Date: 2026-03-31T05:46:33+00:00

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 TaoLineSearchMonitor_MT(TaoLineSearch ls)
     24: {
     25:   TaoLineSearch_MT *mt = (TaoLineSearch_MT *)ls->data;

     27:   PetscFunctionBegin;
     28:   PetscCall(PetscViewerASCIIPrintf(ls->viewer, "stx: %g, fx: %g, dgx: %g\n", (double)mt->stx, (double)mt->fx, (double)mt->dgx));
     29:   PetscCall(PetscViewerASCIIPrintf(ls->viewer, "sty: %g, fy: %g, dgy: %g\n", (double)mt->sty, (double)mt->fy, (double)mt->dgy));
     30:   PetscFunctionReturn(PETSC_SUCCESS);
     31: }

     33: static PetscErrorCode TaoLineSearchApply_MT(TaoLineSearch ls, Vec x, PetscReal *f, Vec g, Vec s)
     34: {
     35:   TaoLineSearch_MT *mt     = (TaoLineSearch_MT *)ls->data;
     36:   PetscReal         xtrapf = 4.0;
     37:   PetscReal         finit, width, width1, dginit, fm, fxm, fym, dgm, dgxm, dgym;
     38:   PetscReal         dgx, dgy, dg, dg2, fx, fy, stx, sty, dgtest;
     39:   PetscReal         ftest1 = 0.0, ftest2 = 0.0;
     40:   PetscInt          i, stage1, n1, n2, nn1, nn2;
     41:   PetscReal         bstepmin1, bstepmin2, bstepmax, ostepmin, ostepmax;
     42:   PetscBool         g_computed = PETSC_FALSE; /* to prevent extra gradient computation */

     44:   PetscFunctionBegin;
     45:   ls->reason = TAOLINESEARCH_CONTINUE_ITERATING;
     46:   PetscCall(TaoLineSearchMonitor(ls, 0, *f, 0.0));
     47:   /* Check work vector */
     48:   if (!mt->work) {
     49:     PetscCall(VecDuplicate(x, &mt->work));
     50:     mt->x = x;
     51:     PetscCall(PetscObjectReference((PetscObject)mt->x));
     52:   } else if (x != mt->x) {
     53:     PetscCall(VecDestroy(&mt->work));
     54:     PetscCall(VecDuplicate(x, &mt->work));
     55:     PetscCall(PetscObjectDereference((PetscObject)mt->x));
     56:     mt->x = x;
     57:     PetscCall(PetscObjectReference((PetscObject)mt->x));
     58:   }

     60:   ostepmax = ls->stepmax;
     61:   ostepmin = ls->stepmin;

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

     79:   PetscCall(VecDot(g, s, &dginit));
     80:   if (PetscIsInfOrNanReal(dginit)) {
     81:     PetscCall(PetscInfo(ls, "Initial Line Search step * g is infinity or NaN (%g)\n", (double)dginit));
     82:     ls->reason = TAOLINESEARCH_FAILED_INFORNAN;
     83:     PetscFunctionReturn(PETSC_SUCCESS);
     84:   }
     85:   if (dginit >= 0.0) {
     86:     PetscCall(PetscInfo(ls, "Initial Line Search step * g is not descent direction (%g)\n", (double)dginit));
     87:     ls->reason = TAOLINESEARCH_FAILED_ASCENT;
     88:     PetscFunctionReturn(PETSC_SUCCESS);
     89:   }

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

    105:   stx = 0.0;
    106:   fx  = finit;
    107:   dgx = dginit;
    108:   sty = 0.0;
    109:   fy  = finit;
    110:   dgy = dginit;

    112:   ls->step = ls->initstep;
    113:   for (i = 0; i < ls->max_funcs; i++) {
    114:     /* Set min and max steps to correspond to the interval of uncertainty */
    115:     if (mt->bracket) {
    116:       ls->stepmin = PetscMin(stx, sty);
    117:       ls->stepmax = PetscMax(stx, sty);
    118:     } else {
    119:       ls->stepmin = stx;
    120:       ls->stepmax = ls->step + xtrapf * (ls->step - stx);
    121:     }

    123:     /* Force the step to be within the bounds */
    124:     ls->step = PetscMax(ls->step, ls->stepmin);
    125:     ls->step = PetscMin(ls->step, ls->stepmax);

    127:     /* If an unusual termination is to occur, then let step be the lowest
    128:      point obtained thus far */
    129:     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))
    130:       ls->step = stx;

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

    134:     if (ls->step == 0.0) {
    135:       PetscCall(PetscInfo(ls, "Step size is zero.\n"));
    136:       ls->reason = TAOLINESEARCH_HALTED_LOWERBOUND;
    137:       break;
    138:     }

    140:     if (ls->bounded) PetscCall(VecMedian(ls->lower, mt->work, ls->upper, mt->work));
    141:     /* Make sure user code doesn't mess with the non-updated solution */
    142:     PetscCall(VecLockReadPush(x));
    143:     if (ls->usegts) {
    144:       PetscCall(TaoLineSearchComputeObjectiveAndGTS(ls, mt->work, f, &dg));
    145:       g_computed = PETSC_FALSE;
    146:     } else {
    147:       PetscCall(TaoLineSearchComputeObjectiveAndGradient(ls, mt->work, f, g));
    148:       g_computed = PETSC_TRUE;
    149:       if (ls->bounded) {
    150:         PetscCall(VecDot(g, x, &dg));
    151:         PetscCall(VecDot(g, mt->work, &dg2));
    152:         dg = (dg2 - dg) / ls->step;
    153:       } else {
    154:         PetscCall(VecDot(g, s, &dg));
    155:       }
    156:     }
    157:     PetscCall(VecLockReadPop(x));

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

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

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

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

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

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

    195:     /* Checks for bad cases */
    196:     if ((mt->bracket && (ls->step <= ls->stepmin || ls->step >= ls->stepmax)) || !mt->infoc) {
    197:       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"));
    198:       ls->reason = TAOLINESEARCH_HALTED_OTHER;
    199:       break;
    200:     }
    201:     if (ls->step == ls->stepmax && *f <= ftest1 && dg <= dgtest) {
    202:       PetscCall(PetscInfo(ls, "Step is at the upper bound, stepmax (%g)\n", (double)ls->stepmax));
    203:       ls->reason = TAOLINESEARCH_HALTED_UPPERBOUND;
    204:       break;
    205:     }
    206:     if (ls->step == ls->stepmin && *f >= ftest1 && dg >= dgtest) {
    207:       PetscCall(PetscInfo(ls, "Step is at the lower bound, stepmin (%g)\n", (double)ls->stepmin));
    208:       ls->reason = TAOLINESEARCH_HALTED_LOWERBOUND;
    209:       break;
    210:     }
    211:     if (mt->bracket && (ls->stepmax - ls->stepmin <= ls->rtol * ls->stepmax)) {
    212:       PetscCall(PetscInfo(ls, "Relative width of interval of uncertainty is at most rtol (%g)\n", (double)ls->rtol));
    213:       ls->reason = TAOLINESEARCH_HALTED_RTOL;
    214:       break;
    215:     }

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

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

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

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

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

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

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

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

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

    275:    Options Database Key:
    276: .  -tao_ls_type more-thuente - use this line search type

    278:    Level: developer

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

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

    301: /*
    302:      The subroutine mcstep is taken from the work of Jorge Nocedal.
    303:      this is a variant of More' and Thuente's routine.

    305:      subroutine mcstep

    307:      the purpose of mcstep is to compute a safeguarded step for
    308:      a linesearch and to update an interval of uncertainty for
    309:      a minimizer of the function.

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

    318:      the subroutine statement is

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

    323:      where

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

    331:        sty, fy, and dy are variables which specify the step,
    332:          the function, and the derivative at the other endpoint of
    333:          the interval of uncertainty. On output these parameters are
    334:          updated appropriately.

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

    341:        bracket is a logical variable which specifies if a minimizer
    342:          has been bracketed.  If the minimizer has not been bracketed
    343:          then on input bracket must be set false.  If the minimizer
    344:          is bracketed then on output bracket is set true.

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

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

    354:      subprograms called

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

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

    361: */

    363: static PetscErrorCode Tao_mcstep(TaoLineSearch ls, PetscReal *stx, PetscReal *fx, PetscReal *dx, PetscReal *sty, PetscReal *fy, PetscReal *dy, PetscReal *stp, PetscReal *fp, PetscReal *dp)
    364: {
    365:   TaoLineSearch_MT *mtP = (TaoLineSearch_MT *)ls->data;
    366:   PetscReal         gamma1, p, q, r, s, sgnd, stpc, stpf, stpq, theta;
    367:   PetscInt          bound;

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

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

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

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

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

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

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

    434:     mtP->infoc = 3;
    435:     bound      = 1;
    436:     theta      = 3 * (*fx - *fp) / (*stp - *stx) + *dx + *dp;
    437:     s          = PetscMax(PetscAbsReal(theta), PetscAbsReal(*dx));
    438:     s          = PetscMax(s, PetscAbsReal(*dp));

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

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

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

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

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

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