a binary file 4757 4758 Collective on TS 4759 4760 Input Parameters: 4761 + ts - the TS context 4762 . step - current time-step 4763 . ptime - current time 4764 . u - current state 4765 - viewer - binary viewer 4766 4767 Level: intermediate 4768 4769 .keywords: TS, vector, monitor, view 4770 4771 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 4772 @*/ 4773 PetscErrorCode TSMonitorSolutionBinary(TS ts,PetscInt step,PetscReal ptime,Vec u,void *viewer) 4774 { 4775 PetscErrorCode ierr; 4776 PetscViewer v = (PetscViewer)viewer; 4777 4778 PetscFunctionBegin; 4779 ierr = VecView(u,v);CHKERRQ(ierr); 4780 PetscFunctionReturn(0); 4781 } 4782 4783 #undef __FUNCT__ 4784 #define __FUNCT__ "TSMonitorSolutionVTK" 4785 /*@C 4786 TSMonitorSolutionVTK - Monitors progress of the TS solvers by VecView() for the solution at each timestep. 4787 4788 Collective on TS 4789 4790 Input Parameters: 4791 + ts - the TS context 4792 . step - current time-step 4793 . ptime - current time 4794 . u - current state 4795 - filenametemplate - string containing a format specifier for the integer time step (e.g. %03D) 4796 4797 Level: intermediate 4798 4799 Notes: 4800 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. 4801 These are named according to the file name template. 4802 4803 This function is normally passed as an argument to TSMonitorSet() along with TSMonitorSolutionVTKDestroy(). 4804 4805 .keywords: TS, vector, monitor, view 4806 4807 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 4808 @*/ 4809 PetscErrorCode TSMonitorSolutionVTK(TS ts,PetscInt step,PetscReal ptime,Vec u,void *filenametemplate) 4810 { 4811 PetscErrorCode ierr; 4812 char filename[PETSC_MAX_PATH_LEN]; 4813 PetscViewer viewer; 4814 4815 PetscFunctionBegin; 4816 ierr = PetscSNPrintf(filename,sizeof(filename),(const char*)filenametemplate,step);CHKERRQ(ierr); 4817 ierr = PetscViewerVTKOpen(PetscObjectComm((PetscObject)ts),filename,FILE_MODE_WRITE,&viewer);CHKERRQ(ierr); 4818 ierr = VecView(u,viewer);CHKERRQ(ierr); 4819 ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr); 4820 PetscFunctionReturn(0); 4821 } 4822 4823 #undef __FUNCT__ 4824 #define __FUNCT__ "TSMonitorSolutionVTKDestroy" 4825 /*@C 4826 TSMonitorSolutionVTKDestroy - Destroy context for monitoring 4827 4828 Collective on TS 4829 4830 Input Parameters: 4831 . filenametemplate - string containing a format specifier for the integer time step (e.g. %03D) 4832 4833 Level: intermediate 4834 4835 Note: 4836 This function is normally passed to TSMonitorSet() along with TSMonitorSolutionVTK(). 4837 4838 .keywords: TS, vector, monitor, view 4839 4840 .seealso: TSMonitorSet(), TSMonitorSolutionVTK() 4841 @*/ 4842 PetscErrorCode TSMonitorSolutionVTKDestroy(void *filenametemplate) 4843 { 4844 PetscErrorCode ierr; 4845 4846 PetscFunctionBegin; 4847 ierr = PetscFree(*(char**)filenametemplate);CHKERRQ(ierr); 4848 PetscFunctionReturn(0); 4849 } 4850 4851 #undef __FUNCT__ 4852 #define __FUNCT__ "TSGetAdapt" 4853 /*@ 4854 TSGetAdapt - Get the adaptive controller context for the current method 4855 4856 Collective on TS if controller has not been created yet 4857 4858 Input Arguments: 4859 . ts - time stepping context 4860 4861 Output Arguments: 4862 . adapt - adaptive controller 4863 4864 Level: intermediate 4865 4866 .seealso: TSAdapt, TSAdaptSetType(), TSAdaptChoose() 4867 @*/ 4868 PetscErrorCode TSGetAdapt(TS ts,TSAdapt *adapt) 4869 { 4870 PetscErrorCode ierr; 4871 4872 PetscFunctionBegin; 4873 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4874 PetscValidPointer(adapt,2); 4875 if (!ts->adapt) { 4876 ierr = TSAdaptCreate(PetscObjectComm((PetscObject)ts),&ts->adapt);CHKERRQ(ierr); 4877 ierr = PetscLogObjectParent((PetscObject)ts,(PetscObject)ts->adapt);CHKERRQ(ierr); 4878 ierr = PetscObjectIncrementTabLevel((PetscObject)ts->adapt,(PetscObject)ts,1);CHKERRQ(ierr); 4879 } 4880 *adapt = ts->adapt; 4881 PetscFunctionReturn(0); 4882 } 4883 4884 #undef __FUNCT__ 4885 #define __FUNCT__ "TSSetTolerances" 4886 /*@ 4887 TSSetTolerances - Set tolerances for local truncation error when using adaptive controller 4888 4889 Logically Collective 4890 4891 Input Arguments: 4892 + ts - time integration context 4893 . atol - scalar absolute tolerances, PETSC_DECIDE to leave current value 4894 . vatol - vector of absolute tolerances or NULL, used in preference to atol if present 4895 . rtol - scalar relative tolerances, PETSC_DECIDE to leave current value 4896 - vrtol - vector of relative tolerances or NULL, used in preference to atol if present 4897 4898 Options Database keys: 4899 + -ts_rtol <rtol> - relative tolerance for local truncation error 4900 - -ts_atol <atol> Absolute tolerance for local truncation error 4901 4902 Level: beginner 4903 4904 .seealso: TS, TSAdapt, TSVecNormWRMS(), TSGetTolerances() 4905 @*/ 4906 PetscErrorCode TSSetTolerances(TS ts,PetscReal atol,Vec vatol,PetscReal rtol,Vec vrtol) 4907 { 4908 PetscErrorCode ierr; 4909 4910 PetscFunctionBegin; 4911 if (atol != PETSC_DECIDE && atol != PETSC_DEFAULT) ts->atol = atol; 4912 if (vatol) { 4913 ierr = PetscObjectReference((PetscObject)vatol);CHKERRQ(ierr); 4914 ierr = VecDestroy(&ts->vatol);CHKERRQ(ierr); 4915 4916 ts->vatol = vatol; 4917 } 4918 if (rtol != PETSC_DECIDE && rtol != PETSC_DEFAULT) ts->rtol = rtol; 4919 if (vrtol) { 4920 ierr = PetscObjectReference((PetscObject)vrtol);CHKERRQ(ierr); 4921 ierr = VecDestroy(&ts->vrtol);CHKERRQ(ierr); 4922 4923 ts->vrtol = vrtol; 4924 } 4925 PetscFunctionReturn(0); 4926 } 4927 4928 #undef __FUNCT__ 4929 #define __FUNCT__ "TSGetTolerances" 4930 /*@ 4931 TSGetTolerances - Get tolerances for local truncation error when using adaptive controller 4932 4933 Logically Collective 4934 4935 Input Arguments: 4936 . ts - time integration context 4937 4938 Output Arguments: 4939 + atol - scalar absolute tolerances, NULL to ignore 4940 . vatol - vector of absolute tolerances, NULL to ignore 4941 . rtol - scalar relative tolerances, NULL to ignore 4942 - vrtol - vector of relative tolerances, NULL to ignore 4943 4944 Level: beginner 4945 4946 .seealso: TS, TSAdapt, TSVecNormWRMS(), TSSetTolerances() 4947 @*/ 4948 PetscErrorCode TSGetTolerances(TS ts,PetscReal *atol,Vec *vatol,PetscReal *rtol,Vec *vrtol) 4949 { 4950 PetscFunctionBegin; 4951 if (atol) *atol = ts->atol; 4952 if (vatol) *vatol = ts->vatol; 4953 if (rtol) *rtol = ts->rtol; 4954 if (vrtol) *vrtol = ts->vrtol; 4955 PetscFunctionReturn(0); 4956 } 4957 4958 #undef __FUNCT__ 4959 #define __FUNCT__ "TSSetDifferentialEquationsIS" 4960 /*@ 4961 TSSetDifferentialEquationsIS - Sets an IS containing locations of differential equations in a DAE 4962 4963 Not Collective 4964 4965 Input Arguments: 4966 + ts - time stepping context 4967 - is_diff - Index set for differential equations 4968 4969 Level: advanced 4970 4971 @*/ 4972 PetscErrorCode TSSetDifferentialEquationsIS(TS ts, IS is_diff) 4973 { 4974 PetscErrorCode ierr; 4975 4976 PetscFunctionBegin; 4977 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4978 PetscValidHeaderSpecific(is_diff,IS_CLASSID,2); 4979 PetscCheckSameComm(ts,1,is_diff,2); 4980 ierr = PetscObjectReference((PetscObject)is_diff);CHKERRQ(ierr); 4981 ierr = ISDestroy(&ts->is_diff);CHKERRQ(ierr); 4982 ts->is_diff = is_diff; 4983 PetscFunctionReturn(0); 4984 } 4985 4986 #undef __FUNCT__ 4987 #define __FUNCT__ "TSErrorWeightedNorm2" 4988 /*@ 4989 TSErrorWeightedNorm2 - compute a weighted 2-norm of the difference between a vector and the current state 4990 4991 Collective on TS 4992 4993 Input Arguments: 4994 + ts - time stepping context 4995 - Y - state vector to be compared to ts->vec_sol 4996 4997 Output Arguments: 4998 . norm - weighted norm, a value of 1.0 is considered small 4999 5000 Level: developer 5001 5002 .seealso: TSErrorWeightedNorm(), TSErrorWeightedNormInfinity() 5003 @*/ 5004 PetscErrorCode TSErrorWeightedNorm2(TS ts,Vec Y,PetscReal *norm) 5005 { 5006 PetscErrorCode ierr; 5007 PetscInt i,n,N,rstart; 5008 const PetscScalar *u,*y; 5009 Vec U; 5010 PetscReal sum,gsum; 5011 PetscReal tol; 5012 5013 PetscFunctionBegin; 5014 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5015 PetscValidHeaderSpecific(Y,VEC_CLASSID,2); 5016 PetscValidPointer(norm,3); 5017 U = ts->vec_sol; 5018 PetscCheckSameTypeAndComm(U,1,Y,2); 5019 if (U == Y) SETERRQ(PetscObjectComm((PetscObject)U),PETSC_ERR_ARG_IDN,"Y cannot be the TS solution vector"); 5020 5021 ierr = VecGetSize(U,&N);CHKERRQ(ierr); 5022 ierr = VecGetLocalSize(U,&n);CHKERRQ(ierr); 5023 ierr = VecGetOwnershipRange(U,&rstart,NULL);CHKERRQ(ierr); 5024 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 5025 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 5026 sum = 0.; 5027 if (ts->vatol && ts->vrtol) { 5028 const PetscScalar *atol,*rtol; 5029 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5030 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5031 if(ts->is_diff) { 5032 const PetscInt *idx; 5033 PetscInt k; 5034 ierr = ISGetIndices(ts->is_diff,&idx);CHKERRQ(ierr); 5035 ierr = ISGetLocalSize(ts->is_diff,&n);CHKERRQ(ierr); 5036 for(i=0; i < n; i++) { 5037 k = idx[i] - rstart; 5038 tol = PetscRealPart(atol[k]) + PetscRealPart(rtol[k])*PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5039 sum += PetscSqr(PetscAbsScalar(y[k] - u[k]) / tol); 5040 } 5041 ierr = ISRestoreIndices(ts->is_diff,&idx);CHKERRQ(ierr); 5042 } else { 5043 for (i=0; i<n; i++) { 5044 tol = PetscRealPart(atol[i]) + PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5045 sum += PetscSqr(PetscAbsScalar(y[i] - u[i]) / tol); 5046 } 5047 } 5048 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5049 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5050 } else if (ts->vatol) { /* vector atol, scalar rtol */ 5051 const PetscScalar *atol; 5052 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5053 if(ts->is_diff) { 5054 const PetscInt *idx; 5055 PetscInt k; 5056 ierr = ISGetIndices(ts->is_diff,&idx);CHKERRQ(ierr); 5057 ierr = ISGetLocalSize(ts->is_diff,&n);CHKERRQ(ierr); 5058 for(i=0; i < n; i++) { 5059 k = idx[i] - rstart; 5060 tol = PetscRealPart(atol[k]) + ts->rtol * PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5061 sum += PetscSqr(PetscAbsScalar(y[k] - u[k]) / tol); 5062 } 5063 ierr = ISRestoreIndices(ts->is_diff,&idx);CHKERRQ(ierr); 5064 } else { 5065 for (i=0; i<n; i++) { 5066 tol = PetscRealPart(atol[i]) + ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5067 sum += PetscSqr(PetscAbsScalar(y[i] - u[i]) / tol); 5068 } 5069 } 5070 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5071 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 5072 const PetscScalar *rtol; 5073 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5074 if(ts->is_diff) { 5075 const PetscInt *idx; 5076 PetscInt k; 5077 ierr = ISGetIndices(ts->is_diff,&idx);CHKERRQ(ierr); 5078 ierr = ISGetLocalSize(ts->is_diff,&n);CHKERRQ(ierr); 5079 for(i=0; i < n; i++) { 5080 k = idx[i] - rstart; 5081 tol = ts->atol + PetscRealPart(rtol[k]) * PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5082 sum += PetscSqr(PetscAbsScalar(y[k] - u[k]) / tol); 5083 } 5084 ierr = ISRestoreIndices(ts->is_diff,&idx);CHKERRQ(ierr); 5085 } else { 5086 for (i=0; i<n; i++) { 5087 tol = ts->atol + PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5088 sum += PetscSqr(PetscAbsScalar(y[i] - u[i]) / tol); 5089 } 5090 } 5091 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5092 } else { /* scalar atol, scalar rtol */ 5093 if (ts->is_diff) { 5094 const PetscInt *idx; 5095 PetscInt k; 5096 ierr = ISGetIndices(ts->is_diff,&idx);CHKERRQ(ierr); 5097 ierr = ISGetLocalSize(ts->is_diff,&n);CHKERRQ(ierr); 5098 for (i=0; i<n; i++) { 5099 k = idx[i] - rstart; 5100 tol = ts->atol + ts->rtol * PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5101 sum += PetscSqr(PetscAbsScalar(y[k] - u[k]) / tol); 5102 } 5103 } else { 5104 for (i=0; i<n; i++) { 5105 tol = ts->atol + ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5106 sum += PetscSqr(PetscAbsScalar(y[i] - u[i]) / tol); 5107 } 5108 } 5109 } 5110 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 5111 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 5112 5113 ierr = MPI_Allreduce(&sum,&gsum,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 5114 *norm = PetscSqrtReal(gsum / N); 5115 5116 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 5117 PetscFunctionReturn(0); 5118 } 5119 5120 #undef __FUNCT__ 5121 #define __FUNCT__ "TSErrorWeightedNormInfinity" 5122 /*@ 5123 TSErrorWeightedNormInfinity - compute a weighted infinity-norm of the difference between a vector and the current state 5124 5125 Collective on TS 5126 5127 Input Arguments: 5128 + ts - time stepping context 5129 - Y - state vector to be compared to ts->vec_sol 5130 5131 Output Arguments: 5132 . norm - weighted norm, a value of 1.0 is considered small 5133 5134 Level: developer 5135 5136 .seealso: TSErrorWeightedNorm(), TSErrorWeightedNorm2() 5137 @*/ 5138 PetscErrorCode TSErrorWeightedNormInfinity(TS ts,Vec Y,PetscReal *norm) 5139 { 5140 PetscErrorCode ierr; 5141 PetscInt i,n,N,rstart,k; 5142 const PetscScalar *u,*y; 5143 Vec U; 5144 PetscReal max,gmax; 5145 PetscReal tol; 5146 5147 PetscFunctionBegin; 5148 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5149 PetscValidHeaderSpecific(Y,VEC_CLASSID,2); 5150 PetscValidPointer(norm,3); 5151 U = ts->vec_sol; 5152 PetscCheckSameTypeAndComm(U,1,Y,2); 5153 if (U == Y) SETERRQ(PetscObjectComm((PetscObject)U),PETSC_ERR_ARG_IDN,"Y cannot be the TS solution vector"); 5154 5155 ierr = VecGetSize(U,&N);CHKERRQ(ierr); 5156 ierr = VecGetLocalSize(U,&n);CHKERRQ(ierr); 5157 ierr = VecGetOwnershipRange(U,&rstart,NULL);CHKERRQ(ierr); 5158 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 5159 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 5160 if (ts->vatol && ts->vrtol) { 5161 const PetscScalar *atol,*rtol; 5162 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5163 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5164 if(ts->is_diff) { 5165 const PetscInt *idx; 5166 ierr = ISGetIndices(ts->is_diff,&idx);CHKERRQ(ierr); 5167 ierr = ISGetLocalSize(ts->is_diff,&n);CHKERRQ(ierr); 5168 5169 k = idx[0]; 5170 tol = PetscRealPart(atol[k]) + PetscRealPart(rtol[k]) * PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5171 max = PetscAbsScalar(y[k] - u[k]) / tol; 5172 for(i=1; i < n; i++) { 5173 k = idx[i] - rstart; 5174 tol = PetscRealPart(atol[k]) + PetscRealPart(rtol[k])*PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5175 max = PetscMax(max,PetscAbsScalar(y[k] - u[k]) / tol); 5176 } 5177 ierr = ISRestoreIndices(ts->is_diff,&idx);CHKERRQ(ierr); 5178 } else { 5179 k = 0; 5180 tol = PetscRealPart(atol[k]) + PetscRealPart(rtol[k]) * PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5181 max = PetscAbsScalar(y[k] - u[k]) / tol; 5182 for (i=1; i<n; i++) { 5183 tol = PetscRealPart(atol[i]) + PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5184 max = PetscMax(max,PetscAbsScalar(y[i] - u[i]) / tol); 5185 } 5186 } 5187 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5188 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5189 } else if (ts->vatol) { /* vector atol, scalar rtol */ 5190 const PetscScalar *atol; 5191 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5192 if(ts->is_diff) { 5193 const PetscInt *idx; 5194 ierr = ISGetIndices(ts->is_diff,&idx);CHKERRQ(ierr); 5195 ierr = ISGetLocalSize(ts->is_diff,&n);CHKERRQ(ierr); 5196 5197 k = idx[0]; 5198 tol = PetscRealPart(atol[k]) + ts->rtol * PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5199 max = PetscAbsScalar(y[k] - u[k]) / tol; 5200 for(i=1; i < n; i++) { 5201 k = idx[i] - rstart; 5202 tol = PetscRealPart(atol[k]) + ts->rtol * PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5203 max = PetscMax(max,PetscAbsScalar(y[k] - u[k]) / tol); 5204 } 5205 ierr = ISRestoreIndices(ts->is_diff,&idx);CHKERRQ(ierr); 5206 } else { 5207 k = 0; 5208 tol = PetscRealPart(atol[k]) + ts->rtol * PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5209 max = PetscAbsScalar(y[k] - u[k]) / tol; 5210 for (i=1; i<n; i++) { 5211 tol = PetscRealPart(atol[i]) + ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5212 max = PetscMax(max,PetscAbsScalar(y[i] - u[i]) / tol); 5213 } 5214 } 5215 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5216 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 5217 const PetscScalar *rtol; 5218 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5219 if(ts->is_diff) { 5220 const PetscInt *idx; 5221 ierr = ISGetIndices(ts->is_diff,&idx);CHKERRQ(ierr); 5222 ierr = ISGetLocalSize(ts->is_diff,&n);CHKERRQ(ierr); 5223 5224 k = idx[0]; 5225 tol = ts->atol + PetscRealPart(rtol[k])*PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5226 max = PetscAbsScalar(y[k] - u[k]) / tol; 5227 for(i=1; i < n; i++) { 5228 k = idx[i] - rstart; 5229 tol = ts->atol + PetscRealPart(rtol[k]) * PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5230 max = PetscMax(max,PetscAbsScalar(y[k] - u[k]) / tol); 5231 } 5232 ierr = ISRestoreIndices(ts->is_diff,&idx);CHKERRQ(ierr); 5233 } else { 5234 k = 0; 5235 tol = ts->atol + PetscRealPart(rtol[k]) * PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5236 max = PetscAbsScalar(y[k] - u[k]) / tol; 5237 for (i=1; i<n; i++) { 5238 tol = ts->atol + PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5239 max = PetscMax(max,PetscAbsScalar(y[i] - u[i]) / tol); 5240 } 5241 } 5242 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5243 } else { /* scalar atol, scalar rtol */ 5244 if (ts->is_diff) { 5245 const PetscInt *idx; 5246 ierr = ISGetIndices(ts->is_diff,&idx);CHKERRQ(ierr); 5247 ierr = ISGetLocalSize(ts->is_diff,&n);CHKERRQ(ierr); 5248 5249 k = idx[0]; 5250 tol = ts->atol + ts->rtol * PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5251 max = PetscAbsScalar(y[k] - u[k]) / tol; 5252 for (i=1; i<n; i++) { 5253 k = idx[i] - rstart; 5254 tol = ts->atol + ts->rtol * PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5255 max = PetscMax(max,PetscAbsScalar(y[k] - u[k]) / tol); 5256 } 5257 ierr = ISRestoreIndices(ts->is_diff,&idx);CHKERRQ(ierr); 5258 } else { 5259 k = 0; 5260 tol = ts->atol + ts->rtol * PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5261 max = PetscAbsScalar(y[k] - u[k]) / tol; 5262 for (i=1; i<n; i++) { 5263 tol = ts->atol + ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5264 max = PetscMax(max,PetscAbsScalar(y[i] - u[i]) / tol); 5265 } 5266 } 5267 } 5268 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 5269 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 5270 5271 ierr = MPI_Allreduce(&max,&gmax,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 5272 *norm = gmax; 5273 5274 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 5275 PetscFunctionReturn(0); 5276 } 5277 5278 #undef __FUNCT__ 5279 #define __FUNCT__ "TSErrorWeightedNorm" 5280 /*@ 5281 TSErrorWeightedNorm - compute a weighted norm of the difference between a vector and the current state 5282 5283 Collective on TS 5284 5285 Input Arguments: 5286 + ts - time stepping context 5287 - Y - state vector to be compared to ts->vec_sol 5288 5289 Options Database Keys: 5290 . -ts_adapt_wnormtype <wnormtype> - 2, INFINITY 5291 5292 Output Arguments: 5293 . norm - weighted norm, a value of 1.0 is considered small 5294 5295 Level: developer 5296 5297 .seealso: TSErrorWeightedNormInfinity(), TSErrorWeightedNorm2() 5298 @*/ 5299 PetscErrorCode TSErrorWeightedNorm(TS ts,Vec Y,PetscReal *norm) 5300 { 5301 5302 PetscFunctionBegin; 5303 5304 if(ts->adapt->wnormtype == NORM_2) { 5305 PetscErrorCode ierr; 5306 ierr = TSErrorWeightedNorm2(ts,Y,norm); 5307 } else if(ts->adapt->wnormtype == NORM_INFINITY) { 5308 PetscErrorCode ierr; 5309 ierr = TSErrorWeightedNormInfinity(ts,Y,norm); 5310 } 5311 5312 PetscFunctionReturn(0); 5313 } 5314 5315 5316 #undef __FUNCT__ 5317 #define __FUNCT__ "TSSetCFLTimeLocal" 5318 /*@ 5319 TSSetCFLTimeLocal - Set the local CFL constraint relative to forward Euler 5320 5321 Logically Collective on TS 5322 5323 Input Arguments: 5324 + ts - time stepping context 5325 - cfltime - maximum stable time step if using forward Euler (value can be different on each process) 5326 5327 Note: 5328 After calling this function, the global CFL time can be obtained by calling TSGetCFLTime() 5329 5330 Level: intermediate 5331 5332 .seealso: TSGetCFLTime(), TSADAPTCFL 5333 @*/ 5334 PetscErrorCode TSSetCFLTimeLocal(TS ts,PetscReal cfltime) 5335 { 5336 PetscFunctionBegin; 5337 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5338 ts->cfltime_local = cfltime; 5339 ts->cfltime = -1.; 5340 PetscFunctionReturn(0); 5341 } 5342 5343 #undef __FUNCT__ 5344 #define __FUNCT__ "TSGetCFLTime" 5345 /*@ 5346 TSGetCFLTime - Get the maximum stable time step according to CFL criteria applied to forward Euler 5347 5348 Collective on TS 5349 5350 Input Arguments: 5351 . ts - time stepping context 5352 5353 Output Arguments: 5354 . cfltime - maximum stable time step for forward Euler 5355 5356 Level: advanced 5357 5358 .seealso: TSSetCFLTimeLocal() 5359 @*/ 5360 PetscErrorCode TSGetCFLTime(TS ts,PetscReal *cfltime) 5361 { 5362 PetscErrorCode ierr; 5363 5364 PetscFunctionBegin; 5365 if (ts->cfltime < 0) { 5366 ierr = MPI_Allreduce(&ts->cfltime_local,&ts->cfltime,1,MPIU_REAL,MPIU_MIN,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 5367 } 5368 *cfltime = ts->cfltime; 5369 PetscFunctionReturn(0); 5370 } 5371 5372 #undef __FUNCT__ 5373 #define __FUNCT__ "TSVISetVariableBounds" 5374 /*@ 5375 TSVISetVariableBounds - Sets the lower and upper bounds for the solution vector. xl <= x <= xu 5376 5377 Input Parameters: 5378 . ts - the TS context. 5379 . xl - lower bound. 5380 . xu - upper bound. 5381 5382 Notes: 5383 If this routine is not called then the lower and upper bounds are set to 5384 PETSC_NINFINITY and PETSC_INFINITY respectively during SNESSetUp(). 5385 5386 Level: advanced 5387 5388 @*/ 5389 PetscErrorCode TSVISetVariableBounds(TS ts, Vec xl, Vec xu) 5390 { 5391 PetscErrorCode ierr; 5392 SNES snes; 5393 5394 PetscFunctionBegin; 5395 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 5396 ierr = SNESVISetVariableBounds(snes,xl,xu);CHKERRQ(ierr); 5397 PetscFunctionReturn(0); 5398 } 5399 5400 #if defined(PETSC_HAVE_MATLAB_ENGINE) 5401 #include <mex.h> 5402 5403 typedef struct {char *funcname; mxArray *ctx;} TSMatlabContext; 5404 5405 #undef __FUNCT__ 5406 #define __FUNCT__ "TSComputeFunction_Matlab" 5407 /* 5408 TSComputeFunction_Matlab - Calls the function that has been set with 5409 TSSetFunctionMatlab(). 5410 5411 Collective on TS 5412 5413 Input Parameters: 5414 + snes - the TS context 5415 - u - input vector 5416 5417 Output Parameter: 5418 . y - function vector, as set by TSSetFunction() 5419 5420 Notes: 5421 TSComputeFunction() is typically used within nonlinear solvers 5422 implementations, so most users would not generally call this routine 5423 themselves. 5424 5425 Level: developer 5426 5427 .keywords: TS, nonlinear, compute, function 5428 5429 .seealso: TSSetFunction(), TSGetFunction() 5430 */ 5431 PetscErrorCode TSComputeFunction_Matlab(TS snes,PetscReal time,Vec u,Vec udot,Vec y, void *ctx) 5432 { 5433 PetscErrorCode ierr; 5434 TSMatlabContext *sctx = (TSMatlabContext*)ctx; 5435 int nlhs = 1,nrhs = 7; 5436 mxArray *plhs[1],*prhs[7]; 5437 long long int lx = 0,lxdot = 0,ly = 0,ls = 0; 5438 5439 PetscFunctionBegin; 5440 PetscValidHeaderSpecific(snes,TS_CLASSID,1); 5441 PetscValidHeaderSpecific(u,VEC_CLASSID,3); 5442 PetscValidHeaderSpecific(udot,VEC_CLASSID,4); 5443 PetscValidHeaderSpecific(y,VEC_CLASSID,5); 5444 PetscCheckSameComm(snes,1,u,3); 5445 PetscCheckSameComm(snes,1,y,5); 5446 5447 ierr = PetscMemcpy(&ls,&snes,sizeof(snes));CHKERRQ(ierr); 5448 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 5449 ierr = PetscMemcpy(&lxdot,&udot,sizeof(udot));CHKERRQ(ierr); 5450 ierr = PetscMemcpy(&ly,&y,sizeof(u));CHKERRQ(ierr); 5451 5452 prhs[0] = mxCreateDoubleScalar((double)ls); 5453 prhs[1] = mxCreateDoubleScalar(time); 5454 prhs[2] = mxCreateDoubleScalar((double)lx); 5455 prhs[3] = mxCreateDoubleScalar((double)lxdot); 5456 prhs[4] = mxCreateDoubleScalar((double)ly); 5457 prhs[5] = mxCreateString(sctx->funcname); 5458 prhs[6] = sctx->ctx; 5459 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSComputeFunctionInternal");CHKERRQ(ierr); 5460 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 5461 mxDestroyArray(prhs[0]); 5462 mxDestroyArray(prhs[1]); 5463 mxDestroyArray(prhs[2]); 5464 mxDestroyArray(prhs[3]); 5465 mxDestroyArray(prhs[4]); 5466 mxDestroyArray(prhs[5]); 5467 mxDestroyArray(plhs[0]); 5468 PetscFunctionReturn(0); 5469 } 5470 5471 5472 #undef __FUNCT__ 5473 #define __FUNCT__ "TSSetFunctionMatlab" 5474 /* 5475 TSSetFunctionMatlab - Sets the function evaluation routine and function 5476 vector for use by the TS routines in solving ODEs 5477 equations from MATLAB. Here the function is a string containing the name of a MATLAB function 5478 5479 Logically Collective on TS 5480 5481 Input Parameters: 5482 + ts - the TS context 5483 - func - function evaluation routine 5484 5485 Calling sequence of func: 5486 $ func (TS ts,PetscReal time,Vec u,Vec udot,Vec f,void *ctx); 5487 5488 Level: beginner 5489 5490 .keywords: TS, nonlinear, set, function 5491 5492 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 5493 */ 5494 PetscErrorCode TSSetFunctionMatlab(TS ts,const char *func,mxArray *ctx) 5495 { 5496 PetscErrorCode ierr; 5497 TSMatlabContext *sctx; 5498 5499 PetscFunctionBegin; 5500 /* currently sctx is memory bleed */ 5501 ierr = PetscMalloc(sizeof(TSMatlabContext),&sctx);CHKERRQ(ierr); 5502 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 5503 /* 5504 This should work, but it doesn't 5505 sctx->ctx = ctx; 5506 mexMakeArrayPersistent(sctx->ctx); 5507 */ 5508 sctx->ctx = mxDuplicateArray(ctx); 5509 5510 ierr = TSSetIFunction(ts,NULL,TSComputeFunction_Matlab,sctx);CHKERRQ(ierr); 5511 PetscFunctionReturn(0); 5512 } 5513 5514 #undef __FUNCT__ 5515 #define __FUNCT__ "TSComputeJacobian_Matlab" 5516 /* 5517 TSComputeJacobian_Matlab - Calls the function that has been set with 5518 TSSetJacobianMatlab(). 5519 5520 Collective on TS 5521 5522 Input Parameters: 5523 + ts - the TS context 5524 . u - input vector 5525 . A, B - the matrices 5526 - ctx - user context 5527 5528 Level: developer 5529 5530 .keywords: TS, nonlinear, compute, function 5531 5532 .seealso: TSSetFunction(), TSGetFunction() 5533 @*/ 5534 PetscErrorCode TSComputeJacobian_Matlab(TS ts,PetscReal time,Vec u,Vec udot,PetscReal shift,Mat A,Mat B,void *ctx) 5535 { 5536 PetscErrorCode ierr; 5537 TSMatlabContext *sctx = (TSMatlabContext*)ctx; 5538 int nlhs = 2,nrhs = 9; 5539 mxArray *plhs[2],*prhs[9]; 5540 long long int lx = 0,lxdot = 0,lA = 0,ls = 0, lB = 0; 5541 5542 PetscFunctionBegin; 5543 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5544 PetscValidHeaderSpecific(u,VEC_CLASSID,3); 5545 5546 /* call Matlab function in ctx with arguments u and y */ 5547 5548 ierr = PetscMemcpy(&ls,&ts,sizeof(ts));CHKERRQ(ierr); 5549 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 5550 ierr = PetscMemcpy(&lxdot,&udot,sizeof(u));CHKERRQ(ierr); 5551 ierr = PetscMemcpy(&lA,A,sizeof(u));CHKERRQ(ierr); 5552 ierr = PetscMemcpy(&lB,B,sizeof(u));CHKERRQ(ierr); 5553 5554 prhs[0] = mxCreateDoubleScalar((double)ls); 5555 prhs[1] = mxCreateDoubleScalar((double)time); 5556 prhs[2] = mxCreateDoubleScalar((double)lx); 5557 prhs[3] = mxCreateDoubleScalar((double)lxdot); 5558 prhs[4] = mxCreateDoubleScalar((double)shift); 5559 prhs[5] = mxCreateDoubleScalar((double)lA); 5560 prhs[6] = mxCreateDoubleScalar((double)lB); 5561 prhs[7] = mxCreateString(sctx->funcname); 5562 prhs[8] = sctx->ctx; 5563 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSComputeJacobianInternal");CHKERRQ(ierr); 5564 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 5565 mxDestroyArray(prhs[0]); 5566 mxDestroyArray(prhs[1]); 5567 mxDestroyArray(prhs[2]); 5568 mxDestroyArray(prhs[3]); 5569 mxDestroyArray(prhs[4]); 5570 mxDestroyArray(prhs[5]); 5571 mxDestroyArray(prhs[6]); 5572 mxDestroyArray(prhs[7]); 5573 mxDestroyArray(plhs[0]); 5574 mxDestroyArray(plhs[1]); 5575 PetscFunctionReturn(0); 5576 } 5577 5578 5579 #undef __FUNCT__ 5580 #define __FUNCT__ "TSSetJacobianMatlab" 5581 /* 5582 TSSetJacobianMatlab - Sets the Jacobian function evaluation routine and two empty Jacobian matrices 5583 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 5584 5585 Logically Collective on TS 5586 5587 Input Parameters: 5588 + ts - the TS context 5589 . A,B - Jacobian matrices 5590 . func - function evaluation routine 5591 - ctx - user context 5592 5593 Calling sequence of func: 5594 $ flag = func (TS ts,PetscReal time,Vec u,Vec udot,Mat A,Mat B,void *ctx); 5595 5596 5597 Level: developer 5598 5599 .keywords: TS, nonlinear, set, function 5600 5601 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 5602 */ 5603 PetscErrorCode TSSetJacobianMatlab(TS ts,Mat A,Mat B,const char *func,mxArray *ctx) 5604 { 5605 PetscErrorCode ierr; 5606 TSMatlabContext *sctx; 5607 5608 PetscFunctionBegin; 5609 /* currently sctx is memory bleed */ 5610 ierr = PetscMalloc(sizeof(TSMatlabContext),&sctx);CHKERRQ(ierr); 5611 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 5612 /* 5613 This should work, but it doesn't 5614 sctx->ctx = ctx; 5615 mexMakeArrayPersistent(sctx->ctx); 5616 */ 5617 sctx->ctx = mxDuplicateArray(ctx); 5618 5619 ierr = TSSetIJacobian(ts,A,B,TSComputeJacobian_Matlab,sctx);CHKERRQ(ierr); 5620 PetscFunctionReturn(0); 5621 } 5622 5623 #undef __FUNCT__ 5624 #define __FUNCT__ "TSMonitor_Matlab" 5625 /* 5626 TSMonitor_Matlab - Calls the function that has been set with TSMonitorSetMatlab(). 5627 5628 Collective on TS 5629 5630 .seealso: TSSetFunction(), TSGetFunction() 5631 @*/ 5632 PetscErrorCode TSMonitor_Matlab(TS ts,PetscInt it, PetscReal time,Vec u, void *ctx) 5633 { 5634 PetscErrorCode ierr; 5635 TSMatlabContext *sctx = (TSMatlabContext*)ctx; 5636 int nlhs = 1,nrhs = 6; 5637 mxArray *plhs[1],*prhs[6]; 5638 long long int lx = 0,ls = 0; 5639 5640 PetscFunctionBegin; 5641 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5642 PetscValidHeaderSpecific(u,VEC_CLASSID,4); 5643 5644 ierr = PetscMemcpy(&ls,&ts,sizeof(ts));CHKERRQ(ierr); 5645 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 5646 5647 prhs[0] = mxCreateDoubleScalar((double)ls); 5648 prhs[1] = mxCreateDoubleScalar((double)it); 5649 prhs[2] = mxCreateDoubleScalar((double)time); 5650 prhs[3] = mxCreateDoubleScalar((double)lx); 5651 prhs[4] = mxCreateString(sctx->funcname); 5652 prhs[5] = sctx->ctx; 5653 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSMonitorInternal");CHKERRQ(ierr); 5654 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 5655 mxDestroyArray(prhs[0]); 5656 mxDestroyArray(prhs[1]); 5657 mxDestroyArray(prhs[2]); 5658 mxDestroyArray(prhs[3]); 5659 mxDestroyArray(prhs[4]); 5660 mxDestroyArray(plhs[0]); 5661 PetscFunctionReturn(0); 5662 } 5663 5664 5665 #undef __FUNCT__ 5666 #define __FUNCT__ "TSMonitorSetMatlab" 5667 /* 5668 TSMonitorSetMatlab - Sets the monitor function from Matlab 5669 5670 Level: developer 5671 5672 .keywords: TS, nonlinear, set, function 5673 5674 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 5675 */ 5676 PetscErrorCode TSMonitorSetMatlab(TS ts,const char *func,mxArray *ctx) 5677 { 5678 PetscErrorCode ierr; 5679 TSMatlabContext *sctx; 5680 5681 PetscFunctionBegin; 5682 /* currently sctx is memory bleed */ 5683 ierr = PetscMalloc(sizeof(TSMatlabContext),&sctx);CHKERRQ(ierr); 5684 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 5685 /* 5686 This should work, but it doesn't 5687 sctx->ctx = ctx; 5688 mexMakeArrayPersistent(sctx->ctx); 5689 */ 5690 sctx->ctx = mxDuplicateArray(ctx); 5691 5692 ierr = TSMonitorSet(ts,TSMonitor_Matlab,sctx,NULL);CHKERRQ(ierr); 5693 PetscFunctionReturn(0); 5694 } 5695 #endif 5696 5697 #undef __FUNCT__ 5698 #define __FUNCT__ "TSMonitorLGSolution" 5699 /*@C 5700 TSMonitorLGSolution - Monitors progress of the TS solvers by plotting each component of the solution vector 5701 in a time based line graph 5702 5703 Collective on TS 5704 5705 Input Parameters: 5706 + ts - the TS context 5707 . step - current time-step 5708 . ptime - current time 5709 - lg - a line graph object 5710 5711 Options Database: 5712 . -ts_monitor_lg_solution_variables 5713 5714 Level: intermediate 5715 5716 Notes: each process in a parallel run displays its component solutions in a separate window 5717 5718 .keywords: TS, vector, monitor, view 5719 5720 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 5721 @*/ 5722 PetscErrorCode TSMonitorLGSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 5723 { 5724 PetscErrorCode ierr; 5725 TSMonitorLGCtx ctx = (TSMonitorLGCtx)dummy; 5726 const PetscScalar *yy; 5727 PetscInt dim; 5728 Vec v; 5729 5730 PetscFunctionBegin; 5731 if (!step) { 5732 PetscDrawAxis axis; 5733 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 5734 ierr = PetscDrawAxisSetLabels(axis,"Solution as function of time","Time","Solution");CHKERRQ(ierr); 5735 if (ctx->names && !ctx->displaynames) { 5736 char **displaynames; 5737 PetscBool flg; 5738 5739 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 5740 ierr = PetscMalloc((dim+1)*sizeof(char*),&displaynames);CHKERRQ(ierr); 5741 ierr = PetscMemzero(displaynames,(dim+1)*sizeof(char*));CHKERRQ(ierr); 5742 ierr = PetscOptionsGetStringArray(((PetscObject)ts)->prefix,"-ts_monitor_lg_solution_variables",displaynames,&dim,&flg);CHKERRQ(ierr); 5743 if (flg) { 5744 ierr = TSMonitorLGCtxSetDisplayVariables(ctx,(const char *const *)displaynames);CHKERRQ(ierr); 5745 } 5746 ierr = PetscStrArrayDestroy(&displaynames);CHKERRQ(ierr); 5747 } 5748 if (ctx->displaynames) { 5749 ierr = PetscDrawLGSetDimension(ctx->lg,ctx->ndisplayvariables);CHKERRQ(ierr); 5750 ierr = PetscDrawLGSetLegend(ctx->lg,(const char *const *)ctx->displaynames);CHKERRQ(ierr); 5751 } else if (ctx->names) { 5752 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 5753 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 5754 ierr = PetscDrawLGSetLegend(ctx->lg,(const char *const *)ctx->names);CHKERRQ(ierr); 5755 } 5756 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 5757 } 5758 if (ctx->transform) { 5759 ierr = (*ctx->transform)(ctx->transformctx,u,&v);CHKERRQ(ierr); 5760 } else { 5761 v = u; 5762 } 5763 ierr = VecGetArrayRead(v,&yy);CHKERRQ(ierr); 5764 #if defined(PETSC_USE_COMPLEX) 5765 { 5766 PetscReal *yreal; 5767 PetscInt i,n; 5768 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 5769 ierr = PetscMalloc1(n,&yreal);CHKERRQ(ierr); 5770 for (i=0; i<n; i++) yreal[i] = PetscRealPart(yy[i]); 5771 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yreal);CHKERRQ(ierr); 5772 ierr = PetscFree(yreal);CHKERRQ(ierr); 5773 } 5774 #else 5775 if (ctx->displaynames) { 5776 PetscInt i; 5777 for (i=0; i<ctx->ndisplayvariables; i++) { 5778 ctx->displayvalues[i] = yy[ctx->displayvariables[i]]; 5779 } 5780 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,ctx->displayvalues);CHKERRQ(ierr); 5781 } else { 5782 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yy);CHKERRQ(ierr); 5783 } 5784 #endif 5785 ierr = VecRestoreArrayRead(v,&yy);CHKERRQ(ierr); 5786 if (ctx->transform) { 5787 ierr = VecDestroy(&v);CHKERRQ(ierr); 5788 } 5789 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 5790 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 5791 } 5792 PetscFunctionReturn(0); 5793 } 5794 5795 5796 #undef __FUNCT__ 5797 #define __FUNCT__ "TSMonitorLGSetVariableNames" 5798 /*@C 5799 TSMonitorLGSetVariableNames - Sets the name of each component in the solution vector so that it may be displayed in the plot 5800 5801 Collective on TS 5802 5803 Input Parameters: 5804 + ts - the TS context 5805 - names - the names of the components, final string must be NULL 5806 5807 Level: intermediate 5808 5809 .keywords: TS, vector, monitor, view 5810 5811 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables(), TSMonitorLGCtxSetVariableNames() 5812 @*/ 5813 PetscErrorCode TSMonitorLGSetVariableNames(TS ts,const char * const *names) 5814 { 5815 PetscErrorCode ierr; 5816 PetscInt i; 5817 5818 PetscFunctionBegin; 5819 for (i=0; i<ts->numbermonitors; i++) { 5820 if (ts->monitor[i] == TSMonitorLGSolution) { 5821 ierr = TSMonitorLGCtxSetVariableNames((TSMonitorLGCtx)ts->monitorcontext[i],names);CHKERRQ(ierr); 5822 break; 5823 } 5824 } 5825 PetscFunctionReturn(0); 5826 } 5827 5828 #undef __FUNCT__ 5829 #define __FUNCT__ "TSMonitorLGCtxSetVariableNames" 5830 /*@C 5831 TSMonitorLGCtxSetVariableNames - Sets the name of each component in the solution vector so that it may be displayed in the plot 5832 5833 Collective on TS 5834 5835 Input Parameters: 5836 + ts - the TS context 5837 - names - the names of the components, final string must be NULL 5838 5839 Level: intermediate 5840 5841 .keywords: TS, vector, monitor, view 5842 5843 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables(), TSMonitorLGSetVariableNames() 5844 @*/ 5845 PetscErrorCode TSMonitorLGCtxSetVariableNames(TSMonitorLGCtx ctx,const char * const *names) 5846 { 5847 PetscErrorCode ierr; 5848 5849 PetscFunctionBegin; 5850 ierr = PetscStrArrayDestroy(&ctx->names);CHKERRQ(ierr); 5851 ierr = PetscStrArrayallocpy(names,&ctx->names);CHKERRQ(ierr); 5852 PetscFunctionReturn(0); 5853 } 5854 5855 #undef __FUNCT__ 5856 #define __FUNCT__ "TSMonitorLGGetVariableNames" 5857 /*@C 5858 TSMonitorLGGetVariableNames - Gets the name of each component in the solution vector so that it may be displayed in the plot 5859 5860 Collective on TS 5861 5862 Input Parameter: 5863 . ts - the TS context 5864 5865 Output Parameter: 5866 . names - the names of the components, final string must be NULL 5867 5868 Level: intermediate 5869 5870 .keywords: TS, vector, monitor, view 5871 5872 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables() 5873 @*/ 5874 PetscErrorCode TSMonitorLGGetVariableNames(TS ts,const char *const **names) 5875 { 5876 PetscInt i; 5877 5878 PetscFunctionBegin; 5879 *names = NULL; 5880 for (i=0; i<ts->numbermonitors; i++) { 5881 if (ts->monitor[i] == TSMonitorLGSolution) { 5882 TSMonitorLGCtx ctx = (TSMonitorLGCtx) ts->monitorcontext[i]; 5883 *names = (const char *const *)ctx->names; 5884 break; 5885 } 5886 } 5887 PetscFunctionReturn(0); 5888 } 5889 5890 #undef __FUNCT__ 5891 #define __FUNCT__ "TSMonitorLGCtxSetDisplayVariables" 5892 /*@C 5893 TSMonitorLGCtxSetDisplayVariables - Sets the variables that are to be display in the monitor 5894 5895 Collective on TS 5896 5897 Input Parameters: 5898 + ctx - the TSMonitorLG context 5899 . displaynames - the names of the components, final string must be NULL 5900 5901 Level: intermediate 5902 5903 .keywords: TS, vector, monitor, view 5904 5905 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames() 5906 @*/ 5907 PetscErrorCode TSMonitorLGCtxSetDisplayVariables(TSMonitorLGCtx ctx,const char * const *displaynames) 5908 { 5909 PetscInt j = 0,k; 5910 PetscErrorCode ierr; 5911 5912 PetscFunctionBegin; 5913 if (!ctx->names) PetscFunctionReturn(0); 5914 ierr = PetscStrArrayDestroy(&ctx->displaynames);CHKERRQ(ierr); 5915 ierr = PetscStrArrayallocpy(displaynames,&ctx->displaynames);CHKERRQ(ierr); 5916 while (displaynames[j]) j++; 5917 ctx->ndisplayvariables = j; 5918 ierr = PetscMalloc1(ctx->ndisplayvariables,&ctx->displayvariables);CHKERRQ(ierr); 5919 ierr = PetscMalloc1(ctx->ndisplayvariables,&ctx->displayvalues);CHKERRQ(ierr); 5920 j = 0; 5921 while (displaynames[j]) { 5922 k = 0; 5923 while (ctx->names[k]) { 5924 PetscBool flg; 5925 ierr = PetscStrcmp(displaynames[j],ctx->names[k],&flg);CHKERRQ(ierr); 5926 if (flg) { 5927 ctx->displayvariables[j] = k; 5928 break; 5929 } 5930 k++; 5931 } 5932 j++; 5933 } 5934 PetscFunctionReturn(0); 5935 } 5936 5937 5938 #undef __FUNCT__ 5939 #define __FUNCT__ "TSMonitorLGSetDisplayVariables" 5940 /*@C 5941 TSMonitorLGSetDisplayVariables - Sets the variables that are to be display in the monitor 5942 5943 Collective on TS 5944 5945 Input Parameters: 5946 + ts - the TS context 5947 . displaynames - the names of the components, final string must be NULL 5948 5949 Level: intermediate 5950 5951 .keywords: TS, vector, monitor, view 5952 5953 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames() 5954 @*/ 5955 PetscErrorCode TSMonitorLGSetDisplayVariables(TS ts,const char * const *displaynames) 5956 { 5957 PetscInt i; 5958 PetscErrorCode ierr; 5959 5960 PetscFunctionBegin; 5961 for (i=0; i<ts->numbermonitors; i++) { 5962 if (ts->monitor[i] == TSMonitorLGSolution) { 5963 ierr = TSMonitorLGCtxSetDisplayVariables((TSMonitorLGCtx)ts->monitorcontext[i],displaynames);CHKERRQ(ierr); 5964 break; 5965 } 5966 } 5967 PetscFunctionReturn(0); 5968 } 5969 5970 #undef __FUNCT__ 5971 #define __FUNCT__ "TSMonitorLGSetTransform" 5972 /*@C 5973 TSMonitorLGSetTransform - Solution vector will be transformed by provided function before being displayed 5974 5975 Collective on TS 5976 5977 Input Parameters: 5978 + ts - the TS context 5979 . transform - the transform function 5980 . destroy - function to destroy the optional context 5981 - ctx - optional context used by transform function 5982 5983 Level: intermediate 5984 5985 .keywords: TS, vector, monitor, view 5986 5987 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames(), TSMonitorLGCtxSetTransform() 5988 @*/ 5989 PetscErrorCode TSMonitorLGSetTransform(TS ts,PetscErrorCode (*transform)(void*,Vec,Vec*),PetscErrorCode (*destroy)(void*),void *tctx) 5990 { 5991 PetscInt i; 5992 PetscErrorCode ierr; 5993 5994 PetscFunctionBegin; 5995 for (i=0; i<ts->numbermonitors; i++) { 5996 if (ts->monitor[i] == TSMonitorLGSolution) { 5997 ierr = TSMonitorLGCtxSetTransform((TSMonitorLGCtx)ts->monitorcontext[i],transform,destroy,tctx);CHKERRQ(ierr); 5998 } 5999 } 6000 PetscFunctionReturn(0); 6001 } 6002 6003 #undef __FUNCT__ 6004 #define __FUNCT__ "TSMonitorLGCtxSetTransform" 6005 /*@C 6006 TSMonitorLGCtxSetTransform - Solution vector will be transformed by provided function before being displayed 6007 6008 Collective on TSLGCtx 6009 6010 Input Parameters: 6011 + ts - the TS context 6012 . transform - the transform function 6013 . destroy - function to destroy the optional context 6014 - ctx - optional context used by transform function 6015 6016 Level: intermediate 6017 6018 .keywords: TS, vector, monitor, view 6019 6020 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames(), TSMonitorLGSetTransform() 6021 @*/ 6022 PetscErrorCode TSMonitorLGCtxSetTransform(TSMonitorLGCtx ctx,PetscErrorCode (*transform)(void*,Vec,Vec*),PetscErrorCode (*destroy)(void*),void *tctx) 6023 { 6024 PetscFunctionBegin; 6025 ctx->transform = transform; 6026 ctx->transformdestroy = destroy; 6027 ctx->transformctx = tctx; 6028 PetscFunctionReturn(0); 6029 } 6030 6031 #undef __FUNCT__ 6032 #define __FUNCT__ "TSMonitorLGError" 6033 /*@C 6034 TSMonitorLGError - Monitors progress of the TS solvers by plotting each component of the solution vector 6035 in a time based line graph 6036 6037 Collective on TS 6038 6039 Input Parameters: 6040 + ts - the TS context 6041 . step - current time-step 6042 . ptime - current time 6043 - lg - a line graph object 6044 6045 Level: intermediate 6046 6047 Notes: 6048 Only for sequential solves. 6049 6050 The user must provide the solution using TSSetSolutionFunction() to use this monitor. 6051 6052 Options Database Keys: 6053 . -ts_monitor_lg_error - create a graphical monitor of error history 6054 6055 .keywords: TS, vector, monitor, view 6056 6057 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSSetSolutionFunction() 6058 @*/ 6059 PetscErrorCode TSMonitorLGError(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 6060 { 6061 PetscErrorCode ierr; 6062 TSMonitorLGCtx ctx = (TSMonitorLGCtx)dummy; 6063 const PetscScalar *yy; 6064 Vec y; 6065 PetscInt dim; 6066 6067 PetscFunctionBegin; 6068 if (!step) { 6069 PetscDrawAxis axis; 6070 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 6071 ierr = PetscDrawAxisSetLabels(axis,"Error in solution as function of time","Time","Solution");CHKERRQ(ierr); 6072 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 6073 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 6074 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 6075 } 6076 ierr = VecDuplicate(u,&y);CHKERRQ(ierr); 6077 ierr = TSComputeSolutionFunction(ts,ptime,y);CHKERRQ(ierr); 6078 ierr = VecAXPY(y,-1.0,u);CHKERRQ(ierr); 6079 ierr = VecGetArrayRead(y,&yy);CHKERRQ(ierr); 6080 #if defined(PETSC_USE_COMPLEX) 6081 { 6082 PetscReal *yreal; 6083 PetscInt i,n; 6084 ierr = VecGetLocalSize(y,&n);CHKERRQ(ierr); 6085 ierr = PetscMalloc1(n,&yreal);CHKERRQ(ierr); 6086 for (i=0; i<n; i++) yreal[i] = PetscRealPart(yy[i]); 6087 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yreal);CHKERRQ(ierr); 6088 ierr = PetscFree(yreal);CHKERRQ(ierr); 6089 } 6090 #else 6091 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yy);CHKERRQ(ierr); 6092 #endif 6093 ierr = VecRestoreArrayRead(y,&yy);CHKERRQ(ierr); 6094 ierr = VecDestroy(&y);CHKERRQ(ierr); 6095 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 6096 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 6097 } 6098 PetscFunctionReturn(0); 6099 } 6100 6101 #undef __FUNCT__ 6102 #define __FUNCT__ "TSMonitorLGSNESIterations" 6103 PetscErrorCode TSMonitorLGSNESIterations(TS ts,PetscInt n,PetscReal ptime,Vec v,void *monctx) 6104 { 6105 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 6106 PetscReal x = ptime,y; 6107 PetscErrorCode ierr; 6108 PetscInt its; 6109 6110 PetscFunctionBegin; 6111 if (!n) { 6112 PetscDrawAxis axis; 6113 6114 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 6115 ierr = PetscDrawAxisSetLabels(axis,"Nonlinear iterations as function of time","Time","SNES Iterations");CHKERRQ(ierr); 6116 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 6117 6118 ctx->snes_its = 0; 6119 } 6120 ierr = TSGetSNESIterations(ts,&its);CHKERRQ(ierr); 6121 y = its - ctx->snes_its; 6122 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 6123 if (((ctx->howoften > 0) && (!(n % ctx->howoften)) && (n > -1)) || ((ctx->howoften == -1) && (n == -1))) { 6124 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 6125 } 6126 ctx->snes_its = its; 6127 PetscFunctionReturn(0); 6128 } 6129 6130 #undef __FUNCT__ 6131 #define __FUNCT__ "TSMonitorLGKSPIterations" 6132 PetscErrorCode TSMonitorLGKSPIterations(TS ts,PetscInt n,PetscReal ptime,Vec v,void *monctx) 6133 { 6134 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 6135 PetscReal x = ptime,y; 6136 PetscErrorCode ierr; 6137 PetscInt its; 6138 6139 PetscFunctionBegin; 6140 if (!n) { 6141 PetscDrawAxis axis; 6142 6143 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 6144 ierr = PetscDrawAxisSetLabels(axis,"Linear iterations as function of time","Time","KSP Iterations");CHKERRQ(ierr); 6145 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 6146 6147 ctx->ksp_its = 0; 6148 } 6149 ierr = TSGetKSPIterations(ts,&its);CHKERRQ(ierr); 6150 y = its - ctx->ksp_its; 6151 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 6152 if (((ctx->howoften > 0) && (!(n % ctx->howoften)) && (n > -1)) || ((ctx->howoften == -1) && (n == -1))) { 6153 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 6154 } 6155 ctx->ksp_its = its; 6156 PetscFunctionReturn(0); 6157 } 6158 6159 #undef __FUNCT__ 6160 #define __FUNCT__ "TSComputeLinearStability" 6161 /*@ 6162 TSComputeLinearStability - computes the linear stability function at a point 6163 6164 Collective on TS and Vec 6165 6166 Input Parameters: 6167 + ts - the TS context 6168 - xr,xi - real and imaginary part of input arguments 6169 6170 Output Parameters: 6171 . yr,yi - real and imaginary part of function value 6172 6173 Level: developer 6174 6175 .keywords: TS, compute 6176 6177 .seealso: TSSetRHSFunction(), TSComputeIFunction() 6178 @*/ 6179 PetscErrorCode TSComputeLinearStability(TS ts,PetscReal xr,PetscReal xi,PetscReal *yr,PetscReal *yi) 6180 { 6181 PetscErrorCode ierr; 6182 6183 PetscFunctionBegin; 6184 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6185 if (!ts->ops->linearstability) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Linearized stability function not provided for this method"); 6186 ierr = (*ts->ops->linearstability)(ts,xr,xi,yr,yi);CHKERRQ(ierr); 6187 PetscFunctionReturn(0); 6188 } 6189 6190 /* ------------------------------------------------------------------------*/ 6191 #undef __FUNCT__ 6192 #define __FUNCT__ "TSMonitorEnvelopeCtxCreate" 6193 /*@C 6194 TSMonitorEnvelopeCtxCreate - Creates a context for use with TSMonitorEnvelope() 6195 6196 Collective on TS 6197 6198 Input Parameters: 6199 . ts - the ODE solver object 6200 6201 Output Parameter: 6202 . ctx - the context 6203 6204 Level: intermediate 6205 6206 .keywords: TS, monitor, line graph, residual, seealso 6207 6208 .seealso: TSMonitorLGTimeStep(), TSMonitorSet(), TSMonitorLGSolution(), TSMonitorLGError() 6209 6210 @*/ 6211 PetscErrorCode TSMonitorEnvelopeCtxCreate(TS ts,TSMonitorEnvelopeCtx *ctx) 6212 { 6213 PetscErrorCode ierr; 6214 6215 PetscFunctionBegin; 6216 ierr = PetscNew(ctx);CHKERRQ(ierr); 6217 PetscFunctionReturn(0); 6218 } 6219 6220 #undef __FUNCT__ 6221 #define __FUNCT__ "TSMonitorEnvelope" 6222 /*@C 6223 TSMonitorEnvelope - Monitors the maximum and minimum value of each component of the solution 6224 6225 Collective on TS 6226 6227 Input Parameters: 6228 + ts - the TS context 6229 . step - current time-step 6230 . ptime - current time 6231 - ctx - the envelope context 6232 6233 Options Database: 6234 . -ts_monitor_envelope 6235 6236 Level: intermediate 6237 6238 Notes: after a solve you can use TSMonitorEnvelopeGetBounds() to access the envelope 6239 6240 .keywords: TS, vector, monitor, view 6241 6242 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorEnvelopeGetBounds() 6243 @*/ 6244 PetscErrorCode TSMonitorEnvelope(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 6245 { 6246 PetscErrorCode ierr; 6247 TSMonitorEnvelopeCtx ctx = (TSMonitorEnvelopeCtx)dummy; 6248 6249 PetscFunctionBegin; 6250 if (!ctx->max) { 6251 ierr = VecDuplicate(u,&ctx->max);CHKERRQ(ierr); 6252 ierr = VecDuplicate(u,&ctx->min);CHKERRQ(ierr); 6253 ierr = VecCopy(u,ctx->max);CHKERRQ(ierr); 6254 ierr = VecCopy(u,ctx->min);CHKERRQ(ierr); 6255 } else { 6256 ierr = VecPointwiseMax(ctx->max,u,ctx->max);CHKERRQ(ierr); 6257 ierr = VecPointwiseMin(ctx->min,u,ctx->min);CHKERRQ(ierr); 6258 } 6259 PetscFunctionReturn(0); 6260 } 6261 6262 6263 #undef __FUNCT__ 6264 #define __FUNCT__ "TSMonitorEnvelopeGetBounds" 6265 /*@C 6266 TSMonitorEnvelopeGetBounds - Gets the bounds for the components of the solution 6267 6268 Collective on TS 6269 6270 Input Parameter: 6271 . ts - the TS context 6272 6273 Output Parameter: 6274 + max - the maximum values 6275 - min - the minimum values 6276 6277 Level: intermediate 6278 6279 .keywords: TS, vector, monitor, view 6280 6281 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables() 6282 @*/ 6283 PetscErrorCode TSMonitorEnvelopeGetBounds(TS ts,Vec *max,Vec *min) 6284 { 6285 PetscInt i; 6286 6287 PetscFunctionBegin; 6288 if (max) *max = NULL; 6289 if (min) *min = NULL; 6290 for (i=0; i<ts->numbermonitors; i++) { 6291 if (ts->monitor[i] == TSMonitorEnvelope) { 6292 TSMonitorEnvelopeCtx ctx = (TSMonitorEnvelopeCtx) ts->monitorcontext[i]; 6293 if (max) *max = ctx->max; 6294 if (min) *min = ctx->min; 6295 break; 6296 } 6297 } 6298 PetscFunctionReturn(0); 6299 } 6300 6301 #undef __FUNCT__ 6302 #define __FUNCT__ "TSMonitorEnvelopeCtxDestroy" 6303 /*@C 6304 TSMonitorEnvelopeCtxDestroy - Destroys a context that was created with TSMonitorEnvelopeCtxCreate(). 6305 6306 Collective on TSMonitorEnvelopeCtx 6307 6308 Input Parameter: 6309 . ctx - the monitor context 6310 6311 Level: intermediate 6312 6313 .keywords: TS, monitor, line graph, destroy 6314 6315 .seealso: TSMonitorLGCtxCreate(), TSMonitorSet(), TSMonitorLGTimeStep(); 6316 @*/ 6317 PetscErrorCode TSMonitorEnvelopeCtxDestroy(TSMonitorEnvelopeCtx *ctx) 6318 { 6319 PetscErrorCode ierr; 6320 6321 PetscFunctionBegin; 6322 ierr = VecDestroy(&(*ctx)->min);CHKERRQ(ierr); 6323 ierr = VecDestroy(&(*ctx)->max);CHKERRQ(ierr); 6324 ierr = PetscFree(*ctx);CHKERRQ(ierr); 6325 PetscFunctionReturn(0); 6326 } 6327 6328 #undef __FUNCT__ 6329 #define __FUNCT__ "TSRollBack" 6330 /*@ 6331 TSRollBack - Rolls back one time step 6332 6333 Collective on TS 6334 6335 Input Parameter: 6336 . ts - the TS context obtained from TSCreate() 6337 6338 Level: advanced 6339 6340 .keywords: TS, timestep, rollback 6341 6342 .seealso: TSCreate(), TSSetUp(), TSDestroy(), TSSolve(), TSSetPreStep(), TSSetPreStage(), TSInterpolate() 6343 @*/ 6344 PetscErrorCode TSRollBack(TS ts) 6345 { 6346 PetscErrorCode ierr; 6347 6348 PetscFunctionBegin; 6349 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 6350 6351 if (!ts->ops->rollback) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSRollBack not implemented for type '%s'",((PetscObject)ts)->type_name); 6352 ierr = (*ts->ops->rollback)(ts);CHKERRQ(ierr); 6353 ts->time_step = ts->ptime - ts->ptime_prev; 6354 ts->ptime = ts->ptime_prev; 6355 ts->steprollback = PETSC_TRUE; /* Flag to indicate that the step is rollbacked */ 6356 PetscFunctionReturn(0); 6357 } 6358 6359 #undef __FUNCT__ 6360 #define __FUNCT__ "TSGetStages" 6361 /*@ 6362 TSGetStages - Get the number of stages and stage values 6363 6364 Input Parameter: 6365 . ts - the TS context obtained from TSCreate() 6366 6367 Level: advanced 6368 6369 .keywords: TS, getstages 6370 6371 .seealso: TSCreate() 6372 @*/ 6373 PetscErrorCode TSGetStages(TS ts,PetscInt *ns, Vec **Y) 6374 { 6375 PetscErrorCode ierr; 6376 6377 PetscFunctionBegin; 6378 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 6379 PetscValidPointer(ns,2); 6380 6381 if (!ts->ops->getstages) *ns=0; 6382 else { 6383 ierr = (*ts->ops->getstages)(ts,ns,Y);CHKERRQ(ierr); 6384 } 6385 PetscFunctionReturn(0); 6386 } 6387 6388 6389 #undef __FUNCT__ 6390 #define __FUNCT__ "TSComputeIJacobianDefaultColor" 6391 /*@C 6392 TSComputeIJacobianDefaultColor - Computes the Jacobian using finite differences and coloring to exploit matrix sparsity. 6393 6394 Collective on SNES 6395 6396 Input Parameters: 6397 + ts - the TS context 6398 . t - current timestep 6399 . U - state vector 6400 . Udot - time derivative of state vector 6401 . shift - shift to apply, see note below 6402 - ctx - an optional user context 6403 6404 Output Parameters: 6405 + J - Jacobian matrix (not altered in this routine) 6406 - B - newly computed Jacobian matrix to use with preconditioner (generally the same as J) 6407 6408 Level: intermediate 6409 6410 Notes: 6411 If F(t,U,Udot)=0 is the DAE, the required Jacobian is 6412 6413 dF/dU + shift*dF/dUdot 6414 6415 Most users should not need to explicitly call this routine, as it 6416 is used internally within the nonlinear solvers. 6417 6418 This will first try to get the coloring from the DM. If the DM type has no coloring 6419 routine, then it will try to get the coloring from the matrix. This requires that the 6420 matrix have nonzero entries precomputed. 6421 6422 .keywords: TS, finite differences, Jacobian, coloring, sparse 6423 .seealso: TSSetIJacobian(), MatFDColoringCreate(), MatFDColoringSetFunction() 6424 @*/ 6425 PetscErrorCode TSComputeIJacobianDefaultColor(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat J,Mat B,void *ctx) 6426 { 6427 SNES snes; 6428 MatFDColoring color; 6429 PetscBool hascolor, matcolor = PETSC_FALSE; 6430 PetscErrorCode ierr; 6431 6432 PetscFunctionBegin; 6433 ierr = PetscOptionsGetBool(((PetscObject) ts)->prefix, "-ts_fd_color_use_mat", &matcolor, NULL);CHKERRQ(ierr); 6434 ierr = PetscObjectQuery((PetscObject) B, "TSMatFDColoring", (PetscObject *) &color);CHKERRQ(ierr); 6435 if (!color) { 6436 DM dm; 6437 ISColoring iscoloring; 6438 6439 ierr = TSGetDM(ts, &dm);CHKERRQ(ierr); 6440 ierr = DMHasColoring(dm, &hascolor);CHKERRQ(ierr); 6441 if (hascolor && !matcolor) { 6442 ierr = DMCreateColoring(dm, IS_COLORING_GLOBAL, &iscoloring);CHKERRQ(ierr); 6443 ierr = MatFDColoringCreate(B, iscoloring, &color);CHKERRQ(ierr); 6444 ierr = MatFDColoringSetFunction(color, (PetscErrorCode (*)(void)) SNESTSFormFunction, (void *) ts);CHKERRQ(ierr); 6445 ierr = MatFDColoringSetFromOptions(color);CHKERRQ(ierr); 6446 ierr = MatFDColoringSetUp(B, iscoloring, color);CHKERRQ(ierr); 6447 ierr = ISColoringDestroy(&iscoloring);CHKERRQ(ierr); 6448 } else { 6449 MatColoring mc; 6450 6451 ierr = MatColoringCreate(B, &mc);CHKERRQ(ierr); 6452 ierr = MatColoringSetDistance(mc, 2);CHKERRQ(ierr); 6453 ierr = MatColoringSetType(mc, MATCOLORINGSL);CHKERRQ(ierr); 6454 ierr = MatColoringSetFromOptions(mc);CHKERRQ(ierr); 6455 ierr = MatColoringApply(mc, &iscoloring);CHKERRQ(ierr); 6456 ierr = MatColoringDestroy(&mc);CHKERRQ(ierr); 6457 ierr = MatFDColoringCreate(B, iscoloring, &color);CHKERRQ(ierr); 6458 ierr = MatFDColoringSetFunction(color, (PetscErrorCode (*)(void)) SNESTSFormFunction, (void *) ts);CHKERRQ(ierr); 6459 ierr = MatFDColoringSetFromOptions(color);CHKERRQ(ierr); 6460 ierr = MatFDColoringSetUp(B, iscoloring, color);CHKERRQ(ierr); 6461 ierr = ISColoringDestroy(&iscoloring);CHKERRQ(ierr); 6462 } 6463 ierr = PetscObjectCompose((PetscObject) B, "TSMatFDColoring", (PetscObject) color);CHKERRQ(ierr); 6464 ierr = PetscObjectDereference((PetscObject) color);CHKERRQ(ierr); 6465 } 6466 ierr = TSGetSNES(ts, &snes);CHKERRQ(ierr); 6467 ierr = MatFDColoringApply(B, color, U, snes);CHKERRQ(ierr); 6468 if (J != B) { 6469 ierr = MatAssemblyBegin(J, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 6470 ierr = MatAssemblyEnd(J, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 6471 } 6472 PetscFunctionReturn(0); 6473 } 6474