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,th->X,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,th->X,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,th->X,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,th->X,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,th->X,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 = TSComputeIJacobianP(ts,th->stage_time,th->X,th->Xdot,1./adjoint_time_step,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); /* get -f_p */ 375 if (quadts) { 376 ierr = TSComputeRHSJacobianP(quadts,th->stage_time,th->X,quadJp);CHKERRQ(ierr); 377 } 378 if (ts->vecs_sensi2p) { 379 /* lambda_s^T F_PU w_1 */ 380 ierr = TSComputeIHessianProductFunctionPU(ts,th->stage_time,th->X,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fpu);CHKERRQ(ierr); 381 /* lambda_s^T F_PP w_2 */ 382 ierr = TSComputeIHessianProductFunctionPP(ts,th->stage_time,th->X,VecsDeltaLam,ts->vec_dir,ts->vecs_fpp);CHKERRQ(ierr); 383 } 384 385 for (nadj=0; nadj<ts->numcost; nadj++) { 386 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr); 387 ierr = VecAXPY(ts->vecs_sensip[nadj],-adjoint_time_step,VecsDeltaMu[nadj]);CHKERRQ(ierr); 388 if (quadJp) { 389 ierr = MatDenseGetColumn(quadJp,nadj,&xarr);CHKERRQ(ierr); 390 ierr = VecPlaceArray(ts->vec_drdp_col,xarr);CHKERRQ(ierr); 391 ierr = VecAXPY(ts->vecs_sensip[nadj],adjoint_time_step,ts->vec_drdp_col);CHKERRQ(ierr); 392 ierr = VecResetArray(ts->vec_drdp_col);CHKERRQ(ierr); 393 ierr = MatDenseRestoreColumn(quadJp,&xarr);CHKERRQ(ierr); 394 } 395 if (ts->vecs_sensi2p) { 396 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam2[nadj],VecsDeltaMu2[nadj]);CHKERRQ(ierr); 397 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step,VecsDeltaMu2[nadj]);CHKERRQ(ierr); 398 if (ts->vecs_fpu) { 399 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step,ts->vecs_fpu[nadj]);CHKERRQ(ierr); 400 } 401 if (ts->vecs_fpp) { 402 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step,ts->vecs_fpp[nadj]);CHKERRQ(ierr); 403 } 404 } 405 } 406 } 407 408 if (ts->vecs_sensi2) { 409 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 410 ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr); 411 } 412 th->status = TS_STEP_COMPLETE; 413 PetscFunctionReturn(0); 414 } 415 416 static PetscErrorCode TSAdjointStep_Theta(TS ts) 417 { 418 TS_Theta *th = (TS_Theta*)ts->data; 419 TS quadts = ts->quadraturets; 420 Vec *VecsDeltaLam = th->VecsDeltaLam,*VecsDeltaMu = th->VecsDeltaMu,*VecsSensiTemp = th->VecsSensiTemp; 421 Vec *VecsDeltaLam2 = th->VecsDeltaLam2,*VecsDeltaMu2 = th->VecsDeltaMu2,*VecsSensi2Temp = th->VecsSensi2Temp; 422 PetscInt nadj; 423 Mat J,Jpre,quadJ = NULL,quadJp = NULL; 424 KSP ksp; 425 PetscScalar *xarr; 426 PetscReal adjoint_time_step; 427 PetscReal adjoint_ptime; /* end time of the adjoint time step (ts->ptime is the start time, ususally ts->ptime is larger than adjoint_ptime) */ 428 PetscErrorCode ierr; 429 430 PetscFunctionBegin; 431 if (th->Theta == 1.) { 432 ierr = TSAdjointStepBEuler_Private(ts);CHKERRQ(ierr); 433 PetscFunctionReturn(0); 434 } 435 th->status = TS_STEP_INCOMPLETE; 436 ierr = SNESGetKSP(ts->snes,&ksp);CHKERRQ(ierr); 437 ierr = TSGetIJacobian(ts,&J,&Jpre,NULL,NULL);CHKERRQ(ierr); 438 if (quadts) { 439 ierr = TSGetRHSJacobian(quadts,&quadJ,NULL,NULL,NULL);CHKERRQ(ierr); 440 ierr = TSGetRHSJacobianP(quadts,&quadJp,NULL,NULL);CHKERRQ(ierr); 441 } 442 /* If endpoint=1, th->ptime and th->X0 will be used; if endpoint=0, th->stage_time and th->X will be used. */ 443 th->stage_time = th->endpoint ? ts->ptime : (ts->ptime+(1.-th->Theta)*ts->time_step); 444 adjoint_ptime = ts->ptime + ts->time_step; 445 adjoint_time_step = -ts->time_step; /* always positive since time_step is negative */ 446 447 /* Build RHS for first-order adjoint */ 448 /* Cost function has an integral term */ 449 if (quadts) { 450 if (th->endpoint) { 451 ierr = TSComputeRHSJacobian(quadts,th->stage_time,ts->vec_sol,quadJ,NULL);CHKERRQ(ierr); 452 } else { 453 ierr = TSComputeRHSJacobian(quadts,th->stage_time,th->X,quadJ,NULL);CHKERRQ(ierr); 454 } 455 } 456 457 for (nadj=0; nadj<ts->numcost; nadj++) { 458 ierr = VecCopy(ts->vecs_sensi[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr); 459 ierr = VecScale(VecsSensiTemp[nadj],1./(th->Theta*adjoint_time_step));CHKERRQ(ierr); 460 if (quadJ) { 461 ierr = MatDenseGetColumn(quadJ,nadj,&xarr);CHKERRQ(ierr); 462 ierr = VecPlaceArray(ts->vec_drdu_col,xarr);CHKERRQ(ierr); 463 ierr = VecAXPY(VecsSensiTemp[nadj],1.,ts->vec_drdu_col);CHKERRQ(ierr); 464 ierr = VecResetArray(ts->vec_drdu_col);CHKERRQ(ierr); 465 ierr = MatDenseRestoreColumn(quadJ,&xarr);CHKERRQ(ierr); 466 } 467 } 468 469 /* Build LHS for first-order adjoint */ 470 th->shift = 1./(th->Theta*adjoint_time_step); 471 if (th->endpoint) { 472 ierr = TSComputeSNESJacobian(ts,ts->vec_sol,J,Jpre);CHKERRQ(ierr); 473 } else { 474 ierr = TSComputeSNESJacobian(ts,th->X,J,Jpre);CHKERRQ(ierr); 475 } 476 ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr); 477 478 /* Solve stage equation LHS*lambda_s = RHS for first-order adjoint */ 479 for (nadj=0; nadj<ts->numcost; nadj++) { 480 KSPConvergedReason kspreason; 481 ierr = KSPSolveTranspose(ksp,VecsSensiTemp[nadj],VecsDeltaLam[nadj]);CHKERRQ(ierr); 482 ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); 483 if (kspreason < 0) { 484 ts->reason = TSADJOINT_DIVERGED_LINEAR_SOLVE; 485 ierr = PetscInfo2(ts,"Step=%D, %Dth cost function, transposed linear solve fails, stopping 1st-order adjoint solve\n",ts->steps,nadj);CHKERRQ(ierr); 486 } 487 } 488 489 /* Second-order adjoint */ 490 if (ts->vecs_sensi2) { /* U_{n+1} */ 491 if (!th->endpoint) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Operation not implemented in TS_Theta"); 492 /* Get w1 at t_{n+1} from TLM matrix */ 493 ierr = MatDenseGetColumn(ts->mat_sensip,0,&xarr);CHKERRQ(ierr); 494 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 495 /* lambda_s^T F_UU w_1 */ 496 ierr = TSComputeIHessianProductFunctionUU(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fuu);CHKERRQ(ierr); 497 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 498 ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr); 499 /* lambda_s^T F_UP w_2 */ 500 ierr = TSComputeIHessianProductFunctionUP(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_dir,ts->vecs_fup);CHKERRQ(ierr); 501 for (nadj=0; nadj<ts->numcost; nadj++) { /* compute the residual */ 502 ierr = VecCopy(ts->vecs_sensi2[nadj],VecsSensi2Temp[nadj]);CHKERRQ(ierr); 503 ierr = VecScale(VecsSensi2Temp[nadj],th->shift);CHKERRQ(ierr); 504 ierr = VecAXPY(VecsSensi2Temp[nadj],-1.,ts->vecs_fuu[nadj]);CHKERRQ(ierr); 505 if (ts->vecs_fup) { 506 ierr = VecAXPY(VecsSensi2Temp[nadj],-1.,ts->vecs_fup[nadj]);CHKERRQ(ierr); 507 } 508 } 509 /* Solve stage equation LHS X = RHS for second-order adjoint */ 510 for (nadj=0; nadj<ts->numcost; nadj++) { 511 KSPConvergedReason kspreason; 512 ierr = KSPSolveTranspose(ksp,VecsSensi2Temp[nadj],VecsDeltaLam2[nadj]);CHKERRQ(ierr); 513 ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); 514 if (kspreason < 0) { 515 ts->reason = TSADJOINT_DIVERGED_LINEAR_SOLVE; 516 ierr = PetscInfo2(ts,"Step=%D, %Dth cost function, transposed linear solve fails, stopping 2nd-order adjoint solve\n",ts->steps,nadj);CHKERRQ(ierr); 517 } 518 } 519 } 520 521 /* Update sensitivities, and evaluate integrals if there is any */ 522 if (th->endpoint) { /* two-stage Theta methods with th->Theta!=1, th->Theta==1 leads to BEuler */ 523 th->shift = 1./((th->Theta-1.)*adjoint_time_step); 524 th->stage_time = adjoint_ptime; 525 ierr = TSComputeSNESJacobian(ts,th->X0,J,Jpre);CHKERRQ(ierr); 526 ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr); 527 /* R_U at t_n */ 528 if (quadts) { 529 ierr = TSComputeRHSJacobian(quadts,adjoint_ptime,th->X0,quadJ,NULL);CHKERRQ(ierr); 530 } 531 for (nadj=0; nadj<ts->numcost; nadj++) { 532 ierr = MatMultTranspose(J,VecsDeltaLam[nadj],ts->vecs_sensi[nadj]);CHKERRQ(ierr); 533 if (quadJ) { 534 ierr = MatDenseGetColumn(quadJ,nadj,&xarr);CHKERRQ(ierr); 535 ierr = VecPlaceArray(ts->vec_drdu_col,xarr);CHKERRQ(ierr); 536 ierr = VecAXPY(ts->vecs_sensi[nadj],-1.,ts->vec_drdu_col);CHKERRQ(ierr); 537 ierr = VecResetArray(ts->vec_drdu_col);CHKERRQ(ierr); 538 ierr = MatDenseRestoreColumn(quadJ,&xarr);CHKERRQ(ierr); 539 } 540 ierr = VecScale(ts->vecs_sensi[nadj],1./th->shift);CHKERRQ(ierr); 541 } 542 543 /* Second-order adjoint */ 544 if (ts->vecs_sensi2) { /* U_n */ 545 /* Get w1 at t_n from TLM matrix */ 546 ierr = MatDenseGetColumn(th->MatFwdSensip0,0,&xarr);CHKERRQ(ierr); 547 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 548 /* lambda_s^T F_UU w_1 */ 549 ierr = TSComputeIHessianProductFunctionUU(ts,adjoint_ptime,th->X0,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fuu);CHKERRQ(ierr); 550 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 551 ierr = MatDenseRestoreColumn(th->MatFwdSensip0,&xarr);CHKERRQ(ierr); 552 /* lambda_s^T F_UU w_2 */ 553 ierr = TSComputeIHessianProductFunctionUP(ts,adjoint_ptime,th->X0,VecsDeltaLam,ts->vec_dir,ts->vecs_fup);CHKERRQ(ierr); 554 for (nadj=0; nadj<ts->numcost; nadj++) { 555 /* 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 */ 556 ierr = MatMultTranspose(J,VecsDeltaLam2[nadj],ts->vecs_sensi2[nadj]);CHKERRQ(ierr); 557 ierr = VecAXPY(ts->vecs_sensi2[nadj],1.,ts->vecs_fuu[nadj]);CHKERRQ(ierr); 558 if (ts->vecs_fup) { 559 ierr = VecAXPY(ts->vecs_sensi2[nadj],1.,ts->vecs_fup[nadj]);CHKERRQ(ierr); 560 } 561 ierr = VecScale(ts->vecs_sensi2[nadj],1./th->shift);CHKERRQ(ierr); 562 } 563 } 564 565 th->stage_time = ts->ptime; /* recover the old value */ 566 567 if (ts->vecs_sensip) { /* sensitivities wrt parameters */ 568 /* U_{n+1} */ 569 ierr = TSComputeIJacobianP(ts,th->stage_time,ts->vec_sol,th->Xdot,-1./(th->Theta*adjoint_time_step),ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 570 if (quadts) { 571 ierr = TSComputeRHSJacobianP(quadts,th->stage_time,ts->vec_sol,quadJp);CHKERRQ(ierr); 572 } 573 for (nadj=0; nadj<ts->numcost; nadj++) { 574 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr); 575 ierr = VecAXPY(ts->vecs_sensip[nadj],-adjoint_time_step*th->Theta,VecsDeltaMu[nadj]);CHKERRQ(ierr); 576 if (quadJp) { 577 ierr = MatDenseGetColumn(quadJp,nadj,&xarr);CHKERRQ(ierr); 578 ierr = VecPlaceArray(ts->vec_drdp_col,xarr);CHKERRQ(ierr); 579 ierr = VecAXPY(ts->vecs_sensip[nadj],adjoint_time_step*th->Theta,ts->vec_drdp_col);CHKERRQ(ierr); 580 ierr = VecResetArray(ts->vec_drdp_col);CHKERRQ(ierr); 581 ierr = MatDenseRestoreColumn(quadJp,&xarr);CHKERRQ(ierr); 582 } 583 } 584 if (ts->vecs_sensi2p) { /* second-order */ 585 /* Get w1 at t_{n+1} from TLM matrix */ 586 ierr = MatDenseGetColumn(ts->mat_sensip,0,&xarr);CHKERRQ(ierr); 587 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 588 /* lambda_s^T F_PU w_1 */ 589 ierr = TSComputeIHessianProductFunctionPU(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fpu);CHKERRQ(ierr); 590 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 591 ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr); 592 593 /* lambda_s^T F_PP w_2 */ 594 ierr = TSComputeIHessianProductFunctionPP(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_dir,ts->vecs_fpp);CHKERRQ(ierr); 595 for (nadj=0; nadj<ts->numcost; nadj++) { 596 /* 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) */ 597 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam2[nadj],VecsDeltaMu2[nadj]);CHKERRQ(ierr); 598 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step*th->Theta,VecsDeltaMu2[nadj]);CHKERRQ(ierr); 599 if (ts->vecs_fpu) { 600 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step*th->Theta,ts->vecs_fpu[nadj]);CHKERRQ(ierr); 601 } 602 if (ts->vecs_fpp) { 603 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step*th->Theta,ts->vecs_fpp[nadj]);CHKERRQ(ierr); 604 } 605 } 606 } 607 608 /* U_s */ 609 ierr = TSComputeIJacobianP(ts,adjoint_ptime,th->X0,th->Xdot,1./((th->Theta-1.0)*adjoint_time_step),ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 610 if (quadts) { 611 ierr = TSComputeRHSJacobianP(quadts,adjoint_ptime,th->X0,quadJp);CHKERRQ(ierr); 612 } 613 for (nadj=0; nadj<ts->numcost; nadj++) { 614 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr); 615 ierr = VecAXPY(ts->vecs_sensip[nadj],-adjoint_time_step*(1.0-th->Theta),VecsDeltaMu[nadj]);CHKERRQ(ierr); 616 if (quadJp) { 617 ierr = MatDenseGetColumn(quadJp,nadj,&xarr);CHKERRQ(ierr); 618 ierr = VecPlaceArray(ts->vec_drdp_col,xarr);CHKERRQ(ierr); 619 ierr = VecAXPY(ts->vecs_sensip[nadj],adjoint_time_step*(1.0-th->Theta),ts->vec_drdp_col);CHKERRQ(ierr); 620 ierr = VecResetArray(ts->vec_drdp_col);CHKERRQ(ierr); 621 ierr = MatDenseRestoreColumn(quadJp,&xarr);CHKERRQ(ierr); 622 } 623 if (ts->vecs_sensi2p) { /* second-order */ 624 /* Get w1 at t_n from TLM matrix */ 625 ierr = MatDenseGetColumn(th->MatFwdSensip0,0,&xarr);CHKERRQ(ierr); 626 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 627 /* lambda_s^T F_PU w_1 */ 628 ierr = TSComputeIHessianProductFunctionPU(ts,adjoint_ptime,th->X0,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fpu);CHKERRQ(ierr); 629 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 630 ierr = MatDenseRestoreColumn(th->MatFwdSensip0,&xarr);CHKERRQ(ierr); 631 /* lambda_s^T F_PP w_2 */ 632 ierr = TSComputeIHessianProductFunctionPP(ts,adjoint_ptime,th->X0,VecsDeltaLam,ts->vec_dir,ts->vecs_fpp);CHKERRQ(ierr); 633 for (nadj=0; nadj<ts->numcost; nadj++) { 634 /* 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) */ 635 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam2[nadj],VecsDeltaMu2[nadj]);CHKERRQ(ierr); 636 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step*(1.0-th->Theta),VecsDeltaMu2[nadj]);CHKERRQ(ierr); 637 if (ts->vecs_fpu) { 638 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step*(1.0-th->Theta),ts->vecs_fpu[nadj]);CHKERRQ(ierr); 639 } 640 if (ts->vecs_fpp) { 641 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step*(1.0-th->Theta),ts->vecs_fpp[nadj]);CHKERRQ(ierr); 642 } 643 } 644 } 645 } 646 } 647 } else { /* one-stage case */ 648 th->shift = 0.0; 649 ierr = TSComputeSNESJacobian(ts,th->X,J,Jpre);CHKERRQ(ierr); /* get -f_y */ 650 ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr); 651 if (quadts) { 652 ierr = TSComputeRHSJacobian(quadts,th->stage_time,th->X,quadJ,NULL);CHKERRQ(ierr); 653 } 654 for (nadj=0; nadj<ts->numcost; nadj++) { 655 ierr = MatMultTranspose(J,VecsDeltaLam[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr); 656 ierr = VecAXPY(ts->vecs_sensi[nadj],-adjoint_time_step,VecsSensiTemp[nadj]);CHKERRQ(ierr); 657 if (quadJ) { 658 ierr = MatDenseGetColumn(quadJ,nadj,&xarr);CHKERRQ(ierr); 659 ierr = VecPlaceArray(ts->vec_drdu_col,xarr);CHKERRQ(ierr); 660 ierr = VecAXPY(ts->vecs_sensi[nadj],adjoint_time_step,ts->vec_drdu_col);CHKERRQ(ierr); 661 ierr = VecResetArray(ts->vec_drdu_col);CHKERRQ(ierr); 662 ierr = MatDenseRestoreColumn(quadJ,&xarr);CHKERRQ(ierr); 663 } 664 } 665 if (ts->vecs_sensip) { 666 ierr = TSComputeIJacobianP(ts,th->stage_time,th->X,th->Xdot,th->shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 667 if (quadts) { 668 ierr = TSComputeRHSJacobianP(quadts,th->stage_time,th->X,quadJp);CHKERRQ(ierr); 669 } 670 for (nadj=0; nadj<ts->numcost; nadj++) { 671 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr); 672 ierr = VecAXPY(ts->vecs_sensip[nadj],-adjoint_time_step,VecsDeltaMu[nadj]);CHKERRQ(ierr); 673 if (quadJp) { 674 ierr = MatDenseGetColumn(quadJp,nadj,&xarr);CHKERRQ(ierr); 675 ierr = VecPlaceArray(ts->vec_drdp_col,xarr);CHKERRQ(ierr); 676 ierr = VecAXPY(ts->vecs_sensip[nadj],adjoint_time_step,ts->vec_drdp_col);CHKERRQ(ierr); 677 ierr = VecResetArray(ts->vec_drdp_col);CHKERRQ(ierr); 678 ierr = MatDenseRestoreColumn(quadJp,&xarr);CHKERRQ(ierr); 679 } 680 } 681 } 682 } 683 684 th->status = TS_STEP_COMPLETE; 685 PetscFunctionReturn(0); 686 } 687 688 static PetscErrorCode TSInterpolate_Theta(TS ts,PetscReal t,Vec X) 689 { 690 TS_Theta *th = (TS_Theta*)ts->data; 691 PetscReal dt = t - ts->ptime; 692 PetscErrorCode ierr; 693 694 PetscFunctionBegin; 695 ierr = VecCopy(ts->vec_sol,th->X);CHKERRQ(ierr); 696 if (th->endpoint) dt *= th->Theta; 697 ierr = VecWAXPY(X,dt,th->Xdot,th->X);CHKERRQ(ierr); 698 PetscFunctionReturn(0); 699 } 700 701 static PetscErrorCode TSEvaluateWLTE_Theta(TS ts,NormType wnormtype,PetscInt *order,PetscReal *wlte) 702 { 703 TS_Theta *th = (TS_Theta*)ts->data; 704 Vec X = ts->vec_sol; /* X = solution */ 705 Vec Y = th->vec_lte_work; /* Y = X + LTE */ 706 PetscReal wltea,wlter; 707 PetscErrorCode ierr; 708 709 PetscFunctionBegin; 710 if (!th->vec_sol_prev) {*wlte = -1; PetscFunctionReturn(0);} 711 /* Cannot compute LTE in first step or in restart after event */ 712 if (ts->steprestart) {*wlte = -1; PetscFunctionReturn(0);} 713 /* Compute LTE using backward differences with non-constant time step */ 714 { 715 PetscReal h = ts->time_step, h_prev = ts->ptime - ts->ptime_prev; 716 PetscReal a = 1 + h_prev/h; 717 PetscScalar scal[3]; Vec vecs[3]; 718 scal[0] = +1/a; scal[1] = -1/(a-1); scal[2] = +1/(a*(a-1)); 719 vecs[0] = X; vecs[1] = th->X0; vecs[2] = th->vec_sol_prev; 720 ierr = VecCopy(X,Y);CHKERRQ(ierr); 721 ierr = VecMAXPY(Y,3,scal,vecs);CHKERRQ(ierr); 722 ierr = TSErrorWeightedNorm(ts,X,Y,wnormtype,wlte,&wltea,&wlter);CHKERRQ(ierr); 723 } 724 if (order) *order = 2; 725 PetscFunctionReturn(0); 726 } 727 728 static PetscErrorCode TSRollBack_Theta(TS ts) 729 { 730 TS_Theta *th = (TS_Theta*)ts->data; 731 TS quadts = ts->quadraturets; 732 PetscErrorCode ierr; 733 734 PetscFunctionBegin; 735 ierr = VecCopy(th->X0,ts->vec_sol);CHKERRQ(ierr); 736 if (quadts && ts->costintegralfwd) { 737 ierr = VecCopy(th->VecCostIntegral0,quadts->vec_sol);CHKERRQ(ierr); 738 } 739 th->status = TS_STEP_INCOMPLETE; 740 if (ts->mat_sensip) { 741 ierr = MatCopy(th->MatFwdSensip0,ts->mat_sensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 742 } 743 if (quadts && quadts->mat_sensip) { 744 ierr = MatCopy(th->MatIntegralSensip0,quadts->mat_sensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 745 } 746 PetscFunctionReturn(0); 747 } 748 749 static PetscErrorCode TSForwardStep_Theta(TS ts) 750 { 751 TS_Theta *th = (TS_Theta*)ts->data; 752 TS quadts = ts->quadraturets; 753 Mat MatDeltaFwdSensip = th->MatDeltaFwdSensip; 754 Vec VecDeltaFwdSensipCol = th->VecDeltaFwdSensipCol; 755 PetscInt ntlm; 756 KSP ksp; 757 Mat J,Jpre,quadJ = NULL,quadJp = NULL; 758 PetscScalar *barr,*xarr; 759 PetscReal previous_shift; 760 PetscErrorCode ierr; 761 762 PetscFunctionBegin; 763 previous_shift = th->shift; 764 ierr = MatCopy(ts->mat_sensip,th->MatFwdSensip0,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 765 766 if (quadts && quadts->mat_sensip) { 767 ierr = MatCopy(quadts->mat_sensip,th->MatIntegralSensip0,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 768 } 769 ierr = SNESGetKSP(ts->snes,&ksp);CHKERRQ(ierr); 770 ierr = TSGetIJacobian(ts,&J,&Jpre,NULL,NULL);CHKERRQ(ierr); 771 if (quadts) { 772 ierr = TSGetRHSJacobian(quadts,&quadJ,NULL,NULL,NULL);CHKERRQ(ierr); 773 ierr = TSGetRHSJacobianP(quadts,&quadJp,NULL,NULL);CHKERRQ(ierr); 774 } 775 776 /* Build RHS */ 777 if (th->endpoint) { /* 2-stage method*/ 778 th->shift = 1./((th->Theta-1.)*th->time_step0); 779 ierr = TSComputeIJacobian(ts,th->ptime0,th->X0,th->Xdot,th->shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr); 780 ierr = MatMatMult(J,ts->mat_sensip,MAT_REUSE_MATRIX,PETSC_DEFAULT,&MatDeltaFwdSensip);CHKERRQ(ierr); 781 ierr = MatScale(MatDeltaFwdSensip,(th->Theta-1.)/th->Theta);CHKERRQ(ierr); 782 783 /* Add the f_p forcing terms */ 784 if (ts->Jacp) { 785 ierr = TSComputeIJacobianP(ts,th->ptime0,th->X0,th->Xdot,th->shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 786 ierr = MatAXPY(MatDeltaFwdSensip,(th->Theta-1.)/th->Theta,ts->Jacp,SUBSET_NONZERO_PATTERN);CHKERRQ(ierr); 787 ierr = TSComputeIJacobianP(ts,th->stage_time,ts->vec_sol,th->Xdot,th->shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 788 ierr = MatAXPY(MatDeltaFwdSensip,-1.,ts->Jacp,SUBSET_NONZERO_PATTERN);CHKERRQ(ierr); 789 } 790 } else { /* 1-stage method */ 791 th->shift = 0.0; 792 ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,th->shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr); 793 ierr = MatMatMult(J,ts->mat_sensip,MAT_REUSE_MATRIX,PETSC_DEFAULT,&MatDeltaFwdSensip);CHKERRQ(ierr); 794 ierr = MatScale(MatDeltaFwdSensip,-1.);CHKERRQ(ierr); 795 796 /* Add the f_p forcing terms */ 797 if (ts->Jacp) { 798 ierr = TSComputeIJacobianP(ts,th->stage_time,th->X,th->Xdot,th->shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 799 ierr = MatAXPY(MatDeltaFwdSensip,-1.,ts->Jacp,SUBSET_NONZERO_PATTERN);CHKERRQ(ierr); 800 } 801 } 802 803 /* Build LHS */ 804 th->shift = previous_shift; /* recover the previous shift used in TSStep_Theta() */ 805 if (th->endpoint) { 806 ierr = TSComputeIJacobian(ts,th->stage_time,ts->vec_sol,th->Xdot,th->shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr); 807 } else { 808 ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,th->shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr); 809 } 810 ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr); 811 812 /* 813 Evaluate the first stage of integral gradients with the 2-stage method: 814 drdu|t_n*S(t_n) + drdp|t_n 815 This is done before the linear solve because the sensitivity variable S(t_n) will be propagated to S(t_{n+1}) 816 */ 817 if (th->endpoint) { /* 2-stage method only */ 818 if (quadts && quadts->mat_sensip) { 819 ierr = TSComputeRHSJacobian(quadts,th->ptime0,th->X0,quadJ,NULL);CHKERRQ(ierr); 820 ierr = TSComputeRHSJacobianP(quadts,th->ptime0,th->X0,quadJp);CHKERRQ(ierr); 821 ierr = MatTransposeMatMult(ts->mat_sensip,quadJ,MAT_REUSE_MATRIX,PETSC_DEFAULT,&th->MatIntegralSensipTemp);CHKERRQ(ierr); 822 ierr = MatAXPY(th->MatIntegralSensipTemp,1,quadJp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 823 ierr = MatAXPY(quadts->mat_sensip,th->time_step0*(1.-th->Theta),th->MatIntegralSensipTemp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 824 } 825 } 826 827 /* Solve the tangent linear equation for forward sensitivities to parameters */ 828 for (ntlm=0; ntlm<th->num_tlm; ntlm++) { 829 KSPConvergedReason kspreason; 830 ierr = MatDenseGetColumn(MatDeltaFwdSensip,ntlm,&barr);CHKERRQ(ierr); 831 ierr = VecPlaceArray(VecDeltaFwdSensipCol,barr);CHKERRQ(ierr); 832 if (th->endpoint) { 833 ierr = MatDenseGetColumn(ts->mat_sensip,ntlm,&xarr);CHKERRQ(ierr); 834 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 835 ierr = KSPSolve(ksp,VecDeltaFwdSensipCol,ts->vec_sensip_col);CHKERRQ(ierr); 836 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 837 ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr); 838 } else { 839 ierr = KSPSolve(ksp,VecDeltaFwdSensipCol,VecDeltaFwdSensipCol);CHKERRQ(ierr); 840 } 841 ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); 842 if (kspreason < 0) { 843 ts->reason = TSFORWARD_DIVERGED_LINEAR_SOLVE; 844 ierr = PetscInfo2(ts,"Step=%D, %Dth tangent linear solve, linear solve fails, stopping tangent linear solve\n",ts->steps,ntlm);CHKERRQ(ierr); 845 } 846 ierr = VecResetArray(VecDeltaFwdSensipCol);CHKERRQ(ierr); 847 ierr = MatDenseRestoreColumn(MatDeltaFwdSensip,&barr);CHKERRQ(ierr); 848 } 849 850 /* 851 Evaluate the second stage of integral gradients with the 2-stage method: 852 drdu|t_{n+1}*S(t_{n+1}) + drdp|t_{n+1} 853 */ 854 if (quadts && quadts->mat_sensip) { 855 if (!th->endpoint) { 856 ierr = MatAXPY(ts->mat_sensip,1,MatDeltaFwdSensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); /* stage sensitivity */ 857 ierr = TSComputeRHSJacobian(quadts,th->stage_time,th->X,quadJ,NULL);CHKERRQ(ierr); 858 ierr = TSComputeRHSJacobianP(quadts,th->stage_time,th->X,quadJp);CHKERRQ(ierr); 859 ierr = MatTransposeMatMult(ts->mat_sensip,quadJ,MAT_REUSE_MATRIX,PETSC_DEFAULT,&th->MatIntegralSensipTemp);CHKERRQ(ierr); 860 ierr = MatAXPY(th->MatIntegralSensipTemp,1,quadJp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 861 ierr = MatAXPY(quadts->mat_sensip,th->time_step0,th->MatIntegralSensipTemp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 862 ierr = MatAXPY(ts->mat_sensip,(1.-th->Theta)/th->Theta,MatDeltaFwdSensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 863 } else { 864 ierr = TSComputeRHSJacobian(quadts,th->stage_time,ts->vec_sol,quadJ,NULL);CHKERRQ(ierr); 865 ierr = TSComputeRHSJacobianP(quadts,th->stage_time,ts->vec_sol,quadJp);CHKERRQ(ierr); 866 ierr = MatTransposeMatMult(ts->mat_sensip,quadJ,MAT_REUSE_MATRIX,PETSC_DEFAULT,&th->MatIntegralSensipTemp);CHKERRQ(ierr); 867 ierr = MatAXPY(th->MatIntegralSensipTemp,1,quadJp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 868 ierr = MatAXPY(quadts->mat_sensip,th->time_step0*th->Theta,th->MatIntegralSensipTemp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 869 } 870 } else { 871 if (!th->endpoint) { 872 ierr = MatAXPY(ts->mat_sensip,1./th->Theta,MatDeltaFwdSensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 873 } 874 } 875 PetscFunctionReturn(0); 876 } 877 878 static PetscErrorCode TSForwardGetStages_Theta(TS ts,PetscInt *ns,Mat **stagesensip) 879 { 880 TS_Theta *th = (TS_Theta*)ts->data; 881 882 PetscFunctionBegin; 883 if (ns) *ns = 1; 884 if (stagesensip) *stagesensip = th->endpoint ? &(th->MatFwdSensip0) : &(th->MatDeltaFwdSensip); 885 PetscFunctionReturn(0); 886 } 887 888 /*------------------------------------------------------------*/ 889 static PetscErrorCode TSReset_Theta(TS ts) 890 { 891 TS_Theta *th = (TS_Theta*)ts->data; 892 PetscErrorCode ierr; 893 894 PetscFunctionBegin; 895 ierr = VecDestroy(&th->X);CHKERRQ(ierr); 896 ierr = VecDestroy(&th->Xdot);CHKERRQ(ierr); 897 ierr = VecDestroy(&th->X0);CHKERRQ(ierr); 898 ierr = VecDestroy(&th->affine);CHKERRQ(ierr); 899 900 ierr = VecDestroy(&th->vec_sol_prev);CHKERRQ(ierr); 901 ierr = VecDestroy(&th->vec_lte_work);CHKERRQ(ierr); 902 903 ierr = VecDestroy(&th->VecCostIntegral0);CHKERRQ(ierr); 904 PetscFunctionReturn(0); 905 } 906 907 static PetscErrorCode TSAdjointReset_Theta(TS ts) 908 { 909 TS_Theta *th = (TS_Theta*)ts->data; 910 PetscErrorCode ierr; 911 912 PetscFunctionBegin; 913 ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaLam);CHKERRQ(ierr); 914 ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaMu);CHKERRQ(ierr); 915 ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaLam2);CHKERRQ(ierr); 916 ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaMu2);CHKERRQ(ierr); 917 ierr = VecDestroyVecs(ts->numcost,&th->VecsSensiTemp);CHKERRQ(ierr); 918 ierr = VecDestroyVecs(ts->numcost,&th->VecsSensi2Temp);CHKERRQ(ierr); 919 PetscFunctionReturn(0); 920 } 921 922 static PetscErrorCode TSDestroy_Theta(TS ts) 923 { 924 PetscErrorCode ierr; 925 926 PetscFunctionBegin; 927 ierr = TSReset_Theta(ts);CHKERRQ(ierr); 928 if (ts->dm) { 929 ierr = DMCoarsenHookRemove(ts->dm,DMCoarsenHook_TSTheta,DMRestrictHook_TSTheta,ts);CHKERRQ(ierr); 930 ierr = DMSubDomainHookRemove(ts->dm,DMSubDomainHook_TSTheta,DMSubDomainRestrictHook_TSTheta,ts);CHKERRQ(ierr); 931 } 932 ierr = PetscFree(ts->data);CHKERRQ(ierr); 933 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetTheta_C",NULL);CHKERRQ(ierr); 934 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetTheta_C",NULL);CHKERRQ(ierr); 935 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetEndpoint_C",NULL);CHKERRQ(ierr); 936 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetEndpoint_C",NULL);CHKERRQ(ierr); 937 PetscFunctionReturn(0); 938 } 939 940 /* 941 This defines the nonlinear equation that is to be solved with SNES 942 G(U) = F[t0+Theta*dt, U, (U-U0)*shift] = 0 943 944 Note that U here is the stage argument. This means that U = U_{n+1} only if endpoint = true, 945 otherwise U = theta U_{n+1} + (1 - theta) U0, which for the case of implicit midpoint is 946 U = (U_{n+1} + U0)/2 947 */ 948 static PetscErrorCode SNESTSFormFunction_Theta(SNES snes,Vec x,Vec y,TS ts) 949 { 950 TS_Theta *th = (TS_Theta*)ts->data; 951 PetscErrorCode ierr; 952 Vec X0,Xdot; 953 DM dm,dmsave; 954 PetscReal shift = th->shift; 955 956 PetscFunctionBegin; 957 ierr = SNESGetDM(snes,&dm);CHKERRQ(ierr); 958 /* When using the endpoint variant, this is actually 1/Theta * Xdot */ 959 ierr = TSThetaGetX0AndXdot(ts,dm,&X0,&Xdot);CHKERRQ(ierr); 960 if (x != X0) { 961 ierr = VecAXPBYPCZ(Xdot,-shift,shift,0,X0,x);CHKERRQ(ierr); 962 } else { 963 ierr = VecZeroEntries(Xdot);CHKERRQ(ierr); 964 } 965 /* DM monkey-business allows user code to call TSGetDM() inside of functions evaluated on levels of FAS */ 966 dmsave = ts->dm; 967 ts->dm = dm; 968 ierr = TSComputeIFunction(ts,th->stage_time,x,Xdot,y,PETSC_FALSE);CHKERRQ(ierr); 969 ts->dm = dmsave; 970 ierr = TSThetaRestoreX0AndXdot(ts,dm,&X0,&Xdot);CHKERRQ(ierr); 971 PetscFunctionReturn(0); 972 } 973 974 static PetscErrorCode SNESTSFormJacobian_Theta(SNES snes,Vec x,Mat A,Mat B,TS ts) 975 { 976 TS_Theta *th = (TS_Theta*)ts->data; 977 PetscErrorCode ierr; 978 Vec Xdot; 979 DM dm,dmsave; 980 PetscReal shift = th->shift; 981 982 PetscFunctionBegin; 983 ierr = SNESGetDM(snes,&dm);CHKERRQ(ierr); 984 /* Xdot has already been computed in SNESTSFormFunction_Theta (SNES guarantees this) */ 985 ierr = TSThetaGetX0AndXdot(ts,dm,NULL,&Xdot);CHKERRQ(ierr); 986 987 dmsave = ts->dm; 988 ts->dm = dm; 989 ierr = TSComputeIJacobian(ts,th->stage_time,x,Xdot,shift,A,B,PETSC_FALSE);CHKERRQ(ierr); 990 ts->dm = dmsave; 991 ierr = TSThetaRestoreX0AndXdot(ts,dm,NULL,&Xdot);CHKERRQ(ierr); 992 PetscFunctionReturn(0); 993 } 994 995 static PetscErrorCode TSForwardSetUp_Theta(TS ts) 996 { 997 TS_Theta *th = (TS_Theta*)ts->data; 998 TS quadts = ts->quadraturets; 999 PetscErrorCode ierr; 1000 1001 PetscFunctionBegin; 1002 /* combine sensitivities to parameters and sensitivities to initial values into one array */ 1003 th->num_tlm = ts->num_parameters; 1004 ierr = MatDuplicate(ts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatDeltaFwdSensip);CHKERRQ(ierr); 1005 if (quadts && quadts->mat_sensip) { 1006 ierr = MatDuplicate(quadts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatIntegralSensipTemp);CHKERRQ(ierr); 1007 ierr = MatDuplicate(quadts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatIntegralSensip0);CHKERRQ(ierr); 1008 } 1009 /* backup sensitivity results for roll-backs */ 1010 ierr = MatDuplicate(ts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatFwdSensip0);CHKERRQ(ierr); 1011 1012 ierr = VecDuplicate(ts->vec_sol,&th->VecDeltaFwdSensipCol);CHKERRQ(ierr); 1013 PetscFunctionReturn(0); 1014 } 1015 1016 static PetscErrorCode TSForwardReset_Theta(TS ts) 1017 { 1018 TS_Theta *th = (TS_Theta*)ts->data; 1019 TS quadts = ts->quadraturets; 1020 PetscErrorCode ierr; 1021 1022 PetscFunctionBegin; 1023 if (quadts && quadts->mat_sensip) { 1024 ierr = MatDestroy(&th->MatIntegralSensipTemp);CHKERRQ(ierr); 1025 ierr = MatDestroy(&th->MatIntegralSensip0);CHKERRQ(ierr); 1026 } 1027 ierr = VecDestroy(&th->VecDeltaFwdSensipCol);CHKERRQ(ierr); 1028 ierr = MatDestroy(&th->MatDeltaFwdSensip);CHKERRQ(ierr); 1029 ierr = MatDestroy(&th->MatFwdSensip0);CHKERRQ(ierr); 1030 PetscFunctionReturn(0); 1031 } 1032 1033 static PetscErrorCode TSSetUp_Theta(TS ts) 1034 { 1035 TS_Theta *th = (TS_Theta*)ts->data; 1036 TS quadts = ts->quadraturets; 1037 PetscBool match; 1038 PetscErrorCode ierr; 1039 1040 PetscFunctionBegin; 1041 if (!th->VecCostIntegral0 && quadts && ts->costintegralfwd) { /* back up cost integral */ 1042 ierr = VecDuplicate(quadts->vec_sol,&th->VecCostIntegral0);CHKERRQ(ierr); 1043 } 1044 if (!th->X) { 1045 ierr = VecDuplicate(ts->vec_sol,&th->X);CHKERRQ(ierr); 1046 } 1047 if (!th->Xdot) { 1048 ierr = VecDuplicate(ts->vec_sol,&th->Xdot);CHKERRQ(ierr); 1049 } 1050 if (!th->X0) { 1051 ierr = VecDuplicate(ts->vec_sol,&th->X0);CHKERRQ(ierr); 1052 } 1053 if (th->endpoint) { 1054 ierr = VecDuplicate(ts->vec_sol,&th->affine);CHKERRQ(ierr); 1055 } 1056 1057 th->order = (th->Theta == 0.5) ? 2 : 1; 1058 th->shift = 1/(th->Theta*ts->time_step); 1059 1060 ierr = TSGetDM(ts,&ts->dm);CHKERRQ(ierr); 1061 ierr = DMCoarsenHookAdd(ts->dm,DMCoarsenHook_TSTheta,DMRestrictHook_TSTheta,ts);CHKERRQ(ierr); 1062 ierr = DMSubDomainHookAdd(ts->dm,DMSubDomainHook_TSTheta,DMSubDomainRestrictHook_TSTheta,ts);CHKERRQ(ierr); 1063 1064 ierr = TSGetAdapt(ts,&ts->adapt);CHKERRQ(ierr); 1065 ierr = TSAdaptCandidatesClear(ts->adapt);CHKERRQ(ierr); 1066 ierr = PetscObjectTypeCompare((PetscObject)ts->adapt,TSADAPTNONE,&match);CHKERRQ(ierr); 1067 if (!match) { 1068 ierr = VecDuplicate(ts->vec_sol,&th->vec_sol_prev);CHKERRQ(ierr); 1069 ierr = VecDuplicate(ts->vec_sol,&th->vec_lte_work);CHKERRQ(ierr); 1070 } 1071 ierr = TSGetSNES(ts,&ts->snes);CHKERRQ(ierr); 1072 PetscFunctionReturn(0); 1073 } 1074 1075 /*------------------------------------------------------------*/ 1076 1077 static PetscErrorCode TSAdjointSetUp_Theta(TS ts) 1078 { 1079 TS_Theta *th = (TS_Theta*)ts->data; 1080 PetscErrorCode ierr; 1081 1082 PetscFunctionBegin; 1083 ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&th->VecsDeltaLam);CHKERRQ(ierr); 1084 ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&th->VecsSensiTemp);CHKERRQ(ierr); 1085 if (ts->vecs_sensip) { 1086 ierr = VecDuplicateVecs(ts->vecs_sensip[0],ts->numcost,&th->VecsDeltaMu);CHKERRQ(ierr); 1087 } 1088 if (ts->vecs_sensi2) { 1089 ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&th->VecsDeltaLam2);CHKERRQ(ierr); 1090 ierr = VecDuplicateVecs(ts->vecs_sensi2[0],ts->numcost,&th->VecsSensi2Temp);CHKERRQ(ierr); 1091 /* hack ts to make implicit TS solver work when users provide only explicit versions of callbacks (RHSFunction,RHSJacobian,RHSHessian etc.) */ 1092 if (!ts->ihessianproduct_fuu) ts->vecs_fuu = ts->vecs_guu; 1093 if (!ts->ihessianproduct_fup) ts->vecs_fup = ts->vecs_gup; 1094 } 1095 if (ts->vecs_sensi2p) { 1096 ierr = VecDuplicateVecs(ts->vecs_sensi2p[0],ts->numcost,&th->VecsDeltaMu2);CHKERRQ(ierr); 1097 /* hack ts to make implicit TS solver work when users provide only explicit versions of callbacks (RHSFunction,RHSJacobian,RHSHessian etc.) */ 1098 if (!ts->ihessianproduct_fpu) ts->vecs_fpu = ts->vecs_gpu; 1099 if (!ts->ihessianproduct_fpp) ts->vecs_fpp = ts->vecs_gpp; 1100 } 1101 PetscFunctionReturn(0); 1102 } 1103 1104 static PetscErrorCode TSSetFromOptions_Theta(PetscOptionItems *PetscOptionsObject,TS ts) 1105 { 1106 TS_Theta *th = (TS_Theta*)ts->data; 1107 PetscErrorCode ierr; 1108 1109 PetscFunctionBegin; 1110 ierr = PetscOptionsHead(PetscOptionsObject,"Theta ODE solver options");CHKERRQ(ierr); 1111 { 1112 ierr = PetscOptionsReal("-ts_theta_theta","Location of stage (0<Theta<=1)","TSThetaSetTheta",th->Theta,&th->Theta,NULL);CHKERRQ(ierr); 1113 ierr = PetscOptionsBool("-ts_theta_endpoint","Use the endpoint instead of midpoint form of the Theta method","TSThetaSetEndpoint",th->endpoint,&th->endpoint,NULL);CHKERRQ(ierr); 1114 ierr = PetscOptionsBool("-ts_theta_initial_guess_extrapolate","Extrapolate stage initial guess from previous solution (sometimes unstable)","TSThetaSetExtrapolate",th->extrapolate,&th->extrapolate,NULL);CHKERRQ(ierr); 1115 } 1116 ierr = PetscOptionsTail();CHKERRQ(ierr); 1117 PetscFunctionReturn(0); 1118 } 1119 1120 static PetscErrorCode TSView_Theta(TS ts,PetscViewer viewer) 1121 { 1122 TS_Theta *th = (TS_Theta*)ts->data; 1123 PetscBool iascii; 1124 PetscErrorCode ierr; 1125 1126 PetscFunctionBegin; 1127 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1128 if (iascii) { 1129 ierr = PetscViewerASCIIPrintf(viewer," Theta=%g\n",(double)th->Theta);CHKERRQ(ierr); 1130 ierr = PetscViewerASCIIPrintf(viewer," Extrapolation=%s\n",th->extrapolate ? "yes" : "no");CHKERRQ(ierr); 1131 } 1132 PetscFunctionReturn(0); 1133 } 1134 1135 static PetscErrorCode TSThetaGetTheta_Theta(TS ts,PetscReal *theta) 1136 { 1137 TS_Theta *th = (TS_Theta*)ts->data; 1138 1139 PetscFunctionBegin; 1140 *theta = th->Theta; 1141 PetscFunctionReturn(0); 1142 } 1143 1144 static PetscErrorCode TSThetaSetTheta_Theta(TS ts,PetscReal theta) 1145 { 1146 TS_Theta *th = (TS_Theta*)ts->data; 1147 1148 PetscFunctionBegin; 1149 if (theta <= 0 || 1 < theta) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Theta %g not in range (0,1]",(double)theta); 1150 th->Theta = theta; 1151 th->order = (th->Theta == 0.5) ? 2 : 1; 1152 PetscFunctionReturn(0); 1153 } 1154 1155 static PetscErrorCode TSThetaGetEndpoint_Theta(TS ts,PetscBool *endpoint) 1156 { 1157 TS_Theta *th = (TS_Theta*)ts->data; 1158 1159 PetscFunctionBegin; 1160 *endpoint = th->endpoint; 1161 PetscFunctionReturn(0); 1162 } 1163 1164 static PetscErrorCode TSThetaSetEndpoint_Theta(TS ts,PetscBool flg) 1165 { 1166 TS_Theta *th = (TS_Theta*)ts->data; 1167 1168 PetscFunctionBegin; 1169 th->endpoint = flg; 1170 PetscFunctionReturn(0); 1171 } 1172 1173 #if defined(PETSC_HAVE_COMPLEX) 1174 static PetscErrorCode TSComputeLinearStability_Theta(TS ts,PetscReal xr,PetscReal xi,PetscReal *yr,PetscReal *yi) 1175 { 1176 PetscComplex z = xr + xi*PETSC_i,f; 1177 TS_Theta *th = (TS_Theta*)ts->data; 1178 const PetscReal one = 1.0; 1179 1180 PetscFunctionBegin; 1181 f = (one + (one - th->Theta)*z)/(one - th->Theta*z); 1182 *yr = PetscRealPartComplex(f); 1183 *yi = PetscImaginaryPartComplex(f); 1184 PetscFunctionReturn(0); 1185 } 1186 #endif 1187 1188 static PetscErrorCode TSGetStages_Theta(TS ts,PetscInt *ns,Vec **Y) 1189 { 1190 TS_Theta *th = (TS_Theta*)ts->data; 1191 1192 PetscFunctionBegin; 1193 if (ns) *ns = 1; 1194 if (Y) *Y = th->endpoint ? &(th->X0) : &(th->X); 1195 PetscFunctionReturn(0); 1196 } 1197 1198 /* ------------------------------------------------------------ */ 1199 /*MC 1200 TSTHETA - DAE solver using the implicit Theta method 1201 1202 Level: beginner 1203 1204 Options Database: 1205 + -ts_theta_theta <Theta> - Location of stage (0<Theta<=1) 1206 . -ts_theta_endpoint <flag> - Use the endpoint (like Crank-Nicholson) instead of midpoint form of the Theta method 1207 - -ts_theta_initial_guess_extrapolate <flg> - Extrapolate stage initial guess from previous solution (sometimes unstable) 1208 1209 Notes: 1210 $ -ts_type theta -ts_theta_theta 1.0 corresponds to backward Euler (TSBEULER) 1211 $ -ts_type theta -ts_theta_theta 0.5 corresponds to the implicit midpoint rule 1212 $ -ts_type theta -ts_theta_theta 0.5 -ts_theta_endpoint corresponds to Crank-Nicholson (TSCN) 1213 1214 This method can be applied to DAE. 1215 1216 This method is cast as a 1-stage implicit Runge-Kutta method. 1217 1218 .vb 1219 Theta | Theta 1220 ------------- 1221 | 1 1222 .ve 1223 1224 For the default Theta=0.5, this is also known as the implicit midpoint rule. 1225 1226 When the endpoint variant is chosen, the method becomes a 2-stage method with first stage explicit: 1227 1228 .vb 1229 0 | 0 0 1230 1 | 1-Theta Theta 1231 ------------------- 1232 | 1-Theta Theta 1233 .ve 1234 1235 For the default Theta=0.5, this is the trapezoid rule (also known as Crank-Nicolson, see TSCN). 1236 1237 To apply a diagonally implicit RK method to DAE, the stage formula 1238 1239 $ Y_i = X + h sum_j a_ij Y'_j 1240 1241 is interpreted as a formula for Y'_i in terms of Y_i and known values (Y'_j, j<i) 1242 1243 .seealso: TSCreate(), TS, TSSetType(), TSCN, TSBEULER, TSThetaSetTheta(), TSThetaSetEndpoint() 1244 1245 M*/ 1246 PETSC_EXTERN PetscErrorCode TSCreate_Theta(TS ts) 1247 { 1248 TS_Theta *th; 1249 PetscErrorCode ierr; 1250 1251 PetscFunctionBegin; 1252 ts->ops->reset = TSReset_Theta; 1253 ts->ops->adjointreset = TSAdjointReset_Theta; 1254 ts->ops->destroy = TSDestroy_Theta; 1255 ts->ops->view = TSView_Theta; 1256 ts->ops->setup = TSSetUp_Theta; 1257 ts->ops->adjointsetup = TSAdjointSetUp_Theta; 1258 ts->ops->adjointreset = TSAdjointReset_Theta; 1259 ts->ops->step = TSStep_Theta; 1260 ts->ops->interpolate = TSInterpolate_Theta; 1261 ts->ops->evaluatewlte = TSEvaluateWLTE_Theta; 1262 ts->ops->rollback = TSRollBack_Theta; 1263 ts->ops->setfromoptions = TSSetFromOptions_Theta; 1264 ts->ops->snesfunction = SNESTSFormFunction_Theta; 1265 ts->ops->snesjacobian = SNESTSFormJacobian_Theta; 1266 #if defined(PETSC_HAVE_COMPLEX) 1267 ts->ops->linearstability = TSComputeLinearStability_Theta; 1268 #endif 1269 ts->ops->getstages = TSGetStages_Theta; 1270 ts->ops->adjointstep = TSAdjointStep_Theta; 1271 ts->ops->adjointintegral = TSAdjointCostIntegral_Theta; 1272 ts->ops->forwardintegral = TSForwardCostIntegral_Theta; 1273 ts->default_adapt_type = TSADAPTNONE; 1274 1275 ts->ops->forwardsetup = TSForwardSetUp_Theta; 1276 ts->ops->forwardreset = TSForwardReset_Theta; 1277 ts->ops->forwardstep = TSForwardStep_Theta; 1278 ts->ops->forwardgetstages = TSForwardGetStages_Theta; 1279 1280 ts->usessnes = PETSC_TRUE; 1281 1282 ierr = PetscNewLog(ts,&th);CHKERRQ(ierr); 1283 ts->data = (void*)th; 1284 1285 th->VecsDeltaLam = NULL; 1286 th->VecsDeltaMu = NULL; 1287 th->VecsSensiTemp = NULL; 1288 th->VecsSensi2Temp = NULL; 1289 1290 th->extrapolate = PETSC_FALSE; 1291 th->Theta = 0.5; 1292 th->order = 2; 1293 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetTheta_C",TSThetaGetTheta_Theta);CHKERRQ(ierr); 1294 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetTheta_C",TSThetaSetTheta_Theta);CHKERRQ(ierr); 1295 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetEndpoint_C",TSThetaGetEndpoint_Theta);CHKERRQ(ierr); 1296 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetEndpoint_C",TSThetaSetEndpoint_Theta);CHKERRQ(ierr); 1297 PetscFunctionReturn(0); 1298 } 1299 1300 /*@ 1301 TSThetaGetTheta - Get the abscissa of the stage in (0,1]. 1302 1303 Not Collective 1304 1305 Input Parameter: 1306 . ts - timestepping context 1307 1308 Output Parameter: 1309 . theta - stage abscissa 1310 1311 Note: 1312 Use of this function is normally only required to hack TSTHETA to use a modified integration scheme. 1313 1314 Level: Advanced 1315 1316 .seealso: TSThetaSetTheta() 1317 @*/ 1318 PetscErrorCode TSThetaGetTheta(TS ts,PetscReal *theta) 1319 { 1320 PetscErrorCode ierr; 1321 1322 PetscFunctionBegin; 1323 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1324 PetscValidPointer(theta,2); 1325 ierr = PetscUseMethod(ts,"TSThetaGetTheta_C",(TS,PetscReal*),(ts,theta));CHKERRQ(ierr); 1326 PetscFunctionReturn(0); 1327 } 1328 1329 /*@ 1330 TSThetaSetTheta - Set the abscissa of the stage in (0,1]. 1331 1332 Not Collective 1333 1334 Input Parameter: 1335 + ts - timestepping context 1336 - theta - stage abscissa 1337 1338 Options Database: 1339 . -ts_theta_theta <theta> 1340 1341 Level: Intermediate 1342 1343 .seealso: TSThetaGetTheta() 1344 @*/ 1345 PetscErrorCode TSThetaSetTheta(TS ts,PetscReal theta) 1346 { 1347 PetscErrorCode ierr; 1348 1349 PetscFunctionBegin; 1350 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1351 ierr = PetscTryMethod(ts,"TSThetaSetTheta_C",(TS,PetscReal),(ts,theta));CHKERRQ(ierr); 1352 PetscFunctionReturn(0); 1353 } 1354 1355 /*@ 1356 TSThetaGetEndpoint - Gets whether to use the endpoint variant of the method (e.g. trapezoid/Crank-Nicolson instead of midpoint rule). 1357 1358 Not Collective 1359 1360 Input Parameter: 1361 . ts - timestepping context 1362 1363 Output Parameter: 1364 . endpoint - PETSC_TRUE when using the endpoint variant 1365 1366 Level: Advanced 1367 1368 .seealso: TSThetaSetEndpoint(), TSTHETA, TSCN 1369 @*/ 1370 PetscErrorCode TSThetaGetEndpoint(TS ts,PetscBool *endpoint) 1371 { 1372 PetscErrorCode ierr; 1373 1374 PetscFunctionBegin; 1375 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1376 PetscValidPointer(endpoint,2); 1377 ierr = PetscUseMethod(ts,"TSThetaGetEndpoint_C",(TS,PetscBool*),(ts,endpoint));CHKERRQ(ierr); 1378 PetscFunctionReturn(0); 1379 } 1380 1381 /*@ 1382 TSThetaSetEndpoint - Sets whether to use the endpoint variant of the method (e.g. trapezoid/Crank-Nicolson instead of midpoint rule). 1383 1384 Not Collective 1385 1386 Input Parameter: 1387 + ts - timestepping context 1388 - flg - PETSC_TRUE to use the endpoint variant 1389 1390 Options Database: 1391 . -ts_theta_endpoint <flg> 1392 1393 Level: Intermediate 1394 1395 .seealso: TSTHETA, TSCN 1396 @*/ 1397 PetscErrorCode TSThetaSetEndpoint(TS ts,PetscBool flg) 1398 { 1399 PetscErrorCode ierr; 1400 1401 PetscFunctionBegin; 1402 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1403 ierr = PetscTryMethod(ts,"TSThetaSetEndpoint_C",(TS,PetscBool),(ts,flg));CHKERRQ(ierr); 1404 PetscFunctionReturn(0); 1405 } 1406 1407 /* 1408 * TSBEULER and TSCN are straightforward specializations of TSTHETA. 1409 * The creation functions for these specializations are below. 1410 */ 1411 1412 static PetscErrorCode TSSetUp_BEuler(TS ts) 1413 { 1414 TS_Theta *th = (TS_Theta*)ts->data; 1415 PetscErrorCode ierr; 1416 1417 PetscFunctionBegin; 1418 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"); 1419 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"); 1420 ierr = TSSetUp_Theta(ts);CHKERRQ(ierr); 1421 PetscFunctionReturn(0); 1422 } 1423 1424 static PetscErrorCode TSView_BEuler(TS ts,PetscViewer viewer) 1425 { 1426 PetscFunctionBegin; 1427 PetscFunctionReturn(0); 1428 } 1429 1430 /*MC 1431 TSBEULER - ODE solver using the implicit backward Euler method 1432 1433 Level: beginner 1434 1435 Notes: 1436 TSBEULER is equivalent to TSTHETA with Theta=1.0 1437 1438 $ -ts_type theta -ts_theta_theta 1.0 1439 1440 .seealso: TSCreate(), TS, TSSetType(), TSEULER, TSCN, TSTHETA 1441 1442 M*/ 1443 PETSC_EXTERN PetscErrorCode TSCreate_BEuler(TS ts) 1444 { 1445 PetscErrorCode ierr; 1446 1447 PetscFunctionBegin; 1448 ierr = TSCreate_Theta(ts);CHKERRQ(ierr); 1449 ierr = TSThetaSetTheta(ts,1.0);CHKERRQ(ierr); 1450 ierr = TSThetaSetEndpoint(ts,PETSC_FALSE);CHKERRQ(ierr); 1451 ts->ops->setup = TSSetUp_BEuler; 1452 ts->ops->view = TSView_BEuler; 1453 PetscFunctionReturn(0); 1454 } 1455 1456 static PetscErrorCode TSSetUp_CN(TS ts) 1457 { 1458 TS_Theta *th = (TS_Theta*)ts->data; 1459 PetscErrorCode ierr; 1460 1461 PetscFunctionBegin; 1462 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"); 1463 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"); 1464 ierr = TSSetUp_Theta(ts);CHKERRQ(ierr); 1465 PetscFunctionReturn(0); 1466 } 1467 1468 static PetscErrorCode TSView_CN(TS ts,PetscViewer viewer) 1469 { 1470 PetscFunctionBegin; 1471 PetscFunctionReturn(0); 1472 } 1473 1474 /*MC 1475 TSCN - ODE solver using the implicit Crank-Nicolson method. 1476 1477 Level: beginner 1478 1479 Notes: 1480 TSCN is equivalent to TSTHETA with Theta=0.5 and the "endpoint" option set. I.e. 1481 1482 $ -ts_type theta -ts_theta_theta 0.5 -ts_theta_endpoint 1483 1484 .seealso: TSCreate(), TS, TSSetType(), TSBEULER, TSTHETA 1485 1486 M*/ 1487 PETSC_EXTERN PetscErrorCode TSCreate_CN(TS ts) 1488 { 1489 PetscErrorCode ierr; 1490 1491 PetscFunctionBegin; 1492 ierr = TSCreate_Theta(ts);CHKERRQ(ierr); 1493 ierr = TSThetaSetTheta(ts,0.5);CHKERRQ(ierr); 1494 ierr = TSThetaSetEndpoint(ts,PETSC_TRUE);CHKERRQ(ierr); 1495 ts->ops->setup = TSSetUp_CN; 1496 ts->ops->view = TSView_CN; 1497 PetscFunctionReturn(0); 1498 } 1499