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 /* 261 Use SNES to compute the Jacobian so that finite differencing could be used when TS Jacobian is not available. 262 */ 263 static PetscErrorCode KSPTSFormOperator_Private(KSP ksp,Vec x,Mat J,Mat Jpre,TS ts) 264 { 265 SNES snes = ts->snes; 266 MatFDColoring color; 267 PetscErrorCode ierr; 268 269 PetscFunctionBegin; 270 /* Force MatFDColoringApply to evaluate the SNES residual function for the base vector */ 271 ierr = PetscObjectQuery((PetscObject)Jpre,"SNESMatFDColoring",(PetscObject*)&color);CHKERRQ(ierr); 272 if (color) { 273 Vec f; 274 ierr = SNESGetFunction(snes,&f,NULL,NULL);CHKERRQ(ierr); 275 ierr = SNESComputeFunction(snes,x,f);CHKERRQ(ierr); 276 } 277 ierr = SNESComputeJacobian(snes,x,J,Jpre);CHKERRQ(ierr); 278 ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr); 279 PetscFunctionReturn(0); 280 } 281 282 static PetscErrorCode TSAdjointStepBEuler_Private(TS ts) 283 { 284 TS_Theta *th = (TS_Theta*)ts->data; 285 TS quadts = ts->quadraturets; 286 Vec *VecsDeltaLam = th->VecsDeltaLam,*VecsDeltaMu = th->VecsDeltaMu,*VecsSensiTemp = th->VecsSensiTemp; 287 Vec *VecsDeltaLam2 = th->VecsDeltaLam2,*VecsDeltaMu2 = th->VecsDeltaMu2,*VecsSensi2Temp = th->VecsSensi2Temp; 288 PetscInt nadj; 289 Mat J,Jpre,quadJ = NULL,quadJp = NULL; 290 KSP ksp; 291 PetscScalar *xarr; 292 TSEquationType eqtype; 293 PetscBool isexplicitode = PETSC_FALSE; 294 PetscErrorCode ierr; 295 296 PetscFunctionBegin; 297 ierr = TSGetEquationType(ts,&eqtype);CHKERRQ(ierr); 298 if (eqtype == TS_EQ_ODE_EXPLICIT) { 299 isexplicitode = PETSC_TRUE; 300 VecsDeltaLam = ts->vecs_sensi; 301 VecsDeltaLam2 = ts->vecs_sensi2; 302 } 303 th->status = TS_STEP_INCOMPLETE; 304 ierr = SNESGetKSP(ts->snes,&ksp);CHKERRQ(ierr); 305 ierr = TSGetIJacobian(ts,&J,&Jpre,NULL,NULL);CHKERRQ(ierr); 306 if (quadts) { 307 ierr = TSGetRHSJacobian(quadts,&quadJ,NULL,NULL,NULL);CHKERRQ(ierr); 308 ierr = TSGetRHSJacobianP(quadts,&quadJp,NULL,NULL);CHKERRQ(ierr); 309 } 310 311 /* If endpoint=1, th->ptime and th->X0 will be used; if endpoint=0, th->stage_time and th->X will be used. */ 312 th->stage_time = ts->ptime; /* time_step is negative*/ 313 th->ptime = ts->ptime + ts->time_step; 314 th->time_step = -ts->time_step; 315 316 /* Build RHS for first-order adjoint lambda_{n+1}/h + r_u^T(n+1) */ 317 if (quadts) { 318 ierr = TSComputeRHSJacobian(quadts,th->stage_time,th->X,quadJ,NULL);CHKERRQ(ierr); 319 } 320 321 for (nadj=0; nadj<ts->numcost; nadj++) { 322 ierr = VecCopy(ts->vecs_sensi[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr); 323 ierr = VecScale(VecsSensiTemp[nadj],1./th->time_step);CHKERRQ(ierr); /* lambda_{n+1}/h */ 324 if (quadJ) { 325 ierr = MatDenseGetColumn(quadJ,nadj,&xarr);CHKERRQ(ierr); 326 ierr = VecPlaceArray(ts->vec_drdu_col,xarr);CHKERRQ(ierr); 327 ierr = VecAXPY(VecsSensiTemp[nadj],1.,ts->vec_drdu_col);CHKERRQ(ierr); 328 ierr = VecResetArray(ts->vec_drdu_col);CHKERRQ(ierr); 329 ierr = MatDenseRestoreColumn(quadJ,&xarr);CHKERRQ(ierr); 330 } 331 } 332 333 /* Build LHS for first-order adjoint */ 334 ierr = KSPTSFormOperator_Private(ksp,th->X,J,Jpre,ts);CHKERRQ(ierr); 335 336 /* Solve stage equation LHS*lambda_s = RHS for first-order adjoint */ 337 for (nadj=0; nadj<ts->numcost; nadj++) { 338 KSPConvergedReason kspreason; 339 ierr = KSPSolveTranspose(ksp,VecsSensiTemp[nadj],VecsDeltaLam[nadj]);CHKERRQ(ierr); 340 ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); 341 if (kspreason < 0) { 342 ts->reason = TSADJOINT_DIVERGED_LINEAR_SOLVE; 343 ierr = PetscInfo2(ts,"Step=%D, %Dth cost function, transposed linear solve fails, stopping adjoint solve\n",ts->steps,nadj);CHKERRQ(ierr); 344 } 345 } 346 347 if (ts->vecs_sensi2) { /* U_{n+1} */ 348 /* Get w1 at t_{n+1} from TLM matrix */ 349 ierr = MatDenseGetColumn(ts->mat_sensip,0,&xarr);CHKERRQ(ierr); 350 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 351 /* lambda_s^T F_UU w_1 */ 352 ierr = TSComputeIHessianProductFunctionUU(ts,th->stage_time,th->X,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fuu);CHKERRQ(ierr); 353 /* lambda_s^T F_UP w_2 */ 354 ierr = TSComputeIHessianProductFunctionUP(ts,th->stage_time,th->X,VecsDeltaLam,ts->vec_dir,ts->vecs_fup);CHKERRQ(ierr); 355 for (nadj=0; nadj<ts->numcost; nadj++) { /* compute the residual */ 356 ierr = VecCopy(ts->vecs_sensi2[nadj],VecsSensi2Temp[nadj]);CHKERRQ(ierr); 357 ierr = VecScale(VecsSensi2Temp[nadj],1./th->time_step);CHKERRQ(ierr); 358 ierr = VecAXPY(VecsSensi2Temp[nadj],-1.,ts->vecs_fuu[nadj]);CHKERRQ(ierr); 359 if (ts->vecs_fup) { 360 ierr = VecAXPY(VecsSensi2Temp[nadj],-1.,ts->vecs_fup[nadj]);CHKERRQ(ierr); 361 } 362 } 363 /* Solve stage equation LHS X = RHS for second-order adjoint */ 364 for (nadj=0; nadj<ts->numcost; nadj++) { 365 KSPConvergedReason kspreason; 366 ierr = KSPSolveTranspose(ksp,VecsSensi2Temp[nadj],VecsDeltaLam2[nadj]);CHKERRQ(ierr); 367 ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); 368 if (kspreason < 0) { 369 ts->reason = TSADJOINT_DIVERGED_LINEAR_SOLVE; 370 ierr = PetscInfo2(ts,"Step=%D, %Dth cost function, transposed linear solve fails, stopping adjoint solve\n",ts->steps,nadj);CHKERRQ(ierr); 371 } 372 } 373 } 374 375 /* Update sensitivities, and evaluate integrals if there is any */ 376 if (!isexplicitode) { 377 th->shift = 0.0; 378 ierr = KSPTSFormOperator_Private(ksp,th->X,J,Jpre,ts);CHKERRQ(ierr); 379 ierr = MatScale(J,-1.);CHKERRQ(ierr); 380 for (nadj=0; nadj<ts->numcost; nadj++) { 381 /* Add f_U \lambda_s to the original RHS */ 382 ierr = MatMultTransposeAdd(J,VecsDeltaLam[nadj],VecsSensiTemp[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr); 383 ierr = VecScale(VecsSensiTemp[nadj],th->time_step);CHKERRQ(ierr); 384 ierr = VecCopy(VecsSensiTemp[nadj],ts->vecs_sensi[nadj]);CHKERRQ(ierr); 385 if (ts->vecs_sensi2) { 386 ierr = MatMultTransposeAdd(J,VecsDeltaLam2[nadj],VecsSensi2Temp[nadj],VecsSensi2Temp[nadj]);CHKERRQ(ierr); 387 ierr = VecScale(VecsSensi2Temp[nadj],th->time_step);CHKERRQ(ierr); 388 ierr = VecCopy(VecsSensi2Temp[nadj],ts->vecs_sensi2[nadj]);CHKERRQ(ierr); 389 } 390 } 391 } 392 if (ts->vecs_sensip) { 393 th->shift = 1./th->time_step;; 394 ierr = TSComputeIJacobianP(ts,th->stage_time,th->X,th->Xdot,th->shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); /* get -f_p */ 395 if (quadts) { 396 ierr = TSComputeRHSJacobianP(quadts,th->stage_time,th->X,quadJp);CHKERRQ(ierr); 397 } 398 if (ts->vecs_sensi2p) { 399 /* lambda_s^T F_PU w_1 */ 400 ierr = TSComputeIHessianProductFunctionPU(ts,th->stage_time,th->X,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fpu);CHKERRQ(ierr); 401 /* lambda_s^T F_PP w_2 */ 402 ierr = TSComputeIHessianProductFunctionPP(ts,th->stage_time,th->X,VecsDeltaLam,ts->vec_dir,ts->vecs_fpp);CHKERRQ(ierr); 403 } 404 405 for (nadj=0; nadj<ts->numcost; nadj++) { 406 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr); 407 ierr = VecAXPY(ts->vecs_sensip[nadj],-th->time_step,VecsDeltaMu[nadj]);CHKERRQ(ierr); 408 if (quadJp) { 409 ierr = MatDenseGetColumn(quadJp,nadj,&xarr);CHKERRQ(ierr); 410 ierr = VecPlaceArray(ts->vec_drdp_col,xarr);CHKERRQ(ierr); 411 ierr = VecAXPY(ts->vecs_sensip[nadj],th->time_step,ts->vec_drdp_col);CHKERRQ(ierr); 412 ierr = VecResetArray(ts->vec_drdp_col);CHKERRQ(ierr); 413 ierr = MatDenseRestoreColumn(quadJp,&xarr);CHKERRQ(ierr); 414 } 415 if (ts->vecs_sensi2p) { 416 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam2[nadj],VecsDeltaMu2[nadj]);CHKERRQ(ierr); 417 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step,VecsDeltaMu2[nadj]);CHKERRQ(ierr); 418 if (ts->vecs_fpu) { 419 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step,ts->vecs_fpu[nadj]);CHKERRQ(ierr); 420 } 421 if (ts->vecs_fpp) { 422 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step,ts->vecs_fpp[nadj]);CHKERRQ(ierr); 423 } 424 } 425 } 426 } 427 428 if (ts->vecs_sensi2) { 429 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 430 ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr); 431 } 432 th->status = TS_STEP_COMPLETE; 433 PetscFunctionReturn(0); 434 } 435 436 static PetscErrorCode TSAdjointStep_Theta(TS ts) 437 { 438 TS_Theta *th = (TS_Theta*)ts->data; 439 TS quadts = ts->quadraturets; 440 Vec *VecsDeltaLam = th->VecsDeltaLam,*VecsDeltaMu = th->VecsDeltaMu,*VecsSensiTemp = th->VecsSensiTemp; 441 Vec *VecsDeltaLam2 = th->VecsDeltaLam2,*VecsDeltaMu2 = th->VecsDeltaMu2,*VecsSensi2Temp = th->VecsSensi2Temp; 442 PetscInt nadj; 443 Mat J,Jpre,quadJ = NULL,quadJp = NULL; 444 KSP ksp; 445 PetscScalar *xarr; 446 PetscErrorCode ierr; 447 448 PetscFunctionBegin; 449 if (th->Theta == 1.) { 450 ierr = TSAdjointStepBEuler_Private(ts);CHKERRQ(ierr); 451 PetscFunctionReturn(0); 452 } 453 th->status = TS_STEP_INCOMPLETE; 454 ierr = SNESGetKSP(ts->snes,&ksp);CHKERRQ(ierr); 455 ierr = TSGetIJacobian(ts,&J,&Jpre,NULL,NULL);CHKERRQ(ierr); 456 if (quadts) { 457 ierr = TSGetRHSJacobian(quadts,&quadJ,NULL,NULL,NULL);CHKERRQ(ierr); 458 ierr = TSGetRHSJacobianP(quadts,&quadJp,NULL,NULL);CHKERRQ(ierr); 459 } 460 /* If endpoint=1, th->ptime and th->X0 will be used; if endpoint=0, th->stage_time and th->X will be used. */ 461 th->stage_time = th->endpoint ? ts->ptime : (ts->ptime+(1.-th->Theta)*ts->time_step); /* time_step is negative*/ 462 th->ptime = ts->ptime + ts->time_step; 463 th->time_step = -ts->time_step; 464 465 /* Build RHS for first-order adjoint */ 466 /* Cost function has an integral term */ 467 if (quadts) { 468 if (th->endpoint) { 469 ierr = TSComputeRHSJacobian(quadts,th->stage_time,ts->vec_sol,quadJ,NULL);CHKERRQ(ierr); 470 } else { 471 ierr = TSComputeRHSJacobian(quadts,th->stage_time,th->X,quadJ,NULL);CHKERRQ(ierr); 472 } 473 } 474 475 for (nadj=0; nadj<ts->numcost; nadj++) { 476 ierr = VecCopy(ts->vecs_sensi[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr); 477 ierr = VecScale(VecsSensiTemp[nadj],1./(th->Theta*th->time_step));CHKERRQ(ierr); 478 if (quadJ) { 479 ierr = MatDenseGetColumn(quadJ,nadj,&xarr);CHKERRQ(ierr); 480 ierr = VecPlaceArray(ts->vec_drdu_col,xarr);CHKERRQ(ierr); 481 ierr = VecAXPY(VecsSensiTemp[nadj],1.,ts->vec_drdu_col);CHKERRQ(ierr); 482 ierr = VecResetArray(ts->vec_drdu_col);CHKERRQ(ierr); 483 ierr = MatDenseRestoreColumn(quadJ,&xarr);CHKERRQ(ierr); 484 } 485 } 486 487 /* Build LHS for first-order adjoint */ 488 th->shift = 1./(th->Theta*th->time_step); 489 if (th->endpoint) { 490 ierr = TSComputeIJacobian(ts,th->stage_time,ts->vec_sol,th->Xdot,th->shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr); 491 } else { 492 ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,th->shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr); 493 } 494 ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr); 495 496 /* Solve stage equation LHS*lambda_s = RHS for first-order adjoint */ 497 for (nadj=0; nadj<ts->numcost; nadj++) { 498 KSPConvergedReason kspreason; 499 ierr = KSPSolveTranspose(ksp,VecsSensiTemp[nadj],VecsDeltaLam[nadj]);CHKERRQ(ierr); 500 ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); 501 if (kspreason < 0) { 502 ts->reason = TSADJOINT_DIVERGED_LINEAR_SOLVE; 503 ierr = PetscInfo2(ts,"Step=%D, %Dth cost function, transposed linear solve fails, stopping adjoint solve\n",ts->steps,nadj);CHKERRQ(ierr); 504 } 505 } 506 507 /* Second-order adjoint */ 508 if (ts->vecs_sensi2) { /* U_{n+1} */ 509 if (!th->endpoint) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Operation not implemented in TS_Theta"); 510 /* Get w1 at t_{n+1} from TLM matrix */ 511 ierr = MatDenseGetColumn(ts->mat_sensip,0,&xarr);CHKERRQ(ierr); 512 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 513 /* lambda_s^T F_UU w_1 */ 514 ierr = TSComputeIHessianProductFunctionUU(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fuu);CHKERRQ(ierr); 515 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 516 ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr); 517 /* lambda_s^T F_UP w_2 */ 518 ierr = TSComputeIHessianProductFunctionUP(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_dir,ts->vecs_fup);CHKERRQ(ierr); 519 for (nadj=0; nadj<ts->numcost; nadj++) { /* compute the residual */ 520 ierr = VecCopy(ts->vecs_sensi2[nadj],VecsSensi2Temp[nadj]);CHKERRQ(ierr); 521 ierr = VecScale(VecsSensi2Temp[nadj],th->shift);CHKERRQ(ierr); 522 ierr = VecAXPY(VecsSensi2Temp[nadj],-1.,ts->vecs_fuu[nadj]);CHKERRQ(ierr); 523 if (ts->vecs_fup) { 524 ierr = VecAXPY(VecsSensi2Temp[nadj],-1.,ts->vecs_fup[nadj]);CHKERRQ(ierr); 525 } 526 } 527 /* Solve stage equation LHS X = RHS for second-order adjoint */ 528 for (nadj=0; nadj<ts->numcost; nadj++) { 529 KSPConvergedReason kspreason; 530 ierr = KSPSolveTranspose(ksp,VecsSensi2Temp[nadj],VecsDeltaLam2[nadj]);CHKERRQ(ierr); 531 ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); 532 if (kspreason < 0) { 533 ts->reason = TSADJOINT_DIVERGED_LINEAR_SOLVE; 534 ierr = PetscInfo2(ts,"Step=%D, %Dth cost function, transposed linear solve fails, stopping adjoint solve\n",ts->steps,nadj);CHKERRQ(ierr); 535 } 536 } 537 } 538 539 /* Update sensitivities, and evaluate integrals if there is any */ 540 if(th->endpoint) { /* two-stage Theta methods with th->Theta!=1, th->Theta==1 leads to BEuler */ 541 th->shift = 1./((th->Theta-1.)*th->time_step); 542 ierr = TSComputeIJacobian(ts,th->ptime,th->X0,th->Xdot,th->shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr); 543 /* R_U at t_n */ 544 if (quadts) { 545 ierr = TSComputeRHSJacobian(quadts,th->ptime,th->X0,quadJ,NULL);CHKERRQ(ierr); 546 } 547 for (nadj=0; nadj<ts->numcost; nadj++) { 548 ierr = MatMultTranspose(J,VecsDeltaLam[nadj],ts->vecs_sensi[nadj]);CHKERRQ(ierr); 549 if (quadJ) { 550 ierr = MatDenseGetColumn(quadJ,nadj,&xarr);CHKERRQ(ierr); 551 ierr = VecPlaceArray(ts->vec_drdu_col,xarr);CHKERRQ(ierr); 552 ierr = VecAXPY(ts->vecs_sensi[nadj],-1.,ts->vec_drdu_col);CHKERRQ(ierr); 553 ierr = VecResetArray(ts->vec_drdu_col);CHKERRQ(ierr); 554 ierr = MatDenseRestoreColumn(quadJ,&xarr);CHKERRQ(ierr); 555 } 556 ierr = VecScale(ts->vecs_sensi[nadj],1./th->shift);CHKERRQ(ierr); 557 } 558 559 /* Second-order adjoint */ 560 if (ts->vecs_sensi2) { /* U_n */ 561 /* Get w1 at t_n from TLM matrix */ 562 ierr = MatDenseGetColumn(th->MatFwdSensip0,0,&xarr);CHKERRQ(ierr); 563 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 564 /* lambda_s^T F_UU w_1 */ 565 ierr = TSComputeIHessianProductFunctionUU(ts,th->ptime,th->X0,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fuu);CHKERRQ(ierr); 566 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 567 ierr = MatDenseRestoreColumn(th->MatFwdSensip0,&xarr);CHKERRQ(ierr); 568 /* lambda_s^T F_UU w_2 */ 569 ierr = TSComputeIHessianProductFunctionUP(ts,th->ptime,th->X0,VecsDeltaLam,ts->vec_dir,ts->vecs_fup);CHKERRQ(ierr); 570 for (nadj=0; nadj<ts->numcost; nadj++) { 571 /* 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 */ 572 ierr = MatMultTranspose(J,VecsDeltaLam2[nadj],ts->vecs_sensi2[nadj]);CHKERRQ(ierr); 573 ierr = VecAXPY(ts->vecs_sensi2[nadj],1.,ts->vecs_fuu[nadj]);CHKERRQ(ierr); 574 if (ts->vecs_fup) { 575 ierr = VecAXPY(ts->vecs_sensi2[nadj],1.,ts->vecs_fup[nadj]);CHKERRQ(ierr); 576 } 577 ierr = VecScale(ts->vecs_sensi2[nadj],1./th->shift);CHKERRQ(ierr); 578 } 579 } 580 581 if (ts->vecs_sensip) { /* sensitivities wrt parameters */ 582 /* U_{n+1} */ 583 th->shift = -1./(th->Theta*th->time_step); 584 ierr = TSComputeIJacobianP(ts,th->stage_time,ts->vec_sol,th->Xdot,th->shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 585 if (quadts) { 586 ierr = TSComputeRHSJacobianP(quadts,th->stage_time,ts->vec_sol,quadJp);CHKERRQ(ierr); 587 } 588 for (nadj=0; nadj<ts->numcost; nadj++) { 589 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr); 590 ierr = VecAXPY(ts->vecs_sensip[nadj],-th->time_step*th->Theta,VecsDeltaMu[nadj]);CHKERRQ(ierr); 591 } 592 if (ts->vecs_sensi2p) { /* second-order */ 593 /* Get w1 at t_{n+1} from TLM matrix */ 594 ierr = MatDenseGetColumn(ts->mat_sensip,0,&xarr);CHKERRQ(ierr); 595 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 596 /* lambda_s^T F_PU w_1 */ 597 ierr = TSComputeIHessianProductFunctionPU(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fpu);CHKERRQ(ierr); 598 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 599 ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr); 600 601 /* lambda_s^T F_PP w_2 */ 602 ierr = TSComputeIHessianProductFunctionPP(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_dir,ts->vecs_fpp);CHKERRQ(ierr); 603 for (nadj=0; nadj<ts->numcost; nadj++) { 604 /* 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) */ 605 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam2[nadj],VecsDeltaMu2[nadj]);CHKERRQ(ierr); 606 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step*th->Theta,VecsDeltaMu2[nadj]);CHKERRQ(ierr); 607 if (ts->vecs_fpu) { 608 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step*th->Theta,ts->vecs_fpu[nadj]);CHKERRQ(ierr); 609 } 610 if (ts->vecs_fpp) { 611 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step*th->Theta,ts->vecs_fpp[nadj]);CHKERRQ(ierr); 612 } 613 } 614 } 615 616 /* U_s */ 617 th->shift = 1./((th->Theta-1.0)*th->time_step); 618 ierr = TSComputeIJacobianP(ts,th->ptime,th->X0,th->Xdot,th->shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 619 if (quadts) { 620 ierr = TSComputeRHSJacobianP(quadts,th->ptime,th->X0,quadJp);CHKERRQ(ierr); 621 } 622 for (nadj=0; nadj<ts->numcost; nadj++) { 623 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr); 624 ierr = VecAXPY(ts->vecs_sensip[nadj],-th->time_step*(1.0-th->Theta),VecsDeltaMu[nadj]);CHKERRQ(ierr); 625 if (ts->vecs_sensi2p) { /* second-order */ 626 /* Get w1 at t_n from TLM matrix */ 627 ierr = MatDenseGetColumn(th->MatFwdSensip0,0,&xarr);CHKERRQ(ierr); 628 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 629 /* lambda_s^T F_PU w_1 */ 630 ierr = TSComputeIHessianProductFunctionPU(ts,th->ptime,th->X0,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fpu);CHKERRQ(ierr); 631 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 632 ierr = MatDenseRestoreColumn(th->MatFwdSensip0,&xarr);CHKERRQ(ierr); 633 /* lambda_s^T F_PP w_2 */ 634 ierr = TSComputeIHessianProductFunctionPP(ts,th->ptime,th->X0,VecsDeltaLam,ts->vec_dir,ts->vecs_fpp);CHKERRQ(ierr); 635 for (nadj=0; nadj<ts->numcost; nadj++) { 636 /* 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) */ 637 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam2[nadj],VecsDeltaMu2[nadj]);CHKERRQ(ierr); 638 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step*(1.0-th->Theta),VecsDeltaMu2[nadj]);CHKERRQ(ierr); 639 if (ts->vecs_fpu) { 640 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step*(1.0-th->Theta),ts->vecs_fpu[nadj]);CHKERRQ(ierr); 641 } 642 if (ts->vecs_fpp) { 643 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step*(1.0-th->Theta),ts->vecs_fpp[nadj]);CHKERRQ(ierr); 644 } 645 } 646 } 647 } 648 } 649 } else { /* one-stage case */ 650 th->shift = 0.0; 651 ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,th->shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr); /* get -f_y */ 652 if (quadts) { 653 ierr = TSComputeRHSJacobian(quadts,th->stage_time,th->X,quadJ,NULL);CHKERRQ(ierr); 654 } 655 for (nadj=0; nadj<ts->numcost; nadj++) { 656 ierr = MatMultTranspose(J,VecsDeltaLam[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr); 657 ierr = VecAXPY(ts->vecs_sensi[nadj],-th->time_step,VecsSensiTemp[nadj]);CHKERRQ(ierr); 658 if (quadJ) { 659 ierr = MatDenseGetColumn(quadJ,nadj,&xarr);CHKERRQ(ierr); 660 ierr = VecPlaceArray(ts->vec_drdu_col,xarr);CHKERRQ(ierr); 661 ierr = VecAXPY(ts->vecs_sensi[nadj],th->time_step,ts->vec_drdu_col);CHKERRQ(ierr); 662 ierr = VecResetArray(ts->vec_drdu_col);CHKERRQ(ierr); 663 ierr = MatDenseRestoreColumn(quadJ,&xarr);CHKERRQ(ierr); 664 } 665 } 666 if (ts->vecs_sensip) { 667 ierr = TSComputeIJacobianP(ts,th->stage_time,th->X,th->Xdot,th->shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 668 if (quadts) { 669 ierr = TSComputeRHSJacobianP(quadts,th->stage_time,th->X,quadJp);CHKERRQ(ierr); 670 } 671 for (nadj=0; nadj<ts->numcost; nadj++) { 672 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr); 673 ierr = VecAXPY(ts->vecs_sensip[nadj],-th->time_step,VecsDeltaMu[nadj]);CHKERRQ(ierr); 674 if (quadJp) { 675 ierr = MatDenseGetColumn(quadJp,nadj,&xarr);CHKERRQ(ierr); 676 ierr = VecPlaceArray(ts->vec_drdp_col,xarr);CHKERRQ(ierr); 677 ierr = VecAXPY(ts->vecs_sensip[nadj],th->time_step,ts->vec_drdp_col);CHKERRQ(ierr); 678 ierr = VecResetArray(ts->vec_drdp_col);CHKERRQ(ierr); 679 ierr = MatDenseRestoreColumn(quadJp,&xarr);CHKERRQ(ierr); 680 } 681 } 682 } 683 } 684 685 th->status = TS_STEP_COMPLETE; 686 PetscFunctionReturn(0); 687 } 688 689 static PetscErrorCode TSInterpolate_Theta(TS ts,PetscReal t,Vec X) 690 { 691 TS_Theta *th = (TS_Theta*)ts->data; 692 PetscReal dt = t - ts->ptime; 693 PetscErrorCode ierr; 694 695 PetscFunctionBegin; 696 ierr = VecCopy(ts->vec_sol,th->X);CHKERRQ(ierr); 697 if (th->endpoint) dt *= th->Theta; 698 ierr = VecWAXPY(X,dt,th->Xdot,th->X);CHKERRQ(ierr); 699 PetscFunctionReturn(0); 700 } 701 702 static PetscErrorCode TSEvaluateWLTE_Theta(TS ts,NormType wnormtype,PetscInt *order,PetscReal *wlte) 703 { 704 TS_Theta *th = (TS_Theta*)ts->data; 705 Vec X = ts->vec_sol; /* X = solution */ 706 Vec Y = th->vec_lte_work; /* Y = X + LTE */ 707 PetscReal wltea,wlter; 708 PetscErrorCode ierr; 709 710 PetscFunctionBegin; 711 if (!th->vec_sol_prev) {*wlte = -1; PetscFunctionReturn(0);} 712 /* Cannot compute LTE in first step or in restart after event */ 713 if (ts->steprestart) {*wlte = -1; PetscFunctionReturn(0);} 714 /* Compute LTE using backward differences with non-constant time step */ 715 { 716 PetscReal h = ts->time_step, h_prev = ts->ptime - ts->ptime_prev; 717 PetscReal a = 1 + h_prev/h; 718 PetscScalar scal[3]; Vec vecs[3]; 719 scal[0] = +1/a; scal[1] = -1/(a-1); scal[2] = +1/(a*(a-1)); 720 vecs[0] = X; vecs[1] = th->X0; vecs[2] = th->vec_sol_prev; 721 ierr = VecCopy(X,Y);CHKERRQ(ierr); 722 ierr = VecMAXPY(Y,3,scal,vecs);CHKERRQ(ierr); 723 ierr = TSErrorWeightedNorm(ts,X,Y,wnormtype,wlte,&wltea,&wlter);CHKERRQ(ierr); 724 } 725 if (order) *order = 2; 726 PetscFunctionReturn(0); 727 } 728 729 static PetscErrorCode TSRollBack_Theta(TS ts) 730 { 731 TS_Theta *th = (TS_Theta*)ts->data; 732 TS quadts = ts->quadraturets; 733 PetscErrorCode ierr; 734 735 PetscFunctionBegin; 736 ierr = VecCopy(th->X0,ts->vec_sol);CHKERRQ(ierr); 737 if (quadts && ts->costintegralfwd) { 738 ierr = VecCopy(th->VecCostIntegral0,quadts->vec_sol);CHKERRQ(ierr); 739 } 740 th->status = TS_STEP_INCOMPLETE; 741 if (ts->mat_sensip) { 742 ierr = MatCopy(th->MatFwdSensip0,ts->mat_sensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 743 } 744 if (quadts && quadts->mat_sensip) { 745 ierr = MatCopy(th->MatIntegralSensip0,quadts->mat_sensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 746 } 747 PetscFunctionReturn(0); 748 } 749 750 static PetscErrorCode TSForwardStep_Theta(TS ts) 751 { 752 TS_Theta *th = (TS_Theta*)ts->data; 753 TS quadts = ts->quadraturets; 754 Mat MatDeltaFwdSensip = th->MatDeltaFwdSensip; 755 Vec VecDeltaFwdSensipCol = th->VecDeltaFwdSensipCol; 756 PetscInt ntlm; 757 KSP ksp; 758 Mat J,Jpre,quadJ = NULL,quadJp = NULL; 759 PetscScalar *barr,*xarr; 760 PetscErrorCode ierr; 761 762 PetscFunctionBegin; 763 ierr = MatCopy(ts->mat_sensip,th->MatFwdSensip0,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 764 765 if (quadts && quadts->mat_sensip) { 766 ierr = MatCopy(quadts->mat_sensip,th->MatIntegralSensip0,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 767 } 768 ierr = SNESGetKSP(ts->snes,&ksp);CHKERRQ(ierr); 769 ierr = TSGetIJacobian(ts,&J,&Jpre,NULL,NULL);CHKERRQ(ierr); 770 if (quadts) { 771 ierr = TSGetRHSJacobian(quadts,&quadJ,NULL,NULL,NULL);CHKERRQ(ierr); 772 ierr = TSGetRHSJacobianP(quadts,&quadJp,NULL,NULL);CHKERRQ(ierr); 773 } 774 775 /* Build RHS */ 776 if (th->endpoint) { /* 2-stage method*/ 777 th->shift = 1./((th->Theta-1.)*th->time_step); 778 ierr = TSComputeIJacobian(ts,th->ptime,th->X0,th->Xdot,th->shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr); 779 ierr = MatMatMult(J,ts->mat_sensip,MAT_REUSE_MATRIX,PETSC_DEFAULT,&MatDeltaFwdSensip);CHKERRQ(ierr); 780 ierr = MatScale(MatDeltaFwdSensip,(th->Theta-1.)/th->Theta);CHKERRQ(ierr); 781 782 /* Add the f_p forcing terms */ 783 if (ts->Jacp) { 784 ierr = TSComputeIJacobianP(ts,th->ptime,th->X0,th->Xdot,th->shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 785 ierr = MatAXPY(MatDeltaFwdSensip,(th->Theta-1.)/th->Theta,ts->Jacp,SUBSET_NONZERO_PATTERN);CHKERRQ(ierr); 786 ierr = TSComputeIJacobianP(ts,th->stage_time,ts->vec_sol,th->Xdot,th->shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 787 ierr = MatAXPY(MatDeltaFwdSensip,-1.,ts->Jacp,SUBSET_NONZERO_PATTERN);CHKERRQ(ierr); 788 } 789 } else { /* 1-stage method */ 790 th->shift = 0.0; 791 ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,th->shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr); 792 ierr = MatMatMult(J,ts->mat_sensip,MAT_REUSE_MATRIX,PETSC_DEFAULT,&MatDeltaFwdSensip);CHKERRQ(ierr); 793 ierr = MatScale(MatDeltaFwdSensip,-1.);CHKERRQ(ierr); 794 795 /* Add the f_p forcing terms */ 796 if (ts->Jacp) { 797 ierr = TSComputeIJacobianP(ts,th->stage_time,th->X,th->Xdot,th->shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 798 ierr = MatAXPY(MatDeltaFwdSensip,-1.,ts->Jacp,SUBSET_NONZERO_PATTERN);CHKERRQ(ierr); 799 } 800 } 801 802 /* Build LHS */ 803 th->shift = 1/(th->Theta*th->time_step); 804 if (th->endpoint) { 805 ierr = TSComputeIJacobian(ts,th->stage_time,ts->vec_sol,th->Xdot,th->shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr); 806 } else { 807 ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,th->shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr); 808 } 809 ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr); 810 811 /* 812 Evaluate the first stage of integral gradients with the 2-stage method: 813 drdu|t_n*S(t_n) + drdp|t_n 814 This is done before the linear solve because the sensitivity variable S(t_n) will be propagated to S(t_{n+1}) 815 */ 816 if (th->endpoint) { /* 2-stage method only */ 817 if (quadts && quadts->mat_sensip) { 818 ierr = TSComputeRHSJacobian(quadts,th->ptime,th->X0,quadJ,NULL);CHKERRQ(ierr); 819 ierr = TSComputeRHSJacobianP(quadts,th->ptime,th->X0,quadJp);CHKERRQ(ierr); 820 ierr = MatTransposeMatMult(ts->mat_sensip,quadJ,MAT_REUSE_MATRIX,PETSC_DEFAULT,&th->MatIntegralSensipTemp);CHKERRQ(ierr); 821 ierr = MatAXPY(th->MatIntegralSensipTemp,1,quadJp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 822 ierr = MatAXPY(quadts->mat_sensip,th->time_step*(1.-th->Theta),th->MatIntegralSensipTemp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 823 } 824 } 825 826 /* Solve the tangent linear equation for forward sensitivities to parameters */ 827 for (ntlm=0; ntlm<th->num_tlm; ntlm++) { 828 KSPConvergedReason kspreason; 829 ierr = MatDenseGetColumn(MatDeltaFwdSensip,ntlm,&barr);CHKERRQ(ierr); 830 ierr = VecPlaceArray(VecDeltaFwdSensipCol,barr);CHKERRQ(ierr); 831 if (th->endpoint) { 832 ierr = MatDenseGetColumn(ts->mat_sensip,ntlm,&xarr);CHKERRQ(ierr); 833 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 834 ierr = KSPSolve(ksp,VecDeltaFwdSensipCol,ts->vec_sensip_col);CHKERRQ(ierr); 835 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 836 ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr); 837 } else { 838 ierr = KSPSolve(ksp,VecDeltaFwdSensipCol,VecDeltaFwdSensipCol);CHKERRQ(ierr); 839 } 840 ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); 841 if (kspreason < 0) { 842 ts->reason = TSFORWARD_DIVERGED_LINEAR_SOLVE; 843 ierr = PetscInfo2(ts,"Step=%D, %Dth tangent linear solve, linear solve fails, stopping tangent linear solve\n",ts->steps,ntlm);CHKERRQ(ierr); 844 } 845 ierr = VecResetArray(VecDeltaFwdSensipCol);CHKERRQ(ierr); 846 ierr = MatDenseRestoreColumn(MatDeltaFwdSensip,&barr);CHKERRQ(ierr); 847 } 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_step,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_step*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 static PetscErrorCode SNESTSFormFunction_Theta(SNES snes,Vec x,Vec y,TS ts) 945 { 946 TS_Theta *th = (TS_Theta*)ts->data; 947 PetscErrorCode ierr; 948 Vec X0,Xdot; 949 DM dm,dmsave; 950 PetscReal shift = th->shift; 951 952 PetscFunctionBegin; 953 ierr = SNESGetDM(snes,&dm);CHKERRQ(ierr); 954 /* When using the endpoint variant, this is actually 1/Theta * Xdot */ 955 ierr = TSThetaGetX0AndXdot(ts,dm,&X0,&Xdot);CHKERRQ(ierr); 956 ierr = VecAXPBYPCZ(Xdot,-shift,shift,0,X0,x);CHKERRQ(ierr); 957 958 /* DM monkey-business allows user code to call TSGetDM() inside of functions evaluated on levels of FAS */ 959 dmsave = ts->dm; 960 ts->dm = dm; 961 ierr = TSComputeIFunction(ts,th->stage_time,x,Xdot,y,PETSC_FALSE);CHKERRQ(ierr); 962 ts->dm = dmsave; 963 ierr = TSThetaRestoreX0AndXdot(ts,dm,&X0,&Xdot);CHKERRQ(ierr); 964 PetscFunctionReturn(0); 965 } 966 967 static PetscErrorCode SNESTSFormJacobian_Theta(SNES snes,Vec x,Mat A,Mat B,TS ts) 968 { 969 TS_Theta *th = (TS_Theta*)ts->data; 970 PetscErrorCode ierr; 971 Vec Xdot; 972 DM dm,dmsave; 973 PetscReal shift = th->shift; 974 975 PetscFunctionBegin; 976 ierr = SNESGetDM(snes,&dm);CHKERRQ(ierr); 977 /* Xdot has already been computed in SNESTSFormFunction_Theta (SNES guarantees this) */ 978 ierr = TSThetaGetX0AndXdot(ts,dm,NULL,&Xdot);CHKERRQ(ierr); 979 980 dmsave = ts->dm; 981 ts->dm = dm; 982 ierr = TSComputeIJacobian(ts,th->stage_time,x,Xdot,shift,A,B,PETSC_FALSE);CHKERRQ(ierr); 983 ts->dm = dmsave; 984 ierr = TSThetaRestoreX0AndXdot(ts,dm,NULL,&Xdot);CHKERRQ(ierr); 985 PetscFunctionReturn(0); 986 } 987 988 static PetscErrorCode TSForwardSetUp_Theta(TS ts) 989 { 990 TS_Theta *th = (TS_Theta*)ts->data; 991 TS quadts = ts->quadraturets; 992 PetscErrorCode ierr; 993 994 PetscFunctionBegin; 995 /* combine sensitivities to parameters and sensitivities to initial values into one array */ 996 th->num_tlm = ts->num_parameters; 997 ierr = MatDuplicate(ts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatDeltaFwdSensip);CHKERRQ(ierr); 998 if (quadts && quadts->mat_sensip) { 999 ierr = MatDuplicate(quadts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatIntegralSensipTemp);CHKERRQ(ierr); 1000 ierr = MatDuplicate(quadts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatIntegralSensip0);CHKERRQ(ierr); 1001 } 1002 /* backup sensitivity results for roll-backs */ 1003 ierr = MatDuplicate(ts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatFwdSensip0);CHKERRQ(ierr); 1004 1005 ierr = VecDuplicate(ts->vec_sol,&th->VecDeltaFwdSensipCol);CHKERRQ(ierr); 1006 PetscFunctionReturn(0); 1007 } 1008 1009 static PetscErrorCode TSForwardReset_Theta(TS ts) 1010 { 1011 TS_Theta *th = (TS_Theta*)ts->data; 1012 TS quadts = ts->quadraturets; 1013 PetscErrorCode ierr; 1014 1015 PetscFunctionBegin; 1016 if (quadts && quadts->mat_sensip) { 1017 ierr = MatDestroy(&th->MatIntegralSensipTemp);CHKERRQ(ierr); 1018 ierr = MatDestroy(&th->MatIntegralSensip0);CHKERRQ(ierr); 1019 } 1020 ierr = VecDestroy(&th->VecDeltaFwdSensipCol);CHKERRQ(ierr); 1021 ierr = MatDestroy(&th->MatDeltaFwdSensip);CHKERRQ(ierr); 1022 ierr = MatDestroy(&th->MatFwdSensip0);CHKERRQ(ierr); 1023 PetscFunctionReturn(0); 1024 } 1025 1026 static PetscErrorCode TSSetUp_Theta(TS ts) 1027 { 1028 TS_Theta *th = (TS_Theta*)ts->data; 1029 TS quadts = ts->quadraturets; 1030 PetscBool match; 1031 PetscErrorCode ierr; 1032 1033 PetscFunctionBegin; 1034 if (!th->VecCostIntegral0 && quadts && ts->costintegralfwd) { /* back up cost integral */ 1035 ierr = VecDuplicate(quadts->vec_sol,&th->VecCostIntegral0);CHKERRQ(ierr); 1036 } 1037 if (!th->X) { 1038 ierr = VecDuplicate(ts->vec_sol,&th->X);CHKERRQ(ierr); 1039 } 1040 if (!th->Xdot) { 1041 ierr = VecDuplicate(ts->vec_sol,&th->Xdot);CHKERRQ(ierr); 1042 } 1043 if (!th->X0) { 1044 ierr = VecDuplicate(ts->vec_sol,&th->X0);CHKERRQ(ierr); 1045 } 1046 if (th->endpoint) { 1047 ierr = VecDuplicate(ts->vec_sol,&th->affine);CHKERRQ(ierr); 1048 } 1049 1050 th->order = (th->Theta == 0.5) ? 2 : 1; 1051 1052 ierr = TSGetDM(ts,&ts->dm);CHKERRQ(ierr); 1053 ierr = DMCoarsenHookAdd(ts->dm,DMCoarsenHook_TSTheta,DMRestrictHook_TSTheta,ts);CHKERRQ(ierr); 1054 ierr = DMSubDomainHookAdd(ts->dm,DMSubDomainHook_TSTheta,DMSubDomainRestrictHook_TSTheta,ts);CHKERRQ(ierr); 1055 1056 ierr = TSGetAdapt(ts,&ts->adapt);CHKERRQ(ierr); 1057 ierr = TSAdaptCandidatesClear(ts->adapt);CHKERRQ(ierr); 1058 ierr = PetscObjectTypeCompare((PetscObject)ts->adapt,TSADAPTNONE,&match);CHKERRQ(ierr); 1059 if (!match) { 1060 ierr = VecDuplicate(ts->vec_sol,&th->vec_sol_prev);CHKERRQ(ierr); 1061 ierr = VecDuplicate(ts->vec_sol,&th->vec_lte_work);CHKERRQ(ierr); 1062 } 1063 ierr = TSGetSNES(ts,&ts->snes);CHKERRQ(ierr); 1064 PetscFunctionReturn(0); 1065 } 1066 1067 /*------------------------------------------------------------*/ 1068 1069 static PetscErrorCode TSAdjointSetUp_Theta(TS ts) 1070 { 1071 TS_Theta *th = (TS_Theta*)ts->data; 1072 PetscErrorCode ierr; 1073 1074 PetscFunctionBegin; 1075 ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&th->VecsDeltaLam);CHKERRQ(ierr); 1076 ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&th->VecsSensiTemp);CHKERRQ(ierr); 1077 if (ts->vecs_sensip) { 1078 ierr = VecDuplicateVecs(ts->vecs_sensip[0],ts->numcost,&th->VecsDeltaMu);CHKERRQ(ierr); 1079 } 1080 if (ts->vecs_sensi2) { 1081 ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&th->VecsDeltaLam2);CHKERRQ(ierr); 1082 ierr = VecDuplicateVecs(ts->vecs_sensi2[0],ts->numcost,&th->VecsSensi2Temp);CHKERRQ(ierr); 1083 /* hack ts to make implicit TS solver work when users provide only explicit versions of callbacks (RHSFunction,RHSJacobian,RHSHessian etc.) */ 1084 if (!ts->ihessianproduct_fuu) ts->vecs_fuu = ts->vecs_guu; 1085 if (!ts->ihessianproduct_fup) ts->vecs_fup = ts->vecs_gup; 1086 } 1087 if (ts->vecs_sensi2p) { 1088 ierr = VecDuplicateVecs(ts->vecs_sensi2p[0],ts->numcost,&th->VecsDeltaMu2);CHKERRQ(ierr); 1089 /* hack ts to make implicit TS solver work when users provide only explicit versions of callbacks (RHSFunction,RHSJacobian,RHSHessian etc.) */ 1090 if (!ts->ihessianproduct_fpu) ts->vecs_fpu = ts->vecs_gpu; 1091 if (!ts->ihessianproduct_fpp) ts->vecs_fpp = ts->vecs_gpp; 1092 } 1093 PetscFunctionReturn(0); 1094 } 1095 1096 static PetscErrorCode TSSetFromOptions_Theta(PetscOptionItems *PetscOptionsObject,TS ts) 1097 { 1098 TS_Theta *th = (TS_Theta*)ts->data; 1099 PetscErrorCode ierr; 1100 1101 PetscFunctionBegin; 1102 ierr = PetscOptionsHead(PetscOptionsObject,"Theta ODE solver options");CHKERRQ(ierr); 1103 { 1104 ierr = PetscOptionsReal("-ts_theta_theta","Location of stage (0<Theta<=1)","TSThetaSetTheta",th->Theta,&th->Theta,NULL);CHKERRQ(ierr); 1105 ierr = PetscOptionsBool("-ts_theta_endpoint","Use the endpoint instead of midpoint form of the Theta method","TSThetaSetEndpoint",th->endpoint,&th->endpoint,NULL);CHKERRQ(ierr); 1106 ierr = PetscOptionsBool("-ts_theta_initial_guess_extrapolate","Extrapolate stage initial guess from previous solution (sometimes unstable)","TSThetaSetExtrapolate",th->extrapolate,&th->extrapolate,NULL);CHKERRQ(ierr); 1107 } 1108 ierr = PetscOptionsTail();CHKERRQ(ierr); 1109 PetscFunctionReturn(0); 1110 } 1111 1112 static PetscErrorCode TSView_Theta(TS ts,PetscViewer viewer) 1113 { 1114 TS_Theta *th = (TS_Theta*)ts->data; 1115 PetscBool iascii; 1116 PetscErrorCode ierr; 1117 1118 PetscFunctionBegin; 1119 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1120 if (iascii) { 1121 ierr = PetscViewerASCIIPrintf(viewer," Theta=%g\n",(double)th->Theta);CHKERRQ(ierr); 1122 ierr = PetscViewerASCIIPrintf(viewer," Extrapolation=%s\n",th->extrapolate ? "yes" : "no");CHKERRQ(ierr); 1123 } 1124 PetscFunctionReturn(0); 1125 } 1126 1127 static PetscErrorCode TSThetaGetTheta_Theta(TS ts,PetscReal *theta) 1128 { 1129 TS_Theta *th = (TS_Theta*)ts->data; 1130 1131 PetscFunctionBegin; 1132 *theta = th->Theta; 1133 PetscFunctionReturn(0); 1134 } 1135 1136 static PetscErrorCode TSThetaSetTheta_Theta(TS ts,PetscReal theta) 1137 { 1138 TS_Theta *th = (TS_Theta*)ts->data; 1139 1140 PetscFunctionBegin; 1141 if (theta <= 0 || 1 < theta) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Theta %g not in range (0,1]",(double)theta); 1142 th->Theta = theta; 1143 th->order = (th->Theta == 0.5) ? 2 : 1; 1144 PetscFunctionReturn(0); 1145 } 1146 1147 static PetscErrorCode TSThetaGetEndpoint_Theta(TS ts,PetscBool *endpoint) 1148 { 1149 TS_Theta *th = (TS_Theta*)ts->data; 1150 1151 PetscFunctionBegin; 1152 *endpoint = th->endpoint; 1153 PetscFunctionReturn(0); 1154 } 1155 1156 static PetscErrorCode TSThetaSetEndpoint_Theta(TS ts,PetscBool flg) 1157 { 1158 TS_Theta *th = (TS_Theta*)ts->data; 1159 1160 PetscFunctionBegin; 1161 th->endpoint = flg; 1162 PetscFunctionReturn(0); 1163 } 1164 1165 #if defined(PETSC_HAVE_COMPLEX) 1166 static PetscErrorCode TSComputeLinearStability_Theta(TS ts,PetscReal xr,PetscReal xi,PetscReal *yr,PetscReal *yi) 1167 { 1168 PetscComplex z = xr + xi*PETSC_i,f; 1169 TS_Theta *th = (TS_Theta*)ts->data; 1170 const PetscReal one = 1.0; 1171 1172 PetscFunctionBegin; 1173 f = (one + (one - th->Theta)*z)/(one - th->Theta*z); 1174 *yr = PetscRealPartComplex(f); 1175 *yi = PetscImaginaryPartComplex(f); 1176 PetscFunctionReturn(0); 1177 } 1178 #endif 1179 1180 static PetscErrorCode TSGetStages_Theta(TS ts,PetscInt *ns,Vec **Y) 1181 { 1182 TS_Theta *th = (TS_Theta*)ts->data; 1183 1184 PetscFunctionBegin; 1185 if (ns) *ns = 1; 1186 if (Y) *Y = th->endpoint ? &(th->X0) : &(th->X); 1187 PetscFunctionReturn(0); 1188 } 1189 1190 /* ------------------------------------------------------------ */ 1191 /*MC 1192 TSTHETA - DAE solver using the implicit Theta method 1193 1194 Level: beginner 1195 1196 Options Database: 1197 + -ts_theta_theta <Theta> - Location of stage (0<Theta<=1) 1198 . -ts_theta_endpoint <flag> - Use the endpoint (like Crank-Nicholson) instead of midpoint form of the Theta method 1199 - -ts_theta_initial_guess_extrapolate <flg> - Extrapolate stage initial guess from previous solution (sometimes unstable) 1200 1201 Notes: 1202 $ -ts_type theta -ts_theta_theta 1.0 corresponds to backward Euler (TSBEULER) 1203 $ -ts_type theta -ts_theta_theta 0.5 corresponds to the implicit midpoint rule 1204 $ -ts_type theta -ts_theta_theta 0.5 -ts_theta_endpoint corresponds to Crank-Nicholson (TSCN) 1205 1206 This method can be applied to DAE. 1207 1208 This method is cast as a 1-stage implicit Runge-Kutta method. 1209 1210 .vb 1211 Theta | Theta 1212 ------------- 1213 | 1 1214 .ve 1215 1216 For the default Theta=0.5, this is also known as the implicit midpoint rule. 1217 1218 When the endpoint variant is chosen, the method becomes a 2-stage method with first stage explicit: 1219 1220 .vb 1221 0 | 0 0 1222 1 | 1-Theta Theta 1223 ------------------- 1224 | 1-Theta Theta 1225 .ve 1226 1227 For the default Theta=0.5, this is the trapezoid rule (also known as Crank-Nicolson, see TSCN). 1228 1229 To apply a diagonally implicit RK method to DAE, the stage formula 1230 1231 $ Y_i = X + h sum_j a_ij Y'_j 1232 1233 is interpreted as a formula for Y'_i in terms of Y_i and known values (Y'_j, j<i) 1234 1235 .seealso: TSCreate(), TS, TSSetType(), TSCN, TSBEULER, TSThetaSetTheta(), TSThetaSetEndpoint() 1236 1237 M*/ 1238 PETSC_EXTERN PetscErrorCode TSCreate_Theta(TS ts) 1239 { 1240 TS_Theta *th; 1241 PetscErrorCode ierr; 1242 1243 PetscFunctionBegin; 1244 ts->ops->reset = TSReset_Theta; 1245 ts->ops->adjointreset = TSAdjointReset_Theta; 1246 ts->ops->destroy = TSDestroy_Theta; 1247 ts->ops->view = TSView_Theta; 1248 ts->ops->setup = TSSetUp_Theta; 1249 ts->ops->adjointsetup = TSAdjointSetUp_Theta; 1250 ts->ops->adjointreset = TSAdjointReset_Theta; 1251 ts->ops->step = TSStep_Theta; 1252 ts->ops->interpolate = TSInterpolate_Theta; 1253 ts->ops->evaluatewlte = TSEvaluateWLTE_Theta; 1254 ts->ops->rollback = TSRollBack_Theta; 1255 ts->ops->setfromoptions = TSSetFromOptions_Theta; 1256 ts->ops->snesfunction = SNESTSFormFunction_Theta; 1257 ts->ops->snesjacobian = SNESTSFormJacobian_Theta; 1258 #if defined(PETSC_HAVE_COMPLEX) 1259 ts->ops->linearstability = TSComputeLinearStability_Theta; 1260 #endif 1261 ts->ops->getstages = TSGetStages_Theta; 1262 ts->ops->adjointstep = TSAdjointStep_Theta; 1263 ts->ops->adjointintegral = TSAdjointCostIntegral_Theta; 1264 ts->ops->forwardintegral = TSForwardCostIntegral_Theta; 1265 ts->default_adapt_type = TSADAPTNONE; 1266 1267 ts->ops->forwardsetup = TSForwardSetUp_Theta; 1268 ts->ops->forwardreset = TSForwardReset_Theta; 1269 ts->ops->forwardstep = TSForwardStep_Theta; 1270 ts->ops->forwardgetstages = TSForwardGetStages_Theta; 1271 1272 ts->usessnes = PETSC_TRUE; 1273 1274 ierr = PetscNewLog(ts,&th);CHKERRQ(ierr); 1275 ts->data = (void*)th; 1276 1277 th->VecsDeltaLam = NULL; 1278 th->VecsDeltaMu = NULL; 1279 th->VecsSensiTemp = NULL; 1280 th->VecsSensi2Temp = NULL; 1281 1282 th->extrapolate = PETSC_FALSE; 1283 th->Theta = 0.5; 1284 th->order = 2; 1285 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetTheta_C",TSThetaGetTheta_Theta);CHKERRQ(ierr); 1286 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetTheta_C",TSThetaSetTheta_Theta);CHKERRQ(ierr); 1287 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetEndpoint_C",TSThetaGetEndpoint_Theta);CHKERRQ(ierr); 1288 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetEndpoint_C",TSThetaSetEndpoint_Theta);CHKERRQ(ierr); 1289 PetscFunctionReturn(0); 1290 } 1291 1292 /*@ 1293 TSThetaGetTheta - Get the abscissa of the stage in (0,1]. 1294 1295 Not Collective 1296 1297 Input Parameter: 1298 . ts - timestepping context 1299 1300 Output Parameter: 1301 . theta - stage abscissa 1302 1303 Note: 1304 Use of this function is normally only required to hack TSTHETA to use a modified integration scheme. 1305 1306 Level: Advanced 1307 1308 .seealso: TSThetaSetTheta() 1309 @*/ 1310 PetscErrorCode TSThetaGetTheta(TS ts,PetscReal *theta) 1311 { 1312 PetscErrorCode ierr; 1313 1314 PetscFunctionBegin; 1315 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1316 PetscValidPointer(theta,2); 1317 ierr = PetscUseMethod(ts,"TSThetaGetTheta_C",(TS,PetscReal*),(ts,theta));CHKERRQ(ierr); 1318 PetscFunctionReturn(0); 1319 } 1320 1321 /*@ 1322 TSThetaSetTheta - Set the abscissa of the stage in (0,1]. 1323 1324 Not Collective 1325 1326 Input Parameter: 1327 + ts - timestepping context 1328 - theta - stage abscissa 1329 1330 Options Database: 1331 . -ts_theta_theta <theta> 1332 1333 Level: Intermediate 1334 1335 .seealso: TSThetaGetTheta() 1336 @*/ 1337 PetscErrorCode TSThetaSetTheta(TS ts,PetscReal theta) 1338 { 1339 PetscErrorCode ierr; 1340 1341 PetscFunctionBegin; 1342 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1343 ierr = PetscTryMethod(ts,"TSThetaSetTheta_C",(TS,PetscReal),(ts,theta));CHKERRQ(ierr); 1344 PetscFunctionReturn(0); 1345 } 1346 1347 /*@ 1348 TSThetaGetEndpoint - Gets whether to use the endpoint variant of the method (e.g. trapezoid/Crank-Nicolson instead of midpoint rule). 1349 1350 Not Collective 1351 1352 Input Parameter: 1353 . ts - timestepping context 1354 1355 Output Parameter: 1356 . endpoint - PETSC_TRUE when using the endpoint variant 1357 1358 Level: Advanced 1359 1360 .seealso: TSThetaSetEndpoint(), TSTHETA, TSCN 1361 @*/ 1362 PetscErrorCode TSThetaGetEndpoint(TS ts,PetscBool *endpoint) 1363 { 1364 PetscErrorCode ierr; 1365 1366 PetscFunctionBegin; 1367 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1368 PetscValidPointer(endpoint,2); 1369 ierr = PetscUseMethod(ts,"TSThetaGetEndpoint_C",(TS,PetscBool*),(ts,endpoint));CHKERRQ(ierr); 1370 PetscFunctionReturn(0); 1371 } 1372 1373 /*@ 1374 TSThetaSetEndpoint - Sets whether to use the endpoint variant of the method (e.g. trapezoid/Crank-Nicolson instead of midpoint rule). 1375 1376 Not Collective 1377 1378 Input Parameter: 1379 + ts - timestepping context 1380 - flg - PETSC_TRUE to use the endpoint variant 1381 1382 Options Database: 1383 . -ts_theta_endpoint <flg> 1384 1385 Level: Intermediate 1386 1387 .seealso: TSTHETA, TSCN 1388 @*/ 1389 PetscErrorCode TSThetaSetEndpoint(TS ts,PetscBool flg) 1390 { 1391 PetscErrorCode ierr; 1392 1393 PetscFunctionBegin; 1394 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1395 ierr = PetscTryMethod(ts,"TSThetaSetEndpoint_C",(TS,PetscBool),(ts,flg));CHKERRQ(ierr); 1396 PetscFunctionReturn(0); 1397 } 1398 1399 /* 1400 * TSBEULER and TSCN are straightforward specializations of TSTHETA. 1401 * The creation functions for these specializations are below. 1402 */ 1403 1404 static PetscErrorCode TSSetUp_BEuler(TS ts) 1405 { 1406 TS_Theta *th = (TS_Theta*)ts->data; 1407 PetscErrorCode ierr; 1408 1409 PetscFunctionBegin; 1410 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"); 1411 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"); 1412 ierr = TSSetUp_Theta(ts);CHKERRQ(ierr); 1413 PetscFunctionReturn(0); 1414 } 1415 1416 static PetscErrorCode TSView_BEuler(TS ts,PetscViewer viewer) 1417 { 1418 PetscFunctionBegin; 1419 PetscFunctionReturn(0); 1420 } 1421 1422 /*MC 1423 TSBEULER - ODE solver using the implicit backward Euler method 1424 1425 Level: beginner 1426 1427 Notes: 1428 TSBEULER is equivalent to TSTHETA with Theta=1.0 1429 1430 $ -ts_type theta -ts_theta_theta 1.0 1431 1432 .seealso: TSCreate(), TS, TSSetType(), TSEULER, TSCN, TSTHETA 1433 1434 M*/ 1435 PETSC_EXTERN PetscErrorCode TSCreate_BEuler(TS ts) 1436 { 1437 PetscErrorCode ierr; 1438 1439 PetscFunctionBegin; 1440 ierr = TSCreate_Theta(ts);CHKERRQ(ierr); 1441 ierr = TSThetaSetTheta(ts,1.0);CHKERRQ(ierr); 1442 ierr = TSThetaSetEndpoint(ts,PETSC_FALSE);CHKERRQ(ierr); 1443 ts->ops->setup = TSSetUp_BEuler; 1444 ts->ops->view = TSView_BEuler; 1445 PetscFunctionReturn(0); 1446 } 1447 1448 static PetscErrorCode TSSetUp_CN(TS ts) 1449 { 1450 TS_Theta *th = (TS_Theta*)ts->data; 1451 PetscErrorCode ierr; 1452 1453 PetscFunctionBegin; 1454 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"); 1455 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"); 1456 ierr = TSSetUp_Theta(ts);CHKERRQ(ierr); 1457 PetscFunctionReturn(0); 1458 } 1459 1460 static PetscErrorCode TSView_CN(TS ts,PetscViewer viewer) 1461 { 1462 PetscFunctionBegin; 1463 PetscFunctionReturn(0); 1464 } 1465 1466 /*MC 1467 TSCN - ODE solver using the implicit Crank-Nicolson method. 1468 1469 Level: beginner 1470 1471 Notes: 1472 TSCN is equivalent to TSTHETA with Theta=0.5 and the "endpoint" option set. I.e. 1473 1474 $ -ts_type theta -ts_theta_theta 0.5 -ts_theta_endpoint 1475 1476 .seealso: TSCreate(), TS, TSSetType(), TSBEULER, TSTHETA 1477 1478 M*/ 1479 PETSC_EXTERN PetscErrorCode TSCreate_CN(TS ts) 1480 { 1481 PetscErrorCode ierr; 1482 1483 PetscFunctionBegin; 1484 ierr = TSCreate_Theta(ts);CHKERRQ(ierr); 1485 ierr = TSThetaSetTheta(ts,0.5);CHKERRQ(ierr); 1486 ierr = TSThetaSetEndpoint(ts,PETSC_TRUE);CHKERRQ(ierr); 1487 ts->ops->setup = TSSetUp_CN; 1488 ts->ops->view = TSView_CN; 1489 PetscFunctionReturn(0); 1490 } 1491