1 /* 2 Code for timestepping with implicit Theta method 3 */ 4 #include <petsc-private/tsimpl.h> /*I "petscts.h" I*/ 5 #include <petscsnes.h> 6 #include <petscdm.h> 7 #include <petscmat.h> 8 9 typedef struct { 10 Vec X,Xdot; /* Storage for one stage */ 11 Vec X0; /* work vector to store X0 */ 12 Vec affine; /* Affine vector needed for residual at beginning of step */ 13 Vec *VecDeltaLam; /* Increment of the adjoint sensitivity w.r.t IC at stage*/ 14 Vec *VecDeltaMu; /* Increment of the adjoint sensitivity w.r.t P at stage*/ 15 Vec *VecSensiTemp; /* Vector to be timed with Jacobian transpose*/ 16 PetscBool extrapolate; 17 PetscBool endpoint; 18 PetscReal Theta; 19 PetscReal stage_time; 20 TSStepStatus status; 21 char *name; 22 PetscInt order; 23 PetscReal ccfl; /* Placeholder for CFL coefficient relative to forward Euler */ 24 PetscBool adapt; /* use time-step adaptivity ? */ 25 } TS_Theta; 26 27 #undef __FUNCT__ 28 #define __FUNCT__ "TSThetaGetX0AndXdot" 29 static PetscErrorCode TSThetaGetX0AndXdot(TS ts,DM dm,Vec *X0,Vec *Xdot) 30 { 31 TS_Theta *th = (TS_Theta*)ts->data; 32 PetscErrorCode ierr; 33 34 PetscFunctionBegin; 35 if (X0) { 36 if (dm && dm != ts->dm) { 37 ierr = DMGetNamedGlobalVector(dm,"TSTheta_X0",X0);CHKERRQ(ierr); 38 } else *X0 = ts->vec_sol; 39 } 40 if (Xdot) { 41 if (dm && dm != ts->dm) { 42 ierr = DMGetNamedGlobalVector(dm,"TSTheta_Xdot",Xdot);CHKERRQ(ierr); 43 } else *Xdot = th->Xdot; 44 } 45 PetscFunctionReturn(0); 46 } 47 48 49 #undef __FUNCT__ 50 #define __FUNCT__ "TSThetaRestoreX0AndXdot" 51 static PetscErrorCode TSThetaRestoreX0AndXdot(TS ts,DM dm,Vec *X0,Vec *Xdot) 52 { 53 PetscErrorCode ierr; 54 55 PetscFunctionBegin; 56 if (X0) { 57 if (dm && dm != ts->dm) { 58 ierr = DMRestoreNamedGlobalVector(dm,"TSTheta_X0",X0);CHKERRQ(ierr); 59 } 60 } 61 if (Xdot) { 62 if (dm && dm != ts->dm) { 63 ierr = DMRestoreNamedGlobalVector(dm,"TSTheta_Xdot",Xdot);CHKERRQ(ierr); 64 } 65 } 66 PetscFunctionReturn(0); 67 } 68 69 #undef __FUNCT__ 70 #define __FUNCT__ "DMCoarsenHook_TSTheta" 71 static PetscErrorCode DMCoarsenHook_TSTheta(DM fine,DM coarse,void *ctx) 72 { 73 74 PetscFunctionBegin; 75 PetscFunctionReturn(0); 76 } 77 78 #undef __FUNCT__ 79 #define __FUNCT__ "DMRestrictHook_TSTheta" 80 static PetscErrorCode DMRestrictHook_TSTheta(DM fine,Mat restrct,Vec rscale,Mat inject,DM coarse,void *ctx) 81 { 82 TS ts = (TS)ctx; 83 PetscErrorCode ierr; 84 Vec X0,Xdot,X0_c,Xdot_c; 85 86 PetscFunctionBegin; 87 ierr = TSThetaGetX0AndXdot(ts,fine,&X0,&Xdot);CHKERRQ(ierr); 88 ierr = TSThetaGetX0AndXdot(ts,coarse,&X0_c,&Xdot_c);CHKERRQ(ierr); 89 ierr = MatRestrict(restrct,X0,X0_c);CHKERRQ(ierr); 90 ierr = MatRestrict(restrct,Xdot,Xdot_c);CHKERRQ(ierr); 91 ierr = VecPointwiseMult(X0_c,rscale,X0_c);CHKERRQ(ierr); 92 ierr = VecPointwiseMult(Xdot_c,rscale,Xdot_c);CHKERRQ(ierr); 93 ierr = TSThetaRestoreX0AndXdot(ts,fine,&X0,&Xdot);CHKERRQ(ierr); 94 ierr = TSThetaRestoreX0AndXdot(ts,coarse,&X0_c,&Xdot_c);CHKERRQ(ierr); 95 PetscFunctionReturn(0); 96 } 97 98 #undef __FUNCT__ 99 #define __FUNCT__ "DMSubDomainHook_TSTheta" 100 static PetscErrorCode DMSubDomainHook_TSTheta(DM dm,DM subdm,void *ctx) 101 { 102 103 PetscFunctionBegin; 104 PetscFunctionReturn(0); 105 } 106 107 #undef __FUNCT__ 108 #define __FUNCT__ "DMSubDomainRestrictHook_TSTheta" 109 static PetscErrorCode DMSubDomainRestrictHook_TSTheta(DM dm,VecScatter gscat,VecScatter lscat,DM subdm,void *ctx) 110 { 111 TS ts = (TS)ctx; 112 PetscErrorCode ierr; 113 Vec X0,Xdot,X0_sub,Xdot_sub; 114 115 PetscFunctionBegin; 116 ierr = TSThetaGetX0AndXdot(ts,dm,&X0,&Xdot);CHKERRQ(ierr); 117 ierr = TSThetaGetX0AndXdot(ts,subdm,&X0_sub,&Xdot_sub);CHKERRQ(ierr); 118 119 ierr = VecScatterBegin(gscat,X0,X0_sub,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 120 ierr = VecScatterEnd(gscat,X0,X0_sub,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 121 122 ierr = VecScatterBegin(gscat,Xdot,Xdot_sub,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 123 ierr = VecScatterEnd(gscat,Xdot,Xdot_sub,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 124 125 ierr = TSThetaRestoreX0AndXdot(ts,dm,&X0,&Xdot);CHKERRQ(ierr); 126 ierr = TSThetaRestoreX0AndXdot(ts,subdm,&X0_sub,&Xdot_sub);CHKERRQ(ierr); 127 PetscFunctionReturn(0); 128 } 129 130 #undef __FUNCT__ 131 #define __FUNCT__ "TSEvaluateStep_Theta" 132 static PetscErrorCode TSEvaluateStep_Theta(TS ts,PetscInt order,Vec U,PetscBool *done) 133 { 134 PetscErrorCode ierr; 135 TS_Theta *th = (TS_Theta*)ts->data; 136 137 PetscFunctionBegin; 138 if (order == 0) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_USER,"No time-step adaptivity implemented for 1st order theta method; Run with -ts_adapt_type none"); 139 if (order == th->order) { 140 if (th->endpoint) { 141 ierr = VecCopy(th->X,U);CHKERRQ(ierr); 142 } else { 143 PetscReal shift = 1./(th->Theta*ts->time_step); 144 ierr = VecAXPBYPCZ(th->Xdot,-shift,shift,0,U,th->X);CHKERRQ(ierr); 145 ierr = VecAXPY(U,ts->time_step,th->Xdot);CHKERRQ(ierr); 146 } 147 } else if (order == th->order-1 && order) { 148 ierr = VecWAXPY(U,ts->time_step,th->Xdot,th->X0);CHKERRQ(ierr); 149 } 150 PetscFunctionReturn(0); 151 } 152 153 #undef __FUNCT__ 154 #define __FUNCT__ "TSRollBack_Theta" 155 static PetscErrorCode TSRollBack_Theta(TS ts) 156 { 157 TS_Theta *th = (TS_Theta*)ts->data; 158 PetscErrorCode ierr; 159 160 PetscFunctionBegin; 161 ierr = VecCopy(th->X0,ts->vec_sol);CHKERRQ(ierr); 162 th->status = TS_STEP_INCOMPLETE; 163 PetscFunctionReturn(0); 164 } 165 166 #undef __FUNCT__ 167 #define __FUNCT__ "TSStep_Theta" 168 static PetscErrorCode TSStep_Theta(TS ts) 169 { 170 TS_Theta *th = (TS_Theta*)ts->data; 171 PetscInt its,lits,reject,next_scheme; 172 PetscReal next_time_step; 173 TSAdapt adapt; 174 PetscBool stageok,accept = PETSC_TRUE; 175 PetscErrorCode ierr; 176 177 PetscFunctionBegin; 178 th->status = TS_STEP_INCOMPLETE; 179 ierr = VecCopy(ts->vec_sol,th->X0);CHKERRQ(ierr); 180 for (reject=0; !ts->reason && th->status != TS_STEP_COMPLETE; ts->reject++) { 181 PetscReal shift = 1./(th->Theta*ts->time_step); 182 th->stage_time = ts->ptime + (th->endpoint ? 1. : th->Theta)*ts->time_step; 183 ierr = TSPreStep(ts);CHKERRQ(ierr); 184 ierr = TSPreStage(ts,th->stage_time);CHKERRQ(ierr); 185 186 if (th->endpoint) { /* This formulation assumes linear time-independent mass matrix */ 187 ierr = VecZeroEntries(th->Xdot);CHKERRQ(ierr); 188 if (!th->affine) {ierr = VecDuplicate(ts->vec_sol,&th->affine);CHKERRQ(ierr);} 189 ierr = TSComputeIFunction(ts,ts->ptime,ts->vec_sol,th->Xdot,th->affine,PETSC_FALSE);CHKERRQ(ierr); 190 ierr = VecScale(th->affine,(th->Theta-1.)/th->Theta);CHKERRQ(ierr); 191 } 192 if (th->extrapolate) { 193 ierr = VecWAXPY(th->X,1./shift,th->Xdot,ts->vec_sol);CHKERRQ(ierr); 194 } else { 195 ierr = VecCopy(ts->vec_sol,th->X);CHKERRQ(ierr); 196 } 197 ierr = SNESSolve(ts->snes,th->affine,th->X);CHKERRQ(ierr); 198 ierr = SNESGetIterationNumber(ts->snes,&its);CHKERRQ(ierr); 199 ierr = SNESGetLinearSolveIterations(ts->snes,&lits);CHKERRQ(ierr); 200 ts->snes_its += its; ts->ksp_its += lits; 201 ierr = TSPostStage(ts,th->stage_time,0,&(th->X));CHKERRQ(ierr); 202 ierr = TSGetAdapt(ts,&adapt);CHKERRQ(ierr); 203 ierr = TSAdaptCheckStage(adapt,ts,&stageok);CHKERRQ(ierr); 204 if (!stageok) {accept = PETSC_FALSE; goto reject_step;} 205 206 ierr = TSEvaluateStep(ts,th->order,ts->vec_sol,NULL);CHKERRQ(ierr); 207 th->status = TS_STEP_PENDING; 208 /* Register only the current method as a candidate because we're not supporting multiple candidates yet. */ 209 ierr = TSGetAdapt(ts,&adapt);CHKERRQ(ierr); 210 ierr = TSAdaptCandidatesClear(adapt);CHKERRQ(ierr); 211 ierr = TSAdaptCandidateAdd(adapt,NULL,th->order,1,th->ccfl,1.0,PETSC_TRUE);CHKERRQ(ierr); 212 ierr = TSAdaptChoose(adapt,ts,ts->time_step,&next_scheme,&next_time_step,&accept);CHKERRQ(ierr); 213 if (!accept) { /* Roll back the current step */ 214 ts->ptime += next_time_step; /* This will be undone in rollback */ 215 th->status = TS_STEP_INCOMPLETE; 216 ierr = TSRollBack(ts);CHKERRQ(ierr); 217 goto reject_step; 218 } 219 220 /* This in only used in the context of TSAdjoint. Evaluate cost integral if there is any */ 221 if (ts->vec_costintegral) { 222 /* Evolve ts->vec_costintegral to compute integrals */ 223 if (th->endpoint) { 224 ierr = TSAdjointComputeCostIntegrand(ts,ts->ptime,th->X0,ts->vec_costintegrand);CHKERRQ(ierr); 225 ierr = VecAXPY(ts->vec_costintegral,ts->time_step*(1.-th->Theta),ts->vec_costintegrand);CHKERRQ(ierr); 226 } 227 ierr = TSAdjointComputeCostIntegrand(ts,th->stage_time,th->X,ts->vec_costintegrand);CHKERRQ(ierr); 228 if (th->endpoint) { 229 ierr = VecAXPY(ts->vec_costintegral,ts->time_step*th->Theta,ts->vec_costintegrand);CHKERRQ(ierr); 230 }else { 231 ierr = VecAXPY(ts->vec_costintegral,ts->time_step,ts->vec_costintegrand);CHKERRQ(ierr); 232 } 233 } 234 235 /* ignore next_scheme for now */ 236 ts->ptime += ts->time_step; 237 ts->time_step = next_time_step; 238 ts->steps++; 239 th->status = TS_STEP_COMPLETE; 240 break; 241 242 reject_step: 243 if (!ts->reason && ++reject > ts->max_reject && ts->max_reject >= 0) { 244 ts->reason = TS_DIVERGED_STEP_REJECTED; 245 ierr = PetscInfo2(ts,"Step=%D, step rejections %D greater than current TS allowed, stopping solve\n",ts->steps,reject);CHKERRQ(ierr); 246 } 247 continue; 248 } 249 PetscFunctionReturn(0); 250 } 251 252 #undef __FUNCT__ 253 #define __FUNCT__ "TSAdjointStep_Theta" 254 static PetscErrorCode TSAdjointStep_Theta(TS ts) 255 { 256 TS_Theta *th = (TS_Theta*)ts->data; 257 Vec *VecDeltaLam = th->VecDeltaLam,*VecDeltaMu = th->VecDeltaMu,*VecSensiTemp = th->VecSensiTemp; 258 PetscInt nadj; 259 PetscErrorCode ierr; 260 Mat J,Jp; 261 KSP ksp; 262 PetscReal shift; 263 264 PetscFunctionBegin; 265 266 th->status = TS_STEP_INCOMPLETE; 267 ierr = SNESGetKSP(ts->snes,&ksp); 268 ierr = TSGetIJacobian(ts,&J,&Jp,NULL,NULL);CHKERRQ(ierr); 269 th->stage_time = ts->ptime + (th->endpoint ? ts->time_step : (1.-th->Theta)*ts->time_step); /* time_step is negative*/ 270 271 ierr = TSPreStep(ts);CHKERRQ(ierr); 272 273 /* Build RHS */ 274 if (ts->vec_costintegral) { /* Cost function has an integral term */ 275 if (th->endpoint) { 276 ierr = TSAdjointComputeDRDYFunction(ts,ts->ptime,ts->vec_sol,ts->vecs_drdy);CHKERRQ(ierr); 277 }else { 278 ierr = TSAdjointComputeDRDYFunction(ts,th->stage_time,th->X,ts->vecs_drdy);CHKERRQ(ierr); 279 } 280 } 281 for (nadj=0; nadj<ts->numcost; nadj++) { 282 ierr = VecCopy(ts->vecs_sensi[nadj],VecSensiTemp[nadj]);CHKERRQ(ierr); 283 ierr = VecScale(VecSensiTemp[nadj],-1./(th->Theta*ts->time_step));CHKERRQ(ierr); 284 if (ts->vec_costintegral) { 285 ierr = VecAXPY(VecSensiTemp[nadj],1.,ts->vecs_drdy[nadj]);CHKERRQ(ierr); 286 } 287 } 288 289 /* Build LHS */ 290 shift = -1./(th->Theta*ts->time_step); 291 if (th->endpoint) { 292 ierr = TSComputeIJacobian(ts,ts->ptime,ts->vec_sol,th->Xdot,shift,J,Jp,PETSC_FALSE);CHKERRQ(ierr); 293 }else { 294 ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,shift,J,Jp,PETSC_FALSE);CHKERRQ(ierr); 295 } 296 ierr = KSPSetOperators(ksp,J,Jp);CHKERRQ(ierr); 297 298 /* Solve LHS X = RHS */ 299 for (nadj=0; nadj<ts->numcost; nadj++) { 300 ierr = KSPSolveTranspose(ksp,VecSensiTemp[nadj],VecDeltaLam[nadj]);CHKERRQ(ierr); 301 } 302 303 /* Update sensitivities, and evaluate integrals if there is any */ 304 if(th->endpoint && th->Theta!=1.) { /* two-stage case */ 305 shift = -1./((th->Theta-1.)*ts->time_step); 306 ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,shift,J,Jp,PETSC_FALSE);CHKERRQ(ierr); 307 if (ts->vec_costintegral) { 308 ierr = TSAdjointComputeDRDYFunction(ts,th->stage_time,th->X,ts->vecs_drdy);CHKERRQ(ierr); 309 } 310 if (!ts->costintegraldone) { 311 /* Evolve ts->vec_costintegral to compute integrals */ 312 ierr = TSAdjointComputeCostIntegrand(ts,ts->ptime,ts->vec_sol,ts->vec_costintegrand);CHKERRQ(ierr); 313 ierr = VecAXPY(ts->vec_costintegral,-ts->time_step*th->Theta,ts->vec_costintegrand);CHKERRQ(ierr); 314 ierr = TSAdjointComputeCostIntegrand(ts,th->stage_time,th->X,ts->vec_costintegrand);CHKERRQ(ierr); 315 ierr = VecAXPY(ts->vec_costintegral,ts->time_step*(th->Theta-1.),ts->vec_costintegrand);CHKERRQ(ierr); 316 } 317 for (nadj=0; nadj<ts->numcost; nadj++) { 318 ierr = MatMultTranspose(J,VecDeltaLam[nadj],ts->vecs_sensi[nadj]);CHKERRQ(ierr); 319 if (ts->vec_costintegral) { 320 ierr = VecAXPY(ts->vecs_sensi[nadj],-1.,ts->vecs_drdy[nadj]);CHKERRQ(ierr); 321 } 322 ierr = VecScale(ts->vecs_sensi[nadj],1./shift);CHKERRQ(ierr); 323 } 324 325 if (ts->vecs_sensip) { /* sensitivities wrt parameters */ 326 ierr = TSAdjointComputeRHSJacobian(ts,ts->ptime,ts->vec_sol,ts->Jacp);CHKERRQ(ierr); 327 for (nadj=0; nadj<ts->numcost; nadj++) { 328 ierr = MatMultTranspose(ts->Jacp,VecDeltaLam[nadj],VecDeltaMu[nadj]);CHKERRQ(ierr); 329 ierr = VecAXPY(ts->vecs_sensip[nadj],-ts->time_step*th->Theta,VecDeltaMu[nadj]);CHKERRQ(ierr); 330 } 331 ierr = TSAdjointComputeRHSJacobian(ts,th->stage_time,th->X,ts->Jacp);CHKERRQ(ierr); 332 for (nadj=0; nadj<ts->numcost; nadj++) { 333 ierr = MatMultTranspose(ts->Jacp,VecDeltaLam[nadj],VecDeltaMu[nadj]);CHKERRQ(ierr); 334 ierr = VecAXPY(ts->vecs_sensip[nadj],-ts->time_step*(1.-th->Theta),VecDeltaMu[nadj]);CHKERRQ(ierr); 335 } 336 if (ts->vec_costintegral) { 337 ierr = TSAdjointComputeDRDPFunction(ts,ts->ptime,ts->vec_sol,ts->vecs_drdp);CHKERRQ(ierr); 338 for (nadj=0; nadj<ts->numcost; nadj++) { 339 ierr = VecAXPY(ts->vecs_sensip[nadj],-ts->time_step*th->Theta,ts->vecs_drdp[nadj]);CHKERRQ(ierr); 340 } 341 ierr = TSAdjointComputeDRDPFunction(ts,th->stage_time,th->X,ts->vecs_drdp);CHKERRQ(ierr); 342 for (nadj=0; nadj<ts->numcost; nadj++) { 343 ierr = VecAXPY(ts->vecs_sensip[nadj],-ts->time_step*(1.-th->Theta),ts->vecs_drdp[nadj]);CHKERRQ(ierr); 344 } 345 } 346 } 347 }else { /* one-stage case */ 348 shift = 0.0; 349 ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,shift,J,Jp,PETSC_FALSE);CHKERRQ(ierr); /* get -f_y */ 350 if (ts->vec_costintegral) { 351 ierr = TSAdjointComputeDRDYFunction(ts,th->stage_time,th->X,ts->vecs_drdy);CHKERRQ(ierr); 352 } 353 if (!ts->costintegraldone) { 354 /* Evolve ts->vec_costintegral to compute integrals */ 355 ierr = TSAdjointComputeCostIntegrand(ts,th->stage_time,th->X,ts->vec_costintegrand);CHKERRQ(ierr); 356 ierr = VecAXPY(ts->vec_costintegral,-ts->time_step,ts->vec_costintegrand);CHKERRQ(ierr); 357 } 358 /* When th->endpoint is true and th->Theta==1 (beuler method), the Jacobian is supposed to be evaluated at ts->ptime like this: 359 if(th->endpoint) { 360 ierr = TSComputeIJacobian(ts,ts->ptime,ts->vec_sol,th->Xdot,shift,J,Jp,PETSC_FALSE);CHKERRQ(ierr); 361 } 362 but ts->ptime and ts->vec_sol have the same values as th->stage_time and th->X in this case. So the code is simplified here. 363 */ 364 for (nadj=0; nadj<ts->numcost; nadj++) { 365 ierr = MatMultTranspose(J,VecDeltaLam[nadj],VecSensiTemp[nadj]);CHKERRQ(ierr); 366 ierr = VecAXPY(ts->vecs_sensi[nadj],ts->time_step,VecSensiTemp[nadj]);CHKERRQ(ierr); 367 if (ts->vec_costintegral) { 368 ierr = VecAXPY(ts->vecs_sensi[nadj],-ts->time_step,ts->vecs_drdy[nadj]);CHKERRQ(ierr); 369 } 370 } 371 if (ts->vecs_sensip) { 372 ierr = TSAdjointComputeRHSJacobian(ts,th->stage_time,th->X,ts->Jacp);CHKERRQ(ierr); 373 for (nadj=0; nadj<ts->numcost; nadj++) { 374 ierr = MatMultTranspose(ts->Jacp,VecDeltaLam[nadj],VecDeltaMu[nadj]);CHKERRQ(ierr); 375 ierr = VecAXPY(ts->vecs_sensip[nadj],-ts->time_step,VecDeltaMu[nadj]);CHKERRQ(ierr); 376 } 377 if (ts->vec_costintegral) { 378 ierr = TSAdjointComputeDRDPFunction(ts,th->stage_time,th->X,ts->vecs_drdp);CHKERRQ(ierr); 379 for (nadj=0; nadj<ts->numcost; nadj++) { 380 ierr = VecAXPY(ts->vecs_sensip[nadj],-ts->time_step,ts->vecs_drdp[nadj]);CHKERRQ(ierr); 381 } 382 } 383 } 384 } 385 386 ts->ptime += ts->time_step; 387 ts->steps++; 388 th->status = TS_STEP_COMPLETE; 389 PetscFunctionReturn(0); 390 } 391 392 #undef __FUNCT__ 393 #define __FUNCT__ "TSInterpolate_Theta" 394 static PetscErrorCode TSInterpolate_Theta(TS ts,PetscReal t,Vec X) 395 { 396 TS_Theta *th = (TS_Theta*)ts->data; 397 PetscReal alpha = t - ts->ptime; 398 PetscErrorCode ierr; 399 400 PetscFunctionBegin; 401 ierr = VecCopy(ts->vec_sol,th->X);CHKERRQ(ierr); 402 if (th->endpoint) alpha *= th->Theta; 403 ierr = VecWAXPY(X,alpha,th->Xdot,th->X);CHKERRQ(ierr); 404 PetscFunctionReturn(0); 405 } 406 407 /*------------------------------------------------------------*/ 408 #undef __FUNCT__ 409 #define __FUNCT__ "TSReset_Theta" 410 static PetscErrorCode TSReset_Theta(TS ts) 411 { 412 TS_Theta *th = (TS_Theta*)ts->data; 413 PetscErrorCode ierr; 414 415 PetscFunctionBegin; 416 ierr = VecDestroy(&th->X);CHKERRQ(ierr); 417 ierr = VecDestroy(&th->Xdot);CHKERRQ(ierr); 418 ierr = VecDestroy(&th->X0);CHKERRQ(ierr); 419 ierr = VecDestroy(&th->affine);CHKERRQ(ierr); 420 ierr = VecDestroyVecs(ts->numcost,&th->VecDeltaLam);CHKERRQ(ierr); 421 ierr = VecDestroyVecs(ts->numcost,&th->VecDeltaMu);CHKERRQ(ierr); 422 ierr = VecDestroyVecs(ts->numcost,&th->VecSensiTemp);CHKERRQ(ierr); 423 PetscFunctionReturn(0); 424 } 425 426 #undef __FUNCT__ 427 #define __FUNCT__ "TSDestroy_Theta" 428 static PetscErrorCode TSDestroy_Theta(TS ts) 429 { 430 PetscErrorCode ierr; 431 432 PetscFunctionBegin; 433 ierr = TSReset_Theta(ts);CHKERRQ(ierr); 434 ierr = PetscFree(ts->data);CHKERRQ(ierr); 435 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetTheta_C",NULL);CHKERRQ(ierr); 436 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetTheta_C",NULL);CHKERRQ(ierr); 437 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetEndpoint_C",NULL);CHKERRQ(ierr); 438 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetEndpoint_C",NULL);CHKERRQ(ierr); 439 PetscFunctionReturn(0); 440 } 441 442 /* 443 This defines the nonlinear equation that is to be solved with SNES 444 G(U) = F[t0+Theta*dt, U, (U-U0)*shift] = 0 445 */ 446 #undef __FUNCT__ 447 #define __FUNCT__ "SNESTSFormFunction_Theta" 448 static PetscErrorCode SNESTSFormFunction_Theta(SNES snes,Vec x,Vec y,TS ts) 449 { 450 TS_Theta *th = (TS_Theta*)ts->data; 451 PetscErrorCode ierr; 452 Vec X0,Xdot; 453 DM dm,dmsave; 454 PetscReal shift = 1./(th->Theta*ts->time_step); 455 456 PetscFunctionBegin; 457 ierr = SNESGetDM(snes,&dm);CHKERRQ(ierr); 458 /* When using the endpoint variant, this is actually 1/Theta * Xdot */ 459 ierr = TSThetaGetX0AndXdot(ts,dm,&X0,&Xdot);CHKERRQ(ierr); 460 ierr = VecAXPBYPCZ(Xdot,-shift,shift,0,X0,x);CHKERRQ(ierr); 461 462 /* DM monkey-business allows user code to call TSGetDM() inside of functions evaluated on levels of FAS */ 463 dmsave = ts->dm; 464 ts->dm = dm; 465 ierr = TSComputeIFunction(ts,th->stage_time,x,Xdot,y,PETSC_FALSE);CHKERRQ(ierr); 466 ts->dm = dmsave; 467 ierr = TSThetaRestoreX0AndXdot(ts,dm,&X0,&Xdot);CHKERRQ(ierr); 468 PetscFunctionReturn(0); 469 } 470 471 #undef __FUNCT__ 472 #define __FUNCT__ "SNESTSFormJacobian_Theta" 473 static PetscErrorCode SNESTSFormJacobian_Theta(SNES snes,Vec x,Mat A,Mat B,TS ts) 474 { 475 TS_Theta *th = (TS_Theta*)ts->data; 476 PetscErrorCode ierr; 477 Vec Xdot; 478 DM dm,dmsave; 479 PetscReal shift = 1./(th->Theta*ts->time_step); 480 481 PetscFunctionBegin; 482 ierr = SNESGetDM(snes,&dm);CHKERRQ(ierr); 483 484 /* th->Xdot has already been computed in SNESTSFormFunction_Theta (SNES guarantees this) */ 485 ierr = TSThetaGetX0AndXdot(ts,dm,NULL,&Xdot);CHKERRQ(ierr); 486 487 dmsave = ts->dm; 488 ts->dm = dm; 489 ierr = TSComputeIJacobian(ts,th->stage_time,x,Xdot,shift,A,B,PETSC_FALSE);CHKERRQ(ierr); 490 ts->dm = dmsave; 491 ierr = TSThetaRestoreX0AndXdot(ts,dm,NULL,&Xdot);CHKERRQ(ierr); 492 PetscFunctionReturn(0); 493 } 494 495 #undef __FUNCT__ 496 #define __FUNCT__ "TSSetUp_Theta" 497 static PetscErrorCode TSSetUp_Theta(TS ts) 498 { 499 TS_Theta *th = (TS_Theta*)ts->data; 500 PetscErrorCode ierr; 501 SNES snes; 502 TSAdapt adapt; 503 DM dm; 504 505 PetscFunctionBegin; 506 if (!th->X) { 507 ierr = VecDuplicate(ts->vec_sol,&th->X);CHKERRQ(ierr); 508 } 509 if (!th->Xdot) { 510 ierr = VecDuplicate(ts->vec_sol,&th->Xdot);CHKERRQ(ierr); 511 } 512 if (!th->X0) { 513 ierr = VecDuplicate(ts->vec_sol,&th->X0);CHKERRQ(ierr); 514 } 515 ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 516 ierr = TSGetDM(ts,&dm);CHKERRQ(ierr); 517 if (dm) { 518 ierr = DMCoarsenHookAdd(dm,DMCoarsenHook_TSTheta,DMRestrictHook_TSTheta,ts);CHKERRQ(ierr); 519 ierr = DMSubDomainHookAdd(dm,DMSubDomainHook_TSTheta,DMSubDomainRestrictHook_TSTheta,ts);CHKERRQ(ierr); 520 } 521 if (th->Theta == 0.5 && th->endpoint) th->order = 2; 522 else th->order = 1; 523 524 ierr = TSGetAdapt(ts,&adapt);CHKERRQ(ierr); 525 if (!th->adapt) { 526 ierr = TSAdaptSetType(adapt,TSADAPTNONE);CHKERRQ(ierr); 527 } 528 PetscFunctionReturn(0); 529 } 530 /*------------------------------------------------------------*/ 531 532 #undef __FUNCT__ 533 #define __FUNCT__ "TSAdjointSetUp_Theta" 534 static PetscErrorCode TSAdjointSetUp_Theta(TS ts) 535 { 536 TS_Theta *th = (TS_Theta*)ts->data; 537 PetscErrorCode ierr; 538 539 PetscFunctionBegin; 540 ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&th->VecDeltaLam);CHKERRQ(ierr); 541 if(ts->vecs_sensip) { 542 ierr = VecDuplicateVecs(ts->vecs_sensip[0],ts->numcost,&th->VecDeltaMu);CHKERRQ(ierr); 543 } 544 ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&th->VecSensiTemp);CHKERRQ(ierr); 545 PetscFunctionReturn(0); 546 } 547 /*------------------------------------------------------------*/ 548 549 #undef __FUNCT__ 550 #define __FUNCT__ "TSSetFromOptions_Theta" 551 static PetscErrorCode TSSetFromOptions_Theta(PetscOptions *PetscOptionsObject,TS ts) 552 { 553 TS_Theta *th = (TS_Theta*)ts->data; 554 PetscErrorCode ierr; 555 556 PetscFunctionBegin; 557 ierr = PetscOptionsHead(PetscOptionsObject,"Theta ODE solver options");CHKERRQ(ierr); 558 { 559 ierr = PetscOptionsReal("-ts_theta_theta","Location of stage (0<Theta<=1)","TSThetaSetTheta",th->Theta,&th->Theta,NULL);CHKERRQ(ierr); 560 ierr = PetscOptionsBool("-ts_theta_extrapolate","Extrapolate stage solution from previous solution (sometimes unstable)","TSThetaSetExtrapolate",th->extrapolate,&th->extrapolate,NULL);CHKERRQ(ierr); 561 ierr = PetscOptionsBool("-ts_theta_endpoint","Use the endpoint instead of midpoint form of the Theta method","TSThetaSetEndpoint",th->endpoint,&th->endpoint,NULL);CHKERRQ(ierr); 562 ierr = PetscOptionsBool("-ts_theta_adapt","Use time-step adaptivity with the Theta method","",th->adapt,&th->adapt,NULL);CHKERRQ(ierr); 563 ierr = SNESSetFromOptions(ts->snes);CHKERRQ(ierr); 564 } 565 ierr = PetscOptionsTail();CHKERRQ(ierr); 566 PetscFunctionReturn(0); 567 } 568 569 #undef __FUNCT__ 570 #define __FUNCT__ "TSView_Theta" 571 static PetscErrorCode TSView_Theta(TS ts,PetscViewer viewer) 572 { 573 TS_Theta *th = (TS_Theta*)ts->data; 574 PetscBool iascii; 575 PetscErrorCode ierr; 576 577 PetscFunctionBegin; 578 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 579 if (iascii) { 580 ierr = PetscViewerASCIIPrintf(viewer," Theta=%g\n",(double)th->Theta);CHKERRQ(ierr); 581 ierr = PetscViewerASCIIPrintf(viewer," Extrapolation=%s\n",th->extrapolate ? "yes" : "no");CHKERRQ(ierr); 582 } 583 if (ts->snes) {ierr = SNESView(ts->snes,viewer);CHKERRQ(ierr);} 584 PetscFunctionReturn(0); 585 } 586 587 #undef __FUNCT__ 588 #define __FUNCT__ "TSThetaGetTheta_Theta" 589 PetscErrorCode TSThetaGetTheta_Theta(TS ts,PetscReal *theta) 590 { 591 TS_Theta *th = (TS_Theta*)ts->data; 592 593 PetscFunctionBegin; 594 *theta = th->Theta; 595 PetscFunctionReturn(0); 596 } 597 598 #undef __FUNCT__ 599 #define __FUNCT__ "TSThetaSetTheta_Theta" 600 PetscErrorCode TSThetaSetTheta_Theta(TS ts,PetscReal theta) 601 { 602 TS_Theta *th = (TS_Theta*)ts->data; 603 604 PetscFunctionBegin; 605 if (theta <= 0 || 1 < theta) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Theta %g not in range (0,1]",(double)theta); 606 th->Theta = theta; 607 PetscFunctionReturn(0); 608 } 609 610 #undef __FUNCT__ 611 #define __FUNCT__ "TSThetaGetEndpoint_Theta" 612 PetscErrorCode TSThetaGetEndpoint_Theta(TS ts,PetscBool *endpoint) 613 { 614 TS_Theta *th = (TS_Theta*)ts->data; 615 616 PetscFunctionBegin; 617 *endpoint = th->endpoint; 618 PetscFunctionReturn(0); 619 } 620 621 #undef __FUNCT__ 622 #define __FUNCT__ "TSThetaSetEndpoint_Theta" 623 PetscErrorCode TSThetaSetEndpoint_Theta(TS ts,PetscBool flg) 624 { 625 TS_Theta *th = (TS_Theta*)ts->data; 626 627 PetscFunctionBegin; 628 th->endpoint = flg; 629 PetscFunctionReturn(0); 630 } 631 632 #if defined(PETSC_HAVE_COMPLEX) 633 #undef __FUNCT__ 634 #define __FUNCT__ "TSComputeLinearStability_Theta" 635 static PetscErrorCode TSComputeLinearStability_Theta(TS ts,PetscReal xr,PetscReal xi,PetscReal *yr,PetscReal *yi) 636 { 637 PetscComplex z = xr + xi*PETSC_i,f; 638 TS_Theta *th = (TS_Theta*)ts->data; 639 const PetscReal one = 1.0; 640 641 PetscFunctionBegin; 642 f = (one + (one - th->Theta)*z)/(one - th->Theta*z); 643 *yr = PetscRealPartComplex(f); 644 *yi = PetscImaginaryPartComplex(f); 645 PetscFunctionReturn(0); 646 } 647 #endif 648 649 #undef __FUNCT__ 650 #define __FUNCT__ "TSGetStages_Theta" 651 static PetscErrorCode TSGetStages_Theta(TS ts,PetscInt *ns,Vec **Y) 652 { 653 TS_Theta *th = (TS_Theta*)ts->data; 654 655 PetscFunctionBegin; 656 *ns = 1; 657 if(Y) { 658 *Y = &(th->X); 659 } 660 PetscFunctionReturn(0); 661 } 662 663 /* ------------------------------------------------------------ */ 664 /*MC 665 TSTHETA - DAE solver using the implicit Theta method 666 667 Level: beginner 668 669 Options Database: 670 -ts_theta_theta <Theta> - Location of stage (0<Theta<=1) 671 -ts_theta_extrapolate <flg> Extrapolate stage solution from previous solution (sometimes unstable) 672 -ts_theta_endpoint <flag> - Use the endpoint (like Crank-Nicholson) instead of midpoint form of the Theta method 673 674 Notes: 675 $ -ts_type theta -ts_theta_theta 1.0 corresponds to backward Euler (TSBEULER) 676 $ -ts_type theta -ts_theta_theta 0.5 corresponds to the implicit midpoint rule 677 $ -ts_type theta -ts_theta_theta 0.5 -ts_theta_endpoint corresponds to Crank-Nicholson (TSCN) 678 679 680 681 This method can be applied to DAE. 682 683 This method is cast as a 1-stage implicit Runge-Kutta method. 684 685 .vb 686 Theta | Theta 687 ------------- 688 | 1 689 .ve 690 691 For the default Theta=0.5, this is also known as the implicit midpoint rule. 692 693 When the endpoint variant is chosen, the method becomes a 2-stage method with first stage explicit: 694 695 .vb 696 0 | 0 0 697 1 | 1-Theta Theta 698 ------------------- 699 | 1-Theta Theta 700 .ve 701 702 For the default Theta=0.5, this is the trapezoid rule (also known as Crank-Nicolson, see TSCN). 703 704 To apply a diagonally implicit RK method to DAE, the stage formula 705 706 $ Y_i = X + h sum_j a_ij Y'_j 707 708 is interpreted as a formula for Y'_i in terms of Y_i and known values (Y'_j, j<i) 709 710 .seealso: TSCreate(), TS, TSSetType(), TSCN, TSBEULER, TSThetaSetTheta(), TSThetaSetEndpoint() 711 712 M*/ 713 #undef __FUNCT__ 714 #define __FUNCT__ "TSCreate_Theta" 715 PETSC_EXTERN PetscErrorCode TSCreate_Theta(TS ts) 716 { 717 TS_Theta *th; 718 PetscErrorCode ierr; 719 720 PetscFunctionBegin; 721 ts->ops->reset = TSReset_Theta; 722 ts->ops->destroy = TSDestroy_Theta; 723 ts->ops->view = TSView_Theta; 724 ts->ops->setup = TSSetUp_Theta; 725 ts->ops->adjointsetup = TSAdjointSetUp_Theta; 726 ts->ops->step = TSStep_Theta; 727 ts->ops->interpolate = TSInterpolate_Theta; 728 ts->ops->evaluatestep = TSEvaluateStep_Theta; 729 ts->ops->rollback = TSRollBack_Theta; 730 ts->ops->setfromoptions = TSSetFromOptions_Theta; 731 ts->ops->snesfunction = SNESTSFormFunction_Theta; 732 ts->ops->snesjacobian = SNESTSFormJacobian_Theta; 733 #if defined(PETSC_HAVE_COMPLEX) 734 ts->ops->linearstability = TSComputeLinearStability_Theta; 735 #endif 736 ts->ops->getstages = TSGetStages_Theta; 737 ts->ops->adjointstep = TSAdjointStep_Theta; 738 739 ierr = PetscNewLog(ts,&th);CHKERRQ(ierr); 740 ts->data = (void*)th; 741 742 th->extrapolate = PETSC_FALSE; 743 th->Theta = 0.5; 744 th->ccfl = 1.0; 745 th->adapt = PETSC_FALSE; 746 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetTheta_C",TSThetaGetTheta_Theta);CHKERRQ(ierr); 747 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetTheta_C",TSThetaSetTheta_Theta);CHKERRQ(ierr); 748 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetEndpoint_C",TSThetaGetEndpoint_Theta);CHKERRQ(ierr); 749 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetEndpoint_C",TSThetaSetEndpoint_Theta);CHKERRQ(ierr); 750 PetscFunctionReturn(0); 751 } 752 753 #undef __FUNCT__ 754 #define __FUNCT__ "TSThetaGetTheta" 755 /*@ 756 TSThetaGetTheta - Get the abscissa of the stage in (0,1]. 757 758 Not Collective 759 760 Input Parameter: 761 . ts - timestepping context 762 763 Output Parameter: 764 . theta - stage abscissa 765 766 Note: 767 Use of this function is normally only required to hack TSTHETA to use a modified integration scheme. 768 769 Level: Advanced 770 771 .seealso: TSThetaSetTheta() 772 @*/ 773 PetscErrorCode TSThetaGetTheta(TS ts,PetscReal *theta) 774 { 775 PetscErrorCode ierr; 776 777 PetscFunctionBegin; 778 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 779 PetscValidPointer(theta,2); 780 ierr = PetscUseMethod(ts,"TSThetaGetTheta_C",(TS,PetscReal*),(ts,theta));CHKERRQ(ierr); 781 PetscFunctionReturn(0); 782 } 783 784 #undef __FUNCT__ 785 #define __FUNCT__ "TSThetaSetTheta" 786 /*@ 787 TSThetaSetTheta - Set the abscissa of the stage in (0,1]. 788 789 Not Collective 790 791 Input Parameter: 792 + ts - timestepping context 793 - theta - stage abscissa 794 795 Options Database: 796 . -ts_theta_theta <theta> 797 798 Level: Intermediate 799 800 .seealso: TSThetaGetTheta() 801 @*/ 802 PetscErrorCode TSThetaSetTheta(TS ts,PetscReal theta) 803 { 804 PetscErrorCode ierr; 805 806 PetscFunctionBegin; 807 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 808 ierr = PetscTryMethod(ts,"TSThetaSetTheta_C",(TS,PetscReal),(ts,theta));CHKERRQ(ierr); 809 PetscFunctionReturn(0); 810 } 811 812 #undef __FUNCT__ 813 #define __FUNCT__ "TSThetaGetEndpoint" 814 /*@ 815 TSThetaGetEndpoint - Gets whether to use the endpoint variant of the method (e.g. trapezoid/Crank-Nicolson instead of midpoint rule). 816 817 Not Collective 818 819 Input Parameter: 820 . ts - timestepping context 821 822 Output Parameter: 823 . endpoint - PETSC_TRUE when using the endpoint variant 824 825 Level: Advanced 826 827 .seealso: TSThetaSetEndpoint(), TSTHETA, TSCN 828 @*/ 829 PetscErrorCode TSThetaGetEndpoint(TS ts,PetscBool *endpoint) 830 { 831 PetscErrorCode ierr; 832 833 PetscFunctionBegin; 834 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 835 PetscValidPointer(endpoint,2); 836 ierr = PetscTryMethod(ts,"TSThetaGetEndpoint_C",(TS,PetscBool*),(ts,endpoint));CHKERRQ(ierr); 837 PetscFunctionReturn(0); 838 } 839 840 #undef __FUNCT__ 841 #define __FUNCT__ "TSThetaSetEndpoint" 842 /*@ 843 TSThetaSetEndpoint - Sets whether to use the endpoint variant of the method (e.g. trapezoid/Crank-Nicolson instead of midpoint rule). 844 845 Not Collective 846 847 Input Parameter: 848 + ts - timestepping context 849 - flg - PETSC_TRUE to use the endpoint variant 850 851 Options Database: 852 . -ts_theta_endpoint <flg> 853 854 Level: Intermediate 855 856 .seealso: TSTHETA, TSCN 857 @*/ 858 PetscErrorCode TSThetaSetEndpoint(TS ts,PetscBool flg) 859 { 860 PetscErrorCode ierr; 861 862 PetscFunctionBegin; 863 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 864 ierr = PetscTryMethod(ts,"TSThetaSetEndpoint_C",(TS,PetscBool),(ts,flg));CHKERRQ(ierr); 865 PetscFunctionReturn(0); 866 } 867 868 /* 869 * TSBEULER and TSCN are straightforward specializations of TSTHETA. 870 * The creation functions for these specializations are below. 871 */ 872 873 #undef __FUNCT__ 874 #define __FUNCT__ "TSView_BEuler" 875 static PetscErrorCode TSView_BEuler(TS ts,PetscViewer viewer) 876 { 877 PetscErrorCode ierr; 878 879 PetscFunctionBegin; 880 ierr = SNESView(ts->snes,viewer);CHKERRQ(ierr); 881 PetscFunctionReturn(0); 882 } 883 884 /*MC 885 TSBEULER - ODE solver using the implicit backward Euler method 886 887 Level: beginner 888 889 Notes: 890 TSBEULER is equivalent to TSTHETA with Theta=1.0 891 892 $ -ts_type theta -ts_theta_theta 1. 893 894 .seealso: TSCreate(), TS, TSSetType(), TSEULER, TSCN, TSTHETA 895 896 M*/ 897 #undef __FUNCT__ 898 #define __FUNCT__ "TSCreate_BEuler" 899 PETSC_EXTERN PetscErrorCode TSCreate_BEuler(TS ts) 900 { 901 PetscErrorCode ierr; 902 903 PetscFunctionBegin; 904 ierr = TSCreate_Theta(ts);CHKERRQ(ierr); 905 ierr = TSThetaSetTheta(ts,1.0);CHKERRQ(ierr); 906 ts->ops->view = TSView_BEuler; 907 PetscFunctionReturn(0); 908 } 909 910 #undef __FUNCT__ 911 #define __FUNCT__ "TSView_CN" 912 static PetscErrorCode TSView_CN(TS ts,PetscViewer viewer) 913 { 914 PetscErrorCode ierr; 915 916 PetscFunctionBegin; 917 ierr = SNESView(ts->snes,viewer);CHKERRQ(ierr); 918 PetscFunctionReturn(0); 919 } 920 921 /*MC 922 TSCN - ODE solver using the implicit Crank-Nicolson method. 923 924 Level: beginner 925 926 Notes: 927 TSCN is equivalent to TSTHETA with Theta=0.5 and the "endpoint" option set. I.e. 928 929 $ -ts_type theta -ts_theta_theta 0.5 -ts_theta_endpoint 930 931 .seealso: TSCreate(), TS, TSSetType(), TSBEULER, TSTHETA 932 933 M*/ 934 #undef __FUNCT__ 935 #define __FUNCT__ "TSCreate_CN" 936 PETSC_EXTERN PetscErrorCode TSCreate_CN(TS ts) 937 { 938 PetscErrorCode ierr; 939 940 PetscFunctionBegin; 941 ierr = TSCreate_Theta(ts);CHKERRQ(ierr); 942 ierr = TSThetaSetTheta(ts,0.5);CHKERRQ(ierr); 943 ierr = TSThetaSetEndpoint(ts,PETSC_TRUE);CHKERRQ(ierr); 944 ts->ops->view = TSView_CN; 945 PetscFunctionReturn(0); 946 } 947