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 lambda_{n+1}/h + r_u^T(n+1) */ 280 ierr = TSComputeDRDUFunction(ts,th->stage_time,th->X,ts->vecs_drdu);CHKERRQ(ierr); 281 for (nadj=0; nadj<ts->numcost; nadj++) { 282 ierr = VecCopy(ts->vecs_sensi[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr); 283 ierr = VecScale(VecsSensiTemp[nadj],1./th->time_step);CHKERRQ(ierr); /* lambda_{n+1}/h */ 284 if (ts->vecs_drdu) { 285 ierr = VecAXPY(VecsSensiTemp[nadj],1.,ts->vecs_drdu[nadj]);CHKERRQ(ierr); 286 } 287 } 288 289 /* Build LHS for first-order adjoint */ 290 shift = 1./th->time_step; 291 ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,shift,J,Jp,PETSC_FALSE);CHKERRQ(ierr); 292 ierr = KSPSetOperators(ksp,J,Jp);CHKERRQ(ierr); 293 294 /* Solve stage equation LHS*lambda_s = RHS for first-order adjoint */ 295 for (nadj=0; nadj<ts->numcost; nadj++) { 296 KSPConvergedReason kspreason; 297 ierr = KSPSolveTranspose(ksp,VecsSensiTemp[nadj],VecsDeltaLam[nadj]);CHKERRQ(ierr); 298 ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); 299 if (kspreason < 0) { 300 ts->reason = TSADJOINT_DIVERGED_LINEAR_SOLVE; 301 ierr = PetscInfo2(ts,"Step=%D, %Dth cost function, transposed linear solve fails, stopping adjoint solve\n",ts->steps,nadj);CHKERRQ(ierr); 302 } 303 } 304 305 if (ts->vecs_sensi2) { /* U_{n+1} */ 306 /* Get w1 at t_{n+1} from TLM matrix */ 307 ierr = MatDenseGetColumn(ts->mat_sensip,0,&xarr);CHKERRQ(ierr); 308 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 309 /* lambda_s^T F_UU w_1 */ 310 ierr = TSComputeIHessianProductFunction1(ts,th->stage_time,th->X,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fuu);CHKERRQ(ierr); 311 /* lambda_s^T F_UP w_2 */ 312 ierr = TSComputeIHessianProductFunction2(ts,th->stage_time,th->X,VecsDeltaLam,ts->vec_dir,ts->vecs_fup);CHKERRQ(ierr); 313 for (nadj=0; nadj<ts->numcost; nadj++) { /* compute the residual */ 314 ierr = VecCopy(ts->vecs_sensi2[nadj],VecsSensi2Temp[nadj]);CHKERRQ(ierr); 315 ierr = VecScale(VecsSensi2Temp[nadj],shift);CHKERRQ(ierr); 316 ierr = VecAXPY(VecsSensi2Temp[nadj],-1.,ts->vecs_fuu[nadj]);CHKERRQ(ierr); 317 if (ts->vecs_fup) { 318 ierr = VecAXPY(VecsSensi2Temp[nadj],-1.,ts->vecs_fup[nadj]);CHKERRQ(ierr); 319 } 320 } 321 /* Solve stage equation LHS X = RHS for second-order adjoint */ 322 for (nadj=0; nadj<ts->numcost; nadj++) { 323 KSPConvergedReason kspreason; 324 ierr = KSPSolveTranspose(ksp,VecsSensi2Temp[nadj],VecsDeltaLam2[nadj]);CHKERRQ(ierr); 325 ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); 326 if (kspreason < 0) { 327 ts->reason = TSADJOINT_DIVERGED_LINEAR_SOLVE; 328 ierr = PetscInfo2(ts,"Step=%D, %Dth cost function, transposed linear solve fails, stopping adjoint solve\n",ts->steps,nadj);CHKERRQ(ierr); 329 } 330 } 331 } 332 333 /* Update sensitivities, and evaluate integrals if there is any */ 334 shift = 0.0; 335 ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,shift,J,Jp,PETSC_FALSE);CHKERRQ(ierr); /* get -f_U */ 336 ierr = MatScale(J,-1.);CHKERRQ(ierr); 337 for (nadj=0; nadj<ts->numcost; nadj++) { 338 /* Add f_U \lambda_s to the original RHS */ 339 ierr = MatMultTransposeAdd(J,VecsDeltaLam[nadj],VecsSensiTemp[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr); 340 ierr = VecScale(VecsSensiTemp[nadj],th->time_step);CHKERRQ(ierr); 341 ierr = VecCopy(VecsSensiTemp[nadj],ts->vecs_sensi[nadj]);CHKERRQ(ierr); 342 if (ts->vecs_sensi2) { 343 ierr = MatMultTransposeAdd(J,VecsDeltaLam2[nadj],VecsSensi2Temp[nadj],VecsSensi2Temp[nadj]);CHKERRQ(ierr); 344 ierr = VecScale(VecsSensi2Temp[nadj],th->time_step);CHKERRQ(ierr); 345 ierr = VecCopy(VecsSensi2Temp[nadj],ts->vecs_sensi2[nadj]);CHKERRQ(ierr); 346 } 347 } 348 if (ts->vecs_sensip) { 349 ierr = TSComputeIJacobianP(ts,th->stage_time,th->X,th->Xdot,shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); /* get -f_p */ 350 ierr = TSComputeDRDPFunction(ts,th->stage_time,th->X,ts->vecs_drdp);CHKERRQ(ierr); 351 if (ts->vecs_sensi2p) { 352 /* lambda_s^T F_PU w_1 */ 353 ierr = TSComputeIHessianProductFunction3(ts,th->stage_time,th->X,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fpu);CHKERRQ(ierr); 354 /* lambda_s^T F_PP w_2 */ 355 ierr = TSComputeIHessianProductFunction4(ts,th->stage_time,th->X,VecsDeltaLam,ts->vec_dir,ts->vecs_fpp);CHKERRQ(ierr); 356 } 357 for (nadj=0; nadj<ts->numcost; nadj++) { 358 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr); 359 ierr = VecAXPY(ts->vecs_sensip[nadj],-th->time_step,VecsDeltaMu[nadj]);CHKERRQ(ierr); 360 if (ts->vecs_drdp) { 361 ierr = VecAXPY(ts->vecs_sensip[nadj],th->time_step,ts->vecs_drdp[nadj]);CHKERRQ(ierr); 362 } 363 if (ts->vecs_sensi2p) { 364 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam2[nadj],VecsDeltaMu2[nadj]);CHKERRQ(ierr); 365 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step,VecsDeltaMu2[nadj]);CHKERRQ(ierr); 366 if (ts->vecs_fpu) { 367 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step,ts->vecs_fpu[nadj]);CHKERRQ(ierr); 368 } 369 if (ts->vecs_fpp) { 370 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step,ts->vecs_fpp[nadj]);CHKERRQ(ierr); 371 } 372 } 373 } 374 } 375 376 if (ts->vecs_sensi2) { 377 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 378 ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr); 379 } 380 th->status = TS_STEP_COMPLETE; 381 PetscFunctionReturn(0); 382 } 383 384 static PetscErrorCode TSAdjointStep_Theta(TS ts) 385 { 386 TS_Theta *th = (TS_Theta*)ts->data; 387 Vec *VecsDeltaLam = th->VecsDeltaLam,*VecsDeltaMu = th->VecsDeltaMu,*VecsSensiTemp = th->VecsSensiTemp; 388 Vec *VecsDeltaLam2 = th->VecsDeltaLam2,*VecsDeltaMu2 = th->VecsDeltaMu2,*VecsSensi2Temp = th->VecsSensi2Temp; 389 PetscInt nadj; 390 Mat J,Jp; 391 KSP ksp; 392 PetscReal shift; 393 PetscScalar *xarr; 394 PetscErrorCode ierr; 395 396 PetscFunctionBegin; 397 if (th->Theta == 1.) { 398 ierr = TSAdjointStepBEuler_Private(ts);CHKERRQ(ierr); 399 PetscFunctionReturn(0); 400 } 401 th->status = TS_STEP_INCOMPLETE; 402 ierr = SNESGetKSP(ts->snes,&ksp);CHKERRQ(ierr); 403 ierr = TSGetIJacobian(ts,&J,&Jp,NULL,NULL);CHKERRQ(ierr); 404 405 /* If endpoint=1, th->ptime and th->X0 will be used; if endpoint=0, th->stage_time and th->X will be used. */ 406 th->stage_time = th->endpoint ? ts->ptime : (ts->ptime+(1.-th->Theta)*ts->time_step); /* time_step is negative*/ 407 th->ptime = ts->ptime + ts->time_step; 408 th->time_step = -ts->time_step; 409 410 /* Build RHS for first-order adjoint */ 411 /* Cost function has an integral term */ 412 if (th->endpoint) { 413 ierr = TSComputeDRDUFunction(ts,th->stage_time,ts->vec_sol,ts->vecs_drdu);CHKERRQ(ierr); 414 } else { 415 ierr = TSComputeDRDUFunction(ts,th->stage_time,th->X,ts->vecs_drdu);CHKERRQ(ierr); 416 } 417 418 for (nadj=0; nadj<ts->numcost; nadj++) { 419 ierr = VecCopy(ts->vecs_sensi[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr); 420 ierr = VecScale(VecsSensiTemp[nadj],1./(th->Theta*th->time_step));CHKERRQ(ierr); 421 if (ts->vec_costintegral) { 422 ierr = VecAXPY(VecsSensiTemp[nadj],1.,ts->vecs_drdu[nadj]);CHKERRQ(ierr); 423 } 424 } 425 426 /* Build LHS for first-order adjoint */ 427 shift = 1./(th->Theta*th->time_step); 428 if (th->endpoint) { 429 ierr = TSComputeIJacobian(ts,th->stage_time,ts->vec_sol,th->Xdot,shift,J,Jp,PETSC_FALSE);CHKERRQ(ierr); 430 } else { 431 ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,shift,J,Jp,PETSC_FALSE);CHKERRQ(ierr); 432 } 433 ierr = KSPSetOperators(ksp,J,Jp);CHKERRQ(ierr); 434 435 /* Solve stage equation LHS*lambda_s = RHS for first-order adjoint */ 436 for (nadj=0; nadj<ts->numcost; nadj++) { 437 KSPConvergedReason kspreason; 438 ierr = KSPSolveTranspose(ksp,VecsSensiTemp[nadj],VecsDeltaLam[nadj]);CHKERRQ(ierr); 439 ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); 440 if (kspreason < 0) { 441 ts->reason = TSADJOINT_DIVERGED_LINEAR_SOLVE; 442 ierr = PetscInfo2(ts,"Step=%D, %Dth cost function, transposed linear solve fails, stopping adjoint solve\n",ts->steps,nadj);CHKERRQ(ierr); 443 } 444 } 445 446 /* Second-order adjoint */ 447 if (ts->vecs_sensi2) { /* U_{n+1} */ 448 if (!th->endpoint) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Operation not implemented in TS_Theta"); 449 /* Get w1 at t_{n+1} from TLM matrix */ 450 ierr = MatDenseGetColumn(ts->mat_sensip,0,&xarr);CHKERRQ(ierr); 451 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 452 /* lambda_s^T F_UU w_1 */ 453 ierr = TSComputeIHessianProductFunction1(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fuu);CHKERRQ(ierr); 454 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 455 ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr); 456 /* lambda_s^T F_UP w_2 */ 457 ierr = TSComputeIHessianProductFunction2(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_dir,ts->vecs_fup);CHKERRQ(ierr); 458 for (nadj=0; nadj<ts->numcost; nadj++) { /* compute the residual */ 459 ierr = VecCopy(ts->vecs_sensi2[nadj],VecsSensi2Temp[nadj]);CHKERRQ(ierr); 460 ierr = VecScale(VecsSensi2Temp[nadj],shift);CHKERRQ(ierr); 461 ierr = VecAXPY(VecsSensi2Temp[nadj],-1.,ts->vecs_fuu[nadj]);CHKERRQ(ierr); 462 if (ts->vecs_fup) { 463 ierr = VecAXPY(VecsSensi2Temp[nadj],-1.,ts->vecs_fup[nadj]);CHKERRQ(ierr); 464 } 465 } 466 /* Solve stage equation LHS X = RHS for second-order adjoint */ 467 for (nadj=0; nadj<ts->numcost; nadj++) { 468 KSPConvergedReason kspreason; 469 ierr = KSPSolveTranspose(ksp,VecsSensi2Temp[nadj],VecsDeltaLam2[nadj]);CHKERRQ(ierr); 470 ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); 471 if (kspreason < 0) { 472 ts->reason = TSADJOINT_DIVERGED_LINEAR_SOLVE; 473 ierr = PetscInfo2(ts,"Step=%D, %Dth cost function, transposed linear solve fails, stopping adjoint solve\n",ts->steps,nadj);CHKERRQ(ierr); 474 } 475 } 476 } 477 478 /* Update sensitivities, and evaluate integrals if there is any */ 479 if(th->endpoint) { /* two-stage Theta methods with th->Theta!=1, th->Theta==1 leads to BEuler */ 480 shift = 1./((th->Theta-1.)*th->time_step); 481 ierr = TSComputeIJacobian(ts,th->ptime,th->X0,th->Xdot,shift,J,Jp,PETSC_FALSE);CHKERRQ(ierr); 482 /* R_U at t_n */ 483 ierr = TSComputeDRDUFunction(ts,th->ptime,th->X0,ts->vecs_drdu);CHKERRQ(ierr); 484 for (nadj=0; nadj<ts->numcost; nadj++) { 485 ierr = MatMultTranspose(J,VecsDeltaLam[nadj],ts->vecs_sensi[nadj]);CHKERRQ(ierr); 486 if (ts->vecs_drdu) { 487 ierr = VecAXPY(ts->vecs_sensi[nadj],-1.,ts->vecs_drdu[nadj]);CHKERRQ(ierr); 488 } 489 ierr = VecScale(ts->vecs_sensi[nadj],1./shift);CHKERRQ(ierr); 490 } 491 492 /* Second-order adjoint */ 493 if (ts->vecs_sensi2) { /* U_n */ 494 /* Get w1 at t_n from TLM matrix */ 495 ierr = MatDenseGetColumn(th->MatFwdSensip0,0,&xarr);CHKERRQ(ierr); 496 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 497 /* lambda_s^T F_UU w_1 */ 498 ierr = TSComputeIHessianProductFunction1(ts,th->ptime,th->X0,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fuu);CHKERRQ(ierr); 499 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 500 ierr = MatDenseRestoreColumn(th->MatFwdSensip0,&xarr);CHKERRQ(ierr); 501 /* lambda_s^T F_UU w_2 */ 502 ierr = TSComputeIHessianProductFunction2(ts,th->ptime,th->X0,VecsDeltaLam,ts->vec_dir,ts->vecs_fup);CHKERRQ(ierr); 503 for (nadj=0; nadj<ts->numcost; nadj++) { 504 /* M^T Lambda_s + h(1-theta) F_U^T Lambda_s + h(1-theta) lambda_s^T F_UU w_1 + lambda_s^T F_UP w_2 */ 505 ierr = MatMultTranspose(J,VecsDeltaLam2[nadj],ts->vecs_sensi2[nadj]);CHKERRQ(ierr); 506 ierr = VecAXPY(ts->vecs_sensi2[nadj],1.,ts->vecs_fuu[nadj]);CHKERRQ(ierr); 507 if (ts->vecs_fup) { 508 ierr = VecAXPY(ts->vecs_sensi2[nadj],1.,ts->vecs_fup[nadj]);CHKERRQ(ierr); 509 } 510 ierr = VecScale(ts->vecs_sensi2[nadj],1./shift);CHKERRQ(ierr); 511 } 512 } 513 514 if (ts->vecs_sensip) { /* sensitivities wrt parameters */ 515 /* U_{n+1} */ 516 shift = -1./(th->Theta*th->time_step); 517 ierr = TSComputeIJacobianP(ts,th->stage_time,ts->vec_sol,th->Xdot,shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 518 ierr = TSComputeDRDPFunction(ts,th->stage_time,ts->vec_sol,ts->vecs_drdp);CHKERRQ(ierr); 519 for (nadj=0; nadj<ts->numcost; nadj++) { 520 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr); 521 ierr = VecAXPY(ts->vecs_sensip[nadj],-th->time_step*th->Theta,VecsDeltaMu[nadj]);CHKERRQ(ierr); 522 } 523 if (ts->vecs_sensi2p) { /* second-order */ 524 /* Get w1 at t_{n+1} from TLM matrix */ 525 ierr = MatDenseGetColumn(ts->mat_sensip,0,&xarr);CHKERRQ(ierr); 526 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 527 /* lambda_s^T F_PU w_1 */ 528 ierr = TSComputeIHessianProductFunction3(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fpu);CHKERRQ(ierr); 529 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 530 ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr); 531 532 /* lambda_s^T F_PP w_2 */ 533 ierr = TSComputeIHessianProductFunction4(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_dir,ts->vecs_fpp);CHKERRQ(ierr); 534 for (nadj=0; nadj<ts->numcost; nadj++) { 535 /* Mu2 <- Mu2 + h theta F_P^T Lambda_s + h theta (lambda_s^T F_UU w_1 + lambda_s^T F_UP w_2) */ 536 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam2[nadj],VecsDeltaMu2[nadj]);CHKERRQ(ierr); 537 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step*th->Theta,VecsDeltaMu2[nadj]);CHKERRQ(ierr); 538 if (ts->vecs_fpu) { 539 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step*th->Theta,ts->vecs_fpu[nadj]);CHKERRQ(ierr); 540 } 541 if (ts->vecs_fpp) { 542 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step*th->Theta,ts->vecs_fpp[nadj]);CHKERRQ(ierr); 543 } 544 } 545 } 546 547 /* U_s */ 548 shift = 1./((th->Theta-1.0)*th->time_step); 549 ierr = TSComputeIJacobianP(ts,th->ptime,th->X0,th->Xdot,shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 550 ierr = TSComputeDRDPFunction(ts,th->ptime,th->X0,ts->vecs_drdp);CHKERRQ(ierr); 551 for (nadj=0; nadj<ts->numcost; nadj++) { 552 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr); 553 ierr = VecAXPY(ts->vecs_sensip[nadj],-th->time_step*(1.0-th->Theta),VecsDeltaMu[nadj]);CHKERRQ(ierr); 554 if (ts->vecs_sensi2p) { /* second-order */ 555 /* Get w1 at t_n from TLM matrix */ 556 ierr = MatDenseGetColumn(th->MatFwdSensip0,0,&xarr);CHKERRQ(ierr); 557 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 558 /* lambda_s^T F_PU w_1 */ 559 ierr = TSComputeIHessianProductFunction3(ts,th->ptime,th->X0,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fpu);CHKERRQ(ierr); 560 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 561 ierr = MatDenseRestoreColumn(th->MatFwdSensip0,&xarr);CHKERRQ(ierr); 562 /* lambda_s^T F_PP w_2 */ 563 ierr = TSComputeIHessianProductFunction4(ts,th->ptime,th->X0,VecsDeltaLam,ts->vec_dir,ts->vecs_fpp);CHKERRQ(ierr); 564 for (nadj=0; nadj<ts->numcost; nadj++) { 565 /* Mu2 <- Mu2 + h(1-theta) F_P^T Lambda_s + h(1-theta) (lambda_s^T F_UU w_1 + lambda_s^T F_UP w_2) */ 566 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam2[nadj],VecsDeltaMu2[nadj]);CHKERRQ(ierr); 567 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step*(1.0-th->Theta),VecsDeltaMu2[nadj]);CHKERRQ(ierr); 568 if (ts->vecs_fpu) { 569 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step*(1.0-th->Theta),ts->vecs_fpu[nadj]);CHKERRQ(ierr); 570 } 571 if (ts->vecs_fpp) { 572 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step*(1.0-th->Theta),ts->vecs_fpp[nadj]);CHKERRQ(ierr); 573 } 574 } 575 } 576 } 577 } 578 } else { /* one-stage case */ 579 shift = 0.0; 580 ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,shift,J,Jp,PETSC_FALSE);CHKERRQ(ierr); /* get -f_y */ 581 ierr = TSComputeDRDUFunction(ts,th->stage_time,th->X,ts->vecs_drdu);CHKERRQ(ierr); 582 for (nadj=0; nadj<ts->numcost; nadj++) { 583 ierr = MatMultTranspose(J,VecsDeltaLam[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr); 584 ierr = VecAXPY(ts->vecs_sensi[nadj],-th->time_step,VecsSensiTemp[nadj]);CHKERRQ(ierr); 585 if (ts->vecs_drdu) { 586 ierr = VecAXPY(ts->vecs_sensi[nadj],th->time_step,ts->vecs_drdu[nadj]);CHKERRQ(ierr); 587 } 588 } 589 if (ts->vecs_sensip) { 590 ierr = TSComputeIJacobianP(ts,th->stage_time,th->X,th->Xdot,shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 591 ierr = TSComputeDRDPFunction(ts,th->stage_time,th->X,ts->vecs_drdp);CHKERRQ(ierr); 592 for (nadj=0; nadj<ts->numcost; nadj++) { 593 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr); 594 ierr = VecAXPY(ts->vecs_sensip[nadj],-th->time_step,VecsDeltaMu[nadj]);CHKERRQ(ierr); 595 if (ts->vecs_drdp) { 596 ierr = VecAXPY(ts->vecs_sensip[nadj],th->time_step,ts->vecs_drdp[nadj]);CHKERRQ(ierr); 597 } 598 } 599 } 600 } 601 602 th->status = TS_STEP_COMPLETE; 603 PetscFunctionReturn(0); 604 } 605 606 static PetscErrorCode TSInterpolate_Theta(TS ts,PetscReal t,Vec X) 607 { 608 TS_Theta *th = (TS_Theta*)ts->data; 609 PetscReal dt = t - ts->ptime; 610 PetscErrorCode ierr; 611 612 PetscFunctionBegin; 613 ierr = VecCopy(ts->vec_sol,th->X);CHKERRQ(ierr); 614 if (th->endpoint) dt *= th->Theta; 615 ierr = VecWAXPY(X,dt,th->Xdot,th->X);CHKERRQ(ierr); 616 PetscFunctionReturn(0); 617 } 618 619 static PetscErrorCode TSEvaluateWLTE_Theta(TS ts,NormType wnormtype,PetscInt *order,PetscReal *wlte) 620 { 621 TS_Theta *th = (TS_Theta*)ts->data; 622 Vec X = ts->vec_sol; /* X = solution */ 623 Vec Y = th->vec_lte_work; /* Y = X + LTE */ 624 PetscReal wltea,wlter; 625 PetscErrorCode ierr; 626 627 PetscFunctionBegin; 628 if (!th->vec_sol_prev) {*wlte = -1; PetscFunctionReturn(0);} 629 /* Cannot compute LTE in first step or in restart after event */ 630 if (ts->steprestart) {*wlte = -1; PetscFunctionReturn(0);} 631 /* Compute LTE using backward differences with non-constant time step */ 632 { 633 PetscReal h = ts->time_step, h_prev = ts->ptime - ts->ptime_prev; 634 PetscReal a = 1 + h_prev/h; 635 PetscScalar scal[3]; Vec vecs[3]; 636 scal[0] = +1/a; scal[1] = -1/(a-1); scal[2] = +1/(a*(a-1)); 637 vecs[0] = X; vecs[1] = th->X0; vecs[2] = th->vec_sol_prev; 638 ierr = VecCopy(X,Y);CHKERRQ(ierr); 639 ierr = VecMAXPY(Y,3,scal,vecs);CHKERRQ(ierr); 640 ierr = TSErrorWeightedNorm(ts,X,Y,wnormtype,wlte,&wltea,&wlter);CHKERRQ(ierr); 641 } 642 if (order) *order = 2; 643 PetscFunctionReturn(0); 644 } 645 646 static PetscErrorCode TSRollBack_Theta(TS ts) 647 { 648 TS_Theta *th = (TS_Theta*)ts->data; 649 PetscInt ncost; 650 PetscErrorCode ierr; 651 652 PetscFunctionBegin; 653 ierr = VecCopy(th->X0,ts->vec_sol);CHKERRQ(ierr); 654 if (ts->vec_costintegral && ts->costintegralfwd) { 655 ierr = VecCopy(th->VecCostIntegral0,ts->vec_costintegral);CHKERRQ(ierr); 656 } 657 th->status = TS_STEP_INCOMPLETE; 658 if (ts->mat_sensip) { 659 ierr = MatCopy(th->MatFwdSensip0,ts->mat_sensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 660 } 661 if (ts->vecs_integral_sensip) { 662 for (ncost=0;ncost<ts->numcost;ncost++) { 663 ierr = VecCopy(th->VecsIntegralSensip0[ncost],ts->vecs_integral_sensip[ncost]);CHKERRQ(ierr); 664 } 665 } 666 PetscFunctionReturn(0); 667 } 668 669 static PetscErrorCode TSForwardStep_Theta(TS ts) 670 { 671 TS_Theta *th = (TS_Theta*)ts->data; 672 Mat MatDeltaFwdSensip = th->MatDeltaFwdSensip; 673 Vec VecDeltaFwdSensipCol = th->VecDeltaFwdSensipCol; 674 PetscInt ncost,ntlm; 675 KSP ksp; 676 Mat J,Jp; 677 PetscReal shift; 678 PetscScalar *barr,*xarr; 679 PetscErrorCode ierr; 680 681 PetscFunctionBegin; 682 ierr = MatCopy(ts->mat_sensip,th->MatFwdSensip0,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 683 684 for (ncost=0; ncost<ts->numcost; ncost++) { 685 if (ts->vecs_integral_sensip) { 686 ierr = VecCopy(ts->vecs_integral_sensip[ncost],th->VecsIntegralSensip0[ncost]);CHKERRQ(ierr); 687 } 688 } 689 690 ierr = SNESGetKSP(ts->snes,&ksp);CHKERRQ(ierr); 691 ierr = TSGetIJacobian(ts,&J,&Jp,NULL,NULL);CHKERRQ(ierr); 692 693 /* Build RHS */ 694 if (th->endpoint) { /* 2-stage method*/ 695 shift = 1./((th->Theta-1.)*th->time_step); 696 ierr = TSComputeIJacobian(ts,th->ptime,th->X0,th->Xdot,shift,J,Jp,PETSC_FALSE);CHKERRQ(ierr); 697 ierr = MatMatMult(J,ts->mat_sensip,MAT_REUSE_MATRIX,PETSC_DEFAULT,&MatDeltaFwdSensip);CHKERRQ(ierr); 698 ierr = MatScale(MatDeltaFwdSensip,(th->Theta-1.)/th->Theta);CHKERRQ(ierr); 699 700 /* Add the f_p forcing terms */ 701 if (ts->Jacp) { 702 ierr = TSComputeIJacobianP(ts,th->ptime,th->X0,th->Xdot,shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 703 ierr = MatAXPY(MatDeltaFwdSensip,(th->Theta-1.)/th->Theta,ts->Jacp,SUBSET_NONZERO_PATTERN);CHKERRQ(ierr); 704 ierr = TSComputeIJacobianP(ts,th->stage_time,ts->vec_sol,th->Xdot,shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 705 ierr = MatAXPY(MatDeltaFwdSensip,-1.,ts->Jacp,SUBSET_NONZERO_PATTERN);CHKERRQ(ierr); 706 } 707 } else { /* 1-stage method */ 708 shift = 0.0; 709 ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,shift,J,Jp,PETSC_FALSE);CHKERRQ(ierr); 710 ierr = MatMatMult(J,ts->mat_sensip,MAT_REUSE_MATRIX,PETSC_DEFAULT,&MatDeltaFwdSensip);CHKERRQ(ierr); 711 ierr = MatScale(MatDeltaFwdSensip,-1.);CHKERRQ(ierr); 712 713 /* Add the f_p forcing terms */ 714 if (ts->Jacp) { 715 ierr = TSComputeIJacobianP(ts,th->stage_time,th->X,th->Xdot,shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 716 ierr = MatAXPY(MatDeltaFwdSensip,-1.,ts->Jacp,SUBSET_NONZERO_PATTERN);CHKERRQ(ierr); 717 } 718 } 719 720 /* Build LHS */ 721 shift = 1/(th->Theta*th->time_step); 722 if (th->endpoint) { 723 ierr = TSComputeIJacobian(ts,th->stage_time,ts->vec_sol,th->Xdot,shift,J,Jp,PETSC_FALSE);CHKERRQ(ierr); 724 } else { 725 ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,shift,J,Jp,PETSC_FALSE);CHKERRQ(ierr); 726 } 727 ierr = KSPSetOperators(ksp,J,Jp);CHKERRQ(ierr); 728 729 /* 730 Evaluate the first stage of integral gradients with the 2-stage method: 731 drdu|t_n*S(t_n) + drdp|t_n 732 This is done before the linear solve because the sensitivity variable S(t_n) will be propagated to S(t_{n+1}) 733 */ 734 if (th->endpoint) { /* 2-stage method only */ 735 if (ts->vecs_integral_sensip) { 736 ierr = TSComputeDRDUFunction(ts,th->ptime,th->X0,ts->vecs_drdu);CHKERRQ(ierr); 737 if (ts->vecs_drdp) { 738 ierr = TSComputeDRDPFunction(ts,th->ptime,th->X0,ts->vecs_drdp);CHKERRQ(ierr); 739 } 740 for (ncost=0; ncost<ts->numcost; ncost++) { 741 ierr = MatMultTranspose(ts->mat_sensip,ts->vecs_drdu[ncost],th->VecIntegralSensipTemp);CHKERRQ(ierr); 742 if (ts->vecs_drdp) { 743 ierr = VecAXPY(th->VecIntegralSensipTemp,1,ts->vecs_drdp[ncost]);CHKERRQ(ierr); 744 } 745 ierr = VecAXPY(ts->vecs_integral_sensip[ncost],th->time_step*(1.-th->Theta),th->VecIntegralSensipTemp);CHKERRQ(ierr); 746 } 747 } 748 } 749 750 /* Solve the tangent linear equation for forward sensitivities to parameters */ 751 for (ntlm=0; ntlm<th->num_tlm; ntlm++) { 752 KSPConvergedReason kspreason; 753 ierr = MatDenseGetColumn(MatDeltaFwdSensip,ntlm,&barr);CHKERRQ(ierr); 754 ierr = VecPlaceArray(VecDeltaFwdSensipCol,barr);CHKERRQ(ierr); 755 if (th->endpoint) { 756 ierr = MatDenseGetColumn(ts->mat_sensip,ntlm,&xarr);CHKERRQ(ierr); 757 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 758 ierr = KSPSolve(ksp,VecDeltaFwdSensipCol,ts->vec_sensip_col);CHKERRQ(ierr); 759 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 760 ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr); 761 } else { 762 ierr = KSPSolve(ksp,VecDeltaFwdSensipCol,VecDeltaFwdSensipCol);CHKERRQ(ierr); 763 } 764 ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); 765 if (kspreason < 0) { 766 ts->reason = TSFORWARD_DIVERGED_LINEAR_SOLVE; 767 ierr = PetscInfo2(ts,"Step=%D, %Dth tangent linear solve, linear solve fails, stopping tangent linear solve\n",ts->steps,ntlm);CHKERRQ(ierr); 768 } 769 ierr = VecResetArray(VecDeltaFwdSensipCol);CHKERRQ(ierr); 770 ierr = MatDenseRestoreColumn(MatDeltaFwdSensip,&barr);CHKERRQ(ierr); 771 } 772 773 774 /* 775 Evaluate the second stage of integral gradients with the 2-stage method: 776 drdu|t_{n+1}*S(t_{n+1}) + drdp|t_{n+1} 777 */ 778 if (ts->vecs_integral_sensip) { 779 if (!th->endpoint) { 780 ierr = MatAXPY(ts->mat_sensip,1,MatDeltaFwdSensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 781 ierr = TSComputeDRDUFunction(ts,th->stage_time,th->X,ts->vecs_drdu);CHKERRQ(ierr); 782 if (ts->vecs_drdp) { 783 ierr = TSComputeDRDPFunction(ts,th->stage_time,th->X,ts->vecs_drdp);CHKERRQ(ierr); 784 } 785 for (ncost=0; ncost<ts->numcost; ncost++) { 786 ierr = MatMultTranspose(ts->mat_sensip,ts->vecs_drdu[ncost],th->VecIntegralSensipTemp);CHKERRQ(ierr); 787 if (ts->vecs_drdp) { 788 ierr = VecAXPY(th->VecIntegralSensipTemp,1,ts->vecs_drdp[ncost]);CHKERRQ(ierr); 789 } 790 ierr = VecAXPY(ts->vecs_integral_sensip[ncost],th->time_step,th->VecIntegralSensipTemp);CHKERRQ(ierr); 791 } 792 ierr = MatAXPY(ts->mat_sensip,(1.-th->Theta)/th->Theta,MatDeltaFwdSensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 793 } else { 794 ierr = TSComputeDRDUFunction(ts,th->stage_time,ts->vec_sol,ts->vecs_drdu);CHKERRQ(ierr); 795 if (ts->vecs_drdp) { 796 ierr = TSComputeDRDPFunction(ts,th->stage_time,ts->vec_sol,ts->vecs_drdp);CHKERRQ(ierr); 797 } 798 for (ncost=0; ncost<ts->numcost; ncost++) { 799 ierr = MatMultTranspose(ts->mat_sensip,ts->vecs_drdu[ncost],th->VecIntegralSensipTemp);CHKERRQ(ierr); 800 if (ts->vecs_drdp) { 801 ierr = VecAXPY(th->VecIntegralSensipTemp,1,ts->vecs_drdp[ncost]);CHKERRQ(ierr); 802 } 803 ierr = VecAXPY(ts->vecs_integral_sensip[ncost],th->time_step*th->Theta,th->VecIntegralSensipTemp);CHKERRQ(ierr); 804 } 805 } 806 } else { 807 if (!th->endpoint) { 808 ierr = MatAXPY(ts->mat_sensip,1./th->Theta,MatDeltaFwdSensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 809 } 810 } 811 PetscFunctionReturn(0); 812 } 813 814 static PetscErrorCode TSForwardGetStages_Theta(TS ts,PetscInt *ns,Mat **stagesensip) 815 { 816 TS_Theta *th = (TS_Theta*)ts->data; 817 818 PetscFunctionBegin; 819 if (ns) *ns = 1; 820 if (stagesensip) *stagesensip = th->endpoint ? &(th->MatFwdSensip0) : &(th->MatDeltaFwdSensip); 821 PetscFunctionReturn(0); 822 } 823 824 /*------------------------------------------------------------*/ 825 static PetscErrorCode TSReset_Theta(TS ts) 826 { 827 TS_Theta *th = (TS_Theta*)ts->data; 828 PetscErrorCode ierr; 829 830 PetscFunctionBegin; 831 ierr = VecDestroy(&th->X);CHKERRQ(ierr); 832 ierr = VecDestroy(&th->Xdot);CHKERRQ(ierr); 833 ierr = VecDestroy(&th->X0);CHKERRQ(ierr); 834 ierr = VecDestroy(&th->affine);CHKERRQ(ierr); 835 836 ierr = VecDestroy(&th->vec_sol_prev);CHKERRQ(ierr); 837 ierr = VecDestroy(&th->vec_lte_work);CHKERRQ(ierr); 838 839 ierr = VecDestroy(&th->VecCostIntegral0);CHKERRQ(ierr); 840 PetscFunctionReturn(0); 841 } 842 843 static PetscErrorCode TSAdjointReset_Theta(TS ts) 844 { 845 TS_Theta *th = (TS_Theta*)ts->data; 846 PetscErrorCode ierr; 847 848 PetscFunctionBegin; 849 ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaLam);CHKERRQ(ierr); 850 ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaMu);CHKERRQ(ierr); 851 ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaLam2);CHKERRQ(ierr); 852 ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaMu2);CHKERRQ(ierr); 853 ierr = VecDestroyVecs(ts->numcost,&th->VecsSensiTemp);CHKERRQ(ierr); 854 ierr = VecDestroyVecs(ts->numcost,&th->VecsSensi2Temp);CHKERRQ(ierr); 855 PetscFunctionReturn(0); 856 } 857 858 static PetscErrorCode TSDestroy_Theta(TS ts) 859 { 860 PetscErrorCode ierr; 861 862 PetscFunctionBegin; 863 ierr = TSReset_Theta(ts);CHKERRQ(ierr); 864 if (ts->dm) { 865 ierr = DMCoarsenHookRemove(ts->dm,DMCoarsenHook_TSTheta,DMRestrictHook_TSTheta,ts);CHKERRQ(ierr); 866 ierr = DMSubDomainHookRemove(ts->dm,DMSubDomainHook_TSTheta,DMSubDomainRestrictHook_TSTheta,ts);CHKERRQ(ierr); 867 } 868 ierr = PetscFree(ts->data);CHKERRQ(ierr); 869 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetTheta_C",NULL);CHKERRQ(ierr); 870 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetTheta_C",NULL);CHKERRQ(ierr); 871 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetEndpoint_C",NULL);CHKERRQ(ierr); 872 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetEndpoint_C",NULL);CHKERRQ(ierr); 873 PetscFunctionReturn(0); 874 } 875 876 /* 877 This defines the nonlinear equation that is to be solved with SNES 878 G(U) = F[t0+Theta*dt, U, (U-U0)*shift] = 0 879 */ 880 static PetscErrorCode SNESTSFormFunction_Theta(SNES snes,Vec x,Vec y,TS ts) 881 { 882 TS_Theta *th = (TS_Theta*)ts->data; 883 PetscErrorCode ierr; 884 Vec X0,Xdot; 885 DM dm,dmsave; 886 PetscReal shift = 1/(th->Theta*ts->time_step); 887 888 PetscFunctionBegin; 889 ierr = SNESGetDM(snes,&dm);CHKERRQ(ierr); 890 /* When using the endpoint variant, this is actually 1/Theta * Xdot */ 891 ierr = TSThetaGetX0AndXdot(ts,dm,&X0,&Xdot);CHKERRQ(ierr); 892 ierr = VecAXPBYPCZ(Xdot,-shift,shift,0,X0,x);CHKERRQ(ierr); 893 894 /* DM monkey-business allows user code to call TSGetDM() inside of functions evaluated on levels of FAS */ 895 dmsave = ts->dm; 896 ts->dm = dm; 897 ierr = TSComputeIFunction(ts,th->stage_time,x,Xdot,y,PETSC_FALSE);CHKERRQ(ierr); 898 ts->dm = dmsave; 899 ierr = TSThetaRestoreX0AndXdot(ts,dm,&X0,&Xdot);CHKERRQ(ierr); 900 PetscFunctionReturn(0); 901 } 902 903 static PetscErrorCode SNESTSFormJacobian_Theta(SNES snes,Vec x,Mat A,Mat B,TS ts) 904 { 905 TS_Theta *th = (TS_Theta*)ts->data; 906 PetscErrorCode ierr; 907 Vec Xdot; 908 DM dm,dmsave; 909 PetscReal shift = 1/(th->Theta*ts->time_step); 910 911 PetscFunctionBegin; 912 ierr = SNESGetDM(snes,&dm);CHKERRQ(ierr); 913 /* Xdot has already been computed in SNESTSFormFunction_Theta (SNES guarantees this) */ 914 ierr = TSThetaGetX0AndXdot(ts,dm,NULL,&Xdot);CHKERRQ(ierr); 915 916 dmsave = ts->dm; 917 ts->dm = dm; 918 ierr = TSComputeIJacobian(ts,th->stage_time,x,Xdot,shift,A,B,PETSC_FALSE);CHKERRQ(ierr); 919 ts->dm = dmsave; 920 ierr = TSThetaRestoreX0AndXdot(ts,dm,NULL,&Xdot);CHKERRQ(ierr); 921 PetscFunctionReturn(0); 922 } 923 924 static PetscErrorCode TSForwardSetUp_Theta(TS ts) 925 { 926 TS_Theta *th = (TS_Theta*)ts->data; 927 PetscErrorCode ierr; 928 929 PetscFunctionBegin; 930 /* combine sensitivities to parameters and sensitivities to initial values into one array */ 931 th->num_tlm = ts->num_parameters; 932 ierr = MatDuplicate(ts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatDeltaFwdSensip);CHKERRQ(ierr); 933 if (ts->vecs_integral_sensip) { 934 ierr = VecDuplicate(ts->vecs_integral_sensip[0],&th->VecIntegralSensipTemp);CHKERRQ(ierr); 935 } 936 /* backup sensitivity results for roll-backs */ 937 ierr = MatDuplicate(ts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatFwdSensip0);CHKERRQ(ierr); 938 939 if (ts->vecs_integral_sensip) { 940 ierr = VecDuplicateVecs(ts->vecs_integral_sensip[0],ts->numcost,&th->VecsIntegralSensip0);CHKERRQ(ierr); 941 } 942 ierr = VecDuplicate(ts->vec_sol,&th->VecDeltaFwdSensipCol);CHKERRQ(ierr); 943 PetscFunctionReturn(0); 944 } 945 946 static PetscErrorCode TSForwardReset_Theta(TS ts) 947 { 948 TS_Theta *th = (TS_Theta*)ts->data; 949 PetscErrorCode ierr; 950 951 PetscFunctionBegin; 952 if (ts->vecs_integral_sensip) { 953 ierr = VecDestroy(&th->VecIntegralSensipTemp);CHKERRQ(ierr); 954 ierr = VecDestroyVecs(ts->numcost,&th->VecsIntegralSensip0);CHKERRQ(ierr); 955 } 956 ierr = VecDestroy(&th->VecDeltaFwdSensipCol);CHKERRQ(ierr); 957 ierr = MatDestroy(&th->MatDeltaFwdSensip);CHKERRQ(ierr); 958 ierr = MatDestroy(&th->MatFwdSensip0);CHKERRQ(ierr); 959 PetscFunctionReturn(0); 960 } 961 962 static PetscErrorCode TSSetUp_Theta(TS ts) 963 { 964 TS_Theta *th = (TS_Theta*)ts->data; 965 PetscBool match; 966 PetscErrorCode ierr; 967 968 PetscFunctionBegin; 969 if (!th->VecCostIntegral0 && ts->vec_costintegral && ts->costintegralfwd) { /* back up cost integral */ 970 ierr = VecDuplicate(ts->vec_costintegral,&th->VecCostIntegral0);CHKERRQ(ierr); 971 } 972 if (!th->X) { 973 ierr = VecDuplicate(ts->vec_sol,&th->X);CHKERRQ(ierr); 974 } 975 if (!th->Xdot) { 976 ierr = VecDuplicate(ts->vec_sol,&th->Xdot);CHKERRQ(ierr); 977 } 978 if (!th->X0) { 979 ierr = VecDuplicate(ts->vec_sol,&th->X0);CHKERRQ(ierr); 980 } 981 if (th->endpoint) { 982 ierr = VecDuplicate(ts->vec_sol,&th->affine);CHKERRQ(ierr); 983 } 984 985 th->order = (th->Theta == 0.5) ? 2 : 1; 986 987 ierr = TSGetDM(ts,&ts->dm);CHKERRQ(ierr); 988 ierr = DMCoarsenHookAdd(ts->dm,DMCoarsenHook_TSTheta,DMRestrictHook_TSTheta,ts);CHKERRQ(ierr); 989 ierr = DMSubDomainHookAdd(ts->dm,DMSubDomainHook_TSTheta,DMSubDomainRestrictHook_TSTheta,ts);CHKERRQ(ierr); 990 991 ierr = TSGetAdapt(ts,&ts->adapt);CHKERRQ(ierr); 992 ierr = TSAdaptCandidatesClear(ts->adapt);CHKERRQ(ierr); 993 ierr = PetscObjectTypeCompare((PetscObject)ts->adapt,TSADAPTNONE,&match);CHKERRQ(ierr); 994 if (!match) { 995 ierr = VecDuplicate(ts->vec_sol,&th->vec_sol_prev);CHKERRQ(ierr); 996 ierr = VecDuplicate(ts->vec_sol,&th->vec_lte_work);CHKERRQ(ierr); 997 } 998 ierr = TSGetSNES(ts,&ts->snes);CHKERRQ(ierr); 999 PetscFunctionReturn(0); 1000 } 1001 1002 /*------------------------------------------------------------*/ 1003 1004 static PetscErrorCode TSAdjointSetUp_Theta(TS ts) 1005 { 1006 TS_Theta *th = (TS_Theta*)ts->data; 1007 PetscErrorCode ierr; 1008 1009 PetscFunctionBegin; 1010 ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&th->VecsDeltaLam);CHKERRQ(ierr); 1011 ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&th->VecsSensiTemp);CHKERRQ(ierr); 1012 if (ts->vecs_sensip) { 1013 ierr = VecDuplicateVecs(ts->vecs_sensip[0],ts->numcost,&th->VecsDeltaMu);CHKERRQ(ierr); 1014 } 1015 if (ts->vecs_sensi2) { 1016 ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&th->VecsDeltaLam2);CHKERRQ(ierr); 1017 ierr = VecDuplicateVecs(ts->vecs_sensi2[0],ts->numcost,&th->VecsSensi2Temp);CHKERRQ(ierr); 1018 } 1019 if (ts->vecs_sensi2p) { 1020 ierr = VecDuplicateVecs(ts->vecs_sensi2p[0],ts->numcost,&th->VecsDeltaMu2);CHKERRQ(ierr); 1021 } 1022 PetscFunctionReturn(0); 1023 } 1024 1025 static PetscErrorCode TSSetFromOptions_Theta(PetscOptionItems *PetscOptionsObject,TS ts) 1026 { 1027 TS_Theta *th = (TS_Theta*)ts->data; 1028 PetscErrorCode ierr; 1029 1030 PetscFunctionBegin; 1031 ierr = PetscOptionsHead(PetscOptionsObject,"Theta ODE solver options");CHKERRQ(ierr); 1032 { 1033 ierr = PetscOptionsReal("-ts_theta_theta","Location of stage (0<Theta<=1)","TSThetaSetTheta",th->Theta,&th->Theta,NULL);CHKERRQ(ierr); 1034 ierr = PetscOptionsBool("-ts_theta_endpoint","Use the endpoint instead of midpoint form of the Theta method","TSThetaSetEndpoint",th->endpoint,&th->endpoint,NULL);CHKERRQ(ierr); 1035 ierr = PetscOptionsBool("-ts_theta_initial_guess_extrapolate","Extrapolate stage initial guess from previous solution (sometimes unstable)","TSThetaSetExtrapolate",th->extrapolate,&th->extrapolate,NULL);CHKERRQ(ierr); 1036 } 1037 ierr = PetscOptionsTail();CHKERRQ(ierr); 1038 PetscFunctionReturn(0); 1039 } 1040 1041 static PetscErrorCode TSView_Theta(TS ts,PetscViewer viewer) 1042 { 1043 TS_Theta *th = (TS_Theta*)ts->data; 1044 PetscBool iascii; 1045 PetscErrorCode ierr; 1046 1047 PetscFunctionBegin; 1048 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1049 if (iascii) { 1050 ierr = PetscViewerASCIIPrintf(viewer," Theta=%g\n",(double)th->Theta);CHKERRQ(ierr); 1051 ierr = PetscViewerASCIIPrintf(viewer," Extrapolation=%s\n",th->extrapolate ? "yes" : "no");CHKERRQ(ierr); 1052 } 1053 PetscFunctionReturn(0); 1054 } 1055 1056 static PetscErrorCode TSThetaGetTheta_Theta(TS ts,PetscReal *theta) 1057 { 1058 TS_Theta *th = (TS_Theta*)ts->data; 1059 1060 PetscFunctionBegin; 1061 *theta = th->Theta; 1062 PetscFunctionReturn(0); 1063 } 1064 1065 static PetscErrorCode TSThetaSetTheta_Theta(TS ts,PetscReal theta) 1066 { 1067 TS_Theta *th = (TS_Theta*)ts->data; 1068 1069 PetscFunctionBegin; 1070 if (theta <= 0 || 1 < theta) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Theta %g not in range (0,1]",(double)theta); 1071 th->Theta = theta; 1072 th->order = (th->Theta == 0.5) ? 2 : 1; 1073 PetscFunctionReturn(0); 1074 } 1075 1076 static PetscErrorCode TSThetaGetEndpoint_Theta(TS ts,PetscBool *endpoint) 1077 { 1078 TS_Theta *th = (TS_Theta*)ts->data; 1079 1080 PetscFunctionBegin; 1081 *endpoint = th->endpoint; 1082 PetscFunctionReturn(0); 1083 } 1084 1085 static PetscErrorCode TSThetaSetEndpoint_Theta(TS ts,PetscBool flg) 1086 { 1087 TS_Theta *th = (TS_Theta*)ts->data; 1088 1089 PetscFunctionBegin; 1090 th->endpoint = flg; 1091 PetscFunctionReturn(0); 1092 } 1093 1094 #if defined(PETSC_HAVE_COMPLEX) 1095 static PetscErrorCode TSComputeLinearStability_Theta(TS ts,PetscReal xr,PetscReal xi,PetscReal *yr,PetscReal *yi) 1096 { 1097 PetscComplex z = xr + xi*PETSC_i,f; 1098 TS_Theta *th = (TS_Theta*)ts->data; 1099 const PetscReal one = 1.0; 1100 1101 PetscFunctionBegin; 1102 f = (one + (one - th->Theta)*z)/(one - th->Theta*z); 1103 *yr = PetscRealPartComplex(f); 1104 *yi = PetscImaginaryPartComplex(f); 1105 PetscFunctionReturn(0); 1106 } 1107 #endif 1108 1109 static PetscErrorCode TSGetStages_Theta(TS ts,PetscInt *ns,Vec **Y) 1110 { 1111 TS_Theta *th = (TS_Theta*)ts->data; 1112 1113 PetscFunctionBegin; 1114 if (ns) *ns = 1; 1115 if (Y) *Y = th->endpoint ? &(th->X0) : &(th->X); 1116 PetscFunctionReturn(0); 1117 } 1118 1119 /* ------------------------------------------------------------ */ 1120 /*MC 1121 TSTHETA - DAE solver using the implicit Theta method 1122 1123 Level: beginner 1124 1125 Options Database: 1126 + -ts_theta_theta <Theta> - Location of stage (0<Theta<=1) 1127 . -ts_theta_endpoint <flag> - Use the endpoint (like Crank-Nicholson) instead of midpoint form of the Theta method 1128 - -ts_theta_initial_guess_extrapolate <flg> - Extrapolate stage initial guess from previous solution (sometimes unstable) 1129 1130 Notes: 1131 $ -ts_type theta -ts_theta_theta 1.0 corresponds to backward Euler (TSBEULER) 1132 $ -ts_type theta -ts_theta_theta 0.5 corresponds to the implicit midpoint rule 1133 $ -ts_type theta -ts_theta_theta 0.5 -ts_theta_endpoint corresponds to Crank-Nicholson (TSCN) 1134 1135 This method can be applied to DAE. 1136 1137 This method is cast as a 1-stage implicit Runge-Kutta method. 1138 1139 .vb 1140 Theta | Theta 1141 ------------- 1142 | 1 1143 .ve 1144 1145 For the default Theta=0.5, this is also known as the implicit midpoint rule. 1146 1147 When the endpoint variant is chosen, the method becomes a 2-stage method with first stage explicit: 1148 1149 .vb 1150 0 | 0 0 1151 1 | 1-Theta Theta 1152 ------------------- 1153 | 1-Theta Theta 1154 .ve 1155 1156 For the default Theta=0.5, this is the trapezoid rule (also known as Crank-Nicolson, see TSCN). 1157 1158 To apply a diagonally implicit RK method to DAE, the stage formula 1159 1160 $ Y_i = X + h sum_j a_ij Y'_j 1161 1162 is interpreted as a formula for Y'_i in terms of Y_i and known values (Y'_j, j<i) 1163 1164 .seealso: TSCreate(), TS, TSSetType(), TSCN, TSBEULER, TSThetaSetTheta(), TSThetaSetEndpoint() 1165 1166 M*/ 1167 PETSC_EXTERN PetscErrorCode TSCreate_Theta(TS ts) 1168 { 1169 TS_Theta *th; 1170 PetscErrorCode ierr; 1171 1172 PetscFunctionBegin; 1173 ts->ops->reset = TSReset_Theta; 1174 ts->ops->adjointreset = TSAdjointReset_Theta; 1175 ts->ops->destroy = TSDestroy_Theta; 1176 ts->ops->view = TSView_Theta; 1177 ts->ops->setup = TSSetUp_Theta; 1178 ts->ops->adjointsetup = TSAdjointSetUp_Theta; 1179 ts->ops->adjointreset = TSAdjointReset_Theta; 1180 ts->ops->step = TSStep_Theta; 1181 ts->ops->interpolate = TSInterpolate_Theta; 1182 ts->ops->evaluatewlte = TSEvaluateWLTE_Theta; 1183 ts->ops->rollback = TSRollBack_Theta; 1184 ts->ops->setfromoptions = TSSetFromOptions_Theta; 1185 ts->ops->snesfunction = SNESTSFormFunction_Theta; 1186 ts->ops->snesjacobian = SNESTSFormJacobian_Theta; 1187 #if defined(PETSC_HAVE_COMPLEX) 1188 ts->ops->linearstability = TSComputeLinearStability_Theta; 1189 #endif 1190 ts->ops->getstages = TSGetStages_Theta; 1191 ts->ops->adjointstep = TSAdjointStep_Theta; 1192 ts->ops->adjointintegral = TSAdjointCostIntegral_Theta; 1193 ts->ops->forwardintegral = TSForwardCostIntegral_Theta; 1194 ts->default_adapt_type = TSADAPTNONE; 1195 1196 ts->ops->forwardsetup = TSForwardSetUp_Theta; 1197 ts->ops->forwardreset = TSForwardReset_Theta; 1198 ts->ops->forwardstep = TSForwardStep_Theta; 1199 ts->ops->forwardgetstages = TSForwardGetStages_Theta; 1200 1201 ts->usessnes = PETSC_TRUE; 1202 1203 ierr = PetscNewLog(ts,&th);CHKERRQ(ierr); 1204 ts->data = (void*)th; 1205 1206 th->VecsDeltaLam = NULL; 1207 th->VecsDeltaMu = NULL; 1208 th->VecsSensiTemp = NULL; 1209 th->VecsSensi2Temp = NULL; 1210 1211 th->extrapolate = PETSC_FALSE; 1212 th->Theta = 0.5; 1213 th->order = 2; 1214 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetTheta_C",TSThetaGetTheta_Theta);CHKERRQ(ierr); 1215 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetTheta_C",TSThetaSetTheta_Theta);CHKERRQ(ierr); 1216 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetEndpoint_C",TSThetaGetEndpoint_Theta);CHKERRQ(ierr); 1217 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetEndpoint_C",TSThetaSetEndpoint_Theta);CHKERRQ(ierr); 1218 PetscFunctionReturn(0); 1219 } 1220 1221 /*@ 1222 TSThetaGetTheta - Get the abscissa of the stage in (0,1]. 1223 1224 Not Collective 1225 1226 Input Parameter: 1227 . ts - timestepping context 1228 1229 Output Parameter: 1230 . theta - stage abscissa 1231 1232 Note: 1233 Use of this function is normally only required to hack TSTHETA to use a modified integration scheme. 1234 1235 Level: Advanced 1236 1237 .seealso: TSThetaSetTheta() 1238 @*/ 1239 PetscErrorCode TSThetaGetTheta(TS ts,PetscReal *theta) 1240 { 1241 PetscErrorCode ierr; 1242 1243 PetscFunctionBegin; 1244 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1245 PetscValidPointer(theta,2); 1246 ierr = PetscUseMethod(ts,"TSThetaGetTheta_C",(TS,PetscReal*),(ts,theta));CHKERRQ(ierr); 1247 PetscFunctionReturn(0); 1248 } 1249 1250 /*@ 1251 TSThetaSetTheta - Set the abscissa of the stage in (0,1]. 1252 1253 Not Collective 1254 1255 Input Parameter: 1256 + ts - timestepping context 1257 - theta - stage abscissa 1258 1259 Options Database: 1260 . -ts_theta_theta <theta> 1261 1262 Level: Intermediate 1263 1264 .seealso: TSThetaGetTheta() 1265 @*/ 1266 PetscErrorCode TSThetaSetTheta(TS ts,PetscReal theta) 1267 { 1268 PetscErrorCode ierr; 1269 1270 PetscFunctionBegin; 1271 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1272 ierr = PetscTryMethod(ts,"TSThetaSetTheta_C",(TS,PetscReal),(ts,theta));CHKERRQ(ierr); 1273 PetscFunctionReturn(0); 1274 } 1275 1276 /*@ 1277 TSThetaGetEndpoint - Gets whether to use the endpoint variant of the method (e.g. trapezoid/Crank-Nicolson instead of midpoint rule). 1278 1279 Not Collective 1280 1281 Input Parameter: 1282 . ts - timestepping context 1283 1284 Output Parameter: 1285 . endpoint - PETSC_TRUE when using the endpoint variant 1286 1287 Level: Advanced 1288 1289 .seealso: TSThetaSetEndpoint(), TSTHETA, TSCN 1290 @*/ 1291 PetscErrorCode TSThetaGetEndpoint(TS ts,PetscBool *endpoint) 1292 { 1293 PetscErrorCode ierr; 1294 1295 PetscFunctionBegin; 1296 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1297 PetscValidPointer(endpoint,2); 1298 ierr = PetscUseMethod(ts,"TSThetaGetEndpoint_C",(TS,PetscBool*),(ts,endpoint));CHKERRQ(ierr); 1299 PetscFunctionReturn(0); 1300 } 1301 1302 /*@ 1303 TSThetaSetEndpoint - Sets whether to use the endpoint variant of the method (e.g. trapezoid/Crank-Nicolson instead of midpoint rule). 1304 1305 Not Collective 1306 1307 Input Parameter: 1308 + ts - timestepping context 1309 - flg - PETSC_TRUE to use the endpoint variant 1310 1311 Options Database: 1312 . -ts_theta_endpoint <flg> 1313 1314 Level: Intermediate 1315 1316 .seealso: TSTHETA, TSCN 1317 @*/ 1318 PetscErrorCode TSThetaSetEndpoint(TS ts,PetscBool flg) 1319 { 1320 PetscErrorCode ierr; 1321 1322 PetscFunctionBegin; 1323 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1324 ierr = PetscTryMethod(ts,"TSThetaSetEndpoint_C",(TS,PetscBool),(ts,flg));CHKERRQ(ierr); 1325 PetscFunctionReturn(0); 1326 } 1327 1328 /* 1329 * TSBEULER and TSCN are straightforward specializations of TSTHETA. 1330 * The creation functions for these specializations are below. 1331 */ 1332 1333 static PetscErrorCode TSSetUp_BEuler(TS ts) 1334 { 1335 TS_Theta *th = (TS_Theta*)ts->data; 1336 PetscErrorCode ierr; 1337 1338 PetscFunctionBegin; 1339 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"); 1340 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"); 1341 ierr = TSSetUp_Theta(ts);CHKERRQ(ierr); 1342 PetscFunctionReturn(0); 1343 } 1344 1345 static PetscErrorCode TSView_BEuler(TS ts,PetscViewer viewer) 1346 { 1347 PetscFunctionBegin; 1348 PetscFunctionReturn(0); 1349 } 1350 1351 /*MC 1352 TSBEULER - ODE solver using the implicit backward Euler method 1353 1354 Level: beginner 1355 1356 Notes: 1357 TSBEULER is equivalent to TSTHETA with Theta=1.0 1358 1359 $ -ts_type theta -ts_theta_theta 1.0 1360 1361 .seealso: TSCreate(), TS, TSSetType(), TSEULER, TSCN, TSTHETA 1362 1363 M*/ 1364 PETSC_EXTERN PetscErrorCode TSCreate_BEuler(TS ts) 1365 { 1366 PetscErrorCode ierr; 1367 1368 PetscFunctionBegin; 1369 ierr = TSCreate_Theta(ts);CHKERRQ(ierr); 1370 ierr = TSThetaSetTheta(ts,1.0);CHKERRQ(ierr); 1371 ierr = TSThetaSetEndpoint(ts,PETSC_FALSE);CHKERRQ(ierr); 1372 ts->ops->setup = TSSetUp_BEuler; 1373 ts->ops->view = TSView_BEuler; 1374 PetscFunctionReturn(0); 1375 } 1376 1377 static PetscErrorCode TSSetUp_CN(TS ts) 1378 { 1379 TS_Theta *th = (TS_Theta*)ts->data; 1380 PetscErrorCode ierr; 1381 1382 PetscFunctionBegin; 1383 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"); 1384 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"); 1385 ierr = TSSetUp_Theta(ts);CHKERRQ(ierr); 1386 PetscFunctionReturn(0); 1387 } 1388 1389 static PetscErrorCode TSView_CN(TS ts,PetscViewer viewer) 1390 { 1391 PetscFunctionBegin; 1392 PetscFunctionReturn(0); 1393 } 1394 1395 /*MC 1396 TSCN - ODE solver using the implicit Crank-Nicolson method. 1397 1398 Level: beginner 1399 1400 Notes: 1401 TSCN is equivalent to TSTHETA with Theta=0.5 and the "endpoint" option set. I.e. 1402 1403 $ -ts_type theta -ts_theta_theta 0.5 -ts_theta_endpoint 1404 1405 .seealso: TSCreate(), TS, TSSetType(), TSBEULER, TSTHETA 1406 1407 M*/ 1408 PETSC_EXTERN PetscErrorCode TSCreate_CN(TS ts) 1409 { 1410 PetscErrorCode ierr; 1411 1412 PetscFunctionBegin; 1413 ierr = TSCreate_Theta(ts);CHKERRQ(ierr); 1414 ierr = TSThetaSetTheta(ts,0.5);CHKERRQ(ierr); 1415 ierr = TSThetaSetEndpoint(ts,PETSC_TRUE);CHKERRQ(ierr); 1416 ts->ops->setup = TSSetUp_CN; 1417 ts->ops->view = TSView_CN; 1418 PetscFunctionReturn(0); 1419 } 1420