/* Code for timestepping with implicit Theta method */ #include /*I "petscts.h" I*/ #include #include #include typedef struct { /* context for time stepping */ PetscReal stage_time; Vec X0,X,Xdot; /* Storage for stages and time derivative */ Vec affine; /* Affine vector needed for residual at beginning of step in endpoint formulation */ PetscReal Theta; PetscReal shift; /* Shift parameter for SNES Jacobian, used by forward, TLM and adjoint */ PetscInt order; PetscBool endpoint; PetscBool extrapolate; TSStepStatus status; Vec VecCostIntegral0; /* Backup for roll-backs due to events, used by cost integral */ PetscReal ptime0; /* Backup for ts->ptime, the start time of current time step, used by TLM and cost integral */ PetscReal time_step0; /* Backup for ts->timestep, the step size of current time step, used by TLM and cost integral*/ /* context for sensitivity analysis */ PetscInt num_tlm; /* Total number of tangent linear equations */ Vec *VecsDeltaLam; /* Increment of the adjoint sensitivity w.r.t IC at stage */ Vec *VecsDeltaMu; /* Increment of the adjoint sensitivity w.r.t P at stage */ Vec *VecsSensiTemp; /* Vector to be multiplied with Jacobian transpose */ Mat MatDeltaFwdSensip; /* Increment of the forward sensitivity at stage */ Vec VecDeltaFwdSensipCol; /* Working vector for holding one column of the sensitivity matrix */ Mat MatFwdSensip0; /* backup for roll-backs due to events */ Mat MatIntegralSensipTemp; /* Working vector for forward integral sensitivity */ Mat MatIntegralSensip0; /* backup for roll-backs due to events */ Vec *VecsDeltaLam2; /* Increment of the 2nd-order adjoint sensitivity w.r.t IC at stage */ Vec *VecsDeltaMu2; /* Increment of the 2nd-order adjoint sensitivity w.r.t P at stage */ Vec *VecsSensi2Temp; /* Working vectors that holds the residual for the second-order adjoint */ Vec *VecsAffine; /* Working vectors to store residuals */ /* context for error estimation */ Vec vec_sol_prev; Vec vec_lte_work; } TS_Theta; static PetscErrorCode TSThetaGetX0AndXdot(TS ts,DM dm,Vec *X0,Vec *Xdot) { TS_Theta *th = (TS_Theta*)ts->data; PetscErrorCode ierr; PetscFunctionBegin; if (X0) { if (dm && dm != ts->dm) { ierr = DMGetNamedGlobalVector(dm,"TSTheta_X0",X0);CHKERRQ(ierr); } else *X0 = ts->vec_sol; } if (Xdot) { if (dm && dm != ts->dm) { ierr = DMGetNamedGlobalVector(dm,"TSTheta_Xdot",Xdot);CHKERRQ(ierr); } else *Xdot = th->Xdot; } PetscFunctionReturn(0); } static PetscErrorCode TSThetaRestoreX0AndXdot(TS ts,DM dm,Vec *X0,Vec *Xdot) { PetscErrorCode ierr; PetscFunctionBegin; if (X0) { if (dm && dm != ts->dm) { ierr = DMRestoreNamedGlobalVector(dm,"TSTheta_X0",X0);CHKERRQ(ierr); } } if (Xdot) { if (dm && dm != ts->dm) { ierr = DMRestoreNamedGlobalVector(dm,"TSTheta_Xdot",Xdot);CHKERRQ(ierr); } } PetscFunctionReturn(0); } static PetscErrorCode DMCoarsenHook_TSTheta(DM fine,DM coarse,void *ctx) { PetscFunctionBegin; PetscFunctionReturn(0); } static PetscErrorCode DMRestrictHook_TSTheta(DM fine,Mat restrct,Vec rscale,Mat inject,DM coarse,void *ctx) { TS ts = (TS)ctx; PetscErrorCode ierr; Vec X0,Xdot,X0_c,Xdot_c; PetscFunctionBegin; ierr = TSThetaGetX0AndXdot(ts,fine,&X0,&Xdot);CHKERRQ(ierr); ierr = TSThetaGetX0AndXdot(ts,coarse,&X0_c,&Xdot_c);CHKERRQ(ierr); ierr = MatRestrict(restrct,X0,X0_c);CHKERRQ(ierr); ierr = MatRestrict(restrct,Xdot,Xdot_c);CHKERRQ(ierr); ierr = VecPointwiseMult(X0_c,rscale,X0_c);CHKERRQ(ierr); ierr = VecPointwiseMult(Xdot_c,rscale,Xdot_c);CHKERRQ(ierr); ierr = TSThetaRestoreX0AndXdot(ts,fine,&X0,&Xdot);CHKERRQ(ierr); ierr = TSThetaRestoreX0AndXdot(ts,coarse,&X0_c,&Xdot_c);CHKERRQ(ierr); PetscFunctionReturn(0); } static PetscErrorCode DMSubDomainHook_TSTheta(DM dm,DM subdm,void *ctx) { PetscFunctionBegin; PetscFunctionReturn(0); } static PetscErrorCode DMSubDomainRestrictHook_TSTheta(DM dm,VecScatter gscat,VecScatter lscat,DM subdm,void *ctx) { TS ts = (TS)ctx; PetscErrorCode ierr; Vec X0,Xdot,X0_sub,Xdot_sub; PetscFunctionBegin; ierr = TSThetaGetX0AndXdot(ts,dm,&X0,&Xdot);CHKERRQ(ierr); ierr = TSThetaGetX0AndXdot(ts,subdm,&X0_sub,&Xdot_sub);CHKERRQ(ierr); ierr = VecScatterBegin(gscat,X0,X0_sub,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); ierr = VecScatterEnd(gscat,X0,X0_sub,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); ierr = VecScatterBegin(gscat,Xdot,Xdot_sub,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); ierr = VecScatterEnd(gscat,Xdot,Xdot_sub,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); ierr = TSThetaRestoreX0AndXdot(ts,dm,&X0,&Xdot);CHKERRQ(ierr); ierr = TSThetaRestoreX0AndXdot(ts,subdm,&X0_sub,&Xdot_sub);CHKERRQ(ierr); PetscFunctionReturn(0); } static PetscErrorCode TSThetaEvaluateCostIntegral(TS ts) { TS_Theta *th = (TS_Theta*)ts->data; TS quadts = ts->quadraturets; PetscErrorCode ierr; PetscFunctionBegin; if (th->endpoint) { /* Evolve ts->vec_costintegral to compute integrals */ if (th->Theta!=1.0) { ierr = TSComputeRHSFunction(quadts,th->ptime0,th->X0,ts->vec_costintegrand);CHKERRQ(ierr); ierr = VecAXPY(quadts->vec_sol,th->time_step0*(1.0-th->Theta),ts->vec_costintegrand);CHKERRQ(ierr); } ierr = TSComputeRHSFunction(quadts,ts->ptime,ts->vec_sol,ts->vec_costintegrand);CHKERRQ(ierr); ierr = VecAXPY(quadts->vec_sol,th->time_step0*th->Theta,ts->vec_costintegrand);CHKERRQ(ierr); } else { ierr = TSComputeRHSFunction(quadts,th->stage_time,th->X,ts->vec_costintegrand);CHKERRQ(ierr); ierr = VecAXPY(quadts->vec_sol,th->time_step0,ts->vec_costintegrand);CHKERRQ(ierr); } PetscFunctionReturn(0); } static PetscErrorCode TSForwardCostIntegral_Theta(TS ts) { TS_Theta *th = (TS_Theta*)ts->data; TS quadts = ts->quadraturets; PetscErrorCode ierr; PetscFunctionBegin; /* backup cost integral */ ierr = VecCopy(quadts->vec_sol,th->VecCostIntegral0);CHKERRQ(ierr); ierr = TSThetaEvaluateCostIntegral(ts);CHKERRQ(ierr); PetscFunctionReturn(0); } static PetscErrorCode TSAdjointCostIntegral_Theta(TS ts) { TS_Theta *th = (TS_Theta*)ts->data; PetscErrorCode ierr; PetscFunctionBegin; /* Like TSForwardCostIntegral(), the adjoint cost integral evaluation relies on ptime0 and time_step0. */ th->ptime0 = ts->ptime + ts->time_step; th->time_step0 = -ts->time_step; ierr = TSThetaEvaluateCostIntegral(ts);CHKERRQ(ierr); PetscFunctionReturn(0); } static PetscErrorCode TSTheta_SNESSolve(TS ts,Vec b,Vec x) { PetscInt nits,lits; PetscErrorCode ierr; PetscFunctionBegin; ierr = SNESSolve(ts->snes,b,x);CHKERRQ(ierr); ierr = SNESGetIterationNumber(ts->snes,&nits);CHKERRQ(ierr); ierr = SNESGetLinearSolveIterations(ts->snes,&lits);CHKERRQ(ierr); ts->snes_its += nits; ts->ksp_its += lits; PetscFunctionReturn(0); } static PetscErrorCode TSStep_Theta(TS ts) { TS_Theta *th = (TS_Theta*)ts->data; PetscInt rejections = 0; PetscBool stageok,accept = PETSC_TRUE; PetscReal next_time_step = ts->time_step; PetscErrorCode ierr; PetscFunctionBegin; if (!ts->steprollback) { if (th->vec_sol_prev) { ierr = VecCopy(th->X0,th->vec_sol_prev);CHKERRQ(ierr); } ierr = VecCopy(ts->vec_sol,th->X0);CHKERRQ(ierr); } th->status = TS_STEP_INCOMPLETE; while (!ts->reason && th->status != TS_STEP_COMPLETE) { th->shift = 1/(th->Theta*ts->time_step); th->stage_time = ts->ptime + (th->endpoint ? (PetscReal)1 : th->Theta)*ts->time_step; ierr = VecCopy(th->X0,th->X);CHKERRQ(ierr); if (th->extrapolate && !ts->steprestart) { ierr = VecAXPY(th->X,1/th->shift,th->Xdot);CHKERRQ(ierr); } if (th->endpoint) { /* This formulation assumes linear time-independent mass matrix */ if (!th->affine) {ierr = VecDuplicate(ts->vec_sol,&th->affine);CHKERRQ(ierr);} ierr = VecZeroEntries(th->Xdot);CHKERRQ(ierr); ierr = TSComputeIFunction(ts,ts->ptime,th->X0,th->Xdot,th->affine,PETSC_FALSE);CHKERRQ(ierr); ierr = VecScale(th->affine,(th->Theta-1)/th->Theta);CHKERRQ(ierr); } else if (th->affine) { /* Just in case th->endpoint is changed between calls to TSStep_Theta() */ ierr = VecZeroEntries(th->affine);CHKERRQ(ierr); } ierr = TSPreStage(ts,th->stage_time);CHKERRQ(ierr); ierr = TSTheta_SNESSolve(ts,th->affine,th->X);CHKERRQ(ierr); ierr = TSPostStage(ts,th->stage_time,0,&th->X);CHKERRQ(ierr); ierr = TSAdaptCheckStage(ts->adapt,ts,th->stage_time,th->X,&stageok);CHKERRQ(ierr); if (!stageok) goto reject_step; th->status = TS_STEP_PENDING; if (th->endpoint) { ierr = VecCopy(th->X,ts->vec_sol);CHKERRQ(ierr); } else { ierr = VecAXPBYPCZ(th->Xdot,-th->shift,th->shift,0,th->X0,th->X);CHKERRQ(ierr); ierr = VecAXPY(ts->vec_sol,ts->time_step,th->Xdot);CHKERRQ(ierr); } ierr = TSAdaptChoose(ts->adapt,ts,ts->time_step,NULL,&next_time_step,&accept);CHKERRQ(ierr); th->status = accept ? TS_STEP_COMPLETE : TS_STEP_INCOMPLETE; if (!accept) { ierr = VecCopy(th->X0,ts->vec_sol);CHKERRQ(ierr); ts->time_step = next_time_step; goto reject_step; } if (ts->forward_solve || ts->costintegralfwd) { /* Save the info for the later use in cost integral evaluation */ th->ptime0 = ts->ptime; th->time_step0 = ts->time_step; } ts->ptime += ts->time_step; ts->time_step = next_time_step; break; reject_step: ts->reject++; accept = PETSC_FALSE; if (!ts->reason && ++rejections > ts->max_reject && ts->max_reject >= 0) { ts->reason = TS_DIVERGED_STEP_REJECTED; ierr = PetscInfo2(ts,"Step=%D, step rejections %D greater than current TS allowed, stopping solve\n",ts->steps,rejections);CHKERRQ(ierr); } } PetscFunctionReturn(0); } static PetscErrorCode TSAdjointStepBEuler_Private(TS ts) { TS_Theta *th = (TS_Theta*)ts->data; TS quadts = ts->quadraturets; Vec *VecsDeltaLam = th->VecsDeltaLam,*VecsDeltaMu = th->VecsDeltaMu,*VecsSensiTemp = th->VecsSensiTemp; Vec *VecsDeltaLam2 = th->VecsDeltaLam2,*VecsDeltaMu2 = th->VecsDeltaMu2,*VecsSensi2Temp = th->VecsSensi2Temp; PetscInt nadj; Mat J,Jpre,quadJ = NULL,quadJp = NULL; KSP ksp; PetscScalar *xarr; TSEquationType eqtype; PetscBool isexplicitode = PETSC_FALSE; PetscReal adjoint_time_step; PetscErrorCode ierr; PetscFunctionBegin; ierr = TSGetEquationType(ts,&eqtype);CHKERRQ(ierr); if (eqtype == TS_EQ_ODE_EXPLICIT) { isexplicitode = PETSC_TRUE; VecsDeltaLam = ts->vecs_sensi; VecsDeltaLam2 = ts->vecs_sensi2; } th->status = TS_STEP_INCOMPLETE; ierr = SNESGetKSP(ts->snes,&ksp);CHKERRQ(ierr); ierr = TSGetIJacobian(ts,&J,&Jpre,NULL,NULL);CHKERRQ(ierr); if (quadts) { ierr = TSGetRHSJacobian(quadts,&quadJ,NULL,NULL,NULL);CHKERRQ(ierr); ierr = TSGetRHSJacobianP(quadts,&quadJp,NULL,NULL);CHKERRQ(ierr); } th->stage_time = ts->ptime; adjoint_time_step = -ts->time_step; /* always positive since time_step is negative */ /* Build RHS for first-order adjoint lambda_{n+1}/h + r_u^T(n+1) */ if (quadts) { ierr = TSComputeRHSJacobian(quadts,th->stage_time,th->X,quadJ,NULL);CHKERRQ(ierr); } for (nadj=0; nadjnumcost; nadj++) { ierr = VecCopy(ts->vecs_sensi[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr); ierr = VecScale(VecsSensiTemp[nadj],1./adjoint_time_step);CHKERRQ(ierr); /* lambda_{n+1}/h */ if (quadJ) { ierr = MatDenseGetColumn(quadJ,nadj,&xarr);CHKERRQ(ierr); ierr = VecPlaceArray(ts->vec_drdu_col,xarr);CHKERRQ(ierr); ierr = VecAXPY(VecsSensiTemp[nadj],1.,ts->vec_drdu_col);CHKERRQ(ierr); ierr = VecResetArray(ts->vec_drdu_col);CHKERRQ(ierr); ierr = MatDenseRestoreColumn(quadJ,&xarr);CHKERRQ(ierr); } } /* Build LHS for first-order adjoint */ th->shift = 1./adjoint_time_step; ierr = TSComputeSNESJacobian(ts,th->X,J,Jpre);CHKERRQ(ierr); ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr); /* Solve stage equation LHS*lambda_s = RHS for first-order adjoint */ for (nadj=0; nadjnumcost; nadj++) { KSPConvergedReason kspreason; ierr = KSPSolveTranspose(ksp,VecsSensiTemp[nadj],VecsDeltaLam[nadj]);CHKERRQ(ierr); ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); if (kspreason < 0) { ts->reason = TSADJOINT_DIVERGED_LINEAR_SOLVE; ierr = PetscInfo2(ts,"Step=%D, %Dth cost function, transposed linear solve fails, stopping 1st-order adjoint solve\n",ts->steps,nadj);CHKERRQ(ierr); } } if (ts->vecs_sensi2) { /* U_{n+1} */ /* Get w1 at t_{n+1} from TLM matrix */ ierr = MatDenseGetColumn(ts->mat_sensip,0,&xarr);CHKERRQ(ierr); ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); /* lambda_s^T F_UU w_1 */ ierr = TSComputeIHessianProductFunctionUU(ts,th->stage_time,th->X,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fuu);CHKERRQ(ierr); /* lambda_s^T F_UP w_2 */ ierr = TSComputeIHessianProductFunctionUP(ts,th->stage_time,th->X,VecsDeltaLam,ts->vec_dir,ts->vecs_fup);CHKERRQ(ierr); for (nadj=0; nadjnumcost; nadj++) { /* compute the residual */ ierr = VecCopy(ts->vecs_sensi2[nadj],VecsSensi2Temp[nadj]);CHKERRQ(ierr); ierr = VecScale(VecsSensi2Temp[nadj],1./adjoint_time_step);CHKERRQ(ierr); ierr = VecAXPY(VecsSensi2Temp[nadj],-1.,ts->vecs_fuu[nadj]);CHKERRQ(ierr); if (ts->vecs_fup) { ierr = VecAXPY(VecsSensi2Temp[nadj],-1.,ts->vecs_fup[nadj]);CHKERRQ(ierr); } } /* Solve stage equation LHS X = RHS for second-order adjoint */ for (nadj=0; nadjnumcost; nadj++) { KSPConvergedReason kspreason; ierr = KSPSolveTranspose(ksp,VecsSensi2Temp[nadj],VecsDeltaLam2[nadj]);CHKERRQ(ierr); ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); if (kspreason < 0) { ts->reason = TSADJOINT_DIVERGED_LINEAR_SOLVE; ierr = PetscInfo2(ts,"Step=%D, %Dth cost function, transposed linear solve fails, stopping 2nd-order adjoint solve\n",ts->steps,nadj);CHKERRQ(ierr); } } } /* Update sensitivities, and evaluate integrals if there is any */ if (!isexplicitode) { th->shift = 0.0; ierr = TSComputeSNESJacobian(ts,th->X,J,Jpre);CHKERRQ(ierr); ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr); ierr = MatScale(J,-1.);CHKERRQ(ierr); for (nadj=0; nadjnumcost; nadj++) { /* Add f_U \lambda_s to the original RHS */ ierr = MatMultTransposeAdd(J,VecsDeltaLam[nadj],VecsSensiTemp[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr); ierr = VecScale(VecsSensiTemp[nadj],adjoint_time_step);CHKERRQ(ierr); ierr = VecCopy(VecsSensiTemp[nadj],ts->vecs_sensi[nadj]);CHKERRQ(ierr); if (ts->vecs_sensi2) { ierr = MatMultTransposeAdd(J,VecsDeltaLam2[nadj],VecsSensi2Temp[nadj],VecsSensi2Temp[nadj]);CHKERRQ(ierr); ierr = VecScale(VecsSensi2Temp[nadj],adjoint_time_step);CHKERRQ(ierr); ierr = VecCopy(VecsSensi2Temp[nadj],ts->vecs_sensi2[nadj]);CHKERRQ(ierr); } } } if (ts->vecs_sensip) { ierr = TSComputeIJacobianP(ts,th->stage_time,th->X,th->Xdot,1./adjoint_time_step,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); /* get -f_p */ if (quadts) { ierr = TSComputeRHSJacobianP(quadts,th->stage_time,th->X,quadJp);CHKERRQ(ierr); } if (ts->vecs_sensi2p) { /* lambda_s^T F_PU w_1 */ ierr = TSComputeIHessianProductFunctionPU(ts,th->stage_time,th->X,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fpu);CHKERRQ(ierr); /* lambda_s^T F_PP w_2 */ ierr = TSComputeIHessianProductFunctionPP(ts,th->stage_time,th->X,VecsDeltaLam,ts->vec_dir,ts->vecs_fpp);CHKERRQ(ierr); } for (nadj=0; nadjnumcost; nadj++) { ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr); ierr = VecAXPY(ts->vecs_sensip[nadj],-adjoint_time_step,VecsDeltaMu[nadj]);CHKERRQ(ierr); if (quadJp) { ierr = MatDenseGetColumn(quadJp,nadj,&xarr);CHKERRQ(ierr); ierr = VecPlaceArray(ts->vec_drdp_col,xarr);CHKERRQ(ierr); ierr = VecAXPY(ts->vecs_sensip[nadj],adjoint_time_step,ts->vec_drdp_col);CHKERRQ(ierr); ierr = VecResetArray(ts->vec_drdp_col);CHKERRQ(ierr); ierr = MatDenseRestoreColumn(quadJp,&xarr);CHKERRQ(ierr); } if (ts->vecs_sensi2p) { ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam2[nadj],VecsDeltaMu2[nadj]);CHKERRQ(ierr); ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step,VecsDeltaMu2[nadj]);CHKERRQ(ierr); if (ts->vecs_fpu) { ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step,ts->vecs_fpu[nadj]);CHKERRQ(ierr); } if (ts->vecs_fpp) { ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step,ts->vecs_fpp[nadj]);CHKERRQ(ierr); } } } } if (ts->vecs_sensi2) { ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr); } th->status = TS_STEP_COMPLETE; PetscFunctionReturn(0); } static PetscErrorCode TSAdjointStep_Theta(TS ts) { TS_Theta *th = (TS_Theta*)ts->data; TS quadts = ts->quadraturets; Vec *VecsDeltaLam = th->VecsDeltaLam,*VecsDeltaMu = th->VecsDeltaMu,*VecsSensiTemp = th->VecsSensiTemp; Vec *VecsDeltaLam2 = th->VecsDeltaLam2,*VecsDeltaMu2 = th->VecsDeltaMu2,*VecsSensi2Temp = th->VecsSensi2Temp; PetscInt nadj; Mat J,Jpre,quadJ = NULL,quadJp = NULL; KSP ksp; PetscScalar *xarr; PetscReal adjoint_time_step; PetscReal adjoint_ptime; /* end time of the adjoint time step (ts->ptime is the start time, ususally ts->ptime is larger than adjoint_ptime) */ PetscErrorCode ierr; PetscFunctionBegin; if (th->Theta == 1.) { ierr = TSAdjointStepBEuler_Private(ts);CHKERRQ(ierr); PetscFunctionReturn(0); } th->status = TS_STEP_INCOMPLETE; ierr = SNESGetKSP(ts->snes,&ksp);CHKERRQ(ierr); ierr = TSGetIJacobian(ts,&J,&Jpre,NULL,NULL);CHKERRQ(ierr); if (quadts) { ierr = TSGetRHSJacobian(quadts,&quadJ,NULL,NULL,NULL);CHKERRQ(ierr); ierr = TSGetRHSJacobianP(quadts,&quadJp,NULL,NULL);CHKERRQ(ierr); } /* If endpoint=1, th->ptime and th->X0 will be used; if endpoint=0, th->stage_time and th->X will be used. */ th->stage_time = th->endpoint ? ts->ptime : (ts->ptime+(1.-th->Theta)*ts->time_step); adjoint_ptime = ts->ptime + ts->time_step; adjoint_time_step = -ts->time_step; /* always positive since time_step is negative */ /* Build RHS for first-order adjoint */ /* Cost function has an integral term */ if (quadts) { if (th->endpoint) { ierr = TSComputeRHSJacobian(quadts,th->stage_time,ts->vec_sol,quadJ,NULL);CHKERRQ(ierr); } else { ierr = TSComputeRHSJacobian(quadts,th->stage_time,th->X,quadJ,NULL);CHKERRQ(ierr); } } for (nadj=0; nadjnumcost; nadj++) { ierr = VecCopy(ts->vecs_sensi[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr); ierr = VecScale(VecsSensiTemp[nadj],1./(th->Theta*adjoint_time_step));CHKERRQ(ierr); if (quadJ) { ierr = MatDenseGetColumn(quadJ,nadj,&xarr);CHKERRQ(ierr); ierr = VecPlaceArray(ts->vec_drdu_col,xarr);CHKERRQ(ierr); ierr = VecAXPY(VecsSensiTemp[nadj],1.,ts->vec_drdu_col);CHKERRQ(ierr); ierr = VecResetArray(ts->vec_drdu_col);CHKERRQ(ierr); ierr = MatDenseRestoreColumn(quadJ,&xarr);CHKERRQ(ierr); } } /* Build LHS for first-order adjoint */ th->shift = 1./(th->Theta*adjoint_time_step); if (th->endpoint) { ierr = TSComputeSNESJacobian(ts,ts->vec_sol,J,Jpre);CHKERRQ(ierr); } else { ierr = TSComputeSNESJacobian(ts,th->X,J,Jpre);CHKERRQ(ierr); } ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr); /* Solve stage equation LHS*lambda_s = RHS for first-order adjoint */ for (nadj=0; nadjnumcost; nadj++) { KSPConvergedReason kspreason; ierr = KSPSolveTranspose(ksp,VecsSensiTemp[nadj],VecsDeltaLam[nadj]);CHKERRQ(ierr); ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); if (kspreason < 0) { ts->reason = TSADJOINT_DIVERGED_LINEAR_SOLVE; ierr = PetscInfo2(ts,"Step=%D, %Dth cost function, transposed linear solve fails, stopping 1st-order adjoint solve\n",ts->steps,nadj);CHKERRQ(ierr); } } /* Second-order adjoint */ if (ts->vecs_sensi2) { /* U_{n+1} */ if (!th->endpoint) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Operation not implemented in TS_Theta"); /* Get w1 at t_{n+1} from TLM matrix */ ierr = MatDenseGetColumn(ts->mat_sensip,0,&xarr);CHKERRQ(ierr); ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); /* lambda_s^T F_UU w_1 */ ierr = TSComputeIHessianProductFunctionUU(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fuu);CHKERRQ(ierr); ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr); /* lambda_s^T F_UP w_2 */ ierr = TSComputeIHessianProductFunctionUP(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_dir,ts->vecs_fup);CHKERRQ(ierr); for (nadj=0; nadjnumcost; nadj++) { /* compute the residual */ ierr = VecCopy(ts->vecs_sensi2[nadj],VecsSensi2Temp[nadj]);CHKERRQ(ierr); ierr = VecScale(VecsSensi2Temp[nadj],th->shift);CHKERRQ(ierr); ierr = VecAXPY(VecsSensi2Temp[nadj],-1.,ts->vecs_fuu[nadj]);CHKERRQ(ierr); if (ts->vecs_fup) { ierr = VecAXPY(VecsSensi2Temp[nadj],-1.,ts->vecs_fup[nadj]);CHKERRQ(ierr); } } /* Solve stage equation LHS X = RHS for second-order adjoint */ for (nadj=0; nadjnumcost; nadj++) { KSPConvergedReason kspreason; ierr = KSPSolveTranspose(ksp,VecsSensi2Temp[nadj],VecsDeltaLam2[nadj]);CHKERRQ(ierr); ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); if (kspreason < 0) { ts->reason = TSADJOINT_DIVERGED_LINEAR_SOLVE; ierr = PetscInfo2(ts,"Step=%D, %Dth cost function, transposed linear solve fails, stopping 2nd-order adjoint solve\n",ts->steps,nadj);CHKERRQ(ierr); } } } /* Update sensitivities, and evaluate integrals if there is any */ if(th->endpoint) { /* two-stage Theta methods with th->Theta!=1, th->Theta==1 leads to BEuler */ th->shift = 1./((th->Theta-1.)*adjoint_time_step); th->stage_time = adjoint_ptime; ierr = TSComputeSNESJacobian(ts,th->X0,J,Jpre);CHKERRQ(ierr); ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr); /* R_U at t_n */ if (quadts) { ierr = TSComputeRHSJacobian(quadts,adjoint_ptime,th->X0,quadJ,NULL);CHKERRQ(ierr); } for (nadj=0; nadjnumcost; nadj++) { ierr = MatMultTranspose(J,VecsDeltaLam[nadj],ts->vecs_sensi[nadj]);CHKERRQ(ierr); if (quadJ) { ierr = MatDenseGetColumn(quadJ,nadj,&xarr);CHKERRQ(ierr); ierr = VecPlaceArray(ts->vec_drdu_col,xarr);CHKERRQ(ierr); ierr = VecAXPY(ts->vecs_sensi[nadj],-1.,ts->vec_drdu_col);CHKERRQ(ierr); ierr = VecResetArray(ts->vec_drdu_col);CHKERRQ(ierr); ierr = MatDenseRestoreColumn(quadJ,&xarr);CHKERRQ(ierr); } ierr = VecScale(ts->vecs_sensi[nadj],1./th->shift);CHKERRQ(ierr); } /* Second-order adjoint */ if (ts->vecs_sensi2) { /* U_n */ /* Get w1 at t_n from TLM matrix */ ierr = MatDenseGetColumn(th->MatFwdSensip0,0,&xarr);CHKERRQ(ierr); ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); /* lambda_s^T F_UU w_1 */ ierr = TSComputeIHessianProductFunctionUU(ts,adjoint_ptime,th->X0,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fuu);CHKERRQ(ierr); ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); ierr = MatDenseRestoreColumn(th->MatFwdSensip0,&xarr);CHKERRQ(ierr); /* lambda_s^T F_UU w_2 */ ierr = TSComputeIHessianProductFunctionUP(ts,adjoint_ptime,th->X0,VecsDeltaLam,ts->vec_dir,ts->vecs_fup);CHKERRQ(ierr); for (nadj=0; nadjnumcost; nadj++) { /* 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 */ ierr = MatMultTranspose(J,VecsDeltaLam2[nadj],ts->vecs_sensi2[nadj]);CHKERRQ(ierr); ierr = VecAXPY(ts->vecs_sensi2[nadj],1.,ts->vecs_fuu[nadj]);CHKERRQ(ierr); if (ts->vecs_fup) { ierr = VecAXPY(ts->vecs_sensi2[nadj],1.,ts->vecs_fup[nadj]);CHKERRQ(ierr); } ierr = VecScale(ts->vecs_sensi2[nadj],1./th->shift);CHKERRQ(ierr); } } th->stage_time = ts->ptime; /* recover the old value */ if (ts->vecs_sensip) { /* sensitivities wrt parameters */ /* U_{n+1} */ ierr = TSComputeIJacobianP(ts,th->stage_time,ts->vec_sol,th->Xdot,-1./(th->Theta*adjoint_time_step),ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); if (quadts) { ierr = TSComputeRHSJacobianP(quadts,th->stage_time,ts->vec_sol,quadJp);CHKERRQ(ierr); } for (nadj=0; nadjnumcost; nadj++) { ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr); ierr = VecAXPY(ts->vecs_sensip[nadj],-adjoint_time_step*th->Theta,VecsDeltaMu[nadj]);CHKERRQ(ierr); } if (ts->vecs_sensi2p) { /* second-order */ /* Get w1 at t_{n+1} from TLM matrix */ ierr = MatDenseGetColumn(ts->mat_sensip,0,&xarr);CHKERRQ(ierr); ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); /* lambda_s^T F_PU w_1 */ ierr = TSComputeIHessianProductFunctionPU(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fpu);CHKERRQ(ierr); ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr); /* lambda_s^T F_PP w_2 */ ierr = TSComputeIHessianProductFunctionPP(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_dir,ts->vecs_fpp);CHKERRQ(ierr); for (nadj=0; nadjnumcost; nadj++) { /* 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) */ ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam2[nadj],VecsDeltaMu2[nadj]);CHKERRQ(ierr); ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step*th->Theta,VecsDeltaMu2[nadj]);CHKERRQ(ierr); if (ts->vecs_fpu) { ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step*th->Theta,ts->vecs_fpu[nadj]);CHKERRQ(ierr); } if (ts->vecs_fpp) { ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step*th->Theta,ts->vecs_fpp[nadj]);CHKERRQ(ierr); } } } /* U_s */ ierr = TSComputeIJacobianP(ts,adjoint_ptime,th->X0,th->Xdot,1./((th->Theta-1.0)*adjoint_time_step),ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); if (quadts) { ierr = TSComputeRHSJacobianP(quadts,adjoint_ptime,th->X0,quadJp);CHKERRQ(ierr); } for (nadj=0; nadjnumcost; nadj++) { ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr); ierr = VecAXPY(ts->vecs_sensip[nadj],-adjoint_time_step*(1.0-th->Theta),VecsDeltaMu[nadj]);CHKERRQ(ierr); if (ts->vecs_sensi2p) { /* second-order */ /* Get w1 at t_n from TLM matrix */ ierr = MatDenseGetColumn(th->MatFwdSensip0,0,&xarr);CHKERRQ(ierr); ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); /* lambda_s^T F_PU w_1 */ ierr = TSComputeIHessianProductFunctionPU(ts,adjoint_ptime,th->X0,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fpu);CHKERRQ(ierr); ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); ierr = MatDenseRestoreColumn(th->MatFwdSensip0,&xarr);CHKERRQ(ierr); /* lambda_s^T F_PP w_2 */ ierr = TSComputeIHessianProductFunctionPP(ts,adjoint_ptime,th->X0,VecsDeltaLam,ts->vec_dir,ts->vecs_fpp);CHKERRQ(ierr); for (nadj=0; nadjnumcost; nadj++) { /* 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) */ ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam2[nadj],VecsDeltaMu2[nadj]);CHKERRQ(ierr); ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step*(1.0-th->Theta),VecsDeltaMu2[nadj]);CHKERRQ(ierr); if (ts->vecs_fpu) { ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step*(1.0-th->Theta),ts->vecs_fpu[nadj]);CHKERRQ(ierr); } if (ts->vecs_fpp) { ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step*(1.0-th->Theta),ts->vecs_fpp[nadj]);CHKERRQ(ierr); } } } } } } else { /* one-stage case */ th->shift = 0.0; ierr = TSComputeSNESJacobian(ts,th->X,J,Jpre);CHKERRQ(ierr); /* get -f_y */ ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr); if (quadts) { ierr = TSComputeRHSJacobian(quadts,th->stage_time,th->X,quadJ,NULL);CHKERRQ(ierr); } for (nadj=0; nadjnumcost; nadj++) { ierr = MatMultTranspose(J,VecsDeltaLam[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr); ierr = VecAXPY(ts->vecs_sensi[nadj],-adjoint_time_step,VecsSensiTemp[nadj]);CHKERRQ(ierr); if (quadJ) { ierr = MatDenseGetColumn(quadJ,nadj,&xarr);CHKERRQ(ierr); ierr = VecPlaceArray(ts->vec_drdu_col,xarr);CHKERRQ(ierr); ierr = VecAXPY(ts->vecs_sensi[nadj],adjoint_time_step,ts->vec_drdu_col);CHKERRQ(ierr); ierr = VecResetArray(ts->vec_drdu_col);CHKERRQ(ierr); ierr = MatDenseRestoreColumn(quadJ,&xarr);CHKERRQ(ierr); } } if (ts->vecs_sensip) { ierr = TSComputeIJacobianP(ts,th->stage_time,th->X,th->Xdot,th->shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); if (quadts) { ierr = TSComputeRHSJacobianP(quadts,th->stage_time,th->X,quadJp);CHKERRQ(ierr); } for (nadj=0; nadjnumcost; nadj++) { ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr); ierr = VecAXPY(ts->vecs_sensip[nadj],-adjoint_time_step,VecsDeltaMu[nadj]);CHKERRQ(ierr); if (quadJp) { ierr = MatDenseGetColumn(quadJp,nadj,&xarr);CHKERRQ(ierr); ierr = VecPlaceArray(ts->vec_drdp_col,xarr);CHKERRQ(ierr); ierr = VecAXPY(ts->vecs_sensip[nadj],adjoint_time_step,ts->vec_drdp_col);CHKERRQ(ierr); ierr = VecResetArray(ts->vec_drdp_col);CHKERRQ(ierr); ierr = MatDenseRestoreColumn(quadJp,&xarr);CHKERRQ(ierr); } } } } th->status = TS_STEP_COMPLETE; PetscFunctionReturn(0); } static PetscErrorCode TSInterpolate_Theta(TS ts,PetscReal t,Vec X) { TS_Theta *th = (TS_Theta*)ts->data; PetscReal dt = t - ts->ptime; PetscErrorCode ierr; PetscFunctionBegin; ierr = VecCopy(ts->vec_sol,th->X);CHKERRQ(ierr); if (th->endpoint) dt *= th->Theta; ierr = VecWAXPY(X,dt,th->Xdot,th->X);CHKERRQ(ierr); PetscFunctionReturn(0); } static PetscErrorCode TSEvaluateWLTE_Theta(TS ts,NormType wnormtype,PetscInt *order,PetscReal *wlte) { TS_Theta *th = (TS_Theta*)ts->data; Vec X = ts->vec_sol; /* X = solution */ Vec Y = th->vec_lte_work; /* Y = X + LTE */ PetscReal wltea,wlter; PetscErrorCode ierr; PetscFunctionBegin; if (!th->vec_sol_prev) {*wlte = -1; PetscFunctionReturn(0);} /* Cannot compute LTE in first step or in restart after event */ if (ts->steprestart) {*wlte = -1; PetscFunctionReturn(0);} /* Compute LTE using backward differences with non-constant time step */ { PetscReal h = ts->time_step, h_prev = ts->ptime - ts->ptime_prev; PetscReal a = 1 + h_prev/h; PetscScalar scal[3]; Vec vecs[3]; scal[0] = +1/a; scal[1] = -1/(a-1); scal[2] = +1/(a*(a-1)); vecs[0] = X; vecs[1] = th->X0; vecs[2] = th->vec_sol_prev; ierr = VecCopy(X,Y);CHKERRQ(ierr); ierr = VecMAXPY(Y,3,scal,vecs);CHKERRQ(ierr); ierr = TSErrorWeightedNorm(ts,X,Y,wnormtype,wlte,&wltea,&wlter);CHKERRQ(ierr); } if (order) *order = 2; PetscFunctionReturn(0); } static PetscErrorCode TSRollBack_Theta(TS ts) { TS_Theta *th = (TS_Theta*)ts->data; TS quadts = ts->quadraturets; PetscErrorCode ierr; PetscFunctionBegin; ierr = VecCopy(th->X0,ts->vec_sol);CHKERRQ(ierr); if (quadts && ts->costintegralfwd) { ierr = VecCopy(th->VecCostIntegral0,quadts->vec_sol);CHKERRQ(ierr); } th->status = TS_STEP_INCOMPLETE; if (ts->mat_sensip) { ierr = MatCopy(th->MatFwdSensip0,ts->mat_sensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); } if (quadts && quadts->mat_sensip) { ierr = MatCopy(th->MatIntegralSensip0,quadts->mat_sensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); } PetscFunctionReturn(0); } static PetscErrorCode TSForwardStep_Theta(TS ts) { TS_Theta *th = (TS_Theta*)ts->data; TS quadts = ts->quadraturets; Mat MatDeltaFwdSensip = th->MatDeltaFwdSensip; Vec VecDeltaFwdSensipCol = th->VecDeltaFwdSensipCol; PetscInt ntlm; KSP ksp; Mat J,Jpre,quadJ = NULL,quadJp = NULL; PetscScalar *barr,*xarr; PetscReal previous_shift; PetscErrorCode ierr; PetscFunctionBegin; previous_shift = th->shift; ierr = MatCopy(ts->mat_sensip,th->MatFwdSensip0,SAME_NONZERO_PATTERN);CHKERRQ(ierr); if (quadts && quadts->mat_sensip) { ierr = MatCopy(quadts->mat_sensip,th->MatIntegralSensip0,SAME_NONZERO_PATTERN);CHKERRQ(ierr); } ierr = SNESGetKSP(ts->snes,&ksp);CHKERRQ(ierr); ierr = TSGetIJacobian(ts,&J,&Jpre,NULL,NULL);CHKERRQ(ierr); if (quadts) { ierr = TSGetRHSJacobian(quadts,&quadJ,NULL,NULL,NULL);CHKERRQ(ierr); ierr = TSGetRHSJacobianP(quadts,&quadJp,NULL,NULL);CHKERRQ(ierr); } /* Build RHS */ if (th->endpoint) { /* 2-stage method*/ th->shift = 1./((th->Theta-1.)*th->time_step0); ierr = TSComputeIJacobian(ts,th->ptime0,th->X0,th->Xdot,th->shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr); ierr = MatMatMult(J,ts->mat_sensip,MAT_REUSE_MATRIX,PETSC_DEFAULT,&MatDeltaFwdSensip);CHKERRQ(ierr); ierr = MatScale(MatDeltaFwdSensip,(th->Theta-1.)/th->Theta);CHKERRQ(ierr); /* Add the f_p forcing terms */ if (ts->Jacp) { ierr = TSComputeIJacobianP(ts,th->ptime0,th->X0,th->Xdot,th->shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); ierr = MatAXPY(MatDeltaFwdSensip,(th->Theta-1.)/th->Theta,ts->Jacp,SUBSET_NONZERO_PATTERN);CHKERRQ(ierr); ierr = TSComputeIJacobianP(ts,th->stage_time,ts->vec_sol,th->Xdot,th->shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); ierr = MatAXPY(MatDeltaFwdSensip,-1.,ts->Jacp,SUBSET_NONZERO_PATTERN);CHKERRQ(ierr); } } else { /* 1-stage method */ th->shift = 0.0; ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,th->shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr); ierr = MatMatMult(J,ts->mat_sensip,MAT_REUSE_MATRIX,PETSC_DEFAULT,&MatDeltaFwdSensip);CHKERRQ(ierr); ierr = MatScale(MatDeltaFwdSensip,-1.);CHKERRQ(ierr); /* Add the f_p forcing terms */ if (ts->Jacp) { ierr = TSComputeIJacobianP(ts,th->stage_time,th->X,th->Xdot,th->shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); ierr = MatAXPY(MatDeltaFwdSensip,-1.,ts->Jacp,SUBSET_NONZERO_PATTERN);CHKERRQ(ierr); } } /* Build LHS */ th->shift = previous_shift; /* recover the previous shift used in TSStep_Theta() */ if (th->endpoint) { ierr = TSComputeIJacobian(ts,th->stage_time,ts->vec_sol,th->Xdot,th->shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr); } else { ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,th->shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr); } ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr); /* Evaluate the first stage of integral gradients with the 2-stage method: drdu|t_n*S(t_n) + drdp|t_n This is done before the linear solve because the sensitivity variable S(t_n) will be propagated to S(t_{n+1}) */ if (th->endpoint) { /* 2-stage method only */ if (quadts && quadts->mat_sensip) { ierr = TSComputeRHSJacobian(quadts,th->ptime0,th->X0,quadJ,NULL);CHKERRQ(ierr); ierr = TSComputeRHSJacobianP(quadts,th->ptime0,th->X0,quadJp);CHKERRQ(ierr); ierr = MatTransposeMatMult(ts->mat_sensip,quadJ,MAT_REUSE_MATRIX,PETSC_DEFAULT,&th->MatIntegralSensipTemp);CHKERRQ(ierr); ierr = MatAXPY(th->MatIntegralSensipTemp,1,quadJp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); ierr = MatAXPY(quadts->mat_sensip,th->time_step0*(1.-th->Theta),th->MatIntegralSensipTemp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); } } /* Solve the tangent linear equation for forward sensitivities to parameters */ for (ntlm=0; ntlmnum_tlm; ntlm++) { KSPConvergedReason kspreason; ierr = MatDenseGetColumn(MatDeltaFwdSensip,ntlm,&barr);CHKERRQ(ierr); ierr = VecPlaceArray(VecDeltaFwdSensipCol,barr);CHKERRQ(ierr); if (th->endpoint) { ierr = MatDenseGetColumn(ts->mat_sensip,ntlm,&xarr);CHKERRQ(ierr); ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr); ierr = KSPSolve(ksp,VecDeltaFwdSensipCol,ts->vec_sensip_col);CHKERRQ(ierr); ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr); ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr); } else { ierr = KSPSolve(ksp,VecDeltaFwdSensipCol,VecDeltaFwdSensipCol);CHKERRQ(ierr); } ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr); if (kspreason < 0) { ts->reason = TSFORWARD_DIVERGED_LINEAR_SOLVE; ierr = PetscInfo2(ts,"Step=%D, %Dth tangent linear solve, linear solve fails, stopping tangent linear solve\n",ts->steps,ntlm);CHKERRQ(ierr); } ierr = VecResetArray(VecDeltaFwdSensipCol);CHKERRQ(ierr); ierr = MatDenseRestoreColumn(MatDeltaFwdSensip,&barr);CHKERRQ(ierr); } /* Evaluate the second stage of integral gradients with the 2-stage method: drdu|t_{n+1}*S(t_{n+1}) + drdp|t_{n+1} */ if (quadts && quadts->mat_sensip) { if (!th->endpoint) { ierr = MatAXPY(ts->mat_sensip,1,MatDeltaFwdSensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); /* stage sensitivity */ ierr = TSComputeRHSJacobian(quadts,th->stage_time,th->X,quadJ,NULL);CHKERRQ(ierr); ierr = TSComputeRHSJacobianP(quadts,th->stage_time,th->X,quadJp);CHKERRQ(ierr); ierr = MatTransposeMatMult(ts->mat_sensip,quadJ,MAT_REUSE_MATRIX,PETSC_DEFAULT,&th->MatIntegralSensipTemp);CHKERRQ(ierr); ierr = MatAXPY(th->MatIntegralSensipTemp,1,quadJp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); ierr = MatAXPY(quadts->mat_sensip,th->time_step0,th->MatIntegralSensipTemp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); ierr = MatAXPY(ts->mat_sensip,(1.-th->Theta)/th->Theta,MatDeltaFwdSensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); } else { ierr = TSComputeRHSJacobian(quadts,th->stage_time,ts->vec_sol,quadJ,NULL);CHKERRQ(ierr); ierr = TSComputeRHSJacobianP(quadts,th->stage_time,ts->vec_sol,quadJp);CHKERRQ(ierr); ierr = MatTransposeMatMult(ts->mat_sensip,quadJ,MAT_REUSE_MATRIX,PETSC_DEFAULT,&th->MatIntegralSensipTemp);CHKERRQ(ierr); ierr = MatAXPY(th->MatIntegralSensipTemp,1,quadJp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); ierr = MatAXPY(quadts->mat_sensip,th->time_step0*th->Theta,th->MatIntegralSensipTemp,SAME_NONZERO_PATTERN);CHKERRQ(ierr); } } else { if (!th->endpoint) { ierr = MatAXPY(ts->mat_sensip,1./th->Theta,MatDeltaFwdSensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); } } PetscFunctionReturn(0); } static PetscErrorCode TSForwardGetStages_Theta(TS ts,PetscInt *ns,Mat **stagesensip) { TS_Theta *th = (TS_Theta*)ts->data; PetscFunctionBegin; if (ns) *ns = 1; if (stagesensip) *stagesensip = th->endpoint ? &(th->MatFwdSensip0) : &(th->MatDeltaFwdSensip); PetscFunctionReturn(0); } /*------------------------------------------------------------*/ static PetscErrorCode TSReset_Theta(TS ts) { TS_Theta *th = (TS_Theta*)ts->data; PetscErrorCode ierr; PetscFunctionBegin; ierr = VecDestroy(&th->X);CHKERRQ(ierr); ierr = VecDestroy(&th->Xdot);CHKERRQ(ierr); ierr = VecDestroy(&th->X0);CHKERRQ(ierr); ierr = VecDestroy(&th->affine);CHKERRQ(ierr); ierr = VecDestroy(&th->vec_sol_prev);CHKERRQ(ierr); ierr = VecDestroy(&th->vec_lte_work);CHKERRQ(ierr); ierr = VecDestroy(&th->VecCostIntegral0);CHKERRQ(ierr); PetscFunctionReturn(0); } static PetscErrorCode TSAdjointReset_Theta(TS ts) { TS_Theta *th = (TS_Theta*)ts->data; PetscErrorCode ierr; PetscFunctionBegin; ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaLam);CHKERRQ(ierr); ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaMu);CHKERRQ(ierr); ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaLam2);CHKERRQ(ierr); ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaMu2);CHKERRQ(ierr); ierr = VecDestroyVecs(ts->numcost,&th->VecsSensiTemp);CHKERRQ(ierr); ierr = VecDestroyVecs(ts->numcost,&th->VecsSensi2Temp);CHKERRQ(ierr); PetscFunctionReturn(0); } static PetscErrorCode TSDestroy_Theta(TS ts) { PetscErrorCode ierr; PetscFunctionBegin; ierr = TSReset_Theta(ts);CHKERRQ(ierr); if (ts->dm) { ierr = DMCoarsenHookRemove(ts->dm,DMCoarsenHook_TSTheta,DMRestrictHook_TSTheta,ts);CHKERRQ(ierr); ierr = DMSubDomainHookRemove(ts->dm,DMSubDomainHook_TSTheta,DMSubDomainRestrictHook_TSTheta,ts);CHKERRQ(ierr); } ierr = PetscFree(ts->data);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetTheta_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetTheta_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetEndpoint_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetEndpoint_C",NULL);CHKERRQ(ierr); PetscFunctionReturn(0); } /* This defines the nonlinear equation that is to be solved with SNES G(U) = F[t0+Theta*dt, U, (U-U0)*shift] = 0 */ static PetscErrorCode SNESTSFormFunction_Theta(SNES snes,Vec x,Vec y,TS ts) { TS_Theta *th = (TS_Theta*)ts->data; PetscErrorCode ierr; Vec X0,Xdot; DM dm,dmsave; PetscReal shift = th->shift; PetscFunctionBegin; ierr = SNESGetDM(snes,&dm);CHKERRQ(ierr); /* When using the endpoint variant, this is actually 1/Theta * Xdot */ ierr = TSThetaGetX0AndXdot(ts,dm,&X0,&Xdot);CHKERRQ(ierr); if (x != X0) { ierr = VecAXPBYPCZ(Xdot,-shift,shift,0,X0,x);CHKERRQ(ierr); } else { ierr = VecZeroEntries(Xdot);CHKERRQ(ierr); } /* DM monkey-business allows user code to call TSGetDM() inside of functions evaluated on levels of FAS */ dmsave = ts->dm; ts->dm = dm; ierr = TSComputeIFunction(ts,th->stage_time,x,Xdot,y,PETSC_FALSE);CHKERRQ(ierr); ts->dm = dmsave; ierr = TSThetaRestoreX0AndXdot(ts,dm,&X0,&Xdot);CHKERRQ(ierr); PetscFunctionReturn(0); } static PetscErrorCode SNESTSFormJacobian_Theta(SNES snes,Vec x,Mat A,Mat B,TS ts) { TS_Theta *th = (TS_Theta*)ts->data; PetscErrorCode ierr; Vec Xdot; DM dm,dmsave; PetscReal shift = th->shift; PetscFunctionBegin; ierr = SNESGetDM(snes,&dm);CHKERRQ(ierr); /* Xdot has already been computed in SNESTSFormFunction_Theta (SNES guarantees this) */ ierr = TSThetaGetX0AndXdot(ts,dm,NULL,&Xdot);CHKERRQ(ierr); dmsave = ts->dm; ts->dm = dm; ierr = TSComputeIJacobian(ts,th->stage_time,x,Xdot,shift,A,B,PETSC_FALSE);CHKERRQ(ierr); ts->dm = dmsave; ierr = TSThetaRestoreX0AndXdot(ts,dm,NULL,&Xdot);CHKERRQ(ierr); PetscFunctionReturn(0); } static PetscErrorCode TSForwardSetUp_Theta(TS ts) { TS_Theta *th = (TS_Theta*)ts->data; TS quadts = ts->quadraturets; PetscErrorCode ierr; PetscFunctionBegin; /* combine sensitivities to parameters and sensitivities to initial values into one array */ th->num_tlm = ts->num_parameters; ierr = MatDuplicate(ts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatDeltaFwdSensip);CHKERRQ(ierr); if (quadts && quadts->mat_sensip) { ierr = MatDuplicate(quadts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatIntegralSensipTemp);CHKERRQ(ierr); ierr = MatDuplicate(quadts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatIntegralSensip0);CHKERRQ(ierr); } /* backup sensitivity results for roll-backs */ ierr = MatDuplicate(ts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatFwdSensip0);CHKERRQ(ierr); ierr = VecDuplicate(ts->vec_sol,&th->VecDeltaFwdSensipCol);CHKERRQ(ierr); PetscFunctionReturn(0); } static PetscErrorCode TSForwardReset_Theta(TS ts) { TS_Theta *th = (TS_Theta*)ts->data; TS quadts = ts->quadraturets; PetscErrorCode ierr; PetscFunctionBegin; if (quadts && quadts->mat_sensip) { ierr = MatDestroy(&th->MatIntegralSensipTemp);CHKERRQ(ierr); ierr = MatDestroy(&th->MatIntegralSensip0);CHKERRQ(ierr); } ierr = VecDestroy(&th->VecDeltaFwdSensipCol);CHKERRQ(ierr); ierr = MatDestroy(&th->MatDeltaFwdSensip);CHKERRQ(ierr); ierr = MatDestroy(&th->MatFwdSensip0);CHKERRQ(ierr); PetscFunctionReturn(0); } static PetscErrorCode TSSetUp_Theta(TS ts) { TS_Theta *th = (TS_Theta*)ts->data; TS quadts = ts->quadraturets; PetscBool match; PetscErrorCode ierr; PetscFunctionBegin; if (!th->VecCostIntegral0 && quadts && ts->costintegralfwd) { /* back up cost integral */ ierr = VecDuplicate(quadts->vec_sol,&th->VecCostIntegral0);CHKERRQ(ierr); } if (!th->X) { ierr = VecDuplicate(ts->vec_sol,&th->X);CHKERRQ(ierr); } if (!th->Xdot) { ierr = VecDuplicate(ts->vec_sol,&th->Xdot);CHKERRQ(ierr); } if (!th->X0) { ierr = VecDuplicate(ts->vec_sol,&th->X0);CHKERRQ(ierr); } if (th->endpoint) { ierr = VecDuplicate(ts->vec_sol,&th->affine);CHKERRQ(ierr); } th->order = (th->Theta == 0.5) ? 2 : 1; th->shift = 1/(th->Theta*ts->time_step); ierr = TSGetDM(ts,&ts->dm);CHKERRQ(ierr); ierr = DMCoarsenHookAdd(ts->dm,DMCoarsenHook_TSTheta,DMRestrictHook_TSTheta,ts);CHKERRQ(ierr); ierr = DMSubDomainHookAdd(ts->dm,DMSubDomainHook_TSTheta,DMSubDomainRestrictHook_TSTheta,ts);CHKERRQ(ierr); ierr = TSGetAdapt(ts,&ts->adapt);CHKERRQ(ierr); ierr = TSAdaptCandidatesClear(ts->adapt);CHKERRQ(ierr); ierr = PetscObjectTypeCompare((PetscObject)ts->adapt,TSADAPTNONE,&match);CHKERRQ(ierr); if (!match) { ierr = VecDuplicate(ts->vec_sol,&th->vec_sol_prev);CHKERRQ(ierr); ierr = VecDuplicate(ts->vec_sol,&th->vec_lte_work);CHKERRQ(ierr); } ierr = TSGetSNES(ts,&ts->snes);CHKERRQ(ierr); PetscFunctionReturn(0); } /*------------------------------------------------------------*/ static PetscErrorCode TSAdjointSetUp_Theta(TS ts) { TS_Theta *th = (TS_Theta*)ts->data; PetscErrorCode ierr; PetscFunctionBegin; ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&th->VecsDeltaLam);CHKERRQ(ierr); ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&th->VecsSensiTemp);CHKERRQ(ierr); if (ts->vecs_sensip) { ierr = VecDuplicateVecs(ts->vecs_sensip[0],ts->numcost,&th->VecsDeltaMu);CHKERRQ(ierr); } if (ts->vecs_sensi2) { ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&th->VecsDeltaLam2);CHKERRQ(ierr); ierr = VecDuplicateVecs(ts->vecs_sensi2[0],ts->numcost,&th->VecsSensi2Temp);CHKERRQ(ierr); /* hack ts to make implicit TS solver work when users provide only explicit versions of callbacks (RHSFunction,RHSJacobian,RHSHessian etc.) */ if (!ts->ihessianproduct_fuu) ts->vecs_fuu = ts->vecs_guu; if (!ts->ihessianproduct_fup) ts->vecs_fup = ts->vecs_gup; } if (ts->vecs_sensi2p) { ierr = VecDuplicateVecs(ts->vecs_sensi2p[0],ts->numcost,&th->VecsDeltaMu2);CHKERRQ(ierr); /* hack ts to make implicit TS solver work when users provide only explicit versions of callbacks (RHSFunction,RHSJacobian,RHSHessian etc.) */ if (!ts->ihessianproduct_fpu) ts->vecs_fpu = ts->vecs_gpu; if (!ts->ihessianproduct_fpp) ts->vecs_fpp = ts->vecs_gpp; } PetscFunctionReturn(0); } static PetscErrorCode TSSetFromOptions_Theta(PetscOptionItems *PetscOptionsObject,TS ts) { TS_Theta *th = (TS_Theta*)ts->data; PetscErrorCode ierr; PetscFunctionBegin; ierr = PetscOptionsHead(PetscOptionsObject,"Theta ODE solver options");CHKERRQ(ierr); { ierr = PetscOptionsReal("-ts_theta_theta","Location of stage (0Theta,&th->Theta,NULL);CHKERRQ(ierr); ierr = PetscOptionsBool("-ts_theta_endpoint","Use the endpoint instead of midpoint form of the Theta method","TSThetaSetEndpoint",th->endpoint,&th->endpoint,NULL);CHKERRQ(ierr); ierr = PetscOptionsBool("-ts_theta_initial_guess_extrapolate","Extrapolate stage initial guess from previous solution (sometimes unstable)","TSThetaSetExtrapolate",th->extrapolate,&th->extrapolate,NULL);CHKERRQ(ierr); } ierr = PetscOptionsTail();CHKERRQ(ierr); PetscFunctionReturn(0); } static PetscErrorCode TSView_Theta(TS ts,PetscViewer viewer) { TS_Theta *th = (TS_Theta*)ts->data; PetscBool iascii; PetscErrorCode ierr; PetscFunctionBegin; ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); if (iascii) { ierr = PetscViewerASCIIPrintf(viewer," Theta=%g\n",(double)th->Theta);CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," Extrapolation=%s\n",th->extrapolate ? "yes" : "no");CHKERRQ(ierr); } PetscFunctionReturn(0); } static PetscErrorCode TSThetaGetTheta_Theta(TS ts,PetscReal *theta) { TS_Theta *th = (TS_Theta*)ts->data; PetscFunctionBegin; *theta = th->Theta; PetscFunctionReturn(0); } static PetscErrorCode TSThetaSetTheta_Theta(TS ts,PetscReal theta) { TS_Theta *th = (TS_Theta*)ts->data; PetscFunctionBegin; if (theta <= 0 || 1 < theta) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Theta %g not in range (0,1]",(double)theta); th->Theta = theta; th->order = (th->Theta == 0.5) ? 2 : 1; PetscFunctionReturn(0); } static PetscErrorCode TSThetaGetEndpoint_Theta(TS ts,PetscBool *endpoint) { TS_Theta *th = (TS_Theta*)ts->data; PetscFunctionBegin; *endpoint = th->endpoint; PetscFunctionReturn(0); } static PetscErrorCode TSThetaSetEndpoint_Theta(TS ts,PetscBool flg) { TS_Theta *th = (TS_Theta*)ts->data; PetscFunctionBegin; th->endpoint = flg; PetscFunctionReturn(0); } #if defined(PETSC_HAVE_COMPLEX) static PetscErrorCode TSComputeLinearStability_Theta(TS ts,PetscReal xr,PetscReal xi,PetscReal *yr,PetscReal *yi) { PetscComplex z = xr + xi*PETSC_i,f; TS_Theta *th = (TS_Theta*)ts->data; const PetscReal one = 1.0; PetscFunctionBegin; f = (one + (one - th->Theta)*z)/(one - th->Theta*z); *yr = PetscRealPartComplex(f); *yi = PetscImaginaryPartComplex(f); PetscFunctionReturn(0); } #endif static PetscErrorCode TSGetStages_Theta(TS ts,PetscInt *ns,Vec **Y) { TS_Theta *th = (TS_Theta*)ts->data; PetscFunctionBegin; if (ns) *ns = 1; if (Y) *Y = th->endpoint ? &(th->X0) : &(th->X); PetscFunctionReturn(0); } /* ------------------------------------------------------------ */ /*MC TSTHETA - DAE solver using the implicit Theta method Level: beginner Options Database: + -ts_theta_theta - Location of stage (0 - Use the endpoint (like Crank-Nicholson) instead of midpoint form of the Theta method - -ts_theta_initial_guess_extrapolate - Extrapolate stage initial guess from previous solution (sometimes unstable) Notes: $ -ts_type theta -ts_theta_theta 1.0 corresponds to backward Euler (TSBEULER) $ -ts_type theta -ts_theta_theta 0.5 corresponds to the implicit midpoint rule $ -ts_type theta -ts_theta_theta 0.5 -ts_theta_endpoint corresponds to Crank-Nicholson (TSCN) This method can be applied to DAE. This method is cast as a 1-stage implicit Runge-Kutta method. .vb Theta | Theta ------------- | 1 .ve For the default Theta=0.5, this is also known as the implicit midpoint rule. When the endpoint variant is chosen, the method becomes a 2-stage method with first stage explicit: .vb 0 | 0 0 1 | 1-Theta Theta ------------------- | 1-Theta Theta .ve For the default Theta=0.5, this is the trapezoid rule (also known as Crank-Nicolson, see TSCN). To apply a diagonally implicit RK method to DAE, the stage formula $ Y_i = X + h sum_j a_ij Y'_j is interpreted as a formula for Y'_i in terms of Y_i and known values (Y'_j, jops->reset = TSReset_Theta; ts->ops->adjointreset = TSAdjointReset_Theta; ts->ops->destroy = TSDestroy_Theta; ts->ops->view = TSView_Theta; ts->ops->setup = TSSetUp_Theta; ts->ops->adjointsetup = TSAdjointSetUp_Theta; ts->ops->adjointreset = TSAdjointReset_Theta; ts->ops->step = TSStep_Theta; ts->ops->interpolate = TSInterpolate_Theta; ts->ops->evaluatewlte = TSEvaluateWLTE_Theta; ts->ops->rollback = TSRollBack_Theta; ts->ops->setfromoptions = TSSetFromOptions_Theta; ts->ops->snesfunction = SNESTSFormFunction_Theta; ts->ops->snesjacobian = SNESTSFormJacobian_Theta; #if defined(PETSC_HAVE_COMPLEX) ts->ops->linearstability = TSComputeLinearStability_Theta; #endif ts->ops->getstages = TSGetStages_Theta; ts->ops->adjointstep = TSAdjointStep_Theta; ts->ops->adjointintegral = TSAdjointCostIntegral_Theta; ts->ops->forwardintegral = TSForwardCostIntegral_Theta; ts->default_adapt_type = TSADAPTNONE; ts->ops->forwardsetup = TSForwardSetUp_Theta; ts->ops->forwardreset = TSForwardReset_Theta; ts->ops->forwardstep = TSForwardStep_Theta; ts->ops->forwardgetstages = TSForwardGetStages_Theta; ts->usessnes = PETSC_TRUE; ierr = PetscNewLog(ts,&th);CHKERRQ(ierr); ts->data = (void*)th; th->VecsDeltaLam = NULL; th->VecsDeltaMu = NULL; th->VecsSensiTemp = NULL; th->VecsSensi2Temp = NULL; th->extrapolate = PETSC_FALSE; th->Theta = 0.5; th->order = 2; ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetTheta_C",TSThetaGetTheta_Theta);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetTheta_C",TSThetaSetTheta_Theta);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetEndpoint_C",TSThetaGetEndpoint_Theta);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetEndpoint_C",TSThetaSetEndpoint_Theta);CHKERRQ(ierr); PetscFunctionReturn(0); } /*@ TSThetaGetTheta - Get the abscissa of the stage in (0,1]. Not Collective Input Parameter: . ts - timestepping context Output Parameter: . theta - stage abscissa Note: Use of this function is normally only required to hack TSTHETA to use a modified integration scheme. Level: Advanced .seealso: TSThetaSetTheta() @*/ PetscErrorCode TSThetaGetTheta(TS ts,PetscReal *theta) { PetscErrorCode ierr; PetscFunctionBegin; PetscValidHeaderSpecific(ts,TS_CLASSID,1); PetscValidPointer(theta,2); ierr = PetscUseMethod(ts,"TSThetaGetTheta_C",(TS,PetscReal*),(ts,theta));CHKERRQ(ierr); PetscFunctionReturn(0); } /*@ TSThetaSetTheta - Set the abscissa of the stage in (0,1]. Not Collective Input Parameter: + ts - timestepping context - theta - stage abscissa Options Database: . -ts_theta_theta Level: Intermediate .seealso: TSThetaGetTheta() @*/ PetscErrorCode TSThetaSetTheta(TS ts,PetscReal theta) { PetscErrorCode ierr; PetscFunctionBegin; PetscValidHeaderSpecific(ts,TS_CLASSID,1); ierr = PetscTryMethod(ts,"TSThetaSetTheta_C",(TS,PetscReal),(ts,theta));CHKERRQ(ierr); PetscFunctionReturn(0); } /*@ TSThetaGetEndpoint - Gets whether to use the endpoint variant of the method (e.g. trapezoid/Crank-Nicolson instead of midpoint rule). Not Collective Input Parameter: . ts - timestepping context Output Parameter: . endpoint - PETSC_TRUE when using the endpoint variant Level: Advanced .seealso: TSThetaSetEndpoint(), TSTHETA, TSCN @*/ PetscErrorCode TSThetaGetEndpoint(TS ts,PetscBool *endpoint) { PetscErrorCode ierr; PetscFunctionBegin; PetscValidHeaderSpecific(ts,TS_CLASSID,1); PetscValidPointer(endpoint,2); ierr = PetscUseMethod(ts,"TSThetaGetEndpoint_C",(TS,PetscBool*),(ts,endpoint));CHKERRQ(ierr); PetscFunctionReturn(0); } /*@ TSThetaSetEndpoint - Sets whether to use the endpoint variant of the method (e.g. trapezoid/Crank-Nicolson instead of midpoint rule). Not Collective Input Parameter: + ts - timestepping context - flg - PETSC_TRUE to use the endpoint variant Options Database: . -ts_theta_endpoint Level: Intermediate .seealso: TSTHETA, TSCN @*/ PetscErrorCode TSThetaSetEndpoint(TS ts,PetscBool flg) { PetscErrorCode ierr; PetscFunctionBegin; PetscValidHeaderSpecific(ts,TS_CLASSID,1); ierr = PetscTryMethod(ts,"TSThetaSetEndpoint_C",(TS,PetscBool),(ts,flg));CHKERRQ(ierr); PetscFunctionReturn(0); } /* * TSBEULER and TSCN are straightforward specializations of TSTHETA. * The creation functions for these specializations are below. */ static PetscErrorCode TSSetUp_BEuler(TS ts) { TS_Theta *th = (TS_Theta*)ts->data; PetscErrorCode ierr; PetscFunctionBegin; 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"); 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"); ierr = TSSetUp_Theta(ts);CHKERRQ(ierr); PetscFunctionReturn(0); } static PetscErrorCode TSView_BEuler(TS ts,PetscViewer viewer) { PetscFunctionBegin; PetscFunctionReturn(0); } /*MC TSBEULER - ODE solver using the implicit backward Euler method Level: beginner Notes: TSBEULER is equivalent to TSTHETA with Theta=1.0 $ -ts_type theta -ts_theta_theta 1.0 .seealso: TSCreate(), TS, TSSetType(), TSEULER, TSCN, TSTHETA M*/ PETSC_EXTERN PetscErrorCode TSCreate_BEuler(TS ts) { PetscErrorCode ierr; PetscFunctionBegin; ierr = TSCreate_Theta(ts);CHKERRQ(ierr); ierr = TSThetaSetTheta(ts,1.0);CHKERRQ(ierr); ierr = TSThetaSetEndpoint(ts,PETSC_FALSE);CHKERRQ(ierr); ts->ops->setup = TSSetUp_BEuler; ts->ops->view = TSView_BEuler; PetscFunctionReturn(0); } static PetscErrorCode TSSetUp_CN(TS ts) { TS_Theta *th = (TS_Theta*)ts->data; PetscErrorCode ierr; PetscFunctionBegin; 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"); 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"); ierr = TSSetUp_Theta(ts);CHKERRQ(ierr); PetscFunctionReturn(0); } static PetscErrorCode TSView_CN(TS ts,PetscViewer viewer) { PetscFunctionBegin; PetscFunctionReturn(0); } /*MC TSCN - ODE solver using the implicit Crank-Nicolson method. Level: beginner Notes: TSCN is equivalent to TSTHETA with Theta=0.5 and the "endpoint" option set. I.e. $ -ts_type theta -ts_theta_theta 0.5 -ts_theta_endpoint .seealso: TSCreate(), TS, TSSetType(), TSBEULER, TSTHETA M*/ PETSC_EXTERN PetscErrorCode TSCreate_CN(TS ts) { PetscErrorCode ierr; PetscFunctionBegin; ierr = TSCreate_Theta(ts);CHKERRQ(ierr); ierr = TSThetaSetTheta(ts,0.5);CHKERRQ(ierr); ierr = TSThetaSetEndpoint(ts,PETSC_TRUE);CHKERRQ(ierr); ts->ops->setup = TSSetUp_CN; ts->ops->view = TSView_CN; PetscFunctionReturn(0); }