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 /* context for time stepping */ 11 PetscReal stage_time; 12 Vec X0,X,Xdot; /* Storage for stages and time derivative */ 13 Vec affine; /* Affine vector needed for residual at beginning of step in endpoint formulation */ 14 PetscReal Theta; 15 PetscReal ptime; 16 PetscReal time_step; 17 PetscInt order; 18 PetscBool endpoint; 19 PetscBool extrapolate; 20 TSStepStatus status; 21 Vec VecCostIntegral0; /* Backup for roll-backs due to events */ 22 23 /* context for sensitivity analysis */ 24 PetscInt num_tlm; /* Total number of tangent linear equations */ 25 Vec *VecsDeltaLam; /* Increment of the adjoint sensitivity w.r.t IC at stage */ 26 Vec *VecsDeltaMu; /* Increment of the adjoint sensitivity w.r.t P at stage */ 27 Vec *VecsSensiTemp; /* Vector to be multiplied with Jacobian transpose */ 28 Mat MatDeltaFwdSensip; /* Increment of the forward sensitivity at stage */ 29 Vec VecDeltaFwdSensipCol; /* Working vector for holding one column of the sensitivity matrix */ 30 Mat MatFwdSensip0; /* backup for roll-backs due to events */ 31 Vec VecIntegralSensipTemp; /* Working vector for forward integral sensitivity */ 32 Vec *VecsIntegralSensip0; /* backup for roll-backs due to events */ 33 Vec *VecsDeltaLam2; /* Increment of the 2nd-order adjoint sensitivity w.r.t IC at stage */ 34 Vec *VecsDeltaMu2; /* Increment of the 2nd-order adjoint sensitivity w.r.t P at stage */ 35 Vec *VecsSensi2Temp; /* Working vectors that holds the residual for the second-order adjoint */ 36 Vec *VecsAffine; /* Working vectors to store residuals */ 37 /* context for error estimation */ 38 Vec vec_sol_prev; 39 Vec vec_lte_work; 40 } TS_Theta; 41 42 static PetscErrorCode TSThetaGetX0AndXdot(TS ts,DM dm,Vec *X0,Vec *Xdot) 43 { 44 TS_Theta *th = (TS_Theta*)ts->data; 45 PetscErrorCode ierr; 46 47 PetscFunctionBegin; 48 if (X0) { 49 if (dm && dm != ts->dm) { 50 ierr = DMGetNamedGlobalVector(dm,"TSTheta_X0",X0);CHKERRQ(ierr); 51 } else *X0 = ts->vec_sol; 52 } 53 if (Xdot) { 54 if (dm && dm != ts->dm) { 55 ierr = DMGetNamedGlobalVector(dm,"TSTheta_Xdot",Xdot);CHKERRQ(ierr); 56 } else *Xdot = th->Xdot; 57 } 58 PetscFunctionReturn(0); 59 } 60 61 static PetscErrorCode TSThetaRestoreX0AndXdot(TS ts,DM dm,Vec *X0,Vec *Xdot) 62 { 63 PetscErrorCode ierr; 64 65 PetscFunctionBegin; 66 if (X0) { 67 if (dm && dm != ts->dm) { 68 ierr = DMRestoreNamedGlobalVector(dm,"TSTheta_X0",X0);CHKERRQ(ierr); 69 } 70 } 71 if (Xdot) { 72 if (dm && dm != ts->dm) { 73 ierr = DMRestoreNamedGlobalVector(dm,"TSTheta_Xdot",Xdot);CHKERRQ(ierr); 74 } 75 } 76 PetscFunctionReturn(0); 77 } 78 79 static PetscErrorCode DMCoarsenHook_TSTheta(DM fine,DM coarse,void *ctx) 80 { 81 PetscFunctionBegin; 82 PetscFunctionReturn(0); 83 } 84 85 static PetscErrorCode DMRestrictHook_TSTheta(DM fine,Mat restrct,Vec rscale,Mat inject,DM coarse,void *ctx) 86 { 87 TS ts = (TS)ctx; 88 PetscErrorCode ierr; 89 Vec X0,Xdot,X0_c,Xdot_c; 90 91 PetscFunctionBegin; 92 ierr = TSThetaGetX0AndXdot(ts,fine,&X0,&Xdot);CHKERRQ(ierr); 93 ierr = TSThetaGetX0AndXdot(ts,coarse,&X0_c,&Xdot_c);CHKERRQ(ierr); 94 ierr = MatRestrict(restrct,X0,X0_c);CHKERRQ(ierr); 95 ierr = MatRestrict(restrct,Xdot,Xdot_c);CHKERRQ(ierr); 96 ierr = VecPointwiseMult(X0_c,rscale,X0_c);CHKERRQ(ierr); 97 ierr = VecPointwiseMult(Xdot_c,rscale,Xdot_c);CHKERRQ(ierr); 98 ierr = TSThetaRestoreX0AndXdot(ts,fine,&X0,&Xdot);CHKERRQ(ierr); 99 ierr = TSThetaRestoreX0AndXdot(ts,coarse,&X0_c,&Xdot_c);CHKERRQ(ierr); 100 PetscFunctionReturn(0); 101 } 102 103 static PetscErrorCode DMSubDomainHook_TSTheta(DM dm,DM subdm,void *ctx) 104 { 105 PetscFunctionBegin; 106 PetscFunctionReturn(0); 107 } 108 109 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 static PetscErrorCode TSThetaEvaluateCostIntegral(TS ts) 131 { 132 TS_Theta *th = (TS_Theta*)ts->data; 133 PetscErrorCode ierr; 134 135 PetscFunctionBegin; 136 if (th->endpoint) { 137 /* Evolve ts->vec_costintegral to compute integrals */ 138 if (th->Theta!=1.0) { 139 ierr = TSComputeCostIntegrand(ts,th->ptime,th->X0,ts->vec_costintegrand);CHKERRQ(ierr); 140 ierr = VecAXPY(ts->vec_costintegral,th->time_step*(1.0-th->Theta),ts->vec_costintegrand);CHKERRQ(ierr); 141 } 142 ierr = TSComputeCostIntegrand(ts,ts->ptime,ts->vec_sol,ts->vec_costintegrand);CHKERRQ(ierr); 143 ierr = VecAXPY(ts->vec_costintegral,th->time_step*th->Theta,ts->vec_costintegrand);CHKERRQ(ierr); 144 } else { 145 ierr = TSComputeCostIntegrand(ts,th->stage_time,th->X,ts->vec_costintegrand);CHKERRQ(ierr); 146 ierr = VecAXPY(ts->vec_costintegral,th->time_step,ts->vec_costintegrand);CHKERRQ(ierr); 147 } 148 PetscFunctionReturn(0); 149 } 150 151 static PetscErrorCode TSForwardCostIntegral_Theta(TS ts) 152 { 153 TS_Theta *th = (TS_Theta*)ts->data; 154 PetscErrorCode ierr; 155 156 PetscFunctionBegin; 157 /* backup cost integral */ 158 ierr = VecCopy(ts->vec_costintegral,th->VecCostIntegral0);CHKERRQ(ierr); 159 ierr = TSThetaEvaluateCostIntegral(ts);CHKERRQ(ierr); 160 PetscFunctionReturn(0); 161 } 162 163 static PetscErrorCode TSAdjointCostIntegral_Theta(TS ts) 164 { 165 PetscErrorCode ierr; 166 167 PetscFunctionBegin; 168 ierr = TSThetaEvaluateCostIntegral(ts);CHKERRQ(ierr); 169 PetscFunctionReturn(0); 170 } 171 172 static PetscErrorCode TSTheta_SNESSolve(TS ts,Vec b,Vec x) 173 { 174 PetscInt nits,lits; 175 PetscErrorCode ierr; 176 177 PetscFunctionBegin; 178 ierr = SNESSolve(ts->snes,b,x);CHKERRQ(ierr); 179 ierr = SNESGetIterationNumber(ts->snes,&nits);CHKERRQ(ierr); 180 ierr = SNESGetLinearSolveIterations(ts->snes,&lits);CHKERRQ(ierr); 181 ts->snes_its += nits; ts->ksp_its += lits; 182 PetscFunctionReturn(0); 183 } 184 185 static PetscErrorCode TSStep_Theta(TS ts) 186 { 187 TS_Theta *th = (TS_Theta*)ts->data; 188 PetscInt rejections = 0; 189 PetscBool stageok,accept = PETSC_TRUE; 190 PetscReal next_time_step = ts->time_step; 191 PetscErrorCode ierr; 192 193 PetscFunctionBegin; 194 if (!ts->steprollback) { 195 if (th->vec_sol_prev) { ierr = VecCopy(th->X0,th->vec_sol_prev);CHKERRQ(ierr); } 196 ierr = VecCopy(ts->vec_sol,th->X0);CHKERRQ(ierr); 197 } 198 199 th->status = TS_STEP_INCOMPLETE; 200 while (!ts->reason && th->status != TS_STEP_COMPLETE) { 201 202 PetscReal shift = 1/(th->Theta*ts->time_step); 203 th->stage_time = ts->ptime + (th->endpoint ? (PetscReal)1 : th->Theta)*ts->time_step; 204 205 ierr = VecCopy(th->X0,th->X);CHKERRQ(ierr); 206 if (th->extrapolate && !ts->steprestart) { 207 ierr = VecAXPY(th->X,1/shift,th->Xdot);CHKERRQ(ierr); 208 } 209 if (th->endpoint) { /* This formulation assumes linear time-independent mass matrix */ 210 if (!th->affine) {ierr = VecDuplicate(ts->vec_sol,&th->affine);CHKERRQ(ierr);} 211 ierr = VecZeroEntries(th->Xdot);CHKERRQ(ierr); 212 ierr = TSComputeIFunction(ts,ts->ptime,th->X0,th->Xdot,th->affine,PETSC_FALSE);CHKERRQ(ierr); 213 ierr = VecScale(th->affine,(th->Theta-1)/th->Theta);CHKERRQ(ierr); 214 } else if (th->affine) { /* Just in case th->endpoint is changed between calls to TSStep_Theta() */ 215 ierr = VecZeroEntries(th->affine);CHKERRQ(ierr); 216 } 217 ierr = TSPreStage(ts,th->stage_time);CHKERRQ(ierr); 218 ierr = TSTheta_SNESSolve(ts,th->affine,th->X);CHKERRQ(ierr); 219 ierr = TSPostStage(ts,th->stage_time,0,&th->X);CHKERRQ(ierr); 220 ierr = TSAdaptCheckStage(ts->adapt,ts,th->stage_time,th->X,&stageok);CHKERRQ(ierr); 221 if (!stageok) goto reject_step; 222 223 th->status = TS_STEP_PENDING; 224 if (th->endpoint) { 225 ierr = VecCopy(th->X,ts->vec_sol);CHKERRQ(ierr); 226 } else { 227 ierr = VecAXPBYPCZ(th->Xdot,-shift,shift,0,th->X0,th->X);CHKERRQ(ierr); 228 ierr = VecAXPY(ts->vec_sol,ts->time_step,th->Xdot);CHKERRQ(ierr); 229 } 230 ierr = TSAdaptChoose(ts->adapt,ts,ts->time_step,NULL,&next_time_step,&accept);CHKERRQ(ierr); 231 th->status = accept ? TS_STEP_COMPLETE : TS_STEP_INCOMPLETE; 232 if (!accept) { 233 ierr = VecCopy(th->X0,ts->vec_sol);CHKERRQ(ierr); 234 ts->time_step = next_time_step; 235 goto reject_step; 236 } 237 238 if (ts->forward_solve || ts->costintegralfwd) { /* Save the info for the later use in cost integral evaluation */ 239 th->ptime = ts->ptime; 240 th->time_step = ts->time_step; 241 } 242 243 ts->ptime += ts->time_step; 244 ts->time_step = next_time_step; 245 break; 246 247 reject_step: 248 ts->reject++; accept = PETSC_FALSE; 249 if (!ts->reason && ++rejections > ts->max_reject && ts->max_reject >= 0) { 250 ts->reason = TS_DIVERGED_STEP_REJECTED; 251 ierr = PetscInfo2(ts,"Step=%D, step rejections %D greater than current TS allowed, stopping solve\n",ts->steps,rejections);CHKERRQ(ierr); 252 } 253 } 254 PetscFunctionReturn(0); 255 } 256 257 static PetscErrorCode TSAdjointStepBEuler_Private(TS ts) 258 { 259 TS_Theta *th = (TS_Theta*)ts->data; 260 Vec *VecsDeltaLam = th->VecsDeltaLam,*VecsDeltaMu = th->VecsDeltaMu,*VecsSensiTemp = th->VecsSensiTemp; 261 Vec *VecsDeltaLam2 = th->VecsDeltaLam2,*VecsDeltaMu2 = th->VecsDeltaMu2,*VecsSensi2Temp = th->VecsSensi2Temp; 262 PetscInt nadj; 263 Mat J,Jp; 264 KSP ksp; 265 PetscReal shift; 266 PetscScalar *xarr; 267 PetscErrorCode ierr; 268 269 PetscFunctionBegin; 270 th->status = TS_STEP_INCOMPLETE; 271 ierr = SNESGetKSP(ts->snes,&ksp);CHKERRQ(ierr); 272 ierr = TSGetIJacobian(ts,&J,&Jp,NULL,NULL);CHKERRQ(ierr); 273 274 /* If endpoint=1, th->ptime and th->X0 will be used; if endpoint=0, th->stage_time and th->X will be used. */ 275 th->stage_time = ts->ptime; /* time_step is negative*/ 276 th->ptime = ts->ptime + ts->time_step; 277 th->time_step = -ts->time_step; 278 279 /* Build RHS for first-order adjoint */ 280 if (ts->vec_costintegral) { /* Cost function has an integral term */ 281 ierr = TSComputeDRDUFunction(ts,th->stage_time,th->X,ts->vecs_drdu);CHKERRQ(ierr); 282 } 283 for (nadj=0; nadj<ts->numcost; nadj++) { 284 ierr = VecCopy(ts->vecs_sensi[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr); 285 ierr = VecScale(VecsSensiTemp[nadj],1./th->time_step);CHKERRQ(ierr); /* lambda_{n+1}/h */ 286 if (ts->vec_costintegral) { 287 ierr = VecAXPY(VecsSensiTemp[nadj],1.,ts->vecs_drdu[nadj]);CHKERRQ(ierr); 288 } 289 } 290 291 /* Build LHS for first-order adjoint */ 292 shift = 1./th->time_step; 293 ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,shift,J,Jp,PETSC_FALSE);CHKERRQ(ierr); 294 ierr = KSPSetOperators(ksp,J,Jp);CHKERRQ(ierr); 295 296 /* Solve stage equation LHS*lambda_s = RHS for first-order adjoint */ 297 for (nadj=0; nadj<ts->numcost; nadj++) { 298 KSPConvergedReason kspreason; 299 ierr = KSPSolveTranspose(ksp,VecsSensiTemp[nadj],VecsDeltaLam[nadj]);CHKERRQ(ierr); 300 ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); 301 if (kspreason < 0) { 302 ts->reason = TSADJOINT_DIVERGED_LINEAR_SOLVE; 303 ierr = PetscInfo2(ts,"Step=%D, %Dth cost function, transposed linear solve fails, stopping adjoint solve\n",ts->steps,nadj);CHKERRQ(ierr); 304 } 305 } 306 307 if (ts->vecs_sensi2) { /* U_{n+1} */ 308 /* Get w1 at t_{n+1} from TLM matrix */ 309 ierr = MatDenseGetColumn(ts->mat_sensip,0,&xarr);CHKERRQ(ierr); 310 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 311 /* lambda_s^T F_UU w_1 */ 312 ierr = TSComputeIHessianProductFunction1(ts,th->stage_time,th->X,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fuu);CHKERRQ(ierr); 313 if (ts->vecs_fup) { 314 /* lambda_s^T F_UP w_2 */ 315 ierr = TSComputeIHessianProductFunction2(ts,th->stage_time,th->X,VecsDeltaLam,ts->vec_dir,ts->vecs_fup);CHKERRQ(ierr); 316 } 317 for (nadj=0; nadj<ts->numcost; nadj++) { /* compute the residual */ 318 ierr = VecCopy(ts->vecs_sensi2[nadj],VecsSensi2Temp[nadj]);CHKERRQ(ierr); 319 ierr = VecScale(VecsSensi2Temp[nadj],shift);CHKERRQ(ierr); 320 ierr = VecAXPY(VecsSensi2Temp[nadj],1.,ts->vecs_fuu[nadj]);CHKERRQ(ierr); 321 if (ts->vecs_fup) { 322 ierr = VecAXPY(VecsSensi2Temp[nadj],1.,ts->vecs_fup[nadj]);CHKERRQ(ierr); 323 } 324 } 325 /* Solve stage equation LHS X = RHS for second-order adjoint */ 326 for (nadj=0; nadj<ts->numcost; nadj++) { 327 KSPConvergedReason kspreason; 328 ierr = KSPSolveTranspose(ksp,VecsSensi2Temp[nadj],VecsDeltaLam2[nadj]);CHKERRQ(ierr); 329 ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); 330 if (kspreason < 0) { 331 ts->reason = TSADJOINT_DIVERGED_LINEAR_SOLVE; 332 ierr = PetscInfo2(ts,"Step=%D, %Dth cost function, transposed linear solve fails, stopping adjoint solve\n",ts->steps,nadj);CHKERRQ(ierr); 333 } 334 } 335 } 336 337 /* Update sensitivities, and evaluate integrals if there is any */ 338 shift = 0.0; 339 ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,shift,J,Jp,PETSC_FALSE);CHKERRQ(ierr); /* get -f_y */ 340 ierr = MatScale(J,-1.);CHKERRQ(ierr); 341 for (nadj=0; nadj<ts->numcost; nadj++) { 342 ierr = MatMultTransposeAdd(J,VecsDeltaLam[nadj],VecsSensiTemp[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr); 343 ierr = VecScale(VecsSensiTemp[nadj],th->time_step);CHKERRQ(ierr); 344 ierr = VecCopy(VecsSensiTemp[nadj],ts->vecs_sensi[nadj]);CHKERRQ(ierr); 345 if (ts->vecs_sensi2) { 346 ierr = MatMultTransposeAdd(J,VecsDeltaLam2[nadj],VecsSensi2Temp[nadj],VecsSensi2Temp[nadj]);CHKERRQ(ierr); 347 ierr = VecScale(VecsSensi2Temp[nadj],th->time_step);CHKERRQ(ierr); 348 ierr = VecCopy(VecsSensi2Temp[nadj],ts->vecs_sensi2[nadj]);CHKERRQ(ierr); 349 } 350 } 351 if (ts->vecs_sensip) { 352 ierr = TSComputeIJacobianP(ts,th->stage_time,th->X,th->Xdot,shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); /* get -f_p */ 353 if (ts->vecs_sensi2p) { 354 if (ts->vecs_fpu) { 355 /* lambda_s^T F_PU w_1 */ 356 ierr = TSComputeIHessianProductFunction3(ts,th->stage_time,th->X,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fpu);CHKERRQ(ierr); 357 } 358 if (ts->vecs_fpp) { 359 /* lambda_s^T F_PU w_2 */ 360 ierr = TSComputeIHessianProductFunction4(ts,th->stage_time,th->X,VecsDeltaLam,ts->vec_dir,ts->vecs_fpp);CHKERRQ(ierr); 361 } 362 } 363 for (nadj=0; nadj<ts->numcost; nadj++) { 364 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr); 365 ierr = VecAXPY(ts->vecs_sensip[nadj],-th->time_step,VecsDeltaMu[nadj]);CHKERRQ(ierr); 366 if (ts->vecs_sensi2p) { 367 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam2[nadj],VecsDeltaMu2[nadj]);CHKERRQ(ierr); 368 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step,VecsDeltaMu2[nadj]);CHKERRQ(ierr); 369 if (ts->vecs_fpu) { 370 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step,ts->vecs_fpu[nadj]);CHKERRQ(ierr); 371 } 372 if (ts->vecs_fpp) { 373 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step,ts->vecs_fpp[nadj]);CHKERRQ(ierr); 374 } 375 } 376 } 377 if (ts->vec_costintegral) { 378 ierr = TSComputeDRDPFunction(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],th->time_step,ts->vecs_drdp[nadj]);CHKERRQ(ierr); 381 } 382 } 383 } 384 385 if (ts->vecs_sensi2) { 386 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 387 ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr); 388 } 389 th->status = TS_STEP_COMPLETE; 390 PetscFunctionReturn(0); 391 } 392 393 static PetscErrorCode TSAdjointStep_Theta(TS ts) 394 { 395 TS_Theta *th = (TS_Theta*)ts->data; 396 Vec *VecsDeltaLam = th->VecsDeltaLam,*VecsDeltaMu = th->VecsDeltaMu,*VecsSensiTemp = th->VecsSensiTemp; 397 Vec *VecsDeltaLam2 = th->VecsDeltaLam2,*VecsDeltaMu2 = th->VecsDeltaMu2,*VecsSensi2Temp = th->VecsSensi2Temp; 398 PetscInt nadj; 399 Mat J,Jp; 400 KSP ksp; 401 PetscReal shift; 402 PetscScalar *xarr; 403 PetscErrorCode ierr; 404 405 PetscFunctionBegin; 406 if (th->Theta == 1.) { 407 ierr = TSAdjointStepBEuler_Private(ts);CHKERRQ(ierr); 408 PetscFunctionReturn(0); 409 } 410 th->status = TS_STEP_INCOMPLETE; 411 ierr = SNESGetKSP(ts->snes,&ksp);CHKERRQ(ierr); 412 ierr = TSGetIJacobian(ts,&J,&Jp,NULL,NULL);CHKERRQ(ierr); 413 414 /* If endpoint=1, th->ptime and th->X0 will be used; if endpoint=0, th->stage_time and th->X will be used. */ 415 th->stage_time = th->endpoint ? ts->ptime : (ts->ptime+(1.-th->Theta)*ts->time_step); /* time_step is negative*/ 416 th->ptime = ts->ptime + ts->time_step; 417 th->time_step = -ts->time_step; 418 419 /* Build RHS for first-order adjoint */ 420 if (ts->vec_costintegral) { /* Cost function has an integral term */ 421 if (th->endpoint) { 422 ierr = TSComputeDRDUFunction(ts,th->stage_time,ts->vec_sol,ts->vecs_drdu);CHKERRQ(ierr); 423 } else { 424 ierr = TSComputeDRDUFunction(ts,th->stage_time,th->X,ts->vecs_drdu);CHKERRQ(ierr); 425 } 426 } 427 for (nadj=0; nadj<ts->numcost; nadj++) { 428 ierr = VecCopy(ts->vecs_sensi[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr); 429 ierr = VecScale(VecsSensiTemp[nadj],1./(th->Theta*th->time_step));CHKERRQ(ierr); 430 if (ts->vec_costintegral) { 431 ierr = VecAXPY(VecsSensiTemp[nadj],1.,ts->vecs_drdu[nadj]);CHKERRQ(ierr); 432 } 433 } 434 435 /* Build LHS for first-order adjoint */ 436 shift = 1./(th->Theta*th->time_step); 437 if (th->endpoint) { 438 ierr = TSComputeIJacobian(ts,th->stage_time,ts->vec_sol,th->Xdot,shift,J,Jp,PETSC_FALSE);CHKERRQ(ierr); 439 } else { 440 ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,shift,J,Jp,PETSC_FALSE);CHKERRQ(ierr); 441 } 442 ierr = KSPSetOperators(ksp,J,Jp);CHKERRQ(ierr); 443 444 /* Solve stage equation LHS*lambda_s = RHS for first-order adjoint */ 445 for (nadj=0; nadj<ts->numcost; nadj++) { 446 ierr = KSPSolveTranspose(ksp,VecsSensiTemp[nadj],VecsDeltaLam[nadj]);CHKERRQ(ierr); 447 } 448 449 if (ts->vecs_sensi2) { /* U_{n+1} */ 450 if (!th->endpoint) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Operation not implemented in TS_Theta"); 451 /* Get w1 at t_{n+1} from TLM matrix */ 452 ierr = MatDenseGetColumn(ts->mat_sensip,0,&xarr);CHKERRQ(ierr); 453 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 454 /* lambda_s^T F_UU w_1 */ 455 ierr = TSComputeIHessianProductFunction1(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fuu);CHKERRQ(ierr); 456 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 457 ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr); 458 if (ts->vecs_fup) { 459 /* lambda_s^T F_UP w_2 */ 460 ierr = TSComputeIHessianProductFunction2(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_dir,ts->vecs_fup);CHKERRQ(ierr); 461 } 462 for (nadj=0; nadj<ts->numcost; nadj++) { /* compute the residual */ 463 ierr = VecCopy(ts->vecs_sensi2[nadj],VecsSensi2Temp[nadj]);CHKERRQ(ierr); 464 ierr = VecScale(VecsSensi2Temp[nadj],1./shift);CHKERRQ(ierr); 465 ierr = VecAXPY(VecsSensi2Temp[nadj],1.,ts->vecs_fuu[nadj]);CHKERRQ(ierr); 466 ierr = VecAXPY(VecsSensi2Temp[nadj],1.,ts->vecs_fuu[nadj]);CHKERRQ(ierr); 467 if (ts->vecs_fup) { 468 ierr = VecAXPY(VecsSensi2Temp[nadj],1.,ts->vecs_fup[nadj]);CHKERRQ(ierr); 469 } 470 if (ts->vec_costintegral) { 471 ierr = VecAXPY(VecsSensi2Temp[nadj],1.,ts->vecs_drdu[nadj]);CHKERRQ(ierr); 472 } 473 } 474 /* Solve stage equation LHS X = RHS for second-order adjoint */ 475 for (nadj=0; nadj<ts->numcost; nadj++) { 476 ierr = KSPSolveTranspose(ksp,VecsSensiTemp[nadj],VecsDeltaLam2[nadj]);CHKERRQ(ierr); 477 } 478 } 479 480 /* Update sensitivities, and evaluate integrals if there is any */ 481 if(th->endpoint) { /* two-stage Theta methods */ 482 if (th->Theta!=1.) { /* general case */ 483 shift = 1./((th->Theta-1.)*th->time_step); 484 ierr = TSComputeIJacobian(ts,th->ptime,th->X0,th->Xdot,shift,J,Jp,PETSC_FALSE);CHKERRQ(ierr); 485 if (ts->vec_costintegral) { /* R_U at t_n */ 486 ierr = TSComputeDRDUFunction(ts,th->ptime,th->X0,ts->vecs_drdu);CHKERRQ(ierr); 487 } 488 for (nadj=0; nadj<ts->numcost; nadj++) { 489 ierr = MatMultTranspose(J,VecsDeltaLam[nadj],ts->vecs_sensi[nadj]);CHKERRQ(ierr); 490 ierr = VecScale(ts->vecs_sensi[nadj],1./shift);CHKERRQ(ierr); 491 if (ts->vec_costintegral) { 492 ierr = VecAXPY(ts->vecs_sensi[nadj],-1./shift,ts->vecs_drdu[nadj]);CHKERRQ(ierr); 493 } 494 } 495 if (ts->vecs_sensi2) { /* second-order */ 496 /* Get w1 at t_n from TLM matrix */ 497 ierr = MatDenseGetColumn(th->MatFwdSensip0,0,&xarr);CHKERRQ(ierr); 498 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 499 /* lambda_s^T F_UU w_1 */ 500 ierr = TSComputeIHessianProductFunction1(ts,th->ptime,th->X0,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fuu);CHKERRQ(ierr); 501 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 502 ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr); 503 if (ts->vecs_fup) { 504 /* lambda_s^T F_UU w_2 */ 505 ierr = TSComputeIHessianProductFunction2(ts,th->ptime,th->X0,VecsDeltaLam,ts->vec_dir,ts->vecs_fup);CHKERRQ(ierr); 506 } 507 for (nadj=0; nadj<ts->numcost; nadj++) { 508 /* M^T Lambda_s + h(1-theta) F_U^T Lambda_s + h(1-theta) R_U */ 509 ierr = MatMultTranspose(J,VecsDeltaLam2[nadj],ts->vecs_sensi2[nadj]);CHKERRQ(ierr); 510 ierr = VecScale(ts->vecs_sensi2[nadj],1./shift);CHKERRQ(ierr); 511 ierr = VecAXPY(ts->vecs_sensi2[nadj],-1./shift,ts->vecs_fuu[nadj]);CHKERRQ(ierr); 512 ierr = VecAXPY(ts->vecs_sensi2[nadj],-1./shift,ts->vecs_fuu[nadj]);CHKERRQ(ierr); 513 if (ts->vecs_fup) { 514 ierr = VecAXPY(ts->vecs_sensi2[nadj],-1./shift,ts->vecs_fup[nadj]);CHKERRQ(ierr); 515 } 516 if (ts->vec_costintegral) { 517 ierr = VecAXPY(ts->vecs_sensi2[nadj],-1./shift,ts->vecs_drdu[nadj]);CHKERRQ(ierr); 518 } 519 } 520 } 521 } else { /* backward Euler */ 522 shift = 0.0; 523 ierr = TSComputeIJacobian(ts,th->stage_time,ts->vec_sol,th->Xdot,shift,J,Jp,PETSC_FALSE);CHKERRQ(ierr); /* get -f_u */ 524 for (nadj=0; nadj<ts->numcost; nadj++) { 525 ierr = MatMultTranspose(J,VecsDeltaLam[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr); 526 ierr = VecAXPY(ts->vecs_sensi[nadj],-th->time_step,VecsSensiTemp[nadj]);CHKERRQ(ierr); 527 if (ts->vec_costintegral) { /* wrong? */ 528 ierr = VecAXPY(ts->vecs_sensi[nadj],th->time_step,ts->vecs_drdu[nadj]);CHKERRQ(ierr); 529 } 530 } 531 if (ts->vecs_sensi2) { 532 for (nadj=0; nadj<ts->numcost; nadj++) { 533 ierr = MatMultTranspose(J,VecsDeltaLam[nadj],VecsSensi2Temp[nadj]);CHKERRQ(ierr); 534 ierr = VecAXPY(ts->vecs_sensi2[nadj],-th->time_step,VecsSensi2Temp[nadj]);CHKERRQ(ierr); 535 } 536 } 537 } 538 539 if (ts->vecs_sensip) { /* sensitivities wrt parameters */ 540 /* U_{n+1} */ 541 ierr = TSComputeRHSJacobianP(ts,th->stage_time,ts->vec_sol,ts->Jacp);CHKERRQ(ierr); 542 if (ts->vec_costintegral) { 543 ierr = TSComputeDRDPFunction(ts,th->stage_time,ts->vec_sol,ts->vecs_drdp);CHKERRQ(ierr); 544 } 545 for (nadj=0; nadj<ts->numcost; nadj++) { 546 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr); 547 ierr = VecAXPY(ts->vecs_sensip[nadj],th->time_step*th->Theta,VecsDeltaMu[nadj]);CHKERRQ(ierr); 548 } 549 if (ts->vecs_sensip2) { /* second-order */ 550 /* lambda_s^T F_PU w_1 */ 551 ierr = TSComputeIHessianProductFunction3(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fpu);CHKERRQ(ierr); 552 /* lambda_s^T F_PP w_2 */ 553 ierr = TSComputeIHessianProductFunction4(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_dir,ts->vecs_fpp);CHKERRQ(ierr); 554 for (nadj=0; nadj<ts->numcost; nadj++) { 555 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam2[nadj],VecsDeltaMu2[nadj]);CHKERRQ(ierr); 556 ierr = VecAXPY(ts->vecs_sensip2[nadj],th->time_step*th->Theta,VecsDeltaMu2[nadj]);CHKERRQ(ierr); 557 if (ts->vecs_fpu) { 558 ierr = VecAXPY(ts->vecs_sensi2[nadj],th->time_step*th->Theta,ts->vecs_fpu[nadj]);CHKERRQ(ierr); 559 } 560 if (ts->vecs_fpp) { 561 ierr = VecAXPY(ts->vecs_sensi2[nadj],th->time_step*th->Theta,ts->vecs_fpp[nadj]);CHKERRQ(ierr); 562 } 563 if (ts->vec_costintegral) { 564 ierr = VecAXPY(ts->vecs_sensip2[nadj],th->time_step*th->Theta,ts->vecs_drdp[nadj]);CHKERRQ(ierr); 565 } 566 } 567 } 568 569 /* U_s */ 570 if (th->Theta!=1.) { 571 ierr = TSComputeRHSJacobianP(ts,th->ptime,th->X0,ts->Jacp);CHKERRQ(ierr); 572 if (ts->vec_costintegral) { 573 ierr = TSComputeDRDPFunction(ts,th->ptime,th->X0,ts->vecs_drdp);CHKERRQ(ierr); 574 } 575 for (nadj=0; nadj<ts->numcost; nadj++) { 576 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr); 577 ierr = VecAXPY(ts->vecs_sensip[nadj],th->time_step*(1.-th->Theta),VecsDeltaMu[nadj]);CHKERRQ(ierr); 578 if (ts->vecs_sensip2) { /* second-order */ 579 /* lambda_s^T F_PU w_1 */ 580 ierr = TSComputeIHessianProductFunction3(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fpu);CHKERRQ(ierr); 581 /* lambda_s^T F_PP w_2 */ 582 ierr = TSComputeIHessianProductFunction4(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_dir,ts->vecs_fpp);CHKERRQ(ierr); 583 for (nadj=0; nadj<ts->numcost; nadj++) { 584 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam2[nadj],VecsDeltaMu2[nadj]);CHKERRQ(ierr); 585 ierr = VecAXPY(ts->vecs_sensip2[nadj],th->time_step*(1.-th->Theta),VecsDeltaMu2[nadj]);CHKERRQ(ierr); 586 if (ts->vecs_fpu) { 587 ierr = VecAXPY(ts->vecs_sensi2[nadj],th->time_step*(1.-th->Theta),ts->vecs_fpu[nadj]);CHKERRQ(ierr); 588 } 589 if (ts->vecs_fpp) { 590 ierr = VecAXPY(ts->vecs_sensi2[nadj],th->time_step*(1.-th->Theta),ts->vecs_fpp[nadj]);CHKERRQ(ierr); 591 } 592 if (ts->vec_costintegral) { 593 ierr = VecAXPY(ts->vecs_sensip2[nadj],th->time_step*(1.-th->Theta),ts->vecs_drdp[nadj]);CHKERRQ(ierr); 594 } 595 } 596 } 597 } 598 } 599 } 600 } else { /* one-stage case */ 601 shift = 0.0; 602 ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,shift,J,Jp,PETSC_FALSE);CHKERRQ(ierr); /* get -f_y */ 603 if (ts->vec_costintegral) { 604 ierr = TSComputeDRDUFunction(ts,th->stage_time,th->X,ts->vecs_drdu);CHKERRQ(ierr); 605 } 606 for (nadj=0; nadj<ts->numcost; nadj++) { 607 ierr = MatMultTranspose(J,VecsDeltaLam[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr); 608 ierr = VecAXPY(ts->vecs_sensi[nadj],-th->time_step,VecsSensiTemp[nadj]);CHKERRQ(ierr); 609 if (ts->vec_costintegral) { 610 ierr = VecAXPY(ts->vecs_sensi[nadj],th->time_step,ts->vecs_drdu[nadj]);CHKERRQ(ierr); 611 } 612 } 613 if (ts->vecs_sensip) { 614 ierr = TSComputeRHSJacobianP(ts,th->stage_time,th->X,ts->Jacp);CHKERRQ(ierr); 615 for (nadj=0; nadj<ts->numcost; nadj++) { 616 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr); 617 ierr = VecAXPY(ts->vecs_sensip[nadj],th->time_step,VecsDeltaMu[nadj]);CHKERRQ(ierr); 618 } 619 if (ts->vec_costintegral) { 620 ierr = TSComputeDRDPFunction(ts,th->stage_time,th->X,ts->vecs_drdp);CHKERRQ(ierr); 621 for (nadj=0; nadj<ts->numcost; nadj++) { 622 ierr = VecAXPY(ts->vecs_sensip[nadj],th->time_step,ts->vecs_drdp[nadj]);CHKERRQ(ierr); 623 } 624 } 625 } 626 } 627 628 th->status = TS_STEP_COMPLETE; 629 PetscFunctionReturn(0); 630 } 631 632 static PetscErrorCode TSInterpolate_Theta(TS ts,PetscReal t,Vec X) 633 { 634 TS_Theta *th = (TS_Theta*)ts->data; 635 PetscReal dt = t - ts->ptime; 636 PetscErrorCode ierr; 637 638 PetscFunctionBegin; 639 ierr = VecCopy(ts->vec_sol,th->X);CHKERRQ(ierr); 640 if (th->endpoint) dt *= th->Theta; 641 ierr = VecWAXPY(X,dt,th->Xdot,th->X);CHKERRQ(ierr); 642 PetscFunctionReturn(0); 643 } 644 645 static PetscErrorCode TSEvaluateWLTE_Theta(TS ts,NormType wnormtype,PetscInt *order,PetscReal *wlte) 646 { 647 TS_Theta *th = (TS_Theta*)ts->data; 648 Vec X = ts->vec_sol; /* X = solution */ 649 Vec Y = th->vec_lte_work; /* Y = X + LTE */ 650 PetscReal wltea,wlter; 651 PetscErrorCode ierr; 652 653 PetscFunctionBegin; 654 if (!th->vec_sol_prev) {*wlte = -1; PetscFunctionReturn(0);} 655 /* Cannot compute LTE in first step or in restart after event */ 656 if (ts->steprestart) {*wlte = -1; PetscFunctionReturn(0);} 657 /* Compute LTE using backward differences with non-constant time step */ 658 { 659 PetscReal h = ts->time_step, h_prev = ts->ptime - ts->ptime_prev; 660 PetscReal a = 1 + h_prev/h; 661 PetscScalar scal[3]; Vec vecs[3]; 662 scal[0] = +1/a; scal[1] = -1/(a-1); scal[2] = +1/(a*(a-1)); 663 vecs[0] = X; vecs[1] = th->X0; vecs[2] = th->vec_sol_prev; 664 ierr = VecCopy(X,Y);CHKERRQ(ierr); 665 ierr = VecMAXPY(Y,3,scal,vecs);CHKERRQ(ierr); 666 ierr = TSErrorWeightedNorm(ts,X,Y,wnormtype,wlte,&wltea,&wlter);CHKERRQ(ierr); 667 } 668 if (order) *order = 2; 669 PetscFunctionReturn(0); 670 } 671 672 static PetscErrorCode TSRollBack_Theta(TS ts) 673 { 674 TS_Theta *th = (TS_Theta*)ts->data; 675 PetscInt ncost; 676 PetscErrorCode ierr; 677 678 PetscFunctionBegin; 679 ierr = VecCopy(th->X0,ts->vec_sol);CHKERRQ(ierr); 680 if (ts->vec_costintegral && ts->costintegralfwd) { 681 ierr = VecCopy(th->VecCostIntegral0,ts->vec_costintegral);CHKERRQ(ierr); 682 } 683 th->status = TS_STEP_INCOMPLETE; 684 if (ts->mat_sensip) { 685 ierr = MatCopy(th->MatFwdSensip0,ts->mat_sensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 686 } 687 if (ts->vecs_integral_sensip) { 688 for (ncost=0;ncost<ts->numcost;ncost++) { 689 ierr = VecCopy(th->VecsIntegralSensip0[ncost],ts->vecs_integral_sensip[ncost]);CHKERRQ(ierr); 690 } 691 } 692 PetscFunctionReturn(0); 693 } 694 695 static PetscErrorCode TSForwardStep_Theta(TS ts) 696 { 697 TS_Theta *th = (TS_Theta*)ts->data; 698 Mat MatDeltaFwdSensip = th->MatDeltaFwdSensip; 699 Vec VecDeltaFwdSensipCol = th->VecDeltaFwdSensipCol; 700 PetscInt ncost,ntlm; 701 KSP ksp; 702 Mat J,Jp; 703 PetscReal shift; 704 PetscScalar *barr,*xarr; 705 PetscErrorCode ierr; 706 707 PetscFunctionBegin; 708 ierr = MatCopy(ts->mat_sensip,th->MatFwdSensip0,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 709 710 for (ncost=0; ncost<ts->numcost; ncost++) { 711 if (ts->vecs_integral_sensip) { 712 ierr = VecCopy(ts->vecs_integral_sensip[ncost],th->VecsIntegralSensip0[ncost]);CHKERRQ(ierr); 713 } 714 } 715 716 ierr = SNESGetKSP(ts->snes,&ksp);CHKERRQ(ierr); 717 ierr = TSGetIJacobian(ts,&J,&Jp,NULL,NULL);CHKERRQ(ierr); 718 719 /* Build RHS */ 720 if (th->endpoint) { /* 2-stage method*/ 721 shift = 1./((th->Theta-1.)*th->time_step); 722 ierr = TSComputeIJacobian(ts,th->ptime,th->X0,th->Xdot,shift,J,Jp,PETSC_FALSE);CHKERRQ(ierr); 723 ierr = MatMatMult(J,ts->mat_sensip,MAT_REUSE_MATRIX,PETSC_DEFAULT,&MatDeltaFwdSensip);CHKERRQ(ierr); 724 ierr = MatScale(MatDeltaFwdSensip,(th->Theta-1.)/th->Theta);CHKERRQ(ierr); 725 726 /* Add the f_p forcing terms */ 727 if (ts->Jacp) { 728 ierr = TSComputeRHSJacobianP(ts,th->ptime,th->X0,ts->Jacp);CHKERRQ(ierr); 729 ierr = MatAXPY(MatDeltaFwdSensip,(1.-th->Theta)/th->Theta,ts->Jacp,SUBSET_NONZERO_PATTERN);CHKERRQ(ierr); 730 ierr = TSComputeRHSJacobianP(ts,th->stage_time,ts->vec_sol,ts->Jacp);CHKERRQ(ierr); 731 ierr = MatAXPY(MatDeltaFwdSensip,1.,ts->Jacp,SUBSET_NONZERO_PATTERN);CHKERRQ(ierr); 732 } 733 } else { /* 1-stage method */ 734 shift = 0.0; 735 ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,shift,J,Jp,PETSC_FALSE);CHKERRQ(ierr); 736 ierr = MatMatMult(J,ts->mat_sensip,MAT_REUSE_MATRIX,PETSC_DEFAULT,&MatDeltaFwdSensip);CHKERRQ(ierr); 737 ierr = MatScale(MatDeltaFwdSensip,-1.);CHKERRQ(ierr); 738 739 /* Add the f_p forcing terms */ 740 if (ts->Jacp) { 741 ierr = TSComputeRHSJacobianP(ts,th->stage_time,th->X,ts->Jacp);CHKERRQ(ierr); 742 ierr = MatAXPY(MatDeltaFwdSensip,1.,ts->Jacp,SUBSET_NONZERO_PATTERN);CHKERRQ(ierr); 743 } 744 } 745 746 /* Build LHS */ 747 shift = 1/(th->Theta*th->time_step); 748 if (th->endpoint) { 749 ierr = TSComputeIJacobian(ts,th->stage_time,ts->vec_sol,th->Xdot,shift,J,Jp,PETSC_FALSE);CHKERRQ(ierr); 750 } else { 751 ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,shift,J,Jp,PETSC_FALSE);CHKERRQ(ierr); 752 } 753 ierr = KSPSetOperators(ksp,J,Jp);CHKERRQ(ierr); 754 755 /* 756 Evaluate the first stage of integral gradients with the 2-stage method: 757 drdu|t_n*S(t_n) + drdp|t_n 758 This is done before the linear solve because the sensitivity variable S(t_n) will be propagated to S(t_{n+1}) 759 */ 760 if (th->endpoint) { /* 2-stage method only */ 761 if (ts->vecs_integral_sensip) { 762 ierr = TSComputeDRDUFunction(ts,th->ptime,th->X0,ts->vecs_drdu);CHKERRQ(ierr); 763 if (ts->vecs_drdp) { 764 ierr = TSComputeDRDPFunction(ts,th->ptime,th->X0,ts->vecs_drdp);CHKERRQ(ierr); 765 } 766 for (ncost=0; ncost<ts->numcost; ncost++) { 767 ierr = MatMultTranspose(ts->mat_sensip,ts->vecs_drdu[ncost],th->VecIntegralSensipTemp);CHKERRQ(ierr); 768 if (ts->vecs_drdp) { 769 ierr = VecAXPY(th->VecIntegralSensipTemp,1,ts->vecs_drdp[ncost]);CHKERRQ(ierr); 770 } 771 ierr = VecAXPY(ts->vecs_integral_sensip[ncost],th->time_step*(1.-th->Theta),th->VecIntegralSensipTemp);CHKERRQ(ierr); 772 } 773 } 774 } 775 776 /* Solve the tangent linear equation for forward sensitivities to parameters */ 777 for (ntlm=0; ntlm<th->num_tlm; ntlm++) { 778 KSPConvergedReason kspreason; 779 ierr = MatDenseGetColumn(MatDeltaFwdSensip,ntlm,&barr);CHKERRQ(ierr); 780 ierr = VecPlaceArray(VecDeltaFwdSensipCol,barr);CHKERRQ(ierr); 781 if (th->endpoint) { 782 ierr = MatDenseGetColumn(ts->mat_sensip,ntlm,&xarr);CHKERRQ(ierr); 783 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 784 ierr = KSPSolve(ksp,VecDeltaFwdSensipCol,ts->vec_sensip_col);CHKERRQ(ierr); 785 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 786 ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr); 787 } else { 788 ierr = KSPSolve(ksp,VecDeltaFwdSensipCol,VecDeltaFwdSensipCol);CHKERRQ(ierr); 789 } 790 ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); 791 if (kspreason < 0) { 792 ts->reason = TSFORWARD_DIVERGED_LINEAR_SOLVE; 793 ierr = PetscInfo2(ts,"Step=%D, %Dth tangent linear solve, linear solve fails, stopping tangent linear solve\n",ts->steps,ntlm);CHKERRQ(ierr); 794 } 795 ierr = VecResetArray(VecDeltaFwdSensipCol);CHKERRQ(ierr); 796 ierr = MatDenseRestoreColumn(MatDeltaFwdSensip,&barr);CHKERRQ(ierr); 797 } 798 799 800 /* 801 Evaluate the second stage of integral gradients with the 2-stage method: 802 drdu|t_{n+1}*S(t_{n+1}) + drdp|t_{n+1} 803 */ 804 if (ts->vecs_integral_sensip) { 805 if (!th->endpoint) { 806 ierr = MatAXPY(ts->mat_sensip,1,MatDeltaFwdSensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 807 ierr = TSComputeDRDUFunction(ts,th->stage_time,th->X,ts->vecs_drdu);CHKERRQ(ierr); 808 if (ts->vecs_drdp) { 809 ierr = TSComputeDRDPFunction(ts,th->stage_time,th->X,ts->vecs_drdp);CHKERRQ(ierr); 810 } 811 for (ncost=0; ncost<ts->numcost; ncost++) { 812 ierr = MatMultTranspose(ts->mat_sensip,ts->vecs_drdu[ncost],th->VecIntegralSensipTemp);CHKERRQ(ierr); 813 if (ts->vecs_drdp) { 814 ierr = VecAXPY(th->VecIntegralSensipTemp,1,ts->vecs_drdp[ncost]);CHKERRQ(ierr); 815 } 816 ierr = VecAXPY(ts->vecs_integral_sensip[ncost],th->time_step,th->VecIntegralSensipTemp);CHKERRQ(ierr); 817 } 818 ierr = MatAXPY(ts->mat_sensip,(1.-th->Theta)/th->Theta,MatDeltaFwdSensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 819 } else { 820 ierr = TSComputeDRDUFunction(ts,th->stage_time,ts->vec_sol,ts->vecs_drdu);CHKERRQ(ierr); 821 if (ts->vecs_drdp) { 822 ierr = TSComputeDRDPFunction(ts,th->stage_time,ts->vec_sol,ts->vecs_drdp);CHKERRQ(ierr); 823 } 824 for (ncost=0; ncost<ts->numcost; ncost++) { 825 ierr = MatMultTranspose(ts->mat_sensip,ts->vecs_drdu[ncost],th->VecIntegralSensipTemp);CHKERRQ(ierr); 826 if (ts->vecs_drdp) { 827 ierr = VecAXPY(th->VecIntegralSensipTemp,1,ts->vecs_drdp[ncost]);CHKERRQ(ierr); 828 } 829 ierr = VecAXPY(ts->vecs_integral_sensip[ncost],th->time_step*th->Theta,th->VecIntegralSensipTemp);CHKERRQ(ierr); 830 } 831 } 832 } else { 833 if (!th->endpoint) { 834 ierr = MatAXPY(ts->mat_sensip,1./th->Theta,MatDeltaFwdSensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 835 } 836 } 837 PetscFunctionReturn(0); 838 } 839 840 static PetscErrorCode TSForwardGetStages_Theta(TS ts,PetscInt *ns,Mat **stagesensip) 841 { 842 TS_Theta *th = (TS_Theta*)ts->data; 843 844 PetscFunctionBegin; 845 if (ns) *ns = 1; 846 if (stagesensip) *stagesensip = th->endpoint ? &(th->MatFwdSensip0) : &(th->MatDeltaFwdSensip); 847 PetscFunctionReturn(0); 848 } 849 850 /*------------------------------------------------------------*/ 851 static PetscErrorCode TSReset_Theta(TS ts) 852 { 853 TS_Theta *th = (TS_Theta*)ts->data; 854 PetscErrorCode ierr; 855 856 PetscFunctionBegin; 857 ierr = VecDestroy(&th->X);CHKERRQ(ierr); 858 ierr = VecDestroy(&th->Xdot);CHKERRQ(ierr); 859 ierr = VecDestroy(&th->X0);CHKERRQ(ierr); 860 ierr = VecDestroy(&th->affine);CHKERRQ(ierr); 861 862 ierr = VecDestroy(&th->vec_sol_prev);CHKERRQ(ierr); 863 ierr = VecDestroy(&th->vec_lte_work);CHKERRQ(ierr); 864 865 ierr = VecDestroy(&th->VecCostIntegral0);CHKERRQ(ierr); 866 if (ts->forward_solve) { 867 if (ts->vecs_integral_sensip) { 868 ierr = VecDestroy(&th->VecIntegralSensipTemp);CHKERRQ(ierr); 869 ierr = VecDestroyVecs(ts->numcost,&th->VecsIntegralSensip0);CHKERRQ(ierr); 870 } 871 ierr = VecDestroy(&th->VecDeltaFwdSensipCol);CHKERRQ(ierr); 872 ierr = MatDestroy(&th->MatDeltaFwdSensip);CHKERRQ(ierr); 873 ierr = MatDestroy(&th->MatFwdSensip0);CHKERRQ(ierr); 874 } 875 ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaLam);CHKERRQ(ierr); 876 ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaMu);CHKERRQ(ierr); 877 ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaLam2);CHKERRQ(ierr); 878 ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaMu2);CHKERRQ(ierr); 879 ierr = VecDestroyVecs(ts->numcost,&th->VecsSensiTemp);CHKERRQ(ierr); 880 ierr = VecDestroyVecs(ts->numcost,&th->VecsSensi2Temp);CHKERRQ(ierr); 881 882 PetscFunctionReturn(0); 883 } 884 885 static PetscErrorCode TSAdjointReset_Theta(TS ts) 886 { 887 TS_Theta *th = (TS_Theta*)ts->data; 888 PetscErrorCode ierr; 889 890 PetscFunctionBegin; 891 ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaLam);CHKERRQ(ierr); 892 ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaMu);CHKERRQ(ierr); 893 ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaLam2);CHKERRQ(ierr); 894 ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaMu2);CHKERRQ(ierr); 895 ierr = VecDestroyVecs(ts->numcost,&th->VecsSensiTemp);CHKERRQ(ierr); 896 ierr = VecDestroyVecs(ts->numcost,&th->VecsSensi2Temp);CHKERRQ(ierr); 897 PetscFunctionReturn(0); 898 } 899 900 static PetscErrorCode TSDestroy_Theta(TS ts) 901 { 902 PetscErrorCode ierr; 903 904 PetscFunctionBegin; 905 ierr = TSReset_Theta(ts);CHKERRQ(ierr); 906 if (ts->dm) { 907 ierr = DMCoarsenHookRemove(ts->dm,DMCoarsenHook_TSTheta,DMRestrictHook_TSTheta,ts);CHKERRQ(ierr); 908 ierr = DMSubDomainHookRemove(ts->dm,DMSubDomainHook_TSTheta,DMSubDomainRestrictHook_TSTheta,ts);CHKERRQ(ierr); 909 } 910 ierr = PetscFree(ts->data);CHKERRQ(ierr); 911 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetTheta_C",NULL);CHKERRQ(ierr); 912 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetTheta_C",NULL);CHKERRQ(ierr); 913 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetEndpoint_C",NULL);CHKERRQ(ierr); 914 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetEndpoint_C",NULL);CHKERRQ(ierr); 915 PetscFunctionReturn(0); 916 } 917 918 /* 919 This defines the nonlinear equation that is to be solved with SNES 920 G(U) = F[t0+Theta*dt, U, (U-U0)*shift] = 0 921 */ 922 static PetscErrorCode SNESTSFormFunction_Theta(SNES snes,Vec x,Vec y,TS ts) 923 { 924 TS_Theta *th = (TS_Theta*)ts->data; 925 PetscErrorCode ierr; 926 Vec X0,Xdot; 927 DM dm,dmsave; 928 PetscReal shift = 1/(th->Theta*ts->time_step); 929 930 PetscFunctionBegin; 931 ierr = SNESGetDM(snes,&dm);CHKERRQ(ierr); 932 /* When using the endpoint variant, this is actually 1/Theta * Xdot */ 933 ierr = TSThetaGetX0AndXdot(ts,dm,&X0,&Xdot);CHKERRQ(ierr); 934 ierr = VecAXPBYPCZ(Xdot,-shift,shift,0,X0,x);CHKERRQ(ierr); 935 936 /* DM monkey-business allows user code to call TSGetDM() inside of functions evaluated on levels of FAS */ 937 dmsave = ts->dm; 938 ts->dm = dm; 939 ierr = TSComputeIFunction(ts,th->stage_time,x,Xdot,y,PETSC_FALSE);CHKERRQ(ierr); 940 ts->dm = dmsave; 941 ierr = TSThetaRestoreX0AndXdot(ts,dm,&X0,&Xdot);CHKERRQ(ierr); 942 PetscFunctionReturn(0); 943 } 944 945 static PetscErrorCode SNESTSFormJacobian_Theta(SNES snes,Vec x,Mat A,Mat B,TS ts) 946 { 947 TS_Theta *th = (TS_Theta*)ts->data; 948 PetscErrorCode ierr; 949 Vec Xdot; 950 DM dm,dmsave; 951 PetscReal shift = 1/(th->Theta*ts->time_step); 952 953 PetscFunctionBegin; 954 ierr = SNESGetDM(snes,&dm);CHKERRQ(ierr); 955 /* Xdot has already been computed in SNESTSFormFunction_Theta (SNES guarantees this) */ 956 ierr = TSThetaGetX0AndXdot(ts,dm,NULL,&Xdot);CHKERRQ(ierr); 957 958 dmsave = ts->dm; 959 ts->dm = dm; 960 ierr = TSComputeIJacobian(ts,th->stage_time,x,Xdot,shift,A,B,PETSC_FALSE);CHKERRQ(ierr); 961 ts->dm = dmsave; 962 ierr = TSThetaRestoreX0AndXdot(ts,dm,NULL,&Xdot);CHKERRQ(ierr); 963 PetscFunctionReturn(0); 964 } 965 966 static PetscErrorCode TSForwardSetUp_Theta(TS ts) 967 { 968 TS_Theta *th = (TS_Theta*)ts->data; 969 PetscErrorCode ierr; 970 971 PetscFunctionBegin; 972 /* combine sensitivities to parameters and sensitivities to initial values into one array */ 973 th->num_tlm = ts->num_parameters; 974 ierr = MatDuplicate(ts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatDeltaFwdSensip);CHKERRQ(ierr); 975 if (ts->vecs_integral_sensip) { 976 ierr = VecDuplicate(ts->vecs_integral_sensip[0],&th->VecIntegralSensipTemp);CHKERRQ(ierr); 977 } 978 /* backup sensitivity results for roll-backs */ 979 ierr = MatDuplicate(ts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatFwdSensip0);CHKERRQ(ierr); 980 981 if (ts->vecs_integral_sensip) { 982 ierr = VecDuplicateVecs(ts->vecs_integral_sensip[0],ts->numcost,&th->VecsIntegralSensip0);CHKERRQ(ierr); 983 } 984 ierr = VecDuplicate(ts->vec_sol,&th->VecDeltaFwdSensipCol);CHKERRQ(ierr); 985 ierr = VecDuplicate(ts->vec_sol,&ts->vec_sensip_col);CHKERRQ(ierr); 986 PetscFunctionReturn(0); 987 } 988 989 static PetscErrorCode TSForwardReset_Theta(TS ts) 990 { 991 TS_Theta *th = (TS_Theta*)ts->data; 992 PetscErrorCode ierr; 993 994 PetscFunctionBegin; 995 if (ts->vecs_integral_sensip) { 996 ierr = VecDestroy(&th->VecIntegralSensipTemp);CHKERRQ(ierr); 997 ierr = VecDestroyVecs(ts->numcost,&th->VecsIntegralSensip0);CHKERRQ(ierr); 998 } 999 ierr = VecDestroy(&th->VecDeltaFwdSensipCol);CHKERRQ(ierr); 1000 ierr = MatDestroy(&th->MatDeltaFwdSensip);CHKERRQ(ierr); 1001 ierr = MatDestroy(&th->MatFwdSensip0);CHKERRQ(ierr); 1002 PetscFunctionReturn(0); 1003 } 1004 1005 static PetscErrorCode TSSetUp_Theta(TS ts) 1006 { 1007 TS_Theta *th = (TS_Theta*)ts->data; 1008 PetscBool match; 1009 PetscErrorCode ierr; 1010 1011 PetscFunctionBegin; 1012 if (!th->VecCostIntegral0 && ts->vec_costintegral && ts->costintegralfwd) { /* back up cost integral */ 1013 ierr = VecDuplicate(ts->vec_costintegral,&th->VecCostIntegral0);CHKERRQ(ierr); 1014 } 1015 if (!th->X) { 1016 ierr = VecDuplicate(ts->vec_sol,&th->X);CHKERRQ(ierr); 1017 } 1018 if (!th->Xdot) { 1019 ierr = VecDuplicate(ts->vec_sol,&th->Xdot);CHKERRQ(ierr); 1020 } 1021 if (!th->X0) { 1022 ierr = VecDuplicate(ts->vec_sol,&th->X0);CHKERRQ(ierr); 1023 } 1024 if (th->endpoint) { 1025 ierr = VecDuplicate(ts->vec_sol,&th->affine);CHKERRQ(ierr); 1026 } 1027 1028 th->order = (th->Theta == 0.5) ? 2 : 1; 1029 1030 ierr = TSGetDM(ts,&ts->dm);CHKERRQ(ierr); 1031 ierr = DMCoarsenHookAdd(ts->dm,DMCoarsenHook_TSTheta,DMRestrictHook_TSTheta,ts);CHKERRQ(ierr); 1032 ierr = DMSubDomainHookAdd(ts->dm,DMSubDomainHook_TSTheta,DMSubDomainRestrictHook_TSTheta,ts);CHKERRQ(ierr); 1033 1034 ierr = TSGetAdapt(ts,&ts->adapt);CHKERRQ(ierr); 1035 ierr = TSAdaptCandidatesClear(ts->adapt);CHKERRQ(ierr); 1036 ierr = PetscObjectTypeCompare((PetscObject)ts->adapt,TSADAPTNONE,&match);CHKERRQ(ierr); 1037 if (!match) { 1038 ierr = VecDuplicate(ts->vec_sol,&th->vec_sol_prev);CHKERRQ(ierr); 1039 ierr = VecDuplicate(ts->vec_sol,&th->vec_lte_work);CHKERRQ(ierr); 1040 } 1041 ierr = TSGetSNES(ts,&ts->snes);CHKERRQ(ierr); 1042 PetscFunctionReturn(0); 1043 } 1044 1045 /*------------------------------------------------------------*/ 1046 1047 static PetscErrorCode TSAdjointSetUp_Theta(TS ts) 1048 { 1049 TS_Theta *th = (TS_Theta*)ts->data; 1050 PetscErrorCode ierr; 1051 1052 PetscFunctionBegin; 1053 ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&th->VecsDeltaLam);CHKERRQ(ierr); 1054 ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&th->VecsSensiTemp);CHKERRQ(ierr); 1055 if (ts->vecs_sensip) { 1056 ierr = VecDuplicateVecs(ts->vecs_sensip[0],ts->numcost,&th->VecsDeltaMu);CHKERRQ(ierr); 1057 } 1058 if (ts->vecs_sensi2) { 1059 ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&th->VecsDeltaLam2);CHKERRQ(ierr); 1060 ierr = VecDuplicateVecs(ts->vecs_sensi2[0],ts->numcost,&th->VecsSensi2Temp);CHKERRQ(ierr); 1061 } 1062 if (ts->vecs_sensi2p) { 1063 ierr = VecDuplicateVecs(ts->vecs_sensi2p[0],ts->numcost,&th->VecsDeltaMu2);CHKERRQ(ierr); 1064 } 1065 PetscFunctionReturn(0); 1066 } 1067 1068 static PetscErrorCode TSSetFromOptions_Theta(PetscOptionItems *PetscOptionsObject,TS ts) 1069 { 1070 TS_Theta *th = (TS_Theta*)ts->data; 1071 PetscErrorCode ierr; 1072 1073 PetscFunctionBegin; 1074 ierr = PetscOptionsHead(PetscOptionsObject,"Theta ODE solver options");CHKERRQ(ierr); 1075 { 1076 ierr = PetscOptionsReal("-ts_theta_theta","Location of stage (0<Theta<=1)","TSThetaSetTheta",th->Theta,&th->Theta,NULL);CHKERRQ(ierr); 1077 ierr = PetscOptionsBool("-ts_theta_endpoint","Use the endpoint instead of midpoint form of the Theta method","TSThetaSetEndpoint",th->endpoint,&th->endpoint,NULL);CHKERRQ(ierr); 1078 ierr = PetscOptionsBool("-ts_theta_initial_guess_extrapolate","Extrapolate stage initial guess from previous solution (sometimes unstable)","TSThetaSetExtrapolate",th->extrapolate,&th->extrapolate,NULL);CHKERRQ(ierr); 1079 } 1080 ierr = PetscOptionsTail();CHKERRQ(ierr); 1081 PetscFunctionReturn(0); 1082 } 1083 1084 static PetscErrorCode TSView_Theta(TS ts,PetscViewer viewer) 1085 { 1086 TS_Theta *th = (TS_Theta*)ts->data; 1087 PetscBool iascii; 1088 PetscErrorCode ierr; 1089 1090 PetscFunctionBegin; 1091 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1092 if (iascii) { 1093 ierr = PetscViewerASCIIPrintf(viewer," Theta=%g\n",(double)th->Theta);CHKERRQ(ierr); 1094 ierr = PetscViewerASCIIPrintf(viewer," Extrapolation=%s\n",th->extrapolate ? "yes" : "no");CHKERRQ(ierr); 1095 } 1096 PetscFunctionReturn(0); 1097 } 1098 1099 static PetscErrorCode TSThetaGetTheta_Theta(TS ts,PetscReal *theta) 1100 { 1101 TS_Theta *th = (TS_Theta*)ts->data; 1102 1103 PetscFunctionBegin; 1104 *theta = th->Theta; 1105 PetscFunctionReturn(0); 1106 } 1107 1108 static PetscErrorCode TSThetaSetTheta_Theta(TS ts,PetscReal theta) 1109 { 1110 TS_Theta *th = (TS_Theta*)ts->data; 1111 1112 PetscFunctionBegin; 1113 if (theta <= 0 || 1 < theta) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Theta %g not in range (0,1]",(double)theta); 1114 th->Theta = theta; 1115 th->order = (th->Theta == 0.5) ? 2 : 1; 1116 PetscFunctionReturn(0); 1117 } 1118 1119 static PetscErrorCode TSThetaGetEndpoint_Theta(TS ts,PetscBool *endpoint) 1120 { 1121 TS_Theta *th = (TS_Theta*)ts->data; 1122 1123 PetscFunctionBegin; 1124 *endpoint = th->endpoint; 1125 PetscFunctionReturn(0); 1126 } 1127 1128 static PetscErrorCode TSThetaSetEndpoint_Theta(TS ts,PetscBool flg) 1129 { 1130 TS_Theta *th = (TS_Theta*)ts->data; 1131 1132 PetscFunctionBegin; 1133 th->endpoint = flg; 1134 PetscFunctionReturn(0); 1135 } 1136 1137 #if defined(PETSC_HAVE_COMPLEX) 1138 static PetscErrorCode TSComputeLinearStability_Theta(TS ts,PetscReal xr,PetscReal xi,PetscReal *yr,PetscReal *yi) 1139 { 1140 PetscComplex z = xr + xi*PETSC_i,f; 1141 TS_Theta *th = (TS_Theta*)ts->data; 1142 const PetscReal one = 1.0; 1143 1144 PetscFunctionBegin; 1145 f = (one + (one - th->Theta)*z)/(one - th->Theta*z); 1146 *yr = PetscRealPartComplex(f); 1147 *yi = PetscImaginaryPartComplex(f); 1148 PetscFunctionReturn(0); 1149 } 1150 #endif 1151 1152 static PetscErrorCode TSGetStages_Theta(TS ts,PetscInt *ns,Vec **Y) 1153 { 1154 TS_Theta *th = (TS_Theta*)ts->data; 1155 1156 PetscFunctionBegin; 1157 if (ns) *ns = 1; 1158 if (Y) *Y = th->endpoint ? &(th->X0) : &(th->X); 1159 PetscFunctionReturn(0); 1160 } 1161 1162 /* ------------------------------------------------------------ */ 1163 /*MC 1164 TSTHETA - DAE solver using the implicit Theta method 1165 1166 Level: beginner 1167 1168 Options Database: 1169 + -ts_theta_theta <Theta> - Location of stage (0<Theta<=1) 1170 . -ts_theta_endpoint <flag> - Use the endpoint (like Crank-Nicholson) instead of midpoint form of the Theta method 1171 - -ts_theta_initial_guess_extrapolate <flg> - Extrapolate stage initial guess from previous solution (sometimes unstable) 1172 1173 Notes: 1174 $ -ts_type theta -ts_theta_theta 1.0 corresponds to backward Euler (TSBEULER) 1175 $ -ts_type theta -ts_theta_theta 0.5 corresponds to the implicit midpoint rule 1176 $ -ts_type theta -ts_theta_theta 0.5 -ts_theta_endpoint corresponds to Crank-Nicholson (TSCN) 1177 1178 This method can be applied to DAE. 1179 1180 This method is cast as a 1-stage implicit Runge-Kutta method. 1181 1182 .vb 1183 Theta | Theta 1184 ------------- 1185 | 1 1186 .ve 1187 1188 For the default Theta=0.5, this is also known as the implicit midpoint rule. 1189 1190 When the endpoint variant is chosen, the method becomes a 2-stage method with first stage explicit: 1191 1192 .vb 1193 0 | 0 0 1194 1 | 1-Theta Theta 1195 ------------------- 1196 | 1-Theta Theta 1197 .ve 1198 1199 For the default Theta=0.5, this is the trapezoid rule (also known as Crank-Nicolson, see TSCN). 1200 1201 To apply a diagonally implicit RK method to DAE, the stage formula 1202 1203 $ Y_i = X + h sum_j a_ij Y'_j 1204 1205 is interpreted as a formula for Y'_i in terms of Y_i and known values (Y'_j, j<i) 1206 1207 .seealso: TSCreate(), TS, TSSetType(), TSCN, TSBEULER, TSThetaSetTheta(), TSThetaSetEndpoint() 1208 1209 M*/ 1210 PETSC_EXTERN PetscErrorCode TSCreate_Theta(TS ts) 1211 { 1212 TS_Theta *th; 1213 PetscErrorCode ierr; 1214 1215 PetscFunctionBegin; 1216 ts->ops->reset = TSReset_Theta; 1217 ts->ops->adjointreset = TSAdjointReset_Theta; 1218 ts->ops->destroy = TSDestroy_Theta; 1219 ts->ops->view = TSView_Theta; 1220 ts->ops->setup = TSSetUp_Theta; 1221 ts->ops->adjointsetup = TSAdjointSetUp_Theta; 1222 ts->ops->adjointreset = TSAdjointReset_Theta; 1223 ts->ops->step = TSStep_Theta; 1224 ts->ops->interpolate = TSInterpolate_Theta; 1225 ts->ops->evaluatewlte = TSEvaluateWLTE_Theta; 1226 ts->ops->rollback = TSRollBack_Theta; 1227 ts->ops->setfromoptions = TSSetFromOptions_Theta; 1228 ts->ops->snesfunction = SNESTSFormFunction_Theta; 1229 ts->ops->snesjacobian = SNESTSFormJacobian_Theta; 1230 #if defined(PETSC_HAVE_COMPLEX) 1231 ts->ops->linearstability = TSComputeLinearStability_Theta; 1232 #endif 1233 ts->ops->getstages = TSGetStages_Theta; 1234 ts->ops->adjointstep = TSAdjointStep_Theta; 1235 ts->ops->adjointintegral = TSAdjointCostIntegral_Theta; 1236 ts->ops->forwardintegral = TSForwardCostIntegral_Theta; 1237 ts->default_adapt_type = TSADAPTNONE; 1238 1239 ts->ops->forwardsetup = TSForwardSetUp_Theta; 1240 ts->ops->forwardreset = TSForwardReset_Theta; 1241 ts->ops->forwardstep = TSForwardStep_Theta; 1242 ts->ops->forwardgetstages = TSForwardGetStages_Theta; 1243 1244 ts->usessnes = PETSC_TRUE; 1245 1246 ierr = PetscNewLog(ts,&th);CHKERRQ(ierr); 1247 ts->data = (void*)th; 1248 1249 th->VecsDeltaLam = NULL; 1250 th->VecsDeltaMu = NULL; 1251 th->VecsSensiTemp = NULL; 1252 th->VecsSensi2Temp = NULL; 1253 1254 th->extrapolate = PETSC_FALSE; 1255 th->Theta = 0.5; 1256 th->order = 2; 1257 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetTheta_C",TSThetaGetTheta_Theta);CHKERRQ(ierr); 1258 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetTheta_C",TSThetaSetTheta_Theta);CHKERRQ(ierr); 1259 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetEndpoint_C",TSThetaGetEndpoint_Theta);CHKERRQ(ierr); 1260 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetEndpoint_C",TSThetaSetEndpoint_Theta);CHKERRQ(ierr); 1261 PetscFunctionReturn(0); 1262 } 1263 1264 /*@ 1265 TSThetaGetTheta - Get the abscissa of the stage in (0,1]. 1266 1267 Not Collective 1268 1269 Input Parameter: 1270 . ts - timestepping context 1271 1272 Output Parameter: 1273 . theta - stage abscissa 1274 1275 Note: 1276 Use of this function is normally only required to hack TSTHETA to use a modified integration scheme. 1277 1278 Level: Advanced 1279 1280 .seealso: TSThetaSetTheta() 1281 @*/ 1282 PetscErrorCode TSThetaGetTheta(TS ts,PetscReal *theta) 1283 { 1284 PetscErrorCode ierr; 1285 1286 PetscFunctionBegin; 1287 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1288 PetscValidPointer(theta,2); 1289 ierr = PetscUseMethod(ts,"TSThetaGetTheta_C",(TS,PetscReal*),(ts,theta));CHKERRQ(ierr); 1290 PetscFunctionReturn(0); 1291 } 1292 1293 /*@ 1294 TSThetaSetTheta - Set the abscissa of the stage in (0,1]. 1295 1296 Not Collective 1297 1298 Input Parameter: 1299 + ts - timestepping context 1300 - theta - stage abscissa 1301 1302 Options Database: 1303 . -ts_theta_theta <theta> 1304 1305 Level: Intermediate 1306 1307 .seealso: TSThetaGetTheta() 1308 @*/ 1309 PetscErrorCode TSThetaSetTheta(TS ts,PetscReal theta) 1310 { 1311 PetscErrorCode ierr; 1312 1313 PetscFunctionBegin; 1314 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1315 ierr = PetscTryMethod(ts,"TSThetaSetTheta_C",(TS,PetscReal),(ts,theta));CHKERRQ(ierr); 1316 PetscFunctionReturn(0); 1317 } 1318 1319 /*@ 1320 TSThetaGetEndpoint - Gets whether to use the endpoint variant of the method (e.g. trapezoid/Crank-Nicolson instead of midpoint rule). 1321 1322 Not Collective 1323 1324 Input Parameter: 1325 . ts - timestepping context 1326 1327 Output Parameter: 1328 . endpoint - PETSC_TRUE when using the endpoint variant 1329 1330 Level: Advanced 1331 1332 .seealso: TSThetaSetEndpoint(), TSTHETA, TSCN 1333 @*/ 1334 PetscErrorCode TSThetaGetEndpoint(TS ts,PetscBool *endpoint) 1335 { 1336 PetscErrorCode ierr; 1337 1338 PetscFunctionBegin; 1339 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1340 PetscValidPointer(endpoint,2); 1341 ierr = PetscUseMethod(ts,"TSThetaGetEndpoint_C",(TS,PetscBool*),(ts,endpoint));CHKERRQ(ierr); 1342 PetscFunctionReturn(0); 1343 } 1344 1345 /*@ 1346 TSThetaSetEndpoint - Sets whether to use the endpoint variant of the method (e.g. trapezoid/Crank-Nicolson instead of midpoint rule). 1347 1348 Not Collective 1349 1350 Input Parameter: 1351 + ts - timestepping context 1352 - flg - PETSC_TRUE to use the endpoint variant 1353 1354 Options Database: 1355 . -ts_theta_endpoint <flg> 1356 1357 Level: Intermediate 1358 1359 .seealso: TSTHETA, TSCN 1360 @*/ 1361 PetscErrorCode TSThetaSetEndpoint(TS ts,PetscBool flg) 1362 { 1363 PetscErrorCode ierr; 1364 1365 PetscFunctionBegin; 1366 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1367 ierr = PetscTryMethod(ts,"TSThetaSetEndpoint_C",(TS,PetscBool),(ts,flg));CHKERRQ(ierr); 1368 PetscFunctionReturn(0); 1369 } 1370 1371 /* 1372 * TSBEULER and TSCN are straightforward specializations of TSTHETA. 1373 * The creation functions for these specializations are below. 1374 */ 1375 1376 static PetscErrorCode TSSetUp_BEuler(TS ts) 1377 { 1378 TS_Theta *th = (TS_Theta*)ts->data; 1379 PetscErrorCode ierr; 1380 1381 PetscFunctionBegin; 1382 if (th->Theta != 1.0) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_OPT_OVERWRITE,"Can not change the default value (1) of theta when using backward Euler\n"); 1383 if (th->endpoint) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_OPT_OVERWRITE,"Can not change to the endpoint form of the Theta methods when using backward Euler\n"); 1384 ierr = TSSetUp_Theta(ts);CHKERRQ(ierr); 1385 PetscFunctionReturn(0); 1386 } 1387 1388 static PetscErrorCode TSView_BEuler(TS ts,PetscViewer viewer) 1389 { 1390 PetscFunctionBegin; 1391 PetscFunctionReturn(0); 1392 } 1393 1394 /*MC 1395 TSBEULER - ODE solver using the implicit backward Euler method 1396 1397 Level: beginner 1398 1399 Notes: 1400 TSBEULER is equivalent to TSTHETA with Theta=1.0 1401 1402 $ -ts_type theta -ts_theta_theta 1.0 1403 1404 .seealso: TSCreate(), TS, TSSetType(), TSEULER, TSCN, TSTHETA 1405 1406 M*/ 1407 PETSC_EXTERN PetscErrorCode TSCreate_BEuler(TS ts) 1408 { 1409 PetscErrorCode ierr; 1410 1411 PetscFunctionBegin; 1412 ierr = TSCreate_Theta(ts);CHKERRQ(ierr); 1413 ierr = TSThetaSetTheta(ts,1.0);CHKERRQ(ierr); 1414 ierr = TSThetaSetEndpoint(ts,PETSC_FALSE);CHKERRQ(ierr); 1415 ts->ops->setup = TSSetUp_BEuler; 1416 ts->ops->view = TSView_BEuler; 1417 PetscFunctionReturn(0); 1418 } 1419 1420 static PetscErrorCode TSSetUp_CN(TS ts) 1421 { 1422 TS_Theta *th = (TS_Theta*)ts->data; 1423 PetscErrorCode ierr; 1424 1425 PetscFunctionBegin; 1426 if (th->Theta != 0.5) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_OPT_OVERWRITE,"Can not change the default value (0.5) of theta when using Crank-Nicolson\n"); 1427 if (!th->endpoint) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_OPT_OVERWRITE,"Can not change to the midpoint form of the Theta methods when using Crank-Nicolson\n"); 1428 ierr = TSSetUp_Theta(ts);CHKERRQ(ierr); 1429 PetscFunctionReturn(0); 1430 } 1431 1432 static PetscErrorCode TSView_CN(TS ts,PetscViewer viewer) 1433 { 1434 PetscFunctionBegin; 1435 PetscFunctionReturn(0); 1436 } 1437 1438 /*MC 1439 TSCN - ODE solver using the implicit Crank-Nicolson method. 1440 1441 Level: beginner 1442 1443 Notes: 1444 TSCN is equivalent to TSTHETA with Theta=0.5 and the "endpoint" option set. I.e. 1445 1446 $ -ts_type theta -ts_theta_theta 0.5 -ts_theta_endpoint 1447 1448 .seealso: TSCreate(), TS, TSSetType(), TSBEULER, TSTHETA 1449 1450 M*/ 1451 PETSC_EXTERN PetscErrorCode TSCreate_CN(TS ts) 1452 { 1453 PetscErrorCode ierr; 1454 1455 PetscFunctionBegin; 1456 ierr = TSCreate_Theta(ts);CHKERRQ(ierr); 1457 ierr = TSThetaSetTheta(ts,0.5);CHKERRQ(ierr); 1458 ierr = TSThetaSetEndpoint(ts,PETSC_TRUE);CHKERRQ(ierr); 1459 ts->ops->setup = TSSetUp_CN; 1460 ts->ops->view = TSView_CN; 1461 PetscFunctionReturn(0); 1462 } 1463