Actual source code: morethuente.c

  1: #include <petsc/private/taolinesearchimpl.h>
  2: #include <../src/tao/linesearch/impls/morethuente/morethuente.h>

  4: /*
  5:    This algorithm is taken from More' and Thuente, "Line search algorithms
  6:    with guaranteed sufficient decrease", Argonne National Laboratory,
  7:    Technical Report MCS-P330-1092.
  8: */

 10: static PetscErrorCode Tao_mcstep(TaoLineSearch ls, PetscReal *stx, PetscReal *fx, PetscReal *dx, PetscReal *sty, PetscReal *fy, PetscReal *dy, PetscReal *stp, PetscReal *fp, PetscReal *dp);

 12: static PetscErrorCode TaoLineSearchDestroy_MT(TaoLineSearch ls)
 13: {
 14:   TaoLineSearch_MT *mt = (TaoLineSearch_MT *)(ls->data);

 16:   PetscFunctionBegin;
 17:   PetscCall(PetscObjectDereference((PetscObject)mt->x));
 18:   PetscCall(VecDestroy(&mt->work));
 19:   PetscCall(PetscFree(ls->data));
 20:   PetscFunctionReturn(PETSC_SUCCESS);
 21: }

 23: static PetscErrorCode TaoLineSearchSetFromOptions_MT(TaoLineSearch ls, PetscOptionItems *PetscOptionsObject)
 24: {
 25:   PetscFunctionBegin;
 26:   PetscFunctionReturn(PETSC_SUCCESS);
 27: }

 29: static PetscErrorCode TaoLineSearchMonitor_MT(TaoLineSearch ls)
 30: {
 31:   TaoLineSearch_MT *mt = (TaoLineSearch_MT *)ls->data;

 33:   PetscFunctionBegin;
 34:   PetscCall(PetscViewerASCIIPrintf(ls->viewer, "stx: %g, fx: %g, dgx: %g\n", (double)mt->stx, (double)mt->fx, (double)mt->dgx));
 35:   PetscCall(PetscViewerASCIIPrintf(ls->viewer, "sty: %g, fy: %g, dgy: %g\n", (double)mt->sty, (double)mt->fy, (double)mt->dgy));
 36:   PetscFunctionReturn(PETSC_SUCCESS);
 37: }

 39: static PetscErrorCode TaoLineSearchApply_MT(TaoLineSearch ls, Vec x, PetscReal *f, Vec g, Vec s)
 40: {
 41:   TaoLineSearch_MT *mt     = (TaoLineSearch_MT *)(ls->data);
 42:   PetscReal         xtrapf = 4.0;
 43:   PetscReal         finit, width, width1, dginit, fm, fxm, fym, dgm, dgxm, dgym;
 44:   PetscReal         dgx, dgy, dg, dg2, fx, fy, stx, sty, dgtest;
 45:   PetscReal         ftest1 = 0.0, ftest2 = 0.0;
 46:   PetscInt          i, stage1, n1, n2, nn1, nn2;
 47:   PetscReal         bstepmin1, bstepmin2, bstepmax, ostepmin, ostepmax;
 48:   PetscBool         g_computed = PETSC_FALSE; /* to prevent extra gradient computation */

 50:   PetscFunctionBegin;
 51:   ls->reason = TAOLINESEARCH_CONTINUE_ITERATING;
 52:   PetscCall(TaoLineSearchMonitor(ls, 0, *f, 0.0));
 53:   /* Check work vector */
 54:   if (!mt->work) {
 55:     PetscCall(VecDuplicate(x, &mt->work));
 56:     mt->x = x;
 57:     PetscCall(PetscObjectReference((PetscObject)mt->x));
 58:   } else if (x != mt->x) {
 59:     PetscCall(VecDestroy(&mt->work));
 60:     PetscCall(VecDuplicate(x, &mt->work));
 61:     PetscCall(PetscObjectDereference((PetscObject)mt->x));
 62:     mt->x = x;
 63:     PetscCall(PetscObjectReference((PetscObject)mt->x));
 64:   }

 66:   ostepmax = ls->stepmax;
 67:   ostepmin = ls->stepmin;

 69:   if (ls->bounded) {
 70:     /* Compute step length needed to make all variables equal a bound */
 71:     /* Compute the smallest steplength that will make one nonbinding variable
 72:      equal the bound */
 73:     PetscCall(VecGetLocalSize(ls->upper, &n1));
 74:     PetscCall(VecGetLocalSize(mt->x, &n2));
 75:     PetscCall(VecGetSize(ls->upper, &nn1));
 76:     PetscCall(VecGetSize(mt->x, &nn2));
 77:     PetscCheck(n1 == n2 && nn1 == nn2, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Variable vector not compatible with bounds vector");
 78:     PetscCall(VecScale(s, -1.0));
 79:     PetscCall(VecBoundGradientProjection(s, x, ls->lower, ls->upper, s));
 80:     PetscCall(VecScale(s, -1.0));
 81:     PetscCall(VecStepBoundInfo(x, s, ls->lower, ls->upper, &bstepmin1, &bstepmin2, &bstepmax));
 82:     ls->stepmax = PetscMin(bstepmax, ls->stepmax);
 83:   }

 85:   PetscCall(VecDot(g, s, &dginit));
 86:   if (PetscIsInfOrNanReal(dginit)) {
 87:     PetscCall(PetscInfo(ls, "Initial Line Search step * g is Inf or Nan (%g)\n", (double)dginit));
 88:     ls->reason = TAOLINESEARCH_FAILED_INFORNAN;
 89:     PetscFunctionReturn(PETSC_SUCCESS);
 90:   }
 91:   if (dginit >= 0.0) {
 92:     PetscCall(PetscInfo(ls, "Initial Line Search step * g is not descent direction (%g)\n", (double)dginit));
 93:     ls->reason = TAOLINESEARCH_FAILED_ASCENT;
 94:     PetscFunctionReturn(PETSC_SUCCESS);
 95:   }

 97:   /* Initialization */
 98:   mt->bracket = 0;
 99:   stage1      = 1;
100:   finit       = *f;
101:   dgtest      = ls->ftol * dginit;
102:   width       = ls->stepmax - ls->stepmin;
103:   width1      = width * 2.0;
104:   PetscCall(VecCopy(x, mt->work));
105:   /* Variable dictionary:
106:    stx, fx, dgx - the step, function, and derivative at the best step
107:    sty, fy, dgy - the step, function, and derivative at the other endpoint
108:    of the interval of uncertainty
109:    step, f, dg - the step, function, and derivative at the current step */

111:   stx = 0.0;
112:   fx  = finit;
113:   dgx = dginit;
114:   sty = 0.0;
115:   fy  = finit;
116:   dgy = dginit;

118:   ls->step = ls->initstep;
119:   for (i = 0; i < ls->max_funcs; i++) {
120:     /* Set min and max steps to correspond to the interval of uncertainty */
121:     if (mt->bracket) {
122:       ls->stepmin = PetscMin(stx, sty);
123:       ls->stepmax = PetscMax(stx, sty);
124:     } else {
125:       ls->stepmin = stx;
126:       ls->stepmax = ls->step + xtrapf * (ls->step - stx);
127:     }

129:     /* Force the step to be within the bounds */
130:     ls->step = PetscMax(ls->step, ls->stepmin);
131:     ls->step = PetscMin(ls->step, ls->stepmax);

133:     /* If an unusual termination is to occur, then let step be the lowest
134:      point obtained thus far */
135:     if (stx != 0 && ((mt->bracket && (ls->step <= ls->stepmin || ls->step >= ls->stepmax)) || (mt->bracket && (ls->stepmax - ls->stepmin <= ls->rtol * ls->stepmax)) || (ls->nfeval + ls->nfgeval >= ls->max_funcs - 1) || mt->infoc == 0))
136:       ls->step = stx;

138:     PetscCall(VecWAXPY(mt->work, ls->step, s, x)); /* W = X + step*S */

140:     if (ls->step == 0.0) {
141:       PetscCall(PetscInfo(ls, "Step size is zero.\n"));
142:       ls->reason = TAOLINESEARCH_HALTED_LOWERBOUND;
143:       break;
144:     }

146:     if (ls->bounded) PetscCall(VecMedian(ls->lower, mt->work, ls->upper, mt->work));
147:     if (ls->usegts) {
148:       PetscCall(TaoLineSearchComputeObjectiveAndGTS(ls, mt->work, f, &dg));
149:       g_computed = PETSC_FALSE;
150:     } else {
151:       PetscCall(TaoLineSearchComputeObjectiveAndGradient(ls, mt->work, f, g));
152:       g_computed = PETSC_TRUE;
153:       if (ls->bounded) {
154:         PetscCall(VecDot(g, x, &dg));
155:         PetscCall(VecDot(g, mt->work, &dg2));
156:         dg = (dg2 - dg) / ls->step;
157:       } else {
158:         PetscCall(VecDot(g, s, &dg));
159:       }
160:     }

162:     /* update bracketing parameters in the MT context for printouts in monitor */
163:     mt->stx = stx;
164:     mt->fx  = fx;
165:     mt->dgx = dgx;
166:     mt->sty = sty;
167:     mt->fy  = fy;
168:     mt->dgy = dgy;
169:     PetscCall(TaoLineSearchMonitor(ls, i + 1, *f, ls->step));

171:     if (i == 0) ls->f_fullstep = *f;

173:     if (PetscIsInfOrNanReal(*f) || PetscIsInfOrNanReal(dg)) {
174:       /* User provided compute function generated Not-a-Number, assume
175:        domain violation and set function value and directional
176:        derivative to infinity. */
177:       *f = PETSC_INFINITY;
178:       dg = PETSC_INFINITY;
179:     }

181:     ftest1 = finit + ls->step * dgtest;
182:     if (ls->bounded) ftest2 = finit + ls->step * dgtest * ls->ftol;

184:     /* Convergence testing */
185:     if ((*f - ftest1 <= PETSC_SMALL * PetscAbsReal(finit)) && (PetscAbsReal(dg) + ls->gtol * dginit <= 0.0)) {
186:       PetscCall(PetscInfo(ls, "Line search success: Sufficient decrease and directional deriv conditions hold\n"));
187:       ls->reason = TAOLINESEARCH_SUCCESS;
188:       break;
189:     }

191:     /* Check Armijo if beyond the first breakpoint */
192:     if (ls->bounded && *f <= ftest2 && ls->step >= bstepmin2) {
193:       PetscCall(PetscInfo(ls, "Line search success: Sufficient decrease.\n"));
194:       ls->reason = TAOLINESEARCH_SUCCESS;
195:       break;
196:     }

198:     /* Checks for bad cases */
199:     if ((mt->bracket && (ls->step <= ls->stepmin || ls->step >= ls->stepmax)) || !mt->infoc) {
200:       PetscCall(PetscInfo(ls, "Rounding errors may prevent further progress. May not be a step satisfying\nsufficient decrease and curvature conditions. Tolerances may be too small.\n"));
201:       ls->reason = TAOLINESEARCH_HALTED_OTHER;
202:       break;
203:     }
204:     if (ls->step == ls->stepmax && *f <= ftest1 && dg <= dgtest) {
205:       PetscCall(PetscInfo(ls, "Step is at the upper bound, stepmax (%g)\n", (double)ls->stepmax));
206:       ls->reason = TAOLINESEARCH_HALTED_UPPERBOUND;
207:       break;
208:     }
209:     if (ls->step == ls->stepmin && *f >= ftest1 && dg >= dgtest) {
210:       PetscCall(PetscInfo(ls, "Step is at the lower bound, stepmin (%g)\n", (double)ls->stepmin));
211:       ls->reason = TAOLINESEARCH_HALTED_LOWERBOUND;
212:       break;
213:     }
214:     if (mt->bracket && (ls->stepmax - ls->stepmin <= ls->rtol * ls->stepmax)) {
215:       PetscCall(PetscInfo(ls, "Relative width of interval of uncertainty is at most rtol (%g)\n", (double)ls->rtol));
216:       ls->reason = TAOLINESEARCH_HALTED_RTOL;
217:       break;
218:     }

220:     /* In the first stage, we seek a step for which the modified function
221:      has a nonpositive value and nonnegative derivative */
222:     if (stage1 && *f <= ftest1 && dg >= dginit * PetscMin(ls->ftol, ls->gtol)) stage1 = 0;

224:     /* A modified function is used to predict the step only if we
225:      have not obtained a step for which the modified function has a
226:      nonpositive function value and nonnegative derivative, and if a
227:      lower function value has been obtained but the decrease is not
228:      sufficient */

230:     if (stage1 && *f <= fx && *f > ftest1) {
231:       fm   = *f - ls->step * dgtest; /* Define modified function */
232:       fxm  = fx - stx * dgtest;      /* and derivatives */
233:       fym  = fy - sty * dgtest;
234:       dgm  = dg - dgtest;
235:       dgxm = dgx - dgtest;
236:       dgym = dgy - dgtest;

238:       /* if (dgxm * (ls->step - stx) >= 0.0) */
239:       /* Update the interval of uncertainty and compute the new step */
240:       PetscCall(Tao_mcstep(ls, &stx, &fxm, &dgxm, &sty, &fym, &dgym, &ls->step, &fm, &dgm));

242:       fx  = fxm + stx * dgtest; /* Reset the function and */
243:       fy  = fym + sty * dgtest; /* gradient values */
244:       dgx = dgxm + dgtest;
245:       dgy = dgym + dgtest;
246:     } else {
247:       /* Update the interval of uncertainty and compute the new step */
248:       PetscCall(Tao_mcstep(ls, &stx, &fx, &dgx, &sty, &fy, &dgy, &ls->step, f, &dg));
249:     }

251:     /* Force a sufficient decrease in the interval of uncertainty */
252:     if (mt->bracket) {
253:       if (PetscAbsReal(sty - stx) >= 0.66 * width1) ls->step = stx + 0.5 * (sty - stx);
254:       width1 = width;
255:       width  = PetscAbsReal(sty - stx);
256:     }
257:   }
258:   if (ls->nfeval + ls->nfgeval > ls->max_funcs) {
259:     PetscCall(PetscInfo(ls, "Number of line search function evals (%" PetscInt_FMT ") > maximum (%" PetscInt_FMT ")\n", ls->nfeval + ls->nfgeval, ls->max_funcs));
260:     ls->reason = TAOLINESEARCH_HALTED_MAXFCN;
261:   }
262:   ls->stepmax = ostepmax;
263:   ls->stepmin = ostepmin;

265:   /* Finish computations */
266:   PetscCall(PetscInfo(ls, "%" PetscInt_FMT " function evals in line search, step = %g\n", ls->nfeval + ls->nfgeval, (double)ls->step));

268:   /* Set new solution vector and compute gradient if needed */
269:   PetscCall(VecCopy(mt->work, x));
270:   if (!g_computed) PetscCall(TaoLineSearchComputeGradient(ls, mt->work, g));
271:   PetscFunctionReturn(PETSC_SUCCESS);
272: }

274: /*MC
275:    TAOLINESEARCHMT - More-Thuente line-search type with cubic interpolation that satisfies both the sufficient decrease and
276:    curvature conditions. This method can take step lengths greater than 1, {cite}`more:92`

278:    Options Database Key:
279: .  -tao_ls_type more-thuente - use this line search type

281:    Level: developer

283: .seealso: `TaoLineSearchCreate()`, `TaoLineSearchSetType()`, `TaoLineSearchApply()`
284: M*/
285: PETSC_EXTERN PetscErrorCode TaoLineSearchCreate_MT(TaoLineSearch ls)
286: {
287:   TaoLineSearch_MT *ctx;

289:   PetscFunctionBegin;
291:   PetscCall(PetscNew(&ctx));
292:   ctx->bracket            = 0;
293:   ctx->infoc              = 1;
294:   ls->data                = (void *)ctx;
295:   ls->initstep            = 1.0;
296:   ls->ops->setup          = NULL;
297:   ls->ops->reset          = NULL;
298:   ls->ops->apply          = TaoLineSearchApply_MT;
299:   ls->ops->destroy        = TaoLineSearchDestroy_MT;
300:   ls->ops->setfromoptions = TaoLineSearchSetFromOptions_MT;
301:   ls->ops->monitor        = TaoLineSearchMonitor_MT;
302:   PetscFunctionReturn(PETSC_SUCCESS);
303: }

305: /*
306:      The subroutine mcstep is taken from the work of Jorge Nocedal.
307:      this is a variant of More' and Thuente's routine.

309:      subroutine mcstep

311:      the purpose of mcstep is to compute a safeguarded step for
312:      a linesearch and to update an interval of uncertainty for
313:      a minimizer of the function.

315:      the parameter stx contains the step with the least function
316:      value. the parameter stp contains the current step. it is
317:      assumed that the derivative at stx is negative in the
318:      direction of the step. if bracket is set true then a
319:      minimizer has been bracketed in an interval of uncertainty
320:      with endpoints stx and sty.

322:      the subroutine statement is

324:      subroutine mcstep(stx,fx,dx,sty,fy,dy,stp,fp,dp,bracket,
325:                        stpmin,stpmax,info)

327:      where

329:        stx, fx, and dx are variables which specify the step,
330:          the function, and the derivative at the best step obtained
331:          so far. The derivative must be negative in the direction
332:          of the step, that is, dx and stp-stx must have opposite
333:          signs. On output these parameters are updated appropriately.

335:        sty, fy, and dy are variables which specify the step,
336:          the function, and the derivative at the other endpoint of
337:          the interval of uncertainty. On output these parameters are
338:          updated appropriately.

340:        stp, fp, and dp are variables which specify the step,
341:          the function, and the derivative at the current step.
342:          If bracket is set true then on input stp must be
343:          between stx and sty. On output stp is set to the new step.

345:        bracket is a logical variable which specifies if a minimizer
346:          has been bracketed.  If the minimizer has not been bracketed
347:          then on input bracket must be set false.  If the minimizer
348:          is bracketed then on output bracket is set true.

350:        stpmin and stpmax are input variables which specify lower
351:          and upper bounds for the step.

353:        info is an integer output variable set as follows:
354:          if info = 1,2,3,4,5, then the step has been computed
355:          according to one of the five cases below. otherwise
356:          info = 0, and this indicates improper input parameters.

358:      subprograms called

360:        fortran-supplied ... abs,max,min,sqrt

362:      argonne national laboratory. minpack project. june 1983
363:      jorge j. more', david j. thuente

365: */

367: static PetscErrorCode Tao_mcstep(TaoLineSearch ls, PetscReal *stx, PetscReal *fx, PetscReal *dx, PetscReal *sty, PetscReal *fy, PetscReal *dy, PetscReal *stp, PetscReal *fp, PetscReal *dp)
368: {
369:   TaoLineSearch_MT *mtP = (TaoLineSearch_MT *)ls->data;
370:   PetscReal         gamma1, p, q, r, s, sgnd, stpc, stpf, stpq, theta;
371:   PetscInt          bound;

373:   PetscFunctionBegin;
374:   /* Check the input parameters for errors */
375:   mtP->infoc = 0;
376:   PetscCheck(!mtP->bracket || (*stp > PetscMin(*stx, *sty) && *stp < PetscMax(*stx, *sty)), PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "bad stp in bracket");
377:   PetscCheck(*dx * (*stp - *stx) < 0.0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "dx * (stp-stx) >= 0.0");
378:   PetscCheck(ls->stepmax >= ls->stepmin, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "stepmax > stepmin");

380:   /* Determine if the derivatives have opposite sign */
381:   sgnd = *dp * (*dx / PetscAbsReal(*dx));

383:   if (*fp > *fx) {
384:     /* Case 1: a higher function value.
385:      The minimum is bracketed. If the cubic step is closer
386:      to stx than the quadratic step, the cubic step is taken,
387:      else the average of the cubic and quadratic steps is taken. */

389:     mtP->infoc = 1;
390:     bound      = 1;
391:     theta      = 3 * (*fx - *fp) / (*stp - *stx) + *dx + *dp;
392:     s          = PetscMax(PetscAbsReal(theta), PetscAbsReal(*dx));
393:     s          = PetscMax(s, PetscAbsReal(*dp));
394:     gamma1     = s * PetscSqrtScalar(PetscPowScalar(theta / s, 2.0) - (*dx / s) * (*dp / s));
395:     if (*stp < *stx) gamma1 = -gamma1;
396:     /* Can p be 0?  Check */
397:     p    = (gamma1 - *dx) + theta;
398:     q    = ((gamma1 - *dx) + gamma1) + *dp;
399:     r    = p / q;
400:     stpc = *stx + r * (*stp - *stx);
401:     stpq = *stx + ((*dx / ((*fx - *fp) / (*stp - *stx) + *dx)) * 0.5) * (*stp - *stx);

403:     if (PetscAbsReal(stpc - *stx) < PetscAbsReal(stpq - *stx)) stpf = stpc;
404:     else stpf = stpc + 0.5 * (stpq - stpc);
405:     mtP->bracket = 1;
406:   } else if (sgnd < 0.0) {
407:     /* Case 2: A lower function value and derivatives of
408:      opposite sign. The minimum is bracketed. If the cubic
409:      step is closer to stx than the quadratic (secant) step,
410:      the cubic step is taken, else the quadratic step is taken. */

412:     mtP->infoc = 2;
413:     bound      = 0;
414:     theta      = 3 * (*fx - *fp) / (*stp - *stx) + *dx + *dp;
415:     s          = PetscMax(PetscAbsReal(theta), PetscAbsReal(*dx));
416:     s          = PetscMax(s, PetscAbsReal(*dp));
417:     gamma1     = s * PetscSqrtScalar(PetscPowScalar(theta / s, 2.0) - (*dx / s) * (*dp / s));
418:     if (*stp > *stx) gamma1 = -gamma1;
419:     p    = (gamma1 - *dp) + theta;
420:     q    = ((gamma1 - *dp) + gamma1) + *dx;
421:     r    = p / q;
422:     stpc = *stp + r * (*stx - *stp);
423:     stpq = *stp + (*dp / (*dp - *dx)) * (*stx - *stp);

425:     if (PetscAbsReal(stpc - *stp) > PetscAbsReal(stpq - *stp)) stpf = stpc;
426:     else stpf = stpq;
427:     mtP->bracket = 1;
428:   } else if (PetscAbsReal(*dp) < PetscAbsReal(*dx)) {
429:     /* Case 3: A lower function value, derivatives of the
430:      same sign, and the magnitude of the derivative decreases.
431:      The cubic step is only used if the cubic tends to infinity
432:      in the direction of the step or if the minimum of the cubic
433:      is beyond stp. Otherwise the cubic step is defined to be
434:      either stepmin or stepmax. The quadratic (secant) step is also
435:      computed and if the minimum is bracketed then the step
436:      closest to stx is taken, else the step farthest away is taken. */

438:     mtP->infoc = 3;
439:     bound      = 1;
440:     theta      = 3 * (*fx - *fp) / (*stp - *stx) + *dx + *dp;
441:     s          = PetscMax(PetscAbsReal(theta), PetscAbsReal(*dx));
442:     s          = PetscMax(s, PetscAbsReal(*dp));

444:     /* The case gamma1 = 0 only arises if the cubic does not tend
445:        to infinity in the direction of the step. */
446:     gamma1 = s * PetscSqrtScalar(PetscMax(0.0, PetscPowScalar(theta / s, 2.0) - (*dx / s) * (*dp / s)));
447:     if (*stp > *stx) gamma1 = -gamma1;
448:     p = (gamma1 - *dp) + theta;
449:     q = (gamma1 + (*dx - *dp)) + gamma1;
450:     r = p / q;
451:     if (r < 0.0 && gamma1 != 0.0) stpc = *stp + r * (*stx - *stp);
452:     else if (*stp > *stx) stpc = ls->stepmax;
453:     else stpc = ls->stepmin;
454:     stpq = *stp + (*dp / (*dp - *dx)) * (*stx - *stp);

456:     if (mtP->bracket) {
457:       if (PetscAbsReal(*stp - stpc) < PetscAbsReal(*stp - stpq)) stpf = stpc;
458:       else stpf = stpq;
459:     } else {
460:       if (PetscAbsReal(*stp - stpc) > PetscAbsReal(*stp - stpq)) stpf = stpc;
461:       else stpf = stpq;
462:     }
463:   } else {
464:     /* Case 4: A lower function value, derivatives of the
465:        same sign, and the magnitude of the derivative does
466:        not decrease. If the minimum is not bracketed, the step
467:        is either stpmin or stpmax, else the cubic step is taken. */

469:     mtP->infoc = 4;
470:     bound      = 0;
471:     if (mtP->bracket) {
472:       theta  = 3 * (*fp - *fy) / (*sty - *stp) + *dy + *dp;
473:       s      = PetscMax(PetscAbsReal(theta), PetscAbsReal(*dy));
474:       s      = PetscMax(s, PetscAbsReal(*dp));
475:       gamma1 = s * PetscSqrtScalar(PetscPowScalar(theta / s, 2.0) - (*dy / s) * (*dp / s));
476:       if (*stp > *sty) gamma1 = -gamma1;
477:       p    = (gamma1 - *dp) + theta;
478:       q    = ((gamma1 - *dp) + gamma1) + *dy;
479:       r    = p / q;
480:       stpc = *stp + r * (*sty - *stp);
481:       stpf = stpc;
482:     } else if (*stp > *stx) {
483:       stpf = ls->stepmax;
484:     } else {
485:       stpf = ls->stepmin;
486:     }
487:   }

489:   /* Update the interval of uncertainty.  This update does not
490:      depend on the new step or the case analysis above. */

492:   if (*fp > *fx) {
493:     *sty = *stp;
494:     *fy  = *fp;
495:     *dy  = *dp;
496:   } else {
497:     if (sgnd < 0.0) {
498:       *sty = *stx;
499:       *fy  = *fx;
500:       *dy  = *dx;
501:     }
502:     *stx = *stp;
503:     *fx  = *fp;
504:     *dx  = *dp;
505:   }

507:   /* Compute the new step and safeguard it. */
508:   stpf = PetscMin(ls->stepmax, stpf);
509:   stpf = PetscMax(ls->stepmin, stpf);
510:   *stp = stpf;
511:   if (mtP->bracket && bound) {
512:     if (*sty > *stx) *stp = PetscMin(*stx + 0.66 * (*sty - *stx), *stp);
513:     else *stp = PetscMax(*stx + 0.66 * (*sty - *stx), *stp);
514:   }
515:   PetscFunctionReturn(PETSC_SUCCESS);
516: }