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 = PetscDrawStringBoxed(draw,x,y,PETSC_DRAW_BLACK,PETSC_DRAW_BLACK,str,NULL,&h);CHKERRQ(ierr); 1466 bottom = y - h; 1467 ierr = PetscDrawPushCurrentPoint(draw,x,bottom);CHKERRQ(ierr); 1468 if (ts->ops->view) { 1469 ierr = (*ts->ops->view)(ts,viewer);CHKERRQ(ierr); 1470 } 1471 ierr = PetscDrawPopCurrentPoint(draw);CHKERRQ(ierr); 1472 #if defined(PETSC_HAVE_SAWS) 1473 } else if (issaws) { 1474 PetscMPIInt rank; 1475 const char *name; 1476 1477 ierr = PetscObjectGetName((PetscObject)ts,&name);CHKERRQ(ierr); 1478 ierr = MPI_Comm_rank(PETSC_COMM_WORLD,&rank);CHKERRQ(ierr); 1479 if (!((PetscObject)ts)->amsmem && !rank) { 1480 char dir[1024]; 1481 1482 ierr = PetscObjectViewSAWs((PetscObject)ts,viewer);CHKERRQ(ierr); 1483 ierr = PetscSNPrintf(dir,1024,"/PETSc/Objects/%s/time_step",name);CHKERRQ(ierr); 1484 PetscStackCallSAWs(SAWs_Register,(dir,&ts->steps,1,SAWs_READ,SAWs_INT)); 1485 ierr = PetscSNPrintf(dir,1024,"/PETSc/Objects/%s/time",name);CHKERRQ(ierr); 1486 PetscStackCallSAWs(SAWs_Register,(dir,&ts->ptime,1,SAWs_READ,SAWs_DOUBLE)); 1487 } 1488 if (ts->ops->view) { 1489 ierr = (*ts->ops->view)(ts,viewer);CHKERRQ(ierr); 1490 } 1491 #endif 1492 } 1493 1494 ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr); 1495 ierr = PetscObjectTypeCompare((PetscObject)ts,TSSUNDIALS,&isundials);CHKERRQ(ierr); 1496 ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr); 1497 PetscFunctionReturn(0); 1498 } 1499 1500 1501 #undef __FUNCT__ 1502 #define __FUNCT__ "TSSetApplicationContext" 1503 /*@ 1504 TSSetApplicationContext - Sets an optional user-defined context for 1505 the timesteppers. 1506 1507 Logically Collective on TS 1508 1509 Input Parameters: 1510 + ts - the TS context obtained from TSCreate() 1511 - usrP - optional user context 1512 1513 Level: intermediate 1514 1515 .keywords: TS, timestep, set, application, context 1516 1517 .seealso: TSGetApplicationContext() 1518 @*/ 1519 PetscErrorCode TSSetApplicationContext(TS ts,void *usrP) 1520 { 1521 PetscFunctionBegin; 1522 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1523 ts->user = usrP; 1524 PetscFunctionReturn(0); 1525 } 1526 1527 #undef __FUNCT__ 1528 #define __FUNCT__ "TSGetApplicationContext" 1529 /*@ 1530 TSGetApplicationContext - Gets the user-defined context for the 1531 timestepper. 1532 1533 Not Collective 1534 1535 Input Parameter: 1536 . ts - the TS context obtained from TSCreate() 1537 1538 Output Parameter: 1539 . usrP - user context 1540 1541 Level: intermediate 1542 1543 .keywords: TS, timestep, get, application, context 1544 1545 .seealso: TSSetApplicationContext() 1546 @*/ 1547 PetscErrorCode TSGetApplicationContext(TS ts,void *usrP) 1548 { 1549 PetscFunctionBegin; 1550 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1551 *(void**)usrP = ts->user; 1552 PetscFunctionReturn(0); 1553 } 1554 1555 #undef __FUNCT__ 1556 #define __FUNCT__ "TSGetTimeStepNumber" 1557 /*@ 1558 TSGetTimeStepNumber - Gets the number of time steps completed. 1559 1560 Not Collective 1561 1562 Input Parameter: 1563 . ts - the TS context obtained from TSCreate() 1564 1565 Output Parameter: 1566 . iter - number of steps completed so far 1567 1568 Level: intermediate 1569 1570 .keywords: TS, timestep, get, iteration, number 1571 .seealso: TSGetTime(), TSGetTimeStep(), TSSetPreStep(), TSSetPreStage(), TSSetPostStage(), TSSetPostStep() 1572 @*/ 1573 PetscErrorCode TSGetTimeStepNumber(TS ts,PetscInt *iter) 1574 { 1575 PetscFunctionBegin; 1576 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1577 PetscValidIntPointer(iter,2); 1578 *iter = ts->steps; 1579 PetscFunctionReturn(0); 1580 } 1581 1582 #undef __FUNCT__ 1583 #define __FUNCT__ "TSSetInitialTimeStep" 1584 /*@ 1585 TSSetInitialTimeStep - Sets the initial timestep to be used, 1586 as well as the initial time. 1587 1588 Logically Collective on TS 1589 1590 Input Parameters: 1591 + ts - the TS context obtained from TSCreate() 1592 . initial_time - the initial time 1593 - time_step - the size of the timestep 1594 1595 Level: intermediate 1596 1597 .seealso: TSSetTimeStep(), TSGetTimeStep() 1598 1599 .keywords: TS, set, initial, timestep 1600 @*/ 1601 PetscErrorCode TSSetInitialTimeStep(TS ts,PetscReal initial_time,PetscReal time_step) 1602 { 1603 PetscErrorCode ierr; 1604 1605 PetscFunctionBegin; 1606 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1607 ierr = TSSetTimeStep(ts,time_step);CHKERRQ(ierr); 1608 ierr = TSSetTime(ts,initial_time);CHKERRQ(ierr); 1609 PetscFunctionReturn(0); 1610 } 1611 1612 #undef __FUNCT__ 1613 #define __FUNCT__ "TSSetTimeStep" 1614 /*@ 1615 TSSetTimeStep - Allows one to reset the timestep at any time, 1616 useful for simple pseudo-timestepping codes. 1617 1618 Logically Collective on TS 1619 1620 Input Parameters: 1621 + ts - the TS context obtained from TSCreate() 1622 - time_step - the size of the timestep 1623 1624 Level: intermediate 1625 1626 .seealso: TSSetInitialTimeStep(), TSGetTimeStep() 1627 1628 .keywords: TS, set, timestep 1629 @*/ 1630 PetscErrorCode TSSetTimeStep(TS ts,PetscReal time_step) 1631 { 1632 PetscFunctionBegin; 1633 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1634 PetscValidLogicalCollectiveReal(ts,time_step,2); 1635 ts->time_step = time_step; 1636 ts->time_step_orig = time_step; 1637 PetscFunctionReturn(0); 1638 } 1639 1640 #undef __FUNCT__ 1641 #define __FUNCT__ "TSSetExactFinalTime" 1642 /*@ 1643 TSSetExactFinalTime - Determines whether to adapt the final time step to 1644 match the exact final time, interpolate solution to the exact final time, 1645 or just return at the final time TS computed. 1646 1647 Logically Collective on TS 1648 1649 Input Parameter: 1650 + ts - the time-step context 1651 - eftopt - exact final time option 1652 1653 Level: beginner 1654 1655 .seealso: TSExactFinalTimeOption 1656 @*/ 1657 PetscErrorCode TSSetExactFinalTime(TS ts,TSExactFinalTimeOption eftopt) 1658 { 1659 PetscFunctionBegin; 1660 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1661 PetscValidLogicalCollectiveEnum(ts,eftopt,2); 1662 ts->exact_final_time = eftopt; 1663 PetscFunctionReturn(0); 1664 } 1665 1666 #undef __FUNCT__ 1667 #define __FUNCT__ "TSGetTimeStep" 1668 /*@ 1669 TSGetTimeStep - Gets the current timestep size. 1670 1671 Not Collective 1672 1673 Input Parameter: 1674 . ts - the TS context obtained from TSCreate() 1675 1676 Output Parameter: 1677 . dt - the current timestep size 1678 1679 Level: intermediate 1680 1681 .seealso: TSSetInitialTimeStep(), TSGetTimeStep() 1682 1683 .keywords: TS, get, timestep 1684 @*/ 1685 PetscErrorCode TSGetTimeStep(TS ts,PetscReal *dt) 1686 { 1687 PetscFunctionBegin; 1688 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1689 PetscValidRealPointer(dt,2); 1690 *dt = ts->time_step; 1691 PetscFunctionReturn(0); 1692 } 1693 1694 #undef __FUNCT__ 1695 #define __FUNCT__ "TSGetSolution" 1696 /*@ 1697 TSGetSolution - Returns the solution at the present timestep. It 1698 is valid to call this routine inside the function that you are evaluating 1699 in order to move to the new timestep. This vector not changed until 1700 the solution at the next timestep has been calculated. 1701 1702 Not Collective, but Vec returned is parallel if TS is parallel 1703 1704 Input Parameter: 1705 . ts - the TS context obtained from TSCreate() 1706 1707 Output Parameter: 1708 . v - the vector containing the solution 1709 1710 Level: intermediate 1711 1712 .seealso: TSGetTimeStep() 1713 1714 .keywords: TS, timestep, get, solution 1715 @*/ 1716 PetscErrorCode TSGetSolution(TS ts,Vec *v) 1717 { 1718 PetscFunctionBegin; 1719 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1720 PetscValidPointer(v,2); 1721 *v = ts->vec_sol; 1722 PetscFunctionReturn(0); 1723 } 1724 1725 #undef __FUNCT__ 1726 #define __FUNCT__ "TSAdjointGetCostGradients" 1727 /*@ 1728 TSAdjointGetCostGradients - 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 TSAdjointGetCostGradients(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 TSAdjointSetCostGradients() 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__ "TSAdjointSetCostGradients" 2320 /*@ 2321 TSAdjointSetCostGradients - 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 TSAdjointSetCostGradients(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 ts->numcost = numcost; 2345 PetscFunctionReturn(0); 2346 } 2347 2348 #undef __FUNCT__ 2349 #define __FUNCT__ "TSAdjointSetRHSJacobian" 2350 /*@C 2351 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. 2352 2353 Logically Collective on TS 2354 2355 Input Parameters: 2356 + ts - The TS context obtained from TSCreate() 2357 - func - The function 2358 2359 Calling sequence of func: 2360 $ func (TS ts,PetscReal t,Vec y,Mat A,void *ctx); 2361 + t - current timestep 2362 . y - input vector (current ODE solution) 2363 . A - output matrix 2364 - ctx - [optional] user-defined function context 2365 2366 Level: intermediate 2367 2368 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 2369 2370 .keywords: TS, sensitivity 2371 .seealso: 2372 @*/ 2373 PetscErrorCode TSAdjointSetRHSJacobian(TS ts,Mat Amat,PetscErrorCode (*func)(TS,PetscReal,Vec,Mat,void*),void *ctx) 2374 { 2375 PetscErrorCode ierr; 2376 2377 PetscFunctionBegin; 2378 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 2379 if (Amat) PetscValidHeaderSpecific(Amat,MAT_CLASSID,2); 2380 2381 ts->rhsjacobianp = func; 2382 ts->rhsjacobianpctx = ctx; 2383 if(Amat) { 2384 ierr = PetscObjectReference((PetscObject)Amat);CHKERRQ(ierr); 2385 ierr = MatDestroy(&ts->Jacp);CHKERRQ(ierr); 2386 ts->Jacp = Amat; 2387 } 2388 PetscFunctionReturn(0); 2389 } 2390 2391 #undef __FUNCT__ 2392 #define __FUNCT__ "TSAdjointComputeRHSJacobian" 2393 /*@C 2394 TSAdjointComputeRHSJacobian - Runs the user-defined Jacobian function. 2395 2396 Collective on TS 2397 2398 Input Parameters: 2399 . ts - The TS context obtained from TSCreate() 2400 2401 Level: developer 2402 2403 .keywords: TS, sensitivity 2404 .seealso: TSAdjointSetRHSJacobian() 2405 @*/ 2406 PetscErrorCode TSAdjointComputeRHSJacobian(TS ts,PetscReal t,Vec X,Mat Amat) 2407 { 2408 PetscErrorCode ierr; 2409 2410 PetscFunctionBegin; 2411 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2412 PetscValidHeaderSpecific(X,VEC_CLASSID,3); 2413 PetscValidPointer(Amat,4); 2414 2415 PetscStackPush("TS user JacobianP function for sensitivity analysis"); 2416 ierr = (*ts->rhsjacobianp)(ts,t,X,Amat,ts->rhsjacobianpctx); CHKERRQ(ierr); 2417 PetscStackPop; 2418 PetscFunctionReturn(0); 2419 } 2420 2421 #undef __FUNCT__ 2422 #define __FUNCT__ "TSAdjointSetCostIntegrand" 2423 /*@C 2424 TSAdjointSetCostIntegrand - Sets the routine for evaluating the integral term in one or more cost functions 2425 2426 Logically Collective on TS 2427 2428 Input Parameters: 2429 + ts - the TS context obtained from TSCreate() 2430 . numcost - number of gradients to be computed, this is the number of cost functions 2431 . rf - routine for evaluating the integrand function 2432 . drdyf - function that computes the gradients of the r's with respect to y,NULL if not a function y 2433 . drdpf - function that computes the gradients of the r's with respect to p, NULL if not a function of p 2434 - ctx - [optional] user-defined context for private data for the function evaluation routine (may be NULL) 2435 2436 Calling sequence of rf: 2437 $ rf(TS ts,PetscReal t,Vec y,Vec f[],void *ctx); 2438 2439 + t - current timestep 2440 . y - input vector 2441 . f - function result; one vector entry for each cost function 2442 - ctx - [optional] user-defined function context 2443 2444 Calling sequence of drdyf: 2445 $ PetscErroCode drdyf(TS ts,PetscReal t,Vec y,Vec *drdy,void *ctx); 2446 2447 Calling sequence of drdpf: 2448 $ PetscErroCode drdpf(TS ts,PetscReal t,Vec y,Vec *drdp,void *ctx); 2449 2450 Level: intermediate 2451 2452 Notes: For optimization there is generally a single cost function, numcost = 1. For sensitivities there may be multiple cost functions 2453 2454 .keywords: TS, sensitivity analysis, timestep, set, quadrature, function 2455 2456 .seealso: TSAdjointSetRHSJacobian(),TSAdjointGetCostGradients(), TSAdjointSetCostGradients() 2457 @*/ 2458 PetscErrorCode TSAdjointSetCostIntegrand(TS ts,PetscInt numcost, PetscErrorCode (*rf)(TS,PetscReal,Vec,Vec,void*), 2459 PetscErrorCode (*drdyf)(TS,PetscReal,Vec,Vec*,void*), 2460 PetscErrorCode (*drdpf)(TS,PetscReal,Vec,Vec*,void*),void *ctx) 2461 { 2462 PetscErrorCode ierr; 2463 2464 PetscFunctionBegin; 2465 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2466 if (!ts->numcost) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"Call TSAdjointSetCostGradients() first so that the number of cost functions can be determined."); 2467 if (ts->numcost && ts->numcost!=numcost) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"The number of cost functions (2rd parameter of TSAdjointSetCostIntegrand()) is inconsistent with the one set by TSAdjointSetCostGradients()"); 2468 2469 ierr = VecCreateSeq(PETSC_COMM_SELF,numcost,&ts->vec_costintegral);CHKERRQ(ierr); 2470 ierr = VecDuplicate(ts->vec_costintegral,&ts->vec_costintegrand);CHKERRQ(ierr); 2471 ts->costintegrand = rf; 2472 ts->costintegrandctx = ctx; 2473 ts->drdyfunction = drdyf; 2474 ts->drdpfunction = drdpf; 2475 PetscFunctionReturn(0); 2476 } 2477 2478 #undef __FUNCT__ 2479 #define __FUNCT__ "TSAdjointGetCostIntegral" 2480 /*@ 2481 TSAdjointGetCostIntegral - Returns the values of the integral term in the cost functions. 2482 It is valid to call the routine after a backward run. 2483 2484 Not Collective 2485 2486 Input Parameter: 2487 . ts - the TS context obtained from TSCreate() 2488 2489 Output Parameter: 2490 . v - the vector containing the integrals for each cost function 2491 2492 Level: intermediate 2493 2494 .seealso: TSAdjointSetCostIntegrand() 2495 2496 .keywords: TS, sensitivity analysis 2497 @*/ 2498 PetscErrorCode TSAdjointGetCostIntegral(TS ts,Vec *v) 2499 { 2500 PetscFunctionBegin; 2501 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2502 PetscValidPointer(v,2); 2503 *v = ts->vec_costintegral; 2504 PetscFunctionReturn(0); 2505 } 2506 2507 #undef __FUNCT__ 2508 #define __FUNCT__ "TSAdjointComputeCostIntegrand" 2509 /*@ 2510 TSAdjointComputeCostIntegrand - Evaluates the integral function in the cost functions. 2511 2512 Input Parameters: 2513 + ts - the TS context 2514 . t - current time 2515 - y - state vector, i.e. current solution 2516 2517 Output Parameter: 2518 . q - vector of size numcost to hold the outputs 2519 2520 Note: 2521 Most users should not need to explicitly call this routine, as it 2522 is used internally within the sensitivity analysis context. 2523 2524 Level: developer 2525 2526 .keywords: TS, compute 2527 2528 .seealso: TSAdjointSetCostIntegrand() 2529 @*/ 2530 PetscErrorCode TSAdjointComputeCostIntegrand(TS ts,PetscReal t,Vec y,Vec q) 2531 { 2532 PetscErrorCode ierr; 2533 2534 PetscFunctionBegin; 2535 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2536 PetscValidHeaderSpecific(y,VEC_CLASSID,3); 2537 PetscValidHeaderSpecific(q,VEC_CLASSID,4); 2538 2539 ierr = PetscLogEventBegin(TS_FunctionEval,ts,y,q,0);CHKERRQ(ierr); 2540 if (ts->costintegrand) { 2541 PetscStackPush("TS user integrand in the cost function"); 2542 ierr = (*ts->costintegrand)(ts,t,y,q,ts->costintegrandctx);CHKERRQ(ierr); 2543 PetscStackPop; 2544 } else { 2545 ierr = VecZeroEntries(q);CHKERRQ(ierr); 2546 } 2547 2548 ierr = PetscLogEventEnd(TS_FunctionEval,ts,y,q,0);CHKERRQ(ierr); 2549 PetscFunctionReturn(0); 2550 } 2551 2552 #undef __FUNCT__ 2553 #define __FUNCT__ "TSAdjointComputeDRDYFunction" 2554 /*@ 2555 TSAdjointComputeDRDYFunction - Runs the user-defined DRDY function. 2556 2557 Collective on TS 2558 2559 Input Parameters: 2560 . ts - The TS context obtained from TSCreate() 2561 2562 Notes: 2563 TSAdjointComputeDRDYFunction() is typically used for sensitivity implementation, 2564 so most users would not generally call this routine themselves. 2565 2566 Level: developer 2567 2568 .keywords: TS, sensitivity 2569 .seealso: TSAdjointComputeDRDYFunction() 2570 @*/ 2571 PetscErrorCode TSAdjointComputeDRDYFunction(TS ts,PetscReal t,Vec y,Vec *drdy) 2572 { 2573 PetscErrorCode ierr; 2574 2575 PetscFunctionBegin; 2576 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2577 PetscValidHeaderSpecific(y,VEC_CLASSID,3); 2578 2579 PetscStackPush("TS user DRDY function for sensitivity analysis"); 2580 ierr = (*ts->drdyfunction)(ts,t,y,drdy,ts->costintegrandctx); CHKERRQ(ierr); 2581 PetscStackPop; 2582 PetscFunctionReturn(0); 2583 } 2584 2585 #undef __FUNCT__ 2586 #define __FUNCT__ "TSAdjointComputeDRDPFunction" 2587 /*@ 2588 TSAdjointComputeDRDPFunction - Runs the user-defined DRDP function. 2589 2590 Collective on TS 2591 2592 Input Parameters: 2593 . ts - The TS context obtained from TSCreate() 2594 2595 Notes: 2596 TSDRDPFunction() is typically used for sensitivity implementation, 2597 so most users would not generally call this routine themselves. 2598 2599 Level: developer 2600 2601 .keywords: TS, sensitivity 2602 .seealso: TSAdjointSetDRDPFunction() 2603 @*/ 2604 PetscErrorCode TSAdjointComputeDRDPFunction(TS ts,PetscReal t,Vec y,Vec *drdp) 2605 { 2606 PetscErrorCode ierr; 2607 2608 PetscFunctionBegin; 2609 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2610 PetscValidHeaderSpecific(y,VEC_CLASSID,3); 2611 2612 PetscStackPush("TS user DRDP function for sensitivity analysis"); 2613 ierr = (*ts->drdpfunction)(ts,t,y,drdp,ts->costintegrandctx); CHKERRQ(ierr); 2614 PetscStackPop; 2615 PetscFunctionReturn(0); 2616 } 2617 2618 #undef __FUNCT__ 2619 #define __FUNCT__ "TSSetPreStep" 2620 /*@C 2621 TSSetPreStep - Sets the general-purpose function 2622 called once at the beginning of each time step. 2623 2624 Logically Collective on TS 2625 2626 Input Parameters: 2627 + ts - The TS context obtained from TSCreate() 2628 - func - The function 2629 2630 Calling sequence of func: 2631 . func (TS ts); 2632 2633 Level: intermediate 2634 2635 Note: 2636 If a step is rejected, TSStep() will call this routine again before each attempt. 2637 The last completed time step number can be queried using TSGetTimeStepNumber(), the 2638 size of the step being attempted can be obtained using TSGetTimeStep(). 2639 2640 .keywords: TS, timestep 2641 .seealso: TSSetPreStage(), TSSetPostStage(), TSSetPostStep(), TSStep() 2642 @*/ 2643 PetscErrorCode TSSetPreStep(TS ts, PetscErrorCode (*func)(TS)) 2644 { 2645 PetscFunctionBegin; 2646 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 2647 ts->prestep = func; 2648 PetscFunctionReturn(0); 2649 } 2650 2651 #undef __FUNCT__ 2652 #define __FUNCT__ "TSPreStep" 2653 /*@ 2654 TSPreStep - Runs the user-defined pre-step function. 2655 2656 Collective on TS 2657 2658 Input Parameters: 2659 . ts - The TS context obtained from TSCreate() 2660 2661 Notes: 2662 TSPreStep() is typically used within time stepping implementations, 2663 so most users would not generally call this routine themselves. 2664 2665 Level: developer 2666 2667 .keywords: TS, timestep 2668 .seealso: TSSetPreStep(), TSPreStage(), TSPostStage(), TSPostStep() 2669 @*/ 2670 PetscErrorCode TSPreStep(TS ts) 2671 { 2672 PetscErrorCode ierr; 2673 2674 PetscFunctionBegin; 2675 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2676 if (ts->prestep) { 2677 PetscStackCallStandard((*ts->prestep),(ts)); 2678 } 2679 PetscFunctionReturn(0); 2680 } 2681 2682 #undef __FUNCT__ 2683 #define __FUNCT__ "TSSetPreStage" 2684 /*@C 2685 TSSetPreStage - Sets the general-purpose function 2686 called once at the beginning of each stage. 2687 2688 Logically Collective on TS 2689 2690 Input Parameters: 2691 + ts - The TS context obtained from TSCreate() 2692 - func - The function 2693 2694 Calling sequence of func: 2695 . PetscErrorCode func(TS ts, PetscReal stagetime); 2696 2697 Level: intermediate 2698 2699 Note: 2700 There may be several stages per time step. If the solve for a given stage fails, the step may be rejected and retried. 2701 The time step number being computed can be queried using TSGetTimeStepNumber() and the total size of the step being 2702 attempted can be obtained using TSGetTimeStep(). The time at the start of the step is available via TSGetTime(). 2703 2704 .keywords: TS, timestep 2705 .seealso: TSSetPostStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext() 2706 @*/ 2707 PetscErrorCode TSSetPreStage(TS ts, PetscErrorCode (*func)(TS,PetscReal)) 2708 { 2709 PetscFunctionBegin; 2710 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 2711 ts->prestage = func; 2712 PetscFunctionReturn(0); 2713 } 2714 2715 #undef __FUNCT__ 2716 #define __FUNCT__ "TSSetPostStage" 2717 /*@C 2718 TSSetPostStage - Sets the general-purpose function 2719 called once at the end of each stage. 2720 2721 Logically Collective on TS 2722 2723 Input Parameters: 2724 + ts - The TS context obtained from TSCreate() 2725 - func - The function 2726 2727 Calling sequence of func: 2728 . PetscErrorCode func(TS ts, PetscReal stagetime, PetscInt stageindex, Vec* Y); 2729 2730 Level: intermediate 2731 2732 Note: 2733 There may be several stages per time step. If the solve for a given stage fails, the step may be rejected and retried. 2734 The time step number being computed can be queried using TSGetTimeStepNumber() and the total size of the step being 2735 attempted can be obtained using TSGetTimeStep(). The time at the start of the step is available via TSGetTime(). 2736 2737 .keywords: TS, timestep 2738 .seealso: TSSetPreStage(), TSSetPreStep(), TSSetPostStep(), TSGetApplicationContext() 2739 @*/ 2740 PetscErrorCode TSSetPostStage(TS ts, PetscErrorCode (*func)(TS,PetscReal,PetscInt,Vec*)) 2741 { 2742 PetscFunctionBegin; 2743 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 2744 ts->poststage = func; 2745 PetscFunctionReturn(0); 2746 } 2747 2748 #undef __FUNCT__ 2749 #define __FUNCT__ "TSPreStage" 2750 /*@ 2751 TSPreStage - Runs the user-defined pre-stage function set using TSSetPreStage() 2752 2753 Collective on TS 2754 2755 Input Parameters: 2756 . ts - The TS context obtained from TSCreate() 2757 stagetime - The absolute time of the current stage 2758 2759 Notes: 2760 TSPreStage() is typically used within time stepping implementations, 2761 most users would not generally call this routine themselves. 2762 2763 Level: developer 2764 2765 .keywords: TS, timestep 2766 .seealso: TSPostStage(), TSSetPreStep(), TSPreStep(), TSPostStep() 2767 @*/ 2768 PetscErrorCode TSPreStage(TS ts, PetscReal stagetime) 2769 { 2770 PetscErrorCode ierr; 2771 2772 PetscFunctionBegin; 2773 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2774 if (ts->prestage) { 2775 PetscStackCallStandard((*ts->prestage),(ts,stagetime)); 2776 } 2777 PetscFunctionReturn(0); 2778 } 2779 2780 #undef __FUNCT__ 2781 #define __FUNCT__ "TSPostStage" 2782 /*@ 2783 TSPostStage - Runs the user-defined post-stage function set using TSSetPostStage() 2784 2785 Collective on TS 2786 2787 Input Parameters: 2788 . ts - The TS context obtained from TSCreate() 2789 stagetime - The absolute time of the current stage 2790 stageindex - Stage number 2791 Y - Array of vectors (of size = total number 2792 of stages) with the stage solutions 2793 2794 Notes: 2795 TSPostStage() is typically used within time stepping implementations, 2796 most users would not generally call this routine themselves. 2797 2798 Level: developer 2799 2800 .keywords: TS, timestep 2801 .seealso: TSPreStage(), TSSetPreStep(), TSPreStep(), TSPostStep() 2802 @*/ 2803 PetscErrorCode TSPostStage(TS ts, PetscReal stagetime, PetscInt stageindex, Vec *Y) 2804 { 2805 PetscErrorCode ierr; 2806 2807 PetscFunctionBegin; 2808 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2809 if (ts->poststage) { 2810 PetscStackCallStandard((*ts->poststage),(ts,stagetime,stageindex,Y)); 2811 } 2812 PetscFunctionReturn(0); 2813 } 2814 2815 #undef __FUNCT__ 2816 #define __FUNCT__ "TSSetPostStep" 2817 /*@C 2818 TSSetPostStep - Sets the general-purpose function 2819 called once at the end of each time step. 2820 2821 Logically Collective on TS 2822 2823 Input Parameters: 2824 + ts - The TS context obtained from TSCreate() 2825 - func - The function 2826 2827 Calling sequence of func: 2828 $ func (TS ts); 2829 2830 Level: intermediate 2831 2832 .keywords: TS, timestep 2833 .seealso: TSSetPreStep(), TSSetPreStage(), TSGetTimeStep(), TSGetTimeStepNumber(), TSGetTime() 2834 @*/ 2835 PetscErrorCode TSSetPostStep(TS ts, PetscErrorCode (*func)(TS)) 2836 { 2837 PetscFunctionBegin; 2838 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 2839 ts->poststep = func; 2840 PetscFunctionReturn(0); 2841 } 2842 2843 #undef __FUNCT__ 2844 #define __FUNCT__ "TSPostStep" 2845 /*@ 2846 TSPostStep - Runs the user-defined post-step function. 2847 2848 Collective on TS 2849 2850 Input Parameters: 2851 . ts - The TS context obtained from TSCreate() 2852 2853 Notes: 2854 TSPostStep() is typically used within time stepping implementations, 2855 so most users would not generally call this routine themselves. 2856 2857 Level: developer 2858 2859 .keywords: TS, timestep 2860 @*/ 2861 PetscErrorCode TSPostStep(TS ts) 2862 { 2863 PetscErrorCode ierr; 2864 2865 PetscFunctionBegin; 2866 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2867 if (ts->poststep) { 2868 PetscStackCallStandard((*ts->poststep),(ts)); 2869 } 2870 PetscFunctionReturn(0); 2871 } 2872 2873 /* ------------ Routines to set performance monitoring options ----------- */ 2874 2875 #undef __FUNCT__ 2876 #define __FUNCT__ "TSMonitorSet" 2877 /*@C 2878 TSMonitorSet - Sets an ADDITIONAL function that is to be used at every 2879 timestep to display the iteration's progress. 2880 2881 Logically Collective on TS 2882 2883 Input Parameters: 2884 + ts - the TS context obtained from TSCreate() 2885 . monitor - monitoring routine 2886 . mctx - [optional] user-defined context for private data for the 2887 monitor routine (use NULL if no context is desired) 2888 - monitordestroy - [optional] routine that frees monitor context 2889 (may be NULL) 2890 2891 Calling sequence of monitor: 2892 $ int monitor(TS ts,PetscInt steps,PetscReal time,Vec u,void *mctx) 2893 2894 + ts - the TS context 2895 . 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 2896 been interpolated to) 2897 . time - current time 2898 . u - current iterate 2899 - mctx - [optional] monitoring context 2900 2901 Notes: 2902 This routine adds an additional monitor to the list of monitors that 2903 already has been loaded. 2904 2905 Fortran notes: Only a single monitor function can be set for each TS object 2906 2907 Level: intermediate 2908 2909 .keywords: TS, timestep, set, monitor 2910 2911 .seealso: TSMonitorDefault(), TSMonitorCancel() 2912 @*/ 2913 PetscErrorCode TSMonitorSet(TS ts,PetscErrorCode (*monitor)(TS,PetscInt,PetscReal,Vec,void*),void *mctx,PetscErrorCode (*mdestroy)(void**)) 2914 { 2915 PetscFunctionBegin; 2916 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2917 if (ts->numbermonitors >= MAXTSMONITORS) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Too many monitors set"); 2918 ts->monitor[ts->numbermonitors] = monitor; 2919 ts->monitordestroy[ts->numbermonitors] = mdestroy; 2920 ts->monitorcontext[ts->numbermonitors++] = (void*)mctx; 2921 PetscFunctionReturn(0); 2922 } 2923 2924 #undef __FUNCT__ 2925 #define __FUNCT__ "TSMonitorCancel" 2926 /*@C 2927 TSMonitorCancel - Clears all the monitors that have been set on a time-step object. 2928 2929 Logically Collective on TS 2930 2931 Input Parameters: 2932 . ts - the TS context obtained from TSCreate() 2933 2934 Notes: 2935 There is no way to remove a single, specific monitor. 2936 2937 Level: intermediate 2938 2939 .keywords: TS, timestep, set, monitor 2940 2941 .seealso: TSMonitorDefault(), TSMonitorSet() 2942 @*/ 2943 PetscErrorCode TSMonitorCancel(TS ts) 2944 { 2945 PetscErrorCode ierr; 2946 PetscInt i; 2947 2948 PetscFunctionBegin; 2949 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 2950 for (i=0; i<ts->numbermonitors; i++) { 2951 if (ts->monitordestroy[i]) { 2952 ierr = (*ts->monitordestroy[i])(&ts->monitorcontext[i]);CHKERRQ(ierr); 2953 } 2954 } 2955 ts->numbermonitors = 0; 2956 PetscFunctionReturn(0); 2957 } 2958 2959 #undef __FUNCT__ 2960 #define __FUNCT__ "TSMonitorDefault" 2961 /*@ 2962 TSMonitorDefault - Sets the Default monitor 2963 2964 Level: intermediate 2965 2966 .keywords: TS, set, monitor 2967 2968 .seealso: TSMonitorDefault(), TSMonitorSet() 2969 @*/ 2970 PetscErrorCode TSMonitorDefault(TS ts,PetscInt step,PetscReal ptime,Vec v,void *dummy) 2971 { 2972 PetscErrorCode ierr; 2973 PetscViewer viewer = dummy ? (PetscViewer) dummy : PETSC_VIEWER_STDOUT_(PetscObjectComm((PetscObject)ts)); 2974 2975 PetscFunctionBegin; 2976 ierr = PetscViewerASCIIAddTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 2977 ierr = PetscViewerASCIIPrintf(viewer,"%D TS dt %g time %g %s",step,(double)ts->time_step,(double)ptime,ts->steprollback ? "(r)\n" : "\n");CHKERRQ(ierr); 2978 ierr = PetscViewerASCIISubtractTab(viewer,((PetscObject)ts)->tablevel);CHKERRQ(ierr); 2979 PetscFunctionReturn(0); 2980 } 2981 2982 #undef __FUNCT__ 2983 #define __FUNCT__ "TSSetRetainStages" 2984 /*@ 2985 TSSetRetainStages - Request that all stages in the upcoming step be stored so that interpolation will be available. 2986 2987 Logically Collective on TS 2988 2989 Input Argument: 2990 . ts - time stepping context 2991 2992 Output Argument: 2993 . flg - PETSC_TRUE or PETSC_FALSE 2994 2995 Level: intermediate 2996 2997 .keywords: TS, set 2998 2999 .seealso: TSInterpolate(), TSSetPostStep() 3000 @*/ 3001 PetscErrorCode TSSetRetainStages(TS ts,PetscBool flg) 3002 { 3003 PetscFunctionBegin; 3004 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3005 ts->retain_stages = flg; 3006 PetscFunctionReturn(0); 3007 } 3008 3009 #undef __FUNCT__ 3010 #define __FUNCT__ "TSInterpolate" 3011 /*@ 3012 TSInterpolate - Interpolate the solution computed during the previous step to an arbitrary location in the interval 3013 3014 Collective on TS 3015 3016 Input Argument: 3017 + ts - time stepping context 3018 - t - time to interpolate to 3019 3020 Output Argument: 3021 . U - state at given time 3022 3023 Notes: 3024 The user should call TSSetRetainStages() before taking a step in which interpolation will be requested. 3025 3026 Level: intermediate 3027 3028 Developer Notes: 3029 TSInterpolate() and the storing of previous steps/stages should be generalized to support delay differential equations and continuous adjoints. 3030 3031 .keywords: TS, set 3032 3033 .seealso: TSSetRetainStages(), TSSetPostStep() 3034 @*/ 3035 PetscErrorCode TSInterpolate(TS ts,PetscReal t,Vec U) 3036 { 3037 PetscErrorCode ierr; 3038 3039 PetscFunctionBegin; 3040 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3041 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 3042 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); 3043 if (!ts->ops->interpolate) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"%s does not provide interpolation",((PetscObject)ts)->type_name); 3044 ierr = (*ts->ops->interpolate)(ts,t,U);CHKERRQ(ierr); 3045 PetscFunctionReturn(0); 3046 } 3047 3048 #undef __FUNCT__ 3049 #define __FUNCT__ "TSStep" 3050 /*@ 3051 TSStep - Steps one time step 3052 3053 Collective on TS 3054 3055 Input Parameter: 3056 . ts - the TS context obtained from TSCreate() 3057 3058 Level: developer 3059 3060 Notes: 3061 The public interface for the ODE/DAE solvers is TSSolve(), you should almost for sure be using that routine and not this routine. 3062 3063 The hook set using TSSetPreStep() is called before each attempt to take the step. In general, the time step size may 3064 be changed due to adaptive error controller or solve failures. Note that steps may contain multiple stages. 3065 3066 This may over-step the final time provided in TSSetDuration() depending on the time-step used. TSSolve() interpolates to exactly the 3067 time provided in TSSetDuration(). One can use TSInterpolate() to determine an interpolated solution within the final timestep. 3068 3069 .keywords: TS, timestep, solve 3070 3071 .seealso: TSCreate(), TSSetUp(), TSDestroy(), TSSolve(), TSSetPreStep(), TSSetPreStage(), TSSetPostStage(), TSInterpolate() 3072 @*/ 3073 PetscErrorCode TSStep(TS ts) 3074 { 3075 DM dm; 3076 PetscErrorCode ierr; 3077 static PetscBool cite = PETSC_FALSE; 3078 3079 PetscFunctionBegin; 3080 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3081 ierr = PetscCitationsRegister("@techreport{tspaper,\n" 3082 " title = {{PETSc/TS}: A Modern Scalable {DAE/ODE} Solver Library},\n" 3083 " author = {Shrirang Abhyankar and Jed Brown and Emil Constantinescu and Debojyoti Ghosh and Barry F. Smith},\n" 3084 " type = {Preprint},\n" 3085 " number = {ANL/MCS-P5061-0114},\n" 3086 " institution = {Argonne National Laboratory},\n" 3087 " year = {2014}\n}\n",&cite); 3088 3089 ierr = TSGetDM(ts, &dm);CHKERRQ(ierr); 3090 ierr = TSSetUp(ts);CHKERRQ(ierr); 3091 3092 ts->reason = TS_CONVERGED_ITERATING; 3093 ts->ptime_prev = ts->ptime; 3094 ierr = DMSetOutputSequenceNumber(dm, ts->steps, ts->ptime);CHKERRQ(ierr); 3095 3096 if (!ts->ops->step) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSStep not implemented for type '%s'",((PetscObject)ts)->type_name); 3097 ierr = PetscLogEventBegin(TS_Step,ts,0,0,0);CHKERRQ(ierr); 3098 ierr = (*ts->ops->step)(ts);CHKERRQ(ierr); 3099 ierr = PetscLogEventEnd(TS_Step,ts,0,0,0);CHKERRQ(ierr); 3100 3101 ts->time_step_prev = ts->ptime - ts->ptime_prev; 3102 ierr = DMSetOutputSequenceNumber(dm, ts->steps, ts->ptime);CHKERRQ(ierr); 3103 3104 if (ts->reason < 0) { 3105 if (ts->errorifstepfailed) { 3106 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]); 3107 else SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s",TSConvergedReasons[ts->reason]); 3108 } 3109 } else if (!ts->reason) { 3110 if (ts->steps >= ts->max_steps) ts->reason = TS_CONVERGED_ITS; 3111 else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME; 3112 } 3113 ts->total_steps++; 3114 ts->steprollback = PETSC_FALSE; 3115 PetscFunctionReturn(0); 3116 } 3117 3118 #undef __FUNCT__ 3119 #define __FUNCT__ "TSAdjointStep" 3120 /*@ 3121 TSAdjointStep - Steps one time step 3122 3123 Collective on TS 3124 3125 Input Parameter: 3126 . ts - the TS context obtained from TSCreate() 3127 3128 Level: intermediate 3129 3130 Notes: 3131 The hook set using TSSetPreStep() is called before each attempt to take the step. In general, the time step size may 3132 be changed due to adaptive error controller or solve failures. Note that steps may contain multiple stages. 3133 3134 This may over-step the final time provided in TSSetDuration() depending on the time-step used. TSSolve() interpolates to exactly the 3135 time provided in TSSetDuration(). One can use TSInterpolate() to determine an interpolated solution within the final timestep. 3136 3137 .keywords: TS, timestep, solve 3138 3139 .seealso: TSCreate(), TSSetUp(), TSDestroy(), TSSolve(), TSSetPreStep(), TSSetPreStage(), TSSetPostStage(), TSInterpolate() 3140 @*/ 3141 PetscErrorCode TSAdjointStep(TS ts) 3142 { 3143 DM dm; 3144 PetscErrorCode ierr; 3145 3146 PetscFunctionBegin; 3147 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 3148 ierr = TSGetDM(ts, &dm);CHKERRQ(ierr); 3149 ierr = TSAdjointSetUp(ts);CHKERRQ(ierr); 3150 3151 ts->reason = TS_CONVERGED_ITERATING; 3152 ts->ptime_prev = ts->ptime; 3153 ierr = DMSetOutputSequenceNumber(dm, ts->steps, ts->ptime);CHKERRQ(ierr); 3154 ierr = VecViewFromOptions(ts->vec_sol, ((PetscObject) ts)->prefix, "-ts_view_solution");CHKERRQ(ierr); 3155 3156 ierr = PetscLogEventBegin(TS_Step,ts,0,0,0);CHKERRQ(ierr); 3157 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); 3158 ierr = (*ts->ops->adjointstep)(ts);CHKERRQ(ierr); 3159 ierr = PetscLogEventEnd(TS_Step,ts,0,0,0);CHKERRQ(ierr); 3160 3161 ts->time_step_prev = ts->ptime - ts->ptime_prev; 3162 ierr = DMSetOutputSequenceNumber(dm, ts->steps, ts->ptime);CHKERRQ(ierr); 3163 3164 if (ts->reason < 0) { 3165 if (ts->errorifstepfailed) { 3166 if (ts->reason == TS_DIVERGED_NONLINEAR_SOLVE) { 3167 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]); 3168 } else if (ts->reason == TS_DIVERGED_STEP_REJECTED) { 3169 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]); 3170 } else SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_NOT_CONVERGED,"TSStep has failed due to %s",TSConvergedReasons[ts->reason]); 3171 } 3172 } else if (!ts->reason) { 3173 if (ts->steps >= ts->adjoint_max_steps) ts->reason = TS_CONVERGED_ITS; 3174 else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME; 3175 } 3176 ts->total_steps--; 3177 PetscFunctionReturn(0); 3178 } 3179 3180 #undef __FUNCT__ 3181 #define __FUNCT__ "TSEvaluateStep" 3182 /*@ 3183 TSEvaluateStep - Evaluate the solution at the end of a time step with a given order of accuracy. 3184 3185 Collective on TS 3186 3187 Input Arguments: 3188 + ts - time stepping context 3189 . order - desired order of accuracy 3190 - done - whether the step was evaluated at this order (pass NULL to generate an error if not available) 3191 3192 Output Arguments: 3193 . U - state at the end of the current step 3194 3195 Level: advanced 3196 3197 Notes: 3198 This function cannot be called until all stages have been evaluated. 3199 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. 3200 3201 .seealso: TSStep(), TSAdapt 3202 @*/ 3203 PetscErrorCode TSEvaluateStep(TS ts,PetscInt order,Vec U,PetscBool *done) 3204 { 3205 PetscErrorCode ierr; 3206 3207 PetscFunctionBegin; 3208 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3209 PetscValidType(ts,1); 3210 PetscValidHeaderSpecific(U,VEC_CLASSID,3); 3211 if (!ts->ops->evaluatestep) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSEvaluateStep not implemented for type '%s'",((PetscObject)ts)->type_name); 3212 ierr = (*ts->ops->evaluatestep)(ts,order,U,done);CHKERRQ(ierr); 3213 PetscFunctionReturn(0); 3214 } 3215 3216 3217 #undef __FUNCT__ 3218 #define __FUNCT__ "TSSolve" 3219 /*@ 3220 TSSolve - Steps the requested number of timesteps. 3221 3222 Collective on TS 3223 3224 Input Parameter: 3225 + ts - the TS context obtained from TSCreate() 3226 - u - the solution vector (can be null if TSSetSolution() was used, otherwise must contain the initial conditions) 3227 3228 Level: beginner 3229 3230 Notes: 3231 The final time returned by this function may be different from the time of the internally 3232 held state accessible by TSGetSolution() and TSGetTime() because the method may have 3233 stepped over the final time. 3234 3235 .keywords: TS, timestep, solve 3236 3237 .seealso: TSCreate(), TSSetSolution(), TSStep() 3238 @*/ 3239 PetscErrorCode TSSolve(TS ts,Vec u) 3240 { 3241 Vec solution; 3242 PetscErrorCode ierr; 3243 3244 PetscFunctionBegin; 3245 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3246 if (u) PetscValidHeaderSpecific(u,VEC_CLASSID,2); 3247 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 */ 3248 PetscValidHeaderSpecific(u,VEC_CLASSID,2); 3249 if (!ts->vec_sol || u == ts->vec_sol) { 3250 ierr = VecDuplicate(u,&solution);CHKERRQ(ierr); 3251 ierr = TSSetSolution(ts,solution);CHKERRQ(ierr); 3252 ierr = VecDestroy(&solution);CHKERRQ(ierr); /* grant ownership */ 3253 } 3254 ierr = VecCopy(u,ts->vec_sol);CHKERRQ(ierr); 3255 } else if (u) { 3256 ierr = TSSetSolution(ts,u);CHKERRQ(ierr); 3257 } 3258 ierr = TSSetUp(ts);CHKERRQ(ierr); 3259 /* reset time step and iteration counters */ 3260 ts->steps = 0; 3261 ts->ksp_its = 0; 3262 ts->snes_its = 0; 3263 ts->num_snes_failures = 0; 3264 ts->reject = 0; 3265 ts->reason = TS_CONVERGED_ITERATING; 3266 3267 ierr = TSViewFromOptions(ts,NULL,"-ts_view_pre");CHKERRQ(ierr); 3268 { 3269 DM dm; 3270 ierr = TSGetDM(ts, &dm);CHKERRQ(ierr); 3271 ierr = DMSetOutputSequenceNumber(dm, ts->steps, ts->ptime);CHKERRQ(ierr); 3272 } 3273 3274 if (ts->ops->solve) { /* This private interface is transitional and should be removed when all implementations are updated. */ 3275 ierr = (*ts->ops->solve)(ts);CHKERRQ(ierr); 3276 ierr = VecCopy(ts->vec_sol,u);CHKERRQ(ierr); 3277 ts->solvetime = ts->ptime; 3278 } else { 3279 /* steps the requested number of timesteps. */ 3280 if (ts->steps >= ts->max_steps) ts->reason = TS_CONVERGED_ITS; 3281 else if (ts->ptime >= ts->max_time) ts->reason = TS_CONVERGED_TIME; 3282 ierr = TSTrajectorySet(ts->trajectory,ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 3283 if(ts->event) { 3284 ierr = TSEventMonitorInitialize(ts);CHKERRQ(ierr); 3285 } 3286 while (!ts->reason) { 3287 ierr = TSMonitor(ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 3288 ierr = TSStep(ts);CHKERRQ(ierr); 3289 if (ts->event) { 3290 ierr = TSEventMonitor(ts);CHKERRQ(ierr); 3291 } 3292 if(!ts->steprollback) { 3293 ierr = TSTrajectorySet(ts->trajectory,ts,ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 3294 ierr = TSPostStep(ts);CHKERRQ(ierr); 3295 } 3296 } 3297 if (ts->exact_final_time == TS_EXACTFINALTIME_INTERPOLATE && ts->ptime > ts->max_time) { 3298 ierr = TSInterpolate(ts,ts->max_time,u);CHKERRQ(ierr); 3299 ts->solvetime = ts->max_time; 3300 solution = u; 3301 } else { 3302 if (u) {ierr = VecCopy(ts->vec_sol,u);CHKERRQ(ierr);} 3303 ts->solvetime = ts->ptime; 3304 solution = ts->vec_sol; 3305 } 3306 ierr = TSMonitor(ts,ts->steps,ts->solvetime,solution);CHKERRQ(ierr); 3307 ierr = VecViewFromOptions(solution, ((PetscObject) ts)->prefix, "-ts_view_solution");CHKERRQ(ierr); 3308 } 3309 3310 ierr = TSViewFromOptions(ts,NULL,"-ts_view");CHKERRQ(ierr); 3311 ierr = PetscObjectSAWsBlock((PetscObject)ts);CHKERRQ(ierr); 3312 if (ts->adjoint_solve) { 3313 ierr = TSAdjointSolve(ts);CHKERRQ(ierr); 3314 } 3315 PetscFunctionReturn(0); 3316 } 3317 3318 #undef __FUNCT__ 3319 #define __FUNCT__ "TSAdjointSolve" 3320 /*@ 3321 TSAdjointSolve - Solves the discrete ajoint problem for an ODE/DAE 3322 3323 Collective on TS 3324 3325 Input Parameter: 3326 . ts - the TS context obtained from TSCreate() 3327 3328 Options Database: 3329 . -ts_adjoint_view_solution <viewerinfo> - views the first gradient with respect to the initial conditions 3330 3331 Level: intermediate 3332 3333 Notes: 3334 This must be called after a call to TSSolve() that solves the forward problem 3335 3336 By default this will integrate back to the initial time, one can use TSAdjointSetSteps() to step back to a later time 3337 3338 .keywords: TS, timestep, solve 3339 3340 .seealso: TSCreate(), TSSetSolution(), TSStep() 3341 @*/ 3342 PetscErrorCode TSAdjointSolve(TS ts) 3343 { 3344 PetscErrorCode ierr; 3345 3346 PetscFunctionBegin; 3347 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3348 ierr = TSAdjointSetUp(ts);CHKERRQ(ierr); 3349 /* reset time step and iteration counters */ 3350 ts->steps = 0; 3351 ts->ksp_its = 0; 3352 ts->snes_its = 0; 3353 ts->num_snes_failures = 0; 3354 ts->reject = 0; 3355 ts->reason = TS_CONVERGED_ITERATING; 3356 3357 if (!ts->adjoint_max_steps) ts->adjoint_max_steps = ts->total_steps; 3358 3359 if (ts->steps >= ts->adjoint_max_steps) ts->reason = TS_CONVERGED_ITS; 3360 while (!ts->reason) { 3361 ierr = TSTrajectoryGet(ts->trajectory,ts,ts->adjoint_max_steps-ts->steps,ts->ptime);CHKERRQ(ierr); 3362 ierr = TSMonitor(ts,ts->adjoint_max_steps-ts->steps,ts->ptime,ts->vec_sol);CHKERRQ(ierr); 3363 ierr = TSAdjointStep(ts);CHKERRQ(ierr); 3364 if (ts->event) { 3365 ierr = TSAdjointEventMonitor(ts);CHKERRQ(ierr); 3366 } 3367 3368 #if 0 /* I don't think PostStep is needed in AdjointSolve */ 3369 if (ts->event->status != TSEVENT_PROCESSING) { 3370 ierr = TSPostStep(ts);CHKERRQ(ierr); 3371 } 3372 } else { 3373 ierr = TSPostStep(ts);CHKERRQ(ierr); 3374 } 3375 #endif 3376 } 3377 ts->solvetime = ts->ptime; 3378 ierr = VecViewFromOptions(ts->vecs_sensi[0], ((PetscObject) ts)->prefix, "-ts_adjoint_view_solution");CHKERRQ(ierr); 3379 PetscFunctionReturn(0); 3380 } 3381 3382 #undef __FUNCT__ 3383 #define __FUNCT__ "TSMonitor" 3384 /*@ 3385 TSMonitor - Runs all user-provided monitor routines set using TSMonitorSet() 3386 3387 Collective on TS 3388 3389 Input Parameters: 3390 + ts - time stepping context obtained from TSCreate() 3391 . step - step number that has just completed 3392 . ptime - model time of the state 3393 - u - state at the current model time 3394 3395 Notes: 3396 TSMonitor() is typically used within the time stepping implementations. 3397 Users might call this function when using the TSStep() interface instead of TSSolve(). 3398 3399 Level: advanced 3400 3401 .keywords: TS, timestep 3402 @*/ 3403 PetscErrorCode TSMonitor(TS ts,PetscInt step,PetscReal ptime,Vec u) 3404 { 3405 PetscErrorCode ierr; 3406 PetscInt i,n = ts->numbermonitors; 3407 3408 PetscFunctionBegin; 3409 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3410 PetscValidHeaderSpecific(u,VEC_CLASSID,4); 3411 ierr = VecLockPush(u);CHKERRQ(ierr); 3412 for (i=0; i<n; i++) { 3413 ierr = (*ts->monitor[i])(ts,step,ptime,u,ts->monitorcontext[i]);CHKERRQ(ierr); 3414 } 3415 ierr = VecLockPop(u);CHKERRQ(ierr); 3416 PetscFunctionReturn(0); 3417 } 3418 3419 /* ------------------------------------------------------------------------*/ 3420 #undef __FUNCT__ 3421 #define __FUNCT__ "TSMonitorLGCtxCreate" 3422 /*@C 3423 TSMonitorLGCtxCreate - Creates a line graph context for use with 3424 TS to monitor the solution process graphically in various ways 3425 3426 Collective on TS 3427 3428 Input Parameters: 3429 + host - the X display to open, or null for the local machine 3430 . label - the title to put in the title bar 3431 . x, y - the screen coordinates of the upper left coordinate of the window 3432 . m, n - the screen width and height in pixels 3433 - howoften - if positive then determines the frequency of the plotting, if -1 then only at the final time 3434 3435 Output Parameter: 3436 . ctx - the context 3437 3438 Options Database Key: 3439 + -ts_monitor_lg_timestep - automatically sets line graph monitor 3440 . -ts_monitor_lg_solution - 3441 . -ts_monitor_lg_error - 3442 . -ts_monitor_lg_ksp_iterations - 3443 . -ts_monitor_lg_snes_iterations - 3444 - -lg_indicate_data_points <true,false> - indicate the data points (at each time step) on the plot; default is true 3445 3446 Notes: 3447 Use TSMonitorLGCtxDestroy() to destroy. 3448 3449 Level: intermediate 3450 3451 .keywords: TS, monitor, line graph, residual, seealso 3452 3453 .seealso: TSMonitorLGTimeStep(), TSMonitorSet(), TSMonitorLGSolution(), TSMonitorLGError() 3454 3455 @*/ 3456 PetscErrorCode TSMonitorLGCtxCreate(MPI_Comm comm,const char host[],const char label[],int x,int y,int m,int n,PetscInt howoften,TSMonitorLGCtx *ctx) 3457 { 3458 PetscDraw win; 3459 PetscErrorCode ierr; 3460 3461 PetscFunctionBegin; 3462 ierr = PetscNew(ctx);CHKERRQ(ierr); 3463 ierr = PetscDrawCreate(comm,host,label,x,y,m,n,&win);CHKERRQ(ierr); 3464 ierr = PetscDrawSetFromOptions(win);CHKERRQ(ierr); 3465 ierr = PetscDrawLGCreate(win,1,&(*ctx)->lg);CHKERRQ(ierr); 3466 ierr = PetscLogObjectParent((PetscObject)(*ctx)->lg,(PetscObject)win);CHKERRQ(ierr); 3467 ierr = PetscDrawLGIndicateDataPoints((*ctx)->lg,PETSC_TRUE);CHKERRQ(ierr); 3468 ierr = PetscDrawLGSetFromOptions((*ctx)->lg);CHKERRQ(ierr); 3469 (*ctx)->howoften = howoften; 3470 PetscFunctionReturn(0); 3471 } 3472 3473 #undef __FUNCT__ 3474 #define __FUNCT__ "TSMonitorLGTimeStep" 3475 PetscErrorCode TSMonitorLGTimeStep(TS ts,PetscInt step,PetscReal ptime,Vec v,void *monctx) 3476 { 3477 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 3478 PetscReal x = ptime,y; 3479 PetscErrorCode ierr; 3480 3481 PetscFunctionBegin; 3482 if (!step) { 3483 PetscDrawAxis axis; 3484 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 3485 ierr = PetscDrawAxisSetLabels(axis,"Timestep as function of time","Time","Time step");CHKERRQ(ierr); 3486 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 3487 ierr = PetscDrawLGIndicateDataPoints(ctx->lg,PETSC_TRUE);CHKERRQ(ierr); 3488 } 3489 ierr = TSGetTimeStep(ts,&y);CHKERRQ(ierr); 3490 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 3491 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 3492 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 3493 } 3494 PetscFunctionReturn(0); 3495 } 3496 3497 #undef __FUNCT__ 3498 #define __FUNCT__ "TSMonitorLGCtxDestroy" 3499 /*@C 3500 TSMonitorLGCtxDestroy - Destroys a line graph context that was created 3501 with TSMonitorLGCtxCreate(). 3502 3503 Collective on TSMonitorLGCtx 3504 3505 Input Parameter: 3506 . ctx - the monitor context 3507 3508 Level: intermediate 3509 3510 .keywords: TS, monitor, line graph, destroy 3511 3512 .seealso: TSMonitorLGCtxCreate(), TSMonitorSet(), TSMonitorLGTimeStep(); 3513 @*/ 3514 PetscErrorCode TSMonitorLGCtxDestroy(TSMonitorLGCtx *ctx) 3515 { 3516 PetscDraw draw; 3517 PetscErrorCode ierr; 3518 3519 PetscFunctionBegin; 3520 if ((*ctx)->transformdestroy) { 3521 ierr = ((*ctx)->transformdestroy)((*ctx)->transformctx);CHKERRQ(ierr); 3522 } 3523 ierr = PetscDrawLGGetDraw((*ctx)->lg,&draw);CHKERRQ(ierr); 3524 ierr = PetscDrawDestroy(&draw);CHKERRQ(ierr); 3525 ierr = PetscDrawLGDestroy(&(*ctx)->lg);CHKERRQ(ierr); 3526 ierr = PetscStrArrayDestroy(&(*ctx)->names);CHKERRQ(ierr); 3527 ierr = PetscStrArrayDestroy(&(*ctx)->displaynames);CHKERRQ(ierr); 3528 ierr = PetscFree((*ctx)->displayvariables);CHKERRQ(ierr); 3529 ierr = PetscFree((*ctx)->displayvalues);CHKERRQ(ierr); 3530 ierr = PetscFree(*ctx);CHKERRQ(ierr); 3531 PetscFunctionReturn(0); 3532 } 3533 3534 #undef __FUNCT__ 3535 #define __FUNCT__ "TSGetTime" 3536 /*@ 3537 TSGetTime - Gets the time of the most recently completed step. 3538 3539 Not Collective 3540 3541 Input Parameter: 3542 . ts - the TS context obtained from TSCreate() 3543 3544 Output Parameter: 3545 . t - the current time 3546 3547 Level: beginner 3548 3549 Note: 3550 When called during time step evaluation (e.g. during residual evaluation or via hooks set using TSSetPreStep(), 3551 TSSetPreStage(), TSSetPostStage(), or TSSetPostStep()), the time is the time at the start of the step being evaluated. 3552 3553 .seealso: TSSetInitialTimeStep(), TSGetTimeStep() 3554 3555 .keywords: TS, get, time 3556 @*/ 3557 PetscErrorCode TSGetTime(TS ts,PetscReal *t) 3558 { 3559 PetscFunctionBegin; 3560 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3561 PetscValidRealPointer(t,2); 3562 *t = ts->ptime; 3563 PetscFunctionReturn(0); 3564 } 3565 3566 #undef __FUNCT__ 3567 #define __FUNCT__ "TSGetPrevTime" 3568 /*@ 3569 TSGetPrevTime - Gets the starting time of the previously completed step. 3570 3571 Not Collective 3572 3573 Input Parameter: 3574 . ts - the TS context obtained from TSCreate() 3575 3576 Output Parameter: 3577 . t - the previous time 3578 3579 Level: beginner 3580 3581 .seealso: TSSetInitialTimeStep(), TSGetTimeStep() 3582 3583 .keywords: TS, get, time 3584 @*/ 3585 PetscErrorCode TSGetPrevTime(TS ts,PetscReal *t) 3586 { 3587 PetscFunctionBegin; 3588 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3589 PetscValidRealPointer(t,2); 3590 *t = ts->ptime_prev; 3591 PetscFunctionReturn(0); 3592 } 3593 3594 #undef __FUNCT__ 3595 #define __FUNCT__ "TSSetTime" 3596 /*@ 3597 TSSetTime - Allows one to reset the time. 3598 3599 Logically Collective on TS 3600 3601 Input Parameters: 3602 + ts - the TS context obtained from TSCreate() 3603 - time - the time 3604 3605 Level: intermediate 3606 3607 .seealso: TSGetTime(), TSSetDuration() 3608 3609 .keywords: TS, set, time 3610 @*/ 3611 PetscErrorCode TSSetTime(TS ts, PetscReal t) 3612 { 3613 PetscFunctionBegin; 3614 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3615 PetscValidLogicalCollectiveReal(ts,t,2); 3616 ts->ptime = t; 3617 PetscFunctionReturn(0); 3618 } 3619 3620 #undef __FUNCT__ 3621 #define __FUNCT__ "TSSetOptionsPrefix" 3622 /*@C 3623 TSSetOptionsPrefix - Sets the prefix used for searching for all 3624 TS options in the database. 3625 3626 Logically Collective on TS 3627 3628 Input Parameter: 3629 + ts - The TS context 3630 - prefix - The prefix to prepend to all option names 3631 3632 Notes: 3633 A hyphen (-) must NOT be given at the beginning of the prefix name. 3634 The first character of all runtime options is AUTOMATICALLY the 3635 hyphen. 3636 3637 Level: advanced 3638 3639 .keywords: TS, set, options, prefix, database 3640 3641 .seealso: TSSetFromOptions() 3642 3643 @*/ 3644 PetscErrorCode TSSetOptionsPrefix(TS ts,const char prefix[]) 3645 { 3646 PetscErrorCode ierr; 3647 SNES snes; 3648 3649 PetscFunctionBegin; 3650 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3651 ierr = PetscObjectSetOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 3652 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 3653 ierr = SNESSetOptionsPrefix(snes,prefix);CHKERRQ(ierr); 3654 PetscFunctionReturn(0); 3655 } 3656 3657 3658 #undef __FUNCT__ 3659 #define __FUNCT__ "TSAppendOptionsPrefix" 3660 /*@C 3661 TSAppendOptionsPrefix - Appends to the prefix used for searching for all 3662 TS options in the database. 3663 3664 Logically Collective on TS 3665 3666 Input Parameter: 3667 + ts - The TS context 3668 - prefix - The prefix to prepend to all option names 3669 3670 Notes: 3671 A hyphen (-) must NOT be given at the beginning of the prefix name. 3672 The first character of all runtime options is AUTOMATICALLY the 3673 hyphen. 3674 3675 Level: advanced 3676 3677 .keywords: TS, append, options, prefix, database 3678 3679 .seealso: TSGetOptionsPrefix() 3680 3681 @*/ 3682 PetscErrorCode TSAppendOptionsPrefix(TS ts,const char prefix[]) 3683 { 3684 PetscErrorCode ierr; 3685 SNES snes; 3686 3687 PetscFunctionBegin; 3688 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3689 ierr = PetscObjectAppendOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 3690 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 3691 ierr = SNESAppendOptionsPrefix(snes,prefix);CHKERRQ(ierr); 3692 PetscFunctionReturn(0); 3693 } 3694 3695 #undef __FUNCT__ 3696 #define __FUNCT__ "TSGetOptionsPrefix" 3697 /*@C 3698 TSGetOptionsPrefix - Sets the prefix used for searching for all 3699 TS options in the database. 3700 3701 Not Collective 3702 3703 Input Parameter: 3704 . ts - The TS context 3705 3706 Output Parameter: 3707 . prefix - A pointer to the prefix string used 3708 3709 Notes: On the fortran side, the user should pass in a string 'prifix' of 3710 sufficient length to hold the prefix. 3711 3712 Level: intermediate 3713 3714 .keywords: TS, get, options, prefix, database 3715 3716 .seealso: TSAppendOptionsPrefix() 3717 @*/ 3718 PetscErrorCode TSGetOptionsPrefix(TS ts,const char *prefix[]) 3719 { 3720 PetscErrorCode ierr; 3721 3722 PetscFunctionBegin; 3723 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 3724 PetscValidPointer(prefix,2); 3725 ierr = PetscObjectGetOptionsPrefix((PetscObject)ts,prefix);CHKERRQ(ierr); 3726 PetscFunctionReturn(0); 3727 } 3728 3729 #undef __FUNCT__ 3730 #define __FUNCT__ "TSGetRHSJacobian" 3731 /*@C 3732 TSGetRHSJacobian - Returns the Jacobian J at the present timestep. 3733 3734 Not Collective, but parallel objects are returned if TS is parallel 3735 3736 Input Parameter: 3737 . ts - The TS context obtained from TSCreate() 3738 3739 Output Parameters: 3740 + Amat - The (approximate) Jacobian J of G, where U_t = G(U,t) (or NULL) 3741 . Pmat - The matrix from which the preconditioner is constructed, usually the same as Amat (or NULL) 3742 . func - Function to compute the Jacobian of the RHS (or NULL) 3743 - ctx - User-defined context for Jacobian evaluation routine (or NULL) 3744 3745 Notes: You can pass in NULL for any return argument you do not need. 3746 3747 Level: intermediate 3748 3749 .seealso: TSGetTimeStep(), TSGetMatrices(), TSGetTime(), TSGetTimeStepNumber() 3750 3751 .keywords: TS, timestep, get, matrix, Jacobian 3752 @*/ 3753 PetscErrorCode TSGetRHSJacobian(TS ts,Mat *Amat,Mat *Pmat,TSRHSJacobian *func,void **ctx) 3754 { 3755 PetscErrorCode ierr; 3756 SNES snes; 3757 DM dm; 3758 3759 PetscFunctionBegin; 3760 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 3761 ierr = SNESGetJacobian(snes,Amat,Pmat,NULL,NULL);CHKERRQ(ierr); 3762 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 3763 ierr = DMTSGetRHSJacobian(dm,func,ctx);CHKERRQ(ierr); 3764 PetscFunctionReturn(0); 3765 } 3766 3767 #undef __FUNCT__ 3768 #define __FUNCT__ "TSGetIJacobian" 3769 /*@C 3770 TSGetIJacobian - Returns the implicit Jacobian at the present timestep. 3771 3772 Not Collective, but parallel objects are returned if TS is parallel 3773 3774 Input Parameter: 3775 . ts - The TS context obtained from TSCreate() 3776 3777 Output Parameters: 3778 + Amat - The (approximate) Jacobian of F(t,U,U_t) 3779 . Pmat - The matrix from which the preconditioner is constructed, often the same as Amat 3780 . f - The function to compute the matrices 3781 - ctx - User-defined context for Jacobian evaluation routine 3782 3783 Notes: You can pass in NULL for any return argument you do not need. 3784 3785 Level: advanced 3786 3787 .seealso: TSGetTimeStep(), TSGetRHSJacobian(), TSGetMatrices(), TSGetTime(), TSGetTimeStepNumber() 3788 3789 .keywords: TS, timestep, get, matrix, Jacobian 3790 @*/ 3791 PetscErrorCode TSGetIJacobian(TS ts,Mat *Amat,Mat *Pmat,TSIJacobian *f,void **ctx) 3792 { 3793 PetscErrorCode ierr; 3794 SNES snes; 3795 DM dm; 3796 3797 PetscFunctionBegin; 3798 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 3799 ierr = SNESSetUpMatrices(snes);CHKERRQ(ierr); 3800 ierr = SNESGetJacobian(snes,Amat,Pmat,NULL,NULL);CHKERRQ(ierr); 3801 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 3802 ierr = DMTSGetIJacobian(dm,f,ctx);CHKERRQ(ierr); 3803 PetscFunctionReturn(0); 3804 } 3805 3806 3807 #undef __FUNCT__ 3808 #define __FUNCT__ "TSMonitorDrawSolution" 3809 /*@C 3810 TSMonitorDrawSolution - Monitors progress of the TS solvers by calling 3811 VecView() for the solution at each timestep 3812 3813 Collective on TS 3814 3815 Input Parameters: 3816 + ts - the TS context 3817 . step - current time-step 3818 . ptime - current time 3819 - dummy - either a viewer or NULL 3820 3821 Options Database: 3822 . -ts_monitor_draw_solution_initial - show initial solution as well as current solution 3823 3824 Notes: the initial solution and current solution are not display with a common axis scaling so generally the option -ts_monitor_draw_solution_initial 3825 will look bad 3826 3827 Level: intermediate 3828 3829 .keywords: TS, vector, monitor, view 3830 3831 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 3832 @*/ 3833 PetscErrorCode TSMonitorDrawSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 3834 { 3835 PetscErrorCode ierr; 3836 TSMonitorDrawCtx ictx = (TSMonitorDrawCtx)dummy; 3837 PetscDraw draw; 3838 3839 PetscFunctionBegin; 3840 if (!step && ictx->showinitial) { 3841 if (!ictx->initialsolution) { 3842 ierr = VecDuplicate(u,&ictx->initialsolution);CHKERRQ(ierr); 3843 } 3844 ierr = VecCopy(u,ictx->initialsolution);CHKERRQ(ierr); 3845 } 3846 if (!(((ictx->howoften > 0) && (!(step % ictx->howoften))) || ((ictx->howoften == -1) && ts->reason))) PetscFunctionReturn(0); 3847 3848 if (ictx->showinitial) { 3849 PetscReal pause; 3850 ierr = PetscViewerDrawGetPause(ictx->viewer,&pause);CHKERRQ(ierr); 3851 ierr = PetscViewerDrawSetPause(ictx->viewer,0.0);CHKERRQ(ierr); 3852 ierr = VecView(ictx->initialsolution,ictx->viewer);CHKERRQ(ierr); 3853 ierr = PetscViewerDrawSetPause(ictx->viewer,pause);CHKERRQ(ierr); 3854 ierr = PetscViewerDrawSetHold(ictx->viewer,PETSC_TRUE);CHKERRQ(ierr); 3855 } 3856 ierr = VecView(u,ictx->viewer);CHKERRQ(ierr); 3857 if (ictx->showtimestepandtime) { 3858 PetscReal xl,yl,xr,yr,h; 3859 char time[32]; 3860 3861 ierr = PetscViewerDrawGetDraw(ictx->viewer,0,&draw);CHKERRQ(ierr); 3862 ierr = PetscSNPrintf(time,32,"Timestep %d Time %g",(int)step,(double)ptime);CHKERRQ(ierr); 3863 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 3864 h = yl + .95*(yr - yl); 3865 ierr = PetscDrawStringCentered(draw,.5*(xl+xr),h,PETSC_DRAW_BLACK,time);CHKERRQ(ierr); 3866 ierr = PetscDrawFlush(draw);CHKERRQ(ierr); 3867 } 3868 3869 if (ictx->showinitial) { 3870 ierr = PetscViewerDrawSetHold(ictx->viewer,PETSC_FALSE);CHKERRQ(ierr); 3871 } 3872 PetscFunctionReturn(0); 3873 } 3874 3875 #undef __FUNCT__ 3876 #define __FUNCT__ "TSMonitorDrawSolutionPhase" 3877 /*@C 3878 TSMonitorDrawSolutionPhase - Monitors progress of the TS solvers by plotting the solution as a phase diagram 3879 3880 Collective on TS 3881 3882 Input Parameters: 3883 + ts - the TS context 3884 . step - current time-step 3885 . ptime - current time 3886 - dummy - either a viewer or NULL 3887 3888 Level: intermediate 3889 3890 .keywords: TS, vector, monitor, view 3891 3892 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 3893 @*/ 3894 PetscErrorCode TSMonitorDrawSolutionPhase(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 3895 { 3896 PetscErrorCode ierr; 3897 TSMonitorDrawCtx ictx = (TSMonitorDrawCtx)dummy; 3898 PetscDraw draw; 3899 MPI_Comm comm; 3900 PetscInt n; 3901 PetscMPIInt size; 3902 PetscReal xl,yl,xr,yr,h; 3903 char time[32]; 3904 const PetscScalar *U; 3905 3906 PetscFunctionBegin; 3907 ierr = PetscObjectGetComm((PetscObject)ts,&comm);CHKERRQ(ierr); 3908 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3909 if (size != 1) SETERRQ(comm,PETSC_ERR_SUP,"Only allowed for sequential runs"); 3910 ierr = VecGetSize(u,&n);CHKERRQ(ierr); 3911 if (n != 2) SETERRQ(comm,PETSC_ERR_SUP,"Only for ODEs with two unknowns"); 3912 3913 ierr = PetscViewerDrawGetDraw(ictx->viewer,0,&draw);CHKERRQ(ierr); 3914 3915 ierr = VecGetArrayRead(u,&U);CHKERRQ(ierr); 3916 ierr = PetscDrawAxisGetLimits(ictx->axis,&xl,&xr,&yl,&yr);CHKERRQ(ierr); 3917 if ((PetscRealPart(U[0]) < xl) || (PetscRealPart(U[1]) < yl) || (PetscRealPart(U[0]) > xr) || (PetscRealPart(U[1]) > yr)) { 3918 ierr = VecRestoreArrayRead(u,&U);CHKERRQ(ierr); 3919 PetscFunctionReturn(0); 3920 } 3921 if (!step) ictx->color++; 3922 ierr = PetscDrawPoint(draw,PetscRealPart(U[0]),PetscRealPart(U[1]),ictx->color);CHKERRQ(ierr); 3923 ierr = VecRestoreArrayRead(u,&U);CHKERRQ(ierr); 3924 3925 if (ictx->showtimestepandtime) { 3926 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 3927 ierr = PetscSNPrintf(time,32,"Timestep %d Time %g",(int)step,(double)ptime);CHKERRQ(ierr); 3928 h = yl + .95*(yr - yl); 3929 ierr = PetscDrawStringCentered(draw,.5*(xl+xr),h,PETSC_DRAW_BLACK,time);CHKERRQ(ierr); 3930 } 3931 ierr = PetscDrawFlush(draw);CHKERRQ(ierr); 3932 PetscFunctionReturn(0); 3933 } 3934 3935 3936 #undef __FUNCT__ 3937 #define __FUNCT__ "TSMonitorDrawCtxDestroy" 3938 /*@C 3939 TSMonitorDrawCtxDestroy - Destroys the monitor context for TSMonitorDrawSolution() 3940 3941 Collective on TS 3942 3943 Input Parameters: 3944 . ctx - the monitor context 3945 3946 Level: intermediate 3947 3948 .keywords: TS, vector, monitor, view 3949 3950 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorDrawSolution(), TSMonitorDrawError() 3951 @*/ 3952 PetscErrorCode TSMonitorDrawCtxDestroy(TSMonitorDrawCtx *ictx) 3953 { 3954 PetscErrorCode ierr; 3955 3956 PetscFunctionBegin; 3957 ierr = PetscDrawAxisDestroy(&(*ictx)->axis);CHKERRQ(ierr); 3958 ierr = PetscViewerDestroy(&(*ictx)->viewer);CHKERRQ(ierr); 3959 ierr = VecDestroy(&(*ictx)->initialsolution);CHKERRQ(ierr); 3960 ierr = PetscFree(*ictx);CHKERRQ(ierr); 3961 PetscFunctionReturn(0); 3962 } 3963 3964 #undef __FUNCT__ 3965 #define __FUNCT__ "TSMonitorDrawCtxCreate" 3966 /*@C 3967 TSMonitorDrawCtxCreate - Creates the monitor context for TSMonitorDrawCtx 3968 3969 Collective on TS 3970 3971 Input Parameter: 3972 . ts - time-step context 3973 3974 Output Patameter: 3975 . ctx - the monitor context 3976 3977 Options Database: 3978 . -ts_monitor_draw_solution_initial - show initial solution as well as current solution 3979 3980 Level: intermediate 3981 3982 .keywords: TS, vector, monitor, view 3983 3984 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorDrawCtx() 3985 @*/ 3986 PetscErrorCode TSMonitorDrawCtxCreate(MPI_Comm comm,const char host[],const char label[],int x,int y,int m,int n,PetscInt howoften,TSMonitorDrawCtx *ctx) 3987 { 3988 PetscErrorCode ierr; 3989 3990 PetscFunctionBegin; 3991 ierr = PetscNew(ctx);CHKERRQ(ierr); 3992 ierr = PetscViewerDrawOpen(comm,host,label,x,y,m,n,&(*ctx)->viewer);CHKERRQ(ierr); 3993 ierr = PetscViewerSetFromOptions((*ctx)->viewer);CHKERRQ(ierr); 3994 3995 (*ctx)->howoften = howoften; 3996 (*ctx)->showinitial = PETSC_FALSE; 3997 ierr = PetscOptionsGetBool(NULL,"-ts_monitor_draw_solution_initial",&(*ctx)->showinitial,NULL);CHKERRQ(ierr); 3998 3999 (*ctx)->showtimestepandtime = PETSC_FALSE; 4000 ierr = PetscOptionsGetBool(NULL,"-ts_monitor_draw_solution_show_time",&(*ctx)->showtimestepandtime,NULL);CHKERRQ(ierr); 4001 (*ctx)->color = PETSC_DRAW_WHITE; 4002 PetscFunctionReturn(0); 4003 } 4004 4005 #undef __FUNCT__ 4006 #define __FUNCT__ "TSMonitorDrawError" 4007 /*@C 4008 TSMonitorDrawError - Monitors progress of the TS solvers by calling 4009 VecView() for the error at each timestep 4010 4011 Collective on TS 4012 4013 Input Parameters: 4014 + ts - the TS context 4015 . step - current time-step 4016 . ptime - current time 4017 - dummy - either a viewer or NULL 4018 4019 Level: intermediate 4020 4021 .keywords: TS, vector, monitor, view 4022 4023 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 4024 @*/ 4025 PetscErrorCode TSMonitorDrawError(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 4026 { 4027 PetscErrorCode ierr; 4028 TSMonitorDrawCtx ctx = (TSMonitorDrawCtx)dummy; 4029 PetscViewer viewer = ctx->viewer; 4030 Vec work; 4031 4032 PetscFunctionBegin; 4033 if (!(((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason))) PetscFunctionReturn(0); 4034 ierr = VecDuplicate(u,&work);CHKERRQ(ierr); 4035 ierr = TSComputeSolutionFunction(ts,ptime,work);CHKERRQ(ierr); 4036 ierr = VecAXPY(work,-1.0,u);CHKERRQ(ierr); 4037 ierr = VecView(work,viewer);CHKERRQ(ierr); 4038 ierr = VecDestroy(&work);CHKERRQ(ierr); 4039 PetscFunctionReturn(0); 4040 } 4041 4042 #include <petsc-private/dmimpl.h> 4043 #undef __FUNCT__ 4044 #define __FUNCT__ "TSSetDM" 4045 /*@ 4046 TSSetDM - Sets the DM that may be used by some preconditioners 4047 4048 Logically Collective on TS and DM 4049 4050 Input Parameters: 4051 + ts - the preconditioner context 4052 - dm - the dm 4053 4054 Level: intermediate 4055 4056 4057 .seealso: TSGetDM(), SNESSetDM(), SNESGetDM() 4058 @*/ 4059 PetscErrorCode TSSetDM(TS ts,DM dm) 4060 { 4061 PetscErrorCode ierr; 4062 SNES snes; 4063 DMTS tsdm; 4064 4065 PetscFunctionBegin; 4066 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4067 ierr = PetscObjectReference((PetscObject)dm);CHKERRQ(ierr); 4068 if (ts->dm) { /* Move the DMTS context over to the new DM unless the new DM already has one */ 4069 if (ts->dm->dmts && !dm->dmts) { 4070 ierr = DMCopyDMTS(ts->dm,dm);CHKERRQ(ierr); 4071 ierr = DMGetDMTS(ts->dm,&tsdm);CHKERRQ(ierr); 4072 if (tsdm->originaldm == ts->dm) { /* Grant write privileges to the replacement DM */ 4073 tsdm->originaldm = dm; 4074 } 4075 } 4076 ierr = DMDestroy(&ts->dm);CHKERRQ(ierr); 4077 } 4078 ts->dm = dm; 4079 4080 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 4081 ierr = SNESSetDM(snes,dm);CHKERRQ(ierr); 4082 PetscFunctionReturn(0); 4083 } 4084 4085 #undef __FUNCT__ 4086 #define __FUNCT__ "TSGetDM" 4087 /*@ 4088 TSGetDM - Gets the DM that may be used by some preconditioners 4089 4090 Not Collective 4091 4092 Input Parameter: 4093 . ts - the preconditioner context 4094 4095 Output Parameter: 4096 . dm - the dm 4097 4098 Level: intermediate 4099 4100 4101 .seealso: TSSetDM(), SNESSetDM(), SNESGetDM() 4102 @*/ 4103 PetscErrorCode TSGetDM(TS ts,DM *dm) 4104 { 4105 PetscErrorCode ierr; 4106 4107 PetscFunctionBegin; 4108 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4109 if (!ts->dm) { 4110 ierr = DMShellCreate(PetscObjectComm((PetscObject)ts),&ts->dm);CHKERRQ(ierr); 4111 if (ts->snes) {ierr = SNESSetDM(ts->snes,ts->dm);CHKERRQ(ierr);} 4112 } 4113 *dm = ts->dm; 4114 PetscFunctionReturn(0); 4115 } 4116 4117 #undef __FUNCT__ 4118 #define __FUNCT__ "SNESTSFormFunction" 4119 /*@ 4120 SNESTSFormFunction - Function to evaluate nonlinear residual 4121 4122 Logically Collective on SNES 4123 4124 Input Parameter: 4125 + snes - nonlinear solver 4126 . U - the current state at which to evaluate the residual 4127 - ctx - user context, must be a TS 4128 4129 Output Parameter: 4130 . F - the nonlinear residual 4131 4132 Notes: 4133 This function is not normally called by users and is automatically registered with the SNES used by TS. 4134 It is most frequently passed to MatFDColoringSetFunction(). 4135 4136 Level: advanced 4137 4138 .seealso: SNESSetFunction(), MatFDColoringSetFunction() 4139 @*/ 4140 PetscErrorCode SNESTSFormFunction(SNES snes,Vec U,Vec F,void *ctx) 4141 { 4142 TS ts = (TS)ctx; 4143 PetscErrorCode ierr; 4144 4145 PetscFunctionBegin; 4146 PetscValidHeaderSpecific(snes,SNES_CLASSID,1); 4147 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 4148 PetscValidHeaderSpecific(F,VEC_CLASSID,3); 4149 PetscValidHeaderSpecific(ts,TS_CLASSID,4); 4150 ierr = (ts->ops->snesfunction)(snes,U,F,ts);CHKERRQ(ierr); 4151 PetscFunctionReturn(0); 4152 } 4153 4154 #undef __FUNCT__ 4155 #define __FUNCT__ "SNESTSFormJacobian" 4156 /*@ 4157 SNESTSFormJacobian - Function to evaluate the Jacobian 4158 4159 Collective on SNES 4160 4161 Input Parameter: 4162 + snes - nonlinear solver 4163 . U - the current state at which to evaluate the residual 4164 - ctx - user context, must be a TS 4165 4166 Output Parameter: 4167 + A - the Jacobian 4168 . B - the preconditioning matrix (may be the same as A) 4169 - flag - indicates any structure change in the matrix 4170 4171 Notes: 4172 This function is not normally called by users and is automatically registered with the SNES used by TS. 4173 4174 Level: developer 4175 4176 .seealso: SNESSetJacobian() 4177 @*/ 4178 PetscErrorCode SNESTSFormJacobian(SNES snes,Vec U,Mat A,Mat B,void *ctx) 4179 { 4180 TS ts = (TS)ctx; 4181 PetscErrorCode ierr; 4182 4183 PetscFunctionBegin; 4184 PetscValidHeaderSpecific(snes,SNES_CLASSID,1); 4185 PetscValidHeaderSpecific(U,VEC_CLASSID,2); 4186 PetscValidPointer(A,3); 4187 PetscValidHeaderSpecific(A,MAT_CLASSID,3); 4188 PetscValidPointer(B,4); 4189 PetscValidHeaderSpecific(B,MAT_CLASSID,4); 4190 PetscValidHeaderSpecific(ts,TS_CLASSID,6); 4191 ierr = (ts->ops->snesjacobian)(snes,U,A,B,ts);CHKERRQ(ierr); 4192 PetscFunctionReturn(0); 4193 } 4194 4195 #undef __FUNCT__ 4196 #define __FUNCT__ "TSComputeRHSFunctionLinear" 4197 /*@C 4198 TSComputeRHSFunctionLinear - Evaluate the right hand side via the user-provided Jacobian, for linear problems only 4199 4200 Collective on TS 4201 4202 Input Arguments: 4203 + ts - time stepping context 4204 . t - time at which to evaluate 4205 . U - state at which to evaluate 4206 - ctx - context 4207 4208 Output Arguments: 4209 . F - right hand side 4210 4211 Level: intermediate 4212 4213 Notes: 4214 This function is intended to be passed to TSSetRHSFunction() to evaluate the right hand side for linear problems. 4215 The matrix (and optionally the evaluation context) should be passed to TSSetRHSJacobian(). 4216 4217 .seealso: TSSetRHSFunction(), TSSetRHSJacobian(), TSComputeRHSJacobianConstant() 4218 @*/ 4219 PetscErrorCode TSComputeRHSFunctionLinear(TS ts,PetscReal t,Vec U,Vec F,void *ctx) 4220 { 4221 PetscErrorCode ierr; 4222 Mat Arhs,Brhs; 4223 4224 PetscFunctionBegin; 4225 ierr = TSGetRHSMats_Private(ts,&Arhs,&Brhs);CHKERRQ(ierr); 4226 ierr = TSComputeRHSJacobian(ts,t,U,Arhs,Brhs);CHKERRQ(ierr); 4227 ierr = MatMult(Arhs,U,F);CHKERRQ(ierr); 4228 PetscFunctionReturn(0); 4229 } 4230 4231 #undef __FUNCT__ 4232 #define __FUNCT__ "TSComputeRHSJacobianConstant" 4233 /*@C 4234 TSComputeRHSJacobianConstant - Reuses a Jacobian that is time-independent. 4235 4236 Collective on TS 4237 4238 Input Arguments: 4239 + ts - time stepping context 4240 . t - time at which to evaluate 4241 . U - state at which to evaluate 4242 - ctx - context 4243 4244 Output Arguments: 4245 + A - pointer to operator 4246 . B - pointer to preconditioning matrix 4247 - flg - matrix structure flag 4248 4249 Level: intermediate 4250 4251 Notes: 4252 This function is intended to be passed to TSSetRHSJacobian() to evaluate the Jacobian for linear time-independent problems. 4253 4254 .seealso: TSSetRHSFunction(), TSSetRHSJacobian(), TSComputeRHSFunctionLinear() 4255 @*/ 4256 PetscErrorCode TSComputeRHSJacobianConstant(TS ts,PetscReal t,Vec U,Mat A,Mat B,void *ctx) 4257 { 4258 PetscFunctionBegin; 4259 PetscFunctionReturn(0); 4260 } 4261 4262 #undef __FUNCT__ 4263 #define __FUNCT__ "TSComputeIFunctionLinear" 4264 /*@C 4265 TSComputeIFunctionLinear - Evaluate the left hand side via the user-provided Jacobian, for linear problems only 4266 4267 Collective on TS 4268 4269 Input Arguments: 4270 + ts - time stepping context 4271 . t - time at which to evaluate 4272 . U - state at which to evaluate 4273 . Udot - time derivative of state vector 4274 - ctx - context 4275 4276 Output Arguments: 4277 . F - left hand side 4278 4279 Level: intermediate 4280 4281 Notes: 4282 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 4283 user is required to write their own TSComputeIFunction. 4284 This function is intended to be passed to TSSetIFunction() to evaluate the left hand side for linear problems. 4285 The matrix (and optionally the evaluation context) should be passed to TSSetIJacobian(). 4286 4287 .seealso: TSSetIFunction(), TSSetIJacobian(), TSComputeIJacobianConstant() 4288 @*/ 4289 PetscErrorCode TSComputeIFunctionLinear(TS ts,PetscReal t,Vec U,Vec Udot,Vec F,void *ctx) 4290 { 4291 PetscErrorCode ierr; 4292 Mat A,B; 4293 4294 PetscFunctionBegin; 4295 ierr = TSGetIJacobian(ts,&A,&B,NULL,NULL);CHKERRQ(ierr); 4296 ierr = TSComputeIJacobian(ts,t,U,Udot,1.0,A,B,PETSC_TRUE);CHKERRQ(ierr); 4297 ierr = MatMult(A,Udot,F);CHKERRQ(ierr); 4298 PetscFunctionReturn(0); 4299 } 4300 4301 #undef __FUNCT__ 4302 #define __FUNCT__ "TSComputeIJacobianConstant" 4303 /*@C 4304 TSComputeIJacobianConstant - Reuses a time-independent for a semi-implicit DAE or ODE 4305 4306 Collective on TS 4307 4308 Input Arguments: 4309 + ts - time stepping context 4310 . t - time at which to evaluate 4311 . U - state at which to evaluate 4312 . Udot - time derivative of state vector 4313 . shift - shift to apply 4314 - ctx - context 4315 4316 Output Arguments: 4317 + A - pointer to operator 4318 . B - pointer to preconditioning matrix 4319 - flg - matrix structure flag 4320 4321 Level: advanced 4322 4323 Notes: 4324 This function is intended to be passed to TSSetIJacobian() to evaluate the Jacobian for linear time-independent problems. 4325 4326 It is only appropriate for problems of the form 4327 4328 $ M Udot = F(U,t) 4329 4330 where M is constant and F is non-stiff. The user must pass M to TSSetIJacobian(). The current implementation only 4331 works with IMEX time integration methods such as TSROSW and TSARKIMEX, since there is no support for de-constructing 4332 an implicit operator of the form 4333 4334 $ shift*M + J 4335 4336 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 4337 a copy of M or reassemble it when requested. 4338 4339 .seealso: TSSetIFunction(), TSSetIJacobian(), TSComputeIFunctionLinear() 4340 @*/ 4341 PetscErrorCode TSComputeIJacobianConstant(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat A,Mat B,void *ctx) 4342 { 4343 PetscErrorCode ierr; 4344 4345 PetscFunctionBegin; 4346 ierr = MatScale(A, shift / ts->ijacobian.shift);CHKERRQ(ierr); 4347 ts->ijacobian.shift = shift; 4348 PetscFunctionReturn(0); 4349 } 4350 4351 #undef __FUNCT__ 4352 #define __FUNCT__ "TSGetEquationType" 4353 /*@ 4354 TSGetEquationType - Gets the type of the equation that TS is solving. 4355 4356 Not Collective 4357 4358 Input Parameter: 4359 . ts - the TS context 4360 4361 Output Parameter: 4362 . equation_type - see TSEquationType 4363 4364 Level: beginner 4365 4366 .keywords: TS, equation type 4367 4368 .seealso: TSSetEquationType(), TSEquationType 4369 @*/ 4370 PetscErrorCode TSGetEquationType(TS ts,TSEquationType *equation_type) 4371 { 4372 PetscFunctionBegin; 4373 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4374 PetscValidPointer(equation_type,2); 4375 *equation_type = ts->equation_type; 4376 PetscFunctionReturn(0); 4377 } 4378 4379 #undef __FUNCT__ 4380 #define __FUNCT__ "TSSetEquationType" 4381 /*@ 4382 TSSetEquationType - Sets the type of the equation that TS is solving. 4383 4384 Not Collective 4385 4386 Input Parameter: 4387 + ts - the TS context 4388 . equation_type - see TSEquationType 4389 4390 Level: advanced 4391 4392 .keywords: TS, equation type 4393 4394 .seealso: TSGetEquationType(), TSEquationType 4395 @*/ 4396 PetscErrorCode TSSetEquationType(TS ts,TSEquationType equation_type) 4397 { 4398 PetscFunctionBegin; 4399 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4400 ts->equation_type = equation_type; 4401 PetscFunctionReturn(0); 4402 } 4403 4404 #undef __FUNCT__ 4405 #define __FUNCT__ "TSGetConvergedReason" 4406 /*@ 4407 TSGetConvergedReason - Gets the reason the TS iteration was stopped. 4408 4409 Not Collective 4410 4411 Input Parameter: 4412 . ts - the TS context 4413 4414 Output Parameter: 4415 . reason - negative value indicates diverged, positive value converged, see TSConvergedReason or the 4416 manual pages for the individual convergence tests for complete lists 4417 4418 Level: beginner 4419 4420 Notes: 4421 Can only be called after the call to TSSolve() is complete. 4422 4423 .keywords: TS, nonlinear, set, convergence, test 4424 4425 .seealso: TSSetConvergenceTest(), TSConvergedReason 4426 @*/ 4427 PetscErrorCode TSGetConvergedReason(TS ts,TSConvergedReason *reason) 4428 { 4429 PetscFunctionBegin; 4430 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4431 PetscValidPointer(reason,2); 4432 *reason = ts->reason; 4433 PetscFunctionReturn(0); 4434 } 4435 4436 #undef __FUNCT__ 4437 #define __FUNCT__ "TSSetConvergedReason" 4438 /*@ 4439 TSSetConvergedReason - Sets the reason for handling the convergence of TSSolve. 4440 4441 Not Collective 4442 4443 Input Parameter: 4444 + ts - the TS context 4445 . reason - negative value indicates diverged, positive value converged, see TSConvergedReason or the 4446 manual pages for the individual convergence tests for complete lists 4447 4448 Level: advanced 4449 4450 Notes: 4451 Can only be called during TSSolve() is active. 4452 4453 .keywords: TS, nonlinear, set, convergence, test 4454 4455 .seealso: TSConvergedReason 4456 @*/ 4457 PetscErrorCode TSSetConvergedReason(TS ts,TSConvergedReason reason) 4458 { 4459 PetscFunctionBegin; 4460 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4461 ts->reason = reason; 4462 PetscFunctionReturn(0); 4463 } 4464 4465 #undef __FUNCT__ 4466 #define __FUNCT__ "TSGetSolveTime" 4467 /*@ 4468 TSGetSolveTime - Gets the time after a call to TSSolve() 4469 4470 Not Collective 4471 4472 Input Parameter: 4473 . ts - the TS context 4474 4475 Output Parameter: 4476 . ftime - the final time. This time should correspond to the final time set with TSSetDuration() 4477 4478 Level: beginner 4479 4480 Notes: 4481 Can only be called after the call to TSSolve() is complete. 4482 4483 .keywords: TS, nonlinear, set, convergence, test 4484 4485 .seealso: TSSetConvergenceTest(), TSConvergedReason 4486 @*/ 4487 PetscErrorCode TSGetSolveTime(TS ts,PetscReal *ftime) 4488 { 4489 PetscFunctionBegin; 4490 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4491 PetscValidPointer(ftime,2); 4492 *ftime = ts->solvetime; 4493 PetscFunctionReturn(0); 4494 } 4495 4496 #undef __FUNCT__ 4497 #define __FUNCT__ "TSGetTotalSteps" 4498 /*@ 4499 TSGetTotalSteps - Gets the total number of steps done since the last call to TSSetUp() or TSCreate() 4500 4501 Not Collective 4502 4503 Input Parameter: 4504 . ts - the TS context 4505 4506 Output Parameter: 4507 . steps - the number of steps 4508 4509 Level: beginner 4510 4511 Notes: 4512 Includes the number of steps for all calls to TSSolve() since TSSetUp() was called 4513 4514 .keywords: TS, nonlinear, set, convergence, test 4515 4516 .seealso: TSSetConvergenceTest(), TSConvergedReason 4517 @*/ 4518 PetscErrorCode TSGetTotalSteps(TS ts,PetscInt *steps) 4519 { 4520 PetscFunctionBegin; 4521 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4522 PetscValidPointer(steps,2); 4523 *steps = ts->total_steps; 4524 PetscFunctionReturn(0); 4525 } 4526 4527 #undef __FUNCT__ 4528 #define __FUNCT__ "TSGetSNESIterations" 4529 /*@ 4530 TSGetSNESIterations - Gets the total number of nonlinear iterations 4531 used by the time integrator. 4532 4533 Not Collective 4534 4535 Input Parameter: 4536 . ts - TS context 4537 4538 Output Parameter: 4539 . nits - number of nonlinear iterations 4540 4541 Notes: 4542 This counter is reset to zero for each successive call to TSSolve(). 4543 4544 Level: intermediate 4545 4546 .keywords: TS, get, number, nonlinear, iterations 4547 4548 .seealso: TSGetKSPIterations() 4549 @*/ 4550 PetscErrorCode TSGetSNESIterations(TS ts,PetscInt *nits) 4551 { 4552 PetscFunctionBegin; 4553 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4554 PetscValidIntPointer(nits,2); 4555 *nits = ts->snes_its; 4556 PetscFunctionReturn(0); 4557 } 4558 4559 #undef __FUNCT__ 4560 #define __FUNCT__ "TSGetKSPIterations" 4561 /*@ 4562 TSGetKSPIterations - Gets the total number of linear iterations 4563 used by the time integrator. 4564 4565 Not Collective 4566 4567 Input Parameter: 4568 . ts - TS context 4569 4570 Output Parameter: 4571 . lits - number of linear iterations 4572 4573 Notes: 4574 This counter is reset to zero for each successive call to TSSolve(). 4575 4576 Level: intermediate 4577 4578 .keywords: TS, get, number, linear, iterations 4579 4580 .seealso: TSGetSNESIterations(), SNESGetKSPIterations() 4581 @*/ 4582 PetscErrorCode TSGetKSPIterations(TS ts,PetscInt *lits) 4583 { 4584 PetscFunctionBegin; 4585 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4586 PetscValidIntPointer(lits,2); 4587 *lits = ts->ksp_its; 4588 PetscFunctionReturn(0); 4589 } 4590 4591 #undef __FUNCT__ 4592 #define __FUNCT__ "TSGetStepRejections" 4593 /*@ 4594 TSGetStepRejections - Gets the total number of rejected steps. 4595 4596 Not Collective 4597 4598 Input Parameter: 4599 . ts - TS context 4600 4601 Output Parameter: 4602 . rejects - number of steps rejected 4603 4604 Notes: 4605 This counter is reset to zero for each successive call to TSSolve(). 4606 4607 Level: intermediate 4608 4609 .keywords: TS, get, number 4610 4611 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetSNESFailures(), TSSetMaxSNESFailures(), TSSetErrorIfStepFails() 4612 @*/ 4613 PetscErrorCode TSGetStepRejections(TS ts,PetscInt *rejects) 4614 { 4615 PetscFunctionBegin; 4616 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4617 PetscValidIntPointer(rejects,2); 4618 *rejects = ts->reject; 4619 PetscFunctionReturn(0); 4620 } 4621 4622 #undef __FUNCT__ 4623 #define __FUNCT__ "TSGetSNESFailures" 4624 /*@ 4625 TSGetSNESFailures - Gets the total number of failed SNES solves 4626 4627 Not Collective 4628 4629 Input Parameter: 4630 . ts - TS context 4631 4632 Output Parameter: 4633 . fails - number of failed nonlinear solves 4634 4635 Notes: 4636 This counter is reset to zero for each successive call to TSSolve(). 4637 4638 Level: intermediate 4639 4640 .keywords: TS, get, number 4641 4642 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSSetMaxSNESFailures() 4643 @*/ 4644 PetscErrorCode TSGetSNESFailures(TS ts,PetscInt *fails) 4645 { 4646 PetscFunctionBegin; 4647 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4648 PetscValidIntPointer(fails,2); 4649 *fails = ts->num_snes_failures; 4650 PetscFunctionReturn(0); 4651 } 4652 4653 #undef __FUNCT__ 4654 #define __FUNCT__ "TSSetMaxStepRejections" 4655 /*@ 4656 TSSetMaxStepRejections - Sets the maximum number of step rejections before a step fails 4657 4658 Not Collective 4659 4660 Input Parameter: 4661 + ts - TS context 4662 - rejects - maximum number of rejected steps, pass -1 for unlimited 4663 4664 Notes: 4665 The counter is reset to zero for each step 4666 4667 Options Database Key: 4668 . -ts_max_reject - Maximum number of step rejections before a step fails 4669 4670 Level: intermediate 4671 4672 .keywords: TS, set, maximum, number 4673 4674 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxSNESFailures(), TSGetStepRejections(), TSGetSNESFailures(), TSSetErrorIfStepFails(), TSGetConvergedReason() 4675 @*/ 4676 PetscErrorCode TSSetMaxStepRejections(TS ts,PetscInt rejects) 4677 { 4678 PetscFunctionBegin; 4679 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4680 ts->max_reject = rejects; 4681 PetscFunctionReturn(0); 4682 } 4683 4684 #undef __FUNCT__ 4685 #define __FUNCT__ "TSSetMaxSNESFailures" 4686 /*@ 4687 TSSetMaxSNESFailures - Sets the maximum number of failed SNES solves 4688 4689 Not Collective 4690 4691 Input Parameter: 4692 + ts - TS context 4693 - fails - maximum number of failed nonlinear solves, pass -1 for unlimited 4694 4695 Notes: 4696 The counter is reset to zero for each successive call to TSSolve(). 4697 4698 Options Database Key: 4699 . -ts_max_snes_failures - Maximum number of nonlinear solve failures 4700 4701 Level: intermediate 4702 4703 .keywords: TS, set, maximum, number 4704 4705 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSGetSNESFailures(), SNESGetConvergedReason(), TSGetConvergedReason() 4706 @*/ 4707 PetscErrorCode TSSetMaxSNESFailures(TS ts,PetscInt fails) 4708 { 4709 PetscFunctionBegin; 4710 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4711 ts->max_snes_failures = fails; 4712 PetscFunctionReturn(0); 4713 } 4714 4715 #undef __FUNCT__ 4716 #define __FUNCT__ "TSSetErrorIfStepFails" 4717 /*@ 4718 TSSetErrorIfStepFails - Error if no step succeeds 4719 4720 Not Collective 4721 4722 Input Parameter: 4723 + ts - TS context 4724 - err - PETSC_TRUE to error if no step succeeds, PETSC_FALSE to return without failure 4725 4726 Options Database Key: 4727 . -ts_error_if_step_fails - Error if no step succeeds 4728 4729 Level: intermediate 4730 4731 .keywords: TS, set, error 4732 4733 .seealso: TSGetSNESIterations(), TSGetKSPIterations(), TSSetMaxStepRejections(), TSGetStepRejections(), TSGetSNESFailures(), TSSetErrorIfStepFails(), TSGetConvergedReason() 4734 @*/ 4735 PetscErrorCode TSSetErrorIfStepFails(TS ts,PetscBool err) 4736 { 4737 PetscFunctionBegin; 4738 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4739 ts->errorifstepfailed = err; 4740 PetscFunctionReturn(0); 4741 } 4742 4743 #undef __FUNCT__ 4744 #define __FUNCT__ "TSMonitorSolutionBinary" 4745 /*@C 4746 TSMonitorSolutionBinary - Monitors progress of the TS solvers by VecView() for the solution at each timestep. Normally the viewer is a binary file 4747 4748 Collective on TS 4749 4750 Input Parameters: 4751 + ts - the TS context 4752 . step - current time-step 4753 . ptime - current time 4754 . u - current state 4755 - viewer - binary viewer 4756 4757 Level: intermediate 4758 4759 .keywords: TS, vector, monitor, view 4760 4761 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 4762 @*/ 4763 PetscErrorCode TSMonitorSolutionBinary(TS ts,PetscInt step,PetscReal ptime,Vec u,void *viewer) 4764 { 4765 PetscErrorCode ierr; 4766 PetscViewer v = (PetscViewer)viewer; 4767 4768 PetscFunctionBegin; 4769 ierr = VecView(u,v);CHKERRQ(ierr); 4770 PetscFunctionReturn(0); 4771 } 4772 4773 #undef __FUNCT__ 4774 #define __FUNCT__ "TSMonitorSolutionVTK" 4775 /*@C 4776 TSMonitorSolutionVTK - Monitors progress of the TS solvers by VecView() for the solution at each timestep. 4777 4778 Collective on TS 4779 4780 Input Parameters: 4781 + ts - the TS context 4782 . step - current time-step 4783 . ptime - current time 4784 . u - current state 4785 - filenametemplate - string containing a format specifier for the integer time step (e.g. %03D) 4786 4787 Level: intermediate 4788 4789 Notes: 4790 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. 4791 These are named according to the file name template. 4792 4793 This function is normally passed as an argument to TSMonitorSet() along with TSMonitorSolutionVTKDestroy(). 4794 4795 .keywords: TS, vector, monitor, view 4796 4797 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 4798 @*/ 4799 PetscErrorCode TSMonitorSolutionVTK(TS ts,PetscInt step,PetscReal ptime,Vec u,void *filenametemplate) 4800 { 4801 PetscErrorCode ierr; 4802 char filename[PETSC_MAX_PATH_LEN]; 4803 PetscViewer viewer; 4804 4805 PetscFunctionBegin; 4806 ierr = PetscSNPrintf(filename,sizeof(filename),(const char*)filenametemplate,step);CHKERRQ(ierr); 4807 ierr = PetscViewerVTKOpen(PetscObjectComm((PetscObject)ts),filename,FILE_MODE_WRITE,&viewer);CHKERRQ(ierr); 4808 ierr = VecView(u,viewer);CHKERRQ(ierr); 4809 ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr); 4810 PetscFunctionReturn(0); 4811 } 4812 4813 #undef __FUNCT__ 4814 #define __FUNCT__ "TSMonitorSolutionVTKDestroy" 4815 /*@C 4816 TSMonitorSolutionVTKDestroy - Destroy context for monitoring 4817 4818 Collective on TS 4819 4820 Input Parameters: 4821 . filenametemplate - string containing a format specifier for the integer time step (e.g. %03D) 4822 4823 Level: intermediate 4824 4825 Note: 4826 This function is normally passed to TSMonitorSet() along with TSMonitorSolutionVTK(). 4827 4828 .keywords: TS, vector, monitor, view 4829 4830 .seealso: TSMonitorSet(), TSMonitorSolutionVTK() 4831 @*/ 4832 PetscErrorCode TSMonitorSolutionVTKDestroy(void *filenametemplate) 4833 { 4834 PetscErrorCode ierr; 4835 4836 PetscFunctionBegin; 4837 ierr = PetscFree(*(char**)filenametemplate);CHKERRQ(ierr); 4838 PetscFunctionReturn(0); 4839 } 4840 4841 #undef __FUNCT__ 4842 #define __FUNCT__ "TSGetAdapt" 4843 /*@ 4844 TSGetAdapt - Get the adaptive controller context for the current method 4845 4846 Collective on TS if controller has not been created yet 4847 4848 Input Arguments: 4849 . ts - time stepping context 4850 4851 Output Arguments: 4852 . adapt - adaptive controller 4853 4854 Level: intermediate 4855 4856 .seealso: TSAdapt, TSAdaptSetType(), TSAdaptChoose() 4857 @*/ 4858 PetscErrorCode TSGetAdapt(TS ts,TSAdapt *adapt) 4859 { 4860 PetscErrorCode ierr; 4861 4862 PetscFunctionBegin; 4863 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4864 PetscValidPointer(adapt,2); 4865 if (!ts->adapt) { 4866 ierr = TSAdaptCreate(PetscObjectComm((PetscObject)ts),&ts->adapt);CHKERRQ(ierr); 4867 ierr = PetscLogObjectParent((PetscObject)ts,(PetscObject)ts->adapt);CHKERRQ(ierr); 4868 ierr = PetscObjectIncrementTabLevel((PetscObject)ts->adapt,(PetscObject)ts,1);CHKERRQ(ierr); 4869 } 4870 *adapt = ts->adapt; 4871 PetscFunctionReturn(0); 4872 } 4873 4874 #undef __FUNCT__ 4875 #define __FUNCT__ "TSSetTolerances" 4876 /*@ 4877 TSSetTolerances - Set tolerances for local truncation error when using adaptive controller 4878 4879 Logically Collective 4880 4881 Input Arguments: 4882 + ts - time integration context 4883 . atol - scalar absolute tolerances, PETSC_DECIDE to leave current value 4884 . vatol - vector of absolute tolerances or NULL, used in preference to atol if present 4885 . rtol - scalar relative tolerances, PETSC_DECIDE to leave current value 4886 - vrtol - vector of relative tolerances or NULL, used in preference to atol if present 4887 4888 Options Database keys: 4889 + -ts_rtol <rtol> - relative tolerance for local truncation error 4890 - -ts_atol <atol> Absolute tolerance for local truncation error 4891 4892 Level: beginner 4893 4894 .seealso: TS, TSAdapt, TSVecNormWRMS(), TSGetTolerances() 4895 @*/ 4896 PetscErrorCode TSSetTolerances(TS ts,PetscReal atol,Vec vatol,PetscReal rtol,Vec vrtol) 4897 { 4898 PetscErrorCode ierr; 4899 4900 PetscFunctionBegin; 4901 if (atol != PETSC_DECIDE && atol != PETSC_DEFAULT) ts->atol = atol; 4902 if (vatol) { 4903 ierr = PetscObjectReference((PetscObject)vatol);CHKERRQ(ierr); 4904 ierr = VecDestroy(&ts->vatol);CHKERRQ(ierr); 4905 4906 ts->vatol = vatol; 4907 } 4908 if (rtol != PETSC_DECIDE && rtol != PETSC_DEFAULT) ts->rtol = rtol; 4909 if (vrtol) { 4910 ierr = PetscObjectReference((PetscObject)vrtol);CHKERRQ(ierr); 4911 ierr = VecDestroy(&ts->vrtol);CHKERRQ(ierr); 4912 4913 ts->vrtol = vrtol; 4914 } 4915 PetscFunctionReturn(0); 4916 } 4917 4918 #undef __FUNCT__ 4919 #define __FUNCT__ "TSGetTolerances" 4920 /*@ 4921 TSGetTolerances - Get tolerances for local truncation error when using adaptive controller 4922 4923 Logically Collective 4924 4925 Input Arguments: 4926 . ts - time integration context 4927 4928 Output Arguments: 4929 + atol - scalar absolute tolerances, NULL to ignore 4930 . vatol - vector of absolute tolerances, NULL to ignore 4931 . rtol - scalar relative tolerances, NULL to ignore 4932 - vrtol - vector of relative tolerances, NULL to ignore 4933 4934 Level: beginner 4935 4936 .seealso: TS, TSAdapt, TSVecNormWRMS(), TSSetTolerances() 4937 @*/ 4938 PetscErrorCode TSGetTolerances(TS ts,PetscReal *atol,Vec *vatol,PetscReal *rtol,Vec *vrtol) 4939 { 4940 PetscFunctionBegin; 4941 if (atol) *atol = ts->atol; 4942 if (vatol) *vatol = ts->vatol; 4943 if (rtol) *rtol = ts->rtol; 4944 if (vrtol) *vrtol = ts->vrtol; 4945 PetscFunctionReturn(0); 4946 } 4947 4948 #undef __FUNCT__ 4949 #define __FUNCT__ "TSSetDifferentialEquationsIS" 4950 /*@ 4951 TSSetDifferentialEquationsIS - Sets an IS containing locations of differential equations in a DAE 4952 4953 Not Collective 4954 4955 Input Arguments: 4956 + ts - time stepping context 4957 - is_diff - Index set for differential equations 4958 4959 Level: advanced 4960 4961 @*/ 4962 PetscErrorCode TSSetDifferentialEquationsIS(TS ts, IS is_diff) 4963 { 4964 PetscErrorCode ierr; 4965 4966 PetscFunctionBegin; 4967 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 4968 PetscValidHeaderSpecific(is_diff,IS_CLASSID,2); 4969 PetscCheckSameComm(ts,1,is_diff,2); 4970 ierr = PetscObjectReference((PetscObject)is_diff);CHKERRQ(ierr); 4971 ierr = ISDestroy(&ts->is_diff);CHKERRQ(ierr); 4972 ts->is_diff = is_diff; 4973 PetscFunctionReturn(0); 4974 } 4975 4976 #undef __FUNCT__ 4977 #define __FUNCT__ "TSErrorWeightedNorm2" 4978 /*@ 4979 TSErrorWeightedNorm2 - compute a weighted 2-norm of the difference between a vector and the current state 4980 4981 Collective on TS 4982 4983 Input Arguments: 4984 + ts - time stepping context 4985 - Y - state vector to be compared to ts->vec_sol 4986 4987 Output Arguments: 4988 . norm - weighted norm, a value of 1.0 is considered small 4989 4990 Level: developer 4991 4992 .seealso: TSErrorWeightedNorm(), TSErrorWeightedNormInfinity() 4993 @*/ 4994 PetscErrorCode TSErrorWeightedNorm2(TS ts,Vec Y,PetscReal *norm) 4995 { 4996 PetscErrorCode ierr; 4997 PetscInt i,n,N,rstart; 4998 const PetscScalar *u,*y; 4999 Vec U; 5000 PetscReal sum,gsum; 5001 PetscReal tol; 5002 5003 PetscFunctionBegin; 5004 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5005 PetscValidHeaderSpecific(Y,VEC_CLASSID,2); 5006 PetscValidPointer(norm,3); 5007 U = ts->vec_sol; 5008 PetscCheckSameTypeAndComm(U,1,Y,2); 5009 if (U == Y) SETERRQ(PetscObjectComm((PetscObject)U),PETSC_ERR_ARG_IDN,"Y cannot be the TS solution vector"); 5010 5011 ierr = VecGetSize(U,&N);CHKERRQ(ierr); 5012 ierr = VecGetLocalSize(U,&n);CHKERRQ(ierr); 5013 ierr = VecGetOwnershipRange(U,&rstart,NULL);CHKERRQ(ierr); 5014 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 5015 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 5016 sum = 0.; 5017 if (ts->vatol && ts->vrtol) { 5018 const PetscScalar *atol,*rtol; 5019 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5020 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5021 if(ts->is_diff) { 5022 const PetscInt *idx; 5023 PetscInt k; 5024 ierr = ISGetIndices(ts->is_diff,&idx);CHKERRQ(ierr); 5025 ierr = ISGetLocalSize(ts->is_diff,&n);CHKERRQ(ierr); 5026 for(i=0; i < n; i++) { 5027 k = idx[i] - rstart; 5028 tol = PetscRealPart(atol[k]) + PetscRealPart(rtol[k])*PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5029 sum += PetscSqr(PetscAbsScalar(y[k] - u[k]) / tol); 5030 } 5031 ierr = ISRestoreIndices(ts->is_diff,&idx);CHKERRQ(ierr); 5032 } else { 5033 for (i=0; i<n; i++) { 5034 tol = PetscRealPart(atol[i]) + PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5035 sum += PetscSqr(PetscAbsScalar(y[i] - u[i]) / tol); 5036 } 5037 } 5038 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5039 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5040 } else if (ts->vatol) { /* vector atol, scalar rtol */ 5041 const PetscScalar *atol; 5042 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5043 if(ts->is_diff) { 5044 const PetscInt *idx; 5045 PetscInt k; 5046 ierr = ISGetIndices(ts->is_diff,&idx);CHKERRQ(ierr); 5047 ierr = ISGetLocalSize(ts->is_diff,&n);CHKERRQ(ierr); 5048 for(i=0; i < n; i++) { 5049 k = idx[i] - rstart; 5050 tol = PetscRealPart(atol[k]) + ts->rtol * PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5051 sum += PetscSqr(PetscAbsScalar(y[k] - u[k]) / tol); 5052 } 5053 ierr = ISRestoreIndices(ts->is_diff,&idx);CHKERRQ(ierr); 5054 } else { 5055 for (i=0; i<n; i++) { 5056 tol = PetscRealPart(atol[i]) + ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5057 sum += PetscSqr(PetscAbsScalar(y[i] - u[i]) / tol); 5058 } 5059 } 5060 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5061 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 5062 const PetscScalar *rtol; 5063 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5064 if(ts->is_diff) { 5065 const PetscInt *idx; 5066 PetscInt k; 5067 ierr = ISGetIndices(ts->is_diff,&idx);CHKERRQ(ierr); 5068 ierr = ISGetLocalSize(ts->is_diff,&n);CHKERRQ(ierr); 5069 for(i=0; i < n; i++) { 5070 k = idx[i] - rstart; 5071 tol = ts->atol + PetscRealPart(rtol[k]) * PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5072 sum += PetscSqr(PetscAbsScalar(y[k] - u[k]) / tol); 5073 } 5074 ierr = ISRestoreIndices(ts->is_diff,&idx);CHKERRQ(ierr); 5075 } else { 5076 for (i=0; i<n; i++) { 5077 tol = ts->atol + PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5078 sum += PetscSqr(PetscAbsScalar(y[i] - u[i]) / tol); 5079 } 5080 } 5081 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5082 } else { /* scalar atol, scalar rtol */ 5083 if (ts->is_diff) { 5084 const PetscInt *idx; 5085 PetscInt k; 5086 ierr = ISGetIndices(ts->is_diff,&idx);CHKERRQ(ierr); 5087 ierr = ISGetLocalSize(ts->is_diff,&n);CHKERRQ(ierr); 5088 for (i=0; i<n; i++) { 5089 k = idx[i] - rstart; 5090 tol = ts->atol + ts->rtol * PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5091 sum += PetscSqr(PetscAbsScalar(y[k] - u[k]) / tol); 5092 } 5093 } else { 5094 for (i=0; i<n; i++) { 5095 tol = ts->atol + ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5096 sum += PetscSqr(PetscAbsScalar(y[i] - u[i]) / tol); 5097 } 5098 } 5099 } 5100 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 5101 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 5102 5103 ierr = MPI_Allreduce(&sum,&gsum,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 5104 *norm = PetscSqrtReal(gsum / N); 5105 5106 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 5107 PetscFunctionReturn(0); 5108 } 5109 5110 #undef __FUNCT__ 5111 #define __FUNCT__ "TSErrorWeightedNormInfinity" 5112 /*@ 5113 TSErrorWeightedNormInfinity - compute a weighted infinity-norm of the difference between a vector and the current state 5114 5115 Collective on TS 5116 5117 Input Arguments: 5118 + ts - time stepping context 5119 - Y - state vector to be compared to ts->vec_sol 5120 5121 Output Arguments: 5122 . norm - weighted norm, a value of 1.0 is considered small 5123 5124 Level: developer 5125 5126 .seealso: TSErrorWeightedNorm(), TSErrorWeightedNorm2() 5127 @*/ 5128 PetscErrorCode TSErrorWeightedNormInfinity(TS ts,Vec Y,PetscReal *norm) 5129 { 5130 PetscErrorCode ierr; 5131 PetscInt i,n,N,rstart,k; 5132 const PetscScalar *u,*y; 5133 Vec U; 5134 PetscReal max,gmax; 5135 PetscReal tol; 5136 5137 PetscFunctionBegin; 5138 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5139 PetscValidHeaderSpecific(Y,VEC_CLASSID,2); 5140 PetscValidPointer(norm,3); 5141 U = ts->vec_sol; 5142 PetscCheckSameTypeAndComm(U,1,Y,2); 5143 if (U == Y) SETERRQ(PetscObjectComm((PetscObject)U),PETSC_ERR_ARG_IDN,"Y cannot be the TS solution vector"); 5144 5145 ierr = VecGetSize(U,&N);CHKERRQ(ierr); 5146 ierr = VecGetLocalSize(U,&n);CHKERRQ(ierr); 5147 ierr = VecGetOwnershipRange(U,&rstart,NULL);CHKERRQ(ierr); 5148 ierr = VecGetArrayRead(U,&u);CHKERRQ(ierr); 5149 ierr = VecGetArrayRead(Y,&y);CHKERRQ(ierr); 5150 if (ts->vatol && ts->vrtol) { 5151 const PetscScalar *atol,*rtol; 5152 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5153 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5154 if(ts->is_diff) { 5155 const PetscInt *idx; 5156 ierr = ISGetIndices(ts->is_diff,&idx);CHKERRQ(ierr); 5157 ierr = ISGetLocalSize(ts->is_diff,&n);CHKERRQ(ierr); 5158 5159 k = idx[0]; 5160 tol = PetscRealPart(atol[k]) + PetscRealPart(rtol[k]) * PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5161 max = PetscAbsScalar(y[k] - u[k]) / tol; 5162 for(i=1; i < n; i++) { 5163 k = idx[i] - rstart; 5164 tol = PetscRealPart(atol[k]) + PetscRealPart(rtol[k])*PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5165 max = PetscMax(max,PetscAbsScalar(y[k] - u[k]) / tol); 5166 } 5167 ierr = ISRestoreIndices(ts->is_diff,&idx);CHKERRQ(ierr); 5168 } else { 5169 k = 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 tol = PetscRealPart(atol[i]) + PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5174 max = PetscMax(max,PetscAbsScalar(y[i] - u[i]) / tol); 5175 } 5176 } 5177 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5178 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5179 } else if (ts->vatol) { /* vector atol, scalar rtol */ 5180 const PetscScalar *atol; 5181 ierr = VecGetArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5182 if(ts->is_diff) { 5183 const PetscInt *idx; 5184 ierr = ISGetIndices(ts->is_diff,&idx);CHKERRQ(ierr); 5185 ierr = ISGetLocalSize(ts->is_diff,&n);CHKERRQ(ierr); 5186 5187 k = idx[0]; 5188 tol = PetscRealPart(atol[k]) + ts->rtol * PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5189 max = PetscAbsScalar(y[k] - u[k]) / tol; 5190 for(i=1; i < n; i++) { 5191 k = idx[i] - rstart; 5192 tol = PetscRealPart(atol[k]) + ts->rtol * PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5193 max = PetscMax(max,PetscAbsScalar(y[k] - u[k]) / tol); 5194 } 5195 ierr = ISRestoreIndices(ts->is_diff,&idx);CHKERRQ(ierr); 5196 } else { 5197 k = 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 tol = PetscRealPart(atol[i]) + ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5202 max = PetscMax(max,PetscAbsScalar(y[i] - u[i]) / tol); 5203 } 5204 } 5205 ierr = VecRestoreArrayRead(ts->vatol,&atol);CHKERRQ(ierr); 5206 } else if (ts->vrtol) { /* scalar atol, vector rtol */ 5207 const PetscScalar *rtol; 5208 ierr = VecGetArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5209 if(ts->is_diff) { 5210 const PetscInt *idx; 5211 ierr = ISGetIndices(ts->is_diff,&idx);CHKERRQ(ierr); 5212 ierr = ISGetLocalSize(ts->is_diff,&n);CHKERRQ(ierr); 5213 5214 k = idx[0]; 5215 tol = ts->atol + PetscRealPart(rtol[k])*PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5216 max = PetscAbsScalar(y[k] - u[k]) / tol; 5217 for(i=1; i < n; i++) { 5218 k = idx[i] - rstart; 5219 tol = ts->atol + PetscRealPart(rtol[k]) * PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5220 max = PetscMax(max,PetscAbsScalar(y[k] - u[k]) / tol); 5221 } 5222 ierr = ISRestoreIndices(ts->is_diff,&idx);CHKERRQ(ierr); 5223 } else { 5224 k = 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 tol = ts->atol + PetscRealPart(rtol[i]) * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5229 max = PetscMax(max,PetscAbsScalar(y[i] - u[i]) / tol); 5230 } 5231 } 5232 ierr = VecRestoreArrayRead(ts->vrtol,&rtol);CHKERRQ(ierr); 5233 } else { /* scalar atol, scalar rtol */ 5234 if (ts->is_diff) { 5235 const PetscInt *idx; 5236 ierr = ISGetIndices(ts->is_diff,&idx);CHKERRQ(ierr); 5237 ierr = ISGetLocalSize(ts->is_diff,&n);CHKERRQ(ierr); 5238 5239 k = idx[0]; 5240 tol = ts->atol + ts->rtol * PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5241 max = PetscAbsScalar(y[k] - u[k]) / tol; 5242 for (i=1; i<n; i++) { 5243 k = idx[i] - rstart; 5244 tol = ts->atol + ts->rtol * PetscMax(PetscAbsScalar(u[k]),PetscAbsScalar(y[k])); 5245 max = PetscMax(max,PetscAbsScalar(y[k] - u[k]) / tol); 5246 } 5247 ierr = ISRestoreIndices(ts->is_diff,&idx);CHKERRQ(ierr); 5248 } else { 5249 k = 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 tol = ts->atol + ts->rtol * PetscMax(PetscAbsScalar(u[i]),PetscAbsScalar(y[i])); 5254 max = PetscMax(max,PetscAbsScalar(y[i] - u[i]) / tol); 5255 } 5256 } 5257 } 5258 ierr = VecRestoreArrayRead(U,&u);CHKERRQ(ierr); 5259 ierr = VecRestoreArrayRead(Y,&y);CHKERRQ(ierr); 5260 5261 ierr = MPI_Allreduce(&max,&gmax,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 5262 *norm = gmax; 5263 5264 if (PetscIsInfOrNanScalar(*norm)) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_FP,"Infinite or not-a-number generated in norm"); 5265 PetscFunctionReturn(0); 5266 } 5267 5268 #undef __FUNCT__ 5269 #define __FUNCT__ "TSErrorWeightedNorm" 5270 /*@ 5271 TSErrorWeightedNorm - compute a weighted norm of the difference between a vector and the current state 5272 5273 Collective on TS 5274 5275 Input Arguments: 5276 + ts - time stepping context 5277 - Y - state vector to be compared to ts->vec_sol 5278 5279 Options Database Keys: 5280 . -ts_adapt_wnormtype <wnormtype> - 2, INFINITY 5281 5282 Output Arguments: 5283 . norm - weighted norm, a value of 1.0 is considered small 5284 5285 Level: developer 5286 5287 .seealso: TSErrorWeightedNormInfinity(), TSErrorWeightedNorm2() 5288 @*/ 5289 PetscErrorCode TSErrorWeightedNorm(TS ts,Vec Y,PetscReal *norm) 5290 { 5291 PetscErrorCode ierr; 5292 5293 PetscFunctionBegin; 5294 if(ts->adapt->wnormtype == NORM_2) { 5295 ierr = TSErrorWeightedNorm2(ts,Y,norm);CHKERRQ(ierr); 5296 } else if(ts->adapt->wnormtype == NORM_INFINITY) { 5297 ierr = TSErrorWeightedNormInfinity(ts,Y,norm);CHKERRQ(ierr); 5298 } 5299 PetscFunctionReturn(0); 5300 } 5301 5302 #undef __FUNCT__ 5303 #define __FUNCT__ "TSSetCFLTimeLocal" 5304 /*@ 5305 TSSetCFLTimeLocal - Set the local CFL constraint relative to forward Euler 5306 5307 Logically Collective on TS 5308 5309 Input Arguments: 5310 + ts - time stepping context 5311 - cfltime - maximum stable time step if using forward Euler (value can be different on each process) 5312 5313 Note: 5314 After calling this function, the global CFL time can be obtained by calling TSGetCFLTime() 5315 5316 Level: intermediate 5317 5318 .seealso: TSGetCFLTime(), TSADAPTCFL 5319 @*/ 5320 PetscErrorCode TSSetCFLTimeLocal(TS ts,PetscReal cfltime) 5321 { 5322 PetscFunctionBegin; 5323 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5324 ts->cfltime_local = cfltime; 5325 ts->cfltime = -1.; 5326 PetscFunctionReturn(0); 5327 } 5328 5329 #undef __FUNCT__ 5330 #define __FUNCT__ "TSGetCFLTime" 5331 /*@ 5332 TSGetCFLTime - Get the maximum stable time step according to CFL criteria applied to forward Euler 5333 5334 Collective on TS 5335 5336 Input Arguments: 5337 . ts - time stepping context 5338 5339 Output Arguments: 5340 . cfltime - maximum stable time step for forward Euler 5341 5342 Level: advanced 5343 5344 .seealso: TSSetCFLTimeLocal() 5345 @*/ 5346 PetscErrorCode TSGetCFLTime(TS ts,PetscReal *cfltime) 5347 { 5348 PetscErrorCode ierr; 5349 5350 PetscFunctionBegin; 5351 if (ts->cfltime < 0) { 5352 ierr = MPI_Allreduce(&ts->cfltime_local,&ts->cfltime,1,MPIU_REAL,MPIU_MIN,PetscObjectComm((PetscObject)ts));CHKERRQ(ierr); 5353 } 5354 *cfltime = ts->cfltime; 5355 PetscFunctionReturn(0); 5356 } 5357 5358 #undef __FUNCT__ 5359 #define __FUNCT__ "TSVISetVariableBounds" 5360 /*@ 5361 TSVISetVariableBounds - Sets the lower and upper bounds for the solution vector. xl <= x <= xu 5362 5363 Input Parameters: 5364 . ts - the TS context. 5365 . xl - lower bound. 5366 . xu - upper bound. 5367 5368 Notes: 5369 If this routine is not called then the lower and upper bounds are set to 5370 PETSC_NINFINITY and PETSC_INFINITY respectively during SNESSetUp(). 5371 5372 Level: advanced 5373 5374 @*/ 5375 PetscErrorCode TSVISetVariableBounds(TS ts, Vec xl, Vec xu) 5376 { 5377 PetscErrorCode ierr; 5378 SNES snes; 5379 5380 PetscFunctionBegin; 5381 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 5382 ierr = SNESVISetVariableBounds(snes,xl,xu);CHKERRQ(ierr); 5383 PetscFunctionReturn(0); 5384 } 5385 5386 #if defined(PETSC_HAVE_MATLAB_ENGINE) 5387 #include <mex.h> 5388 5389 typedef struct {char *funcname; mxArray *ctx;} TSMatlabContext; 5390 5391 #undef __FUNCT__ 5392 #define __FUNCT__ "TSComputeFunction_Matlab" 5393 /* 5394 TSComputeFunction_Matlab - Calls the function that has been set with 5395 TSSetFunctionMatlab(). 5396 5397 Collective on TS 5398 5399 Input Parameters: 5400 + snes - the TS context 5401 - u - input vector 5402 5403 Output Parameter: 5404 . y - function vector, as set by TSSetFunction() 5405 5406 Notes: 5407 TSComputeFunction() is typically used within nonlinear solvers 5408 implementations, so most users would not generally call this routine 5409 themselves. 5410 5411 Level: developer 5412 5413 .keywords: TS, nonlinear, compute, function 5414 5415 .seealso: TSSetFunction(), TSGetFunction() 5416 */ 5417 PetscErrorCode TSComputeFunction_Matlab(TS snes,PetscReal time,Vec u,Vec udot,Vec y, void *ctx) 5418 { 5419 PetscErrorCode ierr; 5420 TSMatlabContext *sctx = (TSMatlabContext*)ctx; 5421 int nlhs = 1,nrhs = 7; 5422 mxArray *plhs[1],*prhs[7]; 5423 long long int lx = 0,lxdot = 0,ly = 0,ls = 0; 5424 5425 PetscFunctionBegin; 5426 PetscValidHeaderSpecific(snes,TS_CLASSID,1); 5427 PetscValidHeaderSpecific(u,VEC_CLASSID,3); 5428 PetscValidHeaderSpecific(udot,VEC_CLASSID,4); 5429 PetscValidHeaderSpecific(y,VEC_CLASSID,5); 5430 PetscCheckSameComm(snes,1,u,3); 5431 PetscCheckSameComm(snes,1,y,5); 5432 5433 ierr = PetscMemcpy(&ls,&snes,sizeof(snes));CHKERRQ(ierr); 5434 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 5435 ierr = PetscMemcpy(&lxdot,&udot,sizeof(udot));CHKERRQ(ierr); 5436 ierr = PetscMemcpy(&ly,&y,sizeof(u));CHKERRQ(ierr); 5437 5438 prhs[0] = mxCreateDoubleScalar((double)ls); 5439 prhs[1] = mxCreateDoubleScalar(time); 5440 prhs[2] = mxCreateDoubleScalar((double)lx); 5441 prhs[3] = mxCreateDoubleScalar((double)lxdot); 5442 prhs[4] = mxCreateDoubleScalar((double)ly); 5443 prhs[5] = mxCreateString(sctx->funcname); 5444 prhs[6] = sctx->ctx; 5445 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSComputeFunctionInternal");CHKERRQ(ierr); 5446 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 5447 mxDestroyArray(prhs[0]); 5448 mxDestroyArray(prhs[1]); 5449 mxDestroyArray(prhs[2]); 5450 mxDestroyArray(prhs[3]); 5451 mxDestroyArray(prhs[4]); 5452 mxDestroyArray(prhs[5]); 5453 mxDestroyArray(plhs[0]); 5454 PetscFunctionReturn(0); 5455 } 5456 5457 5458 #undef __FUNCT__ 5459 #define __FUNCT__ "TSSetFunctionMatlab" 5460 /* 5461 TSSetFunctionMatlab - Sets the function evaluation routine and function 5462 vector for use by the TS routines in solving ODEs 5463 equations from MATLAB. Here the function is a string containing the name of a MATLAB function 5464 5465 Logically Collective on TS 5466 5467 Input Parameters: 5468 + ts - the TS context 5469 - func - function evaluation routine 5470 5471 Calling sequence of func: 5472 $ func (TS ts,PetscReal time,Vec u,Vec udot,Vec f,void *ctx); 5473 5474 Level: beginner 5475 5476 .keywords: TS, nonlinear, set, function 5477 5478 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 5479 */ 5480 PetscErrorCode TSSetFunctionMatlab(TS ts,const char *func,mxArray *ctx) 5481 { 5482 PetscErrorCode ierr; 5483 TSMatlabContext *sctx; 5484 5485 PetscFunctionBegin; 5486 /* currently sctx is memory bleed */ 5487 ierr = PetscMalloc(sizeof(TSMatlabContext),&sctx);CHKERRQ(ierr); 5488 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 5489 /* 5490 This should work, but it doesn't 5491 sctx->ctx = ctx; 5492 mexMakeArrayPersistent(sctx->ctx); 5493 */ 5494 sctx->ctx = mxDuplicateArray(ctx); 5495 5496 ierr = TSSetIFunction(ts,NULL,TSComputeFunction_Matlab,sctx);CHKERRQ(ierr); 5497 PetscFunctionReturn(0); 5498 } 5499 5500 #undef __FUNCT__ 5501 #define __FUNCT__ "TSComputeJacobian_Matlab" 5502 /* 5503 TSComputeJacobian_Matlab - Calls the function that has been set with 5504 TSSetJacobianMatlab(). 5505 5506 Collective on TS 5507 5508 Input Parameters: 5509 + ts - the TS context 5510 . u - input vector 5511 . A, B - the matrices 5512 - ctx - user context 5513 5514 Level: developer 5515 5516 .keywords: TS, nonlinear, compute, function 5517 5518 .seealso: TSSetFunction(), TSGetFunction() 5519 @*/ 5520 PetscErrorCode TSComputeJacobian_Matlab(TS ts,PetscReal time,Vec u,Vec udot,PetscReal shift,Mat A,Mat B,void *ctx) 5521 { 5522 PetscErrorCode ierr; 5523 TSMatlabContext *sctx = (TSMatlabContext*)ctx; 5524 int nlhs = 2,nrhs = 9; 5525 mxArray *plhs[2],*prhs[9]; 5526 long long int lx = 0,lxdot = 0,lA = 0,ls = 0, lB = 0; 5527 5528 PetscFunctionBegin; 5529 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5530 PetscValidHeaderSpecific(u,VEC_CLASSID,3); 5531 5532 /* call Matlab function in ctx with arguments u and y */ 5533 5534 ierr = PetscMemcpy(&ls,&ts,sizeof(ts));CHKERRQ(ierr); 5535 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 5536 ierr = PetscMemcpy(&lxdot,&udot,sizeof(u));CHKERRQ(ierr); 5537 ierr = PetscMemcpy(&lA,A,sizeof(u));CHKERRQ(ierr); 5538 ierr = PetscMemcpy(&lB,B,sizeof(u));CHKERRQ(ierr); 5539 5540 prhs[0] = mxCreateDoubleScalar((double)ls); 5541 prhs[1] = mxCreateDoubleScalar((double)time); 5542 prhs[2] = mxCreateDoubleScalar((double)lx); 5543 prhs[3] = mxCreateDoubleScalar((double)lxdot); 5544 prhs[4] = mxCreateDoubleScalar((double)shift); 5545 prhs[5] = mxCreateDoubleScalar((double)lA); 5546 prhs[6] = mxCreateDoubleScalar((double)lB); 5547 prhs[7] = mxCreateString(sctx->funcname); 5548 prhs[8] = sctx->ctx; 5549 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSComputeJacobianInternal");CHKERRQ(ierr); 5550 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 5551 mxDestroyArray(prhs[0]); 5552 mxDestroyArray(prhs[1]); 5553 mxDestroyArray(prhs[2]); 5554 mxDestroyArray(prhs[3]); 5555 mxDestroyArray(prhs[4]); 5556 mxDestroyArray(prhs[5]); 5557 mxDestroyArray(prhs[6]); 5558 mxDestroyArray(prhs[7]); 5559 mxDestroyArray(plhs[0]); 5560 mxDestroyArray(plhs[1]); 5561 PetscFunctionReturn(0); 5562 } 5563 5564 5565 #undef __FUNCT__ 5566 #define __FUNCT__ "TSSetJacobianMatlab" 5567 /* 5568 TSSetJacobianMatlab - Sets the Jacobian function evaluation routine and two empty Jacobian matrices 5569 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 5570 5571 Logically Collective on TS 5572 5573 Input Parameters: 5574 + ts - the TS context 5575 . A,B - Jacobian matrices 5576 . func - function evaluation routine 5577 - ctx - user context 5578 5579 Calling sequence of func: 5580 $ flag = func (TS ts,PetscReal time,Vec u,Vec udot,Mat A,Mat B,void *ctx); 5581 5582 5583 Level: developer 5584 5585 .keywords: TS, nonlinear, set, function 5586 5587 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 5588 */ 5589 PetscErrorCode TSSetJacobianMatlab(TS ts,Mat A,Mat B,const char *func,mxArray *ctx) 5590 { 5591 PetscErrorCode ierr; 5592 TSMatlabContext *sctx; 5593 5594 PetscFunctionBegin; 5595 /* currently sctx is memory bleed */ 5596 ierr = PetscMalloc(sizeof(TSMatlabContext),&sctx);CHKERRQ(ierr); 5597 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 5598 /* 5599 This should work, but it doesn't 5600 sctx->ctx = ctx; 5601 mexMakeArrayPersistent(sctx->ctx); 5602 */ 5603 sctx->ctx = mxDuplicateArray(ctx); 5604 5605 ierr = TSSetIJacobian(ts,A,B,TSComputeJacobian_Matlab,sctx);CHKERRQ(ierr); 5606 PetscFunctionReturn(0); 5607 } 5608 5609 #undef __FUNCT__ 5610 #define __FUNCT__ "TSMonitor_Matlab" 5611 /* 5612 TSMonitor_Matlab - Calls the function that has been set with TSMonitorSetMatlab(). 5613 5614 Collective on TS 5615 5616 .seealso: TSSetFunction(), TSGetFunction() 5617 @*/ 5618 PetscErrorCode TSMonitor_Matlab(TS ts,PetscInt it, PetscReal time,Vec u, void *ctx) 5619 { 5620 PetscErrorCode ierr; 5621 TSMatlabContext *sctx = (TSMatlabContext*)ctx; 5622 int nlhs = 1,nrhs = 6; 5623 mxArray *plhs[1],*prhs[6]; 5624 long long int lx = 0,ls = 0; 5625 5626 PetscFunctionBegin; 5627 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 5628 PetscValidHeaderSpecific(u,VEC_CLASSID,4); 5629 5630 ierr = PetscMemcpy(&ls,&ts,sizeof(ts));CHKERRQ(ierr); 5631 ierr = PetscMemcpy(&lx,&u,sizeof(u));CHKERRQ(ierr); 5632 5633 prhs[0] = mxCreateDoubleScalar((double)ls); 5634 prhs[1] = mxCreateDoubleScalar((double)it); 5635 prhs[2] = mxCreateDoubleScalar((double)time); 5636 prhs[3] = mxCreateDoubleScalar((double)lx); 5637 prhs[4] = mxCreateString(sctx->funcname); 5638 prhs[5] = sctx->ctx; 5639 ierr = mexCallMATLAB(nlhs,plhs,nrhs,prhs,"PetscTSMonitorInternal");CHKERRQ(ierr); 5640 ierr = mxGetScalar(plhs[0]);CHKERRQ(ierr); 5641 mxDestroyArray(prhs[0]); 5642 mxDestroyArray(prhs[1]); 5643 mxDestroyArray(prhs[2]); 5644 mxDestroyArray(prhs[3]); 5645 mxDestroyArray(prhs[4]); 5646 mxDestroyArray(plhs[0]); 5647 PetscFunctionReturn(0); 5648 } 5649 5650 5651 #undef __FUNCT__ 5652 #define __FUNCT__ "TSMonitorSetMatlab" 5653 /* 5654 TSMonitorSetMatlab - Sets the monitor function from Matlab 5655 5656 Level: developer 5657 5658 .keywords: TS, nonlinear, set, function 5659 5660 .seealso: TSGetFunction(), TSComputeFunction(), TSSetJacobian(), TSSetFunction() 5661 */ 5662 PetscErrorCode TSMonitorSetMatlab(TS ts,const char *func,mxArray *ctx) 5663 { 5664 PetscErrorCode ierr; 5665 TSMatlabContext *sctx; 5666 5667 PetscFunctionBegin; 5668 /* currently sctx is memory bleed */ 5669 ierr = PetscMalloc(sizeof(TSMatlabContext),&sctx);CHKERRQ(ierr); 5670 ierr = PetscStrallocpy(func,&sctx->funcname);CHKERRQ(ierr); 5671 /* 5672 This should work, but it doesn't 5673 sctx->ctx = ctx; 5674 mexMakeArrayPersistent(sctx->ctx); 5675 */ 5676 sctx->ctx = mxDuplicateArray(ctx); 5677 5678 ierr = TSMonitorSet(ts,TSMonitor_Matlab,sctx,NULL);CHKERRQ(ierr); 5679 PetscFunctionReturn(0); 5680 } 5681 #endif 5682 5683 #undef __FUNCT__ 5684 #define __FUNCT__ "TSMonitorLGSolution" 5685 /*@C 5686 TSMonitorLGSolution - Monitors progress of the TS solvers by plotting each component of the solution vector 5687 in a time based line graph 5688 5689 Collective on TS 5690 5691 Input Parameters: 5692 + ts - the TS context 5693 . step - current time-step 5694 . ptime - current time 5695 - lg - a line graph object 5696 5697 Options Database: 5698 . -ts_monitor_lg_solution_variables 5699 5700 Level: intermediate 5701 5702 Notes: each process in a parallel run displays its component solutions in a separate window 5703 5704 .keywords: TS, vector, monitor, view 5705 5706 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView() 5707 @*/ 5708 PetscErrorCode TSMonitorLGSolution(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 5709 { 5710 PetscErrorCode ierr; 5711 TSMonitorLGCtx ctx = (TSMonitorLGCtx)dummy; 5712 const PetscScalar *yy; 5713 PetscInt dim; 5714 Vec v; 5715 5716 PetscFunctionBegin; 5717 if (!step) { 5718 PetscDrawAxis axis; 5719 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 5720 ierr = PetscDrawAxisSetLabels(axis,"Solution as function of time","Time","Solution");CHKERRQ(ierr); 5721 if (ctx->names && !ctx->displaynames) { 5722 char **displaynames; 5723 PetscBool flg; 5724 5725 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 5726 ierr = PetscMalloc((dim+1)*sizeof(char*),&displaynames);CHKERRQ(ierr); 5727 ierr = PetscMemzero(displaynames,(dim+1)*sizeof(char*));CHKERRQ(ierr); 5728 ierr = PetscOptionsGetStringArray(((PetscObject)ts)->prefix,"-ts_monitor_lg_solution_variables",displaynames,&dim,&flg);CHKERRQ(ierr); 5729 if (flg) { 5730 ierr = TSMonitorLGCtxSetDisplayVariables(ctx,(const char *const *)displaynames);CHKERRQ(ierr); 5731 } 5732 ierr = PetscStrArrayDestroy(&displaynames);CHKERRQ(ierr); 5733 } 5734 if (ctx->displaynames) { 5735 ierr = PetscDrawLGSetDimension(ctx->lg,ctx->ndisplayvariables);CHKERRQ(ierr); 5736 ierr = PetscDrawLGSetLegend(ctx->lg,(const char *const *)ctx->displaynames);CHKERRQ(ierr); 5737 } else if (ctx->names) { 5738 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 5739 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 5740 ierr = PetscDrawLGSetLegend(ctx->lg,(const char *const *)ctx->names);CHKERRQ(ierr); 5741 } 5742 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 5743 } 5744 if (ctx->transform) { 5745 ierr = (*ctx->transform)(ctx->transformctx,u,&v);CHKERRQ(ierr); 5746 } else { 5747 v = u; 5748 } 5749 ierr = VecGetArrayRead(v,&yy);CHKERRQ(ierr); 5750 #if defined(PETSC_USE_COMPLEX) 5751 { 5752 PetscReal *yreal; 5753 PetscInt i,n; 5754 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 5755 ierr = PetscMalloc1(n,&yreal);CHKERRQ(ierr); 5756 for (i=0; i<n; i++) yreal[i] = PetscRealPart(yy[i]); 5757 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yreal);CHKERRQ(ierr); 5758 ierr = PetscFree(yreal);CHKERRQ(ierr); 5759 } 5760 #else 5761 if (ctx->displaynames) { 5762 PetscInt i; 5763 for (i=0; i<ctx->ndisplayvariables; i++) { 5764 ctx->displayvalues[i] = yy[ctx->displayvariables[i]]; 5765 } 5766 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,ctx->displayvalues);CHKERRQ(ierr); 5767 } else { 5768 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yy);CHKERRQ(ierr); 5769 } 5770 #endif 5771 ierr = VecRestoreArrayRead(v,&yy);CHKERRQ(ierr); 5772 if (ctx->transform) { 5773 ierr = VecDestroy(&v);CHKERRQ(ierr); 5774 } 5775 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 5776 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 5777 } 5778 PetscFunctionReturn(0); 5779 } 5780 5781 5782 #undef __FUNCT__ 5783 #define __FUNCT__ "TSMonitorLGSetVariableNames" 5784 /*@C 5785 TSMonitorLGSetVariableNames - Sets the name of each component in the solution vector so that it may be displayed in the plot 5786 5787 Collective on TS 5788 5789 Input Parameters: 5790 + ts - the TS context 5791 - names - the names of the components, final string must be NULL 5792 5793 Level: intermediate 5794 5795 .keywords: TS, vector, monitor, view 5796 5797 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables(), TSMonitorLGCtxSetVariableNames() 5798 @*/ 5799 PetscErrorCode TSMonitorLGSetVariableNames(TS ts,const char * const *names) 5800 { 5801 PetscErrorCode ierr; 5802 PetscInt i; 5803 5804 PetscFunctionBegin; 5805 for (i=0; i<ts->numbermonitors; i++) { 5806 if (ts->monitor[i] == TSMonitorLGSolution) { 5807 ierr = TSMonitorLGCtxSetVariableNames((TSMonitorLGCtx)ts->monitorcontext[i],names);CHKERRQ(ierr); 5808 break; 5809 } 5810 } 5811 PetscFunctionReturn(0); 5812 } 5813 5814 #undef __FUNCT__ 5815 #define __FUNCT__ "TSMonitorLGCtxSetVariableNames" 5816 /*@C 5817 TSMonitorLGCtxSetVariableNames - Sets the name of each component in the solution vector so that it may be displayed in the plot 5818 5819 Collective on TS 5820 5821 Input Parameters: 5822 + ts - the TS context 5823 - names - the names of the components, final string must be NULL 5824 5825 Level: intermediate 5826 5827 .keywords: TS, vector, monitor, view 5828 5829 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables(), TSMonitorLGSetVariableNames() 5830 @*/ 5831 PetscErrorCode TSMonitorLGCtxSetVariableNames(TSMonitorLGCtx ctx,const char * const *names) 5832 { 5833 PetscErrorCode ierr; 5834 5835 PetscFunctionBegin; 5836 ierr = PetscStrArrayDestroy(&ctx->names);CHKERRQ(ierr); 5837 ierr = PetscStrArrayallocpy(names,&ctx->names);CHKERRQ(ierr); 5838 PetscFunctionReturn(0); 5839 } 5840 5841 #undef __FUNCT__ 5842 #define __FUNCT__ "TSMonitorLGGetVariableNames" 5843 /*@C 5844 TSMonitorLGGetVariableNames - Gets the name of each component in the solution vector so that it may be displayed in the plot 5845 5846 Collective on TS 5847 5848 Input Parameter: 5849 . ts - the TS context 5850 5851 Output Parameter: 5852 . names - the names of the components, final string must be NULL 5853 5854 Level: intermediate 5855 5856 .keywords: TS, vector, monitor, view 5857 5858 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables() 5859 @*/ 5860 PetscErrorCode TSMonitorLGGetVariableNames(TS ts,const char *const **names) 5861 { 5862 PetscInt i; 5863 5864 PetscFunctionBegin; 5865 *names = NULL; 5866 for (i=0; i<ts->numbermonitors; i++) { 5867 if (ts->monitor[i] == TSMonitorLGSolution) { 5868 TSMonitorLGCtx ctx = (TSMonitorLGCtx) ts->monitorcontext[i]; 5869 *names = (const char *const *)ctx->names; 5870 break; 5871 } 5872 } 5873 PetscFunctionReturn(0); 5874 } 5875 5876 #undef __FUNCT__ 5877 #define __FUNCT__ "TSMonitorLGCtxSetDisplayVariables" 5878 /*@C 5879 TSMonitorLGCtxSetDisplayVariables - Sets the variables that are to be display in the monitor 5880 5881 Collective on TS 5882 5883 Input Parameters: 5884 + ctx - the TSMonitorLG context 5885 . displaynames - the names of the components, final string must be NULL 5886 5887 Level: intermediate 5888 5889 .keywords: TS, vector, monitor, view 5890 5891 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames() 5892 @*/ 5893 PetscErrorCode TSMonitorLGCtxSetDisplayVariables(TSMonitorLGCtx ctx,const char * const *displaynames) 5894 { 5895 PetscInt j = 0,k; 5896 PetscErrorCode ierr; 5897 5898 PetscFunctionBegin; 5899 if (!ctx->names) PetscFunctionReturn(0); 5900 ierr = PetscStrArrayDestroy(&ctx->displaynames);CHKERRQ(ierr); 5901 ierr = PetscStrArrayallocpy(displaynames,&ctx->displaynames);CHKERRQ(ierr); 5902 while (displaynames[j]) j++; 5903 ctx->ndisplayvariables = j; 5904 ierr = PetscMalloc1(ctx->ndisplayvariables,&ctx->displayvariables);CHKERRQ(ierr); 5905 ierr = PetscMalloc1(ctx->ndisplayvariables,&ctx->displayvalues);CHKERRQ(ierr); 5906 j = 0; 5907 while (displaynames[j]) { 5908 k = 0; 5909 while (ctx->names[k]) { 5910 PetscBool flg; 5911 ierr = PetscStrcmp(displaynames[j],ctx->names[k],&flg);CHKERRQ(ierr); 5912 if (flg) { 5913 ctx->displayvariables[j] = k; 5914 break; 5915 } 5916 k++; 5917 } 5918 j++; 5919 } 5920 PetscFunctionReturn(0); 5921 } 5922 5923 5924 #undef __FUNCT__ 5925 #define __FUNCT__ "TSMonitorLGSetDisplayVariables" 5926 /*@C 5927 TSMonitorLGSetDisplayVariables - Sets the variables that are to be display in the monitor 5928 5929 Collective on TS 5930 5931 Input Parameters: 5932 + ts - the TS context 5933 . displaynames - the names of the components, final string must be NULL 5934 5935 Level: intermediate 5936 5937 .keywords: TS, vector, monitor, view 5938 5939 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames() 5940 @*/ 5941 PetscErrorCode TSMonitorLGSetDisplayVariables(TS ts,const char * const *displaynames) 5942 { 5943 PetscInt i; 5944 PetscErrorCode ierr; 5945 5946 PetscFunctionBegin; 5947 for (i=0; i<ts->numbermonitors; i++) { 5948 if (ts->monitor[i] == TSMonitorLGSolution) { 5949 ierr = TSMonitorLGCtxSetDisplayVariables((TSMonitorLGCtx)ts->monitorcontext[i],displaynames);CHKERRQ(ierr); 5950 break; 5951 } 5952 } 5953 PetscFunctionReturn(0); 5954 } 5955 5956 #undef __FUNCT__ 5957 #define __FUNCT__ "TSMonitorLGSetTransform" 5958 /*@C 5959 TSMonitorLGSetTransform - Solution vector will be transformed by provided function before being displayed 5960 5961 Collective on TS 5962 5963 Input Parameters: 5964 + ts - the TS context 5965 . transform - the transform function 5966 . destroy - function to destroy the optional context 5967 - ctx - optional context used by transform function 5968 5969 Level: intermediate 5970 5971 .keywords: TS, vector, monitor, view 5972 5973 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames(), TSMonitorLGCtxSetTransform() 5974 @*/ 5975 PetscErrorCode TSMonitorLGSetTransform(TS ts,PetscErrorCode (*transform)(void*,Vec,Vec*),PetscErrorCode (*destroy)(void*),void *tctx) 5976 { 5977 PetscInt i; 5978 PetscErrorCode ierr; 5979 5980 PetscFunctionBegin; 5981 for (i=0; i<ts->numbermonitors; i++) { 5982 if (ts->monitor[i] == TSMonitorLGSolution) { 5983 ierr = TSMonitorLGCtxSetTransform((TSMonitorLGCtx)ts->monitorcontext[i],transform,destroy,tctx);CHKERRQ(ierr); 5984 } 5985 } 5986 PetscFunctionReturn(0); 5987 } 5988 5989 #undef __FUNCT__ 5990 #define __FUNCT__ "TSMonitorLGCtxSetTransform" 5991 /*@C 5992 TSMonitorLGCtxSetTransform - Solution vector will be transformed by provided function before being displayed 5993 5994 Collective on TSLGCtx 5995 5996 Input Parameters: 5997 + ts - the TS context 5998 . transform - the transform function 5999 . destroy - function to destroy the optional context 6000 - ctx - optional context used by transform function 6001 6002 Level: intermediate 6003 6004 .keywords: TS, vector, monitor, view 6005 6006 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetVariableNames(), TSMonitorLGSetTransform() 6007 @*/ 6008 PetscErrorCode TSMonitorLGCtxSetTransform(TSMonitorLGCtx ctx,PetscErrorCode (*transform)(void*,Vec,Vec*),PetscErrorCode (*destroy)(void*),void *tctx) 6009 { 6010 PetscFunctionBegin; 6011 ctx->transform = transform; 6012 ctx->transformdestroy = destroy; 6013 ctx->transformctx = tctx; 6014 PetscFunctionReturn(0); 6015 } 6016 6017 #undef __FUNCT__ 6018 #define __FUNCT__ "TSMonitorLGError" 6019 /*@C 6020 TSMonitorLGError - Monitors progress of the TS solvers by plotting each component of the solution vector 6021 in a time based line graph 6022 6023 Collective on TS 6024 6025 Input Parameters: 6026 + ts - the TS context 6027 . step - current time-step 6028 . ptime - current time 6029 - lg - a line graph object 6030 6031 Level: intermediate 6032 6033 Notes: 6034 Only for sequential solves. 6035 6036 The user must provide the solution using TSSetSolutionFunction() to use this monitor. 6037 6038 Options Database Keys: 6039 . -ts_monitor_lg_error - create a graphical monitor of error history 6040 6041 .keywords: TS, vector, monitor, view 6042 6043 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSSetSolutionFunction() 6044 @*/ 6045 PetscErrorCode TSMonitorLGError(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 6046 { 6047 PetscErrorCode ierr; 6048 TSMonitorLGCtx ctx = (TSMonitorLGCtx)dummy; 6049 const PetscScalar *yy; 6050 Vec y; 6051 PetscInt dim; 6052 6053 PetscFunctionBegin; 6054 if (!step) { 6055 PetscDrawAxis axis; 6056 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 6057 ierr = PetscDrawAxisSetLabels(axis,"Error in solution as function of time","Time","Solution");CHKERRQ(ierr); 6058 ierr = VecGetLocalSize(u,&dim);CHKERRQ(ierr); 6059 ierr = PetscDrawLGSetDimension(ctx->lg,dim);CHKERRQ(ierr); 6060 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 6061 } 6062 ierr = VecDuplicate(u,&y);CHKERRQ(ierr); 6063 ierr = TSComputeSolutionFunction(ts,ptime,y);CHKERRQ(ierr); 6064 ierr = VecAXPY(y,-1.0,u);CHKERRQ(ierr); 6065 ierr = VecGetArrayRead(y,&yy);CHKERRQ(ierr); 6066 #if defined(PETSC_USE_COMPLEX) 6067 { 6068 PetscReal *yreal; 6069 PetscInt i,n; 6070 ierr = VecGetLocalSize(y,&n);CHKERRQ(ierr); 6071 ierr = PetscMalloc1(n,&yreal);CHKERRQ(ierr); 6072 for (i=0; i<n; i++) yreal[i] = PetscRealPart(yy[i]); 6073 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yreal);CHKERRQ(ierr); 6074 ierr = PetscFree(yreal);CHKERRQ(ierr); 6075 } 6076 #else 6077 ierr = PetscDrawLGAddCommonPoint(ctx->lg,ptime,yy);CHKERRQ(ierr); 6078 #endif 6079 ierr = VecRestoreArrayRead(y,&yy);CHKERRQ(ierr); 6080 ierr = VecDestroy(&y);CHKERRQ(ierr); 6081 if (((ctx->howoften > 0) && (!(step % ctx->howoften))) || ((ctx->howoften == -1) && ts->reason)) { 6082 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 6083 } 6084 PetscFunctionReturn(0); 6085 } 6086 6087 #undef __FUNCT__ 6088 #define __FUNCT__ "TSMonitorLGSNESIterations" 6089 PetscErrorCode TSMonitorLGSNESIterations(TS ts,PetscInt n,PetscReal ptime,Vec v,void *monctx) 6090 { 6091 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 6092 PetscReal x = ptime,y; 6093 PetscErrorCode ierr; 6094 PetscInt its; 6095 6096 PetscFunctionBegin; 6097 if (!n) { 6098 PetscDrawAxis axis; 6099 6100 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 6101 ierr = PetscDrawAxisSetLabels(axis,"Nonlinear iterations as function of time","Time","SNES Iterations");CHKERRQ(ierr); 6102 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 6103 6104 ctx->snes_its = 0; 6105 } 6106 ierr = TSGetSNESIterations(ts,&its);CHKERRQ(ierr); 6107 y = its - ctx->snes_its; 6108 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 6109 if (((ctx->howoften > 0) && (!(n % ctx->howoften)) && (n > -1)) || ((ctx->howoften == -1) && (n == -1))) { 6110 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 6111 } 6112 ctx->snes_its = its; 6113 PetscFunctionReturn(0); 6114 } 6115 6116 #undef __FUNCT__ 6117 #define __FUNCT__ "TSMonitorLGKSPIterations" 6118 PetscErrorCode TSMonitorLGKSPIterations(TS ts,PetscInt n,PetscReal ptime,Vec v,void *monctx) 6119 { 6120 TSMonitorLGCtx ctx = (TSMonitorLGCtx) monctx; 6121 PetscReal x = ptime,y; 6122 PetscErrorCode ierr; 6123 PetscInt its; 6124 6125 PetscFunctionBegin; 6126 if (!n) { 6127 PetscDrawAxis axis; 6128 6129 ierr = PetscDrawLGGetAxis(ctx->lg,&axis);CHKERRQ(ierr); 6130 ierr = PetscDrawAxisSetLabels(axis,"Linear iterations as function of time","Time","KSP Iterations");CHKERRQ(ierr); 6131 ierr = PetscDrawLGReset(ctx->lg);CHKERRQ(ierr); 6132 6133 ctx->ksp_its = 0; 6134 } 6135 ierr = TSGetKSPIterations(ts,&its);CHKERRQ(ierr); 6136 y = its - ctx->ksp_its; 6137 ierr = PetscDrawLGAddPoint(ctx->lg,&x,&y);CHKERRQ(ierr); 6138 if (((ctx->howoften > 0) && (!(n % ctx->howoften)) && (n > -1)) || ((ctx->howoften == -1) && (n == -1))) { 6139 ierr = PetscDrawLGDraw(ctx->lg);CHKERRQ(ierr); 6140 } 6141 ctx->ksp_its = its; 6142 PetscFunctionReturn(0); 6143 } 6144 6145 #undef __FUNCT__ 6146 #define __FUNCT__ "TSComputeLinearStability" 6147 /*@ 6148 TSComputeLinearStability - computes the linear stability function at a point 6149 6150 Collective on TS and Vec 6151 6152 Input Parameters: 6153 + ts - the TS context 6154 - xr,xi - real and imaginary part of input arguments 6155 6156 Output Parameters: 6157 . yr,yi - real and imaginary part of function value 6158 6159 Level: developer 6160 6161 .keywords: TS, compute 6162 6163 .seealso: TSSetRHSFunction(), TSComputeIFunction() 6164 @*/ 6165 PetscErrorCode TSComputeLinearStability(TS ts,PetscReal xr,PetscReal xi,PetscReal *yr,PetscReal *yi) 6166 { 6167 PetscErrorCode ierr; 6168 6169 PetscFunctionBegin; 6170 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 6171 if (!ts->ops->linearstability) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Linearized stability function not provided for this method"); 6172 ierr = (*ts->ops->linearstability)(ts,xr,xi,yr,yi);CHKERRQ(ierr); 6173 PetscFunctionReturn(0); 6174 } 6175 6176 /* ------------------------------------------------------------------------*/ 6177 #undef __FUNCT__ 6178 #define __FUNCT__ "TSMonitorEnvelopeCtxCreate" 6179 /*@C 6180 TSMonitorEnvelopeCtxCreate - Creates a context for use with TSMonitorEnvelope() 6181 6182 Collective on TS 6183 6184 Input Parameters: 6185 . ts - the ODE solver object 6186 6187 Output Parameter: 6188 . ctx - the context 6189 6190 Level: intermediate 6191 6192 .keywords: TS, monitor, line graph, residual, seealso 6193 6194 .seealso: TSMonitorLGTimeStep(), TSMonitorSet(), TSMonitorLGSolution(), TSMonitorLGError() 6195 6196 @*/ 6197 PetscErrorCode TSMonitorEnvelopeCtxCreate(TS ts,TSMonitorEnvelopeCtx *ctx) 6198 { 6199 PetscErrorCode ierr; 6200 6201 PetscFunctionBegin; 6202 ierr = PetscNew(ctx);CHKERRQ(ierr); 6203 PetscFunctionReturn(0); 6204 } 6205 6206 #undef __FUNCT__ 6207 #define __FUNCT__ "TSMonitorEnvelope" 6208 /*@C 6209 TSMonitorEnvelope - Monitors the maximum and minimum value of each component of the solution 6210 6211 Collective on TS 6212 6213 Input Parameters: 6214 + ts - the TS context 6215 . step - current time-step 6216 . ptime - current time 6217 - ctx - the envelope context 6218 6219 Options Database: 6220 . -ts_monitor_envelope 6221 6222 Level: intermediate 6223 6224 Notes: after a solve you can use TSMonitorEnvelopeGetBounds() to access the envelope 6225 6226 .keywords: TS, vector, monitor, view 6227 6228 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorEnvelopeGetBounds() 6229 @*/ 6230 PetscErrorCode TSMonitorEnvelope(TS ts,PetscInt step,PetscReal ptime,Vec u,void *dummy) 6231 { 6232 PetscErrorCode ierr; 6233 TSMonitorEnvelopeCtx ctx = (TSMonitorEnvelopeCtx)dummy; 6234 6235 PetscFunctionBegin; 6236 if (!ctx->max) { 6237 ierr = VecDuplicate(u,&ctx->max);CHKERRQ(ierr); 6238 ierr = VecDuplicate(u,&ctx->min);CHKERRQ(ierr); 6239 ierr = VecCopy(u,ctx->max);CHKERRQ(ierr); 6240 ierr = VecCopy(u,ctx->min);CHKERRQ(ierr); 6241 } else { 6242 ierr = VecPointwiseMax(ctx->max,u,ctx->max);CHKERRQ(ierr); 6243 ierr = VecPointwiseMin(ctx->min,u,ctx->min);CHKERRQ(ierr); 6244 } 6245 PetscFunctionReturn(0); 6246 } 6247 6248 6249 #undef __FUNCT__ 6250 #define __FUNCT__ "TSMonitorEnvelopeGetBounds" 6251 /*@C 6252 TSMonitorEnvelopeGetBounds - Gets the bounds for the components of the solution 6253 6254 Collective on TS 6255 6256 Input Parameter: 6257 . ts - the TS context 6258 6259 Output Parameter: 6260 + max - the maximum values 6261 - min - the minimum values 6262 6263 Level: intermediate 6264 6265 .keywords: TS, vector, monitor, view 6266 6267 .seealso: TSMonitorSet(), TSMonitorDefault(), VecView(), TSMonitorLGSetDisplayVariables() 6268 @*/ 6269 PetscErrorCode TSMonitorEnvelopeGetBounds(TS ts,Vec *max,Vec *min) 6270 { 6271 PetscInt i; 6272 6273 PetscFunctionBegin; 6274 if (max) *max = NULL; 6275 if (min) *min = NULL; 6276 for (i=0; i<ts->numbermonitors; i++) { 6277 if (ts->monitor[i] == TSMonitorEnvelope) { 6278 TSMonitorEnvelopeCtx ctx = (TSMonitorEnvelopeCtx) ts->monitorcontext[i]; 6279 if (max) *max = ctx->max; 6280 if (min) *min = ctx->min; 6281 break; 6282 } 6283 } 6284 PetscFunctionReturn(0); 6285 } 6286 6287 #undef __FUNCT__ 6288 #define __FUNCT__ "TSMonitorEnvelopeCtxDestroy" 6289 /*@C 6290 TSMonitorEnvelopeCtxDestroy - Destroys a context that was created with TSMonitorEnvelopeCtxCreate(). 6291 6292 Collective on TSMonitorEnvelopeCtx 6293 6294 Input Parameter: 6295 . ctx - the monitor context 6296 6297 Level: intermediate 6298 6299 .keywords: TS, monitor, line graph, destroy 6300 6301 .seealso: TSMonitorLGCtxCreate(), TSMonitorSet(), TSMonitorLGTimeStep(); 6302 @*/ 6303 PetscErrorCode TSMonitorEnvelopeCtxDestroy(TSMonitorEnvelopeCtx *ctx) 6304 { 6305 PetscErrorCode ierr; 6306 6307 PetscFunctionBegin; 6308 ierr = VecDestroy(&(*ctx)->min);CHKERRQ(ierr); 6309 ierr = VecDestroy(&(*ctx)->max);CHKERRQ(ierr); 6310 ierr = PetscFree(*ctx);CHKERRQ(ierr); 6311 PetscFunctionReturn(0); 6312 } 6313 6314 #undef __FUNCT__ 6315 #define __FUNCT__ "TSRollBack" 6316 /*@ 6317 TSRollBack - Rolls back one time step 6318 6319 Collective on TS 6320 6321 Input Parameter: 6322 . ts - the TS context obtained from TSCreate() 6323 6324 Level: advanced 6325 6326 .keywords: TS, timestep, rollback 6327 6328 .seealso: TSCreate(), TSSetUp(), TSDestroy(), TSSolve(), TSSetPreStep(), TSSetPreStage(), TSInterpolate() 6329 @*/ 6330 PetscErrorCode TSRollBack(TS ts) 6331 { 6332 PetscErrorCode ierr; 6333 6334 PetscFunctionBegin; 6335 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 6336 6337 if (!ts->ops->rollback) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSRollBack not implemented for type '%s'",((PetscObject)ts)->type_name); 6338 ierr = (*ts->ops->rollback)(ts);CHKERRQ(ierr); 6339 ts->time_step = ts->ptime - ts->ptime_prev; 6340 ts->ptime = ts->ptime_prev; 6341 ts->steprollback = PETSC_TRUE; /* Flag to indicate that the step is rollbacked */ 6342 PetscFunctionReturn(0); 6343 } 6344 6345 #undef __FUNCT__ 6346 #define __FUNCT__ "TSGetStages" 6347 /*@ 6348 TSGetStages - Get the number of stages and stage values 6349 6350 Input Parameter: 6351 . ts - the TS context obtained from TSCreate() 6352 6353 Level: advanced 6354 6355 .keywords: TS, getstages 6356 6357 .seealso: TSCreate() 6358 @*/ 6359 PetscErrorCode TSGetStages(TS ts,PetscInt *ns, Vec **Y) 6360 { 6361 PetscErrorCode ierr; 6362 6363 PetscFunctionBegin; 6364 PetscValidHeaderSpecific(ts, TS_CLASSID,1); 6365 PetscValidPointer(ns,2); 6366 6367 if (!ts->ops->getstages) *ns=0; 6368 else { 6369 ierr = (*ts->ops->getstages)(ts,ns,Y);CHKERRQ(ierr); 6370 } 6371 PetscFunctionReturn(0); 6372 } 6373 6374 6375 #undef __FUNCT__ 6376 #define __FUNCT__ "TSComputeIJacobianDefaultColor" 6377 /*@C 6378 TSComputeIJacobianDefaultColor - Computes the Jacobian using finite differences and coloring to exploit matrix sparsity. 6379 6380 Collective on SNES 6381 6382 Input Parameters: 6383 + ts - the TS context 6384 . t - current timestep 6385 . U - state vector 6386 . Udot - time derivative of state vector 6387 . shift - shift to apply, see note below 6388 - ctx - an optional user context 6389 6390 Output Parameters: 6391 + J - Jacobian matrix (not altered in this routine) 6392 - B - newly computed Jacobian matrix to use with preconditioner (generally the same as J) 6393 6394 Level: intermediate 6395 6396 Notes: 6397 If F(t,U,Udot)=0 is the DAE, the required Jacobian is 6398 6399 dF/dU + shift*dF/dUdot 6400 6401 Most users should not need to explicitly call this routine, as it 6402 is used internally within the nonlinear solvers. 6403 6404 This will first try to get the coloring from the DM. If the DM type has no coloring 6405 routine, then it will try to get the coloring from the matrix. This requires that the 6406 matrix have nonzero entries precomputed. 6407 6408 .keywords: TS, finite differences, Jacobian, coloring, sparse 6409 .seealso: TSSetIJacobian(), MatFDColoringCreate(), MatFDColoringSetFunction() 6410 @*/ 6411 PetscErrorCode TSComputeIJacobianDefaultColor(TS ts,PetscReal t,Vec U,Vec Udot,PetscReal shift,Mat J,Mat B,void *ctx) 6412 { 6413 SNES snes; 6414 MatFDColoring color; 6415 PetscBool hascolor, matcolor = PETSC_FALSE; 6416 PetscErrorCode ierr; 6417 6418 PetscFunctionBegin; 6419 ierr = PetscOptionsGetBool(((PetscObject) ts)->prefix, "-ts_fd_color_use_mat", &matcolor, NULL);CHKERRQ(ierr); 6420 ierr = PetscObjectQuery((PetscObject) B, "TSMatFDColoring", (PetscObject *) &color);CHKERRQ(ierr); 6421 if (!color) { 6422 DM dm; 6423 ISColoring iscoloring; 6424 6425 ierr = TSGetDM(ts, &dm);CHKERRQ(ierr); 6426 ierr = DMHasColoring(dm, &hascolor);CHKERRQ(ierr); 6427 if (hascolor && !matcolor) { 6428 ierr = DMCreateColoring(dm, IS_COLORING_GLOBAL, &iscoloring);CHKERRQ(ierr); 6429 ierr = MatFDColoringCreate(B, iscoloring, &color);CHKERRQ(ierr); 6430 ierr = MatFDColoringSetFunction(color, (PetscErrorCode (*)(void)) SNESTSFormFunction, (void *) ts);CHKERRQ(ierr); 6431 ierr = MatFDColoringSetFromOptions(color);CHKERRQ(ierr); 6432 ierr = MatFDColoringSetUp(B, iscoloring, color);CHKERRQ(ierr); 6433 ierr = ISColoringDestroy(&iscoloring);CHKERRQ(ierr); 6434 } else { 6435 MatColoring mc; 6436 6437 ierr = MatColoringCreate(B, &mc);CHKERRQ(ierr); 6438 ierr = MatColoringSetDistance(mc, 2);CHKERRQ(ierr); 6439 ierr = MatColoringSetType(mc, MATCOLORINGSL);CHKERRQ(ierr); 6440 ierr = MatColoringSetFromOptions(mc);CHKERRQ(ierr); 6441 ierr = MatColoringApply(mc, &iscoloring);CHKERRQ(ierr); 6442 ierr = MatColoringDestroy(&mc);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 } 6449 ierr = PetscObjectCompose((PetscObject) B, "TSMatFDColoring", (PetscObject) color);CHKERRQ(ierr); 6450 ierr = PetscObjectDereference((PetscObject) color);CHKERRQ(ierr); 6451 } 6452 ierr = TSGetSNES(ts, &snes);CHKERRQ(ierr); 6453 ierr = MatFDColoringApply(B, color, U, snes);CHKERRQ(ierr); 6454 if (J != B) { 6455 ierr = MatAssemblyBegin(J, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 6456 ierr = MatAssemblyEnd(J, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 6457 } 6458 PetscFunctionReturn(0); 6459 } 6460