xref: /petsc/src/ts/impls/implicit/theta/theta.c (revision 6a98f8dc3f2c9149905a87dc2e9d0fedaf64e09a)
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    shift;                    /* Shift parameter for SNES Jacobian, used by forward, TLM and adjoint */
16   PetscInt     order;
17   PetscBool    endpoint;
18   PetscBool    extrapolate;
19   TSStepStatus status;
20   Vec          VecCostIntegral0;         /* Backup for roll-backs due to events, used by cost integral */
21   PetscReal    ptime0;                   /* Backup for ts->ptime, the start time of current time step, used by TLM and cost integral */
22   PetscReal    time_step0;               /* Backup for ts->timestep, the step size of current time step, used by TLM and cost integral*/
23 
24   /* context for sensitivity analysis */
25   PetscInt     num_tlm;                  /* Total number of tangent linear equations */
26   Vec          *VecsDeltaLam;            /* Increment of the adjoint sensitivity w.r.t IC at stage */
27   Vec          *VecsDeltaMu;             /* Increment of the adjoint sensitivity w.r.t P at stage */
28   Vec          *VecsSensiTemp;           /* Vector to be multiplied with Jacobian transpose */
29   Mat          MatDeltaFwdSensip;        /* Increment of the forward sensitivity at stage */
30   Vec          VecDeltaFwdSensipCol;     /* Working vector for holding one column of the sensitivity matrix */
31   Mat          MatFwdSensip0;            /* backup for roll-backs due to events */
32   Mat          MatIntegralSensipTemp;    /* Working vector for forward integral sensitivity */
33   Mat          MatIntegralSensip0;       /* backup for roll-backs due to events */
34   Vec          *VecsDeltaLam2;           /* Increment of the 2nd-order adjoint sensitivity w.r.t IC at stage */
35   Vec          *VecsDeltaMu2;            /* Increment of the 2nd-order adjoint sensitivity w.r.t P at stage */
36   Vec          *VecsSensi2Temp;          /* Working vectors that holds the residual for the second-order adjoint */
37   Vec          *VecsAffine;              /* Working vectors to store residuals */
38   /* context for error estimation */
39   Vec          vec_sol_prev;
40   Vec          vec_lte_work;
41 } TS_Theta;
42 
43 static PetscErrorCode TSThetaGetX0AndXdot(TS ts,DM dm,Vec *X0,Vec *Xdot)
44 {
45   TS_Theta       *th = (TS_Theta*)ts->data;
46   PetscErrorCode ierr;
47 
48   PetscFunctionBegin;
49   if (X0) {
50     if (dm && dm != ts->dm) {
51       ierr = DMGetNamedGlobalVector(dm,"TSTheta_X0",X0);CHKERRQ(ierr);
52     } else *X0 = ts->vec_sol;
53   }
54   if (Xdot) {
55     if (dm && dm != ts->dm) {
56       ierr = DMGetNamedGlobalVector(dm,"TSTheta_Xdot",Xdot);CHKERRQ(ierr);
57     } else *Xdot = th->Xdot;
58   }
59   PetscFunctionReturn(0);
60 }
61 
62 static PetscErrorCode TSThetaRestoreX0AndXdot(TS ts,DM dm,Vec *X0,Vec *Xdot)
63 {
64   PetscErrorCode ierr;
65 
66   PetscFunctionBegin;
67   if (X0) {
68     if (dm && dm != ts->dm) {
69       ierr = DMRestoreNamedGlobalVector(dm,"TSTheta_X0",X0);CHKERRQ(ierr);
70     }
71   }
72   if (Xdot) {
73     if (dm && dm != ts->dm) {
74       ierr = DMRestoreNamedGlobalVector(dm,"TSTheta_Xdot",Xdot);CHKERRQ(ierr);
75     }
76   }
77   PetscFunctionReturn(0);
78 }
79 
80 static PetscErrorCode DMCoarsenHook_TSTheta(DM fine,DM coarse,void *ctx)
81 {
82   PetscFunctionBegin;
83   PetscFunctionReturn(0);
84 }
85 
86 static PetscErrorCode DMRestrictHook_TSTheta(DM fine,Mat restrct,Vec rscale,Mat inject,DM coarse,void *ctx)
87 {
88   TS             ts = (TS)ctx;
89   PetscErrorCode ierr;
90   Vec            X0,Xdot,X0_c,Xdot_c;
91 
92   PetscFunctionBegin;
93   ierr = TSThetaGetX0AndXdot(ts,fine,&X0,&Xdot);CHKERRQ(ierr);
94   ierr = TSThetaGetX0AndXdot(ts,coarse,&X0_c,&Xdot_c);CHKERRQ(ierr);
95   ierr = MatRestrict(restrct,X0,X0_c);CHKERRQ(ierr);
96   ierr = MatRestrict(restrct,Xdot,Xdot_c);CHKERRQ(ierr);
97   ierr = VecPointwiseMult(X0_c,rscale,X0_c);CHKERRQ(ierr);
98   ierr = VecPointwiseMult(Xdot_c,rscale,Xdot_c);CHKERRQ(ierr);
99   ierr = TSThetaRestoreX0AndXdot(ts,fine,&X0,&Xdot);CHKERRQ(ierr);
100   ierr = TSThetaRestoreX0AndXdot(ts,coarse,&X0_c,&Xdot_c);CHKERRQ(ierr);
101   PetscFunctionReturn(0);
102 }
103 
104 static PetscErrorCode DMSubDomainHook_TSTheta(DM dm,DM subdm,void *ctx)
105 {
106   PetscFunctionBegin;
107   PetscFunctionReturn(0);
108 }
109 
110 static PetscErrorCode DMSubDomainRestrictHook_TSTheta(DM dm,VecScatter gscat,VecScatter lscat,DM subdm,void *ctx)
111 {
112   TS             ts = (TS)ctx;
113   PetscErrorCode ierr;
114   Vec            X0,Xdot,X0_sub,Xdot_sub;
115 
116   PetscFunctionBegin;
117   ierr = TSThetaGetX0AndXdot(ts,dm,&X0,&Xdot);CHKERRQ(ierr);
118   ierr = TSThetaGetX0AndXdot(ts,subdm,&X0_sub,&Xdot_sub);CHKERRQ(ierr);
119 
120   ierr = VecScatterBegin(gscat,X0,X0_sub,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
121   ierr = VecScatterEnd(gscat,X0,X0_sub,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
122 
123   ierr = VecScatterBegin(gscat,Xdot,Xdot_sub,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
124   ierr = VecScatterEnd(gscat,Xdot,Xdot_sub,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
125 
126   ierr = TSThetaRestoreX0AndXdot(ts,dm,&X0,&Xdot);CHKERRQ(ierr);
127   ierr = TSThetaRestoreX0AndXdot(ts,subdm,&X0_sub,&Xdot_sub);CHKERRQ(ierr);
128   PetscFunctionReturn(0);
129 }
130 
131 static PetscErrorCode TSThetaEvaluateCostIntegral(TS ts)
132 {
133   TS_Theta       *th = (TS_Theta*)ts->data;
134   TS             quadts = ts->quadraturets;
135   PetscErrorCode ierr;
136 
137   PetscFunctionBegin;
138   if (th->endpoint) {
139     /* Evolve ts->vec_costintegral to compute integrals */
140     if (th->Theta!=1.0) {
141       ierr = TSComputeRHSFunction(quadts,th->ptime0,th->X0,ts->vec_costintegrand);CHKERRQ(ierr);
142       ierr = VecAXPY(quadts->vec_sol,th->time_step0*(1.0-th->Theta),ts->vec_costintegrand);CHKERRQ(ierr);
143     }
144     ierr = TSComputeRHSFunction(quadts,ts->ptime,ts->vec_sol,ts->vec_costintegrand);CHKERRQ(ierr);
145     ierr = VecAXPY(quadts->vec_sol,th->time_step0*th->Theta,ts->vec_costintegrand);CHKERRQ(ierr);
146   } else {
147     ierr = TSComputeRHSFunction(quadts,th->stage_time,th->X,ts->vec_costintegrand);CHKERRQ(ierr);
148     ierr = VecAXPY(quadts->vec_sol,th->time_step0,ts->vec_costintegrand);CHKERRQ(ierr);
149   }
150   PetscFunctionReturn(0);
151 }
152 
153 static PetscErrorCode TSForwardCostIntegral_Theta(TS ts)
154 {
155   TS_Theta       *th = (TS_Theta*)ts->data;
156   TS             quadts = ts->quadraturets;
157   PetscErrorCode ierr;
158 
159   PetscFunctionBegin;
160   /* backup cost integral */
161   ierr = VecCopy(quadts->vec_sol,th->VecCostIntegral0);CHKERRQ(ierr);
162   ierr = TSThetaEvaluateCostIntegral(ts);CHKERRQ(ierr);
163   PetscFunctionReturn(0);
164 }
165 
166 static PetscErrorCode TSAdjointCostIntegral_Theta(TS ts)
167 {
168   TS_Theta       *th = (TS_Theta*)ts->data;
169   PetscErrorCode ierr;
170 
171   PetscFunctionBegin;
172   /* Like TSForwardCostIntegral(), the adjoint cost integral evaluation relies on ptime0 and time_step0. */
173   th->ptime0     = ts->ptime + ts->time_step;
174   th->time_step0 = -ts->time_step;
175   ierr = TSThetaEvaluateCostIntegral(ts);CHKERRQ(ierr);
176   PetscFunctionReturn(0);
177 }
178 
179 static PetscErrorCode TSTheta_SNESSolve(TS ts,Vec b,Vec x)
180 {
181   PetscInt       nits,lits;
182   PetscErrorCode ierr;
183 
184   PetscFunctionBegin;
185   ierr = SNESSolve(ts->snes,b,x);CHKERRQ(ierr);
186   ierr = SNESGetIterationNumber(ts->snes,&nits);CHKERRQ(ierr);
187   ierr = SNESGetLinearSolveIterations(ts->snes,&lits);CHKERRQ(ierr);
188   ts->snes_its += nits; ts->ksp_its += lits;
189   PetscFunctionReturn(0);
190 }
191 
192 static PetscErrorCode TSStep_Theta(TS ts)
193 {
194   TS_Theta       *th = (TS_Theta*)ts->data;
195   PetscInt       rejections = 0;
196   PetscBool      stageok,accept = PETSC_TRUE;
197   PetscReal      next_time_step = ts->time_step;
198   PetscErrorCode ierr;
199 
200   PetscFunctionBegin;
201   if (!ts->steprollback) {
202     if (th->vec_sol_prev) { ierr = VecCopy(th->X0,th->vec_sol_prev);CHKERRQ(ierr); }
203     ierr = VecCopy(ts->vec_sol,th->X0);CHKERRQ(ierr);
204   }
205 
206   th->status     = TS_STEP_INCOMPLETE;
207   while (!ts->reason && th->status != TS_STEP_COMPLETE) {
208     th->shift      = 1/(th->Theta*ts->time_step);
209     th->stage_time = ts->ptime + (th->endpoint ? (PetscReal)1 : th->Theta)*ts->time_step;
210     ierr = VecCopy(th->X0,th->X);CHKERRQ(ierr);
211     if (th->extrapolate && !ts->steprestart) {
212       ierr = VecAXPY(th->X,1/th->shift,th->Xdot);CHKERRQ(ierr);
213     }
214     if (th->endpoint) { /* This formulation assumes linear time-independent mass matrix */
215       if (!th->affine) {ierr = VecDuplicate(ts->vec_sol,&th->affine);CHKERRQ(ierr);}
216       ierr = VecZeroEntries(th->Xdot);CHKERRQ(ierr);
217       ierr = TSComputeIFunction(ts,ts->ptime,th->X0,th->Xdot,th->affine,PETSC_FALSE);CHKERRQ(ierr);
218       ierr = VecScale(th->affine,(th->Theta-1)/th->Theta);CHKERRQ(ierr);
219     } else if (th->affine) { /* Just in case th->endpoint is changed between calls to TSStep_Theta() */
220       ierr = VecZeroEntries(th->affine);CHKERRQ(ierr);
221     }
222     ierr = TSPreStage(ts,th->stage_time);CHKERRQ(ierr);
223     ierr = TSTheta_SNESSolve(ts,th->affine,th->X);CHKERRQ(ierr);
224     ierr = TSPostStage(ts,th->stage_time,0,&th->X);CHKERRQ(ierr);
225     ierr = TSAdaptCheckStage(ts->adapt,ts,th->stage_time,th->X,&stageok);CHKERRQ(ierr);
226     if (!stageok) goto reject_step;
227 
228     th->status = TS_STEP_PENDING;
229     if (th->endpoint) {
230       ierr = VecCopy(th->X,ts->vec_sol);CHKERRQ(ierr);
231     } else {
232       ierr = VecAXPBYPCZ(th->Xdot,-th->shift,th->shift,0,th->X0,th->X);CHKERRQ(ierr);
233       ierr = VecAXPY(ts->vec_sol,ts->time_step,th->Xdot);CHKERRQ(ierr);
234     }
235     ierr = TSAdaptChoose(ts->adapt,ts,ts->time_step,NULL,&next_time_step,&accept);CHKERRQ(ierr);
236     th->status = accept ? TS_STEP_COMPLETE : TS_STEP_INCOMPLETE;
237     if (!accept) {
238       ierr = VecCopy(th->X0,ts->vec_sol);CHKERRQ(ierr);
239       ts->time_step = next_time_step;
240       goto reject_step;
241     }
242 
243     if (ts->forward_solve || ts->costintegralfwd) { /* Save the info for the later use in cost integral evaluation */
244       th->ptime0     = ts->ptime;
245       th->time_step0 = ts->time_step;
246     }
247     ts->ptime += ts->time_step;
248     ts->time_step = next_time_step;
249     break;
250 
251   reject_step:
252     ts->reject++; accept = PETSC_FALSE;
253     if (!ts->reason && ++rejections > ts->max_reject && ts->max_reject >= 0) {
254       ts->reason = TS_DIVERGED_STEP_REJECTED;
255       ierr = PetscInfo2(ts,"Step=%D, step rejections %D greater than current TS allowed, stopping solve\n",ts->steps,rejections);CHKERRQ(ierr);
256     }
257   }
258   PetscFunctionReturn(0);
259 }
260 
261 static PetscErrorCode TSAdjointStepBEuler_Private(TS ts)
262 {
263   TS_Theta       *th = (TS_Theta*)ts->data;
264   TS             quadts = ts->quadraturets;
265   Vec            *VecsDeltaLam = th->VecsDeltaLam,*VecsDeltaMu = th->VecsDeltaMu,*VecsSensiTemp = th->VecsSensiTemp;
266   Vec            *VecsDeltaLam2 = th->VecsDeltaLam2,*VecsDeltaMu2 = th->VecsDeltaMu2,*VecsSensi2Temp = th->VecsSensi2Temp;
267   PetscInt       nadj;
268   Mat            J,Jpre,quadJ = NULL,quadJp = NULL;
269   KSP            ksp;
270   PetscScalar    *xarr;
271   TSEquationType eqtype;
272   PetscBool      isexplicitode = PETSC_FALSE;
273   PetscReal      adjoint_time_step;
274   PetscErrorCode ierr;
275 
276   PetscFunctionBegin;
277   ierr = TSGetEquationType(ts,&eqtype);CHKERRQ(ierr);
278   if (eqtype == TS_EQ_ODE_EXPLICIT) {
279     isexplicitode  = PETSC_TRUE;
280     VecsDeltaLam  = ts->vecs_sensi;
281     VecsDeltaLam2 = ts->vecs_sensi2;
282   }
283   th->status = TS_STEP_INCOMPLETE;
284   ierr = SNESGetKSP(ts->snes,&ksp);CHKERRQ(ierr);
285   ierr = TSGetIJacobian(ts,&J,&Jpre,NULL,NULL);CHKERRQ(ierr);
286   if (quadts) {
287     ierr = TSGetRHSJacobian(quadts,&quadJ,NULL,NULL,NULL);CHKERRQ(ierr);
288     ierr = TSGetRHSJacobianP(quadts,&quadJp,NULL,NULL);CHKERRQ(ierr);
289   }
290 
291   th->stage_time    = ts->ptime;
292   adjoint_time_step = -ts->time_step; /* always positive since time_step is negative */
293 
294   /* Build RHS for first-order adjoint lambda_{n+1}/h + r_u^T(n+1) */
295   if (quadts) {
296     ierr = TSComputeRHSJacobian(quadts,th->stage_time,th->X,quadJ,NULL);CHKERRQ(ierr);
297   }
298 
299   for (nadj=0; nadj<ts->numcost; nadj++) {
300     ierr = VecCopy(ts->vecs_sensi[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr);
301     ierr = VecScale(VecsSensiTemp[nadj],1./adjoint_time_step);CHKERRQ(ierr); /* lambda_{n+1}/h */
302     if (quadJ) {
303       ierr = MatDenseGetColumn(quadJ,nadj,&xarr);CHKERRQ(ierr);
304       ierr = VecPlaceArray(ts->vec_drdu_col,xarr);CHKERRQ(ierr);
305       ierr = VecAXPY(VecsSensiTemp[nadj],1.,ts->vec_drdu_col);CHKERRQ(ierr);
306       ierr = VecResetArray(ts->vec_drdu_col);CHKERRQ(ierr);
307       ierr = MatDenseRestoreColumn(quadJ,&xarr);CHKERRQ(ierr);
308     }
309   }
310 
311   /* Build LHS for first-order adjoint */
312   ierr = TSComputeSNESJacobian(ts,th->X,J,Jpre);CHKERRQ(ierr);
313   ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr);
314 
315   /* Solve stage equation LHS*lambda_s = RHS for first-order adjoint */
316   for (nadj=0; nadj<ts->numcost; nadj++) {
317     KSPConvergedReason kspreason;
318     ierr = KSPSolveTranspose(ksp,VecsSensiTemp[nadj],VecsDeltaLam[nadj]);CHKERRQ(ierr);
319     ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr);
320     if (kspreason < 0) {
321       ts->reason = TSADJOINT_DIVERGED_LINEAR_SOLVE;
322       ierr = PetscInfo2(ts,"Step=%D, %Dth cost function, transposed linear solve fails, stopping 1st-order adjoint solve\n",ts->steps,nadj);CHKERRQ(ierr);
323     }
324   }
325 
326   if (ts->vecs_sensi2) { /* U_{n+1} */
327     /* Get w1 at t_{n+1} from TLM matrix */
328     ierr = MatDenseGetColumn(ts->mat_sensip,0,&xarr);CHKERRQ(ierr);
329     ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr);
330     /* lambda_s^T F_UU w_1 */
331     ierr = TSComputeIHessianProductFunctionUU(ts,th->stage_time,th->X,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fuu);CHKERRQ(ierr);
332     /* lambda_s^T F_UP w_2 */
333     ierr = TSComputeIHessianProductFunctionUP(ts,th->stage_time,th->X,VecsDeltaLam,ts->vec_dir,ts->vecs_fup);CHKERRQ(ierr);
334     for (nadj=0; nadj<ts->numcost; nadj++) { /* compute the residual */
335       ierr = VecCopy(ts->vecs_sensi2[nadj],VecsSensi2Temp[nadj]);CHKERRQ(ierr);
336       ierr = VecScale(VecsSensi2Temp[nadj],1./adjoint_time_step);CHKERRQ(ierr);
337       ierr = VecAXPY(VecsSensi2Temp[nadj],-1.,ts->vecs_fuu[nadj]);CHKERRQ(ierr);
338       if (ts->vecs_fup) {
339         ierr = VecAXPY(VecsSensi2Temp[nadj],-1.,ts->vecs_fup[nadj]);CHKERRQ(ierr);
340       }
341     }
342     /* Solve stage equation LHS X = RHS for second-order adjoint */
343     for (nadj=0; nadj<ts->numcost; nadj++) {
344       KSPConvergedReason kspreason;
345       ierr = KSPSolveTranspose(ksp,VecsSensi2Temp[nadj],VecsDeltaLam2[nadj]);CHKERRQ(ierr);
346       ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr);
347       if (kspreason < 0) {
348         ts->reason = TSADJOINT_DIVERGED_LINEAR_SOLVE;
349         ierr = PetscInfo2(ts,"Step=%D, %Dth cost function, transposed linear solve fails, stopping 2nd-order adjoint solve\n",ts->steps,nadj);CHKERRQ(ierr);
350       }
351     }
352   }
353 
354   /* Update sensitivities, and evaluate integrals if there is any */
355   if (!isexplicitode) {
356     th->shift = 0.0;
357     ierr = TSComputeSNESJacobian(ts,th->X,J,Jpre);CHKERRQ(ierr);
358     ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr);
359     ierr = MatScale(J,-1.);CHKERRQ(ierr);
360     for (nadj=0; nadj<ts->numcost; nadj++) {
361       /* Add f_U \lambda_s to the original RHS */
362       ierr = MatMultTransposeAdd(J,VecsDeltaLam[nadj],VecsSensiTemp[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr);
363       ierr = VecScale(VecsSensiTemp[nadj],adjoint_time_step);CHKERRQ(ierr);
364       ierr = VecCopy(VecsSensiTemp[nadj],ts->vecs_sensi[nadj]);CHKERRQ(ierr);
365       if (ts->vecs_sensi2) {
366         ierr = MatMultTransposeAdd(J,VecsDeltaLam2[nadj],VecsSensi2Temp[nadj],VecsSensi2Temp[nadj]);CHKERRQ(ierr);
367         ierr = VecScale(VecsSensi2Temp[nadj],adjoint_time_step);CHKERRQ(ierr);
368         ierr = VecCopy(VecsSensi2Temp[nadj],ts->vecs_sensi2[nadj]);CHKERRQ(ierr);
369       }
370     }
371   }
372   if (ts->vecs_sensip) {
373     ierr = TSComputeIJacobianP(ts,th->stage_time,th->X,th->Xdot,1./adjoint_time_step,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr); /* get -f_p */
374     if (quadts) {
375       ierr = TSComputeRHSJacobianP(quadts,th->stage_time,th->X,quadJp);CHKERRQ(ierr);
376     }
377     if (ts->vecs_sensi2p) {
378       /* lambda_s^T F_PU w_1 */
379       ierr = TSComputeIHessianProductFunctionPU(ts,th->stage_time,th->X,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fpu);CHKERRQ(ierr);
380       /* lambda_s^T F_PP w_2 */
381       ierr = TSComputeIHessianProductFunctionPP(ts,th->stage_time,th->X,VecsDeltaLam,ts->vec_dir,ts->vecs_fpp);CHKERRQ(ierr);
382     }
383 
384     for (nadj=0; nadj<ts->numcost; nadj++) {
385       ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr);
386       ierr = VecAXPY(ts->vecs_sensip[nadj],-adjoint_time_step,VecsDeltaMu[nadj]);CHKERRQ(ierr);
387       if (quadJp) {
388         ierr = MatDenseGetColumn(quadJp,nadj,&xarr);CHKERRQ(ierr);
389         ierr = VecPlaceArray(ts->vec_drdp_col,xarr);CHKERRQ(ierr);
390         ierr = VecAXPY(ts->vecs_sensip[nadj],adjoint_time_step,ts->vec_drdp_col);CHKERRQ(ierr);
391         ierr = VecResetArray(ts->vec_drdp_col);CHKERRQ(ierr);
392         ierr = MatDenseRestoreColumn(quadJp,&xarr);CHKERRQ(ierr);
393       }
394       if (ts->vecs_sensi2p) {
395         ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam2[nadj],VecsDeltaMu2[nadj]);CHKERRQ(ierr);
396         ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step,VecsDeltaMu2[nadj]);CHKERRQ(ierr);
397         if (ts->vecs_fpu) {
398           ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step,ts->vecs_fpu[nadj]);CHKERRQ(ierr);
399         }
400         if (ts->vecs_fpp) {
401           ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step,ts->vecs_fpp[nadj]);CHKERRQ(ierr);
402         }
403       }
404     }
405   }
406 
407   if (ts->vecs_sensi2) {
408     ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr);
409     ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr);
410   }
411   th->status = TS_STEP_COMPLETE;
412   PetscFunctionReturn(0);
413 }
414 
415 static PetscErrorCode TSAdjointStep_Theta(TS ts)
416 {
417   TS_Theta       *th = (TS_Theta*)ts->data;
418   TS             quadts = ts->quadraturets;
419   Vec            *VecsDeltaLam = th->VecsDeltaLam,*VecsDeltaMu = th->VecsDeltaMu,*VecsSensiTemp = th->VecsSensiTemp;
420   Vec            *VecsDeltaLam2 = th->VecsDeltaLam2,*VecsDeltaMu2 = th->VecsDeltaMu2,*VecsSensi2Temp = th->VecsSensi2Temp;
421   PetscInt       nadj;
422   Mat            J,Jpre,quadJ = NULL,quadJp = NULL;
423   KSP            ksp;
424   PetscScalar    *xarr;
425   PetscReal      adjoint_time_step;
426   PetscReal      adjoint_ptime; /* end time of the adjoint time step (ts->ptime is the start time, ususally ts->ptime is larger than adjoint_ptime) */
427   PetscErrorCode ierr;
428 
429   PetscFunctionBegin;
430   if (th->Theta == 1.) {
431     ierr = TSAdjointStepBEuler_Private(ts);CHKERRQ(ierr);
432     PetscFunctionReturn(0);
433   }
434   th->status = TS_STEP_INCOMPLETE;
435   ierr = SNESGetKSP(ts->snes,&ksp);CHKERRQ(ierr);
436   ierr = TSGetIJacobian(ts,&J,&Jpre,NULL,NULL);CHKERRQ(ierr);
437   if (quadts) {
438     ierr = TSGetRHSJacobian(quadts,&quadJ,NULL,NULL,NULL);CHKERRQ(ierr);
439     ierr = TSGetRHSJacobianP(quadts,&quadJp,NULL,NULL);CHKERRQ(ierr);
440   }
441   /* If endpoint=1, th->ptime and th->X0 will be used; if endpoint=0, th->stage_time and th->X will be used. */
442   th->stage_time    = th->endpoint ? ts->ptime : (ts->ptime+(1.-th->Theta)*ts->time_step);
443   adjoint_ptime     = ts->ptime + ts->time_step;
444   adjoint_time_step = -ts->time_step;  /* always positive since time_step is negative */
445 
446   /* Build RHS for first-order adjoint */
447   /* Cost function has an integral term */
448   if (quadts) {
449     if (th->endpoint) {
450       ierr = TSComputeRHSJacobian(quadts,th->stage_time,ts->vec_sol,quadJ,NULL);CHKERRQ(ierr);
451     } else {
452       ierr = TSComputeRHSJacobian(quadts,th->stage_time,th->X,quadJ,NULL);CHKERRQ(ierr);
453     }
454   }
455 
456   for (nadj=0; nadj<ts->numcost; nadj++) {
457     ierr = VecCopy(ts->vecs_sensi[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr);
458     ierr = VecScale(VecsSensiTemp[nadj],1./(th->Theta*adjoint_time_step));CHKERRQ(ierr);
459     if (quadJ) {
460       ierr = MatDenseGetColumn(quadJ,nadj,&xarr);CHKERRQ(ierr);
461       ierr = VecPlaceArray(ts->vec_drdu_col,xarr);CHKERRQ(ierr);
462       ierr = VecAXPY(VecsSensiTemp[nadj],1.,ts->vec_drdu_col);CHKERRQ(ierr);
463       ierr = VecResetArray(ts->vec_drdu_col);CHKERRQ(ierr);
464       ierr = MatDenseRestoreColumn(quadJ,&xarr);CHKERRQ(ierr);
465     }
466   }
467 
468   /* Build LHS for first-order adjoint */
469   th->shift = 1./(th->Theta*adjoint_time_step);
470   if (th->endpoint) {
471     ierr = TSComputeSNESJacobian(ts,ts->vec_sol,J,Jpre);CHKERRQ(ierr);
472   } else {
473     ierr = TSComputeSNESJacobian(ts,th->X,J,Jpre);CHKERRQ(ierr);
474   }
475   ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr);
476 
477   /* Solve stage equation LHS*lambda_s = RHS for first-order adjoint */
478   for (nadj=0; nadj<ts->numcost; nadj++) {
479     KSPConvergedReason kspreason;
480     ierr = KSPSolveTranspose(ksp,VecsSensiTemp[nadj],VecsDeltaLam[nadj]);CHKERRQ(ierr);
481     ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr);
482     if (kspreason < 0) {
483       ts->reason = TSADJOINT_DIVERGED_LINEAR_SOLVE;
484       ierr = PetscInfo2(ts,"Step=%D, %Dth cost function, transposed linear solve fails, stopping 1st-order adjoint solve\n",ts->steps,nadj);CHKERRQ(ierr);
485     }
486   }
487 
488   /* Second-order adjoint */
489   if (ts->vecs_sensi2) { /* U_{n+1} */
490     if (!th->endpoint) SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Operation not implemented in TS_Theta");
491     /* Get w1 at t_{n+1} from TLM matrix */
492     ierr = MatDenseGetColumn(ts->mat_sensip,0,&xarr);CHKERRQ(ierr);
493     ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr);
494     /* lambda_s^T F_UU w_1 */
495     ierr = TSComputeIHessianProductFunctionUU(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fuu);CHKERRQ(ierr);
496     ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr);
497     ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr);
498     /* lambda_s^T F_UP w_2 */
499     ierr = TSComputeIHessianProductFunctionUP(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_dir,ts->vecs_fup);CHKERRQ(ierr);
500     for (nadj=0; nadj<ts->numcost; nadj++) { /* compute the residual */
501       ierr = VecCopy(ts->vecs_sensi2[nadj],VecsSensi2Temp[nadj]);CHKERRQ(ierr);
502       ierr = VecScale(VecsSensi2Temp[nadj],th->shift);CHKERRQ(ierr);
503       ierr = VecAXPY(VecsSensi2Temp[nadj],-1.,ts->vecs_fuu[nadj]);CHKERRQ(ierr);
504       if (ts->vecs_fup) {
505         ierr = VecAXPY(VecsSensi2Temp[nadj],-1.,ts->vecs_fup[nadj]);CHKERRQ(ierr);
506       }
507     }
508     /* Solve stage equation LHS X = RHS for second-order adjoint */
509     for (nadj=0; nadj<ts->numcost; nadj++) {
510       KSPConvergedReason kspreason;
511       ierr = KSPSolveTranspose(ksp,VecsSensi2Temp[nadj],VecsDeltaLam2[nadj]);CHKERRQ(ierr);
512       ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr);
513       if (kspreason < 0) {
514         ts->reason = TSADJOINT_DIVERGED_LINEAR_SOLVE;
515         ierr = PetscInfo2(ts,"Step=%D, %Dth cost function, transposed linear solve fails, stopping 2nd-order adjoint solve\n",ts->steps,nadj);CHKERRQ(ierr);
516       }
517     }
518   }
519 
520   /* Update sensitivities, and evaluate integrals if there is any */
521   if(th->endpoint) { /* two-stage Theta methods with th->Theta!=1, th->Theta==1 leads to BEuler */
522     th->shift      = 1./((th->Theta-1.)*adjoint_time_step);
523     th->stage_time = adjoint_ptime;
524     ierr           = TSComputeSNESJacobian(ts,th->X0,J,Jpre);CHKERRQ(ierr);
525     ierr           = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr);
526     /* R_U at t_n */
527     if (quadts) {
528       ierr = TSComputeRHSJacobian(quadts,adjoint_ptime,th->X0,quadJ,NULL);CHKERRQ(ierr);
529     }
530     for (nadj=0; nadj<ts->numcost; nadj++) {
531       ierr = MatMultTranspose(J,VecsDeltaLam[nadj],ts->vecs_sensi[nadj]);CHKERRQ(ierr);
532       if (quadJ) {
533         ierr = MatDenseGetColumn(quadJ,nadj,&xarr);CHKERRQ(ierr);
534         ierr = VecPlaceArray(ts->vec_drdu_col,xarr);CHKERRQ(ierr);
535         ierr = VecAXPY(ts->vecs_sensi[nadj],-1.,ts->vec_drdu_col);CHKERRQ(ierr);
536         ierr = VecResetArray(ts->vec_drdu_col);CHKERRQ(ierr);
537         ierr = MatDenseRestoreColumn(quadJ,&xarr);CHKERRQ(ierr);
538       }
539       ierr = VecScale(ts->vecs_sensi[nadj],1./th->shift);CHKERRQ(ierr);
540     }
541 
542     /* Second-order adjoint */
543     if (ts->vecs_sensi2) { /* U_n */
544       /* Get w1 at t_n from TLM matrix */
545       ierr = MatDenseGetColumn(th->MatFwdSensip0,0,&xarr);CHKERRQ(ierr);
546       ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr);
547       /* lambda_s^T F_UU w_1 */
548       ierr = TSComputeIHessianProductFunctionUU(ts,adjoint_ptime,th->X0,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fuu);CHKERRQ(ierr);
549       ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr);
550       ierr = MatDenseRestoreColumn(th->MatFwdSensip0,&xarr);CHKERRQ(ierr);
551       /* lambda_s^T F_UU w_2 */
552       ierr = TSComputeIHessianProductFunctionUP(ts,adjoint_ptime,th->X0,VecsDeltaLam,ts->vec_dir,ts->vecs_fup);CHKERRQ(ierr);
553       for (nadj=0; nadj<ts->numcost; nadj++) {
554         /* 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  */
555         ierr = MatMultTranspose(J,VecsDeltaLam2[nadj],ts->vecs_sensi2[nadj]);CHKERRQ(ierr);
556         ierr = VecAXPY(ts->vecs_sensi2[nadj],1.,ts->vecs_fuu[nadj]);CHKERRQ(ierr);
557         if (ts->vecs_fup) {
558           ierr = VecAXPY(ts->vecs_sensi2[nadj],1.,ts->vecs_fup[nadj]);CHKERRQ(ierr);
559         }
560         ierr = VecScale(ts->vecs_sensi2[nadj],1./th->shift);CHKERRQ(ierr);
561       }
562     }
563 
564     th->stage_time = ts->ptime; /* recover the old value */
565 
566     if (ts->vecs_sensip) { /* sensitivities wrt parameters */
567       /* U_{n+1} */
568       ierr = TSComputeIJacobianP(ts,th->stage_time,ts->vec_sol,th->Xdot,-1./(th->Theta*adjoint_time_step),ts->Jacp,PETSC_FALSE);CHKERRQ(ierr);
569       if (quadts) {
570         ierr = TSComputeRHSJacobianP(quadts,th->stage_time,ts->vec_sol,quadJp);CHKERRQ(ierr);
571       }
572       for (nadj=0; nadj<ts->numcost; nadj++) {
573         ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr);
574         ierr = VecAXPY(ts->vecs_sensip[nadj],-adjoint_time_step*th->Theta,VecsDeltaMu[nadj]);CHKERRQ(ierr);
575       }
576       if (ts->vecs_sensi2p) { /* second-order */
577         /* Get w1 at t_{n+1} from TLM matrix */
578         ierr = MatDenseGetColumn(ts->mat_sensip,0,&xarr);CHKERRQ(ierr);
579         ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr);
580         /* lambda_s^T F_PU w_1 */
581         ierr = TSComputeIHessianProductFunctionPU(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fpu);CHKERRQ(ierr);
582         ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr);
583         ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr);
584 
585         /* lambda_s^T F_PP w_2 */
586         ierr = TSComputeIHessianProductFunctionPP(ts,th->stage_time,ts->vec_sol,VecsDeltaLam,ts->vec_dir,ts->vecs_fpp);CHKERRQ(ierr);
587         for (nadj=0; nadj<ts->numcost; nadj++) {
588           /* Mu2 <- Mu2 + h theta F_P^T Lambda_s + h theta (lambda_s^T F_UU w_1 + lambda_s^T F_UP w_2)  */
589           ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam2[nadj],VecsDeltaMu2[nadj]);CHKERRQ(ierr);
590           ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step*th->Theta,VecsDeltaMu2[nadj]);CHKERRQ(ierr);
591           if (ts->vecs_fpu) {
592             ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step*th->Theta,ts->vecs_fpu[nadj]);CHKERRQ(ierr);
593           }
594           if (ts->vecs_fpp) {
595             ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step*th->Theta,ts->vecs_fpp[nadj]);CHKERRQ(ierr);
596           }
597         }
598       }
599 
600       /* U_s */
601       ierr = TSComputeIJacobianP(ts,adjoint_ptime,th->X0,th->Xdot,1./((th->Theta-1.0)*adjoint_time_step),ts->Jacp,PETSC_FALSE);CHKERRQ(ierr);
602       if (quadts) {
603         ierr = TSComputeRHSJacobianP(quadts,adjoint_ptime,th->X0,quadJp);CHKERRQ(ierr);
604       }
605       for (nadj=0; nadj<ts->numcost; nadj++) {
606         ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr);
607         ierr = VecAXPY(ts->vecs_sensip[nadj],-adjoint_time_step*(1.0-th->Theta),VecsDeltaMu[nadj]);CHKERRQ(ierr);
608         if (ts->vecs_sensi2p) { /* second-order */
609           /* Get w1 at t_n from TLM matrix */
610           ierr = MatDenseGetColumn(th->MatFwdSensip0,0,&xarr);CHKERRQ(ierr);
611           ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr);
612           /* lambda_s^T F_PU w_1 */
613           ierr = TSComputeIHessianProductFunctionPU(ts,adjoint_ptime,th->X0,VecsDeltaLam,ts->vec_sensip_col,ts->vecs_fpu);CHKERRQ(ierr);
614           ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr);
615           ierr = MatDenseRestoreColumn(th->MatFwdSensip0,&xarr);CHKERRQ(ierr);
616           /* lambda_s^T F_PP w_2 */
617           ierr = TSComputeIHessianProductFunctionPP(ts,adjoint_ptime,th->X0,VecsDeltaLam,ts->vec_dir,ts->vecs_fpp);CHKERRQ(ierr);
618           for (nadj=0; nadj<ts->numcost; nadj++) {
619             /* 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) */
620             ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam2[nadj],VecsDeltaMu2[nadj]);CHKERRQ(ierr);
621             ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step*(1.0-th->Theta),VecsDeltaMu2[nadj]);CHKERRQ(ierr);
622             if (ts->vecs_fpu) {
623               ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step*(1.0-th->Theta),ts->vecs_fpu[nadj]);CHKERRQ(ierr);
624             }
625             if (ts->vecs_fpp) {
626               ierr = VecAXPY(ts->vecs_sensi2p[nadj],-adjoint_time_step*(1.0-th->Theta),ts->vecs_fpp[nadj]);CHKERRQ(ierr);
627             }
628           }
629         }
630       }
631     }
632   } else { /* one-stage case */
633     th->shift = 0.0;
634     ierr      = TSComputeSNESJacobian(ts,th->X,J,Jpre);CHKERRQ(ierr); /* get -f_y */
635     ierr      = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr);
636     if (quadts) {
637       ierr  = TSComputeRHSJacobian(quadts,th->stage_time,th->X,quadJ,NULL);CHKERRQ(ierr);
638     }
639     for (nadj=0; nadj<ts->numcost; nadj++) {
640       ierr = MatMultTranspose(J,VecsDeltaLam[nadj],VecsSensiTemp[nadj]);CHKERRQ(ierr);
641       ierr = VecAXPY(ts->vecs_sensi[nadj],-adjoint_time_step,VecsSensiTemp[nadj]);CHKERRQ(ierr);
642       if (quadJ) {
643         ierr = MatDenseGetColumn(quadJ,nadj,&xarr);CHKERRQ(ierr);
644         ierr = VecPlaceArray(ts->vec_drdu_col,xarr);CHKERRQ(ierr);
645         ierr = VecAXPY(ts->vecs_sensi[nadj],adjoint_time_step,ts->vec_drdu_col);CHKERRQ(ierr);
646         ierr = VecResetArray(ts->vec_drdu_col);CHKERRQ(ierr);
647         ierr = MatDenseRestoreColumn(quadJ,&xarr);CHKERRQ(ierr);
648       }
649     }
650     if (ts->vecs_sensip) {
651       ierr = TSComputeIJacobianP(ts,th->stage_time,th->X,th->Xdot,th->shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr);
652       if (quadts) {
653         ierr = TSComputeRHSJacobianP(quadts,th->stage_time,th->X,quadJp);CHKERRQ(ierr);
654       }
655       for (nadj=0; nadj<ts->numcost; nadj++) {
656         ierr = MatMultTranspose(ts->Jacp,VecsDeltaLam[nadj],VecsDeltaMu[nadj]);CHKERRQ(ierr);
657         ierr = VecAXPY(ts->vecs_sensip[nadj],-adjoint_time_step,VecsDeltaMu[nadj]);CHKERRQ(ierr);
658         if (quadJp) {
659           ierr = MatDenseGetColumn(quadJp,nadj,&xarr);CHKERRQ(ierr);
660           ierr = VecPlaceArray(ts->vec_drdp_col,xarr);CHKERRQ(ierr);
661           ierr = VecAXPY(ts->vecs_sensip[nadj],adjoint_time_step,ts->vec_drdp_col);CHKERRQ(ierr);
662           ierr = VecResetArray(ts->vec_drdp_col);CHKERRQ(ierr);
663           ierr = MatDenseRestoreColumn(quadJp,&xarr);CHKERRQ(ierr);
664         }
665       }
666     }
667   }
668 
669   th->status = TS_STEP_COMPLETE;
670   PetscFunctionReturn(0);
671 }
672 
673 static PetscErrorCode TSInterpolate_Theta(TS ts,PetscReal t,Vec X)
674 {
675   TS_Theta       *th = (TS_Theta*)ts->data;
676   PetscReal      dt  = t - ts->ptime;
677   PetscErrorCode ierr;
678 
679   PetscFunctionBegin;
680   ierr = VecCopy(ts->vec_sol,th->X);CHKERRQ(ierr);
681   if (th->endpoint) dt *= th->Theta;
682   ierr = VecWAXPY(X,dt,th->Xdot,th->X);CHKERRQ(ierr);
683   PetscFunctionReturn(0);
684 }
685 
686 static PetscErrorCode TSEvaluateWLTE_Theta(TS ts,NormType wnormtype,PetscInt *order,PetscReal *wlte)
687 {
688   TS_Theta       *th = (TS_Theta*)ts->data;
689   Vec            X = ts->vec_sol;      /* X = solution */
690   Vec            Y = th->vec_lte_work; /* Y = X + LTE  */
691   PetscReal      wltea,wlter;
692   PetscErrorCode ierr;
693 
694   PetscFunctionBegin;
695   if (!th->vec_sol_prev) {*wlte = -1; PetscFunctionReturn(0);}
696   /* Cannot compute LTE in first step or in restart after event */
697   if (ts->steprestart) {*wlte = -1; PetscFunctionReturn(0);}
698   /* Compute LTE using backward differences with non-constant time step */
699   {
700     PetscReal   h = ts->time_step, h_prev = ts->ptime - ts->ptime_prev;
701     PetscReal   a = 1 + h_prev/h;
702     PetscScalar scal[3]; Vec vecs[3];
703     scal[0] = +1/a; scal[1] = -1/(a-1); scal[2] = +1/(a*(a-1));
704     vecs[0] = X;    vecs[1] = th->X0;   vecs[2] = th->vec_sol_prev;
705     ierr = VecCopy(X,Y);CHKERRQ(ierr);
706     ierr = VecMAXPY(Y,3,scal,vecs);CHKERRQ(ierr);
707     ierr = TSErrorWeightedNorm(ts,X,Y,wnormtype,wlte,&wltea,&wlter);CHKERRQ(ierr);
708   }
709   if (order) *order = 2;
710   PetscFunctionReturn(0);
711 }
712 
713 static PetscErrorCode TSRollBack_Theta(TS ts)
714 {
715   TS_Theta       *th = (TS_Theta*)ts->data;
716   TS             quadts = ts->quadraturets;
717   PetscErrorCode ierr;
718 
719   PetscFunctionBegin;
720   ierr = VecCopy(th->X0,ts->vec_sol);CHKERRQ(ierr);
721   if (quadts && ts->costintegralfwd) {
722     ierr = VecCopy(th->VecCostIntegral0,quadts->vec_sol);CHKERRQ(ierr);
723   }
724   th->status = TS_STEP_INCOMPLETE;
725   if (ts->mat_sensip) {
726     ierr = MatCopy(th->MatFwdSensip0,ts->mat_sensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr);
727   }
728   if (quadts && quadts->mat_sensip) {
729     ierr = MatCopy(th->MatIntegralSensip0,quadts->mat_sensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr);
730   }
731   PetscFunctionReturn(0);
732 }
733 
734 static PetscErrorCode TSForwardStep_Theta(TS ts)
735 {
736   TS_Theta       *th = (TS_Theta*)ts->data;
737   TS             quadts = ts->quadraturets;
738   Mat            MatDeltaFwdSensip = th->MatDeltaFwdSensip;
739   Vec            VecDeltaFwdSensipCol = th->VecDeltaFwdSensipCol;
740   PetscInt       ntlm;
741   KSP            ksp;
742   Mat            J,Jpre,quadJ = NULL,quadJp = NULL;
743   PetscScalar    *barr,*xarr;
744   PetscReal      previous_shift;
745   PetscErrorCode ierr;
746 
747   PetscFunctionBegin;
748   previous_shift = th->shift;
749   ierr = MatCopy(ts->mat_sensip,th->MatFwdSensip0,SAME_NONZERO_PATTERN);CHKERRQ(ierr);
750 
751   if (quadts && quadts->mat_sensip) {
752     ierr = MatCopy(quadts->mat_sensip,th->MatIntegralSensip0,SAME_NONZERO_PATTERN);CHKERRQ(ierr);
753   }
754   ierr = SNESGetKSP(ts->snes,&ksp);CHKERRQ(ierr);
755   ierr = TSGetIJacobian(ts,&J,&Jpre,NULL,NULL);CHKERRQ(ierr);
756   if (quadts) {
757     ierr = TSGetRHSJacobian(quadts,&quadJ,NULL,NULL,NULL);CHKERRQ(ierr);
758     ierr = TSGetRHSJacobianP(quadts,&quadJp,NULL,NULL);CHKERRQ(ierr);
759   }
760 
761   /* Build RHS */
762   if (th->endpoint) { /* 2-stage method*/
763     th->shift = 1./((th->Theta-1.)*th->time_step0);
764     ierr = TSComputeIJacobian(ts,th->ptime0,th->X0,th->Xdot,th->shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr);
765     ierr = MatMatMult(J,ts->mat_sensip,MAT_REUSE_MATRIX,PETSC_DEFAULT,&MatDeltaFwdSensip);CHKERRQ(ierr);
766     ierr = MatScale(MatDeltaFwdSensip,(th->Theta-1.)/th->Theta);CHKERRQ(ierr);
767 
768     /* Add the f_p forcing terms */
769     if (ts->Jacp) {
770       ierr = TSComputeIJacobianP(ts,th->ptime0,th->X0,th->Xdot,th->shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr);
771       ierr = MatAXPY(MatDeltaFwdSensip,(th->Theta-1.)/th->Theta,ts->Jacp,SUBSET_NONZERO_PATTERN);CHKERRQ(ierr);
772       ierr = TSComputeIJacobianP(ts,th->stage_time,ts->vec_sol,th->Xdot,th->shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr);
773       ierr = MatAXPY(MatDeltaFwdSensip,-1.,ts->Jacp,SUBSET_NONZERO_PATTERN);CHKERRQ(ierr);
774     }
775   } else { /* 1-stage method */
776     th->shift = 0.0;
777     ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,th->shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr);
778     ierr = MatMatMult(J,ts->mat_sensip,MAT_REUSE_MATRIX,PETSC_DEFAULT,&MatDeltaFwdSensip);CHKERRQ(ierr);
779     ierr = MatScale(MatDeltaFwdSensip,-1.);CHKERRQ(ierr);
780 
781     /* Add the f_p forcing terms */
782     if (ts->Jacp) {
783       ierr = TSComputeIJacobianP(ts,th->stage_time,th->X,th->Xdot,th->shift,ts->Jacp,PETSC_FALSE);CHKERRQ(ierr);
784       ierr = MatAXPY(MatDeltaFwdSensip,-1.,ts->Jacp,SUBSET_NONZERO_PATTERN);CHKERRQ(ierr);
785     }
786   }
787 
788   /* Build LHS */
789   th->shift = previous_shift; /* recover the previous shift used in TSStep_Theta() */
790   if (th->endpoint) {
791     ierr = TSComputeIJacobian(ts,th->stage_time,ts->vec_sol,th->Xdot,th->shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr);
792   } else {
793     ierr = TSComputeIJacobian(ts,th->stage_time,th->X,th->Xdot,th->shift,J,Jpre,PETSC_FALSE);CHKERRQ(ierr);
794   }
795   ierr = KSPSetOperators(ksp,J,Jpre);CHKERRQ(ierr);
796 
797   /*
798     Evaluate the first stage of integral gradients with the 2-stage method:
799     drdu|t_n*S(t_n) + drdp|t_n
800     This is done before the linear solve because the sensitivity variable S(t_n) will be propagated to S(t_{n+1})
801   */
802   if (th->endpoint) { /* 2-stage method only */
803     if (quadts && quadts->mat_sensip) {
804       ierr = TSComputeRHSJacobian(quadts,th->ptime0,th->X0,quadJ,NULL);CHKERRQ(ierr);
805       ierr = TSComputeRHSJacobianP(quadts,th->ptime0,th->X0,quadJp);CHKERRQ(ierr);
806       ierr = MatTransposeMatMult(ts->mat_sensip,quadJ,MAT_REUSE_MATRIX,PETSC_DEFAULT,&th->MatIntegralSensipTemp);CHKERRQ(ierr);
807       ierr = MatAXPY(th->MatIntegralSensipTemp,1,quadJp,SAME_NONZERO_PATTERN);CHKERRQ(ierr);
808       ierr = MatAXPY(quadts->mat_sensip,th->time_step0*(1.-th->Theta),th->MatIntegralSensipTemp,SAME_NONZERO_PATTERN);CHKERRQ(ierr);
809     }
810   }
811 
812   /* Solve the tangent linear equation for forward sensitivities to parameters */
813   for (ntlm=0; ntlm<th->num_tlm; ntlm++) {
814     KSPConvergedReason kspreason;
815     ierr = MatDenseGetColumn(MatDeltaFwdSensip,ntlm,&barr);CHKERRQ(ierr);
816     ierr = VecPlaceArray(VecDeltaFwdSensipCol,barr);CHKERRQ(ierr);
817     if (th->endpoint) {
818       ierr = MatDenseGetColumn(ts->mat_sensip,ntlm,&xarr);CHKERRQ(ierr);
819       ierr = VecPlaceArray(ts->vec_sensip_col,xarr);CHKERRQ(ierr);
820       ierr = KSPSolve(ksp,VecDeltaFwdSensipCol,ts->vec_sensip_col);CHKERRQ(ierr);
821       ierr = VecResetArray(ts->vec_sensip_col);CHKERRQ(ierr);
822       ierr = MatDenseRestoreColumn(ts->mat_sensip,&xarr);CHKERRQ(ierr);
823     } else {
824       ierr = KSPSolve(ksp,VecDeltaFwdSensipCol,VecDeltaFwdSensipCol);CHKERRQ(ierr);
825     }
826     ierr = KSPGetConvergedReason(ksp,&kspreason);CHKERRQ(ierr);
827     if (kspreason < 0) {
828       ts->reason = TSFORWARD_DIVERGED_LINEAR_SOLVE;
829       ierr = PetscInfo2(ts,"Step=%D, %Dth tangent linear solve, linear solve fails, stopping tangent linear solve\n",ts->steps,ntlm);CHKERRQ(ierr);
830     }
831     ierr = VecResetArray(VecDeltaFwdSensipCol);CHKERRQ(ierr);
832     ierr = MatDenseRestoreColumn(MatDeltaFwdSensip,&barr);CHKERRQ(ierr);
833   }
834 
835   /*
836     Evaluate the second stage of integral gradients with the 2-stage method:
837     drdu|t_{n+1}*S(t_{n+1}) + drdp|t_{n+1}
838   */
839   if (quadts && quadts->mat_sensip) {
840     if (!th->endpoint) {
841       ierr = MatAXPY(ts->mat_sensip,1,MatDeltaFwdSensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr); /* stage sensitivity */
842       ierr = TSComputeRHSJacobian(quadts,th->stage_time,th->X,quadJ,NULL);CHKERRQ(ierr);
843       ierr = TSComputeRHSJacobianP(quadts,th->stage_time,th->X,quadJp);CHKERRQ(ierr);
844       ierr = MatTransposeMatMult(ts->mat_sensip,quadJ,MAT_REUSE_MATRIX,PETSC_DEFAULT,&th->MatIntegralSensipTemp);CHKERRQ(ierr);
845       ierr = MatAXPY(th->MatIntegralSensipTemp,1,quadJp,SAME_NONZERO_PATTERN);CHKERRQ(ierr);
846       ierr = MatAXPY(quadts->mat_sensip,th->time_step0,th->MatIntegralSensipTemp,SAME_NONZERO_PATTERN);CHKERRQ(ierr);
847       ierr = MatAXPY(ts->mat_sensip,(1.-th->Theta)/th->Theta,MatDeltaFwdSensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr);
848     } else {
849       ierr = TSComputeRHSJacobian(quadts,th->stage_time,ts->vec_sol,quadJ,NULL);CHKERRQ(ierr);
850       ierr = TSComputeRHSJacobianP(quadts,th->stage_time,ts->vec_sol,quadJp);CHKERRQ(ierr);
851       ierr = MatTransposeMatMult(ts->mat_sensip,quadJ,MAT_REUSE_MATRIX,PETSC_DEFAULT,&th->MatIntegralSensipTemp);CHKERRQ(ierr);
852       ierr = MatAXPY(th->MatIntegralSensipTemp,1,quadJp,SAME_NONZERO_PATTERN);CHKERRQ(ierr);
853       ierr = MatAXPY(quadts->mat_sensip,th->time_step0*th->Theta,th->MatIntegralSensipTemp,SAME_NONZERO_PATTERN);CHKERRQ(ierr);
854     }
855   } else {
856     if (!th->endpoint) {
857       ierr = MatAXPY(ts->mat_sensip,1./th->Theta,MatDeltaFwdSensip,SAME_NONZERO_PATTERN);CHKERRQ(ierr);
858     }
859   }
860   PetscFunctionReturn(0);
861 }
862 
863 static PetscErrorCode TSForwardGetStages_Theta(TS ts,PetscInt *ns,Mat **stagesensip)
864 {
865   TS_Theta *th = (TS_Theta*)ts->data;
866 
867   PetscFunctionBegin;
868   if (ns) *ns = 1;
869   if (stagesensip) *stagesensip = th->endpoint ? &(th->MatFwdSensip0) : &(th->MatDeltaFwdSensip);
870   PetscFunctionReturn(0);
871 }
872 
873 /*------------------------------------------------------------*/
874 static PetscErrorCode TSReset_Theta(TS ts)
875 {
876   TS_Theta       *th = (TS_Theta*)ts->data;
877   PetscErrorCode ierr;
878 
879   PetscFunctionBegin;
880   ierr = VecDestroy(&th->X);CHKERRQ(ierr);
881   ierr = VecDestroy(&th->Xdot);CHKERRQ(ierr);
882   ierr = VecDestroy(&th->X0);CHKERRQ(ierr);
883   ierr = VecDestroy(&th->affine);CHKERRQ(ierr);
884 
885   ierr = VecDestroy(&th->vec_sol_prev);CHKERRQ(ierr);
886   ierr = VecDestroy(&th->vec_lte_work);CHKERRQ(ierr);
887 
888   ierr = VecDestroy(&th->VecCostIntegral0);CHKERRQ(ierr);
889   PetscFunctionReturn(0);
890 }
891 
892 static PetscErrorCode TSAdjointReset_Theta(TS ts)
893 {
894   TS_Theta       *th = (TS_Theta*)ts->data;
895   PetscErrorCode ierr;
896 
897   PetscFunctionBegin;
898   ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaLam);CHKERRQ(ierr);
899   ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaMu);CHKERRQ(ierr);
900   ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaLam2);CHKERRQ(ierr);
901   ierr = VecDestroyVecs(ts->numcost,&th->VecsDeltaMu2);CHKERRQ(ierr);
902   ierr = VecDestroyVecs(ts->numcost,&th->VecsSensiTemp);CHKERRQ(ierr);
903   ierr = VecDestroyVecs(ts->numcost,&th->VecsSensi2Temp);CHKERRQ(ierr);
904   PetscFunctionReturn(0);
905 }
906 
907 static PetscErrorCode TSDestroy_Theta(TS ts)
908 {
909   PetscErrorCode ierr;
910 
911   PetscFunctionBegin;
912   ierr = TSReset_Theta(ts);CHKERRQ(ierr);
913   if (ts->dm) {
914     ierr = DMCoarsenHookRemove(ts->dm,DMCoarsenHook_TSTheta,DMRestrictHook_TSTheta,ts);CHKERRQ(ierr);
915     ierr = DMSubDomainHookRemove(ts->dm,DMSubDomainHook_TSTheta,DMSubDomainRestrictHook_TSTheta,ts);CHKERRQ(ierr);
916   }
917   ierr = PetscFree(ts->data);CHKERRQ(ierr);
918   ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetTheta_C",NULL);CHKERRQ(ierr);
919   ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetTheta_C",NULL);CHKERRQ(ierr);
920   ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetEndpoint_C",NULL);CHKERRQ(ierr);
921   ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetEndpoint_C",NULL);CHKERRQ(ierr);
922   PetscFunctionReturn(0);
923 }
924 
925 /*
926   This defines the nonlinear equation that is to be solved with SNES
927   G(U) = F[t0+Theta*dt, U, (U-U0)*shift] = 0
928 */
929 static PetscErrorCode SNESTSFormFunction_Theta(SNES snes,Vec x,Vec y,TS ts)
930 {
931   TS_Theta       *th = (TS_Theta*)ts->data;
932   PetscErrorCode ierr;
933   Vec            X0,Xdot;
934   DM             dm,dmsave;
935   PetscReal      shift = th->shift;
936 
937   PetscFunctionBegin;
938   ierr = SNESGetDM(snes,&dm);CHKERRQ(ierr);
939   /* When using the endpoint variant, this is actually 1/Theta * Xdot */
940   ierr = TSThetaGetX0AndXdot(ts,dm,&X0,&Xdot);CHKERRQ(ierr);
941   if (x != X0) {
942     ierr = VecAXPBYPCZ(Xdot,-shift,shift,0,X0,x);CHKERRQ(ierr);
943   } else {
944     ierr = VecZeroEntries(Xdot);CHKERRQ(ierr);
945   }
946   /* DM monkey-business allows user code to call TSGetDM() inside of functions evaluated on levels of FAS */
947   dmsave = ts->dm;
948   ts->dm = dm;
949   ierr   = TSComputeIFunction(ts,th->stage_time,x,Xdot,y,PETSC_FALSE);CHKERRQ(ierr);
950   ts->dm = dmsave;
951   ierr   = TSThetaRestoreX0AndXdot(ts,dm,&X0,&Xdot);CHKERRQ(ierr);
952   PetscFunctionReturn(0);
953 }
954 
955 static PetscErrorCode SNESTSFormJacobian_Theta(SNES snes,Vec x,Mat A,Mat B,TS ts)
956 {
957   TS_Theta       *th = (TS_Theta*)ts->data;
958   PetscErrorCode ierr;
959   Vec            Xdot;
960   DM             dm,dmsave;
961   PetscReal      shift = th->shift;
962 
963   PetscFunctionBegin;
964   ierr = SNESGetDM(snes,&dm);CHKERRQ(ierr);
965   /* Xdot has already been computed in SNESTSFormFunction_Theta (SNES guarantees this) */
966   ierr = TSThetaGetX0AndXdot(ts,dm,NULL,&Xdot);CHKERRQ(ierr);
967 
968   dmsave = ts->dm;
969   ts->dm = dm;
970   ierr   = TSComputeIJacobian(ts,th->stage_time,x,Xdot,shift,A,B,PETSC_FALSE);CHKERRQ(ierr);
971   ts->dm = dmsave;
972   ierr   = TSThetaRestoreX0AndXdot(ts,dm,NULL,&Xdot);CHKERRQ(ierr);
973   PetscFunctionReturn(0);
974 }
975 
976 static PetscErrorCode TSForwardSetUp_Theta(TS ts)
977 {
978   TS_Theta       *th = (TS_Theta*)ts->data;
979   TS             quadts = ts->quadraturets;
980   PetscErrorCode ierr;
981 
982   PetscFunctionBegin;
983   /* combine sensitivities to parameters and sensitivities to initial values into one array */
984   th->num_tlm = ts->num_parameters;
985   ierr = MatDuplicate(ts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatDeltaFwdSensip);CHKERRQ(ierr);
986   if (quadts && quadts->mat_sensip) {
987     ierr = MatDuplicate(quadts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatIntegralSensipTemp);CHKERRQ(ierr);
988     ierr = MatDuplicate(quadts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatIntegralSensip0);CHKERRQ(ierr);
989   }
990   /* backup sensitivity results for roll-backs */
991   ierr = MatDuplicate(ts->mat_sensip,MAT_DO_NOT_COPY_VALUES,&th->MatFwdSensip0);CHKERRQ(ierr);
992 
993   ierr = VecDuplicate(ts->vec_sol,&th->VecDeltaFwdSensipCol);CHKERRQ(ierr);
994   PetscFunctionReturn(0);
995 }
996 
997 static PetscErrorCode TSForwardReset_Theta(TS ts)
998 {
999   TS_Theta       *th = (TS_Theta*)ts->data;
1000   TS             quadts = ts->quadraturets;
1001   PetscErrorCode ierr;
1002 
1003   PetscFunctionBegin;
1004   if (quadts && quadts->mat_sensip) {
1005     ierr = MatDestroy(&th->MatIntegralSensipTemp);CHKERRQ(ierr);
1006     ierr = MatDestroy(&th->MatIntegralSensip0);CHKERRQ(ierr);
1007   }
1008   ierr = VecDestroy(&th->VecDeltaFwdSensipCol);CHKERRQ(ierr);
1009   ierr = MatDestroy(&th->MatDeltaFwdSensip);CHKERRQ(ierr);
1010   ierr = MatDestroy(&th->MatFwdSensip0);CHKERRQ(ierr);
1011   PetscFunctionReturn(0);
1012 }
1013 
1014 static PetscErrorCode TSSetUp_Theta(TS ts)
1015 {
1016   TS_Theta       *th = (TS_Theta*)ts->data;
1017   TS             quadts = ts->quadraturets;
1018   PetscBool      match;
1019   PetscErrorCode ierr;
1020 
1021   PetscFunctionBegin;
1022   if (!th->VecCostIntegral0 && quadts && ts->costintegralfwd) { /* back up cost integral */
1023     ierr = VecDuplicate(quadts->vec_sol,&th->VecCostIntegral0);CHKERRQ(ierr);
1024   }
1025   if (!th->X) {
1026     ierr = VecDuplicate(ts->vec_sol,&th->X);CHKERRQ(ierr);
1027   }
1028   if (!th->Xdot) {
1029     ierr = VecDuplicate(ts->vec_sol,&th->Xdot);CHKERRQ(ierr);
1030   }
1031   if (!th->X0) {
1032     ierr = VecDuplicate(ts->vec_sol,&th->X0);CHKERRQ(ierr);
1033   }
1034   if (th->endpoint) {
1035     ierr = VecDuplicate(ts->vec_sol,&th->affine);CHKERRQ(ierr);
1036   }
1037 
1038   th->order = (th->Theta == 0.5) ? 2 : 1;
1039   th->shift = 1/(th->Theta*ts->time_step);
1040 
1041   ierr = TSGetDM(ts,&ts->dm);CHKERRQ(ierr);
1042   ierr = DMCoarsenHookAdd(ts->dm,DMCoarsenHook_TSTheta,DMRestrictHook_TSTheta,ts);CHKERRQ(ierr);
1043   ierr = DMSubDomainHookAdd(ts->dm,DMSubDomainHook_TSTheta,DMSubDomainRestrictHook_TSTheta,ts);CHKERRQ(ierr);
1044 
1045   ierr = TSGetAdapt(ts,&ts->adapt);CHKERRQ(ierr);
1046   ierr = TSAdaptCandidatesClear(ts->adapt);CHKERRQ(ierr);
1047   ierr = PetscObjectTypeCompare((PetscObject)ts->adapt,TSADAPTNONE,&match);CHKERRQ(ierr);
1048   if (!match) {
1049     ierr = VecDuplicate(ts->vec_sol,&th->vec_sol_prev);CHKERRQ(ierr);
1050     ierr = VecDuplicate(ts->vec_sol,&th->vec_lte_work);CHKERRQ(ierr);
1051   }
1052   ierr = TSGetSNES(ts,&ts->snes);CHKERRQ(ierr);
1053   PetscFunctionReturn(0);
1054 }
1055 
1056 /*------------------------------------------------------------*/
1057 
1058 static PetscErrorCode TSAdjointSetUp_Theta(TS ts)
1059 {
1060   TS_Theta       *th = (TS_Theta*)ts->data;
1061   PetscErrorCode ierr;
1062 
1063   PetscFunctionBegin;
1064   ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&th->VecsDeltaLam);CHKERRQ(ierr);
1065   ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&th->VecsSensiTemp);CHKERRQ(ierr);
1066   if (ts->vecs_sensip) {
1067     ierr = VecDuplicateVecs(ts->vecs_sensip[0],ts->numcost,&th->VecsDeltaMu);CHKERRQ(ierr);
1068   }
1069   if (ts->vecs_sensi2) {
1070     ierr = VecDuplicateVecs(ts->vecs_sensi[0],ts->numcost,&th->VecsDeltaLam2);CHKERRQ(ierr);
1071     ierr = VecDuplicateVecs(ts->vecs_sensi2[0],ts->numcost,&th->VecsSensi2Temp);CHKERRQ(ierr);
1072     /* hack ts to make implicit TS solver work when users provide only explicit versions of callbacks (RHSFunction,RHSJacobian,RHSHessian etc.) */
1073     if (!ts->ihessianproduct_fuu) ts->vecs_fuu = ts->vecs_guu;
1074     if (!ts->ihessianproduct_fup) ts->vecs_fup = ts->vecs_gup;
1075   }
1076   if (ts->vecs_sensi2p) {
1077     ierr = VecDuplicateVecs(ts->vecs_sensi2p[0],ts->numcost,&th->VecsDeltaMu2);CHKERRQ(ierr);
1078     /* hack ts to make implicit TS solver work when users provide only explicit versions of callbacks (RHSFunction,RHSJacobian,RHSHessian etc.) */
1079     if (!ts->ihessianproduct_fpu) ts->vecs_fpu = ts->vecs_gpu;
1080     if (!ts->ihessianproduct_fpp) ts->vecs_fpp = ts->vecs_gpp;
1081   }
1082   PetscFunctionReturn(0);
1083 }
1084 
1085 static PetscErrorCode TSSetFromOptions_Theta(PetscOptionItems *PetscOptionsObject,TS ts)
1086 {
1087   TS_Theta       *th = (TS_Theta*)ts->data;
1088   PetscErrorCode ierr;
1089 
1090   PetscFunctionBegin;
1091   ierr = PetscOptionsHead(PetscOptionsObject,"Theta ODE solver options");CHKERRQ(ierr);
1092   {
1093     ierr = PetscOptionsReal("-ts_theta_theta","Location of stage (0<Theta<=1)","TSThetaSetTheta",th->Theta,&th->Theta,NULL);CHKERRQ(ierr);
1094     ierr = PetscOptionsBool("-ts_theta_endpoint","Use the endpoint instead of midpoint form of the Theta method","TSThetaSetEndpoint",th->endpoint,&th->endpoint,NULL);CHKERRQ(ierr);
1095     ierr = PetscOptionsBool("-ts_theta_initial_guess_extrapolate","Extrapolate stage initial guess from previous solution (sometimes unstable)","TSThetaSetExtrapolate",th->extrapolate,&th->extrapolate,NULL);CHKERRQ(ierr);
1096   }
1097   ierr = PetscOptionsTail();CHKERRQ(ierr);
1098   PetscFunctionReturn(0);
1099 }
1100 
1101 static PetscErrorCode TSView_Theta(TS ts,PetscViewer viewer)
1102 {
1103   TS_Theta       *th = (TS_Theta*)ts->data;
1104   PetscBool      iascii;
1105   PetscErrorCode ierr;
1106 
1107   PetscFunctionBegin;
1108   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr);
1109   if (iascii) {
1110     ierr = PetscViewerASCIIPrintf(viewer,"  Theta=%g\n",(double)th->Theta);CHKERRQ(ierr);
1111     ierr = PetscViewerASCIIPrintf(viewer,"  Extrapolation=%s\n",th->extrapolate ? "yes" : "no");CHKERRQ(ierr);
1112   }
1113   PetscFunctionReturn(0);
1114 }
1115 
1116 static PetscErrorCode TSThetaGetTheta_Theta(TS ts,PetscReal *theta)
1117 {
1118   TS_Theta *th = (TS_Theta*)ts->data;
1119 
1120   PetscFunctionBegin;
1121   *theta = th->Theta;
1122   PetscFunctionReturn(0);
1123 }
1124 
1125 static PetscErrorCode TSThetaSetTheta_Theta(TS ts,PetscReal theta)
1126 {
1127   TS_Theta *th = (TS_Theta*)ts->data;
1128 
1129   PetscFunctionBegin;
1130   if (theta <= 0 || 1 < theta) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_OUTOFRANGE,"Theta %g not in range (0,1]",(double)theta);
1131   th->Theta = theta;
1132   th->order = (th->Theta == 0.5) ? 2 : 1;
1133   PetscFunctionReturn(0);
1134 }
1135 
1136 static PetscErrorCode TSThetaGetEndpoint_Theta(TS ts,PetscBool *endpoint)
1137 {
1138   TS_Theta *th = (TS_Theta*)ts->data;
1139 
1140   PetscFunctionBegin;
1141   *endpoint = th->endpoint;
1142   PetscFunctionReturn(0);
1143 }
1144 
1145 static PetscErrorCode TSThetaSetEndpoint_Theta(TS ts,PetscBool flg)
1146 {
1147   TS_Theta *th = (TS_Theta*)ts->data;
1148 
1149   PetscFunctionBegin;
1150   th->endpoint = flg;
1151   PetscFunctionReturn(0);
1152 }
1153 
1154 #if defined(PETSC_HAVE_COMPLEX)
1155 static PetscErrorCode TSComputeLinearStability_Theta(TS ts,PetscReal xr,PetscReal xi,PetscReal *yr,PetscReal *yi)
1156 {
1157   PetscComplex   z   = xr + xi*PETSC_i,f;
1158   TS_Theta       *th = (TS_Theta*)ts->data;
1159   const PetscReal one = 1.0;
1160 
1161   PetscFunctionBegin;
1162   f   = (one + (one - th->Theta)*z)/(one - th->Theta*z);
1163   *yr = PetscRealPartComplex(f);
1164   *yi = PetscImaginaryPartComplex(f);
1165   PetscFunctionReturn(0);
1166 }
1167 #endif
1168 
1169 static PetscErrorCode TSGetStages_Theta(TS ts,PetscInt *ns,Vec **Y)
1170 {
1171   TS_Theta     *th = (TS_Theta*)ts->data;
1172 
1173   PetscFunctionBegin;
1174   if (ns) *ns = 1;
1175   if (Y)  *Y  = th->endpoint ? &(th->X0) : &(th->X);
1176   PetscFunctionReturn(0);
1177 }
1178 
1179 /* ------------------------------------------------------------ */
1180 /*MC
1181       TSTHETA - DAE solver using the implicit Theta method
1182 
1183    Level: beginner
1184 
1185    Options Database:
1186 +  -ts_theta_theta <Theta> - Location of stage (0<Theta<=1)
1187 .  -ts_theta_endpoint <flag> - Use the endpoint (like Crank-Nicholson) instead of midpoint form of the Theta method
1188 -  -ts_theta_initial_guess_extrapolate <flg> - Extrapolate stage initial guess from previous solution (sometimes unstable)
1189 
1190    Notes:
1191 $  -ts_type theta -ts_theta_theta 1.0 corresponds to backward Euler (TSBEULER)
1192 $  -ts_type theta -ts_theta_theta 0.5 corresponds to the implicit midpoint rule
1193 $  -ts_type theta -ts_theta_theta 0.5 -ts_theta_endpoint corresponds to Crank-Nicholson (TSCN)
1194 
1195    This method can be applied to DAE.
1196 
1197    This method is cast as a 1-stage implicit Runge-Kutta method.
1198 
1199 .vb
1200   Theta | Theta
1201   -------------
1202         |  1
1203 .ve
1204 
1205    For the default Theta=0.5, this is also known as the implicit midpoint rule.
1206 
1207    When the endpoint variant is chosen, the method becomes a 2-stage method with first stage explicit:
1208 
1209 .vb
1210   0 | 0         0
1211   1 | 1-Theta   Theta
1212   -------------------
1213     | 1-Theta   Theta
1214 .ve
1215 
1216    For the default Theta=0.5, this is the trapezoid rule (also known as Crank-Nicolson, see TSCN).
1217 
1218    To apply a diagonally implicit RK method to DAE, the stage formula
1219 
1220 $  Y_i = X + h sum_j a_ij Y'_j
1221 
1222    is interpreted as a formula for Y'_i in terms of Y_i and known values (Y'_j, j<i)
1223 
1224 .seealso:  TSCreate(), TS, TSSetType(), TSCN, TSBEULER, TSThetaSetTheta(), TSThetaSetEndpoint()
1225 
1226 M*/
1227 PETSC_EXTERN PetscErrorCode TSCreate_Theta(TS ts)
1228 {
1229   TS_Theta       *th;
1230   PetscErrorCode ierr;
1231 
1232   PetscFunctionBegin;
1233   ts->ops->reset           = TSReset_Theta;
1234   ts->ops->adjointreset    = TSAdjointReset_Theta;
1235   ts->ops->destroy         = TSDestroy_Theta;
1236   ts->ops->view            = TSView_Theta;
1237   ts->ops->setup           = TSSetUp_Theta;
1238   ts->ops->adjointsetup    = TSAdjointSetUp_Theta;
1239   ts->ops->adjointreset    = TSAdjointReset_Theta;
1240   ts->ops->step            = TSStep_Theta;
1241   ts->ops->interpolate     = TSInterpolate_Theta;
1242   ts->ops->evaluatewlte    = TSEvaluateWLTE_Theta;
1243   ts->ops->rollback        = TSRollBack_Theta;
1244   ts->ops->setfromoptions  = TSSetFromOptions_Theta;
1245   ts->ops->snesfunction    = SNESTSFormFunction_Theta;
1246   ts->ops->snesjacobian    = SNESTSFormJacobian_Theta;
1247 #if defined(PETSC_HAVE_COMPLEX)
1248   ts->ops->linearstability = TSComputeLinearStability_Theta;
1249 #endif
1250   ts->ops->getstages       = TSGetStages_Theta;
1251   ts->ops->adjointstep     = TSAdjointStep_Theta;
1252   ts->ops->adjointintegral = TSAdjointCostIntegral_Theta;
1253   ts->ops->forwardintegral = TSForwardCostIntegral_Theta;
1254   ts->default_adapt_type   = TSADAPTNONE;
1255 
1256   ts->ops->forwardsetup     = TSForwardSetUp_Theta;
1257   ts->ops->forwardreset     = TSForwardReset_Theta;
1258   ts->ops->forwardstep      = TSForwardStep_Theta;
1259   ts->ops->forwardgetstages = TSForwardGetStages_Theta;
1260 
1261   ts->usessnes = PETSC_TRUE;
1262 
1263   ierr = PetscNewLog(ts,&th);CHKERRQ(ierr);
1264   ts->data = (void*)th;
1265 
1266   th->VecsDeltaLam    = NULL;
1267   th->VecsDeltaMu     = NULL;
1268   th->VecsSensiTemp   = NULL;
1269   th->VecsSensi2Temp  = NULL;
1270 
1271   th->extrapolate = PETSC_FALSE;
1272   th->Theta       = 0.5;
1273   th->order       = 2;
1274   ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetTheta_C",TSThetaGetTheta_Theta);CHKERRQ(ierr);
1275   ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetTheta_C",TSThetaSetTheta_Theta);CHKERRQ(ierr);
1276   ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaGetEndpoint_C",TSThetaGetEndpoint_Theta);CHKERRQ(ierr);
1277   ierr = PetscObjectComposeFunction((PetscObject)ts,"TSThetaSetEndpoint_C",TSThetaSetEndpoint_Theta);CHKERRQ(ierr);
1278   PetscFunctionReturn(0);
1279 }
1280 
1281 /*@
1282   TSThetaGetTheta - Get the abscissa of the stage in (0,1].
1283 
1284   Not Collective
1285 
1286   Input Parameter:
1287 .  ts - timestepping context
1288 
1289   Output Parameter:
1290 .  theta - stage abscissa
1291 
1292   Note:
1293   Use of this function is normally only required to hack TSTHETA to use a modified integration scheme.
1294 
1295   Level: Advanced
1296 
1297 .seealso: TSThetaSetTheta()
1298 @*/
1299 PetscErrorCode  TSThetaGetTheta(TS ts,PetscReal *theta)
1300 {
1301   PetscErrorCode ierr;
1302 
1303   PetscFunctionBegin;
1304   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
1305   PetscValidPointer(theta,2);
1306   ierr = PetscUseMethod(ts,"TSThetaGetTheta_C",(TS,PetscReal*),(ts,theta));CHKERRQ(ierr);
1307   PetscFunctionReturn(0);
1308 }
1309 
1310 /*@
1311   TSThetaSetTheta - Set the abscissa of the stage in (0,1].
1312 
1313   Not Collective
1314 
1315   Input Parameter:
1316 +  ts - timestepping context
1317 -  theta - stage abscissa
1318 
1319   Options Database:
1320 .  -ts_theta_theta <theta>
1321 
1322   Level: Intermediate
1323 
1324 .seealso: TSThetaGetTheta()
1325 @*/
1326 PetscErrorCode  TSThetaSetTheta(TS ts,PetscReal theta)
1327 {
1328   PetscErrorCode ierr;
1329 
1330   PetscFunctionBegin;
1331   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
1332   ierr = PetscTryMethod(ts,"TSThetaSetTheta_C",(TS,PetscReal),(ts,theta));CHKERRQ(ierr);
1333   PetscFunctionReturn(0);
1334 }
1335 
1336 /*@
1337   TSThetaGetEndpoint - Gets whether to use the endpoint variant of the method (e.g. trapezoid/Crank-Nicolson instead of midpoint rule).
1338 
1339   Not Collective
1340 
1341   Input Parameter:
1342 .  ts - timestepping context
1343 
1344   Output Parameter:
1345 .  endpoint - PETSC_TRUE when using the endpoint variant
1346 
1347   Level: Advanced
1348 
1349 .seealso: TSThetaSetEndpoint(), TSTHETA, TSCN
1350 @*/
1351 PetscErrorCode TSThetaGetEndpoint(TS ts,PetscBool *endpoint)
1352 {
1353   PetscErrorCode ierr;
1354 
1355   PetscFunctionBegin;
1356   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
1357   PetscValidPointer(endpoint,2);
1358   ierr = PetscUseMethod(ts,"TSThetaGetEndpoint_C",(TS,PetscBool*),(ts,endpoint));CHKERRQ(ierr);
1359   PetscFunctionReturn(0);
1360 }
1361 
1362 /*@
1363   TSThetaSetEndpoint - Sets whether to use the endpoint variant of the method (e.g. trapezoid/Crank-Nicolson instead of midpoint rule).
1364 
1365   Not Collective
1366 
1367   Input Parameter:
1368 +  ts - timestepping context
1369 -  flg - PETSC_TRUE to use the endpoint variant
1370 
1371   Options Database:
1372 .  -ts_theta_endpoint <flg>
1373 
1374   Level: Intermediate
1375 
1376 .seealso: TSTHETA, TSCN
1377 @*/
1378 PetscErrorCode TSThetaSetEndpoint(TS ts,PetscBool flg)
1379 {
1380   PetscErrorCode ierr;
1381 
1382   PetscFunctionBegin;
1383   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
1384   ierr = PetscTryMethod(ts,"TSThetaSetEndpoint_C",(TS,PetscBool),(ts,flg));CHKERRQ(ierr);
1385   PetscFunctionReturn(0);
1386 }
1387 
1388 /*
1389  * TSBEULER and TSCN are straightforward specializations of TSTHETA.
1390  * The creation functions for these specializations are below.
1391  */
1392 
1393 static PetscErrorCode TSSetUp_BEuler(TS ts)
1394 {
1395   TS_Theta       *th = (TS_Theta*)ts->data;
1396   PetscErrorCode ierr;
1397 
1398   PetscFunctionBegin;
1399   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");
1400   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");
1401   ierr = TSSetUp_Theta(ts);CHKERRQ(ierr);
1402   PetscFunctionReturn(0);
1403 }
1404 
1405 static PetscErrorCode TSView_BEuler(TS ts,PetscViewer viewer)
1406 {
1407   PetscFunctionBegin;
1408   PetscFunctionReturn(0);
1409 }
1410 
1411 /*MC
1412       TSBEULER - ODE solver using the implicit backward Euler method
1413 
1414   Level: beginner
1415 
1416   Notes:
1417   TSBEULER is equivalent to TSTHETA with Theta=1.0
1418 
1419 $  -ts_type theta -ts_theta_theta 1.0
1420 
1421 .seealso:  TSCreate(), TS, TSSetType(), TSEULER, TSCN, TSTHETA
1422 
1423 M*/
1424 PETSC_EXTERN PetscErrorCode TSCreate_BEuler(TS ts)
1425 {
1426   PetscErrorCode ierr;
1427 
1428   PetscFunctionBegin;
1429   ierr = TSCreate_Theta(ts);CHKERRQ(ierr);
1430   ierr = TSThetaSetTheta(ts,1.0);CHKERRQ(ierr);
1431   ierr = TSThetaSetEndpoint(ts,PETSC_FALSE);CHKERRQ(ierr);
1432   ts->ops->setup = TSSetUp_BEuler;
1433   ts->ops->view  = TSView_BEuler;
1434   PetscFunctionReturn(0);
1435 }
1436 
1437 static PetscErrorCode TSSetUp_CN(TS ts)
1438 {
1439   TS_Theta       *th = (TS_Theta*)ts->data;
1440   PetscErrorCode ierr;
1441 
1442   PetscFunctionBegin;
1443   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");
1444   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");
1445   ierr = TSSetUp_Theta(ts);CHKERRQ(ierr);
1446   PetscFunctionReturn(0);
1447 }
1448 
1449 static PetscErrorCode TSView_CN(TS ts,PetscViewer viewer)
1450 {
1451   PetscFunctionBegin;
1452   PetscFunctionReturn(0);
1453 }
1454 
1455 /*MC
1456       TSCN - ODE solver using the implicit Crank-Nicolson method.
1457 
1458   Level: beginner
1459 
1460   Notes:
1461   TSCN is equivalent to TSTHETA with Theta=0.5 and the "endpoint" option set. I.e.
1462 
1463 $  -ts_type theta -ts_theta_theta 0.5 -ts_theta_endpoint
1464 
1465 .seealso:  TSCreate(), TS, TSSetType(), TSBEULER, TSTHETA
1466 
1467 M*/
1468 PETSC_EXTERN PetscErrorCode TSCreate_CN(TS ts)
1469 {
1470   PetscErrorCode ierr;
1471 
1472   PetscFunctionBegin;
1473   ierr = TSCreate_Theta(ts);CHKERRQ(ierr);
1474   ierr = TSThetaSetTheta(ts,0.5);CHKERRQ(ierr);
1475   ierr = TSThetaSetEndpoint(ts,PETSC_TRUE);CHKERRQ(ierr);
1476   ts->ops->setup = TSSetUp_CN;
1477   ts->ops->view  = TSView_CN;
1478   PetscFunctionReturn(0);
1479 }
1480