leastsquares/tests/chwirut2.c

4      petsc.h       - base PETSc routines   petscvec.h - vectors
5      petscsys.h    - system routines        petscmat.h - matrices
6      petscis.h     - index sets            petscksp.h - Krylov subspace methods
7      petscviewer.h - viewers               petscpc.h  - preconditioners
24 static char help[] = "Finds the nonlinear least-squares solution to the model \n\
25             y = exp[-b1*x]/(b2+b3*x)  +  e \n";
30 /* User-defined application context */
33   PetscReal t[NOBSERVATIONS];              /* array of independent variables of observation */
46 /*--------------------------------------------------------------------*/
61   AppCtx    user; /* user-defined work context */
65   PetscCall(PetscOptionsGetInt(NULL, NULL, "-wtype", &wtype, &flg));
103   PetscCall(TaoSetTolerances(tao, 1e-5, 0.0, PETSC_CURRENT));
125 /*--------------------------------------------------------------------*/
130   PetscReal       *y = user->y, *f, *t = user->t;
137   for (i = 0; i < NOBSERVATIONS; i++) f[i] = y[i] - PetscExpScalar(-x[0] * t[i]) / (x[1] + x[2] * t[i]);
144 /*------------------------------------------------------------*/
150   PetscReal       *t = user->t;
157     base = PetscExpScalar(-x[0] * t[i]) / (x[1] + x[2] * t[i]);
159     user->j[i][0] = t[i] * base;
160     user->j[i][1] = base / (x[1] + x[2] * t[i]);
161     user->j[i][2] = base * t[i] / (x[1] + x[2] * t[i]);
165   PetscCall(MatSetValues(J, NOBSERVATIONS, user->idm, NPARAMETERS, user->idn, (PetscReal *)user->j, INSERT_VALUES));
174 /* ------------------------------------------------------------ */
182   x[1] = -1.86;
188 /* ---------------------------------------------------------------------- */
191   PetscReal *t = user->t, *y = user->y;
196   t[i++] = 0.5000;
198   t[i++] = 0.6250;
200   t[i++] = 0.7500;
202   t[i++] = 0.8750;
204   t[i++] = 1.0000;
206   t[i++] = 1.2500;
208   t[i++] = 1.7500;
210   t[i++] = 2.2500;
212   t[i++] = 1.7500;
214   t[i++] = 2.2500;
216   t[i++] = 2.7500;
218   t[i++] = 3.2500;
220   t[i++] = 3.7500;
222   t[i++] = 4.2500;
224   t[i++] = 4.7500;
226   t[i++] = 5.2500;
228   t[i++] = 5.7500;
230   t[i++] = 0.5000;
232   t[i++] = 0.6250;
234   t[i++] = 0.7500;
236   t[i++] = 0.8750;
238   t[i++] = 1.0000;
240   t[i++] = 1.2500;
242   t[i++] = 1.7500;
244   t[i++] = 2.2500;
246   t[i++] = 1.7500;
248   t[i++] = 2.2500;
250   t[i++] = 2.7500;
252   t[i++] = 3.2500;
254   t[i++] = 3.7500;
256   t[i++] = 4.2500;
258   t[i++] = 4.7500;
260   t[i++] = 5.2500;
262   t[i++] = 5.7500;
264   t[i++] = 0.5000;
266   t[i++] = 0.6250;
268   t[i++] = 0.7500;
270   t[i++] = 0.8750;
272   t[i++] = 1.0000;
274   t[i++] = 1.2500;
276   t[i++] = 1.7500;
278   t[i++] = 2.2500;
280   t[i++] = 1.7500;
282   t[i++] = 2.2500;
284   t[i++] = 2.7500;
286   t[i++] = 3.2500;
288   t[i++] = 3.7500;
290   t[i++] = 4.2500;
292   t[i++] = 4.7500;
294   t[i++] = 5.2500;
296   t[i++] = 5.7500;
298   t[i++] = 0.5000;
300   t[i++] = 0.6250;
302   t[i++] = 0.7500;
304   t[i++] = 0.8750;
306   t[i++] = 1.0000;
308   t[i++] = 1.2500;
310   t[i++] = 1.7500;
312   t[i++] = 2.2500;
314   t[i++] = 1.7500;
316   t[i++] = 2.2500;
318   t[i++] = 2.7500;
320   t[i++] = 3.2500;
322   t[i++] = 3.7500;
324   t[i++] = 4.2500;
326   t[i++] = 4.7500;
328   t[i++] = 5.2500;
330   t[i++] = 5.7500;
332   t[i++] = .5000;
334   t[i++] = .7500;
336   t[i++] = 1.5000;
338   t[i++] = 3.0000;
340   t[i++] = 3.0000;
342   t[i++] = 3.0000;
344   t[i++] = 6.0000;
346   t[i++] = .5000;
348   t[i++] = .7500;
350   t[i++] = 1.5000;
352   t[i++] = 3.0000;
354   t[i++] = 3.0000;
356   t[i++] = 3.0000;
358   t[i++] = 6.0000;
360   t[i++] = .5000;
362   t[i++] = .7500;
364   t[i++] = 1.5000;
366   t[i++] = 3.0000;
368   t[i++] = 3.0000;
370   t[i++] = 3.0000;
372   t[i++] = 6.0000;
374   t[i++] = .5000;
376   t[i++] = .7500;
378   t[i++] = 1.5000;
380   t[i++] = 3.0000;
382   t[i++] = 6.0000;
384   t[i++] = 3.0000;
386   t[i++] = 3.0000;
388   t[i++] = 6.0000;
390   t[i++] = .5000;
392   t[i++] = .7500;
394   t[i++] = 1.0000;
396   t[i++] = 1.5000;
398   t[i++] = 2.0000;
400   t[i++] = 2.0000;
402   t[i++] = 2.5000;
404   t[i++] = 3.0000;
406   t[i++] = 4.0000;
408   t[i++] = 5.0000;
410   t[i++] = 6.0000;
412   t[i++] = .5000;
414   t[i++] = .7500;
416   t[i++] = 1.0000;
418   t[i++] = 1.5000;
420   t[i++] = 2.0000;
422   t[i++] = 2.0000;
424   t[i++] = 2.5000;
426   t[i++] = 3.0000;
428   t[i++] = 4.0000;
430   t[i++] = 5.0000;
432   t[i++] = 6.0000;
434   t[i++] = .5000;
436   t[i++] = .7500;
438   t[i++] = 1.0000;
440   t[i++] = 1.5000;
442   t[i++] = 2.0000;
444   t[i++] = 2.0000;
446   t[i++] = 2.5000;
448   t[i++] = 3.0000;
450   t[i++] = 4.0000;
452   t[i++] = 5.0000;
454   t[i++] = 6.0000;
456   t[i++] = .5000;
458   t[i++] = .6250;
460   t[i++] = .7500;
462   t[i++] = .8750;
464   t[i++] = 1.0000;
466   t[i++] = 1.2500;
468   t[i++] = 2.2500;
470   t[i++] = 2.2500;
472   t[i++] = 2.7500;
474   t[i++] = 3.2500;
476   t[i++] = 3.7500;
478   t[i++] = 4.2500;
480   t[i++] = 4.7500;
482   t[i++] = 5.2500;
484   t[i++] = 5.7500;
486   t[i++] = 3.0000;
488   t[i++] = 3.0000;
490   t[i++] = 3.0000;
492   t[i++] = 3.0000;
494   t[i++] = 3.0000;
496   t[i++] = 3.0000;
498   t[i++] = .5000;
500   t[i++] = .7500;
502   t[i++] = 1.0000;
504   t[i++] = 1.5000;
506   t[i++] = 2.0000;
508   t[i++] = 2.5000;
510   t[i++] = 2.0000;
512   t[i++] = 2.5000;
514   t[i++] = 3.0000;
516   t[i++] = 4.0000;
518   t[i++] = 5.0000;
520   t[i++] = 6.0000;
522   t[i++] = .5000;
524   t[i++] = .7500;
526   t[i++] = 1.0000;
528   t[i++] = 1.5000;
530   t[i++] = 2.0000;
532   t[i++] = 2.5000;
534   t[i++] = 2.0000;
536   t[i++] = 2.5000;
538   t[i++] = 3.0000;
540   t[i++] = 4.0000;
542   t[i++] = 5.0000;
544   t[i++] = 6.0000;
546   t[i++] = .5000;
548   t[i++] = .7500;
550   t[i++] = 1.0000;
552   t[i++] = 1.5000;
554   t[i++] = 2.0000;
556   t[i++] = 2.5000;
558   t[i++] = 2.0000;
560   t[i++] = 2.5000;
562   t[i++] = 3.0000;
564   t[i++] = 4.0000;
566   t[i++] = 5.0000;
568   t[i++] = 6.0000;
570   t[i++] = 3.0000;
572   t[i++] = .5000;
574   t[i++] = .7500;
576   t[i++] = 1.5000;
578   t[i++] = 3.0000;
580   t[i++] = 6.0000;
582   t[i++] = 3.0000;
584   t[i++] = 6.0000;
586   t[i++] = 3.0000;
588   t[i++] = 3.0000;
590   t[i++] = 3.0000;
592   t[i++] = 1.7500;
594   t[i++] = 1.7500;
596   t[i++] = .5000;
598   t[i++] = .7500;
600   t[i++] = 1.7500;
602   t[i++] = 1.7500;
604   t[i++] = 2.7500;
606   t[i++] = 3.7500;
608   t[i++] = 1.7500;
610   t[i++] = 1.7500;
612   t[i++] = .5000;
614   t[i++] = .7500;
616   t[i++] = 2.7500;
618   t[i++] = 3.7500;
620   t[i++] = 1.7500;
622   t[i++] = 1.7500;
632        args: -tao_monitor_short -tao_max_it 100 -tao_type pounders -tao_pounders_delta 0.05 -tao_gatol 1.e-5
638        args: -tao_monitor_short -tao_max_it 100 -wtype 1 -tao_type pounders -tao_pounders_delta 0.05 -tao_gatol 1.e-5
644        args: -tao_monitor_short -tao_max_it 100 -wtype 2 -tao_type pounders -tao_pounders_delta 0.05 -tao_gatol 1.e-5
650        args: -tao_monitor_short -tao_max_it 100 -tao_type pounders -tao_pounders_delta 0.05 -pounders_subsolver_tao_type blmvm -tao_gatol 1.e-5