Actual source code: eimex.c

petsc-3.7.3 2016-07-24
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  1: /*
  2:  * eimex.c
  3:  *
  4:  *  Created on: Jun 21, 2012
  5:  *      Written by Hong Zhang (zhang@vt.edu), Virginia Tech
  6:  *                 Emil Constantinescu (emconsta@mcs.anl.gov), Argonne National Laboratory
  7:  */
  8: /*MC
  9:       EIMEX - Time stepping with Extrapolated IMEX methods.

 11:   Notes:
 12:   The general system is written as

 14:   G(t,X,Xdot) = F(t,X)

 16:   where G represents the stiff part and F represents the non-stiff part. The user should provide the stiff part
 17:   of the equation using TSSetIFunction() and the non-stiff part with TSSetRHSFunction().
 18:   This method is designed to be linearly implicit on G and can use an approximate and lagged Jacobian.

 20:   Another common form for the system is

 22:   y'=f(x)+g(x)

 24:   The relationship between F,G and f,g is

 26:   G = y'-g(x), F = f(x)

 28:  References
 29:   E. Constantinescu and A. Sandu, Extrapolated implicit-explicit time stepping, SIAM Journal on Scientific
 30: Computing, 31 (2010), pp. 4452-4477.

 32:       Level: beginner

 34: .seealso:  TSCreate(), TS, TSSetType(), TSEIMEXSetMaxRows(), TSEIMEXSetRowCol(), TSEIMEXSetOrdAdapt()

 36:  M*/
 37: #include <petsc/private/tsimpl.h>                /*I   "petscts.h"   I*/
 38: #include <petscdm.h>

 40: static const PetscInt TSEIMEXDefault = 3;

 42: typedef struct {
 43:   PetscInt     row_ind;         /* Return the term T[row_ind][col_ind] */
 44:   PetscInt     col_ind;         /* Return the term T[row_ind][col_ind] */
 45:   PetscInt     nstages;         /* Numbers of stages in current scheme */
 46:   PetscInt     max_rows;        /* Maximum number of rows */
 47:   PetscInt     *N;              /* Harmonic sequence N[max_rows] */
 48:   Vec          Y;               /* States computed during the step, used to complete the step */
 49:   Vec          Z;               /* For shift*(Y-Z) */
 50:   Vec          *T;              /* Working table, size determined by nstages */
 51:   Vec          YdotRHS;         /* f(x) Work vector holding YdotRHS during residual evaluation */
 52:   Vec          YdotI;           /* xdot-g(x) Work vector holding YdotI = G(t,x,xdot) when xdot =0 */
 53:   Vec          Ydot;            /* f(x)+g(x) Work vector */
 54:   Vec          VecSolPrev;      /* Work vector holding the solution from the previous step (used for interpolation) */
 55:   PetscReal    shift;
 56:   PetscReal    ctime;
 57:   PetscBool    recompute_jacobian; /* Recompute the Jacobian at each stage, default is to freeze the Jacobian at the start of each step */
 58:   PetscBool    ord_adapt;       /* order adapativity */
 59:   TSStepStatus status;
 60: } TS_EIMEX;

 62: /* This function is pure */
 63: static PetscInt Map(PetscInt i, PetscInt j, PetscInt s)
 64: {
 65:   return ((2*s-j+1)*j/2+i-j);
 66: }


 71: static PetscErrorCode TSEvaluateStep_EIMEX(TS ts,PetscInt order,Vec X,PetscBool *done)
 72: {
 73:   TS_EIMEX        *ext = (TS_EIMEX*)ts->data;
 74:   const PetscInt  ns = ext->nstages;
 77:   VecCopy(ext->T[Map(ext->row_ind,ext->col_ind,ns)],X);
 78:   return(0);
 79: }


 84: static PetscErrorCode TSStage_EIMEX(TS ts,PetscInt istage)
 85: {
 86:   TS_EIMEX        *ext = (TS_EIMEX*)ts->data;
 87:   PetscReal       h;
 88:   Vec             Y=ext->Y, Z=ext->Z;
 89:   SNES            snes;
 90:   TSAdapt         adapt;
 91:   PetscInt        i,its,lits;
 92:   PetscBool       accept;
 93:   PetscErrorCode  ierr;

 96:   TSGetSNES(ts,&snes);
 97:   h = ts->time_step/ext->N[istage];/* step size for the istage-th stage */
 98:   ext->shift = 1./h;
 99:   SNESSetLagJacobian(snes,-2); /* Recompute the Jacobian on this solve, but not again */
100:   VecCopy(ext->VecSolPrev,Y); /* Take the previous solution as intial step */

102:   for(i=0; i<ext->N[istage]; i++){
103:     ext->ctime = ts->ptime + h*i;
104:     VecCopy(Y,Z);/* Save the solution of the previous substep */
105:     SNESSolve(snes,NULL,Y);
106:     SNESGetIterationNumber(snes,&its);
107:     SNESGetLinearSolveIterations(snes,&lits);
108:     ts->snes_its += its; ts->ksp_its += lits;
109:     TSGetAdapt(ts,&adapt);
110:     TSAdaptCheckStage(adapt,ts,ext->ctime,Y,&accept);
111:   }

113:   return(0);
114: }


119: static PetscErrorCode TSStep_EIMEX(TS ts)
120: {
121:   TS_EIMEX        *ext = (TS_EIMEX*)ts->data;
122:   const PetscInt  ns = ext->nstages;
123:   Vec             *T=ext->T, Y=ext->Y;

125:   SNES            snes;
126:   PetscInt        i,j;
127:   PetscBool       accept = PETSC_FALSE;
128:   PetscErrorCode  ierr;
129:   PetscReal       alpha,local_error;

132:   TSGetSNES(ts,&snes);
133:   SNESSetType(snes,"ksponly");
134:   ext->status = TS_STEP_INCOMPLETE;

136:   VecCopy(ts->vec_sol,ext->VecSolPrev);

138:   /* Apply n_j steps of the base method to obtain solutions of T(j,1),1<=j<=s */
139:   for(j=0; j<ns; j++){
140:         TSStage_EIMEX(ts,j);
141:         VecCopy(Y,T[j]);
142:   }

144:   for(i=1;i<ns;i++){
145:     for(j=i;j<ns;j++){
146:       alpha = -(PetscReal)ext->N[j]/ext->N[j-i];
147:       VecAXPBYPCZ(T[Map(j,i,ns)],alpha,1.0,0,T[Map(j,i-1,ns)],T[Map(j-1,i-1,ns)]);/* T[j][i]=alpha*T[j][i-1]+T[j-1][i-1] */
148:       alpha = 1.0/(1.0 + alpha);
149:       VecScale(T[Map(j,i,ns)],alpha);
150:     }
151:   }

153:   TSEvaluateStep(ts,ns,ts->vec_sol,NULL);/*update ts solution */

155:   if(ext->ord_adapt && ext->nstages < ext->max_rows){
156:         accept = PETSC_FALSE;
157:         while(!accept && ext->nstages < ext->max_rows){
158:           TSErrorWeightedNorm(ts,ts->vec_sol,T[Map(ext->nstages-1,ext->nstages-2,ext->nstages)],ts->adapt->wnormtype,&local_error);
159:           accept = (local_error < 1.0)? PETSC_TRUE : PETSC_FALSE;

161:           if(!accept){/* add one more stage*/
162:             TSStage_EIMEX(ts,ext->nstages);
163:             ext->nstages++; ext->row_ind++; ext->col_ind++;
164:             /*T table need to be recycled*/
165:             VecDuplicateVecs(ts->vec_sol,(1+ext->nstages)*ext->nstages/2,&ext->T);
166:             for(i=0; i<ext->nstages-1; i++){
167:               for(j=0; j<=i; j++){
168:                 VecCopy(T[Map(i,j,ext->nstages-1)],ext->T[Map(i,j,ext->nstages)]);
169:               }
170:             }
171:             VecDestroyVecs(ext->nstages*(ext->nstages-1)/2,&T);
172:             T = ext->T; /*reset the pointer*/
173:             /*recycling finished, store the new solution*/
174:             VecCopy(Y,T[ext->nstages-1]);
175:             /*extrapolation for the newly added stage*/
176:             for(i=1;i<ext->nstages;i++){
177:               alpha = -(PetscReal)ext->N[ext->nstages-1]/ext->N[ext->nstages-1-i];
178:               VecAXPBYPCZ(T[Map(ext->nstages-1,i,ext->nstages)],alpha,1.0,0,T[Map(ext->nstages-1,i-1,ext->nstages)],T[Map(ext->nstages-1-1,i-1,ext->nstages)]);/*T[ext->nstages-1][i]=alpha*T[ext->nstages-1][i-1]+T[ext->nstages-1-1][i-1]*/
179:               alpha = 1.0/(1.0 + alpha);
180:               VecScale(T[Map(ext->nstages-1,i,ext->nstages)],alpha);
181:             }
182:             /*update ts solution */
183:             TSEvaluateStep(ts,ext->nstages,ts->vec_sol,NULL);
184:           }/*end if !accept*/
185:         }/*end while*/

187:         if(ext->nstages == ext->max_rows){
188:                 PetscInfo(ts,"Max number of rows has been used\n");
189:         }
190:   }/*end if ext->ord_adapt*/
191:   ts->ptime += ts->time_step;
192:   ext->status = TS_STEP_COMPLETE;

194:   if (ext->status != TS_STEP_COMPLETE && !ts->reason) ts->reason = TS_DIVERGED_STEP_REJECTED;
195:   return(0);
196: }

198: /* cubic Hermit spline */
201: static PetscErrorCode TSInterpolate_EIMEX(TS ts,PetscReal itime,Vec X)
202: {
203:   TS_EIMEX       *ext = (TS_EIMEX*)ts->data;
204:   PetscReal      t,a,b;
205:   Vec            Y0=ext->VecSolPrev,Y1=ext->Y,Ydot=ext->Ydot,YdotI=ext->YdotI;
206:   const PetscReal h = ts->ptime - ts->ptime_prev;
209:   t = (itime -ts->ptime + h)/h;
210:   /* YdotI = -f(x)-g(x) */

212:   VecZeroEntries(Ydot);
213:   TSComputeIFunction(ts,ts->ptime-h,Y0,Ydot,YdotI,PETSC_FALSE);

215:   a    = 2.0*t*t*t - 3.0*t*t + 1.0;
216:   b    = -(t*t*t - 2.0*t*t + t)*h;
217:   VecAXPBYPCZ(X,a,b,0.0,Y0,YdotI);

219:   TSComputeIFunction(ts,ts->ptime,Y1,Ydot,YdotI,PETSC_FALSE);
220:   a    = -2.0*t*t*t+3.0*t*t;
221:   b    = -(t*t*t - t*t)*h;
222:   VecAXPBYPCZ(X,a,b,1.0,Y1,YdotI);

224:   return(0);
225: }


230: static PetscErrorCode TSReset_EIMEX(TS ts)
231: {
232:   TS_EIMEX        *ext = (TS_EIMEX*)ts->data;
233:   PetscInt        ns;
234:   PetscErrorCode  ierr;

237:   ns = ext->nstages;
238:   VecDestroyVecs((1+ns)*ns/2,&ext->T);
239:   VecDestroy(&ext->Y);
240:   VecDestroy(&ext->Z);
241:   VecDestroy(&ext->YdotRHS);
242:   VecDestroy(&ext->YdotI);
243:   VecDestroy(&ext->Ydot);
244:   VecDestroy(&ext->VecSolPrev);
245:   PetscFree(ext->N);
246:   return(0);
247: }

251: static PetscErrorCode TSDestroy_EIMEX(TS ts)
252: {
253:   PetscErrorCode  ierr;

256:   TSReset_EIMEX(ts);
257:   PetscFree(ts->data);
258:   PetscObjectComposeFunction((PetscObject)ts,"TSEIMEXSetMaxRows_C",NULL);
259:   PetscObjectComposeFunction((PetscObject)ts,"TSEIMEXSetRowCol_C",NULL);
260:   PetscObjectComposeFunction((PetscObject)ts,"TSEIMEXSetOrdAdapt_C",NULL);

262:   return(0);
263: }


268: static PetscErrorCode TSEIMEXGetVecs(TS ts,DM dm,Vec *Z,Vec *Ydot,Vec *YdotI, Vec *YdotRHS)
269: {
270:   TS_EIMEX       *ext = (TS_EIMEX*)ts->data;

274:   if (Z) {
275:     if (dm && dm != ts->dm) {
276:       DMGetNamedGlobalVector(dm,"TSEIMEX_Z",Z);
277:     } else *Z = ext->Z;
278:   }
279:   if (Ydot) {
280:     if (dm && dm != ts->dm) {
281:       DMGetNamedGlobalVector(dm,"TSEIMEX_Ydot",Ydot);
282:     } else *Ydot = ext->Ydot;
283:   }
284:   if (YdotI) {
285:     if (dm && dm != ts->dm) {
286:       DMGetNamedGlobalVector(dm,"TSEIMEX_YdotI",YdotI);
287:     } else *YdotI = ext->YdotI;
288:   }
289:   if (YdotRHS) {
290:     if (dm && dm != ts->dm) {
291:       DMGetNamedGlobalVector(dm,"TSEIMEX_YdotRHS",YdotRHS);
292:     } else *YdotRHS = ext->YdotRHS;
293:   }
294:   return(0);
295: }


300: static PetscErrorCode TSEIMEXRestoreVecs(TS ts,DM dm,Vec *Z,Vec *Ydot,Vec *YdotI,Vec *YdotRHS)
301: {

305:   if (Z) {
306:     if (dm && dm != ts->dm) {
307:       DMRestoreNamedGlobalVector(dm,"TSEIMEX_Z",Z);
308:     }
309:   }
310:   if (Ydot) {
311:     if (dm && dm != ts->dm) {
312:       DMRestoreNamedGlobalVector(dm,"TSEIMEX_Ydot",Ydot);
313:     }
314:   }
315:   if (YdotI) {
316:     if (dm && dm != ts->dm) {
317:       DMRestoreNamedGlobalVector(dm,"TSEIMEX_YdotI",YdotI);
318:     }
319:   }
320:   if (YdotRHS) {
321:     if (dm && dm != ts->dm) {
322:       DMRestoreNamedGlobalVector(dm,"TSEIMEX_YdotRHS",YdotRHS);
323:     }
324:   }
325:   return(0);
326: }


329: /*
330:   This defines the nonlinear equation that is to be solved with SNES
331:   Fn[t0+Theta*dt, U, (U-U0)*shift] = 0
332:   In the case of Backward Euler, Fn = (U-U0)/h-g(t1,U))
333:   Since FormIFunction calculates G = ydot - g(t,y), ydot will be set to (U-U0)/h
334: */
337: static PetscErrorCode SNESTSFormFunction_EIMEX(SNES snes,Vec X,Vec G,TS ts)
338: {
339:   TS_EIMEX        *ext = (TS_EIMEX*)ts->data;
340:   PetscErrorCode  ierr;
341:   Vec             Ydot,Z;
342:   DM              dm,dmsave;

345:   VecZeroEntries(G);

347:   SNESGetDM(snes,&dm);
348:   TSEIMEXGetVecs(ts,dm,&Z,&Ydot,NULL,NULL);
349:   VecZeroEntries(Ydot);
350:   dmsave = ts->dm;
351:   ts->dm = dm;
352:   TSComputeIFunction(ts,ext->ctime,X,Ydot,G,PETSC_FALSE);
353:   /* PETSC_FALSE indicates non-imex, adding explicit RHS to the implicit I function.  */
354:   VecCopy(G,Ydot);
355:   ts->dm = dmsave;
356:   TSEIMEXRestoreVecs(ts,dm,&Z,&Ydot,NULL,NULL);

358:   return(0);
359: }

361: /*
362:  This defined the Jacobian matrix for SNES. Jn = (I/h-g'(t,y))
363:  */
366: static PetscErrorCode SNESTSFormJacobian_EIMEX(SNES snes,Vec X,Mat A,Mat B,TS ts)
367: {
368:   TS_EIMEX        *ext = (TS_EIMEX*)ts->data;
369:   Vec             Ydot;
370:   PetscErrorCode  ierr;
371:   DM              dm,dmsave;
373:   SNESGetDM(snes,&dm);
374:   TSEIMEXGetVecs(ts,dm,NULL,&Ydot,NULL,NULL);
375:   /*  VecZeroEntries(Ydot); */
376:   /* ext->Ydot have already been computed in SNESTSFormFunction_EIMEX (SNES guarantees this) */
377:   dmsave = ts->dm;
378:   ts->dm = dm;
379:   TSComputeIJacobian(ts,ts->ptime,X,Ydot,ext->shift,A,B,PETSC_TRUE);
380:   ts->dm = dmsave;
381:   TSEIMEXRestoreVecs(ts,dm,NULL,&Ydot,NULL,NULL);
382:   return(0);
383: }

387: static PetscErrorCode DMCoarsenHook_TSEIMEX(DM fine,DM coarse,void *ctx)
388: {

391:   return(0);
392: }

396: static PetscErrorCode DMRestrictHook_TSEIMEX(DM fine,Mat restrct,Vec rscale,Mat inject,DM coarse,void *ctx)
397: {
398:   TS ts = (TS)ctx;
400:   Vec Z,Z_c;

403:   TSEIMEXGetVecs(ts,fine,&Z,NULL,NULL,NULL);
404:   TSEIMEXGetVecs(ts,coarse,&Z_c,NULL,NULL,NULL);
405:   MatRestrict(restrct,Z,Z_c);
406:   VecPointwiseMult(Z_c,rscale,Z_c);
407:   TSEIMEXRestoreVecs(ts,fine,&Z,NULL,NULL,NULL);
408:   TSEIMEXRestoreVecs(ts,coarse,&Z_c,NULL,NULL,NULL);
409:   return(0);
410: }


415: static PetscErrorCode TSSetUp_EIMEX(TS ts)
416: {
417:   TS_EIMEX       *ext = (TS_EIMEX*)ts->data;
419:   DM             dm;

422:   if (!ext->N){ /* ext->max_rows not set */
423:     TSEIMEXSetMaxRows(ts,TSEIMEXDefault);
424:   }
425:   if(-1 == ext->row_ind && -1 == ext->col_ind){
426:         TSEIMEXSetRowCol(ts,ext->max_rows,ext->max_rows);
427:   } else{/* ext->row_ind and col_ind already set */
428:     if (ext->ord_adapt){
429:       PetscInfo(ts,"Order adaptivity is enabled and TSEIMEXSetRowCol or -ts_eimex_row_col option will take no effect\n");
430:     }
431:   }

433:   if(ext->ord_adapt){
434:     ext->nstages = 2; /* Start with the 2-stage scheme */
435:     TSEIMEXSetRowCol(ts,ext->nstages,ext->nstages);
436:   } else{
437:     ext->nstages = ext->max_rows; /* by default nstages is the same as max_rows, this can be changed by setting order adaptivity */
438:   }

440:   VecDuplicateVecs(ts->vec_sol,(1+ext->nstages)*ext->nstages/2,&ext->T);/* full T table */
441:   VecDuplicate(ts->vec_sol,&ext->YdotI);
442:   VecDuplicate(ts->vec_sol,&ext->YdotRHS);
443:   VecDuplicate(ts->vec_sol,&ext->Ydot);
444:   VecDuplicate(ts->vec_sol,&ext->VecSolPrev);
445:   VecDuplicate(ts->vec_sol,&ext->Y);
446:   VecDuplicate(ts->vec_sol,&ext->Z);
447:   TSGetDM(ts,&dm);
448:   if (dm) {
449:     DMCoarsenHookAdd(dm,DMCoarsenHook_TSEIMEX,DMRestrictHook_TSEIMEX,ts);
450:   }
451:   return(0);
452: }

456: static PetscErrorCode TSSetFromOptions_EIMEX(PetscOptionItems *PetscOptionsObject,TS ts)
457: {
458:   TS_EIMEX       *ext = (TS_EIMEX*)ts->data;
460:   PetscInt       tindex[2];
461:   PetscInt       np = 2, nrows=TSEIMEXDefault;

464:   tindex[0] = TSEIMEXDefault;
465:   tindex[1] = TSEIMEXDefault;
466:   PetscOptionsHead(PetscOptionsObject,"EIMEX ODE solver options");
467:   {
468:     PetscBool flg;
469:     PetscOptionsInt("-ts_eimex_max_rows","Define the maximum number of rows used","TSEIMEXSetMaxRows",nrows,&nrows,&flg); /* default value 3 */
470:     if(flg){
471:       TSEIMEXSetMaxRows(ts,nrows);
472:     }
473:     PetscOptionsIntArray("-ts_eimex_row_col","Return the specific term in the T table","TSEIMEXSetRowCol",tindex,&np,&flg);
474:     if(flg){
475:       TSEIMEXSetRowCol(ts,tindex[0],tindex[1]);
476:     }
477:     PetscOptionsBool("-ts_eimex_order_adapt","Solve the problem with adaptive order","TSEIMEXSetOrdAdapt",ext->ord_adapt,&ext->ord_adapt,NULL);
478:   }
479:   PetscOptionsTail();
480:   return(0);
481: }

485: static PetscErrorCode TSView_EIMEX(TS ts,PetscViewer viewer)
486: {
487:   /*  TS_EIMEX         *ext = (TS_EIMEX*)ts->data; */
488:   PetscBool        iascii;
489:   PetscErrorCode   ierr;

492:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
493:   if (iascii) {
494:     PetscViewerASCIIPrintf(viewer,"  EIMEX\n");
495:   }
496:   SNESView(ts->snes,viewer);
497:   return(0);
498: }


503: /*@C
504:   TSEIMEXSetMaxRows - Set the maximum number of rows for EIMEX schemes

506:   Logically collective

508:   Input Parameter:
509: +  ts - timestepping context
510: -  nrows - maximum number of rows

512:   Level: intermediate

514: .seealso: TSEIMEXSetRowCol(), TSEIMEXSetOrdAdapt(), TSEIMEX
515: @*/
516: PetscErrorCode TSEIMEXSetMaxRows(TS ts, PetscInt nrows)
517: {
521:   PetscTryMethod(ts,"TSEIMEXSetMaxRows_C",(TS,PetscInt),(ts,nrows));
522:   return(0);
523: }


528: /*@C
529:   TSEIMEXSetRowCol - Set the type index in the T table for the return value

531:   Logically collective

533:   Input Parameter:
534: +  ts - timestepping context
535: -  tindex - index in the T table

537:   Level: intermediate

539: .seealso: TSEIMEXSetMaxRows(), TSEIMEXSetOrdAdapt(), TSEIMEX
540: @*/
541: PetscErrorCode TSEIMEXSetRowCol(TS ts, PetscInt row, PetscInt col)
542: {
546:   PetscTryMethod(ts,"TSEIMEXSetRowCol_C",(TS,PetscInt, PetscInt),(ts,row,col));
547:   return(0);
548: }


553: /*@C
554:   TSEIMEXSetOrdAdapt - Set the order adaptativity

556:   Logically collective

558:   Input Parameter:
559: +  ts - timestepping context
560: -  tindex - index in the T table

562:   Level: intermediate

564: .seealso: TSEIMEXSetRowCol(), TSEIMEXSetOrdAdapt(), TSEIMEX
565: @*/
566: PetscErrorCode TSEIMEXSetOrdAdapt(TS ts, PetscBool flg)
567: {
571:   PetscTryMethod(ts,"TSEIMEXSetOrdAdapt_C",(TS,PetscBool),(ts,flg));
572:   return(0);
573: }


578: static PetscErrorCode TSEIMEXSetMaxRows_EIMEX(TS ts,PetscInt nrows)
579: {
580:   TS_EIMEX *ext = (TS_EIMEX*)ts->data;
582:   PetscInt       i;

585:   if (nrows < 0 || nrows > 100) SETERRQ1(((PetscObject)ts)->comm,PETSC_ERR_ARG_OUTOFRANGE,"Max number of rows (current value %D) should be an integer number between 1 and 100\n",nrows);
586:   PetscFree(ext->N);
587:   ext->max_rows = nrows;
588:   PetscMalloc1(nrows,&ext->N);
589:   for(i=0;i<nrows;i++) ext->N[i]=i+1;
590:   return(0);
591: }

595: static PetscErrorCode TSEIMEXSetRowCol_EIMEX(TS ts,PetscInt row,PetscInt col)
596: {
597:   TS_EIMEX *ext = (TS_EIMEX*)ts->data;

600:   if (row < 1 || col < 1) SETERRQ2(((PetscObject)ts)->comm,PETSC_ERR_ARG_OUTOFRANGE,"The row or column index (current value %d,%d) should not be less than 1 \n",row,col);
601:   if (row > ext->max_rows || col > ext->max_rows) SETERRQ3(((PetscObject)ts)->comm,PETSC_ERR_ARG_OUTOFRANGE,"The row or column index (current value %d,%d) exceeds the maximum number of rows %d\n",row,col,ext->max_rows);
602:   if (col > row) SETERRQ2(((PetscObject)ts)->comm,PETSC_ERR_ARG_OUTOFRANGE,"The column index (%d) exceeds the row index (%d)\n",col,row);

604:   ext->row_ind = row - 1;
605:   ext->col_ind = col - 1; /* Array index in C starts from 0 */
606:   return(0);
607: }

611: static PetscErrorCode TSEIMEXSetOrdAdapt_EIMEX(TS ts,PetscBool flg)
612: {
613:   TS_EIMEX *ext = (TS_EIMEX*)ts->data;
615:   ext->ord_adapt = flg;
616:   return(0);
617: }

619: /* ------------------------------------------------------------ */
620: /*MC
621:       TSEIMEX - ODE solver using extrapolated IMEX schemes
622:   These methods are intended for problems with well-separated time scales, especially when a slow scale is strongly nonlinear such that it is expensive to solve with a fully implicit method. The user should provide the stiff part of the equation using TSSetIFunction() and the non-stiff part with TSSetRHSFunction().

624:    Notes:
625:   The default is a 3-stage scheme, it can be changed with TSEIMEXSetMaxRows() or -ts_eimex_max_rows

627:   This method currently only works with ODE, for which the stiff part G(t,X,Xdot) has the form Xdot + Ghat(t,X).

629:   Level: beginner

631: .seealso:  TSCreate(), TS
632: M*/
635: PETSC_EXTERN PetscErrorCode TSCreate_EIMEX(TS ts)
636: {
637:   TS_EIMEX       *ext;


642:   ts->ops->reset          = TSReset_EIMEX;
643:   ts->ops->destroy        = TSDestroy_EIMEX;
644:   ts->ops->view           = TSView_EIMEX;
645:   ts->ops->setup          = TSSetUp_EIMEX;
646:   ts->ops->step           = TSStep_EIMEX;
647:   ts->ops->interpolate    = TSInterpolate_EIMEX;
648:   ts->ops->evaluatestep   = TSEvaluateStep_EIMEX;
649:   ts->ops->setfromoptions = TSSetFromOptions_EIMEX;
650:   ts->ops->snesfunction   = SNESTSFormFunction_EIMEX;
651:   ts->ops->snesjacobian   = SNESTSFormJacobian_EIMEX;

653:   PetscNewLog(ts,&ext);
654:   ts->data = (void*)ext;

656:   ext->ord_adapt = PETSC_FALSE; /* By default, no order adapativity */
657:   ext->row_ind   = -1;
658:   ext->col_ind   = -1;
659:   ext->max_rows  = TSEIMEXDefault;
660:   ext->nstages   = TSEIMEXDefault;

662:   PetscObjectComposeFunction((PetscObject)ts,"TSEIMEXSetMaxRows_C", TSEIMEXSetMaxRows_EIMEX);
663:   PetscObjectComposeFunction((PetscObject)ts,"TSEIMEXSetRowCol_C",  TSEIMEXSetRowCol_EIMEX);
664:   PetscObjectComposeFunction((PetscObject)ts,"TSEIMEXSetOrdAdapt_C",TSEIMEXSetOrdAdapt_EIMEX);
665:   return(0);
666: }