Actual source code: rosw.c
petsc-3.6.1 2015-08-06
1: /*
2: Code for timestepping with Rosenbrock W methods
4: Notes:
5: The general system is written as
7: F(t,U,Udot) = G(t,U)
9: where F represents the stiff part of the physics and G represents the non-stiff part.
10: This method is designed to be linearly implicit on F and can use an approximate and lagged Jacobian.
12: */
13: #include <petsc/private/tsimpl.h> /*I "petscts.h" I*/
14: #include <petscdm.h>
16: #include <petsc/private/kernels/blockinvert.h>
18: static TSRosWType TSRosWDefault = TSROSWRA34PW2;
19: static PetscBool TSRosWRegisterAllCalled;
20: static PetscBool TSRosWPackageInitialized;
22: typedef struct _RosWTableau *RosWTableau;
23: struct _RosWTableau {
24: char *name;
25: PetscInt order; /* Classical approximation order of the method */
26: PetscInt s; /* Number of stages */
27: PetscInt pinterp; /* Interpolation order */
28: PetscReal *A; /* Propagation table, strictly lower triangular */
29: PetscReal *Gamma; /* Stage table, lower triangular with nonzero diagonal */
30: PetscBool *GammaZeroDiag; /* Diagonal entries that are zero in stage table Gamma, vector indicating explicit statages */
31: PetscReal *GammaExplicitCorr; /* Coefficients for correction terms needed for explicit stages in transformed variables*/
32: PetscReal *b; /* Step completion table */
33: PetscReal *bembed; /* Step completion table for embedded method of order one less */
34: PetscReal *ASum; /* Row sum of A */
35: PetscReal *GammaSum; /* Row sum of Gamma, only needed for non-autonomous systems */
36: PetscReal *At; /* Propagation table in transformed variables */
37: PetscReal *bt; /* Step completion table in transformed variables */
38: PetscReal *bembedt; /* Step completion table of order one less in transformed variables */
39: PetscReal *GammaInv; /* Inverse of Gamma, used for transformed variables */
40: PetscReal ccfl; /* Placeholder for CFL coefficient relative to forward Euler */
41: PetscReal *binterpt; /* Dense output formula */
42: };
43: typedef struct _RosWTableauLink *RosWTableauLink;
44: struct _RosWTableauLink {
45: struct _RosWTableau tab;
46: RosWTableauLink next;
47: };
48: static RosWTableauLink RosWTableauList;
50: typedef struct {
51: RosWTableau tableau;
52: Vec *Y; /* States computed during the step, used to complete the step */
53: Vec Ydot; /* Work vector holding Ydot during residual evaluation */
54: Vec Ystage; /* Work vector for the state value at each stage */
55: Vec Zdot; /* Ydot = Zdot + shift*Y */
56: Vec Zstage; /* Y = Zstage + Y */
57: Vec VecSolPrev; /* Work vector holding the solution from the previous step (used for interpolation)*/
58: PetscScalar *work; /* Scalar work space of length number of stages, used to prepare VecMAXPY() */
59: PetscReal scoeff; /* shift = scoeff/dt */
60: PetscReal stage_time;
61: PetscReal stage_explicit; /* Flag indicates that the current stage is explicit */
62: PetscBool recompute_jacobian; /* Recompute the Jacobian at each stage, default is to freeze the Jacobian at the start of each step */
63: TSStepStatus status;
64: } TS_RosW;
66: /*MC
67: TSROSWTHETA1 - One stage first order L-stable Rosenbrock-W scheme (aka theta method).
69: Only an approximate Jacobian is needed.
71: Level: intermediate
73: .seealso: TSROSW
74: M*/
76: /*MC
77: TSROSWTHETA2 - One stage second order A-stable Rosenbrock-W scheme (aka theta method).
79: Only an approximate Jacobian is needed.
81: Level: intermediate
83: .seealso: TSROSW
84: M*/
86: /*MC
87: TSROSW2M - Two stage second order L-stable Rosenbrock-W scheme.
89: Only an approximate Jacobian is needed. By default, it is only recomputed once per step. This method is a reflection of TSROSW2P.
91: Level: intermediate
93: .seealso: TSROSW
94: M*/
96: /*MC
97: TSROSW2P - Two stage second order L-stable Rosenbrock-W scheme.
99: Only an approximate Jacobian is needed. By default, it is only recomputed once per step. This method is a reflection of TSROSW2M.
101: Level: intermediate
103: .seealso: TSROSW
104: M*/
106: /*MC
107: TSROSWRA3PW - Three stage third order Rosenbrock-W scheme for PDAE of index 1.
109: Only an approximate Jacobian is needed. By default, it is only recomputed once per step.
111: This is strongly A-stable with R(infty) = 0.73. The embedded method of order 2 is strongly A-stable with R(infty) = 0.73.
113: References:
114: Rang and Angermann, New Rosenbrock-W methods of order 3 for partial differential algebraic equations of index 1, 2005.
116: Level: intermediate
118: .seealso: TSROSW
119: M*/
121: /*MC
122: TSROSWRA34PW2 - Four stage third order L-stable Rosenbrock-W scheme for PDAE of index 1.
124: Only an approximate Jacobian is needed. By default, it is only recomputed once per step.
126: This is strongly A-stable with R(infty) = 0. The embedded method of order 2 is strongly A-stable with R(infty) = 0.48.
128: References:
129: Rang and Angermann, New Rosenbrock-W methods of order 3 for partial differential algebraic equations of index 1, 2005.
131: Level: intermediate
133: .seealso: TSROSW
134: M*/
136: /*MC
137: TSROSWRODAS3 - Four stage third order L-stable Rosenbrock scheme
139: By default, the Jacobian is only recomputed once per step.
141: Both the third order and embedded second order methods are stiffly accurate and L-stable.
143: References:
144: Sandu et al, Benchmarking stiff ODE solvers for atmospheric chemistry problems II, Rosenbrock solvers, 1997.
146: Level: intermediate
148: .seealso: TSROSW, TSROSWSANDU3
149: M*/
151: /*MC
152: TSROSWSANDU3 - Three stage third order L-stable Rosenbrock scheme
154: By default, the Jacobian is only recomputed once per step.
156: The third order method is L-stable, but not stiffly accurate.
157: The second order embedded method is strongly A-stable with R(infty) = 0.5.
158: The internal stages are L-stable.
159: This method is called ROS3 in the paper.
161: References:
162: Sandu et al, Benchmarking stiff ODE solvers for atmospheric chemistry problems II, Rosenbrock solvers, 1997.
164: Level: intermediate
166: .seealso: TSROSW, TSROSWRODAS3
167: M*/
169: /*MC
170: TSROSWASSP3P3S1C - A-stable Rosenbrock-W method with SSP explicit part, third order, three stages
172: By default, the Jacobian is only recomputed once per step.
174: A-stable SPP explicit order 3, 3 stages, CFL 1 (eff = 1/3)
176: References:
177: Emil Constantinescu
179: Level: intermediate
181: .seealso: TSROSW, TSROSWLASSP3P4S2C, TSROSWLLSSP3P4S2C, SSP
182: M*/
184: /*MC
185: TSROSWLASSP3P4S2C - L-stable Rosenbrock-W method with SSP explicit part, third order, four stages
187: By default, the Jacobian is only recomputed once per step.
189: L-stable (A-stable embedded) SPP explicit order 3, 4 stages, CFL 2 (eff = 1/2)
191: References:
192: Emil Constantinescu
194: Level: intermediate
196: .seealso: TSROSW, TSROSWASSP3P3S1C, TSROSWLLSSP3P4S2C, TSSSP
197: M*/
199: /*MC
200: TSROSWLLSSP3P4S2C - L-stable Rosenbrock-W method with SSP explicit part, third order, four stages
202: By default, the Jacobian is only recomputed once per step.
204: L-stable (L-stable embedded) SPP explicit order 3, 4 stages, CFL 2 (eff = 1/2)
206: References:
207: Emil Constantinescu
209: Level: intermediate
211: .seealso: TSROSW, TSROSWASSP3P3S1C, TSROSWLASSP3P4S2C, TSSSP
212: M*/
214: /*MC
215: TSROSWGRK4T - four stage, fourth order Rosenbrock (not W) method from Kaps and Rentrop
217: By default, the Jacobian is only recomputed once per step.
219: A(89.3 degrees)-stable, |R(infty)| = 0.454.
221: This method does not provide a dense output formula.
223: References:
224: Kaps and Rentrop, Generalized Runge-Kutta methods of order four with stepsize control for stiff ordinary differential equations, 1979.
226: Hairer and Wanner, Solving Ordinary Differential Equations II, Section 4 Table 7.2.
228: Hairer's code ros4.f
230: Level: intermediate
232: .seealso: TSROSW, TSROSWSHAMP4, TSROSWVELDD4, TSROSW4L
233: M*/
235: /*MC
236: TSROSWSHAMP4 - four stage, fourth order Rosenbrock (not W) method from Shampine
238: By default, the Jacobian is only recomputed once per step.
240: A-stable, |R(infty)| = 1/3.
242: This method does not provide a dense output formula.
244: References:
245: Shampine, Implementation of Rosenbrock methods, 1982.
247: Hairer and Wanner, Solving Ordinary Differential Equations II, Section 4 Table 7.2.
249: Hairer's code ros4.f
251: Level: intermediate
253: .seealso: TSROSW, TSROSWGRK4T, TSROSWVELDD4, TSROSW4L
254: M*/
256: /*MC
257: TSROSWVELDD4 - four stage, fourth order Rosenbrock (not W) method from van Veldhuizen
259: By default, the Jacobian is only recomputed once per step.
261: A(89.5 degrees)-stable, |R(infty)| = 0.24.
263: This method does not provide a dense output formula.
265: References:
266: van Veldhuizen, D-stability and Kaps-Rentrop methods, 1984.
268: Hairer and Wanner, Solving Ordinary Differential Equations II, Section 4 Table 7.2.
270: Hairer's code ros4.f
272: Level: intermediate
274: .seealso: TSROSW, TSROSWGRK4T, TSROSWSHAMP4, TSROSW4L
275: M*/
277: /*MC
278: TSROSW4L - four stage, fourth order Rosenbrock (not W) method
280: By default, the Jacobian is only recomputed once per step.
282: A-stable and L-stable
284: This method does not provide a dense output formula.
286: References:
287: Hairer and Wanner, Solving Ordinary Differential Equations II, Section 4 Table 7.2.
289: Hairer's code ros4.f
291: Level: intermediate
293: .seealso: TSROSW, TSROSWGRK4T, TSROSWSHAMP4, TSROSW4L
294: M*/
298: /*@C
299: TSRosWRegisterAll - Registers all of the additive Runge-Kutta implicit-explicit methods in TSRosW
301: Not Collective, but should be called by all processes which will need the schemes to be registered
303: Level: advanced
305: .keywords: TS, TSRosW, register, all
307: .seealso: TSRosWRegisterDestroy()
308: @*/
309: PetscErrorCode TSRosWRegisterAll(void)
310: {
314: if (TSRosWRegisterAllCalled) return(0);
315: TSRosWRegisterAllCalled = PETSC_TRUE;
317: {
318: const PetscReal A = 0;
319: const PetscReal Gamma = 1;
320: const PetscReal b = 1;
321: const PetscReal binterpt=1;
323: TSRosWRegister(TSROSWTHETA1,1,1,&A,&Gamma,&b,NULL,1,&binterpt);
324: }
326: {
327: const PetscReal A = 0;
328: const PetscReal Gamma = 0.5;
329: const PetscReal b = 1;
330: const PetscReal binterpt=1;
332: TSRosWRegister(TSROSWTHETA2,2,1,&A,&Gamma,&b,NULL,1,&binterpt);
333: }
335: {
336: /*const PetscReal g = 1. + 1./PetscSqrtReal(2.0); Direct evaluation: 1.707106781186547524401. Used for setting up arrays of values known at compile time below. */
337: const PetscReal
338: A[2][2] = {{0,0}, {1.,0}},
339: Gamma[2][2] = {{1.707106781186547524401,0}, {-2.*1.707106781186547524401,1.707106781186547524401}},
340: b[2] = {0.5,0.5},
341: b1[2] = {1.0,0.0};
342: PetscReal binterpt[2][2];
343: binterpt[0][0] = 1.707106781186547524401 - 1.0;
344: binterpt[1][0] = 2.0 - 1.707106781186547524401;
345: binterpt[0][1] = 1.707106781186547524401 - 1.5;
346: binterpt[1][1] = 1.5 - 1.707106781186547524401;
348: TSRosWRegister(TSROSW2P,2,2,&A[0][0],&Gamma[0][0],b,b1,2,&binterpt[0][0]);
349: }
350: {
351: /*const PetscReal g = 1. - 1./PetscSqrtReal(2.0); Direct evaluation: 0.2928932188134524755992. Used for setting up arrays of values known at compile time below. */
352: const PetscReal
353: A[2][2] = {{0,0}, {1.,0}},
354: Gamma[2][2] = {{0.2928932188134524755992,0}, {-2.*0.2928932188134524755992,0.2928932188134524755992}},
355: b[2] = {0.5,0.5},
356: b1[2] = {1.0,0.0};
357: PetscReal binterpt[2][2];
358: binterpt[0][0] = 0.2928932188134524755992 - 1.0;
359: binterpt[1][0] = 2.0 - 0.2928932188134524755992;
360: binterpt[0][1] = 0.2928932188134524755992 - 1.5;
361: binterpt[1][1] = 1.5 - 0.2928932188134524755992;
363: TSRosWRegister(TSROSW2M,2,2,&A[0][0],&Gamma[0][0],b,b1,2,&binterpt[0][0]);
364: }
365: {
366: /*const PetscReal g = 7.8867513459481287e-01; Directly written in-place below */
367: PetscReal binterpt[3][2];
368: const PetscReal
369: A[3][3] = {{0,0,0},
370: {1.5773502691896257e+00,0,0},
371: {0.5,0,0}},
372: Gamma[3][3] = {{7.8867513459481287e-01,0,0},
373: {-1.5773502691896257e+00,7.8867513459481287e-01,0},
374: {-6.7075317547305480e-01,-1.7075317547305482e-01,7.8867513459481287e-01}},
375: b[3] = {1.0566243270259355e-01,4.9038105676657971e-02,8.4529946162074843e-01},
376: b2[3] = {-1.7863279495408180e-01,1./3.,8.4529946162074843e-01};
378: binterpt[0][0] = -0.8094010767585034;
379: binterpt[1][0] = -0.5;
380: binterpt[2][0] = 2.3094010767585034;
381: binterpt[0][1] = 0.9641016151377548;
382: binterpt[1][1] = 0.5;
383: binterpt[2][1] = -1.4641016151377548;
385: TSRosWRegister(TSROSWRA3PW,3,3,&A[0][0],&Gamma[0][0],b,b2,2,&binterpt[0][0]);
386: }
387: {
388: PetscReal binterpt[4][3];
389: /*const PetscReal g = 4.3586652150845900e-01; Directly written in-place below */
390: const PetscReal
391: A[4][4] = {{0,0,0,0},
392: {8.7173304301691801e-01,0,0,0},
393: {8.4457060015369423e-01,-1.1299064236484185e-01,0,0},
394: {0,0,1.,0}},
395: Gamma[4][4] = {{4.3586652150845900e-01,0,0,0},
396: {-8.7173304301691801e-01,4.3586652150845900e-01,0,0},
397: {-9.0338057013044082e-01,5.4180672388095326e-02,4.3586652150845900e-01,0},
398: {2.4212380706095346e-01,-1.2232505839045147e+00,5.4526025533510214e-01,4.3586652150845900e-01}},
399: b[4] = {2.4212380706095346e-01,-1.2232505839045147e+00,1.5452602553351020e+00,4.3586652150845900e-01},
400: b2[4] = {3.7810903145819369e-01,-9.6042292212423178e-02,5.0000000000000000e-01,2.1793326075422950e-01};
402: binterpt[0][0]=1.0564298455794094;
403: binterpt[1][0]=2.296429974281067;
404: binterpt[2][0]=-1.307599564525376;
405: binterpt[3][0]=-1.045260255335102;
406: binterpt[0][1]=-1.3864882699759573;
407: binterpt[1][1]=-8.262611700275677;
408: binterpt[2][1]=7.250979895056055;
409: binterpt[3][1]=2.398120075195581;
410: binterpt[0][2]=0.5721822314575016;
411: binterpt[1][2]=4.742931142090097;
412: binterpt[2][2]=-4.398120075195578;
413: binterpt[3][2]=-0.9169932983520199;
415: TSRosWRegister(TSROSWRA34PW2,3,4,&A[0][0],&Gamma[0][0],b,b2,3,&binterpt[0][0]);
416: }
417: {
418: /* const PetscReal g = 0.5; Directly written in-place below */
419: const PetscReal
420: A[4][4] = {{0,0,0,0},
421: {0,0,0,0},
422: {1.,0,0,0},
423: {0.75,-0.25,0.5,0}},
424: Gamma[4][4] = {{0.5,0,0,0},
425: {1.,0.5,0,0},
426: {-0.25,-0.25,0.5,0},
427: {1./12,1./12,-2./3,0.5}},
428: b[4] = {5./6,-1./6,-1./6,0.5},
429: b2[4] = {0.75,-0.25,0.5,0};
431: TSRosWRegister(TSROSWRODAS3,3,4,&A[0][0],&Gamma[0][0],b,b2,0,NULL);
432: }
433: {
434: /*const PetscReal g = 0.43586652150845899941601945119356; Directly written in-place below */
435: const PetscReal
436: A[3][3] = {{0,0,0},
437: {0.43586652150845899941601945119356,0,0},
438: {0.43586652150845899941601945119356,0,0}},
439: Gamma[3][3] = {{0.43586652150845899941601945119356,0,0},
440: {-0.19294655696029095575009695436041,0.43586652150845899941601945119356,0},
441: {0,1.74927148125794685173529749738960,0.43586652150845899941601945119356}},
442: b[3] = {-0.75457412385404315829818998646589,1.94100407061964420292840123379419,-0.18642994676560104463021124732829},
443: b2[3] = {-1.53358745784149585370766523913002,2.81745131148625772213931745457622,-0.28386385364476186843165221544619};
445: PetscReal binterpt[3][2];
446: binterpt[0][0] = 3.793692883777660870425141387941;
447: binterpt[1][0] = -2.918692883777660870425141387941;
448: binterpt[2][0] = 0.125;
449: binterpt[0][1] = -0.725741064379812106687651020584;
450: binterpt[1][1] = 0.559074397713145440020984353917;
451: binterpt[2][1] = 0.16666666666666666666666666666667;
453: TSRosWRegister(TSROSWSANDU3,3,3,&A[0][0],&Gamma[0][0],b,b2,2,&binterpt[0][0]);
454: }
455: {
456: /*const PetscReal s3 = PetscSqrtReal(3.),g = (3.0+s3)/6.0;
457: * Direct evaluation: s3 = 1.732050807568877293527;
458: * g = 0.7886751345948128822546;
459: * Values are directly inserted below to ensure availability at compile time (compiler warnings otherwise...) */
460: const PetscReal
461: A[3][3] = {{0,0,0},
462: {1,0,0},
463: {0.25,0.25,0}},
464: Gamma[3][3] = {{0,0,0},
465: {(-3.0-1.732050807568877293527)/6.0,0.7886751345948128822546,0},
466: {(-3.0-1.732050807568877293527)/24.0,(-3.0-1.732050807568877293527)/8.0,0.7886751345948128822546}},
467: b[3] = {1./6.,1./6.,2./3.},
468: b2[3] = {1./4.,1./4.,1./2.};
469: PetscReal binterpt[3][2];
471: binterpt[0][0]=0.089316397477040902157517886164709;
472: binterpt[1][0]=-0.91068360252295909784248211383529;
473: binterpt[2][0]=1.8213672050459181956849642276706;
474: binterpt[0][1]=0.077350269189625764509148780501957;
475: binterpt[1][1]=1.077350269189625764509148780502;
476: binterpt[2][1]=-1.1547005383792515290182975610039;
478: TSRosWRegister(TSROSWASSP3P3S1C,3,3,&A[0][0],&Gamma[0][0],b,b2,2,&binterpt[0][0]);
479: }
481: {
482: const PetscReal
483: A[4][4] = {{0,0,0,0},
484: {1./2.,0,0,0},
485: {1./2.,1./2.,0,0},
486: {1./6.,1./6.,1./6.,0}},
487: Gamma[4][4] = {{1./2.,0,0,0},
488: {0.0,1./4.,0,0},
489: {-2.,-2./3.,2./3.,0},
490: {1./2.,5./36.,-2./9,0}},
491: b[4] = {1./6.,1./6.,1./6.,1./2.},
492: b2[4] = {1./8.,3./4.,1./8.,0};
493: PetscReal binterpt[4][3];
495: binterpt[0][0]=6.25;
496: binterpt[1][0]=-30.25;
497: binterpt[2][0]=1.75;
498: binterpt[3][0]=23.25;
499: binterpt[0][1]=-9.75;
500: binterpt[1][1]=58.75;
501: binterpt[2][1]=-3.25;
502: binterpt[3][1]=-45.75;
503: binterpt[0][2]=3.6666666666666666666666666666667;
504: binterpt[1][2]=-28.333333333333333333333333333333;
505: binterpt[2][2]=1.6666666666666666666666666666667;
506: binterpt[3][2]=23.;
508: TSRosWRegister(TSROSWLASSP3P4S2C,3,4,&A[0][0],&Gamma[0][0],b,b2,3,&binterpt[0][0]);
509: }
511: {
512: const PetscReal
513: A[4][4] = {{0,0,0,0},
514: {1./2.,0,0,0},
515: {1./2.,1./2.,0,0},
516: {1./6.,1./6.,1./6.,0}},
517: Gamma[4][4] = {{1./2.,0,0,0},
518: {0.0,3./4.,0,0},
519: {-2./3.,-23./9.,2./9.,0},
520: {1./18.,65./108.,-2./27,0}},
521: b[4] = {1./6.,1./6.,1./6.,1./2.},
522: b2[4] = {3./16.,10./16.,3./16.,0};
523: PetscReal binterpt[4][3];
525: binterpt[0][0]=1.6911764705882352941176470588235;
526: binterpt[1][0]=3.6813725490196078431372549019608;
527: binterpt[2][0]=0.23039215686274509803921568627451;
528: binterpt[3][0]=-4.6029411764705882352941176470588;
529: binterpt[0][1]=-0.95588235294117647058823529411765;
530: binterpt[1][1]=-6.2401960784313725490196078431373;
531: binterpt[2][1]=-0.31862745098039215686274509803922;
532: binterpt[3][1]=7.5147058823529411764705882352941;
533: binterpt[0][2]=-0.56862745098039215686274509803922;
534: binterpt[1][2]=2.7254901960784313725490196078431;
535: binterpt[2][2]=0.25490196078431372549019607843137;
536: binterpt[3][2]=-2.4117647058823529411764705882353;
538: TSRosWRegister(TSROSWLLSSP3P4S2C,3,4,&A[0][0],&Gamma[0][0],b,b2,3,&binterpt[0][0]);
539: }
541: {
542: PetscReal A[4][4],Gamma[4][4],b[4],b2[4];
543: PetscReal binterpt[4][3];
545: Gamma[0][0]=0.4358665215084589994160194475295062513822671686978816;
546: Gamma[0][1]=0; Gamma[0][2]=0; Gamma[0][3]=0;
547: Gamma[1][0]=-1.997527830934941248426324674704153457289527280554476;
548: Gamma[1][1]=0.4358665215084589994160194475295062513822671686978816;
549: Gamma[1][2]=0; Gamma[1][3]=0;
550: Gamma[2][0]=-1.007948511795029620852002345345404191008352770119903;
551: Gamma[2][1]=-0.004648958462629345562774289390054679806993396798458131;
552: Gamma[2][2]=0.4358665215084589994160194475295062513822671686978816;
553: Gamma[2][3]=0;
554: Gamma[3][0]=-0.6685429734233467180451604600279552604364311322650783;
555: Gamma[3][1]=0.6056625986449338476089525334450053439525178740492984;
556: Gamma[3][2]=-0.9717899277217721234705114616271378792182450260943198;
557: Gamma[3][3]=0;
559: A[0][0]=0; A[0][1]=0; A[0][2]=0; A[0][3]=0;
560: A[1][0]=0.8717330430169179988320388950590125027645343373957631;
561: A[1][1]=0; A[1][2]=0; A[1][3]=0;
562: A[2][0]=0.5275890119763004115618079766722914408876108660811028;
563: A[2][1]=0.07241098802369958843819203208518599088698057726988732;
564: A[2][2]=0; A[2][3]=0;
565: A[3][0]=0.3990960076760701320627260685975778145384666450351314;
566: A[3][1]=-0.4375576546135194437228463747348862825846903771419953;
567: A[3][2]=1.038461646937449311660120300601880176655352737312713;
568: A[3][3]=0;
570: b[0]=0.1876410243467238251612921333138006734899663569186926;
571: b[1]=-0.5952974735769549480478230473706443582188442040780541;
572: b[2]=0.9717899277217721234705114616271378792182450260943198;
573: b[3]=0.4358665215084589994160194475295062513822671686978816;
575: b2[0]=0.2147402862233891404862383521089097657790734483804460;
576: b2[1]=-0.4851622638849390928209050538171743017757490232519684;
577: b2[2]=0.8687250025203875511662123688667549217531982787600080;
578: b2[3]=0.4016969751411624011684543450940068201770721128357014;
580: binterpt[0][0]=2.2565812720167954547104627844105;
581: binterpt[1][0]=1.349166413351089573796243820819;
582: binterpt[2][0]=-2.4695174540533503758652847586647;
583: binterpt[3][0]=-0.13623023131453465264142184656474;
584: binterpt[0][1]=-3.0826699111559187902922463354557;
585: binterpt[1][1]=-2.4689115685996042534544925650515;
586: binterpt[2][1]=5.7428279814696677152129332773553;
587: binterpt[3][1]=-0.19124650171414467146619437684812;
588: binterpt[0][2]=1.0137296634858471607430756831148;
589: binterpt[1][2]=0.52444768167155973161042570784064;
590: binterpt[2][2]=-2.3015205996945452158771370439586;
591: binterpt[3][2]=0.76334325453713832352363565300308;
593: TSRosWRegister(TSROSWARK3,3,4,&A[0][0],&Gamma[0][0],b,b2,3,&binterpt[0][0]);
594: }
595: TSRosWRegisterRos4(TSROSWGRK4T,0.231,PETSC_DEFAULT,PETSC_DEFAULT,0,-0.1282612945269037e+01);
596: TSRosWRegisterRos4(TSROSWSHAMP4,0.5,PETSC_DEFAULT,PETSC_DEFAULT,0,125./108.);
597: TSRosWRegisterRos4(TSROSWVELDD4,0.22570811482256823492,PETSC_DEFAULT,PETSC_DEFAULT,0,-1.355958941201148);
598: TSRosWRegisterRos4(TSROSW4L,0.57282,PETSC_DEFAULT,PETSC_DEFAULT,0,-1.093502252409163);
599: return(0);
600: }
606: /*@C
607: TSRosWRegisterDestroy - Frees the list of schemes that were registered by TSRosWRegister().
609: Not Collective
611: Level: advanced
613: .keywords: TSRosW, register, destroy
614: .seealso: TSRosWRegister(), TSRosWRegisterAll()
615: @*/
616: PetscErrorCode TSRosWRegisterDestroy(void)
617: {
618: PetscErrorCode ierr;
619: RosWTableauLink link;
622: while ((link = RosWTableauList)) {
623: RosWTableau t = &link->tab;
624: RosWTableauList = link->next;
625: PetscFree5(t->A,t->Gamma,t->b,t->ASum,t->GammaSum);
626: PetscFree5(t->At,t->bt,t->GammaInv,t->GammaZeroDiag,t->GammaExplicitCorr);
627: PetscFree2(t->bembed,t->bembedt);
628: PetscFree(t->binterpt);
629: PetscFree(t->name);
630: PetscFree(link);
631: }
632: TSRosWRegisterAllCalled = PETSC_FALSE;
633: return(0);
634: }
638: /*@C
639: TSRosWInitializePackage - This function initializes everything in the TSRosW package. It is called
640: from PetscDLLibraryRegister() when using dynamic libraries, and on the first call to TSCreate_RosW()
641: when using static libraries.
643: Level: developer
645: .keywords: TS, TSRosW, initialize, package
646: .seealso: PetscInitialize()
647: @*/
648: PetscErrorCode TSRosWInitializePackage(void)
649: {
653: if (TSRosWPackageInitialized) return(0);
654: TSRosWPackageInitialized = PETSC_TRUE;
655: TSRosWRegisterAll();
656: PetscRegisterFinalize(TSRosWFinalizePackage);
657: return(0);
658: }
662: /*@C
663: TSRosWFinalizePackage - This function destroys everything in the TSRosW package. It is
664: called from PetscFinalize().
666: Level: developer
668: .keywords: Petsc, destroy, package
669: .seealso: PetscFinalize()
670: @*/
671: PetscErrorCode TSRosWFinalizePackage(void)
672: {
676: TSRosWPackageInitialized = PETSC_FALSE;
677: TSRosWRegisterDestroy();
678: return(0);
679: }
683: /*@C
684: TSRosWRegister - register a Rosenbrock W scheme by providing the entries in the Butcher tableau and optionally embedded approximations and interpolation
686: Not Collective, but the same schemes should be registered on all processes on which they will be used
688: Input Parameters:
689: + name - identifier for method
690: . order - approximation order of method
691: . s - number of stages, this is the dimension of the matrices below
692: . A - Table of propagated stage coefficients (dimension s*s, row-major), strictly lower triangular
693: . Gamma - Table of coefficients in implicit stage equations (dimension s*s, row-major), lower triangular with nonzero diagonal
694: . b - Step completion table (dimension s)
695: . bembed - Step completion table for a scheme of order one less (dimension s, NULL if no embedded scheme is available)
696: . pinterp - Order of the interpolation scheme, equal to the number of columns of binterpt
697: - binterpt - Coefficients of the interpolation formula (dimension s*pinterp)
699: Notes:
700: Several Rosenbrock W methods are provided, this function is only needed to create new methods.
702: Level: advanced
704: .keywords: TS, register
706: .seealso: TSRosW
707: @*/
708: PetscErrorCode TSRosWRegister(TSRosWType name,PetscInt order,PetscInt s,const PetscReal A[],const PetscReal Gamma[],const PetscReal b[],const PetscReal bembed[],
709: PetscInt pinterp,const PetscReal binterpt[])
710: {
711: PetscErrorCode ierr;
712: RosWTableauLink link;
713: RosWTableau t;
714: PetscInt i,j,k;
715: PetscScalar *GammaInv;
724: PetscCalloc1(1,&link);
725: t = &link->tab;
726: PetscStrallocpy(name,&t->name);
727: t->order = order;
728: t->s = s;
729: PetscMalloc5(s*s,&t->A,s*s,&t->Gamma,s,&t->b,s,&t->ASum,s,&t->GammaSum);
730: PetscMalloc5(s*s,&t->At,s,&t->bt,s*s,&t->GammaInv,s,&t->GammaZeroDiag,s*s,&t->GammaExplicitCorr);
731: PetscMemcpy(t->A,A,s*s*sizeof(A[0]));
732: PetscMemcpy(t->Gamma,Gamma,s*s*sizeof(Gamma[0]));
733: PetscMemcpy(t->GammaExplicitCorr,Gamma,s*s*sizeof(Gamma[0]));
734: PetscMemcpy(t->b,b,s*sizeof(b[0]));
735: if (bembed) {
736: PetscMalloc2(s,&t->bembed,s,&t->bembedt);
737: PetscMemcpy(t->bembed,bembed,s*sizeof(bembed[0]));
738: }
739: for (i=0; i<s; i++) {
740: t->ASum[i] = 0;
741: t->GammaSum[i] = 0;
742: for (j=0; j<s; j++) {
743: t->ASum[i] += A[i*s+j];
744: t->GammaSum[i] += Gamma[i*s+j];
745: }
746: }
747: PetscMalloc1(s*s,&GammaInv); /* Need to use Scalar for inverse, then convert back to Real */
748: for (i=0; i<s*s; i++) GammaInv[i] = Gamma[i];
749: for (i=0; i<s; i++) {
750: if (Gamma[i*s+i] == 0.0) {
751: GammaInv[i*s+i] = 1.0;
752: t->GammaZeroDiag[i] = PETSC_TRUE;
753: } else {
754: t->GammaZeroDiag[i] = PETSC_FALSE;
755: }
756: }
758: switch (s) {
759: case 1: GammaInv[0] = 1./GammaInv[0]; break;
760: case 2: PetscKernel_A_gets_inverse_A_2(GammaInv,0); break;
761: case 3: PetscKernel_A_gets_inverse_A_3(GammaInv,0); break;
762: case 4: PetscKernel_A_gets_inverse_A_4(GammaInv,0); break;
763: case 5: {
764: PetscInt ipvt5[5];
765: MatScalar work5[5*5];
766: PetscKernel_A_gets_inverse_A_5(GammaInv,ipvt5,work5,0); break;
767: }
768: case 6: PetscKernel_A_gets_inverse_A_6(GammaInv,0); break;
769: case 7: PetscKernel_A_gets_inverse_A_7(GammaInv,0); break;
770: default: SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not implemented for %D stages",s);
771: }
772: for (i=0; i<s*s; i++) t->GammaInv[i] = PetscRealPart(GammaInv[i]);
773: PetscFree(GammaInv);
775: for (i=0; i<s; i++) {
776: for (k=0; k<i+1; k++) {
777: t->GammaExplicitCorr[i*s+k]=(t->GammaExplicitCorr[i*s+k])*(t->GammaInv[k*s+k]);
778: for (j=k+1; j<i+1; j++) {
779: t->GammaExplicitCorr[i*s+k]+=(t->GammaExplicitCorr[i*s+j])*(t->GammaInv[j*s+k]);
780: }
781: }
782: }
784: for (i=0; i<s; i++) {
785: for (j=0; j<s; j++) {
786: t->At[i*s+j] = 0;
787: for (k=0; k<s; k++) {
788: t->At[i*s+j] += t->A[i*s+k] * t->GammaInv[k*s+j];
789: }
790: }
791: t->bt[i] = 0;
792: for (j=0; j<s; j++) {
793: t->bt[i] += t->b[j] * t->GammaInv[j*s+i];
794: }
795: if (bembed) {
796: t->bembedt[i] = 0;
797: for (j=0; j<s; j++) {
798: t->bembedt[i] += t->bembed[j] * t->GammaInv[j*s+i];
799: }
800: }
801: }
802: t->ccfl = 1.0; /* Fix this */
804: t->pinterp = pinterp;
805: PetscMalloc1(s*pinterp,&t->binterpt);
806: PetscMemcpy(t->binterpt,binterpt,s*pinterp*sizeof(binterpt[0]));
807: link->next = RosWTableauList;
808: RosWTableauList = link;
809: return(0);
810: }
814: /*@C
815: TSRosWRegisterRos4 - register a fourth order Rosenbrock scheme by providing paramter choices
817: Not Collective, but the same schemes should be registered on all processes on which they will be used
819: Input Parameters:
820: + name - identifier for method
821: . gamma - leading coefficient (diagonal entry)
822: . a2 - design parameter, see Table 7.2 of Hairer&Wanner
823: . a3 - design parameter or PETSC_DEFAULT to satisfy one of the order five conditions (Eq 7.22)
824: . b3 - design parameter, see Table 7.2 of Hairer&Wanner
825: . beta43 - design parameter or PETSC_DEFAULT to use Equation 7.21 of Hairer&Wanner
826: . e4 - design parameter for embedded method, see coefficient E4 in ros4.f code from Hairer
828: Notes:
829: This routine encodes the design of fourth order Rosenbrock methods as described in Hairer and Wanner volume 2.
830: It is used here to implement several methods from the book and can be used to experiment with new methods.
831: It was written this way instead of by copying coefficients in order to provide better than double precision satisfaction of the order conditions.
833: Level: developer
835: .keywords: TS, register
837: .seealso: TSRosW, TSRosWRegister()
838: @*/
839: PetscErrorCode TSRosWRegisterRos4(TSRosWType name,PetscReal gamma,PetscReal a2,PetscReal a3,PetscReal b3,PetscReal e4)
840: {
842: /* Declare numeric constants so they can be quad precision without being truncated at double */
843: const PetscReal one = 1,two = 2,three = 3,four = 4,five = 5,six = 6,eight = 8,twelve = 12,twenty = 20,twentyfour = 24,
844: p32 = one/six - gamma + gamma*gamma,
845: p42 = one/eight - gamma/three,
846: p43 = one/twelve - gamma/three,
847: p44 = one/twentyfour - gamma/two + three/two*gamma*gamma - gamma*gamma*gamma,
848: p56 = one/twenty - gamma/four;
849: PetscReal a4,a32,a42,a43,b1,b2,b4,beta2p,beta3p,beta4p,beta32,beta42,beta43,beta32beta2p,beta4jbetajp;
850: PetscReal A[4][4],Gamma[4][4],b[4],bm[4];
851: PetscScalar M[3][3],rhs[3];
854: /* Step 1: choose Gamma (input) */
855: /* Step 2: choose a2,a3,a4; b1,b2,b3,b4 to satisfy order conditions */
856: if (a3 == PETSC_DEFAULT) a3 = (one/five - a2/four)/(one/four - a2/three); /* Eq 7.22 */
857: a4 = a3; /* consequence of 7.20 */
859: /* Solve order conditions 7.15a, 7.15c, 7.15e */
860: M[0][0] = one; M[0][1] = one; M[0][2] = one; /* 7.15a */
861: M[1][0] = 0.0; M[1][1] = a2*a2; M[1][2] = a4*a4; /* 7.15c */
862: M[2][0] = 0.0; M[2][1] = a2*a2*a2; M[2][2] = a4*a4*a4; /* 7.15e */
863: rhs[0] = one - b3;
864: rhs[1] = one/three - a3*a3*b3;
865: rhs[2] = one/four - a3*a3*a3*b3;
866: PetscKernel_A_gets_inverse_A_3(&M[0][0],0);
867: b1 = PetscRealPart(M[0][0]*rhs[0] + M[0][1]*rhs[1] + M[0][2]*rhs[2]);
868: b2 = PetscRealPart(M[1][0]*rhs[0] + M[1][1]*rhs[1] + M[1][2]*rhs[2]);
869: b4 = PetscRealPart(M[2][0]*rhs[0] + M[2][1]*rhs[1] + M[2][2]*rhs[2]);
871: /* Step 3 */
872: beta43 = (p56 - a2*p43) / (b4*a3*a3*(a3 - a2)); /* 7.21 */
873: beta32beta2p = p44 / (b4*beta43); /* 7.15h */
874: beta4jbetajp = (p32 - b3*beta32beta2p) / b4;
875: M[0][0] = b2; M[0][1] = b3; M[0][2] = b4;
876: M[1][0] = a4*a4*beta32beta2p-a3*a3*beta4jbetajp; M[1][1] = a2*a2*beta4jbetajp; M[1][2] = -a2*a2*beta32beta2p;
877: M[2][0] = b4*beta43*a3*a3-p43; M[2][1] = -b4*beta43*a2*a2; M[2][2] = 0;
878: rhs[0] = one/two - gamma; rhs[1] = 0; rhs[2] = -a2*a2*p32;
879: PetscKernel_A_gets_inverse_A_3(&M[0][0],0);
880: beta2p = PetscRealPart(M[0][0]*rhs[0] + M[0][1]*rhs[1] + M[0][2]*rhs[2]);
881: beta3p = PetscRealPart(M[1][0]*rhs[0] + M[1][1]*rhs[1] + M[1][2]*rhs[2]);
882: beta4p = PetscRealPart(M[2][0]*rhs[0] + M[2][1]*rhs[1] + M[2][2]*rhs[2]);
884: /* Step 4: back-substitute */
885: beta32 = beta32beta2p / beta2p;
886: beta42 = (beta4jbetajp - beta43*beta3p) / beta2p;
888: /* Step 5: 7.15f and 7.20, then 7.16 */
889: a43 = 0;
890: a32 = p42 / (b3*a3*beta2p + b4*a4*beta2p);
891: a42 = a32;
893: A[0][0] = 0; A[0][1] = 0; A[0][2] = 0; A[0][3] = 0;
894: A[1][0] = a2; A[1][1] = 0; A[1][2] = 0; A[1][3] = 0;
895: A[2][0] = a3-a32; A[2][1] = a32; A[2][2] = 0; A[2][3] = 0;
896: A[3][0] = a4-a43-a42; A[3][1] = a42; A[3][2] = a43; A[3][3] = 0;
897: Gamma[0][0] = gamma; Gamma[0][1] = 0; Gamma[0][2] = 0; Gamma[0][3] = 0;
898: Gamma[1][0] = beta2p-A[1][0]; Gamma[1][1] = gamma; Gamma[1][2] = 0; Gamma[1][3] = 0;
899: Gamma[2][0] = beta3p-beta32-A[2][0]; Gamma[2][1] = beta32-A[2][1]; Gamma[2][2] = gamma; Gamma[2][3] = 0;
900: Gamma[3][0] = beta4p-beta42-beta43-A[3][0]; Gamma[3][1] = beta42-A[3][1]; Gamma[3][2] = beta43-A[3][2]; Gamma[3][3] = gamma;
901: b[0] = b1; b[1] = b2; b[2] = b3; b[3] = b4;
903: /* Construct embedded formula using given e4. We are solving Equation 7.18. */
904: bm[3] = b[3] - e4*gamma; /* using definition of E4 */
905: bm[2] = (p32 - beta4jbetajp*bm[3]) / (beta32*beta2p); /* fourth row of 7.18 */
906: bm[1] = (one/two - gamma - beta3p*bm[2] - beta4p*bm[3]) / beta2p; /* second row */
907: bm[0] = one - bm[1] - bm[2] - bm[3]; /* first row */
909: {
910: const PetscReal misfit = a2*a2*bm[1] + a3*a3*bm[2] + a4*a4*bm[3] - one/three;
911: if (PetscAbs(misfit) > PETSC_SMALL) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Assumptions violated, could not construct a third order embedded method");
912: }
913: TSRosWRegister(name,4,4,&A[0][0],&Gamma[0][0],b,bm,0,NULL);
914: return(0);
915: }
919: /*
920: The step completion formula is
922: x1 = x0 + b^T Y
924: where Y is the multi-vector of stages corrections. This function can be called before or after ts->vec_sol has been
925: updated. Suppose we have a completion formula b and an embedded formula be of different order. We can write
927: x1e = x0 + be^T Y
928: = x1 - b^T Y + be^T Y
929: = x1 + (be - b)^T Y
931: so we can evaluate the method of different order even after the step has been optimistically completed.
932: */
933: static PetscErrorCode TSEvaluateStep_RosW(TS ts,PetscInt order,Vec U,PetscBool *done)
934: {
935: TS_RosW *ros = (TS_RosW*)ts->data;
936: RosWTableau tab = ros->tableau;
937: PetscScalar *w = ros->work;
938: PetscInt i;
942: if (order == tab->order) {
943: if (ros->status == TS_STEP_INCOMPLETE) { /* Use standard completion formula */
944: VecCopy(ts->vec_sol,U);
945: for (i=0; i<tab->s; i++) w[i] = tab->bt[i];
946: VecMAXPY(U,tab->s,w,ros->Y);
947: } else {VecCopy(ts->vec_sol,U);}
948: if (done) *done = PETSC_TRUE;
949: return(0);
950: } else if (order == tab->order-1) {
951: if (!tab->bembedt) goto unavailable;
952: if (ros->status == TS_STEP_INCOMPLETE) { /* Use embedded completion formula */
953: VecCopy(ts->vec_sol,U);
954: for (i=0; i<tab->s; i++) w[i] = tab->bembedt[i];
955: VecMAXPY(U,tab->s,w,ros->Y);
956: } else { /* Use rollback-and-recomplete formula (bembedt - bt) */
957: for (i=0; i<tab->s; i++) w[i] = tab->bembedt[i] - tab->bt[i];
958: VecCopy(ts->vec_sol,U);
959: VecMAXPY(U,tab->s,w,ros->Y);
960: }
961: if (done) *done = PETSC_TRUE;
962: return(0);
963: }
964: unavailable:
965: if (done) *done = PETSC_FALSE;
966: else SETERRQ3(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"Rosenbrock-W '%s' of order %D cannot evaluate step at order %D",tab->name,tab->order,order);
967: return(0);
968: }
972: PetscErrorCode TSRollBack_RosW(TS ts)
973: {
974: TS_RosW *ros = (TS_RosW*)ts->data;
975: RosWTableau tab = ros->tableau;
976: const PetscInt s = tab->s;
977: PetscScalar *w = ros->work;
978: PetscInt i;
979: Vec *Y = ros->Y;
983: for (i=0; i<s; i++) w[i] = -tab->bt[i];
984: VecMAXPY(ts->vec_sol,s,w,Y);
985: ros->status = TS_STEP_INCOMPLETE;
986: return(0);
987: }
991: static PetscErrorCode TSStep_RosW(TS ts)
992: {
993: TS_RosW *ros = (TS_RosW*)ts->data;
994: RosWTableau tab = ros->tableau;
995: const PetscInt s = tab->s;
996: const PetscReal *At = tab->At,*Gamma = tab->Gamma,*ASum = tab->ASum,*GammaInv = tab->GammaInv;
997: const PetscReal *GammaExplicitCorr = tab->GammaExplicitCorr;
998: const PetscBool *GammaZeroDiag = tab->GammaZeroDiag;
999: PetscScalar *w = ros->work;
1000: Vec *Y = ros->Y,Ydot = ros->Ydot,Zdot = ros->Zdot,Zstage = ros->Zstage;
1001: SNES snes;
1002: TSAdapt adapt;
1003: PetscInt i,j,its,lits,reject,next_scheme;
1004: PetscBool accept;
1005: PetscReal next_time_step;
1006: PetscErrorCode ierr;
1009: TSGetSNES(ts,&snes);
1010: accept = PETSC_TRUE;
1011: next_time_step = ts->time_step;
1012: ros->status = TS_STEP_INCOMPLETE;
1014: for (reject=0; reject<ts->max_reject && !ts->reason; reject++,ts->reject++) {
1015: const PetscReal h = ts->time_step;
1016: TSPreStep(ts);
1017: VecCopy(ts->vec_sol,ros->VecSolPrev); /*move this at the end*/
1018: for (i=0; i<s; i++) {
1019: ros->stage_time = ts->ptime + h*ASum[i];
1020: TSPreStage(ts,ros->stage_time);
1021: if (GammaZeroDiag[i]) {
1022: ros->stage_explicit = PETSC_TRUE;
1023: ros->scoeff = 1.;
1024: } else {
1025: ros->stage_explicit = PETSC_FALSE;
1026: ros->scoeff = 1./Gamma[i*s+i];
1027: }
1029: VecCopy(ts->vec_sol,Zstage);
1030: for (j=0; j<i; j++) w[j] = At[i*s+j];
1031: VecMAXPY(Zstage,i,w,Y);
1033: for (j=0; j<i; j++) w[j] = 1./h * GammaInv[i*s+j];
1034: VecZeroEntries(Zdot);
1035: VecMAXPY(Zdot,i,w,Y);
1037: /* Initial guess taken from last stage */
1038: VecZeroEntries(Y[i]);
1040: if (!ros->stage_explicit) {
1041: if (!ros->recompute_jacobian && !i) {
1042: SNESSetLagJacobian(snes,-2); /* Recompute the Jacobian on this solve, but not again */
1043: }
1044: SNESSolve(snes,NULL,Y[i]);
1045: SNESGetIterationNumber(snes,&its);
1046: SNESGetLinearSolveIterations(snes,&lits);
1047: ts->snes_its += its; ts->ksp_its += lits;
1048: TSGetAdapt(ts,&adapt);
1049: TSAdaptCheckStage(adapt,ts,&accept);
1050: if (!accept) goto reject_step;
1051: } else {
1052: Mat J,Jp;
1053: VecZeroEntries(Ydot); /* Evaluate Y[i]=G(t,Ydot=0,Zstage) */
1054: TSComputeIFunction(ts,ros->stage_time,Zstage,Ydot,Y[i],PETSC_FALSE);
1055: VecScale(Y[i],-1.0);
1056: VecAXPY(Y[i],-1.0,Zdot); /*Y[i]=F(Zstage)-Zdot[=GammaInv*Y]*/
1058: VecZeroEntries(Zstage); /* Zstage = GammaExplicitCorr[i,j] * Y[j] */
1059: for (j=0; j<i; j++) w[j] = GammaExplicitCorr[i*s+j];
1060: VecMAXPY(Zstage,i,w,Y);
1061: /*Y[i] += Y[i] + Jac*Zstage[=Jac*GammaExplicitCorr[i,j] * Y[j]] */
1062: TSGetIJacobian(ts,&J,&Jp,NULL,NULL);
1063: TSComputeIJacobian(ts,ros->stage_time,ts->vec_sol,Ydot,0,J,Jp,PETSC_FALSE);
1064: MatMult(J,Zstage,Zdot);
1066: VecAXPY(Y[i],-1.0,Zdot);
1067: VecScale(Y[i],h);
1068: ts->ksp_its += 1;
1069: }
1070: TSPostStage(ts,ros->stage_time,i,Y);
1071: }
1072: TSEvaluateStep(ts,tab->order,ts->vec_sol,NULL);
1073: ros->status = TS_STEP_PENDING;
1075: /* Register only the current method as a candidate because we're not supporting multiple candidates yet. */
1076: TSGetAdapt(ts,&adapt);
1077: TSAdaptCandidatesClear(adapt);
1078: TSAdaptCandidateAdd(adapt,tab->name,tab->order,1,tab->ccfl,1.*tab->s,PETSC_TRUE);
1079: TSAdaptChoose(adapt,ts,ts->time_step,&next_scheme,&next_time_step,&accept);
1080: if (accept) {
1081: /* ignore next_scheme for now */
1082: ts->ptime += ts->time_step;
1083: ts->time_step = next_time_step;
1084: ts->steps++;
1085: ros->status = TS_STEP_COMPLETE;
1086: break;
1087: } else { /* Roll back the current step */
1088: ts->ptime += next_time_step; /* This will be undone in rollback */
1089: ros->status = TS_STEP_INCOMPLETE;
1090: TSRollBack(ts);
1091: }
1092: reject_step: continue;
1093: }
1094: if (ros->status != TS_STEP_COMPLETE && !ts->reason) ts->reason = TS_DIVERGED_STEP_REJECTED;
1095: return(0);
1096: }
1100: static PetscErrorCode TSInterpolate_RosW(TS ts,PetscReal itime,Vec U)
1101: {
1102: TS_RosW *ros = (TS_RosW*)ts->data;
1103: PetscInt s = ros->tableau->s,pinterp = ros->tableau->pinterp,i,j;
1104: PetscReal h;
1105: PetscReal tt,t;
1106: PetscScalar *bt;
1107: const PetscReal *Bt = ros->tableau->binterpt;
1108: PetscErrorCode ierr;
1109: const PetscReal *GammaInv = ros->tableau->GammaInv;
1110: PetscScalar *w = ros->work;
1111: Vec *Y = ros->Y;
1114: if (!Bt) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSRosW %s does not have an interpolation formula",ros->tableau->name);
1116: switch (ros->status) {
1117: case TS_STEP_INCOMPLETE:
1118: case TS_STEP_PENDING:
1119: h = ts->time_step;
1120: t = (itime - ts->ptime)/h;
1121: break;
1122: case TS_STEP_COMPLETE:
1123: h = ts->time_step_prev;
1124: t = (itime - ts->ptime)/h + 1; /* In the interval [0,1] */
1125: break;
1126: default: SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_PLIB,"Invalid TSStepStatus");
1127: }
1128: PetscMalloc1(s,&bt);
1129: for (i=0; i<s; i++) bt[i] = 0;
1130: for (j=0,tt=t; j<pinterp; j++,tt*=t) {
1131: for (i=0; i<s; i++) {
1132: bt[i] += Bt[i*pinterp+j] * tt;
1133: }
1134: }
1136: /* y(t+tt*h) = y(t) + Sum bt(tt) * GammaInv * Ydot */
1137: /*U<-0*/
1138: VecZeroEntries(U);
1140: /*U<- Sum bt_i * GammaInv(i,1:i) * Y(1:i) */
1141: for (j=0; j<s; j++) w[j]=0;
1142: for (j=0; j<s; j++) {
1143: for (i=j; i<s; i++) {
1144: w[j] += bt[i]*GammaInv[i*s+j];
1145: }
1146: }
1147: VecMAXPY(U,i,w,Y);
1149: /*X<-y(t) + X*/
1150: VecAXPY(U,1.0,ros->VecSolPrev);
1152: PetscFree(bt);
1153: return(0);
1154: }
1156: /*------------------------------------------------------------*/
1159: static PetscErrorCode TSReset_RosW(TS ts)
1160: {
1161: TS_RosW *ros = (TS_RosW*)ts->data;
1162: PetscInt s;
1166: if (!ros->tableau) return(0);
1167: s = ros->tableau->s;
1168: VecDestroyVecs(s,&ros->Y);
1169: VecDestroy(&ros->Ydot);
1170: VecDestroy(&ros->Ystage);
1171: VecDestroy(&ros->Zdot);
1172: VecDestroy(&ros->Zstage);
1173: VecDestroy(&ros->VecSolPrev);
1174: PetscFree(ros->work);
1175: return(0);
1176: }
1180: static PetscErrorCode TSDestroy_RosW(TS ts)
1181: {
1185: TSReset_RosW(ts);
1186: PetscFree(ts->data);
1187: PetscObjectComposeFunction((PetscObject)ts,"TSRosWGetType_C",NULL);
1188: PetscObjectComposeFunction((PetscObject)ts,"TSRosWSetType_C",NULL);
1189: PetscObjectComposeFunction((PetscObject)ts,"TSRosWSetRecomputeJacobian_C",NULL);
1190: return(0);
1191: }
1196: static PetscErrorCode TSRosWGetVecs(TS ts,DM dm,Vec *Ydot,Vec *Zdot,Vec *Ystage,Vec *Zstage)
1197: {
1198: TS_RosW *rw = (TS_RosW*)ts->data;
1202: if (Ydot) {
1203: if (dm && dm != ts->dm) {
1204: DMGetNamedGlobalVector(dm,"TSRosW_Ydot",Ydot);
1205: } else *Ydot = rw->Ydot;
1206: }
1207: if (Zdot) {
1208: if (dm && dm != ts->dm) {
1209: DMGetNamedGlobalVector(dm,"TSRosW_Zdot",Zdot);
1210: } else *Zdot = rw->Zdot;
1211: }
1212: if (Ystage) {
1213: if (dm && dm != ts->dm) {
1214: DMGetNamedGlobalVector(dm,"TSRosW_Ystage",Ystage);
1215: } else *Ystage = rw->Ystage;
1216: }
1217: if (Zstage) {
1218: if (dm && dm != ts->dm) {
1219: DMGetNamedGlobalVector(dm,"TSRosW_Zstage",Zstage);
1220: } else *Zstage = rw->Zstage;
1221: }
1222: return(0);
1223: }
1228: static PetscErrorCode TSRosWRestoreVecs(TS ts,DM dm,Vec *Ydot,Vec *Zdot, Vec *Ystage, Vec *Zstage)
1229: {
1233: if (Ydot) {
1234: if (dm && dm != ts->dm) {
1235: DMRestoreNamedGlobalVector(dm,"TSRosW_Ydot",Ydot);
1236: }
1237: }
1238: if (Zdot) {
1239: if (dm && dm != ts->dm) {
1240: DMRestoreNamedGlobalVector(dm,"TSRosW_Zdot",Zdot);
1241: }
1242: }
1243: if (Ystage) {
1244: if (dm && dm != ts->dm) {
1245: DMRestoreNamedGlobalVector(dm,"TSRosW_Ystage",Ystage);
1246: }
1247: }
1248: if (Zstage) {
1249: if (dm && dm != ts->dm) {
1250: DMRestoreNamedGlobalVector(dm,"TSRosW_Zstage",Zstage);
1251: }
1252: }
1253: return(0);
1254: }
1258: static PetscErrorCode DMCoarsenHook_TSRosW(DM fine,DM coarse,void *ctx)
1259: {
1261: return(0);
1262: }
1266: static PetscErrorCode DMRestrictHook_TSRosW(DM fine,Mat restrct,Vec rscale,Mat inject,DM coarse,void *ctx)
1267: {
1268: TS ts = (TS)ctx;
1270: Vec Ydot,Zdot,Ystage,Zstage;
1271: Vec Ydotc,Zdotc,Ystagec,Zstagec;
1274: TSRosWGetVecs(ts,fine,&Ydot,&Ystage,&Zdot,&Zstage);
1275: TSRosWGetVecs(ts,coarse,&Ydotc,&Ystagec,&Zdotc,&Zstagec);
1276: MatRestrict(restrct,Ydot,Ydotc);
1277: VecPointwiseMult(Ydotc,rscale,Ydotc);
1278: MatRestrict(restrct,Ystage,Ystagec);
1279: VecPointwiseMult(Ystagec,rscale,Ystagec);
1280: MatRestrict(restrct,Zdot,Zdotc);
1281: VecPointwiseMult(Zdotc,rscale,Zdotc);
1282: MatRestrict(restrct,Zstage,Zstagec);
1283: VecPointwiseMult(Zstagec,rscale,Zstagec);
1284: TSRosWRestoreVecs(ts,fine,&Ydot,&Ystage,&Zdot,&Zstage);
1285: TSRosWRestoreVecs(ts,coarse,&Ydotc,&Ystagec,&Zdotc,&Zstagec);
1286: return(0);
1287: }
1292: static PetscErrorCode DMSubDomainHook_TSRosW(DM fine,DM coarse,void *ctx)
1293: {
1295: return(0);
1296: }
1300: static PetscErrorCode DMSubDomainRestrictHook_TSRosW(DM dm,VecScatter gscat,VecScatter lscat,DM subdm,void *ctx)
1301: {
1302: TS ts = (TS)ctx;
1304: Vec Ydot,Zdot,Ystage,Zstage;
1305: Vec Ydots,Zdots,Ystages,Zstages;
1308: TSRosWGetVecs(ts,dm,&Ydot,&Ystage,&Zdot,&Zstage);
1309: TSRosWGetVecs(ts,subdm,&Ydots,&Ystages,&Zdots,&Zstages);
1311: VecScatterBegin(gscat,Ydot,Ydots,INSERT_VALUES,SCATTER_FORWARD);
1312: VecScatterEnd(gscat,Ydot,Ydots,INSERT_VALUES,SCATTER_FORWARD);
1314: VecScatterBegin(gscat,Ystage,Ystages,INSERT_VALUES,SCATTER_FORWARD);
1315: VecScatterEnd(gscat,Ystage,Ystages,INSERT_VALUES,SCATTER_FORWARD);
1317: VecScatterBegin(gscat,Zdot,Zdots,INSERT_VALUES,SCATTER_FORWARD);
1318: VecScatterEnd(gscat,Zdot,Zdots,INSERT_VALUES,SCATTER_FORWARD);
1320: VecScatterBegin(gscat,Zstage,Zstages,INSERT_VALUES,SCATTER_FORWARD);
1321: VecScatterEnd(gscat,Zstage,Zstages,INSERT_VALUES,SCATTER_FORWARD);
1323: TSRosWRestoreVecs(ts,dm,&Ydot,&Ystage,&Zdot,&Zstage);
1324: TSRosWRestoreVecs(ts,subdm,&Ydots,&Ystages,&Zdots,&Zstages);
1325: return(0);
1326: }
1328: /*
1329: This defines the nonlinear equation that is to be solved with SNES
1330: G(U) = F[t0+Theta*dt, U, (U-U0)*shift] = 0
1331: */
1334: static PetscErrorCode SNESTSFormFunction_RosW(SNES snes,Vec U,Vec F,TS ts)
1335: {
1336: TS_RosW *ros = (TS_RosW*)ts->data;
1338: Vec Ydot,Zdot,Ystage,Zstage;
1339: PetscReal shift = ros->scoeff / ts->time_step;
1340: DM dm,dmsave;
1343: SNESGetDM(snes,&dm);
1344: TSRosWGetVecs(ts,dm,&Ydot,&Zdot,&Ystage,&Zstage);
1345: VecWAXPY(Ydot,shift,U,Zdot); /* Ydot = shift*U + Zdot */
1346: VecWAXPY(Ystage,1.0,U,Zstage); /* Ystage = U + Zstage */
1347: dmsave = ts->dm;
1348: ts->dm = dm;
1349: TSComputeIFunction(ts,ros->stage_time,Ystage,Ydot,F,PETSC_FALSE);
1350: ts->dm = dmsave;
1351: TSRosWRestoreVecs(ts,dm,&Ydot,&Zdot,&Ystage,&Zstage);
1352: return(0);
1353: }
1357: static PetscErrorCode SNESTSFormJacobian_RosW(SNES snes,Vec U,Mat A,Mat B,TS ts)
1358: {
1359: TS_RosW *ros = (TS_RosW*)ts->data;
1360: Vec Ydot,Zdot,Ystage,Zstage;
1361: PetscReal shift = ros->scoeff / ts->time_step;
1363: DM dm,dmsave;
1366: /* ros->Ydot and ros->Ystage have already been computed in SNESTSFormFunction_RosW (SNES guarantees this) */
1367: SNESGetDM(snes,&dm);
1368: TSRosWGetVecs(ts,dm,&Ydot,&Zdot,&Ystage,&Zstage);
1369: dmsave = ts->dm;
1370: ts->dm = dm;
1371: TSComputeIJacobian(ts,ros->stage_time,Ystage,Ydot,shift,A,B,PETSC_TRUE);
1372: ts->dm = dmsave;
1373: TSRosWRestoreVecs(ts,dm,&Ydot,&Zdot,&Ystage,&Zstage);
1374: return(0);
1375: }
1379: static PetscErrorCode TSSetUp_RosW(TS ts)
1380: {
1381: TS_RosW *ros = (TS_RosW*)ts->data;
1382: RosWTableau tab = ros->tableau;
1383: PetscInt s = tab->s;
1385: DM dm;
1388: if (!ros->tableau) {
1389: TSRosWSetType(ts,TSRosWDefault);
1390: }
1391: VecDuplicateVecs(ts->vec_sol,s,&ros->Y);
1392: VecDuplicate(ts->vec_sol,&ros->Ydot);
1393: VecDuplicate(ts->vec_sol,&ros->Ystage);
1394: VecDuplicate(ts->vec_sol,&ros->Zdot);
1395: VecDuplicate(ts->vec_sol,&ros->Zstage);
1396: VecDuplicate(ts->vec_sol,&ros->VecSolPrev);
1397: PetscMalloc1(s,&ros->work);
1398: TSGetDM(ts,&dm);
1399: if (dm) {
1400: DMCoarsenHookAdd(dm,DMCoarsenHook_TSRosW,DMRestrictHook_TSRosW,ts);
1401: DMSubDomainHookAdd(dm,DMSubDomainHook_TSRosW,DMSubDomainRestrictHook_TSRosW,ts);
1402: }
1403: return(0);
1404: }
1405: /*------------------------------------------------------------*/
1409: static PetscErrorCode TSSetFromOptions_RosW(PetscOptions *PetscOptionsObject,TS ts)
1410: {
1411: TS_RosW *ros = (TS_RosW*)ts->data;
1413: char rostype[256];
1416: PetscOptionsHead(PetscOptionsObject,"RosW ODE solver options");
1417: {
1418: RosWTableauLink link;
1419: PetscInt count,choice;
1420: PetscBool flg;
1421: const char **namelist;
1422: SNES snes;
1424: PetscStrncpy(rostype,TSRosWDefault,sizeof(rostype));
1425: for (link=RosWTableauList,count=0; link; link=link->next,count++) ;
1426: PetscMalloc1(count,&namelist);
1427: for (link=RosWTableauList,count=0; link; link=link->next,count++) namelist[count] = link->tab.name;
1428: PetscOptionsEList("-ts_rosw_type","Family of Rosenbrock-W method","TSRosWSetType",(const char*const*)namelist,count,rostype,&choice,&flg);
1429: TSRosWSetType(ts,flg ? namelist[choice] : rostype);
1430: PetscFree(namelist);
1432: PetscOptionsBool("-ts_rosw_recompute_jacobian","Recompute the Jacobian at each stage","TSRosWSetRecomputeJacobian",ros->recompute_jacobian,&ros->recompute_jacobian,NULL);
1434: /* Rosenbrock methods are linearly implicit, so set that unless the user has specifically asked for something else */
1435: TSGetSNES(ts,&snes);
1436: if (!((PetscObject)snes)->type_name) {
1437: SNESSetType(snes,SNESKSPONLY);
1438: }
1439: SNESSetFromOptions(snes);
1440: }
1441: PetscOptionsTail();
1442: return(0);
1443: }
1447: static PetscErrorCode PetscFormatRealArray(char buf[],size_t len,const char *fmt,PetscInt n,const PetscReal x[])
1448: {
1450: PetscInt i;
1451: size_t left,count;
1452: char *p;
1455: for (i=0,p=buf,left=len; i<n; i++) {
1456: PetscSNPrintfCount(p,left,fmt,&count,x[i]);
1457: if (count >= left) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Insufficient space in buffer");
1458: left -= count;
1459: p += count;
1460: *p++ = ' ';
1461: }
1462: p[i ? 0 : -1] = 0;
1463: return(0);
1464: }
1468: static PetscErrorCode TSView_RosW(TS ts,PetscViewer viewer)
1469: {
1470: TS_RosW *ros = (TS_RosW*)ts->data;
1471: RosWTableau tab = ros->tableau;
1472: PetscBool iascii;
1474: TSAdapt adapt;
1477: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1478: if (iascii) {
1479: TSRosWType rostype;
1480: PetscInt i;
1481: PetscReal abscissa[512];
1482: char buf[512];
1483: TSRosWGetType(ts,&rostype);
1484: PetscViewerASCIIPrintf(viewer," Rosenbrock-W %s\n",rostype);
1485: PetscFormatRealArray(buf,sizeof(buf),"% 8.6f",tab->s,tab->ASum);
1486: PetscViewerASCIIPrintf(viewer," Abscissa of A = %s\n",buf);
1487: for (i=0; i<tab->s; i++) abscissa[i] = tab->ASum[i] + tab->Gamma[i];
1488: PetscFormatRealArray(buf,sizeof(buf),"% 8.6f",tab->s,abscissa);
1489: PetscViewerASCIIPrintf(viewer," Abscissa of A+Gamma = %s\n",buf);
1490: }
1491: TSGetAdapt(ts,&adapt);
1492: TSAdaptView(adapt,viewer);
1493: SNESView(ts->snes,viewer);
1494: return(0);
1495: }
1499: static PetscErrorCode TSLoad_RosW(TS ts,PetscViewer viewer)
1500: {
1502: SNES snes;
1503: TSAdapt tsadapt;
1506: TSGetAdapt(ts,&tsadapt);
1507: TSAdaptLoad(tsadapt,viewer);
1508: TSGetSNES(ts,&snes);
1509: SNESLoad(snes,viewer);
1510: /* function and Jacobian context for SNES when used with TS is always ts object */
1511: SNESSetFunction(snes,NULL,NULL,ts);
1512: SNESSetJacobian(snes,NULL,NULL,NULL,ts);
1513: return(0);
1514: }
1518: /*@C
1519: TSRosWSetType - Set the type of Rosenbrock-W scheme
1521: Logically collective
1523: Input Parameter:
1524: + ts - timestepping context
1525: - rostype - type of Rosenbrock-W scheme
1527: Level: beginner
1529: .seealso: TSRosWGetType(), TSROSW, TSROSW2M, TSROSW2P, TSROSWRA3PW, TSROSWRA34PW2, TSROSWRODAS3, TSROSWSANDU3, TSROSWASSP3P3S1C, TSROSWLASSP3P4S2C, TSROSWLLSSP3P4S2C, TSROSWARK3
1530: @*/
1531: PetscErrorCode TSRosWSetType(TS ts,TSRosWType rostype)
1532: {
1537: PetscTryMethod(ts,"TSRosWSetType_C",(TS,TSRosWType),(ts,rostype));
1538: return(0);
1539: }
1543: /*@C
1544: TSRosWGetType - Get the type of Rosenbrock-W scheme
1546: Logically collective
1548: Input Parameter:
1549: . ts - timestepping context
1551: Output Parameter:
1552: . rostype - type of Rosenbrock-W scheme
1554: Level: intermediate
1556: .seealso: TSRosWGetType()
1557: @*/
1558: PetscErrorCode TSRosWGetType(TS ts,TSRosWType *rostype)
1559: {
1564: PetscUseMethod(ts,"TSRosWGetType_C",(TS,TSRosWType*),(ts,rostype));
1565: return(0);
1566: }
1570: /*@C
1571: TSRosWSetRecomputeJacobian - Set whether to recompute the Jacobian at each stage. The default is to update the Jacobian once per step.
1573: Logically collective
1575: Input Parameter:
1576: + ts - timestepping context
1577: - flg - PETSC_TRUE to recompute the Jacobian at each stage
1579: Level: intermediate
1581: .seealso: TSRosWGetType()
1582: @*/
1583: PetscErrorCode TSRosWSetRecomputeJacobian(TS ts,PetscBool flg)
1584: {
1589: PetscTryMethod(ts,"TSRosWSetRecomputeJacobian_C",(TS,PetscBool),(ts,flg));
1590: return(0);
1591: }
1595: PetscErrorCode TSRosWGetType_RosW(TS ts,TSRosWType *rostype)
1596: {
1597: TS_RosW *ros = (TS_RosW*)ts->data;
1601: if (!ros->tableau) {TSRosWSetType(ts,TSRosWDefault);}
1602: *rostype = ros->tableau->name;
1603: return(0);
1604: }
1608: PetscErrorCode TSRosWSetType_RosW(TS ts,TSRosWType rostype)
1609: {
1610: TS_RosW *ros = (TS_RosW*)ts->data;
1611: PetscErrorCode ierr;
1612: PetscBool match;
1613: RosWTableauLink link;
1616: if (ros->tableau) {
1617: PetscStrcmp(ros->tableau->name,rostype,&match);
1618: if (match) return(0);
1619: }
1620: for (link = RosWTableauList; link; link=link->next) {
1621: PetscStrcmp(link->tab.name,rostype,&match);
1622: if (match) {
1623: TSReset_RosW(ts);
1624: ros->tableau = &link->tab;
1625: return(0);
1626: }
1627: }
1628: SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_UNKNOWN_TYPE,"Could not find '%s'",rostype);
1629: return(0);
1630: }
1634: PetscErrorCode TSRosWSetRecomputeJacobian_RosW(TS ts,PetscBool flg)
1635: {
1636: TS_RosW *ros = (TS_RosW*)ts->data;
1639: ros->recompute_jacobian = flg;
1640: return(0);
1641: }
1644: /* ------------------------------------------------------------ */
1645: /*MC
1646: TSROSW - ODE solver using Rosenbrock-W schemes
1648: These methods are intended for problems with well-separated time scales, especially when a slow scale is strongly
1649: nonlinear such that it is expensive to solve with a fully implicit method. The user should provide the stiff part
1650: of the equation using TSSetIFunction() and the non-stiff part with TSSetRHSFunction().
1652: Notes:
1653: This method currently only works with autonomous ODE and DAE.
1655: Consider trying TSARKIMEX if the stiff part is strongly nonlinear.
1657: Developer notes:
1658: Rosenbrock-W methods are typically specified for autonomous ODE
1660: $ udot = f(u)
1662: by the stage equations
1664: $ k_i = h f(u_0 + sum_j alpha_ij k_j) + h J sum_j gamma_ij k_j
1666: and step completion formula
1668: $ u_1 = u_0 + sum_j b_j k_j
1670: with step size h and coefficients alpha_ij, gamma_ij, and b_i. Implementing the method in this form would require f(u)
1671: and the Jacobian J to be available, in addition to the shifted matrix I - h gamma_ii J. Following Hairer and Wanner,
1672: we define new variables for the stage equations
1674: $ y_i = gamma_ij k_j
1676: The k_j can be recovered because Gamma is invertible. Let C be the lower triangular part of Gamma^{-1} and define
1678: $ A = Alpha Gamma^{-1}, bt^T = b^T Gamma^{-1}
1680: to rewrite the method as
1682: $ [M/(h gamma_ii) - J] y_i = f(u_0 + sum_j a_ij y_j) + M sum_j (c_ij/h) y_j
1683: $ u_1 = u_0 + sum_j bt_j y_j
1685: where we have introduced the mass matrix M. Continue by defining
1687: $ ydot_i = 1/(h gamma_ii) y_i - sum_j (c_ij/h) y_j
1689: or, more compactly in tensor notation
1691: $ Ydot = 1/h (Gamma^{-1} \otimes I) Y .
1693: Note that Gamma^{-1} is lower triangular. With this definition of Ydot in terms of known quantities and the current
1694: stage y_i, the stage equations reduce to performing one Newton step (typically with a lagged Jacobian) on the
1695: equation
1697: $ g(u_0 + sum_j a_ij y_j + y_i, ydot_i) = 0
1699: with initial guess y_i = 0.
1701: Level: beginner
1703: .seealso: TSCreate(), TS, TSSetType(), TSRosWSetType(), TSRosWRegister(), TSROSWTHETA1, TSROSWTHETA2, TSROSW2M, TSROSW2P, TSROSWRA3PW, TSROSWRA34PW2, TSROSWRODAS3,
1704: TSROSWSANDU3, TSROSWASSP3P3S1C, TSROSWLASSP3P4S2C, TSROSWLLSSP3P4S2C, TSROSWGRK4T, TSROSWSHAMP4, TSROSWVELDD4, TSROSW4L
1705: M*/
1708: PETSC_EXTERN PetscErrorCode TSCreate_RosW(TS ts)
1709: {
1710: TS_RosW *ros;
1714: TSRosWInitializePackage();
1716: ts->ops->reset = TSReset_RosW;
1717: ts->ops->destroy = TSDestroy_RosW;
1718: ts->ops->view = TSView_RosW;
1719: ts->ops->load = TSLoad_RosW;
1720: ts->ops->setup = TSSetUp_RosW;
1721: ts->ops->step = TSStep_RosW;
1722: ts->ops->interpolate = TSInterpolate_RosW;
1723: ts->ops->evaluatestep = TSEvaluateStep_RosW;
1724: ts->ops->rollback = TSRollBack_RosW;
1725: ts->ops->setfromoptions = TSSetFromOptions_RosW;
1726: ts->ops->snesfunction = SNESTSFormFunction_RosW;
1727: ts->ops->snesjacobian = SNESTSFormJacobian_RosW;
1729: PetscNewLog(ts,&ros);
1730: ts->data = (void*)ros;
1732: PetscObjectComposeFunction((PetscObject)ts,"TSRosWGetType_C",TSRosWGetType_RosW);
1733: PetscObjectComposeFunction((PetscObject)ts,"TSRosWSetType_C",TSRosWSetType_RosW);
1734: PetscObjectComposeFunction((PetscObject)ts,"TSRosWSetRecomputeJacobian_C",TSRosWSetRecomputeJacobian_RosW);
1735: return(0);
1736: }