xref: /petsc/src/snes/impls/ls/ls.c (revision 55e7fe800d976e85ed2b5cd8bfdef564daa37bd9)
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     ierr = PetscInfo2(snes,"iter=%D, linear solve iterations=%D\n",snes->iter,lits);CHKERRQ(ierr);
228 
229     if (PetscLogPrintInfo) {
230       ierr = SNESNEWTONLSCheckResidual_Private(snes,snes->jacobian,F,Y);CHKERRQ(ierr);
231     }
232 
233     /* Compute a (scaled) negative update in the line search routine:
234          X <- X - lambda*Y
235        and evaluate F = function(X) (depends on the line search).
236     */
237     gnorm = fnorm;
238     ierr  = SNESLineSearchApply(linesearch, X, F, &fnorm, Y);CHKERRQ(ierr);
239     ierr  = SNESLineSearchGetReason(linesearch, &lssucceed);CHKERRQ(ierr);
240     ierr  = SNESLineSearchGetNorms(linesearch, &xnorm, &fnorm, &ynorm);CHKERRQ(ierr);
241     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);
242     if (snes->reason == SNES_DIVERGED_FUNCTION_COUNT) break;
243     SNESCheckFunctionNorm(snes,fnorm);
244     if (lssucceed) {
245       if (snes->stol*xnorm > ynorm) {
246         snes->reason = SNES_CONVERGED_SNORM_RELATIVE;
247         PetscFunctionReturn(0);
248       }
249       if (++snes->numFailures >= snes->maxFailures) {
250         PetscBool ismin;
251         snes->reason = SNES_DIVERGED_LINE_SEARCH;
252         ierr         = SNESNEWTONLSCheckLocalMin_Private(snes,snes->jacobian,F,fnorm,&ismin);CHKERRQ(ierr);
253         if (ismin) snes->reason = SNES_DIVERGED_LOCAL_MIN;
254         break;
255       }
256     }
257     /* Monitor convergence */
258     ierr       = PetscObjectSAWsTakeAccess((PetscObject)snes);CHKERRQ(ierr);
259     snes->iter = i+1;
260     snes->norm = fnorm;
261     ierr       = PetscObjectSAWsGrantAccess((PetscObject)snes);CHKERRQ(ierr);
262     ierr       = SNESLogConvergenceHistory(snes,snes->norm,lits);CHKERRQ(ierr);
263     ierr       = SNESMonitor(snes,snes->iter,snes->norm);CHKERRQ(ierr);
264     /* Test for convergence */
265     ierr = (*snes->ops->converged)(snes,snes->iter,xnorm,ynorm,fnorm,&snes->reason,snes->cnvP);CHKERRQ(ierr);
266     if (snes->reason) break;
267   }
268   if (i == maxits) {
269     ierr = PetscInfo1(snes,"Maximum number of iterations has been reached: %D\n",maxits);CHKERRQ(ierr);
270     if (!snes->reason) snes->reason = SNES_DIVERGED_MAX_IT;
271   }
272   PetscFunctionReturn(0);
273 }
274 /* -------------------------------------------------------------------------- */
275 /*
276    SNESSetUp_NEWTONLS - Sets up the internal data structures for the later use
277    of the SNESNEWTONLS nonlinear solver.
278 
279    Input Parameter:
280 .  snes - the SNES context
281 .  x - the solution vector
282 
283    Application Interface Routine: SNESSetUp()
284 
285    Notes:
286    For basic use of the SNES solvers, the user need not explicitly call
287    SNESSetUp(), since these actions will automatically occur during
288    the call to SNESSolve().
289  */
290 PetscErrorCode SNESSetUp_NEWTONLS(SNES snes)
291 {
292   PetscErrorCode ierr;
293 
294   PetscFunctionBegin;
295   ierr = SNESSetUpMatrices(snes);CHKERRQ(ierr);
296   if (snes->npcside== PC_LEFT && snes->functype == SNES_FUNCTION_DEFAULT) snes->functype = SNES_FUNCTION_PRECONDITIONED;
297   PetscFunctionReturn(0);
298 }
299 /* -------------------------------------------------------------------------- */
300 
301 PetscErrorCode SNESReset_NEWTONLS(SNES snes)
302 {
303   PetscFunctionBegin;
304   PetscFunctionReturn(0);
305 }
306 
307 /*
308    SNESDestroy_NEWTONLS - Destroys the private SNES_NEWTONLS context that was created
309    with SNESCreate_NEWTONLS().
310 
311    Input Parameter:
312 .  snes - the SNES context
313 
314    Application Interface Routine: SNESDestroy()
315  */
316 PetscErrorCode SNESDestroy_NEWTONLS(SNES snes)
317 {
318   PetscErrorCode ierr;
319 
320   PetscFunctionBegin;
321   ierr = SNESReset_NEWTONLS(snes);CHKERRQ(ierr);
322   ierr = PetscFree(snes->data);CHKERRQ(ierr);
323   PetscFunctionReturn(0);
324 }
325 /* -------------------------------------------------------------------------- */
326 
327 /*
328    SNESView_NEWTONLS - Prints info from the SNESNEWTONLS data structure.
329 
330    Input Parameters:
331 .  SNES - the SNES context
332 .  viewer - visualization context
333 
334    Application Interface Routine: SNESView()
335 */
336 static PetscErrorCode SNESView_NEWTONLS(SNES snes,PetscViewer viewer)
337 {
338   PetscErrorCode ierr;
339   PetscBool      iascii;
340 
341   PetscFunctionBegin;
342   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr);
343   if (iascii) {
344   }
345   PetscFunctionReturn(0);
346 }
347 
348 /* -------------------------------------------------------------------------- */
349 /*
350    SNESSetFromOptions_NEWTONLS - Sets various parameters for the SNESNEWTONLS method.
351 
352    Input Parameter:
353 .  snes - the SNES context
354 
355    Application Interface Routine: SNESSetFromOptions()
356 */
357 static PetscErrorCode SNESSetFromOptions_NEWTONLS(PetscOptionItems *PetscOptionsObject,SNES snes)
358 {
359   PetscErrorCode ierr;
360   SNESLineSearch linesearch;
361 
362   PetscFunctionBegin;
363   if (!snes->linesearch) {
364     ierr = SNESGetLineSearch(snes, &linesearch);CHKERRQ(ierr);
365     ierr = SNESLineSearchSetType(linesearch, SNESLINESEARCHBT);CHKERRQ(ierr);
366   }
367   PetscFunctionReturn(0);
368 }
369 
370 /* -------------------------------------------------------------------------- */
371 /*MC
372       SNESNEWTONLS - Newton based nonlinear solver that uses a line search
373 
374    Options Database:
375 +   -snes_linesearch_type <bt> - bt,basic.  Select line search type
376 .   -snes_linesearch_order <3> - 2, 3. Selects the order of the line search for bt
377 .   -snes_linesearch_norms <true> - Turns on/off computation of the norms for basic linesearch (SNESLineSearchSetComputeNorms())
378 .   -snes_linesearch_alpha <alpha> - Sets alpha used in determining if reduction in function norm is sufficient
379 .   -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)
380 .   -snes_linesearch_minlambda <minlambda>  - Sets the minimum lambda the line search will tolerate
381 .   -snes_linesearch_monitor - print information about progress of line searches
382 -   -snes_linesearch_damping - damping factor used for basic line search
383 
384     Notes:
385     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