1 /* 2 Code for timestepping with implicit Theta method 3 */ 4 #include <petsc/private/tsimpl.h> /*I "petscts.h" I*/ 5 #include <petscsnes.h> 6 #include <petscdm.h> 7 #include <petscmat.h> 8 9 typedef struct { 10 /* context for time stepping */ 11 PetscReal stage_time; 12 Vec X0,X,Xdot; /* Storage for stages and time derivative */ 13 Vec affine; /* Affine vector needed for residual at beginning of step in endpoint formulation */ 14 PetscReal Theta; 15 PetscReal ptime; 16 PetscReal time_step; 17 PetscReal shift; 18 PetscInt order; 19 PetscBool endpoint; 20 PetscBool extrapolate; 21 TSStepStatus status; 22 Vec VecCostIntegral0; /* Backup for roll-backs due to events */ 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->ptime,th->X0,ts->vec_costintegrand);CHKERRQ(ierr); 142 ierr = VecAXPY(quadts->vec_sol,th->time_step*(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_step*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_step,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 PetscErrorCode ierr; 169 170 PetscFunctionBegin; 171 ierr = TSThetaEvaluateCostIntegral(ts);CHKERRQ(ierr); 172 PetscFunctionReturn(0); 173 } 174 175 static PetscErrorCode TSTheta_SNESSolve(TS ts,Vec b,Vec x) 176 { 177 PetscInt nits,lits; 178 PetscErrorCode ierr; 179 180 PetscFunctionBegin; 181 ierr = SNESSolve(ts->snes,b,x);CHKERRQ(ierr); 182 ierr = SNESGetIterationNumber(ts->snes,&nits);CHKERRQ(ierr); 183 ierr = SNESGetLinearSolveIterations(ts->snes,&lits);CHKERRQ(ierr); 184 ts->snes_its += nits; ts->ksp_its += lits; 185 PetscFunctionReturn(0); 186 } 187 188 static PetscErrorCode TSStep_Theta(TS ts) 189 { 190 TS_Theta *th = (TS_Theta*)ts->data; 191 PetscInt rejections = 0; 192 PetscBool stageok,accept = PETSC_TRUE; 193 PetscReal next_time_step = ts->time_step; 194 PetscErrorCode ierr; 195 196 PetscFunctionBegin; 197 if (!ts->steprollback) { 198 if (th->vec_sol_prev) { ierr = VecCopy(th->X0,th->vec_sol_prev);CHKERRQ(ierr); } 199 ierr = VecCopy(ts->vec_sol,th->X0);CHKERRQ(ierr); 200 } 201 202 th->status = TS_STEP_INCOMPLETE; 203 while (!ts->reason && th->status != TS_STEP_COMPLETE) { 204 205 th->shift = 1/(th->Theta*ts->time_step); 206 th->stage_time = ts->ptime + (th->endpoint ? (PetscReal)1 : th->Theta)*ts->time_step; 207 208 ierr = VecCopy(th->X0,th->X);CHKERRQ(ierr); 209 if (th->extrapolate && !ts->steprestart) { 210 ierr = VecAXPY(th->X,1/th->shift,th->Xdot);CHKERRQ(ierr); 211 } 212 if (th->endpoint) { /* This formulation assumes linear time-independent mass matrix */ 213 if (!th->affine) {ierr = VecDuplicate(ts->vec_sol,&th->affine);CHKERRQ(ierr);} 214 ierr = VecZeroEntries(th->Xdot);CHKERRQ(ierr); 215 ierr = TSComputeIFunction(ts,ts->ptime,th->X0,th->Xdot,th->affine,PETSC_FALSE);CHKERRQ(ierr); 216 ierr = VecScale(th->affine,(th->Theta-1)/th->Theta);CHKERRQ(ierr); 217 } else if (th->affine) { /* Just in case th->endpoint is changed between calls to TSStep_Theta() */ 218 ierr = VecZeroEntries(th->affine);CHKERRQ(ierr); 219 } 220 ierr = TSPreStage(ts,th->stage_time);CHKERRQ(ierr); 221 ierr = TSTheta_SNESSolve(ts,th->affine,th->X);CHKERRQ(ierr); 222 ierr = TSPostStage(ts,th->stage_time,0,&th->X);CHKERRQ(ierr); 223 ierr = TSAdaptCheckStage(ts->adapt,ts,th->stage_time,th->X,&stageok);CHKERRQ(ierr); 224 if (!stageok) goto reject_step; 225 226 th->status = TS_STEP_PENDING; 227 if (th->endpoint) { 228 ierr = VecCopy(th->X,ts->vec_sol);CHKERRQ(ierr); 229 } else { 230 ierr = VecAXPBYPCZ(th->Xdot,-th->shift,th->shift,0,th->X0,th->X);CHKERRQ(ierr); 231 ierr = VecAXPY(ts->vec_sol,ts->time_step,th->Xdot);CHKERRQ(ierr); 232 } 233 ierr = TSAdaptChoose(ts->adapt,ts,ts->time_step,NULL,&next_time_step,&accept);CHKERRQ(ierr); 234 th->status = accept ? TS_STEP_COMPLETE : TS_STEP_INCOMPLETE; 235 if (!accept) { 236 ierr = VecCopy(th->X0,ts->vec_sol);CHKERRQ(ierr); 237 ts->time_step = next_time_step; 238 goto reject_step; 239 } 240 241 if (ts->forward_solve || ts->costintegralfwd) { /* Save the info for the later use in cost integral evaluation */ 242 th->ptime = ts->ptime; 243 th->time_step = ts->time_step; 244 } 245 246 ts->ptime += ts->time_step; 247 ts->time_step = next_time_step; 248 break; 249 250 reject_step: 251 ts->reject++; accept = PETSC_FALSE; 252 if (!ts->reason && ++rejections > ts->max_reject && ts->max_reject >= 0) { 253 ts->reason = TS_DIVERGED_STEP_REJECTED; 254 ierr = PetscInfo2(ts,"Step=%D, step rejections %D greater than current TS allowed, stopping solve\n",ts->steps,rejections);CHKERRQ(ierr); 255 } 256 } 257 PetscFunctionReturn(0); 258 } 259 260 static PetscErrorCode TSAdjointStepBEuler_Private(TS ts) 261 { 262 TS_Theta *th = (TS_Theta*)ts->data; 263 TS quadts = ts->quadraturets; 264 Vec *VecsDeltaLam = th->VecsDeltaLam,*VecsDeltaMu = th->VecsDeltaMu,*VecsSensiTemp = th->VecsSensiTemp; 265 Vec *VecsDeltaLam2 = th->VecsDeltaLam2,*VecsDeltaMu2 = th->VecsDeltaMu2,*VecsSensi2Temp = th->VecsSensi2Temp; 266 PetscInt nadj; 267 Mat J,Jpre,quadJ = NULL,quadJp = NULL; 268 KSP ksp; 269 PetscScalar *xarr; 270 TSEquationType eqtype; 271 PetscBool isexplicitode = PETSC_FALSE; 272 PetscErrorCode ierr; 273 274 PetscFunctionBegin; 275 ierr = TSGetEquationType(ts,&eqtype);CHKERRQ(ierr); 276 if (eqtype == TS_EQ_ODE_EXPLICIT) { 277 isexplicitode = PETSC_TRUE; 278 VecsDeltaLam = ts->vecs_sensi; 279 VecsDeltaLam2 = ts->vecs_sensi2; 280 } 281 th->status = TS_STEP_INCOMPLETE; 282 ierr = SNESGetKSP(ts->snes,&ksp);CHKERRQ(ierr); 283 ierr = TSGetIJacobian(ts,&J,&Jpre,NULL,NULL);CHKERRQ(ierr); 284 if (quadts) { 285 ierr = TSGetRHSJacobian(quadts,&quadJ,NULL,NULL,NULL);CHKERRQ(ierr); 286 ierr = TSGetRHSJacobianP(quadts,&quadJp,NULL,NULL);CHKERRQ(ierr); 287 } 288 289 /* If endpoint=1, th->ptime and th->X0 will be used; if endpoint=0, th->stage_time and th->X will be used. */ 290 th->stage_time = ts->ptime; /* time_step is negative*/ 291 th->ptime = ts->ptime + ts->time_step; 292 th->time_step = -ts->time_step; 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./th->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 ierr = TSComputeSNESJacobian(ts,th->X,J,Jpre);CHKERRQ(ierr); 313 ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr); 314 315 /* Solve stage equation LHS*lambda_s = RHS for first-order adjoint */ 316 for (nadj=0; nadj<ts->numcost; nadj++) { 317 KSPConvergedReason kspreason; 318 ierr = KSPSolveTranspose(ksp,VecsSensiTemp[nadj],VecsDeltaLam[nadj]);CHKERRQ(ierr); 319 ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); 320 if (kspreason < 0) { 321 ts->reason = TSADJOINT_DIVERGED_LINEAR_SOLVE; 322 ierr = PetscInfo2(ts,"Step=%D, %Dth cost function, transposed linear solve fails, stopping 1st-order adjoint solve\n",ts->steps,nadj);CHKERRQ(ierr); 323 } 324 } 325 326 if (ts->vecs_sensi2) { /* U_{n+1} */ 327 /* Get w1 at t_{n+1} from TLM matrix */ 328 ierr = MatDenseGetColumn(ts->mat_sensip,0,&xarr);CHKERRQ(ierr); 329 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 330 /* lambda_s^T F_UU w_1 */ 331 ierr = TSComputeIHessianProductFunctionUU(ts,th->stage_time,th->X,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fuu);CHKERRQ(ierr); 332 /* lambda_s^T F_UP w_2 */ 333 ierr = TSComputeIHessianProductFunctionUP(ts,th->stage_time,th->X,VecsDeltaLam,ts->vec_dir,ts->vecs_fup);CHKERRQ(ierr); 334 for (nadj=0; nadj<ts->numcost; nadj++) { /* compute the residual */ 335 ierr = VecCopy(ts->vecs_sensi2[nadj],VecsSensi2Temp[nadj]);CHKERRQ(ierr); 336 ierr = VecScale(VecsSensi2Temp[nadj],1./th->time_step);CHKERRQ(ierr); 337 ierr = VecAXPY(VecsSensi2Temp[nadj],-1.,ts->vecs_fuu[nadj]);CHKERRQ(ierr); 338 if (ts->vecs_fup) { 339 ierr = VecAXPY(VecsSensi2Temp[nadj],-1.,ts->vecs_fup[nadj]);CHKERRQ(ierr); 340 } 341 } 342 /* Solve stage equation LHS X = RHS for second-order adjoint */ 343 for (nadj=0; nadj<ts->numcost; nadj++) { 344 KSPConvergedReason kspreason; 345 ierr = KSPSolveTranspose(ksp,VecsSensi2Temp[nadj],VecsDeltaLam2[nadj]);CHKERRQ(ierr); 346 ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); 347 if (kspreason < 0) { 348 ts->reason = TSADJOINT_DIVERGED_LINEAR_SOLVE; 349 ierr = PetscInfo2(ts,"Step=%D, %Dth cost function, transposed linear solve fails, stopping 2nd-order adjoint solve\n",ts->steps,nadj);CHKERRQ(ierr); 350 } 351 } 352 } 353 354 /* Update sensitivities, and evaluate integrals if there is any */ 355 if (!isexplicitode) { 356 th->shift = 0.0; 357 ierr = TSComputeSNESJacobian(ts,th->X,J,Jpre);CHKERRQ(ierr); 358 ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr); 359 ierr = MatScale(J,-1.);CHKERRQ(ierr); 360 for (nadj=0; nadj<ts->numcost; nadj++) { 361 /* Add f_U \lambda_s to the original RHS */ 362 ierr = MatMultTransposeAdd(J,VecsDeltaLam[nadj],VecsSensiTemp[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr); 363 ierr = VecScale(VecsSensiTemp[nadj],th->time_step);CHKERRQ(ierr); 364 ierr = VecCopy(VecsSensiTemp[nadj],ts->vecs_sensi[nadj]);CHKERRQ(ierr); 365 if (ts->vecs_sensi2) { 366 ierr = MatMultTransposeAdd(J,VecsDeltaLam2[nadj],VecsSensi2Temp[nadj],VecsSensi2Temp[nadj]);CHKERRQ(ierr); 367 ierr = VecScale(VecsSensi2Temp[nadj],th->time_step);CHKERRQ(ierr); 368 ierr = VecCopy(VecsSensi2Temp[nadj],ts->vecs_sensi2[nadj]);CHKERRQ(ierr); 369 } 370 } 371 } 372 if (ts->vecs_sensip) { 373 th->shift = 1./th->time_step;; 374 ierr = TSComputeIJacobianP(ts,th->stage_time,th->X,th->Xdot,th->shift,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],-th->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],th->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],-th->time_step,VecsDeltaMu2[nadj]);CHKERRQ(ierr); 398 if (ts->vecs_fpu) { 399 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step,ts->vecs_fpu[nadj]);CHKERRQ(ierr); 400 } 401 if (ts->vecs_fpp) { 402 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->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 PetscErrorCode ierr; 427 428 PetscFunctionBegin; 429 if (th->Theta == 1.) { 430 ierr = TSAdjointStepBEuler_Private(ts);CHKERRQ(ierr); 431 PetscFunctionReturn(0); 432 } 433 th->status = TS_STEP_INCOMPLETE; 434 ierr = SNESGetKSP(ts->snes,&ksp);CHKERRQ(ierr); 435 ierr = TSGetIJacobian(ts,&J,&Jpre,NULL,NULL);CHKERRQ(ierr); 436 if (quadts) { 437 ierr = TSGetRHSJacobian(quadts,&quadJ,NULL,NULL,NULL);CHKERRQ(ierr); 438 ierr = TSGetRHSJacobianP(quadts,&quadJp,NULL,NULL);CHKERRQ(ierr); 439 } 440 /* If endpoint=1, th->ptime and th->X0 will be used; if endpoint=0, th->stage_time and th->X will be used. */ 441 th->stage_time = th->endpoint ? ts->ptime : (ts->ptime+(1.-th->Theta)*ts->time_step); /* time_step is negative*/ 442 th->ptime = ts->ptime + ts->time_step; 443 th->time_step = -ts->time_step; 444 445 /* Build RHS for first-order adjoint */ 446 /* Cost function has an integral term */ 447 if (quadts) { 448 if (th->endpoint) { 449 ierr = TSComputeRHSJacobian(quadts,th->stage_time,ts->vec_sol,quadJ,NULL);CHKERRQ(ierr); 450 } else { 451 ierr = TSComputeRHSJacobian(quadts,th->stage_time,th->X,quadJ,NULL);CHKERRQ(ierr); 452 } 453 } 454 455 for (nadj=0; nadj<ts->numcost; nadj++) { 456 ierr = VecCopy(ts->vecs_sensi[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr); 457 ierr = VecScale(VecsSensiTemp[nadj],1./(th->Theta*th->time_step));CHKERRQ(ierr); 458 if (quadJ) { 459 ierr = MatDenseGetColumn(quadJ,nadj,&xarr);CHKERRQ(ierr); 460 ierr = VecPlaceArray(ts->vec_drdu_col,xarr);CHKERRQ(ierr); 461 ierr = VecAXPY(VecsSensiTemp[nadj],1.,ts->vec_drdu_col);CHKERRQ(ierr); 462 ierr = VecResetArray(ts->vec_drdu_col);CHKERRQ(ierr); 463 ierr = MatDenseRestoreColumn(quadJ,&xarr);CHKERRQ(ierr); 464 } 465 } 466 467 /* Build LHS for first-order adjoint */ 468 th->shift = 1./(th->Theta*th->time_step); 469 if (th->endpoint) { 470 ierr = TSComputeSNESJacobian(ts,ts->vec_sol,J,Jpre);CHKERRQ(ierr); 471 } else { 472 ierr = TSComputeSNESJacobian(ts,th->X,J,Jpre);CHKERRQ(ierr); 473 } 474 ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr); 475 476 /* Solve stage equation LHS*lambda_s = RHS for first-order adjoint */ 477 for (nadj=0; nadj<ts->numcost; nadj++) { 478 KSPConvergedReason kspreason; 479 ierr = KSPSolveTranspose(ksp,VecsSensiTemp[nadj],VecsDeltaLam[nadj]);CHKERRQ(ierr); 480 ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); 481 if (kspreason < 0) { 482 ts->reason = TSADJOINT_DIVERGED_LINEAR_SOLVE; 483 ierr = PetscInfo2(ts,"Step=%D, %Dth cost function, transposed linear solve fails, stopping 1st-order adjoint solve\n",ts->steps,nadj);CHKERRQ(ierr); 484 } 485 } 486 487 /* Second-order adjoint */ 488 if (ts->vecs_sensi2) { /* U_{n+1} */ 489 if (!th->endpoint) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Operation not implemented in TS_Theta"); 490 /* Get w1 at t_{n+1} from TLM matrix */ 491 ierr = MatDenseGetColumn(ts->mat_sensip,0,&xarr);CHKERRQ(ierr); 492 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 493 /* lambda_s^T F_UU w_1 */ 494 ierr = TSComputeIHessianProductFunctionUU(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fuu);CHKERRQ(ierr); 495 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 496 ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr); 497 /* lambda_s^T F_UP w_2 */ 498 ierr = TSComputeIHessianProductFunctionUP(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_dir,ts->vecs_fup);CHKERRQ(ierr); 499 for (nadj=0; nadj<ts->numcost; nadj++) { /* compute the residual */ 500 ierr = VecCopy(ts->vecs_sensi2[nadj],VecsSensi2Temp[nadj]);CHKERRQ(ierr); 501 ierr = VecScale(VecsSensi2Temp[nadj],th->shift);CHKERRQ(ierr); 502 ierr = VecAXPY(VecsSensi2Temp[nadj],-1.,ts->vecs_fuu[nadj]);CHKERRQ(ierr); 503 if (ts->vecs_fup) { 504 ierr = VecAXPY(VecsSensi2Temp[nadj],-1.,ts->vecs_fup[nadj]);CHKERRQ(ierr); 505 } 506 } 507 /* Solve stage equation LHS X = RHS for second-order adjoint */ 508 for (nadj=0; nadj<ts->numcost; nadj++) { 509 KSPConvergedReason kspreason; 510 ierr = KSPSolveTranspose(ksp,VecsSensi2Temp[nadj],VecsDeltaLam2[nadj]);CHKERRQ(ierr); 511 ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); 512 if (kspreason < 0) { 513 ts->reason = TSADJOINT_DIVERGED_LINEAR_SOLVE; 514 ierr = PetscInfo2(ts,"Step=%D, %Dth cost function, transposed linear solve fails, stopping 2nd-order adjoint solve\n",ts->steps,nadj);CHKERRQ(ierr); 515 } 516 } 517 } 518 519 /* Update sensitivities, and evaluate integrals if there is any */ 520 if(th->endpoint) { /* two-stage Theta methods with th->Theta!=1, th->Theta==1 leads to BEuler */ 521 th->shift = 1./((th->Theta-1.)*th->time_step); 522 th->stage_time = th->ptime; 523 ierr = TSComputeSNESJacobian(ts,th->X0,J,Jpre);CHKERRQ(ierr); 524 ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr); 525 /* R_U at t_n */ 526 if (quadts) { 527 ierr = TSComputeRHSJacobian(quadts,th->ptime,th->X0,quadJ,NULL);CHKERRQ(ierr); 528 } 529 for (nadj=0; nadj<ts->numcost; nadj++) { 530 ierr = MatMultTranspose(J,VecsDeltaLam[nadj],ts->vecs_sensi[nadj]);CHKERRQ(ierr); 531 if (quadJ) { 532 ierr = MatDenseGetColumn(quadJ,nadj,&xarr);CHKERRQ(ierr); 533 ierr = VecPlaceArray(ts->vec_drdu_col,xarr);CHKERRQ(ierr); 534 ierr = VecAXPY(ts->vecs_sensi[nadj],-1.,ts->vec_drdu_col);CHKERRQ(ierr); 535 ierr = VecResetArray(ts->vec_drdu_col);CHKERRQ(ierr); 536 ierr = MatDenseRestoreColumn(quadJ,&xarr);CHKERRQ(ierr); 537 } 538 ierr = VecScale(ts->vecs_sensi[nadj],1./th->shift);CHKERRQ(ierr); 539 } 540 541 /* Second-order adjoint */ 542 if (ts->vecs_sensi2) { /* U_n */ 543 /* Get w1 at t_n from TLM matrix */ 544 ierr = MatDenseGetColumn(th->MatFwdSensip0,0,&xarr);CHKERRQ(ierr); 545 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 546 /* lambda_s^T F_UU w_1 */ 547 ierr = TSComputeIHessianProductFunctionUU(ts,th->ptime,th->X0,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fuu);CHKERRQ(ierr); 548 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 549 ierr = MatDenseRestoreColumn(th->MatFwdSensip0,&xarr);CHKERRQ(ierr); 550 /* lambda_s^T F_UU w_2 */ 551 ierr = TSComputeIHessianProductFunctionUP(ts,th->ptime,th->X0,VecsDeltaLam,ts->vec_dir,ts->vecs_fup);CHKERRQ(ierr); 552 for (nadj=0; nadj<ts->numcost; nadj++) { 553 /* 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 */ 554 ierr = MatMultTranspose(J,VecsDeltaLam2[nadj],ts->vecs_sensi2[nadj]);CHKERRQ(ierr); 555 ierr = VecAXPY(ts->vecs_sensi2[nadj],1.,ts->vecs_fuu[nadj]);CHKERRQ(ierr); 556 if (ts->vecs_fup) { 557 ierr = VecAXPY(ts->vecs_sensi2[nadj],1.,ts->vecs_fup[nadj]);CHKERRQ(ierr); 558 } 559 ierr = VecScale(ts->vecs_sensi2[nadj],1./th->shift);CHKERRQ(ierr); 560 } 561 } 562 563 th->stage_time = ts->ptime; /* recover the old value */ 564 565 if (ts->vecs_sensip) { /* sensitivities wrt parameters */ 566 /* U_{n+1} */ 567 th->shift = -1./(th->Theta*th->time_step); 568 ierr = TSComputeIJacobianP(ts,th->stage_time,ts->vec_sol,th->Xdot,th->shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 569 if (quadts) { 570 ierr = TSComputeRHSJacobianP(quadts,th->stage_time,ts->vec_sol,quadJp);CHKERRQ(ierr); 571 } 572 for (nadj=0; nadj<ts->numcost; nadj++) { 573 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr); 574 ierr = VecAXPY(ts->vecs_sensip[nadj],-th->time_step*th->Theta,VecsDeltaMu[nadj]);CHKERRQ(ierr); 575 } 576 if (ts->vecs_sensi2p) { /* second-order */ 577 /* Get w1 at t_{n+1} from TLM matrix */ 578 ierr = MatDenseGetColumn(ts->mat_sensip,0,&xarr);CHKERRQ(ierr); 579 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 580 /* lambda_s^T F_PU w_1 */ 581 ierr = TSComputeIHessianProductFunctionPU(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fpu);CHKERRQ(ierr); 582 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 583 ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr); 584 585 /* lambda_s^T F_PP w_2 */ 586 ierr = TSComputeIHessianProductFunctionPP(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_dir,ts->vecs_fpp);CHKERRQ(ierr); 587 for (nadj=0; nadj<ts->numcost; nadj++) { 588 /* 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) */ 589 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam2[nadj],VecsDeltaMu2[nadj]);CHKERRQ(ierr); 590 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step*th->Theta,VecsDeltaMu2[nadj]);CHKERRQ(ierr); 591 if (ts->vecs_fpu) { 592 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step*th->Theta,ts->vecs_fpu[nadj]);CHKERRQ(ierr); 593 } 594 if (ts->vecs_fpp) { 595 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step*th->Theta,ts->vecs_fpp[nadj]);CHKERRQ(ierr); 596 } 597 } 598 } 599 600 /* U_s */ 601 th->shift = 1./((th->Theta-1.0)*th->time_step); 602 ierr = TSComputeIJacobianP(ts,th->ptime,th->X0,th->Xdot,th->shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 603 if (quadts) { 604 ierr = TSComputeRHSJacobianP(quadts,th->ptime,th->X0,quadJp);CHKERRQ(ierr); 605 } 606 for (nadj=0; nadj<ts->numcost; nadj++) { 607 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr); 608 ierr = VecAXPY(ts->vecs_sensip[nadj],-th->time_step*(1.0-th->Theta),VecsDeltaMu[nadj]);CHKERRQ(ierr); 609 if (ts->vecs_sensi2p) { /* second-order */ 610 /* Get w1 at t_n from TLM matrix */ 611 ierr = MatDenseGetColumn(th->MatFwdSensip0,0,&xarr);CHKERRQ(ierr); 612 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 613 /* lambda_s^T F_PU w_1 */ 614 ierr = TSComputeIHessianProductFunctionPU(ts,th->ptime,th->X0,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fpu);CHKERRQ(ierr); 615 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 616 ierr = MatDenseRestoreColumn(th->MatFwdSensip0,&xarr);CHKERRQ(ierr); 617 /* lambda_s^T F_PP w_2 */ 618 ierr = TSComputeIHessianProductFunctionPP(ts,th->ptime,th->X0,VecsDeltaLam,ts->vec_dir,ts->vecs_fpp);CHKERRQ(ierr); 619 for (nadj=0; nadj<ts->numcost; nadj++) { 620 /* 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) */ 621 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam2[nadj],VecsDeltaMu2[nadj]);CHKERRQ(ierr); 622 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step*(1.0-th->Theta),VecsDeltaMu2[nadj]);CHKERRQ(ierr); 623 if (ts->vecs_fpu) { 624 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step*(1.0-th->Theta),ts->vecs_fpu[nadj]);CHKERRQ(ierr); 625 } 626 if (ts->vecs_fpp) { 627 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step*(1.0-th->Theta),ts->vecs_fpp[nadj]);CHKERRQ(ierr); 628 } 629 } 630 } 631 } 632 } 633 } else { /* one-stage case */ 634 th->shift = 0.0; 635 ierr = TSComputeSNESJacobian(ts,th->X,J,Jpre);CHKERRQ(ierr); /* get -f_y */ 636 ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr); 637 if (quadts) { 638 ierr = TSComputeRHSJacobian(quadts,th->stage_time,th->X,quadJ,NULL);CHKERRQ(ierr); 639 } 640 for (nadj=0; nadj<ts->numcost; nadj++) { 641 ierr = MatMultTranspose(J,VecsDeltaLam[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr); 642 ierr = VecAXPY(ts->vecs_sensi[nadj],-th->time_step,VecsSensiTemp[nadj]);CHKERRQ(ierr); 643 if (quadJ) { 644 ierr = MatDenseGetColumn(quadJ,nadj,&xarr);CHKERRQ(ierr); 645 ierr = VecPlaceArray(ts->vec_drdu_col,xarr);CHKERRQ(ierr); 646 ierr = VecAXPY(ts->vecs_sensi[nadj],th->time_step,ts->vec_drdu_col);CHKERRQ(ierr); 647 ierr = VecResetArray(ts->vec_drdu_col);CHKERRQ(ierr); 648 ierr = MatDenseRestoreColumn(quadJ,&xarr);CHKERRQ(ierr); 649 } 650 } 651 if (ts->vecs_sensip) { 652 ierr = TSComputeIJacobianP(ts,th->stage_time,th->X,th->Xdot,th->shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 653 if (quadts) { 654 ierr = TSComputeRHSJacobianP(quadts,th->stage_time,th->X,quadJp);CHKERRQ(ierr); 655 } 656 for (nadj=0; nadj<ts->numcost; nadj++) { 657 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr); 658 ierr = VecAXPY(ts->vecs_sensip[nadj],-th->time_step,VecsDeltaMu[nadj]);CHKERRQ(ierr); 659 if (quadJp) { 660 ierr = MatDenseGetColumn(quadJp,nadj,&xarr);CHKERRQ(ierr); 661 ierr = VecPlaceArray(ts->vec_drdp_col,xarr);CHKERRQ(ierr); 662 ierr = VecAXPY(ts->vecs_sensip[nadj],th->time_step,ts->vec_drdp_col);CHKERRQ(ierr); 663 ierr = VecResetArray(ts->vec_drdp_col);CHKERRQ(ierr); 664 ierr = MatDenseRestoreColumn(quadJp,&xarr);CHKERRQ(ierr); 665 } 666 } 667 } 668 } 669 670 th->status = TS_STEP_COMPLETE; 671 PetscFunctionReturn(0); 672 } 673 674 static PetscErrorCode TSInterpolate_Theta(TS ts,PetscReal t,Vec X) 675 { 676 TS_Theta *th = (TS_Theta*)ts->data; 677 PetscReal dt = t - ts->ptime; 678 PetscErrorCode ierr; 679 680 PetscFunctionBegin; 681 ierr = VecCopy(ts->vec_sol,th->X);CHKERRQ(ierr); 682 if (th->endpoint) dt *= th->Theta; 683 ierr = VecWAXPY(X,dt,th->Xdot,th->X);CHKERRQ(ierr); 684 PetscFunctionReturn(0); 685 } 686 687 static PetscErrorCode TSEvaluateWLTE_Theta(TS ts,NormType wnormtype,PetscInt *order,PetscReal *wlte) 688 { 689 TS_Theta *th = (TS_Theta*)ts->data; 690 Vec X = ts->vec_sol; /* X = solution */ 691 Vec Y = th->vec_lte_work; /* Y = X + LTE */ 692 PetscReal wltea,wlter; 693 PetscErrorCode ierr; 694 695 PetscFunctionBegin; 696 if (!th->vec_sol_prev) {*wlte = -1; PetscFunctionReturn(0);} 697 /* Cannot compute LTE in first step or in restart after event */ 698 if (ts->steprestart) {*wlte = -1; PetscFunctionReturn(0);} 699 /* Compute LTE using backward differences with non-constant time step */ 700 { 701 PetscReal h = ts->time_step, h_prev = ts->ptime - ts->ptime_prev; 702 PetscReal a = 1 + h_prev/h; 703 PetscScalar scal[3]; Vec vecs[3]; 704 scal[0] = +1/a; scal[1] = -1/(a-1); scal[2] = +1/(a*(a-1)); 705 vecs[0] = X; vecs[1] = th->X0; vecs[2] = th->vec_sol_prev; 706 ierr = VecCopy(X,Y);CHKERRQ(ierr); 707 ierr = VecMAXPY(Y,3,scal,vecs);CHKERRQ(ierr); 708 ierr = TSErrorWeightedNorm(ts,X,Y,wnormtype,wlte,&wltea,&wlter);CHKERRQ(ierr); 709 } 710 if (order) *order = 2; 711 PetscFunctionReturn(0); 712 } 713 714 static PetscErrorCode TSRollBack_Theta(TS ts) 715 { 716 TS_Theta *th = (TS_Theta*)ts->data; 717 TS quadts = ts->quadraturets; 718 PetscErrorCode ierr; 719 720 PetscFunctionBegin; 721 ierr = VecCopy(th->X0,ts->vec_sol);CHKERRQ(ierr); 722 if (quadts && ts->costintegralfwd) { 723 ierr = VecCopy(th->VecCostIntegral0,quadts->vec_sol);CHKERRQ(ierr); 724 } 725 th->status = TS_STEP_INCOMPLETE; 726 if (ts->mat_sensip) { 727 ierr = MatCopy(th->MatFwdSensip0,ts->mat_sensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 728 } 729 if (quadts && quadts->mat_sensip) { 730 ierr = MatCopy(th->MatIntegralSensip0,quadts->mat_sensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 731 } 732 PetscFunctionReturn(0); 733 } 734 735 static PetscErrorCode TSForwardStep_Theta(TS ts) 736 { 737 TS_Theta *th = (TS_Theta*)ts->data; 738 TS quadts = ts->quadraturets; 739 Mat MatDeltaFwdSensip = th->MatDeltaFwdSensip; 740 Vec VecDeltaFwdSensipCol = th->VecDeltaFwdSensipCol; 741 PetscInt ntlm; 742 KSP ksp; 743 Mat J,Jpre,quadJ = NULL,quadJp = NULL; 744 PetscScalar *barr,*xarr; 745 PetscErrorCode ierr; 746 747 PetscFunctionBegin; 748 ierr = MatCopy(ts->mat_sensip,th->MatFwdSensip0,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 749 750 if (quadts && quadts->mat_sensip) { 751 ierr = MatCopy(quadts->mat_sensip,th->MatIntegralSensip0,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 752 } 753 ierr = SNESGetKSP(ts->snes,&ksp);CHKERRQ(ierr); 754 ierr = TSGetIJacobian(ts,&J,&Jpre,NULL,NULL);CHKERRQ(ierr); 755 if (quadts) { 756 ierr = TSGetRHSJacobian(quadts,&quadJ,NULL,NULL,NULL);CHKERRQ(ierr); 757 ierr = TSGetRHSJacobianP(quadts,&quadJp,NULL,NULL);CHKERRQ(ierr); 758 } 759 760 /* Build RHS */ 761 if (th->endpoint) { /* 2-stage method*/ 762 th->shift = 1./((th->Theta-1.)*th->time_step); 763 ierr = TSComputeIJacobian(ts,th->ptime,th->X0,th->Xdot,th->shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr); 764 ierr = MatMatMult(J,ts->mat_sensip,MAT_REUSE_MATRIX,PETSC_DEFAULT,&MatDeltaFwdSensip);CHKERRQ(ierr); 765 ierr = MatScale(MatDeltaFwdSensip,(th->Theta-1.)/th->Theta);CHKERRQ(ierr); 766 767 /* Add the f_p forcing terms */ 768 if (ts->Jacp) { 769 ierr = TSComputeIJacobianP(ts,th->ptime,th->X0,th->Xdot,th->shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 770 ierr = MatAXPY(MatDeltaFwdSensip,(th->Theta-1.)/th->Theta,ts->Jacp,SUBSET_NONZERO_PATTERN);CHKERRQ(ierr); 771 ierr = TSComputeIJacobianP(ts,th->stage_time,ts->vec_sol,th->Xdot,th->shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 772 ierr = MatAXPY(MatDeltaFwdSensip,-1.,ts->Jacp,SUBSET_NONZERO_PATTERN);CHKERRQ(ierr); 773 } 774 } else { /* 1-stage method */ 775 th->shift = 0.0; 776 ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,th->shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr); 777 ierr = MatMatMult(J,ts->mat_sensip,MAT_REUSE_MATRIX,PETSC_DEFAULT,&MatDeltaFwdSensip);CHKERRQ(ierr); 778 ierr = MatScale(MatDeltaFwdSensip,-1.);CHKERRQ(ierr); 779 780 /* Add the f_p forcing terms */ 781 if (ts->Jacp) { 782 ierr = TSComputeIJacobianP(ts,th->stage_time,th->X,th->Xdot,th->shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 783 ierr = MatAXPY(MatDeltaFwdSensip,-1.,ts->Jacp,SUBSET_NONZERO_PATTERN);CHKERRQ(ierr); 784 } 785 } 786 787 /* Build LHS */ 788 th->shift = 1/(th->Theta*th->time_step); 789 if (th->endpoint) { 790 ierr = TSComputeIJacobian(ts,th->stage_time,ts->vec_sol,th->Xdot,th->shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr); 791 } else { 792 ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,th->shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr); 793 } 794 ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr); 795 796 /* 797 Evaluate the first stage of integral gradients with the 2-stage method: 798 drdu|t_n*S(t_n) + drdp|t_n 799 This is done before the linear solve because the sensitivity variable S(t_n) will be propagated to S(t_{n+1}) 800 */ 801 if (th->endpoint) { /* 2-stage method only */ 802 if (quadts && quadts->mat_sensip) { 803 ierr = TSComputeRHSJacobian(quadts,th->ptime,th->X0,quadJ,NULL);CHKERRQ(ierr); 804 ierr = TSComputeRHSJacobianP(quadts,th->ptime,th->X0,quadJp);CHKERRQ(ierr); 805 ierr = MatTransposeMatMult(ts->mat_sensip,quadJ,MAT_REUSE_MATRIX,PETSC_DEFAULT,&th->MatIntegralSensipTemp);CHKERRQ(ierr); 806 ierr = MatAXPY(th->MatIntegralSensipTemp,1,quadJp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 807 ierr = MatAXPY(quadts->mat_sensip,th->time_step*(1.-th->Theta),th->MatIntegralSensipTemp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 808 } 809 } 810 811 /* Solve the tangent linear equation for forward sensitivities to parameters */ 812 for (ntlm=0; ntlm<th->num_tlm; ntlm++) { 813 KSPConvergedReason kspreason; 814 ierr = MatDenseGetColumn(MatDeltaFwdSensip,ntlm,&barr);CHKERRQ(ierr); 815 ierr = VecPlaceArray(VecDeltaFwdSensipCol,barr);CHKERRQ(ierr); 816 if (th->endpoint) { 817 ierr = MatDenseGetColumn(ts->mat_sensip,ntlm,&xarr);CHKERRQ(ierr); 818 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 819 ierr = KSPSolve(ksp,VecDeltaFwdSensipCol,ts->vec_sensip_col);CHKERRQ(ierr); 820 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 821 ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr); 822 } else { 823 ierr = KSPSolve(ksp,VecDeltaFwdSensipCol,VecDeltaFwdSensipCol);CHKERRQ(ierr); 824 } 825 ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); 826 if (kspreason < 0) { 827 ts->reason = TSFORWARD_DIVERGED_LINEAR_SOLVE; 828 ierr = PetscInfo2(ts,"Step=%D, %Dth tangent linear solve, linear solve fails, stopping tangent linear solve\n",ts->steps,ntlm);CHKERRQ(ierr); 829 } 830 ierr = VecResetArray(VecDeltaFwdSensipCol);CHKERRQ(ierr); 831 ierr = MatDenseRestoreColumn(MatDeltaFwdSensip,&barr);CHKERRQ(ierr); 832 } 833 834 835 /* 836 Evaluate the second stage of integral gradients with the 2-stage method: 837 drdu|t_{n+1}*S(t_{n+1}) + drdp|t_{n+1} 838 */ 839 if (quadts && quadts->mat_sensip) { 840 if (!th->endpoint) { 841 ierr = MatAXPY(ts->mat_sensip,1,MatDeltaFwdSensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); /* stage sensitivity */ 842 ierr = TSComputeRHSJacobian(quadts,th->stage_time,th->X,quadJ,NULL);CHKERRQ(ierr); 843 ierr = TSComputeRHSJacobianP(quadts,th->stage_time,th->X,quadJp);CHKERRQ(ierr); 844 ierr = MatTransposeMatMult(ts->mat_sensip,quadJ,MAT_REUSE_MATRIX,PETSC_DEFAULT,&th->MatIntegralSensipTemp);CHKERRQ(ierr); 845 ierr = MatAXPY(th->MatIntegralSensipTemp,1,quadJp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 846 ierr = MatAXPY(quadts->mat_sensip,th->time_step,th->MatIntegralSensipTemp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 847 ierr = MatAXPY(ts->mat_sensip,(1.-th->Theta)/th->Theta,MatDeltaFwdSensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 848 } else { 849 ierr = TSComputeRHSJacobian(quadts,th->stage_time,ts->vec_sol,quadJ,NULL);CHKERRQ(ierr); 850 ierr = TSComputeRHSJacobianP(quadts,th->stage_time,ts->vec_sol,quadJp);CHKERRQ(ierr); 851 ierr = MatTransposeMatMult(ts->mat_sensip,quadJ,MAT_REUSE_MATRIX,PETSC_DEFAULT,&th->MatIntegralSensipTemp);CHKERRQ(ierr); 852 ierr = MatAXPY(th->MatIntegralSensipTemp,1,quadJp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 853 ierr = MatAXPY(quadts->mat_sensip,th->time_step*th->Theta,th->MatIntegralSensipTemp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 854 } 855 } else { 856 if (!th->endpoint) { 857 ierr = MatAXPY(ts->mat_sensip,1./th->Theta,MatDeltaFwdSensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 858 } 859 } 860 PetscFunctionReturn(0); 861 } 862 863 static PetscErrorCode TSForwardGetStages_Theta(TS ts,PetscInt *ns,Mat **stagesensip) 864 { 865 TS_Theta *th = (TS_Theta*)ts->data; 866 867 PetscFunctionBegin; 868 if (ns) *ns = 1; 869 if (stagesensip) *stagesensip = th->endpoint ? &(th->MatFwdSensip0) : &(th->MatDeltaFwdSensip); 870 PetscFunctionReturn(0); 871 } 872 873 /*------------------------------------------------------------*/ 874 static PetscErrorCode TSReset_Theta(TS ts) 875 { 876 TS_Theta *th = (TS_Theta*)ts->data; 877 PetscErrorCode ierr; 878 879 PetscFunctionBegin; 880 ierr = VecDestroy(&th->X);CHKERRQ(ierr); 881 ierr = VecDestroy(&th->Xdot);CHKERRQ(ierr); 882 ierr = VecDestroy(&th->X0);CHKERRQ(ierr); 883 ierr = VecDestroy(&th->affine);CHKERRQ(ierr); 884 885 ierr = VecDestroy(&th->vec_sol_prev);CHKERRQ(ierr); 886 ierr = VecDestroy(&th->vec_lte_work);CHKERRQ(ierr); 887 888 ierr = VecDestroy(&th->VecCostIntegral0);CHKERRQ(ierr); 889 PetscFunctionReturn(0); 890 } 891 892 static PetscErrorCode TSAdjointReset_Theta(TS ts) 893 { 894 TS_Theta *th = (TS_Theta*)ts->data; 895 PetscErrorCode ierr; 896 897 PetscFunctionBegin; 898 ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaLam);CHKERRQ(ierr); 899 ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaMu);CHKERRQ(ierr); 900 ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaLam2);CHKERRQ(ierr); 901 ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaMu2);CHKERRQ(ierr); 902 ierr = VecDestroyVecs(ts->numcost,&th->VecsSensiTemp);CHKERRQ(ierr); 903 ierr = VecDestroyVecs(ts->numcost,&th->VecsSensi2Temp);CHKERRQ(ierr); 904 PetscFunctionReturn(0); 905 } 906 907 static PetscErrorCode TSDestroy_Theta(TS ts) 908 { 909 PetscErrorCode ierr; 910 911 PetscFunctionBegin; 912 ierr = TSReset_Theta(ts);CHKERRQ(ierr); 913 if (ts->dm) { 914 ierr = DMCoarsenHookRemove(ts->dm,DMCoarsenHook_TSTheta,DMRestrictHook_TSTheta,ts);CHKERRQ(ierr); 915 ierr = DMSubDomainHookRemove(ts->dm,DMSubDomainHook_TSTheta,DMSubDomainRestrictHook_TSTheta,ts);CHKERRQ(ierr); 916 } 917 ierr = PetscFree(ts->data);CHKERRQ(ierr); 918 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetTheta_C",NULL);CHKERRQ(ierr); 919 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetTheta_C",NULL);CHKERRQ(ierr); 920 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetEndpoint_C",NULL);CHKERRQ(ierr); 921 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetEndpoint_C",NULL);CHKERRQ(ierr); 922 PetscFunctionReturn(0); 923 } 924 925 /* 926 This defines the nonlinear equation that is to be solved with SNES 927 G(U) = F[t0+Theta*dt, U, (U-U0)*shift] = 0 928 */ 929 static PetscErrorCode SNESTSFormFunction_Theta(SNES snes,Vec x,Vec y,TS ts) 930 { 931 TS_Theta *th = (TS_Theta*)ts->data; 932 PetscErrorCode ierr; 933 Vec X0,Xdot; 934 DM dm,dmsave; 935 PetscReal shift = th->shift; 936 937 PetscFunctionBegin; 938 ierr = SNESGetDM(snes,&dm);CHKERRQ(ierr); 939 /* When using the endpoint variant, this is actually 1/Theta * Xdot */ 940 ierr = TSThetaGetX0AndXdot(ts,dm,&X0,&Xdot);CHKERRQ(ierr); 941 if (x != X0) { 942 ierr = VecAXPBYPCZ(Xdot,-shift,shift,0,X0,x);CHKERRQ(ierr); 943 } else { 944 ierr = VecZeroEntries(Xdot);CHKERRQ(ierr); 945 } 946 /* DM monkey-business allows user code to call TSGetDM() inside of functions evaluated on levels of FAS */ 947 dmsave = ts->dm; 948 ts->dm = dm; 949 ierr = TSComputeIFunction(ts,th->stage_time,x,Xdot,y,PETSC_FALSE);CHKERRQ(ierr); 950 ts->dm = dmsave; 951 ierr = TSThetaRestoreX0AndXdot(ts,dm,&X0,&Xdot);CHKERRQ(ierr); 952 PetscFunctionReturn(0); 953 } 954 955 static PetscErrorCode SNESTSFormJacobian_Theta(SNES snes,Vec x,Mat A,Mat B,TS ts) 956 { 957 TS_Theta *th = (TS_Theta*)ts->data; 958 PetscErrorCode ierr; 959 Vec Xdot; 960 DM dm,dmsave; 961 PetscReal shift = th->shift; 962 963 PetscFunctionBegin; 964 ierr = SNESGetDM(snes,&dm);CHKERRQ(ierr); 965 /* Xdot has already been computed in SNESTSFormFunction_Theta (SNES guarantees this) */ 966 ierr = TSThetaGetX0AndXdot(ts,dm,NULL,&Xdot);CHKERRQ(ierr); 967 968 dmsave = ts->dm; 969 ts->dm = dm; 970 ierr = TSComputeIJacobian(ts,th->stage_time,x,Xdot,shift,A,B,PETSC_FALSE);CHKERRQ(ierr); 971 ts->dm = dmsave; 972 ierr = TSThetaRestoreX0AndXdot(ts,dm,NULL,&Xdot);CHKERRQ(ierr); 973 PetscFunctionReturn(0); 974 } 975 976 static PetscErrorCode TSForwardSetUp_Theta(TS ts) 977 { 978 TS_Theta *th = (TS_Theta*)ts->data; 979 TS quadts = ts->quadraturets; 980 PetscErrorCode ierr; 981 982 PetscFunctionBegin; 983 /* combine sensitivities to parameters and sensitivities to initial values into one array */ 984 th->num_tlm = ts->num_parameters; 985 ierr = MatDuplicate(ts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatDeltaFwdSensip);CHKERRQ(ierr); 986 if (quadts && quadts->mat_sensip) { 987 ierr = MatDuplicate(quadts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatIntegralSensipTemp);CHKERRQ(ierr); 988 ierr = MatDuplicate(quadts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatIntegralSensip0);CHKERRQ(ierr); 989 } 990 /* backup sensitivity results for roll-backs */ 991 ierr = MatDuplicate(ts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatFwdSensip0);CHKERRQ(ierr); 992 993 ierr = VecDuplicate(ts->vec_sol,&th->VecDeltaFwdSensipCol);CHKERRQ(ierr); 994 PetscFunctionReturn(0); 995 } 996 997 static PetscErrorCode TSForwardReset_Theta(TS ts) 998 { 999 TS_Theta *th = (TS_Theta*)ts->data; 1000 TS quadts = ts->quadraturets; 1001 PetscErrorCode ierr; 1002 1003 PetscFunctionBegin; 1004 if (quadts && quadts->mat_sensip) { 1005 ierr = MatDestroy(&th->MatIntegralSensipTemp);CHKERRQ(ierr); 1006 ierr = MatDestroy(&th->MatIntegralSensip0);CHKERRQ(ierr); 1007 } 1008 ierr = VecDestroy(&th->VecDeltaFwdSensipCol);CHKERRQ(ierr); 1009 ierr = MatDestroy(&th->MatDeltaFwdSensip);CHKERRQ(ierr); 1010 ierr = MatDestroy(&th->MatFwdSensip0);CHKERRQ(ierr); 1011 PetscFunctionReturn(0); 1012 } 1013 1014 static PetscErrorCode TSSetUp_Theta(TS ts) 1015 { 1016 TS_Theta *th = (TS_Theta*)ts->data; 1017 TS quadts = ts->quadraturets; 1018 PetscBool match; 1019 PetscErrorCode ierr; 1020 1021 PetscFunctionBegin; 1022 if (!th->VecCostIntegral0 && quadts && ts->costintegralfwd) { /* back up cost integral */ 1023 ierr = VecDuplicate(quadts->vec_sol,&th->VecCostIntegral0);CHKERRQ(ierr); 1024 } 1025 if (!th->X) { 1026 ierr = VecDuplicate(ts->vec_sol,&th->X);CHKERRQ(ierr); 1027 } 1028 if (!th->Xdot) { 1029 ierr = VecDuplicate(ts->vec_sol,&th->Xdot);CHKERRQ(ierr); 1030 } 1031 if (!th->X0) { 1032 ierr = VecDuplicate(ts->vec_sol,&th->X0);CHKERRQ(ierr); 1033 } 1034 if (th->endpoint) { 1035 ierr = VecDuplicate(ts->vec_sol,&th->affine);CHKERRQ(ierr); 1036 } 1037 1038 th->order = (th->Theta == 0.5) ? 2 : 1; 1039 1040 ierr = TSGetDM(ts,&ts->dm);CHKERRQ(ierr); 1041 ierr = DMCoarsenHookAdd(ts->dm,DMCoarsenHook_TSTheta,DMRestrictHook_TSTheta,ts);CHKERRQ(ierr); 1042 ierr = DMSubDomainHookAdd(ts->dm,DMSubDomainHook_TSTheta,DMSubDomainRestrictHook_TSTheta,ts);CHKERRQ(ierr); 1043 1044 ierr = TSGetAdapt(ts,&ts->adapt);CHKERRQ(ierr); 1045 ierr = TSAdaptCandidatesClear(ts->adapt);CHKERRQ(ierr); 1046 ierr = PetscObjectTypeCompare((PetscObject)ts->adapt,TSADAPTNONE,&match);CHKERRQ(ierr); 1047 if (!match) { 1048 ierr = VecDuplicate(ts->vec_sol,&th->vec_sol_prev);CHKERRQ(ierr); 1049 ierr = VecDuplicate(ts->vec_sol,&th->vec_lte_work);CHKERRQ(ierr); 1050 } 1051 ierr = TSGetSNES(ts,&ts->snes);CHKERRQ(ierr); 1052 PetscFunctionReturn(0); 1053 } 1054 1055 /*------------------------------------------------------------*/ 1056 1057 static PetscErrorCode TSAdjointSetUp_Theta(TS ts) 1058 { 1059 TS_Theta *th = (TS_Theta*)ts->data; 1060 PetscErrorCode ierr; 1061 1062 PetscFunctionBegin; 1063 ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&th->VecsDeltaLam);CHKERRQ(ierr); 1064 ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&th->VecsSensiTemp);CHKERRQ(ierr); 1065 if (ts->vecs_sensip) { 1066 ierr = VecDuplicateVecs(ts->vecs_sensip[0],ts->numcost,&th->VecsDeltaMu);CHKERRQ(ierr); 1067 } 1068 if (ts->vecs_sensi2) { 1069 ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&th->VecsDeltaLam2);CHKERRQ(ierr); 1070 ierr = VecDuplicateVecs(ts->vecs_sensi2[0],ts->numcost,&th->VecsSensi2Temp);CHKERRQ(ierr); 1071 /* hack ts to make implicit TS solver work when users provide only explicit versions of callbacks (RHSFunction,RHSJacobian,RHSHessian etc.) */ 1072 if (!ts->ihessianproduct_fuu) ts->vecs_fuu = ts->vecs_guu; 1073 if (!ts->ihessianproduct_fup) ts->vecs_fup = ts->vecs_gup; 1074 } 1075 if (ts->vecs_sensi2p) { 1076 ierr = VecDuplicateVecs(ts->vecs_sensi2p[0],ts->numcost,&th->VecsDeltaMu2);CHKERRQ(ierr); 1077 /* hack ts to make implicit TS solver work when users provide only explicit versions of callbacks (RHSFunction,RHSJacobian,RHSHessian etc.) */ 1078 if (!ts->ihessianproduct_fpu) ts->vecs_fpu = ts->vecs_gpu; 1079 if (!ts->ihessianproduct_fpp) ts->vecs_fpp = ts->vecs_gpp; 1080 } 1081 PetscFunctionReturn(0); 1082 } 1083 1084 static PetscErrorCode TSSetFromOptions_Theta(PetscOptionItems *PetscOptionsObject,TS ts) 1085 { 1086 TS_Theta *th = (TS_Theta*)ts->data; 1087 PetscErrorCode ierr; 1088 1089 PetscFunctionBegin; 1090 ierr = PetscOptionsHead(PetscOptionsObject,"Theta ODE solver options");CHKERRQ(ierr); 1091 { 1092 ierr = PetscOptionsReal("-ts_theta_theta","Location of stage (0<Theta<=1)","TSThetaSetTheta",th->Theta,&th->Theta,NULL);CHKERRQ(ierr); 1093 ierr = PetscOptionsBool("-ts_theta_endpoint","Use the endpoint instead of midpoint form of the Theta method","TSThetaSetEndpoint",th->endpoint,&th->endpoint,NULL);CHKERRQ(ierr); 1094 ierr = PetscOptionsBool("-ts_theta_initial_guess_extrapolate","Extrapolate stage initial guess from previous solution (sometimes unstable)","TSThetaSetExtrapolate",th->extrapolate,&th->extrapolate,NULL);CHKERRQ(ierr); 1095 } 1096 ierr = PetscOptionsTail();CHKERRQ(ierr); 1097 PetscFunctionReturn(0); 1098 } 1099 1100 static PetscErrorCode TSView_Theta(TS ts,PetscViewer viewer) 1101 { 1102 TS_Theta *th = (TS_Theta*)ts->data; 1103 PetscBool iascii; 1104 PetscErrorCode ierr; 1105 1106 PetscFunctionBegin; 1107 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1108 if (iascii) { 1109 ierr = PetscViewerASCIIPrintf(viewer," Theta=%g\n",(double)th->Theta);CHKERRQ(ierr); 1110 ierr = PetscViewerASCIIPrintf(viewer," Extrapolation=%s\n",th->extrapolate ? "yes" : "no");CHKERRQ(ierr); 1111 } 1112 PetscFunctionReturn(0); 1113 } 1114 1115 static PetscErrorCode TSThetaGetTheta_Theta(TS ts,PetscReal *theta) 1116 { 1117 TS_Theta *th = (TS_Theta*)ts->data; 1118 1119 PetscFunctionBegin; 1120 *theta = th->Theta; 1121 PetscFunctionReturn(0); 1122 } 1123 1124 static PetscErrorCode TSThetaSetTheta_Theta(TS ts,PetscReal theta) 1125 { 1126 TS_Theta *th = (TS_Theta*)ts->data; 1127 1128 PetscFunctionBegin; 1129 if (theta <= 0 || 1 < theta) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Theta %g not in range (0,1]",(double)theta); 1130 th->Theta = theta; 1131 th->order = (th->Theta == 0.5) ? 2 : 1; 1132 PetscFunctionReturn(0); 1133 } 1134 1135 static PetscErrorCode TSThetaGetEndpoint_Theta(TS ts,PetscBool *endpoint) 1136 { 1137 TS_Theta *th = (TS_Theta*)ts->data; 1138 1139 PetscFunctionBegin; 1140 *endpoint = th->endpoint; 1141 PetscFunctionReturn(0); 1142 } 1143 1144 static PetscErrorCode TSThetaSetEndpoint_Theta(TS ts,PetscBool flg) 1145 { 1146 TS_Theta *th = (TS_Theta*)ts->data; 1147 1148 PetscFunctionBegin; 1149 th->endpoint = flg; 1150 PetscFunctionReturn(0); 1151 } 1152 1153 #if defined(PETSC_HAVE_COMPLEX) 1154 static PetscErrorCode TSComputeLinearStability_Theta(TS ts,PetscReal xr,PetscReal xi,PetscReal *yr,PetscReal *yi) 1155 { 1156 PetscComplex z = xr + xi*PETSC_i,f; 1157 TS_Theta *th = (TS_Theta*)ts->data; 1158 const PetscReal one = 1.0; 1159 1160 PetscFunctionBegin; 1161 f = (one + (one - th->Theta)*z)/(one - th->Theta*z); 1162 *yr = PetscRealPartComplex(f); 1163 *yi = PetscImaginaryPartComplex(f); 1164 PetscFunctionReturn(0); 1165 } 1166 #endif 1167 1168 static PetscErrorCode TSGetStages_Theta(TS ts,PetscInt *ns,Vec **Y) 1169 { 1170 TS_Theta *th = (TS_Theta*)ts->data; 1171 1172 PetscFunctionBegin; 1173 if (ns) *ns = 1; 1174 if (Y) *Y = th->endpoint ? &(th->X0) : &(th->X); 1175 PetscFunctionReturn(0); 1176 } 1177 1178 /* ------------------------------------------------------------ */ 1179 /*MC 1180 TSTHETA - DAE solver using the implicit Theta method 1181 1182 Level: beginner 1183 1184 Options Database: 1185 + -ts_theta_theta <Theta> - Location of stage (0<Theta<=1) 1186 . -ts_theta_endpoint <flag> - Use the endpoint (like Crank-Nicholson) instead of midpoint form of the Theta method 1187 - -ts_theta_initial_guess_extrapolate <flg> - Extrapolate stage initial guess from previous solution (sometimes unstable) 1188 1189 Notes: 1190 $ -ts_type theta -ts_theta_theta 1.0 corresponds to backward Euler (TSBEULER) 1191 $ -ts_type theta -ts_theta_theta 0.5 corresponds to the implicit midpoint rule 1192 $ -ts_type theta -ts_theta_theta 0.5 -ts_theta_endpoint corresponds to Crank-Nicholson (TSCN) 1193 1194 This method can be applied to DAE. 1195 1196 This method is cast as a 1-stage implicit Runge-Kutta method. 1197 1198 .vb 1199 Theta | Theta 1200 ------------- 1201 | 1 1202 .ve 1203 1204 For the default Theta=0.5, this is also known as the implicit midpoint rule. 1205 1206 When the endpoint variant is chosen, the method becomes a 2-stage method with first stage explicit: 1207 1208 .vb 1209 0 | 0 0 1210 1 | 1-Theta Theta 1211 ------------------- 1212 | 1-Theta Theta 1213 .ve 1214 1215 For the default Theta=0.5, this is the trapezoid rule (also known as Crank-Nicolson, see TSCN). 1216 1217 To apply a diagonally implicit RK method to DAE, the stage formula 1218 1219 $ Y_i = X + h sum_j a_ij Y'_j 1220 1221 is interpreted as a formula for Y'_i in terms of Y_i and known values (Y'_j, j<i) 1222 1223 .seealso: TSCreate(), TS, TSSetType(), TSCN, TSBEULER, TSThetaSetTheta(), TSThetaSetEndpoint() 1224 1225 M*/ 1226 PETSC_EXTERN PetscErrorCode TSCreate_Theta(TS ts) 1227 { 1228 TS_Theta *th; 1229 PetscErrorCode ierr; 1230 1231 PetscFunctionBegin; 1232 ts->ops->reset = TSReset_Theta; 1233 ts->ops->adjointreset = TSAdjointReset_Theta; 1234 ts->ops->destroy = TSDestroy_Theta; 1235 ts->ops->view = TSView_Theta; 1236 ts->ops->setup = TSSetUp_Theta; 1237 ts->ops->adjointsetup = TSAdjointSetUp_Theta; 1238 ts->ops->adjointreset = TSAdjointReset_Theta; 1239 ts->ops->step = TSStep_Theta; 1240 ts->ops->interpolate = TSInterpolate_Theta; 1241 ts->ops->evaluatewlte = TSEvaluateWLTE_Theta; 1242 ts->ops->rollback = TSRollBack_Theta; 1243 ts->ops->setfromoptions = TSSetFromOptions_Theta; 1244 ts->ops->snesfunction = SNESTSFormFunction_Theta; 1245 ts->ops->snesjacobian = SNESTSFormJacobian_Theta; 1246 #if defined(PETSC_HAVE_COMPLEX) 1247 ts->ops->linearstability = TSComputeLinearStability_Theta; 1248 #endif 1249 ts->ops->getstages = TSGetStages_Theta; 1250 ts->ops->adjointstep = TSAdjointStep_Theta; 1251 ts->ops->adjointintegral = TSAdjointCostIntegral_Theta; 1252 ts->ops->forwardintegral = TSForwardCostIntegral_Theta; 1253 ts->default_adapt_type = TSADAPTNONE; 1254 1255 ts->ops->forwardsetup = TSForwardSetUp_Theta; 1256 ts->ops->forwardreset = TSForwardReset_Theta; 1257 ts->ops->forwardstep = TSForwardStep_Theta; 1258 ts->ops->forwardgetstages = TSForwardGetStages_Theta; 1259 1260 ts->usessnes = PETSC_TRUE; 1261 1262 ierr = PetscNewLog(ts,&th);CHKERRQ(ierr); 1263 ts->data = (void*)th; 1264 1265 th->VecsDeltaLam = NULL; 1266 th->VecsDeltaMu = NULL; 1267 th->VecsSensiTemp = NULL; 1268 th->VecsSensi2Temp = NULL; 1269 1270 th->extrapolate = PETSC_FALSE; 1271 th->Theta = 0.5; 1272 th->order = 2; 1273 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetTheta_C",TSThetaGetTheta_Theta);CHKERRQ(ierr); 1274 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetTheta_C",TSThetaSetTheta_Theta);CHKERRQ(ierr); 1275 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetEndpoint_C",TSThetaGetEndpoint_Theta);CHKERRQ(ierr); 1276 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetEndpoint_C",TSThetaSetEndpoint_Theta);CHKERRQ(ierr); 1277 PetscFunctionReturn(0); 1278 } 1279 1280 /*@ 1281 TSThetaGetTheta - Get the abscissa of the stage in (0,1]. 1282 1283 Not Collective 1284 1285 Input Parameter: 1286 . ts - timestepping context 1287 1288 Output Parameter: 1289 . theta - stage abscissa 1290 1291 Note: 1292 Use of this function is normally only required to hack TSTHETA to use a modified integration scheme. 1293 1294 Level: Advanced 1295 1296 .seealso: TSThetaSetTheta() 1297 @*/ 1298 PetscErrorCode TSThetaGetTheta(TS ts,PetscReal *theta) 1299 { 1300 PetscErrorCode ierr; 1301 1302 PetscFunctionBegin; 1303 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1304 PetscValidPointer(theta,2); 1305 ierr = PetscUseMethod(ts,"TSThetaGetTheta_C",(TS,PetscReal*),(ts,theta));CHKERRQ(ierr); 1306 PetscFunctionReturn(0); 1307 } 1308 1309 /*@ 1310 TSThetaSetTheta - Set the abscissa of the stage in (0,1]. 1311 1312 Not Collective 1313 1314 Input Parameter: 1315 + ts - timestepping context 1316 - theta - stage abscissa 1317 1318 Options Database: 1319 . -ts_theta_theta <theta> 1320 1321 Level: Intermediate 1322 1323 .seealso: TSThetaGetTheta() 1324 @*/ 1325 PetscErrorCode TSThetaSetTheta(TS ts,PetscReal theta) 1326 { 1327 PetscErrorCode ierr; 1328 1329 PetscFunctionBegin; 1330 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1331 ierr = PetscTryMethod(ts,"TSThetaSetTheta_C",(TS,PetscReal),(ts,theta));CHKERRQ(ierr); 1332 PetscFunctionReturn(0); 1333 } 1334 1335 /*@ 1336 TSThetaGetEndpoint - Gets whether to use the endpoint variant of the method (e.g. trapezoid/Crank-Nicolson instead of midpoint rule). 1337 1338 Not Collective 1339 1340 Input Parameter: 1341 . ts - timestepping context 1342 1343 Output Parameter: 1344 . endpoint - PETSC_TRUE when using the endpoint variant 1345 1346 Level: Advanced 1347 1348 .seealso: TSThetaSetEndpoint(), TSTHETA, TSCN 1349 @*/ 1350 PetscErrorCode TSThetaGetEndpoint(TS ts,PetscBool *endpoint) 1351 { 1352 PetscErrorCode ierr; 1353 1354 PetscFunctionBegin; 1355 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1356 PetscValidPointer(endpoint,2); 1357 ierr = PetscUseMethod(ts,"TSThetaGetEndpoint_C",(TS,PetscBool*),(ts,endpoint));CHKERRQ(ierr); 1358 PetscFunctionReturn(0); 1359 } 1360 1361 /*@ 1362 TSThetaSetEndpoint - Sets whether to use the endpoint variant of the method (e.g. trapezoid/Crank-Nicolson instead of midpoint rule). 1363 1364 Not Collective 1365 1366 Input Parameter: 1367 + ts - timestepping context 1368 - flg - PETSC_TRUE to use the endpoint variant 1369 1370 Options Database: 1371 . -ts_theta_endpoint <flg> 1372 1373 Level: Intermediate 1374 1375 .seealso: TSTHETA, TSCN 1376 @*/ 1377 PetscErrorCode TSThetaSetEndpoint(TS ts,PetscBool flg) 1378 { 1379 PetscErrorCode ierr; 1380 1381 PetscFunctionBegin; 1382 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1383 ierr = PetscTryMethod(ts,"TSThetaSetEndpoint_C",(TS,PetscBool),(ts,flg));CHKERRQ(ierr); 1384 PetscFunctionReturn(0); 1385 } 1386 1387 /* 1388 * TSBEULER and TSCN are straightforward specializations of TSTHETA. 1389 * The creation functions for these specializations are below. 1390 */ 1391 1392 static PetscErrorCode TSSetUp_BEuler(TS ts) 1393 { 1394 TS_Theta *th = (TS_Theta*)ts->data; 1395 PetscErrorCode ierr; 1396 1397 PetscFunctionBegin; 1398 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"); 1399 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"); 1400 ierr = TSSetUp_Theta(ts);CHKERRQ(ierr); 1401 PetscFunctionReturn(0); 1402 } 1403 1404 static PetscErrorCode TSView_BEuler(TS ts,PetscViewer viewer) 1405 { 1406 PetscFunctionBegin; 1407 PetscFunctionReturn(0); 1408 } 1409 1410 /*MC 1411 TSBEULER - ODE solver using the implicit backward Euler method 1412 1413 Level: beginner 1414 1415 Notes: 1416 TSBEULER is equivalent to TSTHETA with Theta=1.0 1417 1418 $ -ts_type theta -ts_theta_theta 1.0 1419 1420 .seealso: TSCreate(), TS, TSSetType(), TSEULER, TSCN, TSTHETA 1421 1422 M*/ 1423 PETSC_EXTERN PetscErrorCode TSCreate_BEuler(TS ts) 1424 { 1425 PetscErrorCode ierr; 1426 1427 PetscFunctionBegin; 1428 ierr = TSCreate_Theta(ts);CHKERRQ(ierr); 1429 ierr = TSThetaSetTheta(ts,1.0);CHKERRQ(ierr); 1430 ierr = TSThetaSetEndpoint(ts,PETSC_FALSE);CHKERRQ(ierr); 1431 ts->ops->setup = TSSetUp_BEuler; 1432 ts->ops->view = TSView_BEuler; 1433 PetscFunctionReturn(0); 1434 } 1435 1436 static PetscErrorCode TSSetUp_CN(TS ts) 1437 { 1438 TS_Theta *th = (TS_Theta*)ts->data; 1439 PetscErrorCode ierr; 1440 1441 PetscFunctionBegin; 1442 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"); 1443 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"); 1444 ierr = TSSetUp_Theta(ts);CHKERRQ(ierr); 1445 PetscFunctionReturn(0); 1446 } 1447 1448 static PetscErrorCode TSView_CN(TS ts,PetscViewer viewer) 1449 { 1450 PetscFunctionBegin; 1451 PetscFunctionReturn(0); 1452 } 1453 1454 /*MC 1455 TSCN - ODE solver using the implicit Crank-Nicolson method. 1456 1457 Level: beginner 1458 1459 Notes: 1460 TSCN is equivalent to TSTHETA with Theta=0.5 and the "endpoint" option set. I.e. 1461 1462 $ -ts_type theta -ts_theta_theta 0.5 -ts_theta_endpoint 1463 1464 .seealso: TSCreate(), TS, TSSetType(), TSBEULER, TSTHETA 1465 1466 M*/ 1467 PETSC_EXTERN PetscErrorCode TSCreate_CN(TS ts) 1468 { 1469 PetscErrorCode ierr; 1470 1471 PetscFunctionBegin; 1472 ierr = TSCreate_Theta(ts);CHKERRQ(ierr); 1473 ierr = TSThetaSetTheta(ts,0.5);CHKERRQ(ierr); 1474 ierr = TSThetaSetEndpoint(ts,PETSC_TRUE);CHKERRQ(ierr); 1475 ts->ops->setup = TSSetUp_CN; 1476 ts->ops->view = TSView_CN; 1477 PetscFunctionReturn(0); 1478 } 1479