Actual source code: eimex.c
1: #include <petsc/private/tsimpl.h>
2: #include <petscdm.h>
4: static const PetscInt TSEIMEXDefault = 3;
6: typedef struct {
7: PetscInt row_ind; /* Return the term T[row_ind][col_ind] */
8: PetscInt col_ind; /* Return the term T[row_ind][col_ind] */
9: PetscInt nstages; /* Numbers of stages in current scheme */
10: PetscInt max_rows; /* Maximum number of rows */
11: PetscInt *N; /* Harmonic sequence N[max_rows] */
12: Vec Y; /* States computed during the step, used to complete the step */
13: Vec Z; /* For shift*(Y-Z) */
14: Vec *T; /* Working table, size determined by nstages */
15: Vec YdotRHS; /* g(x) Work vector holding YdotRHS during residual evaluation */
16: Vec YdotI; /* xdot-f(x) Work vector holding YdotI = F(t,x,xdot) when xdot =0 */
17: Vec Ydot; /* f(x)+g(x) Work vector */
18: Vec VecSolPrev; /* Work vector holding the solution from the previous step (used for interpolation) */
19: PetscReal shift;
20: PetscReal ctime;
21: PetscBool recompute_jacobian; /* Recompute the Jacobian at each stage, default is to freeze the Jacobian at the start of each step */
22: PetscBool ord_adapt; /* order adapativity */
23: TSStepStatus status;
24: } TS_EIMEX;
26: /* This function is pure */
27: static PetscInt Map(PetscInt i, PetscInt j, PetscInt s)
28: {
29: return (2 * s - j + 1) * j / 2 + i - j;
30: }
32: static PetscErrorCode TSEvaluateStep_EIMEX(TS ts, PetscInt order, Vec X, PetscBool *done)
33: {
34: TS_EIMEX *ext = (TS_EIMEX *)ts->data;
35: const PetscInt ns = ext->nstages;
37: PetscFunctionBegin;
38: PetscCall(VecCopy(ext->T[Map(ext->row_ind, ext->col_ind, ns)], X));
39: PetscFunctionReturn(PETSC_SUCCESS);
40: }
42: static PetscErrorCode TSStage_EIMEX(TS ts, PetscInt istage)
43: {
44: TS_EIMEX *ext = (TS_EIMEX *)ts->data;
45: PetscReal h;
46: Vec Y = ext->Y, Z = ext->Z;
47: SNES snes;
48: TSAdapt adapt;
49: PetscInt i, its, lits;
50: PetscBool accept;
52: PetscFunctionBegin;
53: PetscCall(TSGetSNES(ts, &snes));
54: h = ts->time_step / ext->N[istage]; /* step size for the istage-th stage */
55: ext->shift = 1. / h;
56: PetscCall(SNESSetLagJacobian(snes, -2)); /* Recompute the Jacobian on this solve, but not again */
57: PetscCall(VecCopy(ext->VecSolPrev, Y)); /* Take the previous solution as initial step */
59: for (i = 0; i < ext->N[istage]; i++) {
60: ext->ctime = ts->ptime + h * i;
61: PetscCall(VecCopy(Y, Z)); /* Save the solution of the previous substep */
62: PetscCall(SNESSolve(snes, NULL, Y));
63: PetscCall(SNESGetIterationNumber(snes, &its));
64: PetscCall(SNESGetLinearSolveIterations(snes, &lits));
65: ts->snes_its += its;
66: ts->ksp_its += lits;
67: PetscCall(TSGetAdapt(ts, &adapt));
68: PetscCall(TSAdaptCheckStage(adapt, ts, ext->ctime, Y, &accept));
69: }
70: PetscFunctionReturn(PETSC_SUCCESS);
71: }
73: static PetscErrorCode TSStep_EIMEX(TS ts)
74: {
75: TS_EIMEX *ext = (TS_EIMEX *)ts->data;
76: const PetscInt ns = ext->nstages;
77: Vec *T = ext->T, Y = ext->Y;
78: SNES snes;
79: PetscInt i, j;
80: PetscBool accept = PETSC_FALSE;
81: PetscReal alpha, local_error, local_error_a, local_error_r;
83: PetscFunctionBegin;
84: PetscCall(TSGetSNES(ts, &snes));
85: PetscCall(SNESSetType(snes, "ksponly"));
86: ext->status = TS_STEP_INCOMPLETE;
88: PetscCall(VecCopy(ts->vec_sol, ext->VecSolPrev));
90: /* Apply n_j steps of the base method to obtain solutions of T(j,1),1<=j<=s */
91: for (j = 0; j < ns; j++) {
92: PetscCall(TSStage_EIMEX(ts, j));
93: PetscCall(VecCopy(Y, T[j]));
94: }
96: for (i = 1; i < ns; i++) {
97: for (j = i; j < ns; j++) {
98: alpha = -(PetscReal)ext->N[j] / ext->N[j - i];
99: PetscCall(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] */
100: alpha = 1.0 / (1.0 + alpha);
101: PetscCall(VecScale(T[Map(j, i, ns)], alpha));
102: }
103: }
105: PetscCall(TSEvaluateStep(ts, ns, ts->vec_sol, NULL)); /*update ts solution */
107: if (ext->ord_adapt && ext->nstages < ext->max_rows) {
108: accept = PETSC_FALSE;
109: while (!accept && ext->nstages < ext->max_rows) {
110: PetscCall(TSErrorWeightedNorm(ts, ts->vec_sol, T[Map(ext->nstages - 1, ext->nstages - 2, ext->nstages)], ts->adapt->wnormtype, &local_error, &local_error_a, &local_error_r));
111: accept = (local_error < 1.0) ? PETSC_TRUE : PETSC_FALSE;
113: if (!accept) { /* add one more stage*/
114: PetscCall(TSStage_EIMEX(ts, ext->nstages));
115: ext->nstages++;
116: ext->row_ind++;
117: ext->col_ind++;
118: /*T table need to be recycled*/
119: PetscCall(VecDuplicateVecs(ts->vec_sol, (1 + ext->nstages) * ext->nstages / 2, &ext->T));
120: for (i = 0; i < ext->nstages - 1; i++) {
121: for (j = 0; j <= i; j++) PetscCall(VecCopy(T[Map(i, j, ext->nstages - 1)], ext->T[Map(i, j, ext->nstages)]));
122: }
123: PetscCall(VecDestroyVecs(ext->nstages * (ext->nstages - 1) / 2, &T));
124: T = ext->T; /*reset the pointer*/
125: /*recycling finished, store the new solution*/
126: PetscCall(VecCopy(Y, T[ext->nstages - 1]));
127: /*extrapolation for the newly added stage*/
128: for (i = 1; i < ext->nstages; i++) {
129: alpha = -(PetscReal)ext->N[ext->nstages - 1] / ext->N[ext->nstages - 1 - i];
130: PetscCall(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]*/
131: alpha = 1.0 / (1.0 + alpha);
132: PetscCall(VecScale(T[Map(ext->nstages - 1, i, ext->nstages)], alpha));
133: }
134: /*update ts solution */
135: PetscCall(TSEvaluateStep(ts, ext->nstages, ts->vec_sol, NULL));
136: } /*end if !accept*/
137: } /*end while*/
139: if (ext->nstages == ext->max_rows) PetscCall(PetscInfo(ts, "Max number of rows has been used\n"));
140: } /*end if ext->ord_adapt*/
141: ts->ptime += ts->time_step;
142: ext->status = TS_STEP_COMPLETE;
144: if (ext->status != TS_STEP_COMPLETE && !ts->reason) ts->reason = TS_DIVERGED_STEP_REJECTED;
145: PetscFunctionReturn(PETSC_SUCCESS);
146: }
148: /* cubic Hermit spline */
149: static PetscErrorCode TSInterpolate_EIMEX(TS ts, PetscReal itime, Vec X)
150: {
151: TS_EIMEX *ext = (TS_EIMEX *)ts->data;
152: PetscReal t, a, b;
153: Vec Y0 = ext->VecSolPrev, Y1 = ext->Y, Ydot = ext->Ydot, YdotI = ext->YdotI;
154: const PetscReal h = ts->ptime - ts->ptime_prev;
156: PetscFunctionBegin;
157: t = (itime - ts->ptime + h) / h;
158: /* YdotI = -f(x)-g(x) */
160: PetscCall(VecZeroEntries(Ydot));
161: PetscCall(TSComputeIFunction(ts, ts->ptime - h, Y0, Ydot, YdotI, PETSC_FALSE));
163: a = 2.0 * t * t * t - 3.0 * t * t + 1.0;
164: b = -(t * t * t - 2.0 * t * t + t) * h;
165: PetscCall(VecAXPBYPCZ(X, a, b, 0.0, Y0, YdotI));
167: PetscCall(TSComputeIFunction(ts, ts->ptime, Y1, Ydot, YdotI, PETSC_FALSE));
168: a = -2.0 * t * t * t + 3.0 * t * t;
169: b = -(t * t * t - t * t) * h;
170: PetscCall(VecAXPBYPCZ(X, a, b, 1.0, Y1, YdotI));
171: PetscFunctionReturn(PETSC_SUCCESS);
172: }
174: static PetscErrorCode TSReset_EIMEX(TS ts)
175: {
176: TS_EIMEX *ext = (TS_EIMEX *)ts->data;
177: PetscInt ns;
179: PetscFunctionBegin;
180: ns = ext->nstages;
181: PetscCall(VecDestroyVecs((1 + ns) * ns / 2, &ext->T));
182: PetscCall(VecDestroy(&ext->Y));
183: PetscCall(VecDestroy(&ext->Z));
184: PetscCall(VecDestroy(&ext->YdotRHS));
185: PetscCall(VecDestroy(&ext->YdotI));
186: PetscCall(VecDestroy(&ext->Ydot));
187: PetscCall(VecDestroy(&ext->VecSolPrev));
188: PetscCall(PetscFree(ext->N));
189: PetscFunctionReturn(PETSC_SUCCESS);
190: }
192: static PetscErrorCode TSDestroy_EIMEX(TS ts)
193: {
194: PetscFunctionBegin;
195: PetscCall(TSReset_EIMEX(ts));
196: PetscCall(PetscFree(ts->data));
197: PetscCall(PetscObjectComposeFunction((PetscObject)ts, "TSEIMEXSetMaxRows_C", NULL));
198: PetscCall(PetscObjectComposeFunction((PetscObject)ts, "TSEIMEXSetRowCol_C", NULL));
199: PetscCall(PetscObjectComposeFunction((PetscObject)ts, "TSEIMEXSetOrdAdapt_C", NULL));
200: PetscFunctionReturn(PETSC_SUCCESS);
201: }
203: static PetscErrorCode TSEIMEXGetVecs(TS ts, DM dm, Vec *Z, Vec *Ydot, Vec *YdotI, Vec *YdotRHS)
204: {
205: TS_EIMEX *ext = (TS_EIMEX *)ts->data;
207: PetscFunctionBegin;
208: if (Z) {
209: if (dm && dm != ts->dm) {
210: PetscCall(DMGetNamedGlobalVector(dm, "TSEIMEX_Z", Z));
211: } else *Z = ext->Z;
212: }
213: if (Ydot) {
214: if (dm && dm != ts->dm) {
215: PetscCall(DMGetNamedGlobalVector(dm, "TSEIMEX_Ydot", Ydot));
216: } else *Ydot = ext->Ydot;
217: }
218: if (YdotI) {
219: if (dm && dm != ts->dm) {
220: PetscCall(DMGetNamedGlobalVector(dm, "TSEIMEX_YdotI", YdotI));
221: } else *YdotI = ext->YdotI;
222: }
223: if (YdotRHS) {
224: if (dm && dm != ts->dm) {
225: PetscCall(DMGetNamedGlobalVector(dm, "TSEIMEX_YdotRHS", YdotRHS));
226: } else *YdotRHS = ext->YdotRHS;
227: }
228: PetscFunctionReturn(PETSC_SUCCESS);
229: }
231: static PetscErrorCode TSEIMEXRestoreVecs(TS ts, DM dm, Vec *Z, Vec *Ydot, Vec *YdotI, Vec *YdotRHS)
232: {
233: PetscFunctionBegin;
234: if (Z) {
235: if (dm && dm != ts->dm) PetscCall(DMRestoreNamedGlobalVector(dm, "TSEIMEX_Z", Z));
236: }
237: if (Ydot) {
238: if (dm && dm != ts->dm) PetscCall(DMRestoreNamedGlobalVector(dm, "TSEIMEX_Ydot", Ydot));
239: }
240: if (YdotI) {
241: if (dm && dm != ts->dm) PetscCall(DMRestoreNamedGlobalVector(dm, "TSEIMEX_YdotI", YdotI));
242: }
243: if (YdotRHS) {
244: if (dm && dm != ts->dm) PetscCall(DMRestoreNamedGlobalVector(dm, "TSEIMEX_YdotRHS", YdotRHS));
245: }
246: PetscFunctionReturn(PETSC_SUCCESS);
247: }
249: /*
250: This defines the nonlinear equation that is to be solved with SNES
251: Fn[t0+Theta*dt, U, (U-U0)*shift] = 0
252: In the case of Backward Euler, Fn = (U-U0)/h-g(t1,U))
253: Since FormIFunction calculates G = ydot - g(t,y), ydot will be set to (U-U0)/h
254: */
255: static PetscErrorCode SNESTSFormFunction_EIMEX(SNES snes, Vec X, Vec G, TS ts)
256: {
257: TS_EIMEX *ext = (TS_EIMEX *)ts->data;
258: Vec Ydot, Z;
259: DM dm, dmsave;
261: PetscFunctionBegin;
262: PetscCall(VecZeroEntries(G));
264: PetscCall(SNESGetDM(snes, &dm));
265: PetscCall(TSEIMEXGetVecs(ts, dm, &Z, &Ydot, NULL, NULL));
266: PetscCall(VecZeroEntries(Ydot));
267: dmsave = ts->dm;
268: ts->dm = dm;
269: PetscCall(TSComputeIFunction(ts, ext->ctime, X, Ydot, G, PETSC_FALSE));
270: /* PETSC_FALSE indicates non-imex, adding explicit RHS to the implicit I function. */
271: PetscCall(VecCopy(G, Ydot));
272: ts->dm = dmsave;
273: PetscCall(TSEIMEXRestoreVecs(ts, dm, &Z, &Ydot, NULL, NULL));
274: PetscFunctionReturn(PETSC_SUCCESS);
275: }
277: /*
278: This defined the Jacobian matrix for SNES. Jn = (I/h-g'(t,y))
279: */
280: static PetscErrorCode SNESTSFormJacobian_EIMEX(SNES snes, Vec X, Mat A, Mat B, TS ts)
281: {
282: TS_EIMEX *ext = (TS_EIMEX *)ts->data;
283: Vec Ydot;
284: DM dm, dmsave;
286: PetscFunctionBegin;
287: PetscCall(SNESGetDM(snes, &dm));
288: PetscCall(TSEIMEXGetVecs(ts, dm, NULL, &Ydot, NULL, NULL));
289: /* PetscCall(VecZeroEntries(Ydot)); */
290: /* ext->Ydot have already been computed in SNESTSFormFunction_EIMEX (SNES guarantees this) */
291: dmsave = ts->dm;
292: ts->dm = dm;
293: PetscCall(TSComputeIJacobian(ts, ts->ptime, X, Ydot, ext->shift, A, B, PETSC_TRUE));
294: ts->dm = dmsave;
295: PetscCall(TSEIMEXRestoreVecs(ts, dm, NULL, &Ydot, NULL, NULL));
296: PetscFunctionReturn(PETSC_SUCCESS);
297: }
299: static PetscErrorCode DMCoarsenHook_TSEIMEX(DM fine, DM coarse, void *ctx)
300: {
301: PetscFunctionBegin;
302: PetscFunctionReturn(PETSC_SUCCESS);
303: }
305: static PetscErrorCode DMRestrictHook_TSEIMEX(DM fine, Mat restrct, Vec rscale, Mat inject, DM coarse, void *ctx)
306: {
307: TS ts = (TS)ctx;
308: Vec Z, Z_c;
310: PetscFunctionBegin;
311: PetscCall(TSEIMEXGetVecs(ts, fine, &Z, NULL, NULL, NULL));
312: PetscCall(TSEIMEXGetVecs(ts, coarse, &Z_c, NULL, NULL, NULL));
313: PetscCall(MatRestrict(restrct, Z, Z_c));
314: PetscCall(VecPointwiseMult(Z_c, rscale, Z_c));
315: PetscCall(TSEIMEXRestoreVecs(ts, fine, &Z, NULL, NULL, NULL));
316: PetscCall(TSEIMEXRestoreVecs(ts, coarse, &Z_c, NULL, NULL, NULL));
317: PetscFunctionReturn(PETSC_SUCCESS);
318: }
320: static PetscErrorCode TSSetUp_EIMEX(TS ts)
321: {
322: TS_EIMEX *ext = (TS_EIMEX *)ts->data;
323: DM dm;
325: PetscFunctionBegin;
326: if (!ext->N) { /* ext->max_rows not set */
327: PetscCall(TSEIMEXSetMaxRows(ts, TSEIMEXDefault));
328: }
329: if (-1 == ext->row_ind && -1 == ext->col_ind) {
330: PetscCall(TSEIMEXSetRowCol(ts, ext->max_rows, ext->max_rows));
331: } else { /* ext->row_ind and col_ind already set */
332: if (ext->ord_adapt) PetscCall(PetscInfo(ts, "Order adaptivity is enabled and TSEIMEXSetRowCol or -ts_eimex_row_col option will take no effect\n"));
333: }
335: if (ext->ord_adapt) {
336: ext->nstages = 2; /* Start with the 2-stage scheme */
337: PetscCall(TSEIMEXSetRowCol(ts, ext->nstages, ext->nstages));
338: } else {
339: ext->nstages = ext->max_rows; /* by default nstages is the same as max_rows, this can be changed by setting order adaptivity */
340: }
342: PetscCall(TSGetAdapt(ts, &ts->adapt));
344: PetscCall(VecDuplicateVecs(ts->vec_sol, (1 + ext->nstages) * ext->nstages / 2, &ext->T)); /* full T table */
345: PetscCall(VecDuplicate(ts->vec_sol, &ext->YdotI));
346: PetscCall(VecDuplicate(ts->vec_sol, &ext->YdotRHS));
347: PetscCall(VecDuplicate(ts->vec_sol, &ext->Ydot));
348: PetscCall(VecDuplicate(ts->vec_sol, &ext->VecSolPrev));
349: PetscCall(VecDuplicate(ts->vec_sol, &ext->Y));
350: PetscCall(VecDuplicate(ts->vec_sol, &ext->Z));
351: PetscCall(TSGetDM(ts, &dm));
352: if (dm) PetscCall(DMCoarsenHookAdd(dm, DMCoarsenHook_TSEIMEX, DMRestrictHook_TSEIMEX, ts));
353: PetscFunctionReturn(PETSC_SUCCESS);
354: }
356: static PetscErrorCode TSSetFromOptions_EIMEX(TS ts, PetscOptionItems *PetscOptionsObject)
357: {
358: TS_EIMEX *ext = (TS_EIMEX *)ts->data;
359: PetscInt tindex[2];
360: PetscInt np = 2, nrows = TSEIMEXDefault;
362: PetscFunctionBegin;
363: tindex[0] = TSEIMEXDefault;
364: tindex[1] = TSEIMEXDefault;
365: PetscOptionsHeadBegin(PetscOptionsObject, "EIMEX ODE solver options");
366: {
367: PetscBool flg;
368: PetscCall(PetscOptionsInt("-ts_eimex_max_rows", "Define the maximum number of rows used", "TSEIMEXSetMaxRows", nrows, &nrows, &flg)); /* default value 3 */
369: if (flg) PetscCall(TSEIMEXSetMaxRows(ts, nrows));
370: PetscCall(PetscOptionsIntArray("-ts_eimex_row_col", "Return the specific term in the T table", "TSEIMEXSetRowCol", tindex, &np, &flg));
371: if (flg) PetscCall(TSEIMEXSetRowCol(ts, tindex[0], tindex[1]));
372: PetscCall(PetscOptionsBool("-ts_eimex_order_adapt", "Solve the problem with adaptive order", "TSEIMEXSetOrdAdapt", ext->ord_adapt, &ext->ord_adapt, NULL));
373: }
374: PetscOptionsHeadEnd();
375: PetscFunctionReturn(PETSC_SUCCESS);
376: }
378: static PetscErrorCode TSView_EIMEX(TS ts, PetscViewer viewer)
379: {
380: PetscFunctionBegin;
381: PetscFunctionReturn(PETSC_SUCCESS);
382: }
384: /*@
385: TSEIMEXSetMaxRows - Set the maximum number of rows for `TSEIMEX` schemes
387: Logically Collective
389: Input Parameters:
390: + ts - timestepping context
391: - nrows - maximum number of rows
393: Level: intermediate
395: .seealso: [](ch_ts), `TSEIMEXSetRowCol()`, `TSEIMEXSetOrdAdapt()`, `TSEIMEX`
396: @*/
397: PetscErrorCode TSEIMEXSetMaxRows(TS ts, PetscInt nrows)
398: {
399: PetscFunctionBegin;
401: PetscTryMethod(ts, "TSEIMEXSetMaxRows_C", (TS, PetscInt), (ts, nrows));
402: PetscFunctionReturn(PETSC_SUCCESS);
403: }
405: /*@
406: TSEIMEXSetRowCol - Set the number of rows and the number of columns for the tableau that represents the T solution in the `TSEIMEX` scheme
408: Logically Collective
410: Input Parameters:
411: + ts - timestepping context
412: . row - the row
413: - col - the column
415: Level: intermediate
417: .seealso: [](ch_ts), `TSEIMEXSetMaxRows()`, `TSEIMEXSetOrdAdapt()`, `TSEIMEX`
418: @*/
419: PetscErrorCode TSEIMEXSetRowCol(TS ts, PetscInt row, PetscInt col)
420: {
421: PetscFunctionBegin;
423: PetscTryMethod(ts, "TSEIMEXSetRowCol_C", (TS, PetscInt, PetscInt), (ts, row, col));
424: PetscFunctionReturn(PETSC_SUCCESS);
425: }
427: /*@
428: TSEIMEXSetOrdAdapt - Set the order adaptativity for the `TSEIMEX` schemes
430: Logically Collective
432: Input Parameters:
433: + ts - timestepping context
434: - flg - index in the T table
436: Level: intermediate
438: .seealso: [](ch_ts), `TSEIMEXSetRowCol()`, `TSEIMEX`
439: @*/
440: PetscErrorCode TSEIMEXSetOrdAdapt(TS ts, PetscBool flg)
441: {
442: PetscFunctionBegin;
444: PetscTryMethod(ts, "TSEIMEXSetOrdAdapt_C", (TS, PetscBool), (ts, flg));
445: PetscFunctionReturn(PETSC_SUCCESS);
446: }
448: static PetscErrorCode TSEIMEXSetMaxRows_EIMEX(TS ts, PetscInt nrows)
449: {
450: TS_EIMEX *ext = (TS_EIMEX *)ts->data;
451: PetscInt i;
453: PetscFunctionBegin;
454: PetscCheck(nrows >= 0 && nrows <= 100, ((PetscObject)ts)->comm, PETSC_ERR_ARG_OUTOFRANGE, "Max number of rows (current value %" PetscInt_FMT ") should be an integer number between 1 and 100", nrows);
455: PetscCall(PetscFree(ext->N));
456: ext->max_rows = nrows;
457: PetscCall(PetscMalloc1(nrows, &ext->N));
458: for (i = 0; i < nrows; i++) ext->N[i] = i + 1;
459: PetscFunctionReturn(PETSC_SUCCESS);
460: }
462: static PetscErrorCode TSEIMEXSetRowCol_EIMEX(TS ts, PetscInt row, PetscInt col)
463: {
464: TS_EIMEX *ext = (TS_EIMEX *)ts->data;
466: PetscFunctionBegin;
467: PetscCheck(row >= 1 && col >= 1, ((PetscObject)ts)->comm, PETSC_ERR_ARG_OUTOFRANGE, "The row or column index (current value %" PetscInt_FMT ",%" PetscInt_FMT ") should not be less than 1 ", row, col);
468: PetscCheck(row <= ext->max_rows && col <= ext->max_rows, ((PetscObject)ts)->comm, PETSC_ERR_ARG_OUTOFRANGE, "The row or column index (current value %" PetscInt_FMT ",%" PetscInt_FMT ") exceeds the maximum number of rows %" PetscInt_FMT, row, col,
469: ext->max_rows);
470: PetscCheck(col <= row, ((PetscObject)ts)->comm, PETSC_ERR_ARG_OUTOFRANGE, "The column index (%" PetscInt_FMT ") exceeds the row index (%" PetscInt_FMT ")", col, row);
472: ext->row_ind = row - 1;
473: ext->col_ind = col - 1; /* Array index in C starts from 0 */
474: PetscFunctionReturn(PETSC_SUCCESS);
475: }
477: static PetscErrorCode TSEIMEXSetOrdAdapt_EIMEX(TS ts, PetscBool flg)
478: {
479: TS_EIMEX *ext = (TS_EIMEX *)ts->data;
481: PetscFunctionBegin;
482: ext->ord_adapt = flg;
483: PetscFunctionReturn(PETSC_SUCCESS);
484: }
486: /*MC
487: TSEIMEX - Time stepping with Extrapolated W-IMEX methods {cite}`constantinescu_a2010a`.
489: These methods are intended for problems with well-separated time scales, especially when a slow scale is strongly nonlinear such that it
490: is expensive to solve with a fully implicit method. The user should provide the stiff part of the equation using `TSSetIFunction()` and the
491: non-stiff part with `TSSetRHSFunction()`.
493: Level: beginner
495: Notes:
496: The default is a 3-stage scheme, it can be changed with `TSEIMEXSetMaxRows()` or -ts_eimex_max_rows
498: This method currently only works with ODEs, for which the stiff part $ F(t,X,Xdot) $ has the form $ Xdot + Fhat(t,X)$.
500: The general system is written as
502: $$
503: F(t,X,Xdot) = G(t,X)
504: $$
506: where F represents the stiff part and G represents the non-stiff part. The user should provide the stiff part
507: of the equation using TSSetIFunction() and the non-stiff part with `TSSetRHSFunction()`.
508: This method is designed to be linearly implicit on G and can use an approximate and lagged Jacobian.
510: Another common form for the system is
512: $$
513: y'=f(x)+g(x)
514: $$
516: The relationship between F,G and f,g is
518: $$
519: F = y'-f(x), G = g(x)
520: $$
522: .seealso: [](ch_ts), `TSCreate()`, `TS`, `TSSetType()`, `TSEIMEXSetMaxRows()`, `TSEIMEXSetRowCol()`, `TSEIMEXSetOrdAdapt()`, `TSType`
523: M*/
524: PETSC_EXTERN PetscErrorCode TSCreate_EIMEX(TS ts)
525: {
526: TS_EIMEX *ext;
528: PetscFunctionBegin;
529: ts->ops->reset = TSReset_EIMEX;
530: ts->ops->destroy = TSDestroy_EIMEX;
531: ts->ops->view = TSView_EIMEX;
532: ts->ops->setup = TSSetUp_EIMEX;
533: ts->ops->step = TSStep_EIMEX;
534: ts->ops->interpolate = TSInterpolate_EIMEX;
535: ts->ops->evaluatestep = TSEvaluateStep_EIMEX;
536: ts->ops->setfromoptions = TSSetFromOptions_EIMEX;
537: ts->ops->snesfunction = SNESTSFormFunction_EIMEX;
538: ts->ops->snesjacobian = SNESTSFormJacobian_EIMEX;
539: ts->default_adapt_type = TSADAPTNONE;
541: ts->usessnes = PETSC_TRUE;
543: PetscCall(PetscNew(&ext));
544: ts->data = (void *)ext;
546: ext->ord_adapt = PETSC_FALSE; /* By default, no order adapativity */
547: ext->row_ind = -1;
548: ext->col_ind = -1;
549: ext->max_rows = TSEIMEXDefault;
550: ext->nstages = TSEIMEXDefault;
552: PetscCall(PetscObjectComposeFunction((PetscObject)ts, "TSEIMEXSetMaxRows_C", TSEIMEXSetMaxRows_EIMEX));
553: PetscCall(PetscObjectComposeFunction((PetscObject)ts, "TSEIMEXSetRowCol_C", TSEIMEXSetRowCol_EIMEX));
554: PetscCall(PetscObjectComposeFunction((PetscObject)ts, "TSEIMEXSetOrdAdapt_C", TSEIMEXSetOrdAdapt_EIMEX));
555: PetscFunctionReturn(PETSC_SUCCESS);
556: }