Actual source code: eimex.c
petsc-3.5.4 2015-05-23
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,&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: TSErrorNormWRMS(ts,T[Map(ext->nstages-1,ext->nstages-2,ext->nstages)],&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 */
192: ts->ptime += ts->time_step;
193: ts->steps++;
194: ext->status = TS_STEP_COMPLETE;
196: if (ext->status != TS_STEP_COMPLETE && !ts->reason) ts->reason = TS_DIVERGED_STEP_REJECTED;
197: return(0);
198: }
201: /* cubic Hermit spline */
204: static PetscErrorCode TSInterpolate_EIMEX(TS ts,PetscReal itime,Vec X)
205: {
206: TS_EIMEX *ext = (TS_EIMEX*)ts->data;
207: PetscReal t,a,b;
208: Vec Y0=ext->VecSolPrev,Y1=ext->Y,
209: Ydot=ext->Ydot,YdotI=ext->YdotI;
210: const PetscReal h = ts->time_step_prev;
213: t = (itime -ts->ptime + h)/h;
214: /* YdotI = -f(x)-g(x) */
216: VecZeroEntries(Ydot);
217: TSComputeIFunction(ts,ts->ptime-h,Y0,Ydot,YdotI,PETSC_FALSE);
219: a = 2.0*t*t*t - 3.0*t*t + 1.0;
220: b = -(t*t*t - 2.0*t*t + t)*h;
221: VecAXPBYPCZ(X,a,b,0.0,Y0,YdotI);
223: TSComputeIFunction(ts,ts->ptime,Y1,Ydot,YdotI,PETSC_FALSE);
224: a = -2.0*t*t*t+3.0*t*t;
225: b = -(t*t*t - t*t)*h;
226: VecAXPBYPCZ(X,a,b,1.0,Y1,YdotI);
228: return(0);
229: }
234: static PetscErrorCode TSReset_EIMEX(TS ts)
235: {
236: TS_EIMEX *ext = (TS_EIMEX*)ts->data;
237: PetscInt ns;
238: PetscErrorCode ierr;
241: ns = ext->nstages;
242: VecDestroyVecs((1+ns)*ns/2,&ext->T);
243: VecDestroy(&ext->Y);
244: VecDestroy(&ext->Z);
245: VecDestroy(&ext->YdotRHS);
246: VecDestroy(&ext->YdotI);
247: VecDestroy(&ext->Ydot);
248: VecDestroy(&ext->VecSolPrev);
249: PetscFree(ext->N);
250: return(0);
251: }
255: static PetscErrorCode TSDestroy_EIMEX(TS ts)
256: {
257: PetscErrorCode ierr;
260: TSReset_EIMEX(ts);
261: PetscFree(ts->data);
262: PetscObjectComposeFunction((PetscObject)ts,"TSEIMEXSetMaxRows_C",NULL);
263: PetscObjectComposeFunction((PetscObject)ts,"TSEIMEXSetRowCol_C",NULL);
264: PetscObjectComposeFunction((PetscObject)ts,"TSEIMEXSetOrdAdapt_C",NULL);
266: return(0);
267: }
272: static PetscErrorCode TSEIMEXGetVecs(TS ts,DM dm,Vec *Z,Vec *Ydot,Vec *YdotI, Vec *YdotRHS)
273: {
274: TS_EIMEX *ext = (TS_EIMEX*)ts->data;
278: if (Z) {
279: if (dm && dm != ts->dm) {
280: DMGetNamedGlobalVector(dm,"TSEIMEX_Z",Z);
281: } else *Z = ext->Z;
282: }
283: if (Ydot) {
284: if (dm && dm != ts->dm) {
285: DMGetNamedGlobalVector(dm,"TSEIMEX_Ydot",Ydot);
286: } else *Ydot = ext->Ydot;
287: }
288: if (YdotI) {
289: if (dm && dm != ts->dm) {
290: DMGetNamedGlobalVector(dm,"TSEIMEX_YdotI",YdotI);
291: } else *YdotI = ext->YdotI;
292: }
293: if (YdotRHS) {
294: if (dm && dm != ts->dm) {
295: DMGetNamedGlobalVector(dm,"TSEIMEX_YdotRHS",YdotRHS);
296: } else *YdotRHS = ext->YdotRHS;
297: }
298: return(0);
299: }
304: static PetscErrorCode TSEIMEXRestoreVecs(TS ts,DM dm,Vec *Z,Vec *Ydot,Vec *YdotI,Vec *YdotRHS)
305: {
309: if (Z) {
310: if (dm && dm != ts->dm) {
311: DMRestoreNamedGlobalVector(dm,"TSEIMEX_Z",Z);
312: }
313: }
314: if (Ydot) {
315: if (dm && dm != ts->dm) {
316: DMRestoreNamedGlobalVector(dm,"TSEIMEX_Ydot",Ydot);
317: }
318: }
319: if (YdotI) {
320: if (dm && dm != ts->dm) {
321: DMRestoreNamedGlobalVector(dm,"TSEIMEX_YdotI",YdotI);
322: }
323: }
324: if (YdotRHS) {
325: if (dm && dm != ts->dm) {
326: DMRestoreNamedGlobalVector(dm,"TSEIMEX_YdotRHS",YdotRHS);
327: }
328: }
329: return(0);
330: }
333: /*
334: This defines the nonlinear equation that is to be solved with SNES
335: Fn[t0+Theta*dt, U, (U-U0)*shift] = 0
336: In the case of Backward Euler, Fn = (U-U0)/h-g(t1,U))
337: Since FormIFunction calculates G = ydot - g(t,y), ydot will be set to (U-U0)/h
338: */
341: static PetscErrorCode SNESTSFormFunction_EIMEX(SNES snes,Vec X,Vec G,TS ts)
342: {
343: TS_EIMEX *ext = (TS_EIMEX*)ts->data;
344: PetscErrorCode ierr;
345: Vec Ydot,Z;
346: DM dm,dmsave;
349: VecZeroEntries(G);
351: SNESGetDM(snes,&dm);
352: TSEIMEXGetVecs(ts,dm,&Z,&Ydot,NULL,NULL);
353: VecZeroEntries(Ydot);
354: dmsave = ts->dm;
355: ts->dm = dm;
356: TSComputeIFunction(ts,ext->ctime,X,Ydot,G,PETSC_FALSE);
357: /* PETSC_FALSE indicates non-imex, adding explicit RHS to the implicit I function. */
358: VecCopy(G,Ydot);
359: ts->dm = dmsave;
360: TSEIMEXRestoreVecs(ts,dm,&Z,&Ydot,NULL,NULL);
362: return(0);
363: }
365: /*
366: This defined the Jacobian matrix for SNES. Jn = (I/h-g'(t,y))
367: */
370: static PetscErrorCode SNESTSFormJacobian_EIMEX(SNES snes,Vec X,Mat A,Mat B,TS ts)
371: {
372: TS_EIMEX *ext = (TS_EIMEX*)ts->data;
373: Vec Ydot;
374: PetscErrorCode ierr;
375: DM dm,dmsave;
377: SNESGetDM(snes,&dm);
378: TSEIMEXGetVecs(ts,dm,NULL,&Ydot,NULL,NULL);
379: /* VecZeroEntries(Ydot); */
380: /* ext->Ydot have already been computed in SNESTSFormFunction_EIMEX (SNES guarantees this) */
381: dmsave = ts->dm;
382: ts->dm = dm;
383: TSComputeIJacobian(ts,ts->ptime,X,Ydot,ext->shift,A,B,PETSC_TRUE);
384: ts->dm = dmsave;
385: TSEIMEXRestoreVecs(ts,dm,NULL,&Ydot,NULL,NULL);
386: return(0);
387: }
391: static PetscErrorCode DMCoarsenHook_TSEIMEX(DM fine,DM coarse,void *ctx)
392: {
395: return(0);
396: }
400: static PetscErrorCode DMRestrictHook_TSEIMEX(DM fine,Mat restrct,Vec rscale,Mat inject,DM coarse,void *ctx)
401: {
402: TS ts = (TS)ctx;
404: Vec Z,Z_c;
407: TSEIMEXGetVecs(ts,fine,&Z,NULL,NULL,NULL);
408: TSEIMEXGetVecs(ts,coarse,&Z_c,NULL,NULL,NULL);
409: MatRestrict(restrct,Z,Z_c);
410: VecPointwiseMult(Z_c,rscale,Z_c);
411: TSEIMEXRestoreVecs(ts,fine,&Z,NULL,NULL,NULL);
412: TSEIMEXRestoreVecs(ts,coarse,&Z_c,NULL,NULL,NULL);
413: return(0);
414: }
419: static PetscErrorCode TSSetUp_EIMEX(TS ts)
420: {
421: TS_EIMEX *ext = (TS_EIMEX*)ts->data;
423: DM dm;
426: if (!ext->N){ /* ext->max_rows not set */
427: TSEIMEXSetMaxRows(ts,TSEIMEXDefault);
428: }
429: if(-1 == ext->row_ind && -1 == ext->col_ind){
430: TSEIMEXSetRowCol(ts,ext->max_rows,ext->max_rows);
431: }else{/* ext->row_ind and col_ind already set */
432: if(ext->ord_adapt){
433: PetscInfo(ts,"Order adaptivity is enabled and TSEIMEXSetRowCol or -ts_eimex_row_col option will take no effect\n");
434: }
435: }
437: if(ext->ord_adapt){
438: ext->nstages = 2; /* Start with the 2-stage scheme */
439: TSEIMEXSetRowCol(ts,ext->nstages,ext->nstages);
440: }else{
441: ext->nstages = ext->max_rows; /* by default nstages is the same as max_rows, this can be changed by setting order adaptivity */
442: }
444: VecDuplicateVecs(ts->vec_sol,(1+ext->nstages)*ext->nstages/2,&ext->T);/* full T table */
445: VecDuplicate(ts->vec_sol,&ext->YdotI);
446: VecDuplicate(ts->vec_sol,&ext->YdotRHS);
447: VecDuplicate(ts->vec_sol,&ext->Ydot);
448: VecDuplicate(ts->vec_sol,&ext->VecSolPrev);
449: VecDuplicate(ts->vec_sol,&ext->Y);
450: VecDuplicate(ts->vec_sol,&ext->Z);
451: TSGetDM(ts,&dm);
452: if (dm) {
453: DMCoarsenHookAdd(dm,DMCoarsenHook_TSEIMEX,DMRestrictHook_TSEIMEX,ts);
454: }
455: return(0);
456: }
460: static PetscErrorCode TSSetFromOptions_EIMEX(TS ts)
461: {
462: TS_EIMEX *ext = (TS_EIMEX*)ts->data;
464: PetscInt tindex[2];
465: PetscInt np = 2, nrows=TSEIMEXDefault;
468: tindex[0] = TSEIMEXDefault;
469: tindex[1] = TSEIMEXDefault;
470: PetscOptionsHead("EIMEX ODE solver options");
471: {
472: PetscBool flg;
473: flg = PETSC_FALSE;
474: PetscOptionsInt("-ts_eimex_max_rows","Define the maximum number of rows used","TSEIMEXSetMaxRows",nrows,&nrows,&flg); /* default value 3 */
475: if(flg){
476: TSEIMEXSetMaxRows(ts,nrows);
477: }
478: PetscOptionsIntArray("-ts_eimex_row_col","Return the specific term in the T table","TSEIMEXSetRowCol",tindex,&np,&flg);
479: if(flg){
480: TSEIMEXSetRowCol(ts,tindex[0],tindex[1]);
481: }
482: PetscOptionsBool("-ts_eimex_order_adapt","Solve the problem with adaptive order","TSEIMEXSetOrdAdapt",ext->ord_adapt,&ext->ord_adapt,NULL);
483: SNESSetFromOptions(ts->snes);
484: }
485: PetscOptionsTail();
486: return(0);
487: }
491: static PetscErrorCode TSView_EIMEX(TS ts,PetscViewer viewer)
492: {
493: /* TS_EIMEX *ext = (TS_EIMEX*)ts->data; */
494: PetscBool iascii;
495: PetscErrorCode ierr;
498: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
499: if (iascii) {
500: PetscViewerASCIIPrintf(viewer," EIMEX\n");
501: }
502: SNESView(ts->snes,viewer);
503: return(0);
504: }
509: /*@C
510: TSEIMEXSetMaxRows - Set the maximum number of rows for EIMEX schemes
512: Logically collective
514: Input Parameter:
515: + ts - timestepping context
516: - nrows - maximum number of rows
518: Level: intermediate
520: .seealso: TSEIMEXSetRowCol(), TSEIMEXSetOrdAdapt(), TSEIMEX
521: @*/
522: PetscErrorCode TSEIMEXSetMaxRows(TS ts, PetscInt nrows)
523: {
527: PetscTryMethod(ts,"TSEIMEXSetMaxRows_C",(TS,PetscInt),(ts,nrows));
528: return(0);
529: }
534: /*@C
535: TSEIMEXSetRowCol - Set the type index in the T table for the return value
537: Logically collective
539: Input Parameter:
540: + ts - timestepping context
541: - tindex - index in the T table
543: Level: intermediate
545: .seealso: TSEIMEXSetMaxRows(), TSEIMEXSetOrdAdapt(), TSEIMEX
546: @*/
547: PetscErrorCode TSEIMEXSetRowCol(TS ts, PetscInt row, PetscInt col)
548: {
552: PetscTryMethod(ts,"TSEIMEXSetRowCol_C",(TS,PetscInt, PetscInt),(ts,row,col));
553: return(0);
554: }
559: /*@C
560: TSEIMEXSetOrdAdapt - Set the order adaptativity
562: Logically collective
564: Input Parameter:
565: + ts - timestepping context
566: - tindex - index in the T table
568: Level: intermediate
570: .seealso: TSEIMEXSetRowCol(), TSEIMEXSetOrdAdapt(), TSEIMEX
571: @*/
572: PetscErrorCode TSEIMEXSetOrdAdapt(TS ts, PetscBool flg)
573: {
577: PetscTryMethod(ts,"TSEIMEXSetOrdAdapt_C",(TS,PetscBool),(ts,flg));
578: return(0);
579: }
584: static PetscErrorCode TSEIMEXSetMaxRows_EIMEX(TS ts,PetscInt nrows)
585: {
586: TS_EIMEX *ext = (TS_EIMEX*)ts->data;
588: PetscInt i;
591: 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);
592: PetscFree(ext->N);
593: ext->max_rows = nrows;
594: PetscMalloc1(nrows,&ext->N);
595: for(i=0;i<nrows;i++) ext->N[i]=i+1;
596: return(0);
597: }
601: static PetscErrorCode TSEIMEXSetRowCol_EIMEX(TS ts,PetscInt row,PetscInt col)
602: {
603: TS_EIMEX *ext = (TS_EIMEX*)ts->data;
606: 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);
607: 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);
608: if (col > row) SETERRQ2(((PetscObject)ts)->comm,PETSC_ERR_ARG_OUTOFRANGE,"The column index (%d) exceeds the row index (%d)\n",col,row);
610: ext->row_ind = row - 1;
611: ext->col_ind = col - 1; /* Array index in C starts from 0 */
612: return(0);
613: }
617: static PetscErrorCode TSEIMEXSetOrdAdapt_EIMEX(TS ts,PetscBool flg)
618: {
619: TS_EIMEX *ext = (TS_EIMEX*)ts->data;
621: ext->ord_adapt = flg;
622: return(0);
623: }
625: /* ------------------------------------------------------------ */
626: /*MC
627: TSEIMEX - ODE solver using extrapolated IMEX schemes
628: 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().
630: Notes:
631: The default is a 3-stage scheme, it can be changed with TSEIMEXSetMaxRows() or -ts_eimex_max_rows
633: This method currently only works with ODE, for which the stiff part G(t,X,Xdot) has the form Xdot + Ghat(t,X).
635: Level: beginner
637: .seealso: TSCreate(), TS
638: M*/
641: PETSC_EXTERN PetscErrorCode TSCreate_EIMEX(TS ts)
642: {
643: TS_EIMEX *ext;
648: ts->ops->reset = TSReset_EIMEX;
649: ts->ops->destroy = TSDestroy_EIMEX;
650: ts->ops->view = TSView_EIMEX;
651: ts->ops->setup = TSSetUp_EIMEX;
652: ts->ops->step = TSStep_EIMEX;
653: ts->ops->interpolate = TSInterpolate_EIMEX;
654: ts->ops->evaluatestep = TSEvaluateStep_EIMEX;
655: ts->ops->setfromoptions = TSSetFromOptions_EIMEX;
656: ts->ops->snesfunction = SNESTSFormFunction_EIMEX;
657: ts->ops->snesjacobian = SNESTSFormJacobian_EIMEX;
659: PetscNewLog(ts,&ext);
660: ts->data = (void*)ext;
662: ext->ord_adapt = PETSC_FALSE; /* By default, no order adapativity */
663: ext->row_ind = -1;
664: ext->col_ind = -1;
665: ext->max_rows = TSEIMEXDefault;
666: ext->nstages = TSEIMEXDefault;
668: PetscObjectComposeFunction((PetscObject)ts,"TSEIMEXSetMaxRows_C", TSEIMEXSetMaxRows_EIMEX);
669: PetscObjectComposeFunction((PetscObject)ts,"TSEIMEXSetRowCol_C", TSEIMEXSetRowCol_EIMEX);
670: PetscObjectComposeFunction((PetscObject)ts,"TSEIMEXSetOrdAdapt_C",TSEIMEXSetOrdAdapt_EIMEX);
671: return(0);
672: }