Date: 2021-03-03T22:27:40+00:00

Actual source code: snesdnest.c
petsc-3.14.5 2021-03-03
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      2: /* fnoise/snesdnest.F -- translated by f2c (version 20020314).
      3: */
      4: #include <petscsys.h>
      5: #define FALSE_ 0
      6: #define TRUE_ 1

      8: /*  Noise estimation routine, written by Jorge More'.  Details are below. */

     10: PETSC_INTERN PetscErrorCode SNESNoise_dnest_(PetscInt*,PetscScalar*,PetscScalar*,PetscScalar*,PetscScalar*,PetscScalar*,PetscInt*,PetscScalar*);

     12: PetscErrorCode SNESNoise_dnest_(PetscInt *nf, double *fval,double *h__,double *fnoise, double *fder2, double *hopt, PetscInt *info, double *eps)
     13: {
     14:   /* Initialized data */

     16:   static double const__[15] = { .71,.41,.23,.12,.063,.033,.018,.0089,
     17:                                 .0046,.0024,.0012,6.1e-4,3.1e-4,1.6e-4,8e-5 };

     19:   /* System generated locals */
     20:   PetscInt i__1;
     21:   double   d__1, d__2, d__3, d__4;

     24:   /* Local variables */
     25:   static double   emin, emax;
     26:   static PetscInt dsgn[6];
     27:   static double   f_max, f_min, stdv;
     28:   static PetscInt i__, j;
     29:   static double   scale;
     30:   static PetscInt mh;
     31:   static PetscInt cancel[6], dnoise;
     32:   static double   err2, est1, est2, est3, est4;

     34: /*     ********** */

     36: /*     Subroutine dnest */

     38: /*     This subroutine estimates the noise in a function */
     39: /*     and provides estimates of the optimal difference parameter */
     40: /*     for a forward-difference approximation. */

     42: /*     The user must provide a difference parameter h, and the */
     43: /*     function value at nf points centered around the current point. */
     44: /*     For example, if nf = 7, the user must provide */

     46: /*        f(x-2*h), f(x-h), f(x), f(x+h),  f(x+2*h), */

     48: /*     in the array fval. The use of nf = 7 function evaluations is */
     49: /*     recommended. */

     51: /*     The noise in the function is roughly defined as the variance in */
     52: /*     the computed value of the function. The noise in the function */
     53: /*     provides valuable information. For example, function values */
     54: /*     smaller than the noise should be considered to be zero. */

     56: /*     This subroutine requires an initial estimate for h. Under estimates */
     57: /*     are usually preferred. If noise is not detected, the user should */
     58: /*     increase or decrease h according to the ouput value of info. */
     59: /*     In most cases, the subroutine detects noise with the initial */
     60: /*     value of h. */

     62: /*     The subroutine statement is */

     64: /*       subroutine dnest(nf,fval,h,hopt,fnoise,info,eps) */

     66: /*     where */

     68: /*       nf is a PetscInt variable. */
     69: /*         On entry nf is the number of function values. */
     70: /*         On exit nf is unchanged. */

     72: /*       f is a double precision array of dimension nf. */
     73: /*         On entry f contains the function values. */
     74: /*         On exit f is overwritten. */

     76: /*       h is a double precision variable. */
     77: /*         On entry h is an estimate of the optimal difference parameter. */
     78: /*         On exit h is unchanged. */

     80: /*       fnoise is a double precision variable. */
     81: /*         On entry fnoise need not be specified. */
     82: /*         On exit fnoise is set to an estimate of the function noise */
     83: /*            if noise is detected; otherwise fnoise is set to zero. */

     85: /*       hopt is a double precision variable. */
     86: /*         On entry hopt need not be specified. */
     87: /*         On exit hopt is set to an estimate of the optimal difference */
     88: /*            parameter if noise is detected; otherwise hopt is set to zero. */

     90: /*       info is a PetscInt variable. */
     91: /*         On entry info need not be specified. */
     92: /*         On exit info is set as follows: */

     94: /*            info = 1  Noise has been detected. */

     96: /*            info = 2  Noise has not been detected; h is too small. */
     97: /*                      Try 100*h for the next value of h. */

     99: /*            info = 3  Noise has not been detected; h is too large. */
    100: /*                      Try h/100 for the next value of h. */

    102: /*            info = 4  Noise has been detected but the estimate of hopt */
    103: /*                      is not reliable; h is too small. */

    105: /*       eps is a double precision work array of dimension nf. */

    107: /*     MINPACK-2 Project. April 1997. */
    108: /*     Argonne National Laboratory. */
    109: /*     Jorge J. More'. */

    111: /*     ********** */
    112:   /* Parameter adjustments */
    113:   --eps;
    114:   --fval;

    116:   /* Function Body */
    117:   *fnoise = 0.;
    118:   *fder2  = 0.;
    119:   *hopt   = 0.;
    120: /*     Compute an estimate of the second derivative and */
    121: /*     determine a bound on the error. */
    122:   mh   = (*nf + 1) / 2;
    123:   est1 = (fval[mh + 1] - fval[mh] * 2 + fval[mh - 1]) / *h__ / *h__;
    124:   est2 = (fval[mh + 2] - fval[mh] * 2 + fval[mh - 2]) / (*h__ * 2) / (*h__ * 2);
    125:   est3 = (fval[mh + 3] - fval[mh] * 2 + fval[mh - 3]) / (*h__ * 3) / (*h__ * 3);
    126:   est4 = (est1 + est2 + est3) / 3;
    127: /* Computing MAX */
    128: /* Computing PETSCMAX */
    129:   d__3 = PetscMax(est1,est2);
    130: /* Computing MIN */
    131:   d__4 = PetscMin(est1,est2);
    132:   d__1 = PetscMax(d__3,est3) - est4;
    133:   d__2 = est4 - PetscMin(d__4,est3);
    134:   err2 = PetscMax(d__1,d__2);
    135: /*      write (2,123) est1, est2, est3 */
    136: /* 123  format ('Second derivative estimates', 3d12.2) */
    137:   if (err2 <= PetscAbsScalar(est4) * .1) *fder2 = est4;
    138:   else if (err2 < PetscAbsScalar(est4))  *fder2 = est3;
    139:   else *fder2 = 0.;

    141: /*     Compute the range of function values. */
    142:   f_min = fval[1];
    143:   f_max = fval[1];
    144:   i__1  = *nf;
    145:   for (i__ = 2; i__ <= i__1; ++i__) {
    146:     /* Computing MIN */
    147:     d__1 = f_min;
    148:     d__2 = fval[i__];
    149:     f_min = PetscMin(d__1,d__2);

    151:     /* Computing MAX */
    152:     d__1 = f_max;
    153:     d__2 = fval[i__];
    154:     f_max = PetscMax(d__1,d__2);
    155:   }
    156: /*     Construct the difference table. */
    157:   dnoise = FALSE_;
    158:   for (j = 1; j <= 6; ++j) {
    159:     dsgn[j - 1]   = FALSE_;
    160:     cancel[j - 1] = FALSE_;
    161:     scale         = 0.;
    162:     i__1          = *nf - j;
    163:     for (i__ = 1; i__ <= i__1; ++i__) {
    164:       fval[i__] = fval[i__ + 1] - fval[i__];
    165:       if (fval[i__] == 0.) cancel[j - 1] = TRUE_;

    167:       /* Computing MAX */
    168:       d__1 = fval[i__];
    169:       d__2 = scale;
    170:       d__3 = PetscAbsScalar(d__1);
    171:       scale = PetscMax(d__2,d__3);
    172:     }

    174:     /*        Compute the estimates for the noise level. */
    175:     if (scale == 0.) stdv = 0.;
    176:     else {
    177:       stdv = 0.;
    178:       i__1 = *nf - j;
    179:       for (i__ = 1; i__ <= i__1; ++i__) {
    180:         /* Computing 2nd power */
    181:         d__1 = fval[i__] / scale;
    182:         stdv += d__1 * d__1;
    183:       }
    184:       stdv = scale * PetscSqrtScalar(stdv / (*nf - j));
    185:     }
    186:     eps[j] = const__[j - 1] * stdv;
    187: /*        Determine differences in sign. */
    188:     i__1 = *nf - j - 1;
    189:     for (i__ = 1; i__ <= i__1; ++i__) {
    190:       /* Computing MIN */
    191:       d__1 = fval[i__];
    192:       d__2 = fval[i__ + 1];
    193:       /* Computing MAX */
    194:       d__3 = fval[i__];
    195:       d__4 = fval[i__ + 1];
    196:       if (PetscMin(d__1,d__2) < 0. && PetscMax(d__3,d__4) > 0.) dsgn[j - 1] = TRUE_;
    197:     }
    198:   }
    199:   /*     First requirement for detection of noise. */
    200:   dnoise = dsgn[3];
    201:   /*     Check for h too small or too large. */
    202:   *info = 0;
    203:   if (f_max == f_min) *info = 2;
    204:   else /* if (complicated condition) */ {
    205:     /* Computing MIN */
    206:     d__1 = PetscAbsScalar(f_max);
    207:     d__2 = PetscAbsScalar(f_min);
    208:     if (f_max - f_min > PetscMin(d__1,d__2) * .1) *info = 3;
    209:   }
    210:   if (*info != 0) return(0);

    212:   /*     Determine the noise level. */
    213:   /* Computing MIN */
    214:   d__1 = PetscMin(eps[4],eps[5]);
    215:   emin = PetscMin(d__1,eps[6]);

    217:   /* Computing MAX */
    218:   d__1 = PetscMax(eps[4],eps[5]);
    219:   emax = PetscMax(d__1,eps[6]);

    221:   if (emax <= emin * 4 && dnoise) {
    222:     *fnoise = (eps[4] + eps[5] + eps[6]) / 3;
    223:     if (*fder2 != 0.) {
    224:       *info = 1;
    225:       *hopt = PetscSqrtScalar(*fnoise / PetscAbsScalar(*fder2)) * 1.68;
    226:     } else {
    227:       *info = 4;
    228:       *hopt = *h__ * 10;
    229:     }
    230:     return(0);
    231:   }

    233:   /* Computing MIN */
    234:   d__1 = PetscMin(eps[3],eps[4]);
    235:   emin = PetscMin(d__1,eps[5]);

    237:   /* Computing MAX */
    238:   d__1 = PetscMax(eps[3],eps[4]);
    239:   emax = PetscMax(d__1,eps[5]);

    241:   if (emax <= emin * 4 && dnoise) {
    242:     *fnoise = (eps[3] + eps[4] + eps[5]) / 3;
    243:     if (*fder2 != 0.) {
    244:       *info = 1;
    245:       *hopt = PetscSqrtScalar(*fnoise / PetscAbsScalar(*fder2)) * 1.68;
    246:     } else {
    247:       *info = 4;
    248:       *hopt = *h__ * 10;
    249:     }
    250:     return(0);
    251:   }
    252: /*     Noise not detected; decide if h is too small or too large. */
    253:   if (!cancel[3]) {
    254:     if (dsgn[3]) *info = 2;
    255:     else *info = 3;
    256:     return(0);
    257:   }
    258:   if (!cancel[2]) {
    259:     if (dsgn[2]) *info = 2;
    260:     else *info = 3;
    261:     return(0);
    262:   }
    263: /*     If there is cancelllation on the third and fourth column */
    264: /*     then h is too small */
    265:   *info = 2;
    266:   return(0);
    267: /*      if (cancel .or. dsgn(3)) then */
    268: /*         info = 2 */
    269: /*      else */
    270: /*         info = 3 */
    271: /*      end if */
    272: } /* dnest_ */