1 /* 2 Code for timestepping with implicit Theta method 3 */ 4 #include <petsc/private/tsimpl.h> /*I "petscts.h" I*/ 5 #include <petscsnes.h> 6 #include <petscdm.h> 7 #include <petscmat.h> 8 9 typedef struct { 10 /* context for time stepping */ 11 PetscReal stage_time; 12 Vec X0,X,Xdot; /* Storage for stages and time derivative */ 13 Vec affine; /* Affine vector needed for residual at beginning of step in endpoint formulation */ 14 PetscReal Theta; 15 PetscReal ptime; 16 PetscReal time_step; 17 PetscInt order; 18 PetscBool endpoint; 19 PetscBool extrapolate; 20 TSStepStatus status; 21 Vec VecCostIntegral0; /* Backup for roll-backs due to events */ 22 23 /* context for sensitivity analysis */ 24 PetscInt num_tlm; /* Total number of tangent linear equations */ 25 Vec *VecsDeltaLam; /* Increment of the adjoint sensitivity w.r.t IC at stage */ 26 Vec *VecsDeltaMu; /* Increment of the adjoint sensitivity w.r.t P at stage */ 27 Vec *VecsSensiTemp; /* Vector to be multiplied with Jacobian transpose */ 28 Mat MatDeltaFwdSensip; /* Increment of the forward sensitivity at stage */ 29 Vec VecDeltaFwdSensipCol; /* Working vector for holding one column of the sensitivity matrix */ 30 Mat MatFwdSensip0; /* backup for roll-backs due to events */ 31 Mat MatIntegralSensipTemp; /* Working vector for forward integral sensitivity */ 32 Mat MatIntegralSensip0; /* backup for roll-backs due to events */ 33 Vec *VecsDeltaLam2; /* Increment of the 2nd-order adjoint sensitivity w.r.t IC at stage */ 34 Vec *VecsDeltaMu2; /* Increment of the 2nd-order adjoint sensitivity w.r.t P at stage */ 35 Vec *VecsSensi2Temp; /* Working vectors that holds the residual for the second-order adjoint */ 36 Vec *VecsAffine; /* Working vectors to store residuals */ 37 /* context for error estimation */ 38 Vec vec_sol_prev; 39 Vec vec_lte_work; 40 } TS_Theta; 41 42 static PetscErrorCode TSThetaGetX0AndXdot(TS ts,DM dm,Vec *X0,Vec *Xdot) 43 { 44 TS_Theta *th = (TS_Theta*)ts->data; 45 PetscErrorCode ierr; 46 47 PetscFunctionBegin; 48 if (X0) { 49 if (dm && dm != ts->dm) { 50 ierr = DMGetNamedGlobalVector(dm,"TSTheta_X0",X0);CHKERRQ(ierr); 51 } else *X0 = ts->vec_sol; 52 } 53 if (Xdot) { 54 if (dm && dm != ts->dm) { 55 ierr = DMGetNamedGlobalVector(dm,"TSTheta_Xdot",Xdot);CHKERRQ(ierr); 56 } else *Xdot = th->Xdot; 57 } 58 PetscFunctionReturn(0); 59 } 60 61 static PetscErrorCode TSThetaRestoreX0AndXdot(TS ts,DM dm,Vec *X0,Vec *Xdot) 62 { 63 PetscErrorCode ierr; 64 65 PetscFunctionBegin; 66 if (X0) { 67 if (dm && dm != ts->dm) { 68 ierr = DMRestoreNamedGlobalVector(dm,"TSTheta_X0",X0);CHKERRQ(ierr); 69 } 70 } 71 if (Xdot) { 72 if (dm && dm != ts->dm) { 73 ierr = DMRestoreNamedGlobalVector(dm,"TSTheta_Xdot",Xdot);CHKERRQ(ierr); 74 } 75 } 76 PetscFunctionReturn(0); 77 } 78 79 static PetscErrorCode DMCoarsenHook_TSTheta(DM fine,DM coarse,void *ctx) 80 { 81 PetscFunctionBegin; 82 PetscFunctionReturn(0); 83 } 84 85 static PetscErrorCode DMRestrictHook_TSTheta(DM fine,Mat restrct,Vec rscale,Mat inject,DM coarse,void *ctx) 86 { 87 TS ts = (TS)ctx; 88 PetscErrorCode ierr; 89 Vec X0,Xdot,X0_c,Xdot_c; 90 91 PetscFunctionBegin; 92 ierr = TSThetaGetX0AndXdot(ts,fine,&X0,&Xdot);CHKERRQ(ierr); 93 ierr = TSThetaGetX0AndXdot(ts,coarse,&X0_c,&Xdot_c);CHKERRQ(ierr); 94 ierr = MatRestrict(restrct,X0,X0_c);CHKERRQ(ierr); 95 ierr = MatRestrict(restrct,Xdot,Xdot_c);CHKERRQ(ierr); 96 ierr = VecPointwiseMult(X0_c,rscale,X0_c);CHKERRQ(ierr); 97 ierr = VecPointwiseMult(Xdot_c,rscale,Xdot_c);CHKERRQ(ierr); 98 ierr = TSThetaRestoreX0AndXdot(ts,fine,&X0,&Xdot);CHKERRQ(ierr); 99 ierr = TSThetaRestoreX0AndXdot(ts,coarse,&X0_c,&Xdot_c);CHKERRQ(ierr); 100 PetscFunctionReturn(0); 101 } 102 103 static PetscErrorCode DMSubDomainHook_TSTheta(DM dm,DM subdm,void *ctx) 104 { 105 PetscFunctionBegin; 106 PetscFunctionReturn(0); 107 } 108 109 static PetscErrorCode DMSubDomainRestrictHook_TSTheta(DM dm,VecScatter gscat,VecScatter lscat,DM subdm,void *ctx) 110 { 111 TS ts = (TS)ctx; 112 PetscErrorCode ierr; 113 Vec X0,Xdot,X0_sub,Xdot_sub; 114 115 PetscFunctionBegin; 116 ierr = TSThetaGetX0AndXdot(ts,dm,&X0,&Xdot);CHKERRQ(ierr); 117 ierr = TSThetaGetX0AndXdot(ts,subdm,&X0_sub,&Xdot_sub);CHKERRQ(ierr); 118 119 ierr = VecScatterBegin(gscat,X0,X0_sub,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 120 ierr = VecScatterEnd(gscat,X0,X0_sub,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 121 122 ierr = VecScatterBegin(gscat,Xdot,Xdot_sub,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 123 ierr = VecScatterEnd(gscat,Xdot,Xdot_sub,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 124 125 ierr = TSThetaRestoreX0AndXdot(ts,dm,&X0,&Xdot);CHKERRQ(ierr); 126 ierr = TSThetaRestoreX0AndXdot(ts,subdm,&X0_sub,&Xdot_sub);CHKERRQ(ierr); 127 PetscFunctionReturn(0); 128 } 129 130 static PetscErrorCode TSThetaEvaluateCostIntegral(TS ts) 131 { 132 TS_Theta *th = (TS_Theta*)ts->data; 133 TS quadts = ts->quadraturets; 134 PetscErrorCode ierr; 135 136 PetscFunctionBegin; 137 if (th->endpoint) { 138 /* Evolve ts->vec_costintegral to compute integrals */ 139 if (th->Theta!=1.0) { 140 ierr = TSComputeRHSFunction(quadts,th->ptime,th->X0,ts->vec_costintegrand);CHKERRQ(ierr); 141 ierr = VecAXPY(quadts->vec_sol,th->time_step*(1.0-th->Theta),ts->vec_costintegrand);CHKERRQ(ierr); 142 } 143 ierr = TSComputeRHSFunction(quadts,ts->ptime,ts->vec_sol,ts->vec_costintegrand);CHKERRQ(ierr); 144 ierr = VecAXPY(quadts->vec_sol,th->time_step*th->Theta,ts->vec_costintegrand);CHKERRQ(ierr); 145 } else { 146 ierr = TSComputeRHSFunction(quadts,th->stage_time,th->X,ts->vec_costintegrand);CHKERRQ(ierr); 147 ierr = VecAXPY(quadts->vec_sol,th->time_step,ts->vec_costintegrand);CHKERRQ(ierr); 148 } 149 PetscFunctionReturn(0); 150 } 151 152 static PetscErrorCode TSForwardCostIntegral_Theta(TS ts) 153 { 154 TS_Theta *th = (TS_Theta*)ts->data; 155 TS quadts = ts->quadraturets; 156 PetscErrorCode ierr; 157 158 PetscFunctionBegin; 159 /* backup cost integral */ 160 ierr = VecCopy(quadts->vec_sol,th->VecCostIntegral0);CHKERRQ(ierr); 161 ierr = TSThetaEvaluateCostIntegral(ts);CHKERRQ(ierr); 162 PetscFunctionReturn(0); 163 } 164 165 static PetscErrorCode TSAdjointCostIntegral_Theta(TS ts) 166 { 167 PetscErrorCode ierr; 168 169 PetscFunctionBegin; 170 ierr = TSThetaEvaluateCostIntegral(ts);CHKERRQ(ierr); 171 PetscFunctionReturn(0); 172 } 173 174 static PetscErrorCode TSTheta_SNESSolve(TS ts,Vec b,Vec x) 175 { 176 PetscInt nits,lits; 177 PetscErrorCode ierr; 178 179 PetscFunctionBegin; 180 ierr = SNESSolve(ts->snes,b,x);CHKERRQ(ierr); 181 ierr = SNESGetIterationNumber(ts->snes,&nits);CHKERRQ(ierr); 182 ierr = SNESGetLinearSolveIterations(ts->snes,&lits);CHKERRQ(ierr); 183 ts->snes_its += nits; ts->ksp_its += lits; 184 PetscFunctionReturn(0); 185 } 186 187 static PetscErrorCode TSStep_Theta(TS ts) 188 { 189 TS_Theta *th = (TS_Theta*)ts->data; 190 PetscInt rejections = 0; 191 PetscBool stageok,accept = PETSC_TRUE; 192 PetscReal next_time_step = ts->time_step; 193 PetscErrorCode ierr; 194 195 PetscFunctionBegin; 196 if (!ts->steprollback) { 197 if (th->vec_sol_prev) { ierr = VecCopy(th->X0,th->vec_sol_prev);CHKERRQ(ierr); } 198 ierr = VecCopy(ts->vec_sol,th->X0);CHKERRQ(ierr); 199 } 200 201 th->status = TS_STEP_INCOMPLETE; 202 while (!ts->reason && th->status != TS_STEP_COMPLETE) { 203 204 PetscReal shift = 1/(th->Theta*ts->time_step); 205 th->stage_time = ts->ptime + (th->endpoint ? (PetscReal)1 : th->Theta)*ts->time_step; 206 207 ierr = VecCopy(th->X0,th->X);CHKERRQ(ierr); 208 if (th->extrapolate && !ts->steprestart) { 209 ierr = VecAXPY(th->X,1/shift,th->Xdot);CHKERRQ(ierr); 210 } 211 if (th->endpoint) { /* This formulation assumes linear time-independent mass matrix */ 212 if (!th->affine) {ierr = VecDuplicate(ts->vec_sol,&th->affine);CHKERRQ(ierr);} 213 ierr = VecZeroEntries(th->Xdot);CHKERRQ(ierr); 214 ierr = TSComputeIFunction(ts,ts->ptime,th->X0,th->Xdot,th->affine,PETSC_FALSE);CHKERRQ(ierr); 215 ierr = VecScale(th->affine,(th->Theta-1)/th->Theta);CHKERRQ(ierr); 216 } else if (th->affine) { /* Just in case th->endpoint is changed between calls to TSStep_Theta() */ 217 ierr = VecZeroEntries(th->affine);CHKERRQ(ierr); 218 } 219 ierr = TSPreStage(ts,th->stage_time);CHKERRQ(ierr); 220 ierr = TSTheta_SNESSolve(ts,th->affine,th->X);CHKERRQ(ierr); 221 ierr = TSPostStage(ts,th->stage_time,0,&th->X);CHKERRQ(ierr); 222 ierr = TSAdaptCheckStage(ts->adapt,ts,th->stage_time,th->X,&stageok);CHKERRQ(ierr); 223 if (!stageok) goto reject_step; 224 225 th->status = TS_STEP_PENDING; 226 if (th->endpoint) { 227 ierr = VecCopy(th->X,ts->vec_sol);CHKERRQ(ierr); 228 } else { 229 ierr = VecAXPBYPCZ(th->Xdot,-shift,shift,0,th->X0,th->X);CHKERRQ(ierr); 230 ierr = VecAXPY(ts->vec_sol,ts->time_step,th->Xdot);CHKERRQ(ierr); 231 } 232 ierr = TSAdaptChoose(ts->adapt,ts,ts->time_step,NULL,&next_time_step,&accept);CHKERRQ(ierr); 233 th->status = accept ? TS_STEP_COMPLETE : TS_STEP_INCOMPLETE; 234 if (!accept) { 235 ierr = VecCopy(th->X0,ts->vec_sol);CHKERRQ(ierr); 236 ts->time_step = next_time_step; 237 goto reject_step; 238 } 239 240 if (ts->forward_solve || ts->costintegralfwd) { /* Save the info for the later use in cost integral evaluation */ 241 th->ptime = ts->ptime; 242 th->time_step = ts->time_step; 243 } 244 245 ts->ptime += ts->time_step; 246 ts->time_step = next_time_step; 247 break; 248 249 reject_step: 250 ts->reject++; accept = PETSC_FALSE; 251 if (!ts->reason && ++rejections > ts->max_reject && ts->max_reject >= 0) { 252 ts->reason = TS_DIVERGED_STEP_REJECTED; 253 ierr = PetscInfo2(ts,"Step=%D, step rejections %D greater than current TS allowed, stopping solve\n",ts->steps,rejections);CHKERRQ(ierr); 254 } 255 } 256 PetscFunctionReturn(0); 257 } 258 259 /* 260 Use SNES to compute the Jacobian so that finite differencing could be used when TS Jacobian is not available. 261 */ 262 static PetscErrorCode KSPTSFormOperator_Private(KSP ksp,Vec x,Mat J,Mat Jpre,TS ts) 263 { 264 SNES snes = ts->snes; 265 MatFDColoring color; 266 PetscErrorCode ierr; 267 268 PetscFunctionBegin; 269 /* Force MatFDColoringApply to evaluate the SNES residual function for the base vector */ 270 ierr = PetscObjectQuery((PetscObject)Jpre,"SNESMatFDColoring",(PetscObject*)&color);CHKERRQ(ierr); 271 if (color) { 272 Vec f; 273 ierr = SNESGetFunction(snes,&f,NULL,NULL);CHKERRQ(ierr); 274 ierr = SNESComputeFunction(snes,x,f);CHKERRQ(ierr); 275 } 276 ierr = SNESComputeJacobian(snes,x,J,Jpre);CHKERRQ(ierr); 277 ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr); 278 PetscFunctionReturn(0); 279 } 280 281 static PetscErrorCode TSAdjointStepBEuler_Private(TS ts) 282 { 283 TS_Theta *th = (TS_Theta*)ts->data; 284 TS quadts = ts->quadraturets; 285 Vec *VecsDeltaLam = th->VecsDeltaLam,*VecsDeltaMu = th->VecsDeltaMu,*VecsSensiTemp = th->VecsSensiTemp; 286 Vec *VecsDeltaLam2 = th->VecsDeltaLam2,*VecsDeltaMu2 = th->VecsDeltaMu2,*VecsSensi2Temp = th->VecsSensi2Temp; 287 PetscInt nadj; 288 Mat J,Jpre,quadJ = NULL,quadJp = NULL; 289 KSP ksp; 290 PetscScalar *xarr; 291 TSEquationType eqtype; 292 PetscBool isexplicitode = PETSC_FALSE; 293 PetscErrorCode ierr; 294 295 PetscFunctionBegin; 296 ierr = TSGetEquationType(ts,&eqtype);CHKERRQ(ierr); 297 if (eqtype == TS_EQ_ODE_EXPLICIT) { 298 isexplicitode = PETSC_TRUE; 299 VecsDeltaLam = ts->vecs_sensi; 300 VecsDeltaLam2 = ts->vecs_sensi2; 301 } 302 th->status = TS_STEP_INCOMPLETE; 303 ierr = SNESGetKSP(ts->snes,&ksp);CHKERRQ(ierr); 304 ierr = TSGetIJacobian(ts,&J,&Jpre,NULL,NULL);CHKERRQ(ierr); 305 if (quadts) { 306 ierr = TSGetRHSJacobian(quadts,&quadJ,NULL,NULL,NULL);CHKERRQ(ierr); 307 ierr = TSGetRHSJacobianP(quadts,&quadJp,NULL,NULL);CHKERRQ(ierr); 308 } 309 310 /* If endpoint=1, th->ptime and th->X0 will be used; if endpoint=0, th->stage_time and th->X will be used. */ 311 th->stage_time = ts->ptime; /* time_step is negative*/ 312 th->ptime = ts->ptime + ts->time_step; 313 th->time_step = -ts->time_step; 314 315 /* Build RHS for first-order adjoint lambda_{n+1}/h + r_u^T(n+1) */ 316 if (quadts) { 317 ierr = TSComputeRHSJacobian(quadts,th->stage_time,th->X,quadJ,NULL);CHKERRQ(ierr); 318 } 319 320 for (nadj=0; nadj<ts->numcost; nadj++) { 321 ierr = VecCopy(ts->vecs_sensi[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr); 322 ierr = VecScale(VecsSensiTemp[nadj],1./th->time_step);CHKERRQ(ierr); /* lambda_{n+1}/h */ 323 if (quadJ) { 324 ierr = MatDenseGetColumn(quadJ,nadj,&xarr);CHKERRQ(ierr); 325 ierr = VecPlaceArray(ts->vec_drdu_col,xarr);CHKERRQ(ierr); 326 ierr = VecAXPY(VecsSensiTemp[nadj],1.,ts->vec_drdu_col);CHKERRQ(ierr); 327 ierr = VecResetArray(ts->vec_drdu_col);CHKERRQ(ierr); 328 ierr = MatDenseRestoreColumn(quadJ,&xarr);CHKERRQ(ierr); 329 } 330 } 331 332 /* Build LHS for first-order adjoint */ 333 ierr = KSPTSFormOperator_Private(ksp,th->X,J,Jpre,ts);CHKERRQ(ierr); 334 335 /* Solve stage equation LHS*lambda_s = RHS for first-order adjoint */ 336 for (nadj=0; nadj<ts->numcost; nadj++) { 337 KSPConvergedReason kspreason; 338 ierr = KSPSolveTranspose(ksp,VecsSensiTemp[nadj],VecsDeltaLam[nadj]);CHKERRQ(ierr); 339 ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); 340 if (kspreason < 0) { 341 ts->reason = TSADJOINT_DIVERGED_LINEAR_SOLVE; 342 ierr = PetscInfo2(ts,"Step=%D, %Dth cost function, transposed linear solve fails, stopping adjoint solve\n",ts->steps,nadj);CHKERRQ(ierr); 343 } 344 } 345 346 if (ts->vecs_sensi2) { /* U_{n+1} */ 347 /* Get w1 at t_{n+1} from TLM matrix */ 348 ierr = MatDenseGetColumn(ts->mat_sensip,0,&xarr);CHKERRQ(ierr); 349 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 350 /* lambda_s^T F_UU w_1 */ 351 ierr = TSComputeIHessianProductFunctionUU(ts,th->stage_time,th->X,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fuu);CHKERRQ(ierr); 352 /* lambda_s^T F_UP w_2 */ 353 ierr = TSComputeIHessianProductFunctionUP(ts,th->stage_time,th->X,VecsDeltaLam,ts->vec_dir,ts->vecs_fup);CHKERRQ(ierr); 354 for (nadj=0; nadj<ts->numcost; nadj++) { /* compute the residual */ 355 ierr = VecCopy(ts->vecs_sensi2[nadj],VecsSensi2Temp[nadj]);CHKERRQ(ierr); 356 ierr = VecScale(VecsSensi2Temp[nadj],1./th->time_step);CHKERRQ(ierr); 357 ierr = VecAXPY(VecsSensi2Temp[nadj],-1.,ts->vecs_fuu[nadj]);CHKERRQ(ierr); 358 if (ts->vecs_fup) { 359 ierr = VecAXPY(VecsSensi2Temp[nadj],-1.,ts->vecs_fup[nadj]);CHKERRQ(ierr); 360 } 361 } 362 /* Solve stage equation LHS X = RHS for second-order adjoint */ 363 for (nadj=0; nadj<ts->numcost; nadj++) { 364 KSPConvergedReason kspreason; 365 ierr = KSPSolveTranspose(ksp,VecsSensi2Temp[nadj],VecsDeltaLam2[nadj]);CHKERRQ(ierr); 366 ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); 367 if (kspreason < 0) { 368 ts->reason = TSADJOINT_DIVERGED_LINEAR_SOLVE; 369 ierr = PetscInfo2(ts,"Step=%D, %Dth cost function, transposed linear solve fails, stopping adjoint solve\n",ts->steps,nadj);CHKERRQ(ierr); 370 } 371 } 372 } 373 374 /* Update sensitivities, and evaluate integrals if there is any */ 375 if (!isexplicitode) { 376 PetscReal shift = 0.0; 377 ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr); /* get -f_U */ 378 ierr = MatScale(J,-1.);CHKERRQ(ierr); 379 for (nadj=0; nadj<ts->numcost; nadj++) { 380 /* Add f_U \lambda_s to the original RHS */ 381 ierr = MatMultTransposeAdd(J,VecsDeltaLam[nadj],VecsSensiTemp[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr); 382 ierr = VecScale(VecsSensiTemp[nadj],th->time_step);CHKERRQ(ierr); 383 ierr = VecCopy(VecsSensiTemp[nadj],ts->vecs_sensi[nadj]);CHKERRQ(ierr); 384 if (ts->vecs_sensi2) { 385 ierr = MatMultTransposeAdd(J,VecsDeltaLam2[nadj],VecsSensi2Temp[nadj],VecsSensi2Temp[nadj]);CHKERRQ(ierr); 386 ierr = VecScale(VecsSensi2Temp[nadj],th->time_step);CHKERRQ(ierr); 387 ierr = VecCopy(VecsSensi2Temp[nadj],ts->vecs_sensi2[nadj]);CHKERRQ(ierr); 388 } 389 } 390 } 391 if (ts->vecs_sensip) { 392 PetscReal shift = 1./th->time_step;; 393 ierr = TSComputeIJacobianP(ts,th->stage_time,th->X,th->Xdot,shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); /* get -f_p */ 394 if (quadts) { 395 ierr = TSComputeRHSJacobianP(quadts,th->stage_time,th->X,quadJp);CHKERRQ(ierr); 396 } 397 if (ts->vecs_sensi2p) { 398 /* lambda_s^T F_PU w_1 */ 399 ierr = TSComputeIHessianProductFunctionPU(ts,th->stage_time,th->X,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fpu);CHKERRQ(ierr); 400 /* lambda_s^T F_PP w_2 */ 401 ierr = TSComputeIHessianProductFunctionPP(ts,th->stage_time,th->X,VecsDeltaLam,ts->vec_dir,ts->vecs_fpp);CHKERRQ(ierr); 402 } 403 404 for (nadj=0; nadj<ts->numcost; nadj++) { 405 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr); 406 ierr = VecAXPY(ts->vecs_sensip[nadj],-th->time_step,VecsDeltaMu[nadj]);CHKERRQ(ierr); 407 if (quadJp) { 408 ierr = MatDenseGetColumn(quadJp,nadj,&xarr);CHKERRQ(ierr); 409 ierr = VecPlaceArray(ts->vec_drdp_col,xarr);CHKERRQ(ierr); 410 ierr = VecAXPY(ts->vecs_sensip[nadj],th->time_step,ts->vec_drdp_col);CHKERRQ(ierr); 411 ierr = VecResetArray(ts->vec_drdp_col);CHKERRQ(ierr); 412 ierr = MatDenseRestoreColumn(quadJp,&xarr);CHKERRQ(ierr); 413 } 414 if (ts->vecs_sensi2p) { 415 ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam2[nadj],VecsDeltaMu2[nadj]);CHKERRQ(ierr); 416 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step,VecsDeltaMu2[nadj]);CHKERRQ(ierr); 417 if (ts->vecs_fpu) { 418 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step,ts->vecs_fpu[nadj]);CHKERRQ(ierr); 419 } 420 if (ts->vecs_fpp) { 421 ierr = VecAXPY(ts->vecs_sensi2p[nadj],-th->time_step,ts->vecs_fpp[nadj]);CHKERRQ(ierr); 422 } 423 } 424 } 425 } 426 427 if (ts->vecs_sensi2) { 428 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 429 ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr); 430 } 431 th->status = TS_STEP_COMPLETE; 432 PetscFunctionReturn(0); 433 } 434 435 static PetscErrorCode TSAdjointStep_Theta(TS ts) 436 { 437 TS_Theta *th = (TS_Theta*)ts->data; 438 TS quadts = ts->quadraturets; 439 Vec *VecsDeltaLam = th->VecsDeltaLam,*VecsDeltaMu = th->VecsDeltaMu,*VecsSensiTemp = th->VecsSensiTemp; 440 Vec *VecsDeltaLam2 = th->VecsDeltaLam2,*VecsDeltaMu2 = th->VecsDeltaMu2,*VecsSensi2Temp = th->VecsSensi2Temp; 441 PetscInt nadj; 442 Mat J,Jpre,quadJ = NULL,quadJp = NULL; 443 KSP ksp; 444 PetscReal shift; 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 shift = 1./(th->Theta*th->time_step); 489 if (th->endpoint) { 490 ierr = TSComputeIJacobian(ts,th->stage_time,ts->vec_sol,th->Xdot,shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr); 491 } else { 492 ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,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],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 shift = 1./((th->Theta-1.)*th->time_step); 542 ierr = TSComputeIJacobian(ts,th->ptime,th->X0,th->Xdot,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./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./shift);CHKERRQ(ierr); 578 } 579 } 580 581 if (ts->vecs_sensip) { /* sensitivities wrt parameters */ 582 /* U_{n+1} */ 583 shift = -1./(th->Theta*th->time_step); 584 ierr = TSComputeIJacobianP(ts,th->stage_time,ts->vec_sol,th->Xdot,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 shift = 1./((th->Theta-1.0)*th->time_step); 618 ierr = TSComputeIJacobianP(ts,th->ptime,th->X0,th->Xdot,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 shift = 0.0; 651 ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,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,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 PetscReal shift; 760 PetscScalar *barr,*xarr; 761 PetscErrorCode ierr; 762 763 PetscFunctionBegin; 764 ierr = MatCopy(ts->mat_sensip,th->MatFwdSensip0,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 765 766 if (quadts && quadts->mat_sensip) { 767 ierr = MatCopy(quadts->mat_sensip,th->MatIntegralSensip0,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 768 } 769 ierr = SNESGetKSP(ts->snes,&ksp);CHKERRQ(ierr); 770 ierr = TSGetIJacobian(ts,&J,&Jpre,NULL,NULL);CHKERRQ(ierr); 771 if (quadts) { 772 ierr = TSGetRHSJacobian(quadts,&quadJ,NULL,NULL,NULL);CHKERRQ(ierr); 773 ierr = TSGetRHSJacobianP(quadts,&quadJp,NULL,NULL);CHKERRQ(ierr); 774 } 775 776 /* Build RHS */ 777 if (th->endpoint) { /* 2-stage method*/ 778 shift = 1./((th->Theta-1.)*th->time_step); 779 ierr = TSComputeIJacobian(ts,th->ptime,th->X0,th->Xdot,shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr); 780 ierr = MatMatMult(J,ts->mat_sensip,MAT_REUSE_MATRIX,PETSC_DEFAULT,&MatDeltaFwdSensip);CHKERRQ(ierr); 781 ierr = MatScale(MatDeltaFwdSensip,(th->Theta-1.)/th->Theta);CHKERRQ(ierr); 782 783 /* Add the f_p forcing terms */ 784 if (ts->Jacp) { 785 ierr = TSComputeIJacobianP(ts,th->ptime,th->X0,th->Xdot,shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 786 ierr = MatAXPY(MatDeltaFwdSensip,(th->Theta-1.)/th->Theta,ts->Jacp,SUBSET_NONZERO_PATTERN);CHKERRQ(ierr); 787 ierr = TSComputeIJacobianP(ts,th->stage_time,ts->vec_sol,th->Xdot,shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 788 ierr = MatAXPY(MatDeltaFwdSensip,-1.,ts->Jacp,SUBSET_NONZERO_PATTERN);CHKERRQ(ierr); 789 } 790 } else { /* 1-stage method */ 791 shift = 0.0; 792 ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr); 793 ierr = MatMatMult(J,ts->mat_sensip,MAT_REUSE_MATRIX,PETSC_DEFAULT,&MatDeltaFwdSensip);CHKERRQ(ierr); 794 ierr = MatScale(MatDeltaFwdSensip,-1.);CHKERRQ(ierr); 795 796 /* Add the f_p forcing terms */ 797 if (ts->Jacp) { 798 ierr = TSComputeIJacobianP(ts,th->stage_time,th->X,th->Xdot,shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); 799 ierr = MatAXPY(MatDeltaFwdSensip,-1.,ts->Jacp,SUBSET_NONZERO_PATTERN);CHKERRQ(ierr); 800 } 801 } 802 803 /* Build LHS */ 804 shift = 1/(th->Theta*th->time_step); 805 if (th->endpoint) { 806 ierr = TSComputeIJacobian(ts,th->stage_time,ts->vec_sol,th->Xdot,shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr); 807 } else { 808 ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr); 809 } 810 ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr); 811 812 /* 813 Evaluate the first stage of integral gradients with the 2-stage method: 814 drdu|t_n*S(t_n) + drdp|t_n 815 This is done before the linear solve because the sensitivity variable S(t_n) will be propagated to S(t_{n+1}) 816 */ 817 if (th->endpoint) { /* 2-stage method only */ 818 if (quadts && quadts->mat_sensip) { 819 ierr = TSComputeRHSJacobian(quadts,th->ptime,th->X0,quadJ,NULL);CHKERRQ(ierr); 820 ierr = TSComputeRHSJacobianP(quadts,th->ptime,th->X0,quadJp);CHKERRQ(ierr); 821 ierr = MatTransposeMatMult(ts->mat_sensip,quadJ,MAT_REUSE_MATRIX,PETSC_DEFAULT,&th->MatIntegralSensipTemp);CHKERRQ(ierr); 822 ierr = MatAXPY(th->MatIntegralSensipTemp,1,quadJp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 823 ierr = MatAXPY(quadts->mat_sensip,th->time_step*(1.-th->Theta),th->MatIntegralSensipTemp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 824 } 825 } 826 827 /* Solve the tangent linear equation for forward sensitivities to parameters */ 828 for (ntlm=0; ntlm<th->num_tlm; ntlm++) { 829 KSPConvergedReason kspreason; 830 ierr = MatDenseGetColumn(MatDeltaFwdSensip,ntlm,&barr);CHKERRQ(ierr); 831 ierr = VecPlaceArray(VecDeltaFwdSensipCol,barr);CHKERRQ(ierr); 832 if (th->endpoint) { 833 ierr = MatDenseGetColumn(ts->mat_sensip,ntlm,&xarr);CHKERRQ(ierr); 834 ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); 835 ierr = KSPSolve(ksp,VecDeltaFwdSensipCol,ts->vec_sensip_col);CHKERRQ(ierr); 836 ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); 837 ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr); 838 } else { 839 ierr = KSPSolve(ksp,VecDeltaFwdSensipCol,VecDeltaFwdSensipCol);CHKERRQ(ierr); 840 } 841 ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); 842 if (kspreason < 0) { 843 ts->reason = TSFORWARD_DIVERGED_LINEAR_SOLVE; 844 ierr = PetscInfo2(ts,"Step=%D, %Dth tangent linear solve, linear solve fails, stopping tangent linear solve\n",ts->steps,ntlm);CHKERRQ(ierr); 845 } 846 ierr = VecResetArray(VecDeltaFwdSensipCol);CHKERRQ(ierr); 847 ierr = MatDenseRestoreColumn(MatDeltaFwdSensip,&barr);CHKERRQ(ierr); 848 } 849 850 851 /* 852 Evaluate the second stage of integral gradients with the 2-stage method: 853 drdu|t_{n+1}*S(t_{n+1}) + drdp|t_{n+1} 854 */ 855 if (quadts && quadts->mat_sensip) { 856 if (!th->endpoint) { 857 ierr = MatAXPY(ts->mat_sensip,1,MatDeltaFwdSensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); /* stage sensitivity */ 858 ierr = TSComputeRHSJacobian(quadts,th->stage_time,th->X,quadJ,NULL);CHKERRQ(ierr); 859 ierr = TSComputeRHSJacobianP(quadts,th->stage_time,th->X,quadJp);CHKERRQ(ierr); 860 ierr = MatTransposeMatMult(ts->mat_sensip,quadJ,MAT_REUSE_MATRIX,PETSC_DEFAULT,&th->MatIntegralSensipTemp);CHKERRQ(ierr); 861 ierr = MatAXPY(th->MatIntegralSensipTemp,1,quadJp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 862 ierr = MatAXPY(quadts->mat_sensip,th->time_step,th->MatIntegralSensipTemp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 863 ierr = MatAXPY(ts->mat_sensip,(1.-th->Theta)/th->Theta,MatDeltaFwdSensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 864 } else { 865 ierr = TSComputeRHSJacobian(quadts,th->stage_time,ts->vec_sol,quadJ,NULL);CHKERRQ(ierr); 866 ierr = TSComputeRHSJacobianP(quadts,th->stage_time,ts->vec_sol,quadJp);CHKERRQ(ierr); 867 ierr = MatTransposeMatMult(ts->mat_sensip,quadJ,MAT_REUSE_MATRIX,PETSC_DEFAULT,&th->MatIntegralSensipTemp);CHKERRQ(ierr); 868 ierr = MatAXPY(th->MatIntegralSensipTemp,1,quadJp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 869 ierr = MatAXPY(quadts->mat_sensip,th->time_step*th->Theta,th->MatIntegralSensipTemp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 870 } 871 } else { 872 if (!th->endpoint) { 873 ierr = MatAXPY(ts->mat_sensip,1./th->Theta,MatDeltaFwdSensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 874 } 875 } 876 PetscFunctionReturn(0); 877 } 878 879 static PetscErrorCode TSForwardGetStages_Theta(TS ts,PetscInt *ns,Mat **stagesensip) 880 { 881 TS_Theta *th = (TS_Theta*)ts->data; 882 883 PetscFunctionBegin; 884 if (ns) *ns = 1; 885 if (stagesensip) *stagesensip = th->endpoint ? &(th->MatFwdSensip0) : &(th->MatDeltaFwdSensip); 886 PetscFunctionReturn(0); 887 } 888 889 /*------------------------------------------------------------*/ 890 static PetscErrorCode TSReset_Theta(TS ts) 891 { 892 TS_Theta *th = (TS_Theta*)ts->data; 893 PetscErrorCode ierr; 894 895 PetscFunctionBegin; 896 ierr = VecDestroy(&th->X);CHKERRQ(ierr); 897 ierr = VecDestroy(&th->Xdot);CHKERRQ(ierr); 898 ierr = VecDestroy(&th->X0);CHKERRQ(ierr); 899 ierr = VecDestroy(&th->affine);CHKERRQ(ierr); 900 901 ierr = VecDestroy(&th->vec_sol_prev);CHKERRQ(ierr); 902 ierr = VecDestroy(&th->vec_lte_work);CHKERRQ(ierr); 903 904 ierr = VecDestroy(&th->VecCostIntegral0);CHKERRQ(ierr); 905 PetscFunctionReturn(0); 906 } 907 908 static PetscErrorCode TSAdjointReset_Theta(TS ts) 909 { 910 TS_Theta *th = (TS_Theta*)ts->data; 911 PetscErrorCode ierr; 912 913 PetscFunctionBegin; 914 ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaLam);CHKERRQ(ierr); 915 ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaMu);CHKERRQ(ierr); 916 ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaLam2);CHKERRQ(ierr); 917 ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaMu2);CHKERRQ(ierr); 918 ierr = VecDestroyVecs(ts->numcost,&th->VecsSensiTemp);CHKERRQ(ierr); 919 ierr = VecDestroyVecs(ts->numcost,&th->VecsSensi2Temp);CHKERRQ(ierr); 920 PetscFunctionReturn(0); 921 } 922 923 static PetscErrorCode TSDestroy_Theta(TS ts) 924 { 925 PetscErrorCode ierr; 926 927 PetscFunctionBegin; 928 ierr = TSReset_Theta(ts);CHKERRQ(ierr); 929 if (ts->dm) { 930 ierr = DMCoarsenHookRemove(ts->dm,DMCoarsenHook_TSTheta,DMRestrictHook_TSTheta,ts);CHKERRQ(ierr); 931 ierr = DMSubDomainHookRemove(ts->dm,DMSubDomainHook_TSTheta,DMSubDomainRestrictHook_TSTheta,ts);CHKERRQ(ierr); 932 } 933 ierr = PetscFree(ts->data);CHKERRQ(ierr); 934 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetTheta_C",NULL);CHKERRQ(ierr); 935 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetTheta_C",NULL);CHKERRQ(ierr); 936 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetEndpoint_C",NULL);CHKERRQ(ierr); 937 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetEndpoint_C",NULL);CHKERRQ(ierr); 938 PetscFunctionReturn(0); 939 } 940 941 /* 942 This defines the nonlinear equation that is to be solved with SNES 943 G(U) = F[t0+Theta*dt, U, (U-U0)*shift] = 0 944 */ 945 static PetscErrorCode SNESTSFormFunction_Theta(SNES snes,Vec x,Vec y,TS ts) 946 { 947 TS_Theta *th = (TS_Theta*)ts->data; 948 PetscErrorCode ierr; 949 Vec X0,Xdot; 950 DM dm,dmsave; 951 PetscReal shift = 1/(th->Theta*ts->time_step); 952 953 PetscFunctionBegin; 954 ierr = SNESGetDM(snes,&dm);CHKERRQ(ierr); 955 /* When using the endpoint variant, this is actually 1/Theta * Xdot */ 956 ierr = TSThetaGetX0AndXdot(ts,dm,&X0,&Xdot);CHKERRQ(ierr); 957 ierr = VecAXPBYPCZ(Xdot,-shift,shift,0,X0,x);CHKERRQ(ierr); 958 959 /* DM monkey-business allows user code to call TSGetDM() inside of functions evaluated on levels of FAS */ 960 dmsave = ts->dm; 961 ts->dm = dm; 962 ierr = TSComputeIFunction(ts,th->stage_time,x,Xdot,y,PETSC_FALSE);CHKERRQ(ierr); 963 ts->dm = dmsave; 964 ierr = TSThetaRestoreX0AndXdot(ts,dm,&X0,&Xdot);CHKERRQ(ierr); 965 PetscFunctionReturn(0); 966 } 967 968 static PetscErrorCode SNESTSFormJacobian_Theta(SNES snes,Vec x,Mat A,Mat B,TS ts) 969 { 970 TS_Theta *th = (TS_Theta*)ts->data; 971 PetscErrorCode ierr; 972 Vec Xdot; 973 DM dm,dmsave; 974 PetscReal shift = 1/(th->Theta*ts->time_step); 975 976 PetscFunctionBegin; 977 ierr = SNESGetDM(snes,&dm);CHKERRQ(ierr); 978 /* Xdot has already been computed in SNESTSFormFunction_Theta (SNES guarantees this) */ 979 ierr = TSThetaGetX0AndXdot(ts,dm,NULL,&Xdot);CHKERRQ(ierr); 980 981 dmsave = ts->dm; 982 ts->dm = dm; 983 ierr = TSComputeIJacobian(ts,th->stage_time,x,Xdot,shift,A,B,PETSC_FALSE);CHKERRQ(ierr); 984 ts->dm = dmsave; 985 ierr = TSThetaRestoreX0AndXdot(ts,dm,NULL,&Xdot);CHKERRQ(ierr); 986 PetscFunctionReturn(0); 987 } 988 989 static PetscErrorCode TSForwardSetUp_Theta(TS ts) 990 { 991 TS_Theta *th = (TS_Theta*)ts->data; 992 TS quadts = ts->quadraturets; 993 PetscErrorCode ierr; 994 995 PetscFunctionBegin; 996 /* combine sensitivities to parameters and sensitivities to initial values into one array */ 997 th->num_tlm = ts->num_parameters; 998 ierr = MatDuplicate(ts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatDeltaFwdSensip);CHKERRQ(ierr); 999 if (quadts && quadts->mat_sensip) { 1000 ierr = MatDuplicate(quadts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatIntegralSensipTemp);CHKERRQ(ierr); 1001 ierr = MatDuplicate(quadts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatIntegralSensip0);CHKERRQ(ierr); 1002 } 1003 /* backup sensitivity results for roll-backs */ 1004 ierr = MatDuplicate(ts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatFwdSensip0);CHKERRQ(ierr); 1005 1006 ierr = VecDuplicate(ts->vec_sol,&th->VecDeltaFwdSensipCol);CHKERRQ(ierr); 1007 PetscFunctionReturn(0); 1008 } 1009 1010 static PetscErrorCode TSForwardReset_Theta(TS ts) 1011 { 1012 TS_Theta *th = (TS_Theta*)ts->data; 1013 TS quadts = ts->quadraturets; 1014 PetscErrorCode ierr; 1015 1016 PetscFunctionBegin; 1017 if (quadts && quadts->mat_sensip) { 1018 ierr = MatDestroy(&th->MatIntegralSensipTemp);CHKERRQ(ierr); 1019 ierr = MatDestroy(&th->MatIntegralSensip0);CHKERRQ(ierr); 1020 } 1021 ierr = VecDestroy(&th->VecDeltaFwdSensipCol);CHKERRQ(ierr); 1022 ierr = MatDestroy(&th->MatDeltaFwdSensip);CHKERRQ(ierr); 1023 ierr = MatDestroy(&th->MatFwdSensip0);CHKERRQ(ierr); 1024 PetscFunctionReturn(0); 1025 } 1026 1027 static PetscErrorCode TSSetUp_Theta(TS ts) 1028 { 1029 TS_Theta *th = (TS_Theta*)ts->data; 1030 TS quadts = ts->quadraturets; 1031 PetscBool match; 1032 PetscErrorCode ierr; 1033 1034 PetscFunctionBegin; 1035 if (!th->VecCostIntegral0 && quadts && ts->costintegralfwd) { /* back up cost integral */ 1036 ierr = VecDuplicate(quadts->vec_sol,&th->VecCostIntegral0);CHKERRQ(ierr); 1037 } 1038 if (!th->X) { 1039 ierr = VecDuplicate(ts->vec_sol,&th->X);CHKERRQ(ierr); 1040 } 1041 if (!th->Xdot) { 1042 ierr = VecDuplicate(ts->vec_sol,&th->Xdot);CHKERRQ(ierr); 1043 } 1044 if (!th->X0) { 1045 ierr = VecDuplicate(ts->vec_sol,&th->X0);CHKERRQ(ierr); 1046 } 1047 if (th->endpoint) { 1048 ierr = VecDuplicate(ts->vec_sol,&th->affine);CHKERRQ(ierr); 1049 } 1050 1051 th->order = (th->Theta == 0.5) ? 2 : 1; 1052 1053 ierr = TSGetDM(ts,&ts->dm);CHKERRQ(ierr); 1054 ierr = DMCoarsenHookAdd(ts->dm,DMCoarsenHook_TSTheta,DMRestrictHook_TSTheta,ts);CHKERRQ(ierr); 1055 ierr = DMSubDomainHookAdd(ts->dm,DMSubDomainHook_TSTheta,DMSubDomainRestrictHook_TSTheta,ts);CHKERRQ(ierr); 1056 1057 ierr = TSGetAdapt(ts,&ts->adapt);CHKERRQ(ierr); 1058 ierr = TSAdaptCandidatesClear(ts->adapt);CHKERRQ(ierr); 1059 ierr = PetscObjectTypeCompare((PetscObject)ts->adapt,TSADAPTNONE,&match);CHKERRQ(ierr); 1060 if (!match) { 1061 ierr = VecDuplicate(ts->vec_sol,&th->vec_sol_prev);CHKERRQ(ierr); 1062 ierr = VecDuplicate(ts->vec_sol,&th->vec_lte_work);CHKERRQ(ierr); 1063 } 1064 ierr = TSGetSNES(ts,&ts->snes);CHKERRQ(ierr); 1065 PetscFunctionReturn(0); 1066 } 1067 1068 /*------------------------------------------------------------*/ 1069 1070 static PetscErrorCode TSAdjointSetUp_Theta(TS ts) 1071 { 1072 TS_Theta *th = (TS_Theta*)ts->data; 1073 PetscErrorCode ierr; 1074 1075 PetscFunctionBegin; 1076 ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&th->VecsDeltaLam);CHKERRQ(ierr); 1077 ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&th->VecsSensiTemp);CHKERRQ(ierr); 1078 if (ts->vecs_sensip) { 1079 ierr = VecDuplicateVecs(ts->vecs_sensip[0],ts->numcost,&th->VecsDeltaMu);CHKERRQ(ierr); 1080 } 1081 if (ts->vecs_sensi2) { 1082 ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&th->VecsDeltaLam2);CHKERRQ(ierr); 1083 ierr = VecDuplicateVecs(ts->vecs_sensi2[0],ts->numcost,&th->VecsSensi2Temp);CHKERRQ(ierr); 1084 /* hack ts to make implicit TS solver work when users provide only explicit versions of callbacks (RHSFunction,RHSJacobian,RHSHessian etc.) */ 1085 if (!ts->ihessianproduct_fuu) ts->vecs_fuu = ts->vecs_guu; 1086 if (!ts->ihessianproduct_fup) ts->vecs_fup = ts->vecs_gup; 1087 } 1088 if (ts->vecs_sensi2p) { 1089 ierr = VecDuplicateVecs(ts->vecs_sensi2p[0],ts->numcost,&th->VecsDeltaMu2);CHKERRQ(ierr); 1090 /* hack ts to make implicit TS solver work when users provide only explicit versions of callbacks (RHSFunction,RHSJacobian,RHSHessian etc.) */ 1091 if (!ts->ihessianproduct_fpu) ts->vecs_fpu = ts->vecs_gpu; 1092 if (!ts->ihessianproduct_fpp) ts->vecs_fpp = ts->vecs_gpp; 1093 } 1094 PetscFunctionReturn(0); 1095 } 1096 1097 static PetscErrorCode TSSetFromOptions_Theta(PetscOptionItems *PetscOptionsObject,TS ts) 1098 { 1099 TS_Theta *th = (TS_Theta*)ts->data; 1100 PetscErrorCode ierr; 1101 1102 PetscFunctionBegin; 1103 ierr = PetscOptionsHead(PetscOptionsObject,"Theta ODE solver options");CHKERRQ(ierr); 1104 { 1105 ierr = PetscOptionsReal("-ts_theta_theta","Location of stage (0<Theta<=1)","TSThetaSetTheta",th->Theta,&th->Theta,NULL);CHKERRQ(ierr); 1106 ierr = PetscOptionsBool("-ts_theta_endpoint","Use the endpoint instead of midpoint form of the Theta method","TSThetaSetEndpoint",th->endpoint,&th->endpoint,NULL);CHKERRQ(ierr); 1107 ierr = PetscOptionsBool("-ts_theta_initial_guess_extrapolate","Extrapolate stage initial guess from previous solution (sometimes unstable)","TSThetaSetExtrapolate",th->extrapolate,&th->extrapolate,NULL);CHKERRQ(ierr); 1108 } 1109 ierr = PetscOptionsTail();CHKERRQ(ierr); 1110 PetscFunctionReturn(0); 1111 } 1112 1113 static PetscErrorCode TSView_Theta(TS ts,PetscViewer viewer) 1114 { 1115 TS_Theta *th = (TS_Theta*)ts->data; 1116 PetscBool iascii; 1117 PetscErrorCode ierr; 1118 1119 PetscFunctionBegin; 1120 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1121 if (iascii) { 1122 ierr = PetscViewerASCIIPrintf(viewer," Theta=%g\n",(double)th->Theta);CHKERRQ(ierr); 1123 ierr = PetscViewerASCIIPrintf(viewer," Extrapolation=%s\n",th->extrapolate ? "yes" : "no");CHKERRQ(ierr); 1124 } 1125 PetscFunctionReturn(0); 1126 } 1127 1128 static PetscErrorCode TSThetaGetTheta_Theta(TS ts,PetscReal *theta) 1129 { 1130 TS_Theta *th = (TS_Theta*)ts->data; 1131 1132 PetscFunctionBegin; 1133 *theta = th->Theta; 1134 PetscFunctionReturn(0); 1135 } 1136 1137 static PetscErrorCode TSThetaSetTheta_Theta(TS ts,PetscReal theta) 1138 { 1139 TS_Theta *th = (TS_Theta*)ts->data; 1140 1141 PetscFunctionBegin; 1142 if (theta <= 0 || 1 < theta) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Theta %g not in range (0,1]",(double)theta); 1143 th->Theta = theta; 1144 th->order = (th->Theta == 0.5) ? 2 : 1; 1145 PetscFunctionReturn(0); 1146 } 1147 1148 static PetscErrorCode TSThetaGetEndpoint_Theta(TS ts,PetscBool *endpoint) 1149 { 1150 TS_Theta *th = (TS_Theta*)ts->data; 1151 1152 PetscFunctionBegin; 1153 *endpoint = th->endpoint; 1154 PetscFunctionReturn(0); 1155 } 1156 1157 static PetscErrorCode TSThetaSetEndpoint_Theta(TS ts,PetscBool flg) 1158 { 1159 TS_Theta *th = (TS_Theta*)ts->data; 1160 1161 PetscFunctionBegin; 1162 th->endpoint = flg; 1163 PetscFunctionReturn(0); 1164 } 1165 1166 #if defined(PETSC_HAVE_COMPLEX) 1167 static PetscErrorCode TSComputeLinearStability_Theta(TS ts,PetscReal xr,PetscReal xi,PetscReal *yr,PetscReal *yi) 1168 { 1169 PetscComplex z = xr + xi*PETSC_i,f; 1170 TS_Theta *th = (TS_Theta*)ts->data; 1171 const PetscReal one = 1.0; 1172 1173 PetscFunctionBegin; 1174 f = (one + (one - th->Theta)*z)/(one - th->Theta*z); 1175 *yr = PetscRealPartComplex(f); 1176 *yi = PetscImaginaryPartComplex(f); 1177 PetscFunctionReturn(0); 1178 } 1179 #endif 1180 1181 static PetscErrorCode TSGetStages_Theta(TS ts,PetscInt *ns,Vec **Y) 1182 { 1183 TS_Theta *th = (TS_Theta*)ts->data; 1184 1185 PetscFunctionBegin; 1186 if (ns) *ns = 1; 1187 if (Y) *Y = th->endpoint ? &(th->X0) : &(th->X); 1188 PetscFunctionReturn(0); 1189 } 1190 1191 /* ------------------------------------------------------------ */ 1192 /*MC 1193 TSTHETA - DAE solver using the implicit Theta method 1194 1195 Level: beginner 1196 1197 Options Database: 1198 + -ts_theta_theta <Theta> - Location of stage (0<Theta<=1) 1199 . -ts_theta_endpoint <flag> - Use the endpoint (like Crank-Nicholson) instead of midpoint form of the Theta method 1200 - -ts_theta_initial_guess_extrapolate <flg> - Extrapolate stage initial guess from previous solution (sometimes unstable) 1201 1202 Notes: 1203 $ -ts_type theta -ts_theta_theta 1.0 corresponds to backward Euler (TSBEULER) 1204 $ -ts_type theta -ts_theta_theta 0.5 corresponds to the implicit midpoint rule 1205 $ -ts_type theta -ts_theta_theta 0.5 -ts_theta_endpoint corresponds to Crank-Nicholson (TSCN) 1206 1207 This method can be applied to DAE. 1208 1209 This method is cast as a 1-stage implicit Runge-Kutta method. 1210 1211 .vb 1212 Theta | Theta 1213 ------------- 1214 | 1 1215 .ve 1216 1217 For the default Theta=0.5, this is also known as the implicit midpoint rule. 1218 1219 When the endpoint variant is chosen, the method becomes a 2-stage method with first stage explicit: 1220 1221 .vb 1222 0 | 0 0 1223 1 | 1-Theta Theta 1224 ------------------- 1225 | 1-Theta Theta 1226 .ve 1227 1228 For the default Theta=0.5, this is the trapezoid rule (also known as Crank-Nicolson, see TSCN). 1229 1230 To apply a diagonally implicit RK method to DAE, the stage formula 1231 1232 $ Y_i = X + h sum_j a_ij Y'_j 1233 1234 is interpreted as a formula for Y'_i in terms of Y_i and known values (Y'_j, j<i) 1235 1236 .seealso: TSCreate(), TS, TSSetType(), TSCN, TSBEULER, TSThetaSetTheta(), TSThetaSetEndpoint() 1237 1238 M*/ 1239 PETSC_EXTERN PetscErrorCode TSCreate_Theta(TS ts) 1240 { 1241 TS_Theta *th; 1242 PetscErrorCode ierr; 1243 1244 PetscFunctionBegin; 1245 ts->ops->reset = TSReset_Theta; 1246 ts->ops->adjointreset = TSAdjointReset_Theta; 1247 ts->ops->destroy = TSDestroy_Theta; 1248 ts->ops->view = TSView_Theta; 1249 ts->ops->setup = TSSetUp_Theta; 1250 ts->ops->adjointsetup = TSAdjointSetUp_Theta; 1251 ts->ops->adjointreset = TSAdjointReset_Theta; 1252 ts->ops->step = TSStep_Theta; 1253 ts->ops->interpolate = TSInterpolate_Theta; 1254 ts->ops->evaluatewlte = TSEvaluateWLTE_Theta; 1255 ts->ops->rollback = TSRollBack_Theta; 1256 ts->ops->setfromoptions = TSSetFromOptions_Theta; 1257 ts->ops->snesfunction = SNESTSFormFunction_Theta; 1258 ts->ops->snesjacobian = SNESTSFormJacobian_Theta; 1259 #if defined(PETSC_HAVE_COMPLEX) 1260 ts->ops->linearstability = TSComputeLinearStability_Theta; 1261 #endif 1262 ts->ops->getstages = TSGetStages_Theta; 1263 ts->ops->adjointstep = TSAdjointStep_Theta; 1264 ts->ops->adjointintegral = TSAdjointCostIntegral_Theta; 1265 ts->ops->forwardintegral = TSForwardCostIntegral_Theta; 1266 ts->default_adapt_type = TSADAPTNONE; 1267 1268 ts->ops->forwardsetup = TSForwardSetUp_Theta; 1269 ts->ops->forwardreset = TSForwardReset_Theta; 1270 ts->ops->forwardstep = TSForwardStep_Theta; 1271 ts->ops->forwardgetstages = TSForwardGetStages_Theta; 1272 1273 ts->usessnes = PETSC_TRUE; 1274 1275 ierr = PetscNewLog(ts,&th);CHKERRQ(ierr); 1276 ts->data = (void*)th; 1277 1278 th->VecsDeltaLam = NULL; 1279 th->VecsDeltaMu = NULL; 1280 th->VecsSensiTemp = NULL; 1281 th->VecsSensi2Temp = NULL; 1282 1283 th->extrapolate = PETSC_FALSE; 1284 th->Theta = 0.5; 1285 th->order = 2; 1286 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetTheta_C",TSThetaGetTheta_Theta);CHKERRQ(ierr); 1287 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetTheta_C",TSThetaSetTheta_Theta);CHKERRQ(ierr); 1288 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetEndpoint_C",TSThetaGetEndpoint_Theta);CHKERRQ(ierr); 1289 ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetEndpoint_C",TSThetaSetEndpoint_Theta);CHKERRQ(ierr); 1290 PetscFunctionReturn(0); 1291 } 1292 1293 /*@ 1294 TSThetaGetTheta - Get the abscissa of the stage in (0,1]. 1295 1296 Not Collective 1297 1298 Input Parameter: 1299 . ts - timestepping context 1300 1301 Output Parameter: 1302 . theta - stage abscissa 1303 1304 Note: 1305 Use of this function is normally only required to hack TSTHETA to use a modified integration scheme. 1306 1307 Level: Advanced 1308 1309 .seealso: TSThetaSetTheta() 1310 @*/ 1311 PetscErrorCode TSThetaGetTheta(TS ts,PetscReal *theta) 1312 { 1313 PetscErrorCode ierr; 1314 1315 PetscFunctionBegin; 1316 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1317 PetscValidPointer(theta,2); 1318 ierr = PetscUseMethod(ts,"TSThetaGetTheta_C",(TS,PetscReal*),(ts,theta));CHKERRQ(ierr); 1319 PetscFunctionReturn(0); 1320 } 1321 1322 /*@ 1323 TSThetaSetTheta - Set the abscissa of the stage in (0,1]. 1324 1325 Not Collective 1326 1327 Input Parameter: 1328 + ts - timestepping context 1329 - theta - stage abscissa 1330 1331 Options Database: 1332 . -ts_theta_theta <theta> 1333 1334 Level: Intermediate 1335 1336 .seealso: TSThetaGetTheta() 1337 @*/ 1338 PetscErrorCode TSThetaSetTheta(TS ts,PetscReal theta) 1339 { 1340 PetscErrorCode ierr; 1341 1342 PetscFunctionBegin; 1343 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1344 ierr = PetscTryMethod(ts,"TSThetaSetTheta_C",(TS,PetscReal),(ts,theta));CHKERRQ(ierr); 1345 PetscFunctionReturn(0); 1346 } 1347 1348 /*@ 1349 TSThetaGetEndpoint - Gets whether to use the endpoint variant of the method (e.g. trapezoid/Crank-Nicolson instead of midpoint rule). 1350 1351 Not Collective 1352 1353 Input Parameter: 1354 . ts - timestepping context 1355 1356 Output Parameter: 1357 . endpoint - PETSC_TRUE when using the endpoint variant 1358 1359 Level: Advanced 1360 1361 .seealso: TSThetaSetEndpoint(), TSTHETA, TSCN 1362 @*/ 1363 PetscErrorCode TSThetaGetEndpoint(TS ts,PetscBool *endpoint) 1364 { 1365 PetscErrorCode ierr; 1366 1367 PetscFunctionBegin; 1368 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1369 PetscValidPointer(endpoint,2); 1370 ierr = PetscUseMethod(ts,"TSThetaGetEndpoint_C",(TS,PetscBool*),(ts,endpoint));CHKERRQ(ierr); 1371 PetscFunctionReturn(0); 1372 } 1373 1374 /*@ 1375 TSThetaSetEndpoint - Sets whether to use the endpoint variant of the method (e.g. trapezoid/Crank-Nicolson instead of midpoint rule). 1376 1377 Not Collective 1378 1379 Input Parameter: 1380 + ts - timestepping context 1381 - flg - PETSC_TRUE to use the endpoint variant 1382 1383 Options Database: 1384 . -ts_theta_endpoint <flg> 1385 1386 Level: Intermediate 1387 1388 .seealso: TSTHETA, TSCN 1389 @*/ 1390 PetscErrorCode TSThetaSetEndpoint(TS ts,PetscBool flg) 1391 { 1392 PetscErrorCode ierr; 1393 1394 PetscFunctionBegin; 1395 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 1396 ierr = PetscTryMethod(ts,"TSThetaSetEndpoint_C",(TS,PetscBool),(ts,flg));CHKERRQ(ierr); 1397 PetscFunctionReturn(0); 1398 } 1399 1400 /* 1401 * TSBEULER and TSCN are straightforward specializations of TSTHETA. 1402 * The creation functions for these specializations are below. 1403 */ 1404 1405 static PetscErrorCode TSSetUp_BEuler(TS ts) 1406 { 1407 TS_Theta *th = (TS_Theta*)ts->data; 1408 PetscErrorCode ierr; 1409 1410 PetscFunctionBegin; 1411 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"); 1412 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"); 1413 ierr = TSSetUp_Theta(ts);CHKERRQ(ierr); 1414 PetscFunctionReturn(0); 1415 } 1416 1417 static PetscErrorCode TSView_BEuler(TS ts,PetscViewer viewer) 1418 { 1419 PetscFunctionBegin; 1420 PetscFunctionReturn(0); 1421 } 1422 1423 /*MC 1424 TSBEULER - ODE solver using the implicit backward Euler method 1425 1426 Level: beginner 1427 1428 Notes: 1429 TSBEULER is equivalent to TSTHETA with Theta=1.0 1430 1431 $ -ts_type theta -ts_theta_theta 1.0 1432 1433 .seealso: TSCreate(), TS, TSSetType(), TSEULER, TSCN, TSTHETA 1434 1435 M*/ 1436 PETSC_EXTERN PetscErrorCode TSCreate_BEuler(TS ts) 1437 { 1438 PetscErrorCode ierr; 1439 1440 PetscFunctionBegin; 1441 ierr = TSCreate_Theta(ts);CHKERRQ(ierr); 1442 ierr = TSThetaSetTheta(ts,1.0);CHKERRQ(ierr); 1443 ierr = TSThetaSetEndpoint(ts,PETSC_FALSE);CHKERRQ(ierr); 1444 ts->ops->setup = TSSetUp_BEuler; 1445 ts->ops->view = TSView_BEuler; 1446 PetscFunctionReturn(0); 1447 } 1448 1449 static PetscErrorCode TSSetUp_CN(TS ts) 1450 { 1451 TS_Theta *th = (TS_Theta*)ts->data; 1452 PetscErrorCode ierr; 1453 1454 PetscFunctionBegin; 1455 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"); 1456 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"); 1457 ierr = TSSetUp_Theta(ts);CHKERRQ(ierr); 1458 PetscFunctionReturn(0); 1459 } 1460 1461 static PetscErrorCode TSView_CN(TS ts,PetscViewer viewer) 1462 { 1463 PetscFunctionBegin; 1464 PetscFunctionReturn(0); 1465 } 1466 1467 /*MC 1468 TSCN - ODE solver using the implicit Crank-Nicolson method. 1469 1470 Level: beginner 1471 1472 Notes: 1473 TSCN is equivalent to TSTHETA with Theta=0.5 and the "endpoint" option set. I.e. 1474 1475 $ -ts_type theta -ts_theta_theta 0.5 -ts_theta_endpoint 1476 1477 .seealso: TSCreate(), TS, TSSetType(), TSBEULER, TSTHETA 1478 1479 M*/ 1480 PETSC_EXTERN PetscErrorCode TSCreate_CN(TS ts) 1481 { 1482 PetscErrorCode ierr; 1483 1484 PetscFunctionBegin; 1485 ierr = TSCreate_Theta(ts);CHKERRQ(ierr); 1486 ierr = TSThetaSetTheta(ts,0.5);CHKERRQ(ierr); 1487 ierr = TSThetaSetEndpoint(ts,PETSC_TRUE);CHKERRQ(ierr); 1488 ts->ops->setup = TSSetUp_CN; 1489 ts->ops->view = TSView_CN; 1490 PetscFunctionReturn(0); 1491 } 1492