xref: /petsc/src/snes/impls/ls/ls.c (revision 5b6bfdb9644f185dbf5e5a09b808ec241507e1e7)
1 
2 #include <../src/snes/impls/ls/lsimpl.h>
3 
4 /*
5      Checks if J^T F = 0 which implies we've found a local minimum of the norm of the function,
6     || F(u) ||_2 but not a zero, F(u) = 0. In the case when one cannot compute J^T F we use the fact that
7     0 = (J^T F)^T W = F^T J W iff W not in the null space of J. Thanks for Jorge More
8     for this trick. One assumes that the probability that W is in the null space of J is very, very small.
9 */
10 static PetscErrorCode SNESNEWTONLSCheckLocalMin_Private(SNES snes,Mat A,Vec F,PetscReal fnorm,PetscBool  *ismin)
11 {
12   PetscReal      a1;
13   PetscErrorCode ierr;
14   PetscBool      hastranspose;
15   Vec            W;
16 
17   PetscFunctionBegin;
18   *ismin = PETSC_FALSE;
19   ierr   = MatHasOperation(A,MATOP_MULT_TRANSPOSE,&hastranspose);CHKERRQ(ierr);
20   ierr   = VecDuplicate(F,&W);CHKERRQ(ierr);
21   if (hastranspose) {
22     /* Compute || J^T F|| */
23     ierr = MatMultTranspose(A,F,W);CHKERRQ(ierr);
24     ierr = VecNorm(W,NORM_2,&a1);CHKERRQ(ierr);
25     ierr = PetscInfo1(snes,"|| J^T F|| %14.12e near zero implies found a local minimum\n",(double)(a1/fnorm));CHKERRQ(ierr);
26     if (a1/fnorm < 1.e-4) *ismin = PETSC_TRUE;
27   } else {
28     Vec         work;
29     PetscScalar result;
30     PetscReal   wnorm;
31 
32     ierr = VecSetRandom(W,NULL);CHKERRQ(ierr);
33     ierr = VecNorm(W,NORM_2,&wnorm);CHKERRQ(ierr);
34     ierr = VecDuplicate(W,&work);CHKERRQ(ierr);
35     ierr = MatMult(A,W,work);CHKERRQ(ierr);
36     ierr = VecDot(F,work,&result);CHKERRQ(ierr);
37     ierr = VecDestroy(&work);CHKERRQ(ierr);
38     a1   = PetscAbsScalar(result)/(fnorm*wnorm);
39     ierr = PetscInfo1(snes,"(F^T J random)/(|| F ||*||random|| %14.12e near zero implies found a local minimum\n",(double)a1);CHKERRQ(ierr);
40     if (a1 < 1.e-4) *ismin = PETSC_TRUE;
41   }
42   ierr = VecDestroy(&W);CHKERRQ(ierr);
43   PetscFunctionReturn(0);
44 }
45 
46 /*
47      Checks if J^T(F - J*X) = 0
48 */
49 static PetscErrorCode SNESNEWTONLSCheckResidual_Private(SNES snes,Mat A,Vec F,Vec X)
50 {
51   PetscReal      a1,a2;
52   PetscErrorCode ierr;
53   PetscBool      hastranspose;
54 
55   PetscFunctionBegin;
56   ierr = MatHasOperation(A,MATOP_MULT_TRANSPOSE,&hastranspose);CHKERRQ(ierr);
57   if (hastranspose) {
58     Vec   W1,W2;
59 
60     ierr = VecDuplicate(F,&W1);CHKERRQ(ierr);
61     ierr = VecDuplicate(F,&W2);CHKERRQ(ierr);
62     ierr = MatMult(A,X,W1);CHKERRQ(ierr);
63     ierr = VecAXPY(W1,-1.0,F);CHKERRQ(ierr);
64 
65     /* Compute || J^T W|| */
66     ierr = MatMultTranspose(A,W1,W2);CHKERRQ(ierr);
67     ierr = VecNorm(W1,NORM_2,&a1);CHKERRQ(ierr);
68     ierr = VecNorm(W2,NORM_2,&a2);CHKERRQ(ierr);
69     if (a1 != 0.0) {
70       ierr = PetscInfo1(snes,"||J^T(F-Ax)||/||F-AX|| %14.12e near zero implies inconsistent rhs\n",(double)(a2/a1));CHKERRQ(ierr);
71     }
72     ierr = VecDestroy(&W1);CHKERRQ(ierr);
73     ierr = VecDestroy(&W2);CHKERRQ(ierr);
74   }
75   PetscFunctionReturn(0);
76 }
77 
78 /*  --------------------------------------------------------------------
79 
80      This file implements a truncated Newton method with a line search,
81      for solving a system of nonlinear equations, using the KSP, Vec,
82      and Mat interfaces for linear solvers, vectors, and matrices,
83      respectively.
84 
85      The following basic routines are required for each nonlinear solver:
86           SNESCreate_XXX()          - Creates a nonlinear solver context
87           SNESSetFromOptions_XXX()  - Sets runtime options
88           SNESSolve_XXX()           - Solves the nonlinear system
89           SNESDestroy_XXX()         - Destroys the nonlinear solver context
90      The suffix "_XXX" denotes a particular implementation, in this case
91      we use _NEWTONLS (e.g., SNESCreate_NEWTONLS, SNESSolve_NEWTONLS) for solving
92      systems of nonlinear equations with a line search (LS) method.
93      These routines are actually called via the common user interface
94      routines SNESCreate(), SNESSetFromOptions(), SNESSolve(), and
95      SNESDestroy(), so the application code interface remains identical
96      for all nonlinear solvers.
97 
98      Another key routine is:
99           SNESSetUp_XXX()           - Prepares for the use of a nonlinear solver
100      by setting data structures and options.   The interface routine SNESSetUp()
101      is not usually called directly by the user, but instead is called by
102      SNESSolve() if necessary.
103 
104      Additional basic routines are:
105           SNESView_XXX()            - Prints details of runtime options that
106                                       have actually been used.
107      These are called by application codes via the interface routines
108      SNESView().
109 
110      The various types of solvers (preconditioners, Krylov subspace methods,
111      nonlinear solvers, timesteppers) are all organized similarly, so the
112      above description applies to these categories also.
113 
114     -------------------------------------------------------------------- */
115 /*
116    SNESSolve_NEWTONLS - Solves a nonlinear system with a truncated Newton
117    method with a line search.
118 
119    Input Parameters:
120 .  snes - the SNES context
121 
122    Output Parameter:
123 .  outits - number of iterations until termination
124 
125    Application Interface Routine: SNESSolve()
126 
127    Notes:
128    This implements essentially a truncated Newton method with a
129    line search.  By default a cubic backtracking line search
130    is employed, as described in the text "Numerical Methods for
131    Unconstrained Optimization and Nonlinear Equations" by Dennis
132    and Schnabel.
133 */
134 PetscErrorCode SNESSolve_NEWTONLS(SNES snes)
135 {
136   PetscErrorCode       ierr;
137   PetscInt             maxits,i,lits;
138   SNESLineSearchReason lssucceed;
139   PetscReal            fnorm,gnorm,xnorm,ynorm;
140   Vec                  Y,X,F;
141   SNESLineSearch       linesearch;
142   SNESConvergedReason  reason;
143 
144   PetscFunctionBegin;
145   if (snes->xl || snes->xu || snes->ops->computevariablebounds) SETERRQ1(PetscObjectComm((PetscObject)snes),PETSC_ERR_ARG_WRONGSTATE, "SNES solver %s does not support bounds", ((PetscObject)snes)->type_name);
146 
147   snes->numFailures            = 0;
148   snes->numLinearSolveFailures = 0;
149   snes->reason                 = SNES_CONVERGED_ITERATING;
150 
151   maxits = snes->max_its;               /* maximum number of iterations */
152   X      = snes->vec_sol;               /* solution vector */
153   F      = snes->vec_func;              /* residual vector */
154   Y      = snes->vec_sol_update;        /* newton step */
155 
156   ierr       = PetscObjectSAWsTakeAccess((PetscObject)snes);CHKERRQ(ierr);
157   snes->iter = 0;
158   snes->norm = 0.0;
159   ierr       = PetscObjectSAWsGrantAccess((PetscObject)snes);CHKERRQ(ierr);
160   ierr       = SNESGetLineSearch(snes, &linesearch);CHKERRQ(ierr);
161 
162   /* compute the preconditioned function first in the case of left preconditioning with preconditioned function */
163   if (snes->npc && snes->npcside== PC_LEFT && snes->functype == SNES_FUNCTION_PRECONDITIONED) {
164     ierr = SNESApplyNPC(snes,X,NULL,F);CHKERRQ(ierr);
165     ierr = SNESGetConvergedReason(snes->npc,&reason);CHKERRQ(ierr);
166     if (reason < 0  && reason != SNES_DIVERGED_MAX_IT) {
167       snes->reason = SNES_DIVERGED_INNER;
168       PetscFunctionReturn(0);
169     }
170 
171     ierr = VecNormBegin(F,NORM_2,&fnorm);CHKERRQ(ierr);
172     ierr = VecNormEnd(F,NORM_2,&fnorm);CHKERRQ(ierr);
173   } else {
174     if (!snes->vec_func_init_set) {
175       ierr = SNESComputeFunction(snes,X,F);CHKERRQ(ierr);
176     } else snes->vec_func_init_set = PETSC_FALSE;
177   }
178 
179   ierr = VecNorm(F,NORM_2,&fnorm);CHKERRQ(ierr);        /* fnorm <- ||F||  */
180   SNESCheckFunctionNorm(snes,fnorm);
181   ierr       = PetscObjectSAWsTakeAccess((PetscObject)snes);CHKERRQ(ierr);
182   snes->norm = fnorm;
183   ierr       = PetscObjectSAWsGrantAccess((PetscObject)snes);CHKERRQ(ierr);
184   ierr       = SNESLogConvergenceHistory(snes,fnorm,0);CHKERRQ(ierr);
185   ierr       = SNESMonitor(snes,0,fnorm);CHKERRQ(ierr);
186 
187   /* test convergence */
188   ierr = (*snes->ops->converged)(snes,0,0.0,0.0,fnorm,&snes->reason,snes->cnvP);CHKERRQ(ierr);
189   if (snes->reason) PetscFunctionReturn(0);
190 
191   for (i=0; i<maxits; i++) {
192 
193     /* Call general purpose update function */
194     if (snes->ops->update) {
195       ierr = (*snes->ops->update)(snes, snes->iter);CHKERRQ(ierr);
196     }
197 
198     /* apply the nonlinear preconditioner */
199     if (snes->npc) {
200       if (snes->npcside== PC_RIGHT) {
201         ierr = SNESSetInitialFunction(snes->npc, F);CHKERRQ(ierr);
202         ierr = PetscLogEventBegin(SNES_NPCSolve,snes->npc,X,snes->vec_rhs,0);CHKERRQ(ierr);
203         ierr = SNESSolve(snes->npc, snes->vec_rhs, X);CHKERRQ(ierr);
204         ierr = PetscLogEventEnd(SNES_NPCSolve,snes->npc,X,snes->vec_rhs,0);CHKERRQ(ierr);
205         ierr = SNESGetConvergedReason(snes->npc,&reason);CHKERRQ(ierr);
206         if (reason < 0  && reason != SNES_DIVERGED_MAX_IT) {
207           snes->reason = SNES_DIVERGED_INNER;
208           PetscFunctionReturn(0);
209         }
210         ierr = SNESGetNPCFunction(snes,F,&fnorm);CHKERRQ(ierr);
211       } else if (snes->npcside== PC_LEFT && snes->functype == SNES_FUNCTION_UNPRECONDITIONED) {
212         ierr = SNESApplyNPC(snes,X,F,F);CHKERRQ(ierr);
213         ierr = SNESGetConvergedReason(snes->npc,&reason);CHKERRQ(ierr);
214         if (reason < 0  && reason != SNES_DIVERGED_MAX_IT) {
215           snes->reason = SNES_DIVERGED_INNER;
216           PetscFunctionReturn(0);
217         }
218       }
219     }
220 
221     /* Solve J Y = F, where J is Jacobian matrix */
222     ierr = SNESComputeJacobian(snes,X,snes->jacobian,snes->jacobian_pre);CHKERRQ(ierr);
223     ierr = KSPSetOperators(snes->ksp,snes->jacobian,snes->jacobian_pre);CHKERRQ(ierr);
224     ierr = KSPSolve(snes->ksp,F,Y);CHKERRQ(ierr);
225     SNESCheckKSPSolve(snes);
226     ierr              = KSPGetIterationNumber(snes->ksp,&lits);CHKERRQ(ierr);
227     snes->linear_its += lits;
228     ierr              = PetscInfo2(snes,"iter=%D, linear solve iterations=%D\n",snes->iter,lits);CHKERRQ(ierr);
229 
230     if (PetscLogPrintInfo) {
231       ierr = SNESNEWTONLSCheckResidual_Private(snes,snes->jacobian,F,Y);CHKERRQ(ierr);
232     }
233 
234     /* Compute a (scaled) negative update in the line search routine:
235          X <- X - lambda*Y
236        and evaluate F = function(X) (depends on the line search).
237     */
238     gnorm = fnorm;
239     ierr  = SNESLineSearchApply(linesearch, X, F, &fnorm, Y);CHKERRQ(ierr);
240     ierr  = SNESLineSearchGetReason(linesearch, &lssucceed);CHKERRQ(ierr);
241     ierr  = SNESLineSearchGetNorms(linesearch, &xnorm, &fnorm, &ynorm);CHKERRQ(ierr);
242     ierr  = PetscInfo4(snes,"fnorm=%18.16e, gnorm=%18.16e, ynorm=%18.16e, lssucceed=%d\n",(double)gnorm,(double)fnorm,(double)ynorm,(int)lssucceed);CHKERRQ(ierr);
243     if (snes->reason == SNES_DIVERGED_FUNCTION_COUNT) break;
244     SNESCheckFunctionNorm(snes,fnorm);
245     if (lssucceed) {
246       if (snes->stol*xnorm > ynorm) {
247         snes->reason = SNES_CONVERGED_SNORM_RELATIVE;
248         PetscFunctionReturn(0);
249       }
250       if (++snes->numFailures >= snes->maxFailures) {
251         PetscBool ismin;
252         snes->reason = SNES_DIVERGED_LINE_SEARCH;
253         ierr         = SNESNEWTONLSCheckLocalMin_Private(snes,snes->jacobian,F,fnorm,&ismin);CHKERRQ(ierr);
254         if (ismin) snes->reason = SNES_DIVERGED_LOCAL_MIN;
255         break;
256       }
257     }
258     /* Monitor convergence */
259     ierr       = PetscObjectSAWsTakeAccess((PetscObject)snes);CHKERRQ(ierr);
260     snes->iter = i+1;
261     snes->norm = fnorm;
262     ierr       = PetscObjectSAWsGrantAccess((PetscObject)snes);CHKERRQ(ierr);
263     ierr       = SNESLogConvergenceHistory(snes,snes->norm,lits);CHKERRQ(ierr);
264     ierr       = SNESMonitor(snes,snes->iter,snes->norm);CHKERRQ(ierr);
265     /* Test for convergence */
266     ierr = (*snes->ops->converged)(snes,snes->iter,xnorm,ynorm,fnorm,&snes->reason,snes->cnvP);CHKERRQ(ierr);
267     if (snes->reason) break;
268   }
269   if (i == maxits) {
270     ierr = PetscInfo1(snes,"Maximum number of iterations has been reached: %D\n",maxits);CHKERRQ(ierr);
271     if (!snes->reason) snes->reason = SNES_DIVERGED_MAX_IT;
272   }
273   PetscFunctionReturn(0);
274 }
275 /* -------------------------------------------------------------------------- */
276 /*
277    SNESSetUp_NEWTONLS - Sets up the internal data structures for the later use
278    of the SNESNEWTONLS nonlinear solver.
279 
280    Input Parameter:
281 .  snes - the SNES context
282 .  x - the solution vector
283 
284    Application Interface Routine: SNESSetUp()
285 
286    Notes:
287    For basic use of the SNES solvers, the user need not explicitly call
288    SNESSetUp(), since these actions will automatically occur during
289    the call to SNESSolve().
290  */
291 PetscErrorCode SNESSetUp_NEWTONLS(SNES snes)
292 {
293   PetscErrorCode ierr;
294 
295   PetscFunctionBegin;
296   ierr = SNESSetUpMatrices(snes);CHKERRQ(ierr);
297   if (snes->npcside== PC_LEFT && snes->functype == SNES_FUNCTION_DEFAULT) snes->functype = SNES_FUNCTION_PRECONDITIONED;
298   PetscFunctionReturn(0);
299 }
300 /* -------------------------------------------------------------------------- */
301 
302 PetscErrorCode SNESReset_NEWTONLS(SNES snes)
303 {
304   PetscFunctionBegin;
305   PetscFunctionReturn(0);
306 }
307 
308 /*
309    SNESDestroy_NEWTONLS - Destroys the private SNES_NEWTONLS context that was created
310    with SNESCreate_NEWTONLS().
311 
312    Input Parameter:
313 .  snes - the SNES context
314 
315    Application Interface Routine: SNESDestroy()
316  */
317 PetscErrorCode SNESDestroy_NEWTONLS(SNES snes)
318 {
319   PetscErrorCode ierr;
320 
321   PetscFunctionBegin;
322   ierr = SNESReset_NEWTONLS(snes);CHKERRQ(ierr);
323   ierr = PetscFree(snes->data);CHKERRQ(ierr);
324   PetscFunctionReturn(0);
325 }
326 /* -------------------------------------------------------------------------- */
327 
328 /*
329    SNESView_NEWTONLS - Prints info from the SNESNEWTONLS data structure.
330 
331    Input Parameters:
332 .  SNES - the SNES context
333 .  viewer - visualization context
334 
335    Application Interface Routine: SNESView()
336 */
337 static PetscErrorCode SNESView_NEWTONLS(SNES snes,PetscViewer viewer)
338 {
339   PetscErrorCode ierr;
340   PetscBool      iascii;
341 
342   PetscFunctionBegin;
343   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr);
344   if (iascii) {
345   }
346   PetscFunctionReturn(0);
347 }
348 
349 /* -------------------------------------------------------------------------- */
350 /*
351    SNESSetFromOptions_NEWTONLS - Sets various parameters for the SNESNEWTONLS method.
352 
353    Input Parameter:
354 .  snes - the SNES context
355 
356    Application Interface Routine: SNESSetFromOptions()
357 */
358 static PetscErrorCode SNESSetFromOptions_NEWTONLS(PetscOptionItems *PetscOptionsObject,SNES snes)
359 {
360   PetscErrorCode ierr;
361   SNESLineSearch linesearch;
362 
363   PetscFunctionBegin;
364   if (!snes->linesearch) {
365     ierr = SNESGetLineSearch(snes, &linesearch);CHKERRQ(ierr);
366     ierr = SNESLineSearchSetType(linesearch, SNESLINESEARCHBT);CHKERRQ(ierr);
367   }
368   PetscFunctionReturn(0);
369 }
370 
371 /* -------------------------------------------------------------------------- */
372 /*MC
373       SNESNEWTONLS - Newton based nonlinear solver that uses a line search
374 
375    Options Database:
376 +   -snes_linesearch_type <bt> - bt,basic.  Select line search type
377 .   -snes_linesearch_order <3> - 2, 3. Selects the order of the line search for bt
378 .   -snes_linesearch_norms <true> - Turns on/off computation of the norms for basic linesearch (SNESLineSearchSetComputeNorms())
379 .   -snes_linesearch_alpha <alpha> - Sets alpha used in determining if reduction in function norm is sufficient
380 .   -snes_linesearch_maxstep <maxstep> - Sets the maximum stepsize the line search will use (if the 2-norm(y) > maxstep then scale y to be y = (maxstep/2-norm(y)) *y)
381 .   -snes_linesearch_minlambda <minlambda>  - Sets the minimum lambda the line search will tolerate
382 .   -snes_linesearch_monitor - print information about progress of line searches
383 -   -snes_linesearch_damping - damping factor used for basic line search
384 
385     Notes: This is the default nonlinear solver in SNES
386 
387    Level: beginner
388 
389 .seealso:  SNESCreate(), SNES, SNESSetType(), SNESNEWTONTR, SNESQN, SNESLineSearchSetType(), SNESLineSearchSetOrder()
390            SNESLineSearchSetPostCheck(), SNESLineSearchSetPreCheck() SNESLineSearchSetComputeNorms()
391 
392 M*/
393 PETSC_EXTERN PetscErrorCode SNESCreate_NEWTONLS(SNES snes)
394 {
395   PetscErrorCode ierr;
396   SNES_NEWTONLS  *neP;
397 
398   PetscFunctionBegin;
399   snes->ops->setup          = SNESSetUp_NEWTONLS;
400   snes->ops->solve          = SNESSolve_NEWTONLS;
401   snes->ops->destroy        = SNESDestroy_NEWTONLS;
402   snes->ops->setfromoptions = SNESSetFromOptions_NEWTONLS;
403   snes->ops->view           = SNESView_NEWTONLS;
404   snes->ops->reset          = SNESReset_NEWTONLS;
405 
406   snes->npcside = PC_RIGHT;
407   snes->usesksp = PETSC_TRUE;
408   snes->usesnpc = PETSC_TRUE;
409 
410   snes->alwayscomputesfinalresidual = PETSC_TRUE;
411 
412   ierr          = PetscNewLog(snes,&neP);CHKERRQ(ierr);
413   snes->data    = (void*)neP;
414   PetscFunctionReturn(0);
415 }
416