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 stage solution, u^n + dt a_{11} k_1, and time derivative u^{n+1}_t */ 13 Vec affine; /* Affine vector needed for residual at beginning of step in endpoint formulation */ 14 PetscReal Theta; 15 PetscReal shift; /* Shift parameter for SNES Jacobian, used by forward, TLM and adjoint */ 16 PetscInt order; 17 PetscBool endpoint; 18 PetscBool extrapolate; 19 TSStepStatus status; 20 Vec VecCostIntegral0; /* Backup for roll-backs due to events, used by cost integral */ 21 PetscReal ptime0; /* Backup for ts->ptime, the start time of current time step, used by TLM and cost integral */ 22 PetscReal time_step0; /* Backup for ts->timestep, the step size of current time step, used by TLM and cost integral*/ 23 24 /* context for sensitivity analysis */ 25 PetscInt num_tlm; /* Total number of tangent linear equations */ 26 Vec *VecsDeltaLam; /* Increment of the adjoint sensitivity w.r.t IC at stage */ 27 Vec *VecsDeltaMu; /* Increment of the adjoint sensitivity w.r.t P at stage */ 28 Vec *VecsSensiTemp; /* Vector to be multiplied with Jacobian transpose */ 29 Mat MatDeltaFwdSensip; /* Increment of the forward sensitivity at stage */ 30 Vec VecDeltaFwdSensipCol; /* Working vector for holding one column of the sensitivity matrix */ 31 Mat MatFwdSensip0; /* backup for roll-backs due to events */ 32 Mat MatIntegralSensipTemp; /* Working vector for forward integral sensitivity */ 33 Mat MatIntegralSensip0; /* backup for roll-backs due to events */ 34 Vec *VecsDeltaLam2; /* Increment of the 2nd-order adjoint sensitivity w.r.t IC at stage */ 35 Vec *VecsDeltaMu2; /* Increment of the 2nd-order adjoint sensitivity w.r.t P at stage */ 36 Vec *VecsSensi2Temp; /* Working vectors that holds the residual for the second-order adjoint */ 37 Vec *VecsAffine; /* Working vectors to store residuals */ 38 /* context for error estimation */ 39 Vec vec_sol_prev; 40 Vec vec_lte_work; 41 } TS_Theta; 42 43 static PetscErrorCode TSThetaGetX0AndXdot(TS ts,DM dm,Vec *X0,Vec *Xdot) 44 { 45 TS_Theta *th = (TS_Theta*)ts->data; 46 PetscErrorCode ierr; 47 48 PetscFunctionBegin; 49 if (X0) { 50 if (dm && dm != ts->dm) { 51 ierr = DMGetNamedGlobalVector(dm,"TSTheta_X0",X0);CHKERRQ(ierr); 52 } else *X0 = ts->vec_sol; 53 } 54 if (Xdot) { 55 if (dm && dm != ts->dm) { 56 ierr = DMGetNamedGlobalVector(dm,"TSTheta_Xdot",Xdot);CHKERRQ(ierr); 57 } else *Xdot = th->Xdot; 58 } 59 PetscFunctionReturn(0); 60 } 61 62 static PetscErrorCode TSThetaRestoreX0AndXdot(TS ts,DM dm,Vec *X0,Vec *Xdot) 63 { 64 PetscErrorCode ierr; 65 66 PetscFunctionBegin; 67 if (X0) { 68 if (dm && dm != ts->dm) { 69 ierr = DMRestoreNamedGlobalVector(dm,"TSTheta_X0",X0);CHKERRQ(ierr); 70 } 71 } 72 if (Xdot) { 73 if (dm && dm != ts->dm) { 74 ierr = DMRestoreNamedGlobalVector(dm,"TSTheta_Xdot",Xdot);CHKERRQ(ierr); 75 } 76 } 77 PetscFunctionReturn(0); 78 } 79 80 static PetscErrorCode DMCoarsenHook_TSTheta(DM fine,DM coarse,void *ctx) 81 { 82 PetscFunctionBegin; 83 PetscFunctionReturn(0); 84 } 85 86 static PetscErrorCode DMRestrictHook_TSTheta(DM fine,Mat restrct,Vec rscale,Mat inject,DM coarse,void *ctx) 87 { 88 TS ts = (TS)ctx; 89 PetscErrorCode ierr; 90 Vec X0,Xdot,X0_c,Xdot_c; 91 92 PetscFunctionBegin; 93 ierr = TSThetaGetX0AndXdot(ts,fine,&X0,&Xdot);CHKERRQ(ierr); 94 ierr = TSThetaGetX0AndXdot(ts,coarse,&X0_c,&Xdot_c);CHKERRQ(ierr); 95 ierr = MatRestrict(restrct,X0,X0_c);CHKERRQ(ierr); 96 ierr = MatRestrict(restrct,Xdot,Xdot_c);CHKERRQ(ierr); 97 ierr = VecPointwiseMult(X0_c,rscale,X0_c);CHKERRQ(ierr); 98 ierr = VecPointwiseMult(Xdot_c,rscale,Xdot_c);CHKERRQ(ierr); 99 ierr = TSThetaRestoreX0AndXdot(ts,fine,&X0,&Xdot);CHKERRQ(ierr); 100 ierr = TSThetaRestoreX0AndXdot(ts,coarse,&X0_c,&Xdot_c);CHKERRQ(ierr); 101 PetscFunctionReturn(0); 102 } 103 104 static PetscErrorCode DMSubDomainHook_TSTheta(DM dm,DM subdm,void *ctx) 105 { 106 PetscFunctionBegin; 107 PetscFunctionReturn(0); 108 } 109 110 static PetscErrorCode DMSubDomainRestrictHook_TSTheta(DM dm,VecScatter gscat,VecScatter lscat,DM subdm,void *ctx) 111 { 112 TS ts = (TS)ctx; 113 PetscErrorCode ierr; 114 Vec X0,Xdot,X0_sub,Xdot_sub; 115 116 PetscFunctionBegin; 117 ierr = TSThetaGetX0AndXdot(ts,dm,&X0,&Xdot);CHKERRQ(ierr); 118 ierr = TSThetaGetX0AndXdot(ts,subdm,&X0_sub,&Xdot_sub);CHKERRQ(ierr); 119 120 ierr = VecScatterBegin(gscat,X0,X0_sub,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 121 ierr = VecScatterEnd(gscat,X0,X0_sub,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 122 123 ierr = VecScatterBegin(gscat,Xdot,Xdot_sub,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 124 ierr = VecScatterEnd(gscat,Xdot,Xdot_sub,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 125 126 ierr = TSThetaRestoreX0AndXdot(ts,dm,&X0,&Xdot);CHKERRQ(ierr); 127 ierr = TSThetaRestoreX0AndXdot(ts,subdm,&X0_sub,&Xdot_sub);CHKERRQ(ierr); 128 PetscFunctionReturn(0); 129 } 130 131 static PetscErrorCode TSThetaEvaluateCostIntegral(TS ts) 132 { 133 TS_Theta *th = (TS_Theta*)ts->data; 134 TS quadts = ts->quadraturets; 135 PetscErrorCode ierr; 136 137 PetscFunctionBegin; 138 if (th->endpoint) { 139 /* Evolve ts->vec_costintegral to compute integrals */ 140 if (th->Theta!=1.0) { 141 ierr = TSComputeRHSFunction(quadts,th->ptime0,th->X0,ts->vec_costintegrand);CHKERRQ(ierr); 142 ierr = VecAXPY(quadts->vec_sol,th->time_step0*(1.0-th->Theta),ts->vec_costintegrand);CHKERRQ(ierr); 143 } 144 ierr = TSComputeRHSFunction(quadts,ts->ptime,ts->vec_sol,ts->vec_costintegrand);CHKERRQ(ierr); 145 ierr = VecAXPY(quadts->vec_sol,th->time_step0*th->Theta,ts->vec_costintegrand);CHKERRQ(ierr); 146 } else { 147 ierr = TSComputeRHSFunction(quadts,th->stage_time,th->X,ts->vec_costintegrand);CHKERRQ(ierr); 148 ierr = VecAXPY(quadts->vec_sol,th->time_step0,ts->vec_costintegrand);CHKERRQ(ierr); 149 } 150 PetscFunctionReturn(0); 151 } 152 153 static PetscErrorCode TSForwardCostIntegral_Theta(TS ts) 154 { 155 TS_Theta *th = (TS_Theta*)ts->data; 156 TS quadts = ts->quadraturets; 157 PetscErrorCode ierr; 158 159 PetscFunctionBegin; 160 /* backup cost integral */ 161 ierr = VecCopy(quadts->vec_sol,th->VecCostIntegral0);CHKERRQ(ierr); 162 ierr = TSThetaEvaluateCostIntegral(ts);CHKERRQ(ierr); 163 PetscFunctionReturn(0); 164 } 165 166 static PetscErrorCode TSAdjointCostIntegral_Theta(TS ts) 167 { 168 TS_Theta *th = (TS_Theta*)ts->data; 169 PetscErrorCode ierr; 170 171 PetscFunctionBegin; 172 /* Like TSForwardCostIntegral(), the adjoint cost integral evaluation relies on ptime0 and time_step0. */ 173 th->ptime0 = ts->ptime + ts->time_step; 174 th->time_step0 = -ts->time_step; 175 ierr = TSThetaEvaluateCostIntegral(ts);CHKERRQ(ierr); 176 PetscFunctionReturn(0); 177 } 178 179 static PetscErrorCode TSTheta_SNESSolve(TS ts,Vec b,Vec x) 180 { 181 PetscInt nits,lits; 182 PetscErrorCode ierr; 183 184 PetscFunctionBegin; 185 ierr = SNESSolve(ts->snes,b,x);CHKERRQ(ierr); 186 ierr = SNESGetIterationNumber(ts->snes,&nits);CHKERRQ(ierr); 187 ierr = SNESGetLinearSolveIterations(ts->snes,&lits);CHKERRQ(ierr); 188 ts->snes_its += nits; ts->ksp_its += lits; 189 PetscFunctionReturn(0); 190 } 191 192 static PetscErrorCode TSStep_Theta(TS ts) 193 { 194 TS_Theta *th = (TS_Theta*)ts->data; 195 PetscInt rejections = 0; 196 PetscBool stageok,accept = PETSC_TRUE; 197 PetscReal next_time_step = ts->time_step; 198 PetscErrorCode ierr; 199 200 PetscFunctionBegin; 201 if (!ts->steprollback) { 202 if (th->vec_sol_prev) { ierr = VecCopy(th->X0,th->vec_sol_prev);CHKERRQ(ierr); } 203 ierr = VecCopy(ts->vec_sol,th->X0);CHKERRQ(ierr); 204 } 205 206 th->status = TS_STEP_INCOMPLETE; 207 while (!ts->reason && th->status != TS_STEP_COMPLETE) { 208 th->shift = 1/(th->Theta*ts->time_step); 209 th->stage_time = ts->ptime + (th->endpoint ? (PetscReal)1 : th->Theta)*ts->time_step; 210 ierr = VecCopy(th->X0,th->X);CHKERRQ(ierr); 211 if (th->extrapolate && !ts->steprestart) { 212 ierr = VecAXPY(th->X,1/th->shift,th->Xdot);CHKERRQ(ierr); 213 } 214 if (th->endpoint) { /* This formulation assumes linear time-independent mass matrix */ 215 if (!th->affine) {ierr = VecDuplicate(ts->vec_sol,&th->affine);CHKERRQ(ierr);} 216 ierr = VecZeroEntries(th->Xdot);CHKERRQ(ierr); 217 ierr = TSComputeIFunction(ts,ts->ptime,th->X0,th->Xdot,th->affine,PETSC_FALSE);CHKERRQ(ierr); 218 ierr = VecScale(th->affine,(th->Theta-1)/th->Theta);CHKERRQ(ierr); 219 } else if (th->affine) { /* Just in case th->endpoint is changed between calls to TSStep_Theta() */ 220 ierr = VecZeroEntries(th->affine);CHKERRQ(ierr); 221 } 222 ierr = TSPreStage(ts,th->stage_time);CHKERRQ(ierr); 223 ierr = TSTheta_SNESSolve(ts,th->affine,th->X);CHKERRQ(ierr); 224 ierr = TSPostStage(ts,th->stage_time,0,&th->X);CHKERRQ(ierr); 225 ierr = TSAdaptCheckStage(ts->adapt,ts,th->stage_time,th->X,&stageok);CHKERRQ(ierr); 226 if (!stageok) goto reject_step; 227 228 th->status = TS_STEP_PENDING; 229 if (th->endpoint) { 230 ierr = VecCopy(th->X,ts->vec_sol);CHKERRQ(ierr); 231 } else { 232 ierr = VecAXPBYPCZ(th->Xdot,-th->shift,th->shift,0,th->X0,th->X);CHKERRQ(ierr); 233 ierr = VecAXPY(ts->vec_sol,ts->time_step,th->Xdot);CHKERRQ(ierr); 234 } 235 ierr = TSAdaptChoose(ts->adapt,ts,ts->time_step,NULL,&next_time_step,&accept);CHKERRQ(ierr); 236 th->status = accept ? TS_STEP_COMPLETE : TS_STEP_INCOMPLETE; 237 if (!accept) { 238 ierr = VecCopy(th->X0,ts->vec_sol);CHKERRQ(ierr); 239 ts->time_step = next_time_step; 240 goto reject_step; 241 } 242 243 if (ts->forward_solve || ts->costintegralfwd) { /* Save the info for the later use in cost integral evaluation */ 244 th->ptime0 = ts->ptime; 245 th->time_step0 = ts->time_step; 246 } 247 ts->ptime += ts->time_step; 248 ts->time_step = next_time_step; 249 break; 250 251 reject_step: 252 ts->reject++; accept = PETSC_FALSE; 253 if (!ts->reason && ++rejections > ts->max_reject && ts->max_reject >= 0) { 254 ts->reason = TS_DIVERGED_STEP_REJECTED; 255 ierr = PetscInfo2(ts,"Step=%D, step rejections %D greater than current TS allowed, stopping solve\n",ts->steps,rejections);CHKERRQ(ierr); 256 } 257 } 258 PetscFunctionReturn(0); 259 } 260 261 static PetscErrorCode TSAdjointStepBEuler_Private(TS ts) 262 { 263 TS_Theta *th = (TS_Theta*)ts->data; 264 TS quadts = ts->quadraturets; 265 Vec *VecsDeltaLam = th->VecsDeltaLam,*VecsDeltaMu = th->VecsDeltaMu,*VecsSensiTemp = th->VecsSensiTemp; 266 Vec *VecsDeltaLam2 = th->VecsDeltaLam2,*VecsDeltaMu2 = th->VecsDeltaMu2,*VecsSensi2Temp = th->VecsSensi2Temp; 267 PetscInt nadj; 268 Mat J,Jpre,quadJ = NULL,quadJp = NULL; 269 KSP ksp; 270 PetscScalar *xarr; 271 TSEquationType eqtype; 272 PetscBool isexplicitode = PETSC_FALSE; 273 PetscReal adjoint_time_step; 274 PetscErrorCode ierr; 275 276 PetscFunctionBegin; 277 ierr = TSGetEquationType(ts,&eqtype);CHKERRQ(ierr); 278 if (eqtype == TS_EQ_ODE_EXPLICIT) { 279 isexplicitode = PETSC_TRUE; 280 VecsDeltaLam = ts->vecs_sensi; 281 VecsDeltaLam2 = ts->vecs_sensi2; 282 } 283 th->status = TS_STEP_INCOMPLETE; 284 ierr = SNESGetKSP(ts->snes,&ksp);CHKERRQ(ierr); 285 ierr = TSGetIJacobian(ts,&J,&Jpre,NULL,NULL);CHKERRQ(ierr); 286 if (quadts) { 287 ierr = TSGetRHSJacobian(quadts,&quadJ,NULL,NULL,NULL);CHKERRQ(ierr); 288 ierr = TSGetRHSJacobianP(quadts,&quadJp,NULL,NULL);CHKERRQ(ierr); 289 } 290 291 th->stage_time = ts->ptime; 292 adjoint_time_step = -ts->time_step; /* always positive since time_step is negative */ 293 294 /* Build RHS for first-order adjoint lambda_{n+1}/h + r_u^T(n+1) */ 295 if (quadts) { 296 ierr = TSComputeRHSJacobian(quadts,th->stage_time,ts->vec_sol,quadJ,NULL);CHKERRQ(ierr); 297 } 298 299 for (nadj=0; nadj<ts->numcost; nadj++) { 300 ierr = VecCopy(ts->vecs_sensi[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr); 301 ierr = VecScale(VecsSensiTemp[nadj],1./adjoint_time_step);CHKERRQ(ierr); /* lambda_{n+1}/h */ 302 if (quadJ) { 303 ierr = MatDenseGetColumn(quadJ,nadj,&xarr);CHKERRQ(ierr); 304 ierr = VecPlaceArray(ts->vec_drdu_col,xarr);CHKERRQ(ierr); 305 ierr = VecAXPY(VecsSensiTemp[nadj],1.,ts->vec_drdu_col);CHKERRQ(ierr); 306 ierr = VecResetArray(ts->vec_drdu_col);CHKERRQ(ierr); 307 ierr = MatDenseRestoreColumn(quadJ,&xarr);CHKERRQ(ierr); 308 } 309 } 310 311 /* Build LHS for first-order adjoint */ 312 th->shift = 1./adjoint_time_step; 313 ierr = TSComputeSNESJacobian(ts,ts->vec_sol,J,Jpre);CHKERRQ(ierr); 314 ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr); 315 316 /* Solve stage equation LHS*lambda_s = RHS for first-order adjoint */ 317 for (nadj=0; nadj<ts->numcost; nadj++) { 318 KSPConvergedReason kspreason; 319 ierr = KSPSolveTranspose(ksp,VecsSensiTemp[nadj],VecsDeltaLam[nadj]);CHKERRQ(ierr); 320 ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); 321 if (kspreason < 0) { 322 ts->reason = TSADJOINT_DIVERGED_LINEAR_SOLVE; 323 ierr = PetscInfo2(ts,"Step=%D, %Dth cost function, transposed linear solve fails, stopping 1st-order adjoint solve\n",ts->steps,nadj);CHKERRQ(ierr); 324 } 325 } 326 327 if (ts->vecs_sensi2) { /* U_{n+1} */ 328 /* Get w1 at t_{n+1} from TLM matrix */ 329 ierr = MatDenseGetColumn(ts->mat_sensip,0,&xarr);CHKERRQ(ierr); 330 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 331 /* lambda_s^T F_UU w_1 */ 332 ierr = TSComputeIHessianProductFunctionUU(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fuu);CHKERRQ(ierr); 333 /* lambda_s^T F_UP w_2 */ 334 ierr = TSComputeIHessianProductFunctionUP(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_dir,ts->vecs_fup);CHKERRQ(ierr); 335 for (nadj=0; nadj<ts->numcost; nadj++) { /* compute the residual */ 336 ierr = VecCopy(ts->vecs_sensi2[nadj],VecsSensi2Temp[nadj]);CHKERRQ(ierr); 337 ierr = VecScale(VecsSensi2Temp[nadj],1./adjoint_time_step);CHKERRQ(ierr); 338 ierr = VecAXPY(VecsSensi2Temp[nadj],-1.,ts->vecs_fuu[nadj]);CHKERRQ(ierr); 339 if (ts->vecs_fup) { 340 ierr = VecAXPY(VecsSensi2Temp[nadj],-1.,ts->vecs_fup[nadj]);CHKERRQ(ierr); 341 } 342 } 343 /* Solve stage equation LHS X = RHS for second-order adjoint */ 344 for (nadj=0; nadj<ts->numcost; nadj++) { 345 KSPConvergedReason kspreason; 346 ierr = KSPSolveTranspose(ksp,VecsSensi2Temp[nadj],VecsDeltaLam2[nadj]);CHKERRQ(ierr); 347 ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); 348 if (kspreason < 0) { 349 ts->reason = TSADJOINT_DIVERGED_LINEAR_SOLVE; 350 ierr = PetscInfo2(ts,"Step=%D, %Dth cost function, transposed linear solve fails, stopping 2nd-order adjoint solve\n",ts->steps,nadj);CHKERRQ(ierr); 351 } 352 } 353 } 354 355 /* Update sensitivities, and evaluate integrals if there is any */ 356 if (!isexplicitode) { 357 th->shift = 0.0; 358 ierr = TSComputeSNESJacobian(ts,ts->vec_sol,J,Jpre);CHKERRQ(ierr); 359 ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr); 360 ierr = MatScale(J,-1.);CHKERRQ(ierr); 361 for (nadj=0; nadj<ts->numcost; nadj++) { 362 /* Add f_U \lambda_s to the original RHS */ 363 ierr = MatMultTransposeAdd(J,VecsDeltaLam[nadj],VecsSensiTemp[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr); 364 ierr = VecScale(VecsSensiTemp[nadj],adjoint_time_step);CHKERRQ(ierr); 365 ierr = VecCopy(VecsSensiTemp[nadj],ts->vecs_sensi[nadj]);CHKERRQ(ierr); 366 if (ts->vecs_sensi2) { 367 ierr = MatMultTransposeAdd(J,VecsDeltaLam2[nadj],VecsSensi2Temp[nadj],VecsSensi2Temp[nadj]);CHKERRQ(ierr); 368 ierr = VecScale(VecsSensi2Temp[nadj],adjoint_time_step);CHKERRQ(ierr); 369 ierr = VecCopy(VecsSensi2Temp[nadj],ts->vecs_sensi2[nadj]);CHKERRQ(ierr); 370 } 371 } 372 } 373 if (ts->vecs_sensip) { 374 ierr = VecAXPBYPCZ(th->Xdot,-1./adjoint_time_step,1.0/adjoint_time_step,0,th->X0,ts->vec_sol);CHKERRQ(ierr); 375 ierr = TSComputeIJacobianP(ts,th->stage_time,ts->vec_sol,th->Xdot,1./adjoint_time_step,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); /* get -f_p */ 376 if (quadts) { 377 ierr = TSComputeRHSJacobianP(quadts,th->stage_time,ts->vec_sol,quadJp);CHKERRQ(ierr); 378 } 379 if (ts->vecs_sensi2p) { 380 /* lambda_s^T F_PU w_1 */ 381 ierr = TSComputeIHessianProductFunctionPU(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fpu);CHKERRQ(ierr); 382 /* lambda_s^T F_PP w_2 */ 383 ierr = TSComputeIHessianProductFunctionPP(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_dir,ts->vecs_fpp);CHKERRQ(ierr); 384 } 385 386 for (nadj=0; nadj<ts->numcost; nadj++) { 387 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr); 388 ierr = VecAXPY(ts->vecs_sensip[nadj],-adjoint_time_step,VecsDeltaMu[nadj]);CHKERRQ(ierr); 389 if (quadJp) { 390 ierr = MatDenseGetColumn(quadJp,nadj,&xarr);CHKERRQ(ierr); 391 ierr = VecPlaceArray(ts->vec_drdp_col,xarr);CHKERRQ(ierr); 392 ierr = VecAXPY(ts->vecs_sensip[nadj],adjoint_time_step,ts->vec_drdp_col);CHKERRQ(ierr); 393 ierr = VecResetArray(ts->vec_drdp_col);CHKERRQ(ierr); 394 ierr = MatDenseRestoreColumn(quadJp,&xarr);CHKERRQ(ierr); 395 } 396 if (ts->vecs_sensi2p) { 397 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam2[nadj],VecsDeltaMu2[nadj]);CHKERRQ(ierr); 398 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step,VecsDeltaMu2[nadj]);CHKERRQ(ierr); 399 if (ts->vecs_fpu) { 400 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step,ts->vecs_fpu[nadj]);CHKERRQ(ierr); 401 } 402 if (ts->vecs_fpp) { 403 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step,ts->vecs_fpp[nadj]);CHKERRQ(ierr); 404 } 405 } 406 } 407 } 408 409 if (ts->vecs_sensi2) { 410 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 411 ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr); 412 } 413 th->status = TS_STEP_COMPLETE; 414 PetscFunctionReturn(0); 415 } 416 417 static PetscErrorCode TSAdjointStep_Theta(TS ts) 418 { 419 TS_Theta *th = (TS_Theta*)ts->data; 420 TS quadts = ts->quadraturets; 421 Vec *VecsDeltaLam = th->VecsDeltaLam,*VecsDeltaMu = th->VecsDeltaMu,*VecsSensiTemp = th->VecsSensiTemp; 422 Vec *VecsDeltaLam2 = th->VecsDeltaLam2,*VecsDeltaMu2 = th->VecsDeltaMu2,*VecsSensi2Temp = th->VecsSensi2Temp; 423 PetscInt nadj; 424 Mat J,Jpre,quadJ = NULL,quadJp = NULL; 425 KSP ksp; 426 PetscScalar *xarr; 427 PetscReal adjoint_time_step; 428 PetscReal adjoint_ptime; /* end time of the adjoint time step (ts->ptime is the start time, ususally ts->ptime is larger than adjoint_ptime) */ 429 PetscErrorCode ierr; 430 431 PetscFunctionBegin; 432 if (th->Theta == 1.) { 433 ierr = TSAdjointStepBEuler_Private(ts);CHKERRQ(ierr); 434 PetscFunctionReturn(0); 435 } 436 th->status = TS_STEP_INCOMPLETE; 437 ierr = SNESGetKSP(ts->snes,&ksp);CHKERRQ(ierr); 438 ierr = TSGetIJacobian(ts,&J,&Jpre,NULL,NULL);CHKERRQ(ierr); 439 if (quadts) { 440 ierr = TSGetRHSJacobian(quadts,&quadJ,NULL,NULL,NULL);CHKERRQ(ierr); 441 ierr = TSGetRHSJacobianP(quadts,&quadJp,NULL,NULL);CHKERRQ(ierr); 442 } 443 /* If endpoint=1, th->ptime and th->X0 will be used; if endpoint=0, th->stage_time and th->X will be used. */ 444 th->stage_time = th->endpoint ? ts->ptime : (ts->ptime+(1.-th->Theta)*ts->time_step); 445 adjoint_ptime = ts->ptime + ts->time_step; 446 adjoint_time_step = -ts->time_step; /* always positive since time_step is negative */ 447 448 if (!th->endpoint) { 449 ierr = VecAXPBYPCZ(th->X,1.0-th->Theta,th->Theta,0,th->X0,ts->vec_sol);CHKERRQ(ierr); 450 } 451 452 /* Build RHS for first-order adjoint */ 453 /* Cost function has an integral term */ 454 if (quadts) { 455 if (th->endpoint) { 456 ierr = TSComputeRHSJacobian(quadts,th->stage_time,ts->vec_sol,quadJ,NULL);CHKERRQ(ierr); 457 } else { 458 ierr = TSComputeRHSJacobian(quadts,th->stage_time,th->X,quadJ,NULL);CHKERRQ(ierr); 459 } 460 } 461 462 for (nadj=0; nadj<ts->numcost; nadj++) { 463 ierr = VecCopy(ts->vecs_sensi[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr); 464 ierr = VecScale(VecsSensiTemp[nadj],1./(th->Theta*adjoint_time_step));CHKERRQ(ierr); 465 if (quadJ) { 466 ierr = MatDenseGetColumn(quadJ,nadj,&xarr);CHKERRQ(ierr); 467 ierr = VecPlaceArray(ts->vec_drdu_col,xarr);CHKERRQ(ierr); 468 ierr = VecAXPY(VecsSensiTemp[nadj],1.,ts->vec_drdu_col);CHKERRQ(ierr); 469 ierr = VecResetArray(ts->vec_drdu_col);CHKERRQ(ierr); 470 ierr = MatDenseRestoreColumn(quadJ,&xarr);CHKERRQ(ierr); 471 } 472 } 473 474 /* Build LHS for first-order adjoint */ 475 th->shift = 1./(th->Theta*adjoint_time_step); 476 if (th->endpoint) { 477 ierr = TSComputeSNESJacobian(ts,ts->vec_sol,J,Jpre);CHKERRQ(ierr); 478 } else { 479 ierr = TSComputeSNESJacobian(ts,th->X,J,Jpre);CHKERRQ(ierr); 480 } 481 ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr); 482 483 /* Solve stage equation LHS*lambda_s = RHS for first-order adjoint */ 484 for (nadj=0; nadj<ts->numcost; nadj++) { 485 KSPConvergedReason kspreason; 486 ierr = KSPSolveTranspose(ksp,VecsSensiTemp[nadj],VecsDeltaLam[nadj]);CHKERRQ(ierr); 487 ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); 488 if (kspreason < 0) { 489 ts->reason = TSADJOINT_DIVERGED_LINEAR_SOLVE; 490 ierr = PetscInfo2(ts,"Step=%D, %Dth cost function, transposed linear solve fails, stopping 1st-order adjoint solve\n",ts->steps,nadj);CHKERRQ(ierr); 491 } 492 } 493 494 /* Second-order adjoint */ 495 if (ts->vecs_sensi2) { /* U_{n+1} */ 496 if (!th->endpoint) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Operation not implemented in TS_Theta"); 497 /* Get w1 at t_{n+1} from TLM matrix */ 498 ierr = MatDenseGetColumn(ts->mat_sensip,0,&xarr);CHKERRQ(ierr); 499 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 500 /* lambda_s^T F_UU w_1 */ 501 ierr = TSComputeIHessianProductFunctionUU(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fuu);CHKERRQ(ierr); 502 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 503 ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr); 504 /* lambda_s^T F_UP w_2 */ 505 ierr = TSComputeIHessianProductFunctionUP(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_dir,ts->vecs_fup);CHKERRQ(ierr); 506 for (nadj=0; nadj<ts->numcost; nadj++) { /* compute the residual */ 507 ierr = VecCopy(ts->vecs_sensi2[nadj],VecsSensi2Temp[nadj]);CHKERRQ(ierr); 508 ierr = VecScale(VecsSensi2Temp[nadj],th->shift);CHKERRQ(ierr); 509 ierr = VecAXPY(VecsSensi2Temp[nadj],-1.,ts->vecs_fuu[nadj]);CHKERRQ(ierr); 510 if (ts->vecs_fup) { 511 ierr = VecAXPY(VecsSensi2Temp[nadj],-1.,ts->vecs_fup[nadj]);CHKERRQ(ierr); 512 } 513 } 514 /* Solve stage equation LHS X = RHS for second-order adjoint */ 515 for (nadj=0; nadj<ts->numcost; nadj++) { 516 KSPConvergedReason kspreason; 517 ierr = KSPSolveTranspose(ksp,VecsSensi2Temp[nadj],VecsDeltaLam2[nadj]);CHKERRQ(ierr); 518 ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); 519 if (kspreason < 0) { 520 ts->reason = TSADJOINT_DIVERGED_LINEAR_SOLVE; 521 ierr = PetscInfo2(ts,"Step=%D, %Dth cost function, transposed linear solve fails, stopping 2nd-order adjoint solve\n",ts->steps,nadj);CHKERRQ(ierr); 522 } 523 } 524 } 525 526 /* Update sensitivities, and evaluate integrals if there is any */ 527 if (th->endpoint) { /* two-stage Theta methods with th->Theta!=1, th->Theta==1 leads to BEuler */ 528 th->shift = 1./((th->Theta-1.)*adjoint_time_step); 529 th->stage_time = adjoint_ptime; 530 ierr = TSComputeSNESJacobian(ts,th->X0,J,Jpre);CHKERRQ(ierr); 531 ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr); 532 /* R_U at t_n */ 533 if (quadts) { 534 ierr = TSComputeRHSJacobian(quadts,adjoint_ptime,th->X0,quadJ,NULL);CHKERRQ(ierr); 535 } 536 for (nadj=0; nadj<ts->numcost; nadj++) { 537 ierr = MatMultTranspose(J,VecsDeltaLam[nadj],ts->vecs_sensi[nadj]);CHKERRQ(ierr); 538 if (quadJ) { 539 ierr = MatDenseGetColumn(quadJ,nadj,&xarr);CHKERRQ(ierr); 540 ierr = VecPlaceArray(ts->vec_drdu_col,xarr);CHKERRQ(ierr); 541 ierr = VecAXPY(ts->vecs_sensi[nadj],-1.,ts->vec_drdu_col);CHKERRQ(ierr); 542 ierr = VecResetArray(ts->vec_drdu_col);CHKERRQ(ierr); 543 ierr = MatDenseRestoreColumn(quadJ,&xarr);CHKERRQ(ierr); 544 } 545 ierr = VecScale(ts->vecs_sensi[nadj],1./th->shift);CHKERRQ(ierr); 546 } 547 548 /* Second-order adjoint */ 549 if (ts->vecs_sensi2) { /* U_n */ 550 /* Get w1 at t_n from TLM matrix */ 551 ierr = MatDenseGetColumn(th->MatFwdSensip0,0,&xarr);CHKERRQ(ierr); 552 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 553 /* lambda_s^T F_UU w_1 */ 554 ierr = TSComputeIHessianProductFunctionUU(ts,adjoint_ptime,th->X0,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fuu);CHKERRQ(ierr); 555 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 556 ierr = MatDenseRestoreColumn(th->MatFwdSensip0,&xarr);CHKERRQ(ierr); 557 /* lambda_s^T F_UU w_2 */ 558 ierr = TSComputeIHessianProductFunctionUP(ts,adjoint_ptime,th->X0,VecsDeltaLam,ts->vec_dir,ts->vecs_fup);CHKERRQ(ierr); 559 for (nadj=0; nadj<ts->numcost; nadj++) { 560 /* 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 */ 561 ierr = MatMultTranspose(J,VecsDeltaLam2[nadj],ts->vecs_sensi2[nadj]);CHKERRQ(ierr); 562 ierr = VecAXPY(ts->vecs_sensi2[nadj],1.,ts->vecs_fuu[nadj]);CHKERRQ(ierr); 563 if (ts->vecs_fup) { 564 ierr = VecAXPY(ts->vecs_sensi2[nadj],1.,ts->vecs_fup[nadj]);CHKERRQ(ierr); 565 } 566 ierr = VecScale(ts->vecs_sensi2[nadj],1./th->shift);CHKERRQ(ierr); 567 } 568 } 569 570 th->stage_time = ts->ptime; /* recover the old value */ 571 572 if (ts->vecs_sensip) { /* sensitivities wrt parameters */ 573 /* U_{n+1} */ 574 th->shift = 1.0/(adjoint_time_step*th->Theta); 575 ierr = VecAXPBYPCZ(th->Xdot,-th->shift,th->shift,0,th->X0,ts->vec_sol);CHKERRQ(ierr); 576 ierr = TSComputeIJacobianP(ts,th->stage_time,ts->vec_sol,th->Xdot,-1./(th->Theta*adjoint_time_step),ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 577 if (quadts) { 578 ierr = TSComputeRHSJacobianP(quadts,th->stage_time,ts->vec_sol,quadJp);CHKERRQ(ierr); 579 } 580 for (nadj=0; nadj<ts->numcost; nadj++) { 581 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr); 582 ierr = VecAXPY(ts->vecs_sensip[nadj],-adjoint_time_step*th->Theta,VecsDeltaMu[nadj]);CHKERRQ(ierr); 583 if (quadJp) { 584 ierr = MatDenseGetColumn(quadJp,nadj,&xarr);CHKERRQ(ierr); 585 ierr = VecPlaceArray(ts->vec_drdp_col,xarr);CHKERRQ(ierr); 586 ierr = VecAXPY(ts->vecs_sensip[nadj],adjoint_time_step*th->Theta,ts->vec_drdp_col);CHKERRQ(ierr); 587 ierr = VecResetArray(ts->vec_drdp_col);CHKERRQ(ierr); 588 ierr = MatDenseRestoreColumn(quadJp,&xarr);CHKERRQ(ierr); 589 } 590 } 591 if (ts->vecs_sensi2p) { /* second-order */ 592 /* Get w1 at t_{n+1} from TLM matrix */ 593 ierr = MatDenseGetColumn(ts->mat_sensip,0,&xarr);CHKERRQ(ierr); 594 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 595 /* lambda_s^T F_PU w_1 */ 596 ierr = TSComputeIHessianProductFunctionPU(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fpu);CHKERRQ(ierr); 597 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 598 ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr); 599 600 /* lambda_s^T F_PP w_2 */ 601 ierr = TSComputeIHessianProductFunctionPP(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_dir,ts->vecs_fpp);CHKERRQ(ierr); 602 for (nadj=0; nadj<ts->numcost; nadj++) { 603 /* 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) */ 604 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam2[nadj],VecsDeltaMu2[nadj]);CHKERRQ(ierr); 605 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step*th->Theta,VecsDeltaMu2[nadj]);CHKERRQ(ierr); 606 if (ts->vecs_fpu) { 607 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step*th->Theta,ts->vecs_fpu[nadj]);CHKERRQ(ierr); 608 } 609 if (ts->vecs_fpp) { 610 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step*th->Theta,ts->vecs_fpp[nadj]);CHKERRQ(ierr); 611 } 612 } 613 } 614 615 /* U_s */ 616 ierr = VecZeroEntries(th->Xdot);CHKERRQ(ierr); 617 ierr = TSComputeIJacobianP(ts,adjoint_ptime,th->X0,th->Xdot,1./((th->Theta-1.0)*adjoint_time_step),ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 618 if (quadts) { 619 ierr = TSComputeRHSJacobianP(quadts,adjoint_ptime,th->X0,quadJp);CHKERRQ(ierr); 620 } 621 for (nadj=0; nadj<ts->numcost; nadj++) { 622 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr); 623 ierr = VecAXPY(ts->vecs_sensip[nadj],-adjoint_time_step*(1.0-th->Theta),VecsDeltaMu[nadj]);CHKERRQ(ierr); 624 if (quadJp) { 625 ierr = MatDenseGetColumn(quadJp,nadj,&xarr);CHKERRQ(ierr); 626 ierr = VecPlaceArray(ts->vec_drdp_col,xarr);CHKERRQ(ierr); 627 ierr = VecAXPY(ts->vecs_sensip[nadj],adjoint_time_step*(1.0-th->Theta),ts->vec_drdp_col);CHKERRQ(ierr); 628 ierr = VecResetArray(ts->vec_drdp_col);CHKERRQ(ierr); 629 ierr = MatDenseRestoreColumn(quadJp,&xarr);CHKERRQ(ierr); 630 } 631 if (ts->vecs_sensi2p) { /* second-order */ 632 /* Get w1 at t_n from TLM matrix */ 633 ierr = MatDenseGetColumn(th->MatFwdSensip0,0,&xarr);CHKERRQ(ierr); 634 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 635 /* lambda_s^T F_PU w_1 */ 636 ierr = TSComputeIHessianProductFunctionPU(ts,adjoint_ptime,th->X0,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fpu);CHKERRQ(ierr); 637 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 638 ierr = MatDenseRestoreColumn(th->MatFwdSensip0,&xarr);CHKERRQ(ierr); 639 /* lambda_s^T F_PP w_2 */ 640 ierr = TSComputeIHessianProductFunctionPP(ts,adjoint_ptime,th->X0,VecsDeltaLam,ts->vec_dir,ts->vecs_fpp);CHKERRQ(ierr); 641 for (nadj=0; nadj<ts->numcost; nadj++) { 642 /* 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) */ 643 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam2[nadj],VecsDeltaMu2[nadj]);CHKERRQ(ierr); 644 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step*(1.0-th->Theta),VecsDeltaMu2[nadj]);CHKERRQ(ierr); 645 if (ts->vecs_fpu) { 646 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step*(1.0-th->Theta),ts->vecs_fpu[nadj]);CHKERRQ(ierr); 647 } 648 if (ts->vecs_fpp) { 649 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step*(1.0-th->Theta),ts->vecs_fpp[nadj]);CHKERRQ(ierr); 650 } 651 } 652 } 653 } 654 } 655 } else { /* one-stage case */ 656 th->shift = 0.0; 657 ierr = TSComputeSNESJacobian(ts,th->X,J,Jpre);CHKERRQ(ierr); /* get -f_y */ 658 ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr); 659 if (quadts) { 660 ierr = TSComputeRHSJacobian(quadts,th->stage_time,th->X,quadJ,NULL);CHKERRQ(ierr); 661 } 662 for (nadj=0; nadj<ts->numcost; nadj++) { 663 ierr = MatMultTranspose(J,VecsDeltaLam[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr); 664 ierr = VecAXPY(ts->vecs_sensi[nadj],-adjoint_time_step,VecsSensiTemp[nadj]);CHKERRQ(ierr); 665 if (quadJ) { 666 ierr = MatDenseGetColumn(quadJ,nadj,&xarr);CHKERRQ(ierr); 667 ierr = VecPlaceArray(ts->vec_drdu_col,xarr);CHKERRQ(ierr); 668 ierr = VecAXPY(ts->vecs_sensi[nadj],adjoint_time_step,ts->vec_drdu_col);CHKERRQ(ierr); 669 ierr = VecResetArray(ts->vec_drdu_col);CHKERRQ(ierr); 670 ierr = MatDenseRestoreColumn(quadJ,&xarr);CHKERRQ(ierr); 671 } 672 } 673 if (ts->vecs_sensip) { 674 th->shift = 1.0/(adjoint_time_step*th->Theta); 675 ierr = VecAXPBYPCZ(th->Xdot,-th->shift,th->shift,0,th->X0,th->X);CHKERRQ(ierr); 676 ierr = TSComputeIJacobianP(ts,th->stage_time,th->X,th->Xdot,th->shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 677 if (quadts) { 678 ierr = TSComputeRHSJacobianP(quadts,th->stage_time,th->X,quadJp);CHKERRQ(ierr); 679 } 680 for (nadj=0; nadj<ts->numcost; nadj++) { 681 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr); 682 ierr = VecAXPY(ts->vecs_sensip[nadj],-adjoint_time_step,VecsDeltaMu[nadj]);CHKERRQ(ierr); 683 if (quadJp) { 684 ierr = MatDenseGetColumn(quadJp,nadj,&xarr);CHKERRQ(ierr); 685 ierr = VecPlaceArray(ts->vec_drdp_col,xarr);CHKERRQ(ierr); 686 ierr = VecAXPY(ts->vecs_sensip[nadj],adjoint_time_step,ts->vec_drdp_col);CHKERRQ(ierr); 687 ierr = VecResetArray(ts->vec_drdp_col);CHKERRQ(ierr); 688 ierr = MatDenseRestoreColumn(quadJp,&xarr);CHKERRQ(ierr); 689 } 690 } 691 } 692 } 693 694 th->status = TS_STEP_COMPLETE; 695 PetscFunctionReturn(0); 696 } 697 698 static PetscErrorCode TSInterpolate_Theta(TS ts,PetscReal t,Vec X) 699 { 700 TS_Theta *th = (TS_Theta*)ts->data; 701 PetscReal dt = t - ts->ptime; 702 PetscErrorCode ierr; 703 704 PetscFunctionBegin; 705 ierr = VecCopy(ts->vec_sol,th->X);CHKERRQ(ierr); 706 if (th->endpoint) dt *= th->Theta; 707 ierr = VecWAXPY(X,dt,th->Xdot,th->X);CHKERRQ(ierr); 708 PetscFunctionReturn(0); 709 } 710 711 static PetscErrorCode TSEvaluateWLTE_Theta(TS ts,NormType wnormtype,PetscInt *order,PetscReal *wlte) 712 { 713 TS_Theta *th = (TS_Theta*)ts->data; 714 Vec X = ts->vec_sol; /* X = solution */ 715 Vec Y = th->vec_lte_work; /* Y = X + LTE */ 716 PetscReal wltea,wlter; 717 PetscErrorCode ierr; 718 719 PetscFunctionBegin; 720 if (!th->vec_sol_prev) {*wlte = -1; PetscFunctionReturn(0);} 721 /* Cannot compute LTE in first step or in restart after event */ 722 if (ts->steprestart) {*wlte = -1; PetscFunctionReturn(0);} 723 /* Compute LTE using backward differences with non-constant time step */ 724 { 725 PetscReal h = ts->time_step, h_prev = ts->ptime - ts->ptime_prev; 726 PetscReal a = 1 + h_prev/h; 727 PetscScalar scal[3]; Vec vecs[3]; 728 scal[0] = +1/a; scal[1] = -1/(a-1); scal[2] = +1/(a*(a-1)); 729 vecs[0] = X; vecs[1] = th->X0; vecs[2] = th->vec_sol_prev; 730 ierr = VecCopy(X,Y);CHKERRQ(ierr); 731 ierr = VecMAXPY(Y,3,scal,vecs);CHKERRQ(ierr); 732 ierr = TSErrorWeightedNorm(ts,X,Y,wnormtype,wlte,&wltea,&wlter);CHKERRQ(ierr); 733 } 734 if (order) *order = 2; 735 PetscFunctionReturn(0); 736 } 737 738 static PetscErrorCode TSRollBack_Theta(TS ts) 739 { 740 TS_Theta *th = (TS_Theta*)ts->data; 741 TS quadts = ts->quadraturets; 742 PetscErrorCode ierr; 743 744 PetscFunctionBegin; 745 ierr = VecCopy(th->X0,ts->vec_sol);CHKERRQ(ierr); 746 if (quadts && ts->costintegralfwd) { 747 ierr = VecCopy(th->VecCostIntegral0,quadts->vec_sol);CHKERRQ(ierr); 748 } 749 th->status = TS_STEP_INCOMPLETE; 750 if (ts->mat_sensip) { 751 ierr = MatCopy(th->MatFwdSensip0,ts->mat_sensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 752 } 753 if (quadts && quadts->mat_sensip) { 754 ierr = MatCopy(th->MatIntegralSensip0,quadts->mat_sensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 755 } 756 PetscFunctionReturn(0); 757 } 758 759 static PetscErrorCode TSForwardStep_Theta(TS ts) 760 { 761 TS_Theta *th = (TS_Theta*)ts->data; 762 TS quadts = ts->quadraturets; 763 Mat MatDeltaFwdSensip = th->MatDeltaFwdSensip; 764 Vec VecDeltaFwdSensipCol = th->VecDeltaFwdSensipCol; 765 PetscInt ntlm; 766 KSP ksp; 767 Mat J,Jpre,quadJ = NULL,quadJp = NULL; 768 PetscScalar *barr,*xarr; 769 PetscReal previous_shift; 770 PetscErrorCode ierr; 771 772 PetscFunctionBegin; 773 previous_shift = th->shift; 774 ierr = MatCopy(ts->mat_sensip,th->MatFwdSensip0,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 775 776 if (quadts && quadts->mat_sensip) { 777 ierr = MatCopy(quadts->mat_sensip,th->MatIntegralSensip0,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 778 } 779 ierr = SNESGetKSP(ts->snes,&ksp);CHKERRQ(ierr); 780 ierr = TSGetIJacobian(ts,&J,&Jpre,NULL,NULL);CHKERRQ(ierr); 781 if (quadts) { 782 ierr = TSGetRHSJacobian(quadts,&quadJ,NULL,NULL,NULL);CHKERRQ(ierr); 783 ierr = TSGetRHSJacobianP(quadts,&quadJp,NULL,NULL);CHKERRQ(ierr); 784 } 785 786 /* Build RHS */ 787 if (th->endpoint) { /* 2-stage method*/ 788 th->shift = 1./((th->Theta-1.)*th->time_step0); 789 ierr = TSComputeIJacobian(ts,th->ptime0,th->X0,th->Xdot,th->shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr); 790 ierr = MatMatMult(J,ts->mat_sensip,MAT_REUSE_MATRIX,PETSC_DEFAULT,&MatDeltaFwdSensip);CHKERRQ(ierr); 791 ierr = MatScale(MatDeltaFwdSensip,(th->Theta-1.)/th->Theta);CHKERRQ(ierr); 792 793 /* Add the f_p forcing terms */ 794 if (ts->Jacp) { 795 ierr = VecZeroEntries(th->Xdot);CHKERRQ(ierr); 796 ierr = TSComputeIJacobianP(ts,th->ptime0,th->X0,th->Xdot,th->shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 797 ierr = MatAXPY(MatDeltaFwdSensip,(th->Theta-1.)/th->Theta,ts->Jacp,SUBSET_NONZERO_PATTERN);CHKERRQ(ierr); 798 th->shift = previous_shift; 799 ierr = VecAXPBYPCZ(th->Xdot,-th->shift,th->shift,0,th->X0,ts->vec_sol);CHKERRQ(ierr); 800 ierr = TSComputeIJacobianP(ts,th->stage_time,ts->vec_sol,th->Xdot,th->shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 801 ierr = MatAXPY(MatDeltaFwdSensip,-1.,ts->Jacp,SUBSET_NONZERO_PATTERN);CHKERRQ(ierr); 802 } 803 } else { /* 1-stage method */ 804 th->shift = 0.0; 805 ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,th->shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr); 806 ierr = MatMatMult(J,ts->mat_sensip,MAT_REUSE_MATRIX,PETSC_DEFAULT,&MatDeltaFwdSensip);CHKERRQ(ierr); 807 ierr = MatScale(MatDeltaFwdSensip,-1.);CHKERRQ(ierr); 808 809 /* Add the f_p forcing terms */ 810 if (ts->Jacp) { 811 th->shift = previous_shift; 812 ierr = VecAXPBYPCZ(th->Xdot,-th->shift,th->shift,0,th->X0,th->X);CHKERRQ(ierr); 813 ierr = TSComputeIJacobianP(ts,th->stage_time,th->X,th->Xdot,th->shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 814 ierr = MatAXPY(MatDeltaFwdSensip,-1.,ts->Jacp,SUBSET_NONZERO_PATTERN);CHKERRQ(ierr); 815 } 816 } 817 818 /* Build LHS */ 819 th->shift = previous_shift; /* recover the previous shift used in TSStep_Theta() */ 820 if (th->endpoint) { 821 ierr = TSComputeIJacobian(ts,th->stage_time,ts->vec_sol,th->Xdot,th->shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr); 822 } else { 823 ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,th->shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr); 824 } 825 ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr); 826 827 /* 828 Evaluate the first stage of integral gradients with the 2-stage method: 829 drdu|t_n*S(t_n) + drdp|t_n 830 This is done before the linear solve because the sensitivity variable S(t_n) will be propagated to S(t_{n+1}) 831 */ 832 if (th->endpoint) { /* 2-stage method only */ 833 if (quadts && quadts->mat_sensip) { 834 ierr = TSComputeRHSJacobian(quadts,th->ptime0,th->X0,quadJ,NULL);CHKERRQ(ierr); 835 ierr = TSComputeRHSJacobianP(quadts,th->ptime0,th->X0,quadJp);CHKERRQ(ierr); 836 ierr = MatTransposeMatMult(ts->mat_sensip,quadJ,MAT_REUSE_MATRIX,PETSC_DEFAULT,&th->MatIntegralSensipTemp);CHKERRQ(ierr); 837 ierr = MatAXPY(th->MatIntegralSensipTemp,1,quadJp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 838 ierr = MatAXPY(quadts->mat_sensip,th->time_step0*(1.-th->Theta),th->MatIntegralSensipTemp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 839 } 840 } 841 842 /* Solve the tangent linear equation for forward sensitivities to parameters */ 843 for (ntlm=0; ntlm<th->num_tlm; ntlm++) { 844 KSPConvergedReason kspreason; 845 ierr = MatDenseGetColumn(MatDeltaFwdSensip,ntlm,&barr);CHKERRQ(ierr); 846 ierr = VecPlaceArray(VecDeltaFwdSensipCol,barr);CHKERRQ(ierr); 847 if (th->endpoint) { 848 ierr = MatDenseGetColumn(ts->mat_sensip,ntlm,&xarr);CHKERRQ(ierr); 849 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 850 ierr = KSPSolve(ksp,VecDeltaFwdSensipCol,ts->vec_sensip_col);CHKERRQ(ierr); 851 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 852 ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr); 853 } else { 854 ierr = KSPSolve(ksp,VecDeltaFwdSensipCol,VecDeltaFwdSensipCol);CHKERRQ(ierr); 855 } 856 ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); 857 if (kspreason < 0) { 858 ts->reason = TSFORWARD_DIVERGED_LINEAR_SOLVE; 859 ierr = PetscInfo2(ts,"Step=%D, %Dth tangent linear solve, linear solve fails, stopping tangent linear solve\n",ts->steps,ntlm);CHKERRQ(ierr); 860 } 861 ierr = VecResetArray(VecDeltaFwdSensipCol);CHKERRQ(ierr); 862 ierr = MatDenseRestoreColumn(MatDeltaFwdSensip,&barr);CHKERRQ(ierr); 863 } 864 865 /* 866 Evaluate the second stage of integral gradients with the 2-stage method: 867 drdu|t_{n+1}*S(t_{n+1}) + drdp|t_{n+1} 868 */ 869 if (quadts && quadts->mat_sensip) { 870 if (!th->endpoint) { 871 ierr = MatAXPY(ts->mat_sensip,1,MatDeltaFwdSensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); /* stage sensitivity */ 872 ierr = TSComputeRHSJacobian(quadts,th->stage_time,th->X,quadJ,NULL);CHKERRQ(ierr); 873 ierr = TSComputeRHSJacobianP(quadts,th->stage_time,th->X,quadJp);CHKERRQ(ierr); 874 ierr = MatTransposeMatMult(ts->mat_sensip,quadJ,MAT_REUSE_MATRIX,PETSC_DEFAULT,&th->MatIntegralSensipTemp);CHKERRQ(ierr); 875 ierr = MatAXPY(th->MatIntegralSensipTemp,1,quadJp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 876 ierr = MatAXPY(quadts->mat_sensip,th->time_step0,th->MatIntegralSensipTemp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 877 ierr = MatAXPY(ts->mat_sensip,(1.-th->Theta)/th->Theta,MatDeltaFwdSensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 878 } else { 879 ierr = TSComputeRHSJacobian(quadts,th->stage_time,ts->vec_sol,quadJ,NULL);CHKERRQ(ierr); 880 ierr = TSComputeRHSJacobianP(quadts,th->stage_time,ts->vec_sol,quadJp);CHKERRQ(ierr); 881 ierr = MatTransposeMatMult(ts->mat_sensip,quadJ,MAT_REUSE_MATRIX,PETSC_DEFAULT,&th->MatIntegralSensipTemp);CHKERRQ(ierr); 882 ierr = MatAXPY(th->MatIntegralSensipTemp,1,quadJp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 883 ierr = MatAXPY(quadts->mat_sensip,th->time_step0*th->Theta,th->MatIntegralSensipTemp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 884 } 885 } else { 886 if (!th->endpoint) { 887 ierr = MatAXPY(ts->mat_sensip,1./th->Theta,MatDeltaFwdSensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 888 } 889 } 890 PetscFunctionReturn(0); 891 } 892 893 static PetscErrorCode TSForwardGetStages_Theta(TS ts,PetscInt *ns,Mat **stagesensip) 894 { 895 TS_Theta *th = (TS_Theta*)ts->data; 896 897 PetscFunctionBegin; 898 if (ns) *ns = 1; 899 if (stagesensip) *stagesensip = th->endpoint ? &(th->MatFwdSensip0) : &(th->MatDeltaFwdSensip); 900 PetscFunctionReturn(0); 901 } 902 903 /*------------------------------------------------------------*/ 904 static PetscErrorCode TSReset_Theta(TS ts) 905 { 906 TS_Theta *th = (TS_Theta*)ts->data; 907 PetscErrorCode ierr; 908 909 PetscFunctionBegin; 910 ierr = VecDestroy(&th->X);CHKERRQ(ierr); 911 ierr = VecDestroy(&th->Xdot);CHKERRQ(ierr); 912 ierr = VecDestroy(&th->X0);CHKERRQ(ierr); 913 ierr = VecDestroy(&th->affine);CHKERRQ(ierr); 914 915 ierr = VecDestroy(&th->vec_sol_prev);CHKERRQ(ierr); 916 ierr = VecDestroy(&th->vec_lte_work);CHKERRQ(ierr); 917 918 ierr = VecDestroy(&th->VecCostIntegral0);CHKERRQ(ierr); 919 PetscFunctionReturn(0); 920 } 921 922 static PetscErrorCode TSAdjointReset_Theta(TS ts) 923 { 924 TS_Theta *th = (TS_Theta*)ts->data; 925 PetscErrorCode ierr; 926 927 PetscFunctionBegin; 928 ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaLam);CHKERRQ(ierr); 929 ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaMu);CHKERRQ(ierr); 930 ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaLam2);CHKERRQ(ierr); 931 ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaMu2);CHKERRQ(ierr); 932 ierr = VecDestroyVecs(ts->numcost,&th->VecsSensiTemp);CHKERRQ(ierr); 933 ierr = VecDestroyVecs(ts->numcost,&th->VecsSensi2Temp);CHKERRQ(ierr); 934 PetscFunctionReturn(0); 935 } 936 937 static PetscErrorCode TSDestroy_Theta(TS ts) 938 { 939 PetscErrorCode ierr; 940 941 PetscFunctionBegin; 942 ierr = TSReset_Theta(ts);CHKERRQ(ierr); 943 if (ts->dm) { 944 ierr = DMCoarsenHookRemove(ts->dm,DMCoarsenHook_TSTheta,DMRestrictHook_TSTheta,ts);CHKERRQ(ierr); 945 ierr = DMSubDomainHookRemove(ts->dm,DMSubDomainHook_TSTheta,DMSubDomainRestrictHook_TSTheta,ts);CHKERRQ(ierr); 946 } 947 ierr = PetscFree(ts->data);CHKERRQ(ierr); 948 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetTheta_C",NULL);CHKERRQ(ierr); 949 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetTheta_C",NULL);CHKERRQ(ierr); 950 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetEndpoint_C",NULL);CHKERRQ(ierr); 951 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetEndpoint_C",NULL);CHKERRQ(ierr); 952 PetscFunctionReturn(0); 953 } 954 955 /* 956 This defines the nonlinear equation that is to be solved with SNES 957 G(U) = F[t0+Theta*dt, U, (U-U0)*shift] = 0 958 959 Note that U here is the stage argument. This means that U = U_{n+1} only if endpoint = true, 960 otherwise U = theta U_{n+1} + (1 - theta) U0, which for the case of implicit midpoint is 961 U = (U_{n+1} + U0)/2 962 */ 963 static PetscErrorCode SNESTSFormFunction_Theta(SNES snes,Vec x,Vec y,TS ts) 964 { 965 TS_Theta *th = (TS_Theta*)ts->data; 966 PetscErrorCode ierr; 967 Vec X0,Xdot; 968 DM dm,dmsave; 969 PetscReal shift = th->shift; 970 971 PetscFunctionBegin; 972 ierr = SNESGetDM(snes,&dm);CHKERRQ(ierr); 973 /* When using the endpoint variant, this is actually 1/Theta * Xdot */ 974 ierr = TSThetaGetX0AndXdot(ts,dm,&X0,&Xdot);CHKERRQ(ierr); 975 if (x != X0) { 976 ierr = VecAXPBYPCZ(Xdot,-shift,shift,0,X0,x);CHKERRQ(ierr); 977 } else { 978 ierr = VecZeroEntries(Xdot);CHKERRQ(ierr); 979 } 980 /* DM monkey-business allows user code to call TSGetDM() inside of functions evaluated on levels of FAS */ 981 dmsave = ts->dm; 982 ts->dm = dm; 983 ierr = TSComputeIFunction(ts,th->stage_time,x,Xdot,y,PETSC_FALSE);CHKERRQ(ierr); 984 ts->dm = dmsave; 985 ierr = TSThetaRestoreX0AndXdot(ts,dm,&X0,&Xdot);CHKERRQ(ierr); 986 PetscFunctionReturn(0); 987 } 988 989 static PetscErrorCode SNESTSFormJacobian_Theta(SNES snes,Vec x,Mat A,Mat B,TS ts) 990 { 991 TS_Theta *th = (TS_Theta*)ts->data; 992 PetscErrorCode ierr; 993 Vec Xdot; 994 DM dm,dmsave; 995 PetscReal shift = th->shift; 996 997 PetscFunctionBegin; 998 ierr = SNESGetDM(snes,&dm);CHKERRQ(ierr); 999 /* Xdot has already been computed in SNESTSFormFunction_Theta (SNES guarantees this) */ 1000 ierr = TSThetaGetX0AndXdot(ts,dm,NULL,&Xdot);CHKERRQ(ierr); 1001 1002 dmsave = ts->dm; 1003 ts->dm = dm; 1004 ierr = TSComputeIJacobian(ts,th->stage_time,x,Xdot,shift,A,B,PETSC_FALSE);CHKERRQ(ierr); 1005 ts->dm = dmsave; 1006 ierr = TSThetaRestoreX0AndXdot(ts,dm,NULL,&Xdot);CHKERRQ(ierr); 1007 PetscFunctionReturn(0); 1008 } 1009 1010 static PetscErrorCode TSForwardSetUp_Theta(TS ts) 1011 { 1012 TS_Theta *th = (TS_Theta*)ts->data; 1013 TS quadts = ts->quadraturets; 1014 PetscErrorCode ierr; 1015 1016 PetscFunctionBegin; 1017 /* combine sensitivities to parameters and sensitivities to initial values into one array */ 1018 th->num_tlm = ts->num_parameters; 1019 ierr = MatDuplicate(ts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatDeltaFwdSensip);CHKERRQ(ierr); 1020 if (quadts && quadts->mat_sensip) { 1021 ierr = MatDuplicate(quadts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatIntegralSensipTemp);CHKERRQ(ierr); 1022 ierr = MatDuplicate(quadts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatIntegralSensip0);CHKERRQ(ierr); 1023 } 1024 /* backup sensitivity results for roll-backs */ 1025 ierr = MatDuplicate(ts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatFwdSensip0);CHKERRQ(ierr); 1026 1027 ierr = VecDuplicate(ts->vec_sol,&th->VecDeltaFwdSensipCol);CHKERRQ(ierr); 1028 PetscFunctionReturn(0); 1029 } 1030 1031 static PetscErrorCode TSForwardReset_Theta(TS ts) 1032 { 1033 TS_Theta *th = (TS_Theta*)ts->data; 1034 TS quadts = ts->quadraturets; 1035 PetscErrorCode ierr; 1036 1037 PetscFunctionBegin; 1038 if (quadts && quadts->mat_sensip) { 1039 ierr = MatDestroy(&th->MatIntegralSensipTemp);CHKERRQ(ierr); 1040 ierr = MatDestroy(&th->MatIntegralSensip0);CHKERRQ(ierr); 1041 } 1042 ierr = VecDestroy(&th->VecDeltaFwdSensipCol);CHKERRQ(ierr); 1043 ierr = MatDestroy(&th->MatDeltaFwdSensip);CHKERRQ(ierr); 1044 ierr = MatDestroy(&th->MatFwdSensip0);CHKERRQ(ierr); 1045 PetscFunctionReturn(0); 1046 } 1047 1048 static PetscErrorCode TSSetUp_Theta(TS ts) 1049 { 1050 TS_Theta *th = (TS_Theta*)ts->data; 1051 TS quadts = ts->quadraturets; 1052 PetscBool match; 1053 PetscErrorCode ierr; 1054 1055 PetscFunctionBegin; 1056 if (!th->VecCostIntegral0 && quadts && ts->costintegralfwd) { /* back up cost integral */ 1057 ierr = VecDuplicate(quadts->vec_sol,&th->VecCostIntegral0);CHKERRQ(ierr); 1058 } 1059 if (!th->X) { 1060 ierr = VecDuplicate(ts->vec_sol,&th->X);CHKERRQ(ierr); 1061 } 1062 if (!th->Xdot) { 1063 ierr = VecDuplicate(ts->vec_sol,&th->Xdot);CHKERRQ(ierr); 1064 } 1065 if (!th->X0) { 1066 ierr = VecDuplicate(ts->vec_sol,&th->X0);CHKERRQ(ierr); 1067 } 1068 if (th->endpoint) { 1069 ierr = VecDuplicate(ts->vec_sol,&th->affine);CHKERRQ(ierr); 1070 } 1071 1072 th->order = (th->Theta == 0.5) ? 2 : 1; 1073 th->shift = 1/(th->Theta*ts->time_step); 1074 1075 ierr = TSGetDM(ts,&ts->dm);CHKERRQ(ierr); 1076 ierr = DMCoarsenHookAdd(ts->dm,DMCoarsenHook_TSTheta,DMRestrictHook_TSTheta,ts);CHKERRQ(ierr); 1077 ierr = DMSubDomainHookAdd(ts->dm,DMSubDomainHook_TSTheta,DMSubDomainRestrictHook_TSTheta,ts);CHKERRQ(ierr); 1078 1079 ierr = TSGetAdapt(ts,&ts->adapt);CHKERRQ(ierr); 1080 ierr = TSAdaptCandidatesClear(ts->adapt);CHKERRQ(ierr); 1081 ierr = PetscObjectTypeCompare((PetscObject)ts->adapt,TSADAPTNONE,&match);CHKERRQ(ierr); 1082 if (!match) { 1083 ierr = VecDuplicate(ts->vec_sol,&th->vec_sol_prev);CHKERRQ(ierr); 1084 ierr = VecDuplicate(ts->vec_sol,&th->vec_lte_work);CHKERRQ(ierr); 1085 } 1086 ierr = TSGetSNES(ts,&ts->snes);CHKERRQ(ierr); 1087 PetscFunctionReturn(0); 1088 } 1089 1090 /*------------------------------------------------------------*/ 1091 1092 static PetscErrorCode TSAdjointSetUp_Theta(TS ts) 1093 { 1094 TS_Theta *th = (TS_Theta*)ts->data; 1095 PetscErrorCode ierr; 1096 1097 PetscFunctionBegin; 1098 ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&th->VecsDeltaLam);CHKERRQ(ierr); 1099 ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&th->VecsSensiTemp);CHKERRQ(ierr); 1100 if (ts->vecs_sensip) { 1101 ierr = VecDuplicateVecs(ts->vecs_sensip[0],ts->numcost,&th->VecsDeltaMu);CHKERRQ(ierr); 1102 } 1103 if (ts->vecs_sensi2) { 1104 ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&th->VecsDeltaLam2);CHKERRQ(ierr); 1105 ierr = VecDuplicateVecs(ts->vecs_sensi2[0],ts->numcost,&th->VecsSensi2Temp);CHKERRQ(ierr); 1106 /* hack ts to make implicit TS solver work when users provide only explicit versions of callbacks (RHSFunction,RHSJacobian,RHSHessian etc.) */ 1107 if (!ts->ihessianproduct_fuu) ts->vecs_fuu = ts->vecs_guu; 1108 if (!ts->ihessianproduct_fup) ts->vecs_fup = ts->vecs_gup; 1109 } 1110 if (ts->vecs_sensi2p) { 1111 ierr = VecDuplicateVecs(ts->vecs_sensi2p[0],ts->numcost,&th->VecsDeltaMu2);CHKERRQ(ierr); 1112 /* hack ts to make implicit TS solver work when users provide only explicit versions of callbacks (RHSFunction,RHSJacobian,RHSHessian etc.) */ 1113 if (!ts->ihessianproduct_fpu) ts->vecs_fpu = ts->vecs_gpu; 1114 if (!ts->ihessianproduct_fpp) ts->vecs_fpp = ts->vecs_gpp; 1115 } 1116 PetscFunctionReturn(0); 1117 } 1118 1119 static PetscErrorCode TSSetFromOptions_Theta(PetscOptionItems *PetscOptionsObject,TS ts) 1120 { 1121 TS_Theta *th = (TS_Theta*)ts->data; 1122 PetscErrorCode ierr; 1123 1124 PetscFunctionBegin; 1125 ierr = PetscOptionsHead(PetscOptionsObject,"Theta ODE solver options");CHKERRQ(ierr); 1126 { 1127 ierr = PetscOptionsReal("-ts_theta_theta","Location of stage (0<Theta<=1)","TSThetaSetTheta",th->Theta,&th->Theta,NULL);CHKERRQ(ierr); 1128 ierr = PetscOptionsBool("-ts_theta_endpoint","Use the endpoint instead of midpoint form of the Theta method","TSThetaSetEndpoint",th->endpoint,&th->endpoint,NULL);CHKERRQ(ierr); 1129 ierr = PetscOptionsBool("-ts_theta_initial_guess_extrapolate","Extrapolate stage initial guess from previous solution (sometimes unstable)","TSThetaSetExtrapolate",th->extrapolate,&th->extrapolate,NULL);CHKERRQ(ierr); 1130 } 1131 ierr = PetscOptionsTail();CHKERRQ(ierr); 1132 PetscFunctionReturn(0); 1133 } 1134 1135 static PetscErrorCode TSView_Theta(TS ts,PetscViewer viewer) 1136 { 1137 TS_Theta *th = (TS_Theta*)ts->data; 1138 PetscBool iascii; 1139 PetscErrorCode ierr; 1140 1141 PetscFunctionBegin; 1142 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1143 if (iascii) { 1144 ierr = PetscViewerASCIIPrintf(viewer," Theta=%g\n",(double)th->Theta);CHKERRQ(ierr); 1145 ierr = PetscViewerASCIIPrintf(viewer," Extrapolation=%s\n",th->extrapolate ? "yes" : "no");CHKERRQ(ierr); 1146 } 1147 PetscFunctionReturn(0); 1148 } 1149 1150 static PetscErrorCode TSThetaGetTheta_Theta(TS ts,PetscReal *theta) 1151 { 1152 TS_Theta *th = (TS_Theta*)ts->data; 1153 1154 PetscFunctionBegin; 1155 *theta = th->Theta; 1156 PetscFunctionReturn(0); 1157 } 1158 1159 static PetscErrorCode TSThetaSetTheta_Theta(TS ts,PetscReal theta) 1160 { 1161 TS_Theta *th = (TS_Theta*)ts->data; 1162 1163 PetscFunctionBegin; 1164 if (theta <= 0 || 1 < theta) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Theta %g not in range (0,1]",(double)theta); 1165 th->Theta = theta; 1166 th->order = (th->Theta == 0.5) ? 2 : 1; 1167 PetscFunctionReturn(0); 1168 } 1169 1170 static PetscErrorCode TSThetaGetEndpoint_Theta(TS ts,PetscBool *endpoint) 1171 { 1172 TS_Theta *th = (TS_Theta*)ts->data; 1173 1174 PetscFunctionBegin; 1175 *endpoint = th->endpoint; 1176 PetscFunctionReturn(0); 1177 } 1178 1179 static PetscErrorCode TSThetaSetEndpoint_Theta(TS ts,PetscBool flg) 1180 { 1181 TS_Theta *th = (TS_Theta*)ts->data; 1182 1183 PetscFunctionBegin; 1184 th->endpoint = flg; 1185 PetscFunctionReturn(0); 1186 } 1187 1188 #if defined(PETSC_HAVE_COMPLEX) 1189 static PetscErrorCode TSComputeLinearStability_Theta(TS ts,PetscReal xr,PetscReal xi,PetscReal *yr,PetscReal *yi) 1190 { 1191 PetscComplex z = xr + xi*PETSC_i,f; 1192 TS_Theta *th = (TS_Theta*)ts->data; 1193 const PetscReal one = 1.0; 1194 1195 PetscFunctionBegin; 1196 f = (one + (one - th->Theta)*z)/(one - th->Theta*z); 1197 *yr = PetscRealPartComplex(f); 1198 *yi = PetscImaginaryPartComplex(f); 1199 PetscFunctionReturn(0); 1200 } 1201 #endif 1202 1203 static PetscErrorCode TSGetStages_Theta(TS ts,PetscInt *ns,Vec **Y) 1204 { 1205 TS_Theta *th = (TS_Theta*)ts->data; 1206 1207 PetscFunctionBegin; 1208 if (ns) *ns = 1; 1209 if (Y) *Y = &(th->X0); 1210 PetscFunctionReturn(0); 1211 } 1212 1213 /* ------------------------------------------------------------ */ 1214 /*MC 1215 TSTHETA - DAE solver using the implicit Theta method 1216 1217 Level: beginner 1218 1219 Options Database: 1220 + -ts_theta_theta <Theta> - Location of stage (0<Theta<=1) 1221 . -ts_theta_endpoint <flag> - Use the endpoint (like Crank-Nicholson) instead of midpoint form of the Theta method 1222 - -ts_theta_initial_guess_extrapolate <flg> - Extrapolate stage initial guess from previous solution (sometimes unstable) 1223 1224 Notes: 1225 $ -ts_type theta -ts_theta_theta 1.0 corresponds to backward Euler (TSBEULER) 1226 $ -ts_type theta -ts_theta_theta 0.5 corresponds to the implicit midpoint rule 1227 $ -ts_type theta -ts_theta_theta 0.5 -ts_theta_endpoint corresponds to Crank-Nicholson (TSCN) 1228 1229 This method can be applied to DAE. 1230 1231 This method is cast as a 1-stage implicit Runge-Kutta method. 1232 1233 .vb 1234 Theta | Theta 1235 ------------- 1236 | 1 1237 .ve 1238 1239 For the default Theta=0.5, this is also known as the implicit midpoint rule. 1240 1241 When the endpoint variant is chosen, the method becomes a 2-stage method with first stage explicit: 1242 1243 .vb 1244 0 | 0 0 1245 1 | 1-Theta Theta 1246 ------------------- 1247 | 1-Theta Theta 1248 .ve 1249 1250 For the default Theta=0.5, this is the trapezoid rule (also known as Crank-Nicolson, see TSCN). 1251 1252 To apply a diagonally implicit RK method to DAE, the stage formula 1253 1254 $ Y_i = X + h sum_j a_ij Y'_j 1255 1256 is interpreted as a formula for Y'_i in terms of Y_i and known values (Y'_j, j<i) 1257 1258 .seealso: TSCreate(), TS, TSSetType(), TSCN, TSBEULER, TSThetaSetTheta(), TSThetaSetEndpoint() 1259 1260 M*/ 1261 PETSC_EXTERN PetscErrorCode TSCreate_Theta(TS ts) 1262 { 1263 TS_Theta *th; 1264 PetscErrorCode ierr; 1265 1266 PetscFunctionBegin; 1267 ts->ops->reset = TSReset_Theta; 1268 ts->ops->adjointreset = TSAdjointReset_Theta; 1269 ts->ops->destroy = TSDestroy_Theta; 1270 ts->ops->view = TSView_Theta; 1271 ts->ops->setup = TSSetUp_Theta; 1272 ts->ops->adjointsetup = TSAdjointSetUp_Theta; 1273 ts->ops->adjointreset = TSAdjointReset_Theta; 1274 ts->ops->step = TSStep_Theta; 1275 ts->ops->interpolate = TSInterpolate_Theta; 1276 ts->ops->evaluatewlte = TSEvaluateWLTE_Theta; 1277 ts->ops->rollback = TSRollBack_Theta; 1278 ts->ops->setfromoptions = TSSetFromOptions_Theta; 1279 ts->ops->snesfunction = SNESTSFormFunction_Theta; 1280 ts->ops->snesjacobian = SNESTSFormJacobian_Theta; 1281 #if defined(PETSC_HAVE_COMPLEX) 1282 ts->ops->linearstability = TSComputeLinearStability_Theta; 1283 #endif 1284 ts->ops->getstages = TSGetStages_Theta; 1285 ts->ops->adjointstep = TSAdjointStep_Theta; 1286 ts->ops->adjointintegral = TSAdjointCostIntegral_Theta; 1287 ts->ops->forwardintegral = TSForwardCostIntegral_Theta; 1288 ts->default_adapt_type = TSADAPTNONE; 1289 1290 ts->ops->forwardsetup = TSForwardSetUp_Theta; 1291 ts->ops->forwardreset = TSForwardReset_Theta; 1292 ts->ops->forwardstep = TSForwardStep_Theta; 1293 ts->ops->forwardgetstages = TSForwardGetStages_Theta; 1294 1295 ts->usessnes = PETSC_TRUE; 1296 1297 ierr = PetscNewLog(ts,&th);CHKERRQ(ierr); 1298 ts->data = (void*)th; 1299 1300 th->VecsDeltaLam = NULL; 1301 th->VecsDeltaMu = NULL; 1302 th->VecsSensiTemp = NULL; 1303 th->VecsSensi2Temp = NULL; 1304 1305 th->extrapolate = PETSC_FALSE; 1306 th->Theta = 0.5; 1307 th->order = 2; 1308 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetTheta_C",TSThetaGetTheta_Theta);CHKERRQ(ierr); 1309 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetTheta_C",TSThetaSetTheta_Theta);CHKERRQ(ierr); 1310 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetEndpoint_C",TSThetaGetEndpoint_Theta);CHKERRQ(ierr); 1311 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetEndpoint_C",TSThetaSetEndpoint_Theta);CHKERRQ(ierr); 1312 PetscFunctionReturn(0); 1313 } 1314 1315 /*@ 1316 TSThetaGetTheta - Get the abscissa of the stage in (0,1]. 1317 1318 Not Collective 1319 1320 Input Parameter: 1321 . ts - timestepping context 1322 1323 Output Parameter: 1324 . theta - stage abscissa 1325 1326 Note: 1327 Use of this function is normally only required to hack TSTHETA to use a modified integration scheme. 1328 1329 Level: Advanced 1330 1331 .seealso: TSThetaSetTheta() 1332 @*/ 1333 PetscErrorCode TSThetaGetTheta(TS ts,PetscReal *theta) 1334 { 1335 PetscErrorCode ierr; 1336 1337 PetscFunctionBegin; 1338 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1339 PetscValidPointer(theta,2); 1340 ierr = PetscUseMethod(ts,"TSThetaGetTheta_C",(TS,PetscReal*),(ts,theta));CHKERRQ(ierr); 1341 PetscFunctionReturn(0); 1342 } 1343 1344 /*@ 1345 TSThetaSetTheta - Set the abscissa of the stage in (0,1]. 1346 1347 Not Collective 1348 1349 Input Parameter: 1350 + ts - timestepping context 1351 - theta - stage abscissa 1352 1353 Options Database: 1354 . -ts_theta_theta <theta> 1355 1356 Level: Intermediate 1357 1358 .seealso: TSThetaGetTheta() 1359 @*/ 1360 PetscErrorCode TSThetaSetTheta(TS ts,PetscReal theta) 1361 { 1362 PetscErrorCode ierr; 1363 1364 PetscFunctionBegin; 1365 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1366 ierr = PetscTryMethod(ts,"TSThetaSetTheta_C",(TS,PetscReal),(ts,theta));CHKERRQ(ierr); 1367 PetscFunctionReturn(0); 1368 } 1369 1370 /*@ 1371 TSThetaGetEndpoint - Gets whether to use the endpoint variant of the method (e.g. trapezoid/Crank-Nicolson instead of midpoint rule). 1372 1373 Not Collective 1374 1375 Input Parameter: 1376 . ts - timestepping context 1377 1378 Output Parameter: 1379 . endpoint - PETSC_TRUE when using the endpoint variant 1380 1381 Level: Advanced 1382 1383 .seealso: TSThetaSetEndpoint(), TSTHETA, TSCN 1384 @*/ 1385 PetscErrorCode TSThetaGetEndpoint(TS ts,PetscBool *endpoint) 1386 { 1387 PetscErrorCode ierr; 1388 1389 PetscFunctionBegin; 1390 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1391 PetscValidPointer(endpoint,2); 1392 ierr = PetscUseMethod(ts,"TSThetaGetEndpoint_C",(TS,PetscBool*),(ts,endpoint));CHKERRQ(ierr); 1393 PetscFunctionReturn(0); 1394 } 1395 1396 /*@ 1397 TSThetaSetEndpoint - Sets whether to use the endpoint variant of the method (e.g. trapezoid/Crank-Nicolson instead of midpoint rule). 1398 1399 Not Collective 1400 1401 Input Parameter: 1402 + ts - timestepping context 1403 - flg - PETSC_TRUE to use the endpoint variant 1404 1405 Options Database: 1406 . -ts_theta_endpoint <flg> 1407 1408 Level: Intermediate 1409 1410 .seealso: TSTHETA, TSCN 1411 @*/ 1412 PetscErrorCode TSThetaSetEndpoint(TS ts,PetscBool flg) 1413 { 1414 PetscErrorCode ierr; 1415 1416 PetscFunctionBegin; 1417 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1418 ierr = PetscTryMethod(ts,"TSThetaSetEndpoint_C",(TS,PetscBool),(ts,flg));CHKERRQ(ierr); 1419 PetscFunctionReturn(0); 1420 } 1421 1422 /* 1423 * TSBEULER and TSCN are straightforward specializations of TSTHETA. 1424 * The creation functions for these specializations are below. 1425 */ 1426 1427 static PetscErrorCode TSSetUp_BEuler(TS ts) 1428 { 1429 TS_Theta *th = (TS_Theta*)ts->data; 1430 PetscErrorCode ierr; 1431 1432 PetscFunctionBegin; 1433 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"); 1434 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"); 1435 ierr = TSSetUp_Theta(ts);CHKERRQ(ierr); 1436 PetscFunctionReturn(0); 1437 } 1438 1439 static PetscErrorCode TSView_BEuler(TS ts,PetscViewer viewer) 1440 { 1441 PetscFunctionBegin; 1442 PetscFunctionReturn(0); 1443 } 1444 1445 /*MC 1446 TSBEULER - ODE solver using the implicit backward Euler method 1447 1448 Level: beginner 1449 1450 Notes: 1451 TSBEULER is equivalent to TSTHETA with Theta=1.0 1452 1453 $ -ts_type theta -ts_theta_theta 1.0 1454 1455 .seealso: TSCreate(), TS, TSSetType(), TSEULER, TSCN, TSTHETA 1456 1457 M*/ 1458 PETSC_EXTERN PetscErrorCode TSCreate_BEuler(TS ts) 1459 { 1460 PetscErrorCode ierr; 1461 1462 PetscFunctionBegin; 1463 ierr = TSCreate_Theta(ts);CHKERRQ(ierr); 1464 ierr = TSThetaSetTheta(ts,1.0);CHKERRQ(ierr); 1465 ierr = TSThetaSetEndpoint(ts,PETSC_FALSE);CHKERRQ(ierr); 1466 ts->ops->setup = TSSetUp_BEuler; 1467 ts->ops->view = TSView_BEuler; 1468 PetscFunctionReturn(0); 1469 } 1470 1471 static PetscErrorCode TSSetUp_CN(TS ts) 1472 { 1473 TS_Theta *th = (TS_Theta*)ts->data; 1474 PetscErrorCode ierr; 1475 1476 PetscFunctionBegin; 1477 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"); 1478 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"); 1479 ierr = TSSetUp_Theta(ts);CHKERRQ(ierr); 1480 PetscFunctionReturn(0); 1481 } 1482 1483 static PetscErrorCode TSView_CN(TS ts,PetscViewer viewer) 1484 { 1485 PetscFunctionBegin; 1486 PetscFunctionReturn(0); 1487 } 1488 1489 /*MC 1490 TSCN - ODE solver using the implicit Crank-Nicolson method. 1491 1492 Level: beginner 1493 1494 Notes: 1495 TSCN is equivalent to TSTHETA with Theta=0.5 and the "endpoint" option set. I.e. 1496 1497 $ -ts_type theta -ts_theta_theta 0.5 -ts_theta_endpoint 1498 1499 .seealso: TSCreate(), TS, TSSetType(), TSBEULER, TSTHETA 1500 1501 M*/ 1502 PETSC_EXTERN PetscErrorCode TSCreate_CN(TS ts) 1503 { 1504 PetscErrorCode ierr; 1505 1506 PetscFunctionBegin; 1507 ierr = TSCreate_Theta(ts);CHKERRQ(ierr); 1508 ierr = TSThetaSetTheta(ts,0.5);CHKERRQ(ierr); 1509 ierr = TSThetaSetEndpoint(ts,PETSC_TRUE);CHKERRQ(ierr); 1510 ts->ops->setup = TSSetUp_CN; 1511 ts->ops->view = TSView_CN; 1512 PetscFunctionReturn(0); 1513 } 1514