xref: /petsc/src/ts/impls/rosw/rosw.c (revision fb8e56e08d4d0bfe9fc63603ca1f7fddd68abbdb)
1 /*
2   Code for timestepping with Rosenbrock W methods
3 
4   Notes:
5   The general system is written as
6 
7   F(t,U,Udot) = G(t,U)
8 
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.
11 
12 */
13 #include <petsc-private/tsimpl.h>                /*I   "petscts.h"   I*/
14 #include <petscdm.h>
15 
16 #include <petsc-private/kernels/blockinvert.h>
17 
18 static TSRosWType TSRosWDefault = TSROSWRA34PW2;
19 static PetscBool  TSRosWRegisterAllCalled;
20 static PetscBool  TSRosWPackageInitialized;
21 
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;
49 
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;
65 
66 /*MC
67      TSROSWTHETA1 - One stage first order L-stable Rosenbrock-W scheme (aka theta method).
68 
69      Only an approximate Jacobian is needed.
70 
71      Level: intermediate
72 
73 .seealso: TSROSW
74 M*/
75 
76 /*MC
77      TSROSWTHETA2 - One stage second order A-stable Rosenbrock-W scheme (aka theta method).
78 
79      Only an approximate Jacobian is needed.
80 
81      Level: intermediate
82 
83 .seealso: TSROSW
84 M*/
85 
86 /*MC
87      TSROSW2M - Two stage second order L-stable Rosenbrock-W scheme.
88 
89      Only an approximate Jacobian is needed. By default, it is only recomputed once per step. This method is a reflection of TSROSW2P.
90 
91      Level: intermediate
92 
93 .seealso: TSROSW
94 M*/
95 
96 /*MC
97      TSROSW2P - Two stage second order L-stable Rosenbrock-W scheme.
98 
99      Only an approximate Jacobian is needed. By default, it is only recomputed once per step. This method is a reflection of TSROSW2M.
100 
101      Level: intermediate
102 
103 .seealso: TSROSW
104 M*/
105 
106 /*MC
107      TSROSWRA3PW - Three stage third order Rosenbrock-W scheme for PDAE of index 1.
108 
109      Only an approximate Jacobian is needed. By default, it is only recomputed once per step.
110 
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.
112 
113      References:
114      Rang and Angermann, New Rosenbrock-W methods of order 3 for partial differential algebraic equations of index 1, 2005.
115 
116      Level: intermediate
117 
118 .seealso: TSROSW
119 M*/
120 
121 /*MC
122      TSROSWRA34PW2 - Four stage third order L-stable Rosenbrock-W scheme for PDAE of index 1.
123 
124      Only an approximate Jacobian is needed. By default, it is only recomputed once per step.
125 
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.
127 
128      References:
129      Rang and Angermann, New Rosenbrock-W methods of order 3 for partial differential algebraic equations of index 1, 2005.
130 
131      Level: intermediate
132 
133 .seealso: TSROSW
134 M*/
135 
136 /*MC
137      TSROSWRODAS3 - Four stage third order L-stable Rosenbrock scheme
138 
139      By default, the Jacobian is only recomputed once per step.
140 
141      Both the third order and embedded second order methods are stiffly accurate and L-stable.
142 
143      References:
144      Sandu et al, Benchmarking stiff ODE solvers for atmospheric chemistry problems II, Rosenbrock solvers, 1997.
145 
146      Level: intermediate
147 
148 .seealso: TSROSW, TSROSWSANDU3
149 M*/
150 
151 /*MC
152      TSROSWSANDU3 - Three stage third order L-stable Rosenbrock scheme
153 
154      By default, the Jacobian is only recomputed once per step.
155 
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.
160 
161      References:
162      Sandu et al, Benchmarking stiff ODE solvers for atmospheric chemistry problems II, Rosenbrock solvers, 1997.
163 
164      Level: intermediate
165 
166 .seealso: TSROSW, TSROSWRODAS3
167 M*/
168 
169 /*MC
170      TSROSWASSP3P3S1C - A-stable Rosenbrock-W method with SSP explicit part, third order, three stages
171 
172      By default, the Jacobian is only recomputed once per step.
173 
174      A-stable SPP explicit order 3, 3 stages, CFL 1 (eff = 1/3)
175 
176      References:
177      Emil Constantinescu
178 
179      Level: intermediate
180 
181 .seealso: TSROSW, TSROSWLASSP3P4S2C, TSROSWLLSSP3P4S2C, SSP
182 M*/
183 
184 /*MC
185      TSROSWLASSP3P4S2C - L-stable Rosenbrock-W method with SSP explicit part, third order, four stages
186 
187      By default, the Jacobian is only recomputed once per step.
188 
189      L-stable (A-stable embedded) SPP explicit order 3, 4 stages, CFL 2 (eff = 1/2)
190 
191      References:
192      Emil Constantinescu
193 
194      Level: intermediate
195 
196 .seealso: TSROSW, TSROSWASSP3P3S1C, TSROSWLLSSP3P4S2C, TSSSP
197 M*/
198 
199 /*MC
200      TSROSWLLSSP3P4S2C - L-stable Rosenbrock-W method with SSP explicit part, third order, four stages
201 
202      By default, the Jacobian is only recomputed once per step.
203 
204      L-stable (L-stable embedded) SPP explicit order 3, 4 stages, CFL 2 (eff = 1/2)
205 
206      References:
207      Emil Constantinescu
208 
209      Level: intermediate
210 
211 .seealso: TSROSW, TSROSWASSP3P3S1C, TSROSWLASSP3P4S2C, TSSSP
212 M*/
213 
214 /*MC
215      TSROSWGRK4T - four stage, fourth order Rosenbrock (not W) method from Kaps and Rentrop
216 
217      By default, the Jacobian is only recomputed once per step.
218 
219      A(89.3 degrees)-stable, |R(infty)| = 0.454.
220 
221      This method does not provide a dense output formula.
222 
223      References:
224      Kaps and Rentrop, Generalized Runge-Kutta methods of order four with stepsize control for stiff ordinary differential equations, 1979.
225 
226      Hairer and Wanner, Solving Ordinary Differential Equations II, Section 4 Table 7.2.
227 
228      Hairer's code ros4.f
229 
230      Level: intermediate
231 
232 .seealso: TSROSW, TSROSWSHAMP4, TSROSWVELDD4, TSROSW4L
233 M*/
234 
235 /*MC
236      TSROSWSHAMP4 - four stage, fourth order Rosenbrock (not W) method from Shampine
237 
238      By default, the Jacobian is only recomputed once per step.
239 
240      A-stable, |R(infty)| = 1/3.
241 
242      This method does not provide a dense output formula.
243 
244      References:
245      Shampine, Implementation of Rosenbrock methods, 1982.
246 
247      Hairer and Wanner, Solving Ordinary Differential Equations II, Section 4 Table 7.2.
248 
249      Hairer's code ros4.f
250 
251      Level: intermediate
252 
253 .seealso: TSROSW, TSROSWGRK4T, TSROSWVELDD4, TSROSW4L
254 M*/
255 
256 /*MC
257      TSROSWVELDD4 - four stage, fourth order Rosenbrock (not W) method from van Veldhuizen
258 
259      By default, the Jacobian is only recomputed once per step.
260 
261      A(89.5 degrees)-stable, |R(infty)| = 0.24.
262 
263      This method does not provide a dense output formula.
264 
265      References:
266      van Veldhuizen, D-stability and Kaps-Rentrop methods, 1984.
267 
268      Hairer and Wanner, Solving Ordinary Differential Equations II, Section 4 Table 7.2.
269 
270      Hairer's code ros4.f
271 
272      Level: intermediate
273 
274 .seealso: TSROSW, TSROSWGRK4T, TSROSWSHAMP4, TSROSW4L
275 M*/
276 
277 /*MC
278      TSROSW4L - four stage, fourth order Rosenbrock (not W) method
279 
280      By default, the Jacobian is only recomputed once per step.
281 
282      A-stable and L-stable
283 
284      This method does not provide a dense output formula.
285 
286      References:
287      Hairer and Wanner, Solving Ordinary Differential Equations II, Section 4 Table 7.2.
288 
289      Hairer's code ros4.f
290 
291      Level: intermediate
292 
293 .seealso: TSROSW, TSROSWGRK4T, TSROSWSHAMP4, TSROSW4L
294 M*/
295 
296 #undef __FUNCT__
297 #define __FUNCT__ "TSRosWRegisterAll"
298 /*@C
299   TSRosWRegisterAll - Registers all of the additive Runge-Kutta implicit-explicit methods in TSRosW
300 
301   Not Collective, but should be called by all processes which will need the schemes to be registered
302 
303   Level: advanced
304 
305 .keywords: TS, TSRosW, register, all
306 
307 .seealso:  TSRosWRegisterDestroy()
308 @*/
309 PetscErrorCode TSRosWRegisterAll(void)
310 {
311   PetscErrorCode ierr;
312 
313   PetscFunctionBegin;
314   if (TSRosWRegisterAllCalled) PetscFunctionReturn(0);
315   TSRosWRegisterAllCalled = PETSC_TRUE;
316 
317   {
318     const PetscReal A = 0;
319     const PetscReal Gamma = 1;
320     const PetscReal b = 1;
321     const PetscReal binterpt=1;
322 
323     ierr = TSRosWRegister(TSROSWTHETA1,1,1,&A,&Gamma,&b,NULL,1,&binterpt);CHKERRQ(ierr);
324   }
325 
326   {
327     const PetscReal A = 0;
328     const PetscReal Gamma = 0.5;
329     const PetscReal b = 1;
330     const PetscReal binterpt=1;
331 
332     ierr = TSRosWRegister(TSROSWTHETA2,2,1,&A,&Gamma,&b,NULL,1,&binterpt);CHKERRQ(ierr);
333   }
334 
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;
347 
348     ierr = TSRosWRegister(TSROSW2P,2,2,&A[0][0],&Gamma[0][0],b,b1,2,&binterpt[0][0]);CHKERRQ(ierr);
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;
362 
363     ierr = TSRosWRegister(TSROSW2M,2,2,&A[0][0],&Gamma[0][0],b,b1,2,&binterpt[0][0]);CHKERRQ(ierr);
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};
377 
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;
384 
385       ierr = TSRosWRegister(TSROSWRA3PW,3,3,&A[0][0],&Gamma[0][0],b,b2,2,&binterpt[0][0]);CHKERRQ(ierr);
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};
401 
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;
414 
415     ierr = TSRosWRegister(TSROSWRA34PW2,3,4,&A[0][0],&Gamma[0][0],b,b2,3,&binterpt[0][0]);CHKERRQ(ierr);
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};
430 
431     ierr = TSRosWRegister(TSROSWRODAS3,3,4,&A[0][0],&Gamma[0][0],b,b2,0,NULL);CHKERRQ(ierr);
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};
444 
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;
452 
453     ierr = TSRosWRegister(TSROSWSANDU3,3,3,&A[0][0],&Gamma[0][0],b,b2,2,&binterpt[0][0]);CHKERRQ(ierr);
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];
470 
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;
477 
478     ierr = TSRosWRegister(TSROSWASSP3P3S1C,3,3,&A[0][0],&Gamma[0][0],b,b2,2,&binterpt[0][0]);CHKERRQ(ierr);
479   }
480 
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];
494 
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.;
507 
508     ierr = TSRosWRegister(TSROSWLASSP3P4S2C,3,4,&A[0][0],&Gamma[0][0],b,b2,3,&binterpt[0][0]);CHKERRQ(ierr);
509   }
510 
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];
524 
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;
537 
538     ierr = TSRosWRegister(TSROSWLLSSP3P4S2C,3,4,&A[0][0],&Gamma[0][0],b,b2,3,&binterpt[0][0]);CHKERRQ(ierr);
539   }
540 
541   {
542     PetscReal A[4][4],Gamma[4][4],b[4],b2[4];
543     PetscReal binterpt[4][3];
544 
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;
558 
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;
569 
570     b[0]=0.1876410243467238251612921333138006734899663569186926;
571     b[1]=-0.5952974735769549480478230473706443582188442040780541;
572     b[2]=0.9717899277217721234705114616271378792182450260943198;
573     b[3]=0.4358665215084589994160194475295062513822671686978816;
574 
575     b2[0]=0.2147402862233891404862383521089097657790734483804460;
576     b2[1]=-0.4851622638849390928209050538171743017757490232519684;
577     b2[2]=0.8687250025203875511662123688667549217531982787600080;
578     b2[3]=0.4016969751411624011684543450940068201770721128357014;
579 
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;
592 
593     ierr = TSRosWRegister(TSROSWARK3,3,4,&A[0][0],&Gamma[0][0],b,b2,3,&binterpt[0][0]);CHKERRQ(ierr);
594   }
595   ierr = TSRosWRegisterRos4(TSROSWGRK4T,0.231,PETSC_DEFAULT,PETSC_DEFAULT,0,-0.1282612945269037e+01);CHKERRQ(ierr);
596   ierr = TSRosWRegisterRos4(TSROSWSHAMP4,0.5,PETSC_DEFAULT,PETSC_DEFAULT,0,125./108.);CHKERRQ(ierr);
597   ierr = TSRosWRegisterRos4(TSROSWVELDD4,0.22570811482256823492,PETSC_DEFAULT,PETSC_DEFAULT,0,-1.355958941201148);CHKERRQ(ierr);
598   ierr = TSRosWRegisterRos4(TSROSW4L,0.57282,PETSC_DEFAULT,PETSC_DEFAULT,0,-1.093502252409163);CHKERRQ(ierr);
599   PetscFunctionReturn(0);
600 }
601 
602 
603 
604 #undef __FUNCT__
605 #define __FUNCT__ "TSRosWRegisterDestroy"
606 /*@C
607    TSRosWRegisterDestroy - Frees the list of schemes that were registered by TSRosWRegister().
608 
609    Not Collective
610 
611    Level: advanced
612 
613 .keywords: TSRosW, register, destroy
614 .seealso: TSRosWRegister(), TSRosWRegisterAll()
615 @*/
616 PetscErrorCode TSRosWRegisterDestroy(void)
617 {
618   PetscErrorCode  ierr;
619   RosWTableauLink link;
620 
621   PetscFunctionBegin;
622   while ((link = RosWTableauList)) {
623     RosWTableau t = &link->tab;
624     RosWTableauList = link->next;
625     ierr = PetscFree5(t->A,t->Gamma,t->b,t->ASum,t->GammaSum);CHKERRQ(ierr);
626     ierr = PetscFree5(t->At,t->bt,t->GammaInv,t->GammaZeroDiag,t->GammaExplicitCorr);CHKERRQ(ierr);
627     ierr = PetscFree2(t->bembed,t->bembedt);CHKERRQ(ierr);
628     ierr = PetscFree(t->binterpt);CHKERRQ(ierr);
629     ierr = PetscFree(t->name);CHKERRQ(ierr);
630     ierr = PetscFree(link);CHKERRQ(ierr);
631   }
632   TSRosWRegisterAllCalled = PETSC_FALSE;
633   PetscFunctionReturn(0);
634 }
635 
636 #undef __FUNCT__
637 #define __FUNCT__ "TSRosWInitializePackage"
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.
642 
643   Level: developer
644 
645 .keywords: TS, TSRosW, initialize, package
646 .seealso: PetscInitialize()
647 @*/
648 PetscErrorCode TSRosWInitializePackage(void)
649 {
650   PetscErrorCode ierr;
651 
652   PetscFunctionBegin;
653   if (TSRosWPackageInitialized) PetscFunctionReturn(0);
654   TSRosWPackageInitialized = PETSC_TRUE;
655   ierr = TSRosWRegisterAll();CHKERRQ(ierr);
656   ierr = PetscRegisterFinalize(TSRosWFinalizePackage);CHKERRQ(ierr);
657   PetscFunctionReturn(0);
658 }
659 
660 #undef __FUNCT__
661 #define __FUNCT__ "TSRosWFinalizePackage"
662 /*@C
663   TSRosWFinalizePackage - This function destroys everything in the TSRosW package. It is
664   called from PetscFinalize().
665 
666   Level: developer
667 
668 .keywords: Petsc, destroy, package
669 .seealso: PetscFinalize()
670 @*/
671 PetscErrorCode TSRosWFinalizePackage(void)
672 {
673   PetscErrorCode ierr;
674 
675   PetscFunctionBegin;
676   TSRosWPackageInitialized = PETSC_FALSE;
677   ierr = TSRosWRegisterDestroy();CHKERRQ(ierr);
678   PetscFunctionReturn(0);
679 }
680 
681 #undef __FUNCT__
682 #define __FUNCT__ "TSRosWRegister"
683 /*@C
684    TSRosWRegister - register a Rosenbrock W scheme by providing the entries in the Butcher tableau and optionally embedded approximations and interpolation
685 
686    Not Collective, but the same schemes should be registered on all processes on which they will be used
687 
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)
698 
699    Notes:
700    Several Rosenbrock W methods are provided, this function is only needed to create new methods.
701 
702    Level: advanced
703 
704 .keywords: TS, register
705 
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;
716 
717   PetscFunctionBegin;
718   PetscValidCharPointer(name,1);
719   PetscValidPointer(A,4);
720   PetscValidPointer(Gamma,5);
721   PetscValidPointer(b,6);
722   if (bembed) PetscValidPointer(bembed,7);
723 
724   ierr     = PetscMalloc(sizeof(*link),&link);CHKERRQ(ierr);
725   ierr     = PetscMemzero(link,sizeof(*link));CHKERRQ(ierr);
726   t        = &link->tab;
727   ierr     = PetscStrallocpy(name,&t->name);CHKERRQ(ierr);
728   t->order = order;
729   t->s     = s;
730   ierr     = PetscMalloc5(s*s,PetscReal,&t->A,s*s,PetscReal,&t->Gamma,s,PetscReal,&t->b,s,PetscReal,&t->ASum,s,PetscReal,&t->GammaSum);CHKERRQ(ierr);
731   ierr     = PetscMalloc5(s*s,PetscReal,&t->At,s,PetscReal,&t->bt,s*s,PetscReal,&t->GammaInv,s,PetscBool,&t->GammaZeroDiag,s*s,PetscReal,&t->GammaExplicitCorr);CHKERRQ(ierr);
732   ierr     = PetscMemcpy(t->A,A,s*s*sizeof(A[0]));CHKERRQ(ierr);
733   ierr     = PetscMemcpy(t->Gamma,Gamma,s*s*sizeof(Gamma[0]));CHKERRQ(ierr);
734   ierr     = PetscMemcpy(t->GammaExplicitCorr,Gamma,s*s*sizeof(Gamma[0]));CHKERRQ(ierr);
735   ierr     = PetscMemcpy(t->b,b,s*sizeof(b[0]));CHKERRQ(ierr);
736   if (bembed) {
737     ierr = PetscMalloc2(s,PetscReal,&t->bembed,s,PetscReal,&t->bembedt);CHKERRQ(ierr);
738     ierr = PetscMemcpy(t->bembed,bembed,s*sizeof(bembed[0]));CHKERRQ(ierr);
739   }
740   for (i=0; i<s; i++) {
741     t->ASum[i]     = 0;
742     t->GammaSum[i] = 0;
743     for (j=0; j<s; j++) {
744       t->ASum[i]     += A[i*s+j];
745       t->GammaSum[i] += Gamma[i*s+j];
746     }
747   }
748   ierr = PetscMalloc(s*s*sizeof(PetscScalar),&GammaInv);CHKERRQ(ierr); /* Need to use Scalar for inverse, then convert back to Real */
749   for (i=0; i<s*s; i++) GammaInv[i] = Gamma[i];
750   for (i=0; i<s; i++) {
751     if (Gamma[i*s+i] == 0.0) {
752       GammaInv[i*s+i] = 1.0;
753       t->GammaZeroDiag[i] = PETSC_TRUE;
754     } else {
755       t->GammaZeroDiag[i] = PETSC_FALSE;
756     }
757   }
758 
759   switch (s) {
760   case 1: GammaInv[0] = 1./GammaInv[0]; break;
761   case 2: ierr = PetscKernel_A_gets_inverse_A_2(GammaInv,0);CHKERRQ(ierr); break;
762   case 3: ierr = PetscKernel_A_gets_inverse_A_3(GammaInv,0);CHKERRQ(ierr); break;
763   case 4: ierr = PetscKernel_A_gets_inverse_A_4(GammaInv,0);CHKERRQ(ierr); break;
764   case 5: {
765     PetscInt  ipvt5[5];
766     MatScalar work5[5*5];
767     ierr = PetscKernel_A_gets_inverse_A_5(GammaInv,ipvt5,work5,0);CHKERRQ(ierr); break;
768   }
769   case 6: ierr = PetscKernel_A_gets_inverse_A_6(GammaInv,0);CHKERRQ(ierr); break;
770   case 7: ierr = PetscKernel_A_gets_inverse_A_7(GammaInv,0);CHKERRQ(ierr); break;
771   default: SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not implemented for %D stages",s);
772   }
773   for (i=0; i<s*s; i++) t->GammaInv[i] = PetscRealPart(GammaInv[i]);
774   ierr = PetscFree(GammaInv);CHKERRQ(ierr);
775 
776   for (i=0; i<s; i++) {
777     for (k=0; k<i+1; k++) {
778       t->GammaExplicitCorr[i*s+k]=(t->GammaExplicitCorr[i*s+k])*(t->GammaInv[k*s+k]);
779       for (j=k+1; j<i+1; j++) {
780         t->GammaExplicitCorr[i*s+k]+=(t->GammaExplicitCorr[i*s+j])*(t->GammaInv[j*s+k]);
781       }
782     }
783   }
784 
785   for (i=0; i<s; i++) {
786     for (j=0; j<s; j++) {
787       t->At[i*s+j] = 0;
788       for (k=0; k<s; k++) {
789         t->At[i*s+j] += t->A[i*s+k] * t->GammaInv[k*s+j];
790       }
791     }
792     t->bt[i] = 0;
793     for (j=0; j<s; j++) {
794       t->bt[i] += t->b[j] * t->GammaInv[j*s+i];
795     }
796     if (bembed) {
797       t->bembedt[i] = 0;
798       for (j=0; j<s; j++) {
799         t->bembedt[i] += t->bembed[j] * t->GammaInv[j*s+i];
800       }
801     }
802   }
803   t->ccfl = 1.0;                /* Fix this */
804 
805   t->pinterp = pinterp;
806   ierr = PetscMalloc(s*pinterp*sizeof(binterpt[0]),&t->binterpt);CHKERRQ(ierr);
807   ierr = PetscMemcpy(t->binterpt,binterpt,s*pinterp*sizeof(binterpt[0]));CHKERRQ(ierr);
808   link->next = RosWTableauList;
809   RosWTableauList = link;
810   PetscFunctionReturn(0);
811 }
812 
813 #undef __FUNCT__
814 #define __FUNCT__ "TSRosWRegisterRos4"
815 /*@C
816    TSRosWRegisterRos4 - register a fourth order Rosenbrock scheme by providing paramter choices
817 
818    Not Collective, but the same schemes should be registered on all processes on which they will be used
819 
820    Input Parameters:
821 +  name - identifier for method
822 .  gamma - leading coefficient (diagonal entry)
823 .  a2 - design parameter, see Table 7.2 of Hairer&Wanner
824 .  a3 - design parameter or PETSC_DEFAULT to satisfy one of the order five conditions (Eq 7.22)
825 .  b3 - design parameter, see Table 7.2 of Hairer&Wanner
826 .  beta43 - design parameter or PETSC_DEFAULT to use Equation 7.21 of Hairer&Wanner
827 .  e4 - design parameter for embedded method, see coefficient E4 in ros4.f code from Hairer
828 
829    Notes:
830    This routine encodes the design of fourth order Rosenbrock methods as described in Hairer and Wanner volume 2.
831    It is used here to implement several methods from the book and can be used to experiment with new methods.
832    It was written this way instead of by copying coefficients in order to provide better than double precision satisfaction of the order conditions.
833 
834    Level: developer
835 
836 .keywords: TS, register
837 
838 .seealso: TSRosW, TSRosWRegister()
839 @*/
840 PetscErrorCode TSRosWRegisterRos4(TSRosWType name,PetscReal gamma,PetscReal a2,PetscReal a3,PetscReal b3,PetscReal e4)
841 {
842   PetscErrorCode ierr;
843   /* Declare numeric constants so they can be quad precision without being truncated at double */
844   const PetscReal one = 1,two = 2,three = 3,four = 4,five = 5,six = 6,eight = 8,twelve = 12,twenty = 20,twentyfour = 24,
845     p32 = one/six - gamma + gamma*gamma,
846     p42 = one/eight - gamma/three,
847     p43 = one/twelve - gamma/three,
848     p44 = one/twentyfour - gamma/two + three/two*gamma*gamma - gamma*gamma*gamma,
849     p56 = one/twenty - gamma/four;
850   PetscReal   a4,a32,a42,a43,b1,b2,b4,beta2p,beta3p,beta4p,beta32,beta42,beta43,beta32beta2p,beta4jbetajp;
851   PetscReal   A[4][4],Gamma[4][4],b[4],bm[4];
852   PetscScalar M[3][3],rhs[3];
853 
854   PetscFunctionBegin;
855   /* Step 1: choose Gamma (input) */
856   /* Step 2: choose a2,a3,a4; b1,b2,b3,b4 to satisfy order conditions */
857   if (a3 == PETSC_DEFAULT) a3 = (one/five - a2/four)/(one/four - a2/three); /* Eq 7.22 */
858   a4 = a3;                                                  /* consequence of 7.20 */
859 
860   /* Solve order conditions 7.15a, 7.15c, 7.15e */
861   M[0][0] = one; M[0][1] = one;      M[0][2] = one;      /* 7.15a */
862   M[1][0] = 0.0; M[1][1] = a2*a2;    M[1][2] = a4*a4;    /* 7.15c */
863   M[2][0] = 0.0; M[2][1] = a2*a2*a2; M[2][2] = a4*a4*a4; /* 7.15e */
864   rhs[0]  = one - b3;
865   rhs[1]  = one/three - a3*a3*b3;
866   rhs[2]  = one/four - a3*a3*a3*b3;
867   ierr    = PetscKernel_A_gets_inverse_A_3(&M[0][0],0);CHKERRQ(ierr);
868   b1      = PetscRealPart(M[0][0]*rhs[0] + M[0][1]*rhs[1] + M[0][2]*rhs[2]);
869   b2      = PetscRealPart(M[1][0]*rhs[0] + M[1][1]*rhs[1] + M[1][2]*rhs[2]);
870   b4      = PetscRealPart(M[2][0]*rhs[0] + M[2][1]*rhs[1] + M[2][2]*rhs[2]);
871 
872   /* Step 3 */
873   beta43       = (p56 - a2*p43) / (b4*a3*a3*(a3 - a2)); /* 7.21 */
874   beta32beta2p =  p44 / (b4*beta43);                    /* 7.15h */
875   beta4jbetajp = (p32 - b3*beta32beta2p) / b4;
876   M[0][0]      = b2;                                    M[0][1] = b3;                 M[0][2] = b4;
877   M[1][0]      = a4*a4*beta32beta2p-a3*a3*beta4jbetajp; M[1][1] = a2*a2*beta4jbetajp; M[1][2] = -a2*a2*beta32beta2p;
878   M[2][0]      = b4*beta43*a3*a3-p43;                   M[2][1] = -b4*beta43*a2*a2;   M[2][2] = 0;
879   rhs[0]       = one/two - gamma; rhs[1] = 0; rhs[2] = -a2*a2*p32;
880   ierr         = PetscKernel_A_gets_inverse_A_3(&M[0][0],0);CHKERRQ(ierr);
881   beta2p       = PetscRealPart(M[0][0]*rhs[0] + M[0][1]*rhs[1] + M[0][2]*rhs[2]);
882   beta3p       = PetscRealPart(M[1][0]*rhs[0] + M[1][1]*rhs[1] + M[1][2]*rhs[2]);
883   beta4p       = PetscRealPart(M[2][0]*rhs[0] + M[2][1]*rhs[1] + M[2][2]*rhs[2]);
884 
885   /* Step 4: back-substitute */
886   beta32 = beta32beta2p / beta2p;
887   beta42 = (beta4jbetajp - beta43*beta3p) / beta2p;
888 
889   /* Step 5: 7.15f and 7.20, then 7.16 */
890   a43 = 0;
891   a32 = p42 / (b3*a3*beta2p + b4*a4*beta2p);
892   a42 = a32;
893 
894   A[0][0]     = 0;          A[0][1] = 0;   A[0][2] = 0;   A[0][3] = 0;
895   A[1][0]     = a2;         A[1][1] = 0;   A[1][2] = 0;   A[1][3] = 0;
896   A[2][0]     = a3-a32;     A[2][1] = a32; A[2][2] = 0;   A[2][3] = 0;
897   A[3][0]     = a4-a43-a42; A[3][1] = a42; A[3][2] = a43; A[3][3] = 0;
898   Gamma[0][0] = gamma;                        Gamma[0][1] = 0;              Gamma[0][2] = 0;              Gamma[0][3] = 0;
899   Gamma[1][0] = beta2p-A[1][0];               Gamma[1][1] = gamma;          Gamma[1][2] = 0;              Gamma[1][3] = 0;
900   Gamma[2][0] = beta3p-beta32-A[2][0];        Gamma[2][1] = beta32-A[2][1]; Gamma[2][2] = gamma;          Gamma[2][3] = 0;
901   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;
902   b[0] = b1; b[1] = b2; b[2] = b3; b[3] = b4;
903 
904   /* Construct embedded formula using given e4. We are solving Equation 7.18. */
905   bm[3] = b[3] - e4*gamma;                                          /* using definition of E4 */
906   bm[2] = (p32 - beta4jbetajp*bm[3]) / (beta32*beta2p);             /* fourth row of 7.18 */
907   bm[1] = (one/two - gamma - beta3p*bm[2] - beta4p*bm[3]) / beta2p; /* second row */
908   bm[0] = one - bm[1] - bm[2] - bm[3];                              /* first row */
909 
910   {
911     const PetscReal misfit = a2*a2*bm[1] + a3*a3*bm[2] + a4*a4*bm[3] - one/three;
912     if (PetscAbs(misfit) > PETSC_SMALL) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Assumptions violated, could not construct a third order embedded method");
913   }
914   ierr = TSRosWRegister(name,4,4,&A[0][0],&Gamma[0][0],b,bm,0,NULL);CHKERRQ(ierr);
915   PetscFunctionReturn(0);
916 }
917 
918 #undef __FUNCT__
919 #define __FUNCT__ "TSEvaluateStep_RosW"
920 /*
921  The step completion formula is
922 
923  x1 = x0 + b^T Y
924 
925  where Y is the multi-vector of stages corrections. This function can be called before or after ts->vec_sol has been
926  updated. Suppose we have a completion formula b and an embedded formula be of different order. We can write
927 
928  x1e = x0 + be^T Y
929      = x1 - b^T Y + be^T Y
930      = x1 + (be - b)^T Y
931 
932  so we can evaluate the method of different order even after the step has been optimistically completed.
933 */
934 static PetscErrorCode TSEvaluateStep_RosW(TS ts,PetscInt order,Vec U,PetscBool *done)
935 {
936   TS_RosW        *ros = (TS_RosW*)ts->data;
937   RosWTableau    tab  = ros->tableau;
938   PetscScalar    *w   = ros->work;
939   PetscInt       i;
940   PetscErrorCode ierr;
941 
942   PetscFunctionBegin;
943   if (order == tab->order) {
944     if (ros->status == TS_STEP_INCOMPLETE) { /* Use standard completion formula */
945       ierr = VecCopy(ts->vec_sol,U);CHKERRQ(ierr);
946       for (i=0; i<tab->s; i++) w[i] = tab->bt[i];
947       ierr = VecMAXPY(U,tab->s,w,ros->Y);CHKERRQ(ierr);
948     } else {ierr = VecCopy(ts->vec_sol,U);CHKERRQ(ierr);}
949     if (done) *done = PETSC_TRUE;
950     PetscFunctionReturn(0);
951   } else if (order == tab->order-1) {
952     if (!tab->bembedt) goto unavailable;
953     if (ros->status == TS_STEP_INCOMPLETE) { /* Use embedded completion formula */
954       ierr = VecCopy(ts->vec_sol,U);CHKERRQ(ierr);
955       for (i=0; i<tab->s; i++) w[i] = tab->bembedt[i];
956       ierr = VecMAXPY(U,tab->s,w,ros->Y);CHKERRQ(ierr);
957     } else {                    /* Use rollback-and-recomplete formula (bembedt - bt) */
958       for (i=0; i<tab->s; i++) w[i] = tab->bembedt[i] - tab->bt[i];
959       ierr = VecCopy(ts->vec_sol,U);CHKERRQ(ierr);
960       ierr = VecMAXPY(U,tab->s,w,ros->Y);CHKERRQ(ierr);
961     }
962     if (done) *done = PETSC_TRUE;
963     PetscFunctionReturn(0);
964   }
965   unavailable:
966   if (done) *done = PETSC_FALSE;
967   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);
968   PetscFunctionReturn(0);
969 }
970 
971 #undef __FUNCT__
972 #define __FUNCT__ "TSStep_RosW"
973 static PetscErrorCode TSStep_RosW(TS ts)
974 {
975   TS_RosW         *ros = (TS_RosW*)ts->data;
976   RosWTableau     tab  = ros->tableau;
977   const PetscInt  s    = tab->s;
978   const PetscReal *At  = tab->At,*Gamma = tab->Gamma,*ASum = tab->ASum,*GammaInv = tab->GammaInv;
979   const PetscReal *GammaExplicitCorr = tab->GammaExplicitCorr;
980   const PetscBool *GammaZeroDiag = tab->GammaZeroDiag;
981   PetscScalar     *w   = ros->work;
982   Vec             *Y   = ros->Y,Ydot = ros->Ydot,Zdot = ros->Zdot,Zstage = ros->Zstage;
983   SNES            snes;
984   TSAdapt         adapt;
985   PetscInt        i,j,its,lits,reject,next_scheme;
986   PetscReal       next_time_step;
987   PetscBool       accept;
988   PetscErrorCode  ierr;
989   MatStructure    str;
990 
991   PetscFunctionBegin;
992   ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr);
993   next_time_step = ts->time_step;
994   accept         = PETSC_TRUE;
995   ros->status    = TS_STEP_INCOMPLETE;
996 
997   for (reject=0; reject<ts->max_reject && !ts->reason; reject++,ts->reject++) {
998     const PetscReal h = ts->time_step;
999     ierr = TSPreStep(ts);CHKERRQ(ierr);
1000     ierr = VecCopy(ts->vec_sol,ros->VecSolPrev);CHKERRQ(ierr); /*move this at the end*/
1001     for (i=0; i<s; i++) {
1002       ros->stage_time = ts->ptime + h*ASum[i];
1003       ierr = TSPreStage(ts,ros->stage_time);CHKERRQ(ierr);
1004       if (GammaZeroDiag[i]) {
1005         ros->stage_explicit = PETSC_TRUE;
1006         ros->scoeff         = 1.;
1007       } else {
1008         ros->stage_explicit = PETSC_FALSE;
1009         ros->scoeff         = 1./Gamma[i*s+i];
1010       }
1011 
1012       ierr = VecCopy(ts->vec_sol,Zstage);CHKERRQ(ierr);
1013       for (j=0; j<i; j++) w[j] = At[i*s+j];
1014       ierr = VecMAXPY(Zstage,i,w,Y);CHKERRQ(ierr);
1015 
1016       for (j=0; j<i; j++) w[j] = 1./h * GammaInv[i*s+j];
1017       ierr = VecZeroEntries(Zdot);CHKERRQ(ierr);
1018       ierr = VecMAXPY(Zdot,i,w,Y);CHKERRQ(ierr);
1019 
1020       /* Initial guess taken from last stage */
1021       ierr = VecZeroEntries(Y[i]);CHKERRQ(ierr);
1022 
1023       if (!ros->stage_explicit) {
1024         if (!ros->recompute_jacobian && !i) {
1025           ierr = SNESSetLagJacobian(snes,-2);CHKERRQ(ierr); /* Recompute the Jacobian on this solve, but not again */
1026         }
1027         ierr = SNESSolve(snes,NULL,Y[i]);CHKERRQ(ierr);
1028         ierr = SNESGetIterationNumber(snes,&its);CHKERRQ(ierr);
1029         ierr = SNESGetLinearSolveIterations(snes,&lits);CHKERRQ(ierr);
1030         ts->snes_its += its; ts->ksp_its += lits;
1031         ierr = TSGetAdapt(ts,&adapt);CHKERRQ(ierr);
1032         ierr = TSAdaptCheckStage(adapt,ts,&accept);CHKERRQ(ierr);
1033         if (!accept) goto reject_step;
1034       } else {
1035         Mat J,Jp;
1036         ierr = VecZeroEntries(Ydot);CHKERRQ(ierr); /* Evaluate Y[i]=G(t,Ydot=0,Zstage) */
1037         ierr = TSComputeIFunction(ts,ros->stage_time,Zstage,Ydot,Y[i],PETSC_FALSE);CHKERRQ(ierr);
1038         ierr = VecScale(Y[i],-1.0);CHKERRQ(ierr);
1039         ierr = VecAXPY(Y[i],-1.0,Zdot);CHKERRQ(ierr); /*Y[i]=F(Zstage)-Zdot[=GammaInv*Y]*/
1040 
1041         ierr = VecZeroEntries(Zstage);CHKERRQ(ierr); /* Zstage = GammaExplicitCorr[i,j] * Y[j] */
1042         for (j=0; j<i; j++) w[j] = GammaExplicitCorr[i*s+j];
1043         ierr = VecMAXPY(Zstage,i,w,Y);CHKERRQ(ierr);
1044         /*Y[i] += Y[i] + Jac*Zstage[=Jac*GammaExplicitCorr[i,j] * Y[j]] */
1045         str  = SAME_NONZERO_PATTERN;
1046         ierr = TSGetIJacobian(ts,&J,&Jp,NULL,NULL);CHKERRQ(ierr);
1047         ierr = TSComputeIJacobian(ts,ros->stage_time,ts->vec_sol,Ydot,0,&J,&Jp,&str,PETSC_FALSE);CHKERRQ(ierr);
1048         ierr = MatMult(J,Zstage,Zdot);CHKERRQ(ierr);
1049 
1050         ierr = VecAXPY(Y[i],-1.0,Zdot);CHKERRQ(ierr);
1051         ierr = VecScale(Y[i],h);
1052         ts->ksp_its += 1;
1053       }
1054     }
1055     ierr = TSEvaluateStep(ts,tab->order,ts->vec_sol,NULL);CHKERRQ(ierr);
1056     ros->status = TS_STEP_PENDING;
1057 
1058     /* Register only the current method as a candidate because we're not supporting multiple candidates yet. */
1059     ierr = TSGetAdapt(ts,&adapt);CHKERRQ(ierr);
1060     ierr = TSAdaptCandidatesClear(adapt);CHKERRQ(ierr);
1061     ierr = TSAdaptCandidateAdd(adapt,tab->name,tab->order,1,tab->ccfl,1.*tab->s,PETSC_TRUE);CHKERRQ(ierr);
1062     ierr = TSAdaptChoose(adapt,ts,ts->time_step,&next_scheme,&next_time_step,&accept);CHKERRQ(ierr);
1063     if (accept) {
1064       /* ignore next_scheme for now */
1065       ts->ptime    += ts->time_step;
1066       ts->time_step = next_time_step;
1067       ts->steps++;
1068       ros->status = TS_STEP_COMPLETE;
1069       break;
1070     } else {                    /* Roll back the current step */
1071       for (i=0; i<s; i++) w[i] = -tab->bt[i];
1072       ierr = VecMAXPY(ts->vec_sol,s,w,Y);CHKERRQ(ierr);
1073       ts->time_step = next_time_step;
1074       ros->status   = TS_STEP_INCOMPLETE;
1075     }
1076 reject_step: continue;
1077   }
1078   if (ros->status != TS_STEP_COMPLETE && !ts->reason) ts->reason = TS_DIVERGED_STEP_REJECTED;
1079   PetscFunctionReturn(0);
1080 }
1081 
1082 #undef __FUNCT__
1083 #define __FUNCT__ "TSInterpolate_RosW"
1084 static PetscErrorCode TSInterpolate_RosW(TS ts,PetscReal itime,Vec U)
1085 {
1086   TS_RosW         *ros = (TS_RosW*)ts->data;
1087   PetscInt        s    = ros->tableau->s,pinterp = ros->tableau->pinterp,i,j;
1088   PetscReal       h;
1089   PetscReal       tt,t;
1090   PetscScalar     *bt;
1091   const PetscReal *Bt = ros->tableau->binterpt;
1092   PetscErrorCode  ierr;
1093   const PetscReal *GammaInv = ros->tableau->GammaInv;
1094   PetscScalar     *w        = ros->work;
1095   Vec             *Y        = ros->Y;
1096 
1097   PetscFunctionBegin;
1098   if (!Bt) SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_SUP,"TSRosW %s does not have an interpolation formula",ros->tableau->name);
1099 
1100   switch (ros->status) {
1101   case TS_STEP_INCOMPLETE:
1102   case TS_STEP_PENDING:
1103     h = ts->time_step;
1104     t = (itime - ts->ptime)/h;
1105     break;
1106   case TS_STEP_COMPLETE:
1107     h = ts->time_step_prev;
1108     t = (itime - ts->ptime)/h + 1; /* In the interval [0,1] */
1109     break;
1110   default: SETERRQ(PetscObjectComm((PetscObject)ts),PETSC_ERR_PLIB,"Invalid TSStepStatus");
1111   }
1112   ierr = PetscMalloc(s*sizeof(bt[0]),&bt);CHKERRQ(ierr);
1113   for (i=0; i<s; i++) bt[i] = 0;
1114   for (j=0,tt=t; j<pinterp; j++,tt*=t) {
1115     for (i=0; i<s; i++) {
1116       bt[i] += Bt[i*pinterp+j] * tt;
1117     }
1118   }
1119 
1120   /* y(t+tt*h) = y(t) + Sum bt(tt) * GammaInv * Ydot */
1121   /*U<-0*/
1122   ierr = VecZeroEntries(U);CHKERRQ(ierr);
1123 
1124   /*U<- Sum bt_i * GammaInv(i,1:i) * Y(1:i) */
1125   for (j=0; j<s; j++) w[j]=0;
1126   for (j=0; j<s; j++) {
1127     for (i=j; i<s; i++) {
1128       w[j] +=  bt[i]*GammaInv[i*s+j];
1129     }
1130   }
1131   ierr = VecMAXPY(U,i,w,Y);CHKERRQ(ierr);
1132 
1133   /*X<-y(t) + X*/
1134   ierr = VecAXPY(U,1.0,ros->VecSolPrev);CHKERRQ(ierr);
1135 
1136   ierr = PetscFree(bt);CHKERRQ(ierr);
1137   PetscFunctionReturn(0);
1138 }
1139 
1140 /*------------------------------------------------------------*/
1141 #undef __FUNCT__
1142 #define __FUNCT__ "TSReset_RosW"
1143 static PetscErrorCode TSReset_RosW(TS ts)
1144 {
1145   TS_RosW        *ros = (TS_RosW*)ts->data;
1146   PetscInt       s;
1147   PetscErrorCode ierr;
1148 
1149   PetscFunctionBegin;
1150   if (!ros->tableau) PetscFunctionReturn(0);
1151   s    = ros->tableau->s;
1152   ierr = VecDestroyVecs(s,&ros->Y);CHKERRQ(ierr);
1153   ierr = VecDestroy(&ros->Ydot);CHKERRQ(ierr);
1154   ierr = VecDestroy(&ros->Ystage);CHKERRQ(ierr);
1155   ierr = VecDestroy(&ros->Zdot);CHKERRQ(ierr);
1156   ierr = VecDestroy(&ros->Zstage);CHKERRQ(ierr);
1157   ierr = VecDestroy(&ros->VecSolPrev);CHKERRQ(ierr);
1158   ierr = PetscFree(ros->work);CHKERRQ(ierr);
1159   PetscFunctionReturn(0);
1160 }
1161 
1162 #undef __FUNCT__
1163 #define __FUNCT__ "TSDestroy_RosW"
1164 static PetscErrorCode TSDestroy_RosW(TS ts)
1165 {
1166   PetscErrorCode ierr;
1167 
1168   PetscFunctionBegin;
1169   ierr = TSReset_RosW(ts);CHKERRQ(ierr);
1170   ierr = PetscFree(ts->data);CHKERRQ(ierr);
1171   ierr = PetscObjectComposeFunction((PetscObject)ts,"TSRosWGetType_C",NULL);CHKERRQ(ierr);
1172   ierr = PetscObjectComposeFunction((PetscObject)ts,"TSRosWSetType_C",NULL);CHKERRQ(ierr);
1173   ierr = PetscObjectComposeFunction((PetscObject)ts,"TSRosWSetRecomputeJacobian_C",NULL);CHKERRQ(ierr);
1174   PetscFunctionReturn(0);
1175 }
1176 
1177 
1178 #undef __FUNCT__
1179 #define __FUNCT__ "TSRosWGetVecs"
1180 static PetscErrorCode TSRosWGetVecs(TS ts,DM dm,Vec *Ydot,Vec *Zdot,Vec *Ystage,Vec *Zstage)
1181 {
1182   TS_RosW        *rw = (TS_RosW*)ts->data;
1183   PetscErrorCode ierr;
1184 
1185   PetscFunctionBegin;
1186   if (Ydot) {
1187     if (dm && dm != ts->dm) {
1188       ierr = DMGetNamedGlobalVector(dm,"TSRosW_Ydot",Ydot);CHKERRQ(ierr);
1189     } else *Ydot = rw->Ydot;
1190   }
1191   if (Zdot) {
1192     if (dm && dm != ts->dm) {
1193       ierr = DMGetNamedGlobalVector(dm,"TSRosW_Zdot",Zdot);CHKERRQ(ierr);
1194     } else *Zdot = rw->Zdot;
1195   }
1196   if (Ystage) {
1197     if (dm && dm != ts->dm) {
1198       ierr = DMGetNamedGlobalVector(dm,"TSRosW_Ystage",Ystage);CHKERRQ(ierr);
1199     } else *Ystage = rw->Ystage;
1200   }
1201   if (Zstage) {
1202     if (dm && dm != ts->dm) {
1203       ierr = DMGetNamedGlobalVector(dm,"TSRosW_Zstage",Zstage);CHKERRQ(ierr);
1204     } else *Zstage = rw->Zstage;
1205   }
1206   PetscFunctionReturn(0);
1207 }
1208 
1209 
1210 #undef __FUNCT__
1211 #define __FUNCT__ "TSRosWRestoreVecs"
1212 static PetscErrorCode TSRosWRestoreVecs(TS ts,DM dm,Vec *Ydot,Vec *Zdot, Vec *Ystage, Vec *Zstage)
1213 {
1214   PetscErrorCode ierr;
1215 
1216   PetscFunctionBegin;
1217   if (Ydot) {
1218     if (dm && dm != ts->dm) {
1219       ierr = DMRestoreNamedGlobalVector(dm,"TSRosW_Ydot",Ydot);CHKERRQ(ierr);
1220     }
1221   }
1222   if (Zdot) {
1223     if (dm && dm != ts->dm) {
1224       ierr = DMRestoreNamedGlobalVector(dm,"TSRosW_Zdot",Zdot);CHKERRQ(ierr);
1225     }
1226   }
1227   if (Ystage) {
1228     if (dm && dm != ts->dm) {
1229       ierr = DMRestoreNamedGlobalVector(dm,"TSRosW_Ystage",Ystage);CHKERRQ(ierr);
1230     }
1231   }
1232   if (Zstage) {
1233     if (dm && dm != ts->dm) {
1234       ierr = DMRestoreNamedGlobalVector(dm,"TSRosW_Zstage",Zstage);CHKERRQ(ierr);
1235     }
1236   }
1237   PetscFunctionReturn(0);
1238 }
1239 
1240 #undef __FUNCT__
1241 #define __FUNCT__ "DMCoarsenHook_TSRosW"
1242 static PetscErrorCode DMCoarsenHook_TSRosW(DM fine,DM coarse,void *ctx)
1243 {
1244   PetscFunctionBegin;
1245   PetscFunctionReturn(0);
1246 }
1247 
1248 #undef __FUNCT__
1249 #define __FUNCT__ "DMRestrictHook_TSRosW"
1250 static PetscErrorCode DMRestrictHook_TSRosW(DM fine,Mat restrct,Vec rscale,Mat inject,DM coarse,void *ctx)
1251 {
1252   TS             ts = (TS)ctx;
1253   PetscErrorCode ierr;
1254   Vec            Ydot,Zdot,Ystage,Zstage;
1255   Vec            Ydotc,Zdotc,Ystagec,Zstagec;
1256 
1257   PetscFunctionBegin;
1258   ierr = TSRosWGetVecs(ts,fine,&Ydot,&Ystage,&Zdot,&Zstage);CHKERRQ(ierr);
1259   ierr = TSRosWGetVecs(ts,coarse,&Ydotc,&Ystagec,&Zdotc,&Zstagec);CHKERRQ(ierr);
1260   ierr = MatRestrict(restrct,Ydot,Ydotc);CHKERRQ(ierr);
1261   ierr = VecPointwiseMult(Ydotc,rscale,Ydotc);CHKERRQ(ierr);
1262   ierr = MatRestrict(restrct,Ystage,Ystagec);CHKERRQ(ierr);
1263   ierr = VecPointwiseMult(Ystagec,rscale,Ystagec);CHKERRQ(ierr);
1264   ierr = MatRestrict(restrct,Zdot,Zdotc);CHKERRQ(ierr);
1265   ierr = VecPointwiseMult(Zdotc,rscale,Zdotc);CHKERRQ(ierr);
1266   ierr = MatRestrict(restrct,Zstage,Zstagec);CHKERRQ(ierr);
1267   ierr = VecPointwiseMult(Zstagec,rscale,Zstagec);CHKERRQ(ierr);
1268   ierr = TSRosWRestoreVecs(ts,fine,&Ydot,&Ystage,&Zdot,&Zstage);CHKERRQ(ierr);
1269   ierr = TSRosWRestoreVecs(ts,coarse,&Ydotc,&Ystagec,&Zdotc,&Zstagec);CHKERRQ(ierr);
1270   PetscFunctionReturn(0);
1271 }
1272 
1273 
1274 #undef __FUNCT__
1275 #define __FUNCT__ "DMSubDomainHook_TSRosW"
1276 static PetscErrorCode DMSubDomainHook_TSRosW(DM fine,DM coarse,void *ctx)
1277 {
1278   PetscFunctionBegin;
1279   PetscFunctionReturn(0);
1280 }
1281 
1282 #undef __FUNCT__
1283 #define __FUNCT__ "DMSubDomainRestrictHook_TSRosW"
1284 static PetscErrorCode DMSubDomainRestrictHook_TSRosW(DM dm,VecScatter gscat,VecScatter lscat,DM subdm,void *ctx)
1285 {
1286   TS             ts = (TS)ctx;
1287   PetscErrorCode ierr;
1288   Vec            Ydot,Zdot,Ystage,Zstage;
1289   Vec            Ydots,Zdots,Ystages,Zstages;
1290 
1291   PetscFunctionBegin;
1292   ierr = TSRosWGetVecs(ts,dm,&Ydot,&Ystage,&Zdot,&Zstage);CHKERRQ(ierr);
1293   ierr = TSRosWGetVecs(ts,subdm,&Ydots,&Ystages,&Zdots,&Zstages);CHKERRQ(ierr);
1294 
1295   ierr = VecScatterBegin(gscat,Ydot,Ydots,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
1296   ierr = VecScatterEnd(gscat,Ydot,Ydots,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
1297 
1298   ierr = VecScatterBegin(gscat,Ystage,Ystages,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
1299   ierr = VecScatterEnd(gscat,Ystage,Ystages,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
1300 
1301   ierr = VecScatterBegin(gscat,Zdot,Zdots,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
1302   ierr = VecScatterEnd(gscat,Zdot,Zdots,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
1303 
1304   ierr = VecScatterBegin(gscat,Zstage,Zstages,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
1305   ierr = VecScatterEnd(gscat,Zstage,Zstages,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
1306 
1307   ierr = TSRosWRestoreVecs(ts,dm,&Ydot,&Ystage,&Zdot,&Zstage);CHKERRQ(ierr);
1308   ierr = TSRosWRestoreVecs(ts,subdm,&Ydots,&Ystages,&Zdots,&Zstages);CHKERRQ(ierr);
1309   PetscFunctionReturn(0);
1310 }
1311 
1312 /*
1313   This defines the nonlinear equation that is to be solved with SNES
1314   G(U) = F[t0+Theta*dt, U, (U-U0)*shift] = 0
1315 */
1316 #undef __FUNCT__
1317 #define __FUNCT__ "SNESTSFormFunction_RosW"
1318 static PetscErrorCode SNESTSFormFunction_RosW(SNES snes,Vec U,Vec F,TS ts)
1319 {
1320   TS_RosW        *ros = (TS_RosW*)ts->data;
1321   PetscErrorCode ierr;
1322   Vec            Ydot,Zdot,Ystage,Zstage;
1323   PetscReal      shift = ros->scoeff / ts->time_step;
1324   DM             dm,dmsave;
1325 
1326   PetscFunctionBegin;
1327   ierr   = SNESGetDM(snes,&dm);CHKERRQ(ierr);
1328   ierr   = TSRosWGetVecs(ts,dm,&Ydot,&Zdot,&Ystage,&Zstage);CHKERRQ(ierr);
1329   ierr   = VecWAXPY(Ydot,shift,U,Zdot);CHKERRQ(ierr);    /* Ydot = shift*U + Zdot */
1330   ierr   = VecWAXPY(Ystage,1.0,U,Zstage);CHKERRQ(ierr);  /* Ystage = U + Zstage */
1331   dmsave = ts->dm;
1332   ts->dm = dm;
1333   ierr   = TSComputeIFunction(ts,ros->stage_time,Ystage,Ydot,F,PETSC_FALSE);CHKERRQ(ierr);
1334   ts->dm = dmsave;
1335   ierr   = TSRosWRestoreVecs(ts,dm,&Ydot,&Zdot,&Ystage,&Zstage);CHKERRQ(ierr);
1336   PetscFunctionReturn(0);
1337 }
1338 
1339 #undef __FUNCT__
1340 #define __FUNCT__ "SNESTSFormJacobian_RosW"
1341 static PetscErrorCode SNESTSFormJacobian_RosW(SNES snes,Vec U,Mat *A,Mat *B,MatStructure *str,TS ts)
1342 {
1343   TS_RosW        *ros = (TS_RosW*)ts->data;
1344   Vec            Ydot,Zdot,Ystage,Zstage;
1345   PetscReal      shift = ros->scoeff / ts->time_step;
1346   PetscErrorCode ierr;
1347   DM             dm,dmsave;
1348 
1349   PetscFunctionBegin;
1350   /* ros->Ydot and ros->Ystage have already been computed in SNESTSFormFunction_RosW (SNES guarantees this) */
1351   ierr   = SNESGetDM(snes,&dm);CHKERRQ(ierr);
1352   ierr   = TSRosWGetVecs(ts,dm,&Ydot,&Zdot,&Ystage,&Zstage);CHKERRQ(ierr);
1353   dmsave = ts->dm;
1354   ts->dm = dm;
1355   ierr   = TSComputeIJacobian(ts,ros->stage_time,Ystage,Ydot,shift,A,B,str,PETSC_TRUE);CHKERRQ(ierr);
1356   ts->dm = dmsave;
1357   ierr   = TSRosWRestoreVecs(ts,dm,&Ydot,&Zdot,&Ystage,&Zstage);CHKERRQ(ierr);
1358   PetscFunctionReturn(0);
1359 }
1360 
1361 #undef __FUNCT__
1362 #define __FUNCT__ "TSSetUp_RosW"
1363 static PetscErrorCode TSSetUp_RosW(TS ts)
1364 {
1365   TS_RosW        *ros = (TS_RosW*)ts->data;
1366   RosWTableau    tab  = ros->tableau;
1367   PetscInt       s    = tab->s;
1368   PetscErrorCode ierr;
1369   DM             dm;
1370 
1371   PetscFunctionBegin;
1372   if (!ros->tableau) {
1373     ierr = TSRosWSetType(ts,TSRosWDefault);CHKERRQ(ierr);
1374   }
1375   ierr = VecDuplicateVecs(ts->vec_sol,s,&ros->Y);CHKERRQ(ierr);
1376   ierr = VecDuplicate(ts->vec_sol,&ros->Ydot);CHKERRQ(ierr);
1377   ierr = VecDuplicate(ts->vec_sol,&ros->Ystage);CHKERRQ(ierr);
1378   ierr = VecDuplicate(ts->vec_sol,&ros->Zdot);CHKERRQ(ierr);
1379   ierr = VecDuplicate(ts->vec_sol,&ros->Zstage);CHKERRQ(ierr);
1380   ierr = VecDuplicate(ts->vec_sol,&ros->VecSolPrev);CHKERRQ(ierr);
1381   ierr = PetscMalloc(s*sizeof(ros->work[0]),&ros->work);CHKERRQ(ierr);
1382   ierr = TSGetDM(ts,&dm);CHKERRQ(ierr);
1383   if (dm) {
1384     ierr = DMCoarsenHookAdd(dm,DMCoarsenHook_TSRosW,DMRestrictHook_TSRosW,ts);CHKERRQ(ierr);
1385     ierr = DMSubDomainHookAdd(dm,DMSubDomainHook_TSRosW,DMSubDomainRestrictHook_TSRosW,ts);CHKERRQ(ierr);
1386   }
1387   PetscFunctionReturn(0);
1388 }
1389 /*------------------------------------------------------------*/
1390 
1391 #undef __FUNCT__
1392 #define __FUNCT__ "TSSetFromOptions_RosW"
1393 static PetscErrorCode TSSetFromOptions_RosW(TS ts)
1394 {
1395   TS_RosW        *ros = (TS_RosW*)ts->data;
1396   PetscErrorCode ierr;
1397   char           rostype[256];
1398 
1399   PetscFunctionBegin;
1400   ierr = PetscOptionsHead("RosW ODE solver options");CHKERRQ(ierr);
1401   {
1402     RosWTableauLink link;
1403     PetscInt        count,choice;
1404     PetscBool       flg;
1405     const char      **namelist;
1406     SNES            snes;
1407 
1408     ierr = PetscStrncpy(rostype,TSRosWDefault,sizeof(rostype));CHKERRQ(ierr);
1409     for (link=RosWTableauList,count=0; link; link=link->next,count++) ;
1410     ierr = PetscMalloc(count*sizeof(char*),&namelist);CHKERRQ(ierr);
1411     for (link=RosWTableauList,count=0; link; link=link->next,count++) namelist[count] = link->tab.name;
1412     ierr = PetscOptionsEList("-ts_rosw_type","Family of Rosenbrock-W method","TSRosWSetType",(const char*const*)namelist,count,rostype,&choice,&flg);CHKERRQ(ierr);
1413     ierr = TSRosWSetType(ts,flg ? namelist[choice] : rostype);CHKERRQ(ierr);
1414     ierr = PetscFree(namelist);CHKERRQ(ierr);
1415 
1416     ierr = PetscOptionsBool("-ts_rosw_recompute_jacobian","Recompute the Jacobian at each stage","TSRosWSetRecomputeJacobian",ros->recompute_jacobian,&ros->recompute_jacobian,NULL);CHKERRQ(ierr);
1417 
1418     /* Rosenbrock methods are linearly implicit, so set that unless the user has specifically asked for something else */
1419     ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr);
1420     if (!((PetscObject)snes)->type_name) {
1421       ierr = SNESSetType(snes,SNESKSPONLY);CHKERRQ(ierr);
1422     }
1423     ierr = SNESSetFromOptions(snes);CHKERRQ(ierr);
1424   }
1425   ierr = PetscOptionsTail();CHKERRQ(ierr);
1426   PetscFunctionReturn(0);
1427 }
1428 
1429 #undef __FUNCT__
1430 #define __FUNCT__ "PetscFormatRealArray"
1431 static PetscErrorCode PetscFormatRealArray(char buf[],size_t len,const char *fmt,PetscInt n,const PetscReal x[])
1432 {
1433   PetscErrorCode ierr;
1434   PetscInt       i;
1435   size_t         left,count;
1436   char           *p;
1437 
1438   PetscFunctionBegin;
1439   for (i=0,p=buf,left=len; i<n; i++) {
1440     ierr = PetscSNPrintfCount(p,left,fmt,&count,x[i]);CHKERRQ(ierr);
1441     if (count >= left) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Insufficient space in buffer");
1442     left -= count;
1443     p    += count;
1444     *p++  = ' ';
1445   }
1446   p[i ? 0 : -1] = 0;
1447   PetscFunctionReturn(0);
1448 }
1449 
1450 #undef __FUNCT__
1451 #define __FUNCT__ "TSView_RosW"
1452 static PetscErrorCode TSView_RosW(TS ts,PetscViewer viewer)
1453 {
1454   TS_RosW        *ros = (TS_RosW*)ts->data;
1455   RosWTableau    tab  = ros->tableau;
1456   PetscBool      iascii;
1457   PetscErrorCode ierr;
1458   TSAdapt        adapt;
1459 
1460   PetscFunctionBegin;
1461   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr);
1462   if (iascii) {
1463     TSRosWType rostype;
1464     PetscInt   i;
1465     PetscReal  abscissa[512];
1466     char       buf[512];
1467     ierr = TSRosWGetType(ts,&rostype);CHKERRQ(ierr);
1468     ierr = PetscViewerASCIIPrintf(viewer,"  Rosenbrock-W %s\n",rostype);CHKERRQ(ierr);
1469     ierr = PetscFormatRealArray(buf,sizeof(buf),"% 8.6f",tab->s,tab->ASum);CHKERRQ(ierr);
1470     ierr = PetscViewerASCIIPrintf(viewer,"  Abscissa of A       = %s\n",buf);CHKERRQ(ierr);
1471     for (i=0; i<tab->s; i++) abscissa[i] = tab->ASum[i] + tab->Gamma[i];
1472     ierr = PetscFormatRealArray(buf,sizeof(buf),"% 8.6f",tab->s,abscissa);CHKERRQ(ierr);
1473     ierr = PetscViewerASCIIPrintf(viewer,"  Abscissa of A+Gamma = %s\n",buf);CHKERRQ(ierr);
1474   }
1475   ierr = TSGetAdapt(ts,&adapt);CHKERRQ(ierr);
1476   ierr = TSAdaptView(adapt,viewer);CHKERRQ(ierr);
1477   ierr = SNESView(ts->snes,viewer);CHKERRQ(ierr);
1478   PetscFunctionReturn(0);
1479 }
1480 
1481 #undef __FUNCT__
1482 #define __FUNCT__ "TSRosWSetType"
1483 /*@C
1484   TSRosWSetType - Set the type of Rosenbrock-W scheme
1485 
1486   Logically collective
1487 
1488   Input Parameter:
1489 +  ts - timestepping context
1490 -  rostype - type of Rosenbrock-W scheme
1491 
1492   Level: beginner
1493 
1494 .seealso: TSRosWGetType(), TSROSW, TSROSW2M, TSROSW2P, TSROSWRA3PW, TSROSWRA34PW2, TSROSWRODAS3, TSROSWSANDU3, TSROSWASSP3P3S1C, TSROSWLASSP3P4S2C, TSROSWLLSSP3P4S2C, TSROSWARK3
1495 @*/
1496 PetscErrorCode TSRosWSetType(TS ts,TSRosWType rostype)
1497 {
1498   PetscErrorCode ierr;
1499 
1500   PetscFunctionBegin;
1501   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
1502   ierr = PetscTryMethod(ts,"TSRosWSetType_C",(TS,TSRosWType),(ts,rostype));CHKERRQ(ierr);
1503   PetscFunctionReturn(0);
1504 }
1505 
1506 #undef __FUNCT__
1507 #define __FUNCT__ "TSRosWGetType"
1508 /*@C
1509   TSRosWGetType - Get the type of Rosenbrock-W scheme
1510 
1511   Logically collective
1512 
1513   Input Parameter:
1514 .  ts - timestepping context
1515 
1516   Output Parameter:
1517 .  rostype - type of Rosenbrock-W scheme
1518 
1519   Level: intermediate
1520 
1521 .seealso: TSRosWGetType()
1522 @*/
1523 PetscErrorCode TSRosWGetType(TS ts,TSRosWType *rostype)
1524 {
1525   PetscErrorCode ierr;
1526 
1527   PetscFunctionBegin;
1528   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
1529   ierr = PetscUseMethod(ts,"TSRosWGetType_C",(TS,TSRosWType*),(ts,rostype));CHKERRQ(ierr);
1530   PetscFunctionReturn(0);
1531 }
1532 
1533 #undef __FUNCT__
1534 #define __FUNCT__ "TSRosWSetRecomputeJacobian"
1535 /*@C
1536   TSRosWSetRecomputeJacobian - Set whether to recompute the Jacobian at each stage. The default is to update the Jacobian once per step.
1537 
1538   Logically collective
1539 
1540   Input Parameter:
1541 +  ts - timestepping context
1542 -  flg - PETSC_TRUE to recompute the Jacobian at each stage
1543 
1544   Level: intermediate
1545 
1546 .seealso: TSRosWGetType()
1547 @*/
1548 PetscErrorCode TSRosWSetRecomputeJacobian(TS ts,PetscBool flg)
1549 {
1550   PetscErrorCode ierr;
1551 
1552   PetscFunctionBegin;
1553   PetscValidHeaderSpecific(ts,TS_CLASSID,1);
1554   ierr = PetscTryMethod(ts,"TSRosWSetRecomputeJacobian_C",(TS,PetscBool),(ts,flg));CHKERRQ(ierr);
1555   PetscFunctionReturn(0);
1556 }
1557 
1558 #undef __FUNCT__
1559 #define __FUNCT__ "TSRosWGetType_RosW"
1560 PetscErrorCode  TSRosWGetType_RosW(TS ts,TSRosWType *rostype)
1561 {
1562   TS_RosW        *ros = (TS_RosW*)ts->data;
1563   PetscErrorCode ierr;
1564 
1565   PetscFunctionBegin;
1566   if (!ros->tableau) {ierr = TSRosWSetType(ts,TSRosWDefault);CHKERRQ(ierr);}
1567   *rostype = ros->tableau->name;
1568   PetscFunctionReturn(0);
1569 }
1570 
1571 #undef __FUNCT__
1572 #define __FUNCT__ "TSRosWSetType_RosW"
1573 PetscErrorCode  TSRosWSetType_RosW(TS ts,TSRosWType rostype)
1574 {
1575   TS_RosW         *ros = (TS_RosW*)ts->data;
1576   PetscErrorCode  ierr;
1577   PetscBool       match;
1578   RosWTableauLink link;
1579 
1580   PetscFunctionBegin;
1581   if (ros->tableau) {
1582     ierr = PetscStrcmp(ros->tableau->name,rostype,&match);CHKERRQ(ierr);
1583     if (match) PetscFunctionReturn(0);
1584   }
1585   for (link = RosWTableauList; link; link=link->next) {
1586     ierr = PetscStrcmp(link->tab.name,rostype,&match);CHKERRQ(ierr);
1587     if (match) {
1588       ierr = TSReset_RosW(ts);CHKERRQ(ierr);
1589       ros->tableau = &link->tab;
1590       PetscFunctionReturn(0);
1591     }
1592   }
1593   SETERRQ1(PetscObjectComm((PetscObject)ts),PETSC_ERR_ARG_UNKNOWN_TYPE,"Could not find '%s'",rostype);
1594   PetscFunctionReturn(0);
1595 }
1596 
1597 #undef __FUNCT__
1598 #define __FUNCT__ "TSRosWSetRecomputeJacobian_RosW"
1599 PetscErrorCode  TSRosWSetRecomputeJacobian_RosW(TS ts,PetscBool flg)
1600 {
1601   TS_RosW *ros = (TS_RosW*)ts->data;
1602 
1603   PetscFunctionBegin;
1604   ros->recompute_jacobian = flg;
1605   PetscFunctionReturn(0);
1606 }
1607 
1608 
1609 /* ------------------------------------------------------------ */
1610 /*MC
1611       TSROSW - ODE solver using Rosenbrock-W schemes
1612 
1613   These methods are intended for problems with well-separated time scales, especially when a slow scale is strongly
1614   nonlinear such that it is expensive to solve with a fully implicit method. The user should provide the stiff part
1615   of the equation using TSSetIFunction() and the non-stiff part with TSSetRHSFunction().
1616 
1617   Notes:
1618   This method currently only works with autonomous ODE and DAE.
1619 
1620   Developer notes:
1621   Rosenbrock-W methods are typically specified for autonomous ODE
1622 
1623 $  udot = f(u)
1624 
1625   by the stage equations
1626 
1627 $  k_i = h f(u_0 + sum_j alpha_ij k_j) + h J sum_j gamma_ij k_j
1628 
1629   and step completion formula
1630 
1631 $  u_1 = u_0 + sum_j b_j k_j
1632 
1633   with step size h and coefficients alpha_ij, gamma_ij, and b_i. Implementing the method in this form would require f(u)
1634   and the Jacobian J to be available, in addition to the shifted matrix I - h gamma_ii J. Following Hairer and Wanner,
1635   we define new variables for the stage equations
1636 
1637 $  y_i = gamma_ij k_j
1638 
1639   The k_j can be recovered because Gamma is invertible. Let C be the lower triangular part of Gamma^{-1} and define
1640 
1641 $  A = Alpha Gamma^{-1}, bt^T = b^T Gamma^{-i}
1642 
1643   to rewrite the method as
1644 
1645 $  [M/(h gamma_ii) - J] y_i = f(u_0 + sum_j a_ij y_j) + M sum_j (c_ij/h) y_j
1646 $  u_1 = u_0 + sum_j bt_j y_j
1647 
1648    where we have introduced the mass matrix M. Continue by defining
1649 
1650 $  ydot_i = 1/(h gamma_ii) y_i - sum_j (c_ij/h) y_j
1651 
1652    or, more compactly in tensor notation
1653 
1654 $  Ydot = 1/h (Gamma^{-1} \otimes I) Y .
1655 
1656    Note that Gamma^{-1} is lower triangular. With this definition of Ydot in terms of known quantities and the current
1657    stage y_i, the stage equations reduce to performing one Newton step (typically with a lagged Jacobian) on the
1658    equation
1659 
1660 $  g(u_0 + sum_j a_ij y_j + y_i, ydot_i) = 0
1661 
1662    with initial guess y_i = 0.
1663 
1664   Level: beginner
1665 
1666 .seealso:  TSCreate(), TS, TSSetType(), TSRosWSetType(), TSRosWRegister(), TSROSW2M, TSROSW2P, TSROSWRA3PW, TSROSWRA34PW2, TSROSWRODAS3,
1667            TSROSWSANDU3, TSROSWASSP3P3S1C, TSROSWLASSP3P4S2C, TSROSWLLSSP3P4S2C, TSROSWGRK4T, TSROSWSHAMP4, TSROSWVELDD4, TSROSW4L
1668 M*/
1669 #undef __FUNCT__
1670 #define __FUNCT__ "TSCreate_RosW"
1671 PETSC_EXTERN PetscErrorCode TSCreate_RosW(TS ts)
1672 {
1673   TS_RosW        *ros;
1674   PetscErrorCode ierr;
1675 
1676   PetscFunctionBegin;
1677 #if !defined(PETSC_USE_DYNAMIC_LIBRARIES)
1678   ierr = TSRosWInitializePackage();CHKERRQ(ierr);
1679 #endif
1680 
1681   ts->ops->reset          = TSReset_RosW;
1682   ts->ops->destroy        = TSDestroy_RosW;
1683   ts->ops->view           = TSView_RosW;
1684   ts->ops->setup          = TSSetUp_RosW;
1685   ts->ops->step           = TSStep_RosW;
1686   ts->ops->interpolate    = TSInterpolate_RosW;
1687   ts->ops->evaluatestep   = TSEvaluateStep_RosW;
1688   ts->ops->setfromoptions = TSSetFromOptions_RosW;
1689   ts->ops->snesfunction   = SNESTSFormFunction_RosW;
1690   ts->ops->snesjacobian   = SNESTSFormJacobian_RosW;
1691 
1692   ierr = PetscNewLog(ts,TS_RosW,&ros);CHKERRQ(ierr);
1693   ts->data = (void*)ros;
1694 
1695   ierr = PetscObjectComposeFunction((PetscObject)ts,"TSRosWGetType_C",TSRosWGetType_RosW);CHKERRQ(ierr);
1696   ierr = PetscObjectComposeFunction((PetscObject)ts,"TSRosWSetType_C",TSRosWSetType_RosW);CHKERRQ(ierr);
1697   ierr = PetscObjectComposeFunction((PetscObject)ts,"TSRosWSetRecomputeJacobian_C",TSRosWSetRecomputeJacobian_RosW);CHKERRQ(ierr);
1698   PetscFunctionReturn(0);
1699 }
1700