CPraxis Class Reference

#include <CPraxis.h>

Collaboration diagram for CPraxis:

Classes
struct	Global
struct	Q

Public Member Functions
	CPraxis ()
C_FLOAT64	flin_ (C_INT *, C_INT *, C_FLOAT64 *, FPraxis *, C_FLOAT64 *, C_INT *)
int	min_ (C_INT *, C_INT *, C_INT *, C_FLOAT64 *, C_FLOAT64 *, C_FLOAT64 *, bool *, FPraxis *f, C_FLOAT64 *, C_FLOAT64 *, C_FLOAT64 *, C_FLOAT64 *)
int	minfit_ (C_INT *, C_INT *, C_FLOAT64 *, C_FLOAT64 *, C_FLOAT64 *, C_FLOAT64 *)
C_FLOAT64	praxis_ (C_FLOAT64 *t0, C_FLOAT64 *machep, C_FLOAT64 *h0, C_INT *n, C_INT *prin, C_FLOAT64 *x, FPraxis *f, C_FLOAT64 *fmin)
int	print_ (C_INT *n, C_FLOAT64 *x, C_INT *prin, C_FLOAT64 *fmin)
int	quad_ (C_INT *, FPraxis *f, C_FLOAT64 *, C_FLOAT64 *, C_FLOAT64 *, C_FLOAT64 *)
	~CPraxis ()

Private Attributes
Global	global_1
CRandom *	mpRandom
Q	q_1

Detailed Description

Definition at line 61 of file CPraxis.h.

Constructor & Destructor Documentation

CPraxis::CPraxis

(

)

Definition at line 58 of file CPraxis.cpp.

References CRandom::createGenerator(), and mpRandom.

                :
    mpRandom(NULL)
{
  mpRandom = CRandom::createGenerator();
}

CPraxis::~CPraxis

(

)

Definition at line 64 of file CPraxis.cpp.

References mpRandom, and pdelete.

{
  pdelete(mpRandom);
}

Member Function Documentation

C_FLOAT64 CPraxis::flin_	(	C_INT *	n,
		C_INT *	j,
		C_FLOAT64 *	l,
		FPraxis *	f,
		C_FLOAT64 *	x,
		C_INT *	nf
	)

Definition at line 1591 of file CPraxis.cpp.

References C_FLOAT64, C_INT, CPraxis::Q::q0, CPraxis::Q::q1, q_1, CPraxis::Q::qa, CPraxis::Q::qb, CPraxis::Q::qc, CPraxis::Q::qd0, CPraxis::Q::qd1, and CPraxis::Q::v.

Referenced by min_().

{
  /* System generated locals */
  C_INT i__1;
  C_FLOAT64 ret_val;

  /* Local variables */
  static C_INT i__;
  static C_FLOAT64 t[100];

  /* ...FLIN IS THE FUNCTION OF ONE REAL VARIABLE L THAT IS MINIMIZED */
  /*   BY THE SUBROUTINE MIN... */
  /* Parameter adjustments */
  --x;

  /* Function Body */
  if (*j == 0)
    {
      goto L2;
    }

  /* ...THE SEARCH IS LINEAR... */
  i__1 = *n;

  for (i__ = 1; i__ <= i__1; ++i__)
    {
      /* L1: */
      t[i__ - 1] = x[i__] + *l * q_1.v[i__ + *j * 100 - 101];
    }

  goto L4;
  /* ...THE SEARCH IS ALONG A PARABOLIC SPACE CURVE... */
L2:
  q_1.qa = *l * (*l - q_1.qd1) / (q_1.qd0 * (q_1.qd0 + q_1.qd1));
  q_1.qb = (*l + q_1.qd0) * (q_1.qd1 - *l) / (q_1.qd0 * q_1.qd1);
  q_1.qc = *l * (*l + q_1.qd0) / (q_1.qd1 * (q_1.qd0 + q_1.qd1));
  i__1 = *n;

  for (i__ = 1; i__ <= i__1; ++i__)
    {
      /* L3: */
      t[i__ -1] = q_1.qa * q_1.q0[i__ - 1] + q_1.qb * x[i__] + q_1.qc *
                  q_1.q1[i__ - 1];
    }

  /* ...THE FUNCTION EVALUATION COUNTER NF IS INCREMENTED... */
L4:
  ++(*nf);
  ret_val = (*f)(t, n);
  return ret_val;
} /* flin_ */

int CPraxis::min_	(	C_INT *	n,
		C_INT *	j,
		C_INT *	nits,
		C_FLOAT64 *	d2,
		C_FLOAT64 *	x1,
		C_FLOAT64 *	f1,
		bool *	fk,
		FPraxis *	f,
		C_FLOAT64 *	x,
		C_FLOAT64 *	t,
		C_FLOAT64 *	machep,
		C_FLOAT64 *	h__
	)

Definition at line 1329 of file CPraxis.cpp.

References C_FLOAT64, C_INT, dmax, dmin, CPraxis::Global::dmin__, flin_(), CPraxis::Global::fx, global_1, CPraxis::Global::ldt, CPraxis::Global::nf, CPraxis::Global::nl, q_1, TRUE_, and CPraxis::Q::v.

Referenced by praxis_(), and quad_().

{
  /* System generated locals */
  C_INT i__1;
  C_FLOAT64 d__1, d__2;

  /* Local variables */
  static C_FLOAT64 temp;
  static C_INT i__, k;
  static C_FLOAT64 s, small, d1, f0, f2, m2, m4, t2, x2, fm;
  static bool dz;
  static C_FLOAT64 xm, sf1, sx1;

  /* ...THE SUBROUTINE MIN MINIMIZES F FROM X IN THE DIRECTION V(*,J) UNLESS */
  /*   J IS LESS THAN 1, WHEN A QUADRATIC SEARCH IS MADE IN THE PLANE */
  /*   DEFINED BY Q0,Q1,X. */
  /*   D2 IS EITHER ZERO OR AN APPROXIMATION TO HALF F". */
  /*   ON ENTRY, X1 IS AN ESTIMATE OF THE DISTANCE FROM X TO THE MINIMUM */
  /*   ALONG V(*,J) (OR, IF J=0, A CURVE).  ON RETURN, X1 IS THE DISTANCE */
  /*   FOUND. */
  /*   IF FK=.TRUE., THEN F1 IS FLIN(X1).  OTHERWISE X1 AND F1 ARE IGNORED */
  /*   ON ENTRY UNLESS FINAL FX IS GREATER THAN F1. */
  /*   NITS CONTROLS THE NUMBER OF TIMES AN ATTEMPT WILL BE MADE TO HALVE */
  /*   THE INTERVAL. */
  /* Parameter adjustments */
  --x;

  /* Function Body */
  /* Computing 2nd power */
  d__1 = *machep;
  small = d__1 * d__1;
  m2 = sqrt(*machep);
  m4 = sqrt(m2);
  sf1 = *f1;
  sx1 = *x1;
  k = 0;
  xm = 0.;
  fm = global_1.fx;
  f0 = global_1.fx;
  dz = *d2 < *machep;
  /* ...FIND THE STEP SIZE... */
  s = 0.;
  i__1 = *n;

  for (i__ = 1; i__ <= i__1; ++i__)
    {
      /* L1: */
      /* Computing 2nd power */
      d__1 = x[i__];
      s += d__1 * d__1;
    }

  s = sqrt(s);
  temp = *d2;

  if (dz)
    {
      temp = global_1.dmin__;
    }

  t2 = m4 * sqrt(fabs(global_1.fx) / temp + s * global_1.ldt) + m2 *
       global_1.ldt;
  s = m4 * s + *t;

  if (dz && t2 > s)
    {
      t2 = s;
    }

  t2 = dmax(t2, small);
  /* Computing MIN */
  d__1 = t2, d__2 = *h__ * .01;
  t2 = dmin(d__1, d__2);

  if (!(*fk) || *f1 > fm)
    {
      goto L2;
    }

  xm = *x1;
  fm = *f1;
L2:

  if (*fk && fabs(*x1) >= t2)
    {
      goto L3;
    }

  temp = 1.;

  if (*x1 < 0.)
    {
      temp = -1.;
    }

  *x1 = temp * t2;
  *f1 = flin_(n, j, x1, f, &x[1], &global_1.nf);
L3:

  if (*f1 > fm)
    {
      goto L4;
    }

  xm = *x1;
  fm = *f1;
L4:

  if (! dz)
    {
      goto L6;
    }

  /* ...EVALUATE FLIN AT ANOTHER POINT AND ESTIMATE THE SECOND DERIVATIVE...
   */
  x2 = -(*x1);

  if (f0 >= *f1)
    {
      x2 = *x1 * 2.;
    }

  f2 = flin_(n, j, &x2, f, &x[1], &global_1.nf);

  if (f2 > fm)
    {
      goto L5;
    }

  xm = x2;
  fm = f2;
L5:
  *d2 = (x2 * (*f1 - f0) - *x1 * (f2 - f0)) / (*x1 * x2 * (*x1 - x2));
  /* ...ESTIMATE THE FIRST DERIVATIVE AT 0... */
L6:
  d1 = (*f1 - f0) / *x1 - *x1 * *d2;
  dz = TRUE_;

  /* ...PREDICT THE MINIMUM... */
  if (*d2 > small)
    {
      goto L7;
    }

  x2 = *h__;

  if (d1 >= 0.)
    {
      x2 = -x2;
    }

  goto L8;
L7:
  x2 = d1 * -.5 / *d2;
L8:

  if (fabs(x2) <= *h__)
    {
      goto L11;
    }

  if (x2 <= 0.)
    {
      goto L9;
    }
  else
    {
      goto L10;
    }

L9:
  x2 = -(*h__);
  goto L11;
L10:
  x2 = *h__;
  /* ...EVALUATE F AT THE PREDICTED MINIMUM... */
L11:
  f2 = flin_(n, j, &x2, f, &x[1], &global_1.nf);

  if (k >= *nits || f2 <= f0)
    {
      goto L12;
    }

  /* ...NO SUCCESS, SO TRY AGAIN... */
  ++k;

  if (f0 < *f1 && *x1 * x2 > 0.)
    {
      goto L4;
    }

  x2 *= .5;
  goto L11;
  /* ...INCREMENT THE ONE-DIMENSIONAL SEARCH COUNTER... */
L12:
  ++global_1.nl;

  if (f2 <= fm)
    {
      goto L13;
    }

  x2 = xm;
  goto L14;
L13:
  fm = f2;
  /* ...GET A NEW ESTIMATE OF THE SECOND DERIVATIVE... */
L14:

  if ((d__1 = x2 * (x2 - *x1), fabs(d__1)) <= small)
    {
      goto L15;
    }

  *d2 = (x2 * (*f1 - f0) - *x1 * (fm - f0)) / (*x1 * x2 * (*x1 - x2));
  goto L16;
L15:

  if (k > 0)
    {
      *d2 = 0.;
    }

L16:

  if (*d2 <= small)
    {
      *d2 = small;
    }

  *x1 = x2;
  global_1.fx = fm;

  if (sf1 >= global_1.fx)
    {
      goto L17;
    }

  global_1.fx = sf1;
  *x1 = sx1;
  /* ...UPDATE X FOR LINEAR BUT NOT PARABOLIC SEARCH... */
L17:

  if (*j == 0)
    {
      return 0;
    }

  i__1 = *n;

  for (i__ = 1; i__ <= i__1; ++i__)
    {
      /* L18: */
      x[i__] += *x1 * q_1.v[i__ + *j * 100 - 101];
    }

  return 0;
} /* min_ */

int CPraxis::minfit_	(	C_INT *	m,
		C_INT *	n,
		C_FLOAT64 *	machep,
		C_FLOAT64 *	tol,
		C_FLOAT64 *	ab,
		C_FLOAT64 *	q
	)

Definition at line 800 of file CPraxis.cpp.

References C_FLOAT64, and C_INT.

Referenced by praxis_().

{
  /* System generated locals */
  C_INT ab_dim1, ab_offset, i__1, i__2, i__3;
  C_FLOAT64 d__1, d__2;

  /* Local variables */
  static C_FLOAT64 temp, c__, e[100], f, g, h__;
  static C_INT i__, j, k, l;
  static C_FLOAT64 s, x, y, z__;
  static C_INT l2, ii, kk, kt, ll2, lp1;
  static C_FLOAT64 eps;

  /* ...AN IMPROVED VERSION OF MINFIT (SEE GOLUB AND REINSCH, 1969) */
  /*   RESTRICTED TO M=N,P=0. */
  /*   THE SINGULAR VALUES OF THE ARRAY AB ARE RETURNED IN Q AND AB IS */
  /*   OVERWRITTEN WITH THE ORTHOGONAL MATRIX V SUCH THAT U.DIAG(Q) = AB.V,
  */
  /*   WHERE U IS ANOTHER ORTHOGONAL MATRIX. */
  /* ...HOUSEHOLDER'S REDUCTION TO BIDIAGONAL FORM... */
  /* Parameter adjustments */
  --q;
  ab_dim1 = *m;
  ab_offset = ab_dim1 + 1;
  ab -= ab_offset;

  /* Function Body */
  if (*n == 1)
    {
      goto L200;
    }

  eps = *machep;
  g = 0.;
  x = 0.;
  i__1 = *n;

  for (i__ = 1; i__ <= i__1; ++i__)
    {
      e[i__ - 1] = g;
      s = 0.;
      l = i__ + 1;
      i__2 = *n;

      for (j = i__; j <= i__2; ++j)
        {
          /* L1: */
          /* Computing 2nd power */
          d__1 = ab[j + i__ * ab_dim1];
          s += d__1 * d__1;
        }

      g = 0.;

      if (s < *tol)
        {
          goto L4;
        }

      f = ab[i__ + i__ * ab_dim1];
      g = sqrt(s);

      if (f >= 0.)
        {
          g = -g;
        }

      h__ = f * g - s;
      ab[i__ + i__ * ab_dim1] = f - g;

      if (l > *n)
        {
          goto L4;
        }

      i__2 = *n;

      for (j = l; j <= i__2; ++j)
        {
          f = 0.;
          i__3 = *n;

          for (k = i__; k <= i__3; ++k)
            {
              /* L2: */
              f += ab[k + i__ * ab_dim1] * ab[k + j * ab_dim1];
            }

          f /= h__;
          i__3 = *n;

          for (k = i__; k <= i__3; ++k)
            {
              /* L3: */
              ab[k + j * ab_dim1] += f * ab[k + i__ * ab_dim1];
            }
        }

L4:
      q[i__] = g;
      s = 0.;

      if (i__ == *n)
        {
          goto L6;
        }

      i__3 = *n;

      for (j = l; j <= i__3; ++j)
        {
          /* L5: */
          s += ab[i__ + j * ab_dim1] * ab[i__ + j * ab_dim1];
        }

L6:
      g = 0.;

      if (s < *tol)
        {
          goto L10;
        }

      if (i__ == *n)
        {
          goto L16;
        }

      f = ab[i__ + (i__ + 1) * ab_dim1];
L16:
      g = sqrt(s);

      if (f >= 0.)
        {
          g = -g;
        }

      h__ = f * g - s;

      if (i__ == *n)
        {
          goto L10;
        }

      ab[i__ + (i__ + 1) * ab_dim1] = f - g;
      i__3 = *n;

      for (j = l; j <= i__3; ++j)
        {
          /* L7: */
          e[j - 1] = ab[i__ + j * ab_dim1] / h__;
        }

      i__3 = *n;

      for (j = l; j <= i__3; ++j)
        {
          s = 0.;
          i__2 = *n;

          for (k = l; k <= i__2; ++k)
            {
              /* L8: */
              s += ab[j + k * ab_dim1] * ab[i__ + k * ab_dim1];
            }

          i__2 = *n;

          for (k = l; k <= i__2; ++k)
            {
              /* L9: */
              ab[j + k * ab_dim1] += s * e[k - 1];
            }
        }

L10:
      y = (d__1 = q[i__], fabs(d__1)) + (d__2 = e[i__ - 1], fabs(d__2));

      /* L11: */
      if (y > x)
        {
          x = y;
        }
    }

  /* ...ACCUMULATION OF RIGHT-HAND TRANSFORMATIONS... */
  ab[*n + *n * ab_dim1] = 1.;
  g = e[*n - 1];
  l = *n;
  i__1 = *n;

  for (ii = 2; ii <= i__1; ++ii)
    {
      i__ = *n - ii + 1;

      if (g == 0.)
        {
          goto L23;
        }

      h__ = ab[i__ + (i__ + 1) * ab_dim1] * g;
      i__2 = *n;

      for (j = l; j <= i__2; ++j)
        {
          /* L20: */
          ab[j + i__ * ab_dim1] = ab[i__ + j * ab_dim1] / h__;
        }

      i__2 = *n;

      for (j = l; j <= i__2; ++j)
        {
          s = 0.;
          i__3 = *n;

          for (k = l; k <= i__3; ++k)
            {
              /* L21: */
              s += ab[i__ + k * ab_dim1] * ab[k + j * ab_dim1];
            }

          i__3 = *n;

          for (k = l; k <= i__3; ++k)
            {
              /* L22: */
              ab[k + j * ab_dim1] += s * ab[k + i__ * ab_dim1];
            }
        }

L23:
      i__3 = *n;

      for (j = l; j <= i__3; ++j)
        {
          ab[i__ + j * ab_dim1] = 0.;
          /* L24: */
          ab[j + i__ * ab_dim1] = 0.;
        }

      ab[i__ + i__ * ab_dim1] = 1.;
      g = e[i__ - 1];
      /* L25: */
      l = i__;
    }

  /* ...DIAGONALIZATION OF THE BIDIAGONAL FORM... */
  /* L100: */
  eps *= x;
  i__1 = *n;

  for (kk = 1; kk <= i__1; ++kk)
    {
      k = *n - kk + 1;
      kt = 0;
L101:
      ++kt;

      if (kt <= 30)
        {
          goto L102;
        }

      e[k - 1] = 0.;
      printf("QR FAILED\n");
L102:
      i__3 = k;

      for (ll2 = 1; ll2 <= i__3; ++ll2)
        {
          l2 = k - ll2 + 1;
          l = l2;

          if ((d__1 = e[l - 1], fabs(d__1)) <= eps)
            {
              goto L120;
            }

          if (l == 1)
            {
              goto L103;
            }

          if ((d__1 = q[l - 1], fabs(d__1)) <= eps)
            {
              goto L110;
            }

L103:
          ;
        }

      /* ...CANCELLATION OF E(L) IF L>1... */
L110:
      c__ = 0.;
      s = 1.;
      i__3 = k;

      for (i__ = l; i__ <= i__3; ++i__)
        {
          f = s * e[i__ - 1];
          e[i__ - 1] = c__ * e[i__ - 1];

          if (fabs(f) <= eps)
            {
              goto L120;
            }

          g = q[i__];

          /* ...Q(I) = H = DSQRT(G*G + F*F)... */
          if (fabs(f) < fabs(g))
            {
              goto L113;
            }

          if (f != 0.)
            {
              goto L112;
            }
          else
            {
              goto L111;
            }

L111:
          h__ = 0.;
          goto L114;
L112:
          /* Computing 2nd power */
          d__1 = g / f;
          h__ = fabs(f) * sqrt(d__1 * d__1 + 1);
          goto L114;
L113:
          /* Computing 2nd power */
          d__1 = f / g;
          h__ = fabs(g) * sqrt(d__1 * d__1 + 1);
L114:
          q[i__] = h__;

          if (h__ != 0.)
            {
              goto L115;
            }

          g = 1.;
          h__ = 1.;
L115:
          c__ = g / h__;
          /* L116: */
          s = -f / h__;
        }

      /* ...TEST FOR CONVERGENCE... */
L120:
      z__ = q[k];

      if (l == k)
        {
          goto L140;
        }

      /* ...SHIFT FROM BOTTOM 2*2 MINOR... */
      x = q[l];
      y = q[k - 1];
      g = e[k - 2];
      h__ = e[k - 1];
      f = ((y - z__) * (y + z__) + (g - h__) * (g + h__)) / (h__ * 2 * y);
      g = sqrt(f * f + 1.);
      temp = f - g;

      if (f >= 0.)
        {
          temp = f + g;
        }

      f = ((x - z__) * (x + z__) + h__ * (y / temp - h__)) / x;
      /* ...NEXT QR TRANSFORMATION... */
      c__ = 1.;
      s = 1.;
      lp1 = l + 1;

      if (lp1 > k)
        {
          goto L133;
        }

      i__3 = k;

      for (i__ = lp1; i__ <= i__3; ++i__)
        {
          g = e[i__ - 1];
          y = q[i__];
          h__ = s * g;
          g *= c__;

          if (fabs(f) < fabs(h__))
            {
              goto L123;
            }

          if (f != 0.)
            {
              goto L122;
            }
          else
            {
              goto L121;
            }

L121:
          z__ = 0.;
          goto L124;
L122:
          /* Computing 2nd power */
          d__1 = h__ / f;
          z__ = fabs(f) * sqrt(d__1 * d__1 + 1);
          goto L124;
L123:
          /* Computing 2nd power */
          d__1 = f / h__;
          z__ = fabs(h__) * sqrt(d__1 * d__1 + 1);
L124:
          e[i__ - 2] = z__;

          if (z__ != 0.)
            {
              goto L125;
            }

          f = 1.;
          z__ = 1.;
L125:
          c__ = f / z__;
          s = h__ / z__;
          f = x * c__ + g * s;
          g = -x * s + g * c__;
          h__ = y * s;
          y *= c__;
          i__2 = *n;

          for (j = 1; j <= i__2; ++j)
            {
              x = ab[j + (i__ - 1) * ab_dim1];
              z__ = ab[j + i__ * ab_dim1];
              ab[j + (i__ - 1) * ab_dim1] = x * c__ + z__ * s;
              /* L126: */
              ab[j + i__ * ab_dim1] = -x * s + z__ * c__;
            }

          if (fabs(f) < fabs(h__))
            {
              goto L129;
            }

          if (f != 0.)
            {
              goto L128;
            }
          else
            {
              goto L127;
            }

L127:
          z__ = 0.;
          goto L130;
L128:
          /* Computing 2nd power */
          d__1 = h__ / f;
          z__ = fabs(f) * sqrt(d__1 * d__1 + 1);
          goto L130;
L129:
          /* Computing 2nd power */
          d__1 = f / h__;
          z__ = fabs(h__) * sqrt(d__1 * d__1 + 1);
L130:
          q[i__ - 1] = z__;

          if (z__ != 0.)
            {
              goto L131;
            }

          f = 1.;
          z__ = 1.;
L131:
          c__ = f / z__;
          s = h__ / z__;
          f = c__ * g + s * y;
          /* L132: */
          x = -s * g + c__ * y;
        }

L133:
      e[l - 1] = 0.;
      e[k - 1] = f;
      q[k] = x;
      goto L101;
      /* ...CONVERGENCE:  Q(K) IS MADE NON-NEGATIVE... */
L140:

      if (z__ >= 0.)
        {
          goto L150;
        }

      q[k] = -z__;
      i__3 = *n;

      for (j = 1; j <= i__3; ++j)
        {
          /* L141: */
          ab[j + k * ab_dim1] = -ab[j + k * ab_dim1];
        }

L150:
      ;
    }

  return 0;
L200:
  q[1] = ab[ab_dim1 + 1];
  ab[ab_dim1 + 1] = 1.;
  return 0;
} /* minfit_ */

C_FLOAT64 CPraxis::praxis_	(	C_FLOAT64 *	t0,
		C_FLOAT64 *	machep,
		C_FLOAT64 *	h0,
		C_INT *	n,
		C_INT *	prin,
		C_FLOAT64 *	x,
		FPraxis *	f,
		C_FLOAT64 *	fmin
	)

Definition at line 69 of file CPraxis.cpp.

References c__1, c__2, c__3, c__4, c_false, C_FLOAT64, C_INT, c_true, CPraxis::Global::dmin__, FALSE_, CPraxis::Global::fx, CRandom::getRandomCC(), global_1, CPraxis::Global::ldt, maprnt_(), min_(), minfit_(), mpRandom, CPraxis::Global::nf, CPraxis::Global::nl, print_(), CPraxis::Q::q0, CPraxis::Q::q1, q_1, CPraxis::Q::qd0, CPraxis::Q::qf1, quad_(), sort_(), TRUE_, CPraxis::Q::v, and vcprnt_().

Referenced by COptMethodPraxis::optimise().

{
  /* System generated locals */
  C_INT i__1, i__2, i__3;
  C_FLOAT64 ret_val, d__1;

  /* Local variables */
  static C_FLOAT64 scbd;
  static C_INT idim;
  static bool illc;
  static C_INT klmk;
  static C_FLOAT64 d__[100], h__, ldfac;
  static C_INT i__, j, k;
  static C_FLOAT64 s, t, y[100], large, z__[100], small, value, f1;
  static C_INT k2;
  static C_FLOAT64 m2, m4, t2, df, dn;
  static C_INT kl, ii;
  static C_FLOAT64 sf;
  static C_INT kt;
  static C_FLOAT64 sl, vlarge;
  static C_FLOAT64 vsmall;
  static C_INT km1, im1;
  static C_FLOAT64 dni, lds;
  static C_INT ktm;

  C_FLOAT64 lastValue = std::numeric_limits<C_FLOAT64>::infinity();

  /*                             LAST MODIFIED 3/1/73 */

  /*     PRAXIS RETURNS THE MINIMUM OF THE FUNCTION F(X,N) OF N VARIABLES */
  /*     USING THE PRINCIPAL AXIS METHOD.  THE GRADIENT OF THE FUNCTION IS */
  /*     NOT REQUIRED. */

  /*     FOR A DESCRIPTION OF THE ALGORITHM, SEE CHAPTER SEVEN OF */
  /*     "ALGORITHMS FOR FINDING ZEROS AND EXTREMA OF FUNCTIONS WITHOUT */
  /*     CALCULATING DERIVATIVES" BY RICHARD P BRENT. */

  /*     THE PARAMETERS ARE: */
  /*     T0       IS A TOLERANCE.  PRAXIS ATTEMPTS TO RETURN PRAXIS=F(X) */
  /*              SUCH THAT IF X0 IS THE TRUE LOCAL MINIMUM NEAR X, THEN */
  /*              NORM(X-X0) < T0 + SQUAREROOT(MACHEP)*NORM(X). */
  /*     MACHEP   IS THE MACHINE PRECISION, THE SMALLEST NUMBER SUCH THAT */
  /*              1 + MACHEP > 1.  MACHEP SHOULD BE 16.**-13 (ABOUT */
  /*              2.22D-16) FOR REAL*8 ARITHMETIC ON THE IBM 360. */
  /*     H0       IS THE MAXIMUM STEP SIZE.  H0 SHOULD BE SET TO ABOUT THE */
  /*              MAXIMUM DISTANCE FROM THE INITIAL GUESS TO THE MINIMUM. */
  /*              (IF H0 IS SET TOO LARGE OR TOO SMALL, THE INITIAL RATE OF */
  /*              CONVERGENCE MAY BE SLOW.) */
  /*     N        (AT LEAST TWO) IS THE NUMBER OF VARIABLES UPON WHICH */
  /*              THE FUNCTION DEPENDS. */
  /*     PRIN     CONTROLS THE PRINTING OF INTERMEDIATE RESULTS. */
  /*              IF PRIN=0, NOTHING IS PRINTED. */
  /*              IF PRIN=1, F IS PRINTED AFTER EVERY N+1 OR N+2 LINEAR */
  /*              MINIMIZATIONS.  FINAL X IS PRINTED, BUT INTERMEDIATE X IS */
  /*              PRINTED ONLY IF N IS AT MOST 4. */
  /*              IF PRIN=2, THE SCALE FACTORS AND THE PRINCIPAL VALUES OF */
  /*              THE APPROXIMATING QUADRATIC FORM ARE ALSO PRINTED. */
  /*              IF PRIN=3, X IS ALSO PRINTED AFTER EVERY FEW LINEAR */
  /*              MINIMIZATIONS. */
  /*              IF PRIN=4, THE PRINCIPAL VECTORS OF THE APPROXIMATING */
  /*              QUADRATIC FORM ARE ALSO PRINTED. */
  /*     X        IS AN ARRAY CONTAINING ON ENTRY A GUESS OF THE POINT OF */
  /*              MINIMUM, ON RETURN THE ESTIMATED POINT OF MINIMUM. */
  /*     F(X,N)   IS THE FUNCTION TO BE MINIMIZED.  F SHOULD BE A REAL*8 */
  /*              FUNCTION DECLARED EXTERNAL IN THE CALLING PROGRAM. */
  /*     FMIN     IS AN ESTIMATE OF THE MINIMUM, USED ONLY IN PRINTING */
  /*              INTERMEDIATE RESULTS. */
  /*     THE APPROXIMATING QUADRATIC FORM IS */
  /*              Q(X') = F(X,N) + (1/2) * (X'-X)-TRANSPOSE * A * (X'-X) */
  /*     WHERE X IS THE BEST ESTIMATE OF THE MINIMUM AND A IS */
  /*              INVERSE(V-TRANSPOSE) * D * INVERSE(V) */
  /*     (V(*,*) IS THE MATRIX OF SEARCH DIRECTIONS; D(*) IS THE ARRAY */
  /*     OF SECOND DIFFERENCES).  IF F HAS CONTINUOUS SECOND DERIVATIVES */
  /*     NEAR X0, A WILL TEND TO THE HESSIAN OF F AT X0 AS X APPROACHES X0. */

  /*     IT IS ASSUMED THAT ON FLOATING-POINT UNDERFLOW THE RESULT IS SET */
  /*     TO ZERO. */
  /*     THE USER SHOULD OBSERVE THE COMMENT ON HEURISTIC NUMBERS AFTER */
  /*     THE INITIALIZATION OF MACHINE DEPENDENT NUMBERS. */

  /* .....IF N>20 OR IF N<20 AND YOU NEED MORE SPACE, CHANGE '20' TO THE */
  /*     LARGEST VALUE OF N IN THE NEXT CARD, IN THE CARD 'IDIM=20', AND */
  /*     IN THE DIMENSION STATEMENTS IN SUBROUTINES MINFIT,MIN,FLIN,QUAD. */

  /* .....INITIALIZATION..... */
  /*     MACHINE DEPENDENT NUMBERS: */

  /* Parameter adjustments */
  --x;

  /* Function Body */
  small = *machep * *machep;
  vsmall = small * small;
  large = 1. / small;
  vlarge = 1. / vsmall;
  m2 = sqrt(*machep);
  m4 = sqrt(m2);

  /*     HEURISTIC NUMBERS: */
  /*     IF THE AXES MAY BE BADLY SCALED (WHICH IS TO BE AVOIDED IF */
  /*     POSSIBLE), THEN SET SCBD=10.  OTHERWISE SET SCBD=1. */
  /*     IF THE PROBLEM IS KNOWN TO BE ILL-CONDITIONED, SET ILLC=TRUE. */
  /*     OTHERWISE SET ILLC=FALSE. */
  /*     KTM IS THE NUMBER OF ITERATIONS WITHOUT IMPROVEMENT BEFORE THE */
  /*     ALGORITHM TERMINATES.  KTM=4 IS VERY CAUTIOUS; USUALLY KTM=1 */
  /*     IS SATISFACTORY. */

  scbd = 1.;
  illc = FALSE_;
  ktm = 1;

  ldfac = .01;

  if (illc)
    {
      ldfac = .1;
    }

  kt = 0;
  global_1.nl = 0;
  global_1.nf = 1;
  global_1.fx = (*f)(&x[1], n);
  q_1.qf1 = global_1.fx;
  t = small + fabs(*t0);
  t2 = t;
  global_1.dmin__ = small;
  h__ = *h0;

  if (h__ < t * 100)
    {
      h__ = t * 100;
    }

  global_1.ldt = h__;
  /* .....THE FIRST SET OF SEARCH DIRECTIONS V IS THE IDENTITY MATRIX.....
  */
  i__1 = *n;

  for (i__ = 1; i__ <= i__1; ++i__)
    {
      i__2 = *n;

      for (j = 1; j <= i__2; ++j)
        {
          /* L10: */
          q_1.v[i__ + j * 100 - 101] = 0.;
        }

      /* L20: */
      q_1.v[i__ + i__ * 100 - 101] = 1.;
    }

  d__[0] = 0.;
  q_1.qd0 = 0.;
  i__1 = *n;

  for (i__ = 1; i__ <= i__1; ++i__)
    {
      q_1.q0[i__ - 1] = x[i__];
      /* L30: */
      q_1.q1[i__ - 1] = x[i__];
    }

  if (*prin > 0)
    {
      print_(n, &x[1], prin, fmin);
    }

  /* .....THE MAIN LOOP STARTS HERE..... */
L40:
  sf = d__[0];
  d__[0] = 0.;
  s = 0.;

  /* .....MINIMIZE ALONG THE FIRST DIRECTION V(*,1). */
  /*     FX MUST BE PASSED TO MIN BY VALUE. */
  value = global_1.fx;
  min_(n, &c__1, &c__2, d__, &s, &value, &c_false, f, &x[1], &t,
       machep, &h__);

  if (s > 0.)
    {
      goto L50;
    }

  i__1 = *n;

  for (i__ = 1; i__ <= i__1; ++i__)
    {
      /* L45: */
      q_1.v[i__ - 1] = -q_1.v[i__ - 1];
    }

L50:

  if (sf > d__[0] * .9 && sf * .9 < d__[0])
    {
      goto L70;
    }

  i__1 = *n;

  for (i__ = 2; i__ <= i__1; ++i__)
    {
      /* L60: */
      d__[i__ - 1] = 0.;
    }

  /* .....THE INNER LOOP STARTS HERE..... */
L70:
  i__1 = *n;

  for (k = 2; k <= i__1; ++k)
    {
      i__2 = *n;

      for (i__ = 1; i__ <= i__2; ++i__)
        {
          /* L75: */
          y[i__ - 1] = x[i__];
        }

      sf = global_1.fx;

      if (kt > 0)
        {
          illc = TRUE_;
        }

L80:
      kl = k;
      df = 0.;

      /* .....A RANDOM STEP FOLLOWS (TO AVOID RESOLUTION VALLEYS). */
      /*     PRAXIS ASSUMES THAT RANDOM RETURNS A RANDOM NUMBER UNIFORMLY */
      /*     DISTRIBUTED IN (0,1). */

      if (! illc)
        {
          goto L95;
        }

      i__2 = *n;

      for (i__ = 1; i__ <= i__2; ++i__)
        {
          s = (global_1.ldt * .1 + t2 * pow(10.0, (C_FLOAT64)kt)) * (mpRandom->getRandomCC() - 0.5);
          z__[i__ - 1] = s;
          i__3 = *n;

          for (j = 1; j <= i__3; ++j)
            {
              /* L85: */
              x[j] += s * q_1.v[j + i__ * 100 - 101];
            }

          /* L90: */
        }

      global_1.fx = (*f)(&x[1], n);
      ++global_1.nf;

      /* .....MINIMIZE ALONG THE "NON-CONJUGATE" DIRECTIONS V(*,K),...,V(*,N
      ) */

L95:
      i__2 = *n;

      for (k2 = k; k2 <= i__2; ++k2)
        {
          sl = global_1.fx;
          s = 0.;
          value = global_1.fx;
          min_(n, &k2, &c__2, &d__[k2 - 1], &s, &value, &c_false, f, &
               x[1], &t, machep, &h__);

          if (illc)
            {
              goto L97;
            }

          s = sl - global_1.fx;
          goto L99;
L97:
          /* Computing 2nd power */
          d__1 = s + z__[k2 - 1];
          s = d__[k2 - 1] * (d__1 * d__1);
L99:

          if (df > s)
            {
              goto L105;
            }

          df = s;
          kl = k2;
L105:
          ;
        }

      if (illc || df >= (d__1 = *machep * 100 * global_1.fx, fabs(d__1)))
        {
          goto L110;
        }

      /* .....IF THERE WAS NOT MUCH IMPROVEMENT ON THE FIRST TRY, SET */
      /*     ILLC=TRUE AND START THE INNER LOOP AGAIN..... */

      illc = TRUE_;
      goto L80;
L110:

      if (k == 2 && *prin > 1)
        {
          vcprnt_(&c__1, d__, n);
        }

      /* .....MINIMIZE ALONG THE "CONJUGATE" DIRECTIONS V(*,1),...,V(*,K-1)
      */

      km1 = k - 1;
      i__2 = km1;

      for (k2 = 1; k2 <= i__2; ++k2)
        {
          s = 0.;
          value = global_1.fx;
          min_(n, &k2, &c__2, &d__[k2 - 1], &s, &value, &c_false, f, &
               x[1], &t, machep, &h__);
          /* L120: */
        }

      f1 = global_1.fx;
      global_1.fx = sf;
      lds = 0.;
      i__2 = *n;

      for (i__ = 1; i__ <= i__2; ++i__)
        {
          sl = x[i__];
          x[i__] = y[i__ - 1];
          sl -= y[i__ - 1];
          y[i__ - 1] = sl;
          /* L130: */
          lds += sl * sl;
        }

      lds = sqrt(lds);

      if (lds <= small)
        {
          goto L160;
        }

      /* .....DISCARD DIRECTION V(*,KL). */
      /*     IF NO RANDOM STEP WAS TAKEN, V(*,KL) IS THE "NON-CONJUGATE" */
      /*     DIRECTION ALONG WHICH THE GREATEST IMPROVEMENT WAS MADE..... */

      klmk = kl - k;

      if (klmk < 1)
        {
          goto L141;
        }

      i__2 = klmk;

      for (ii = 1; ii <= i__2; ++ii)
        {
          i__ = kl - ii;
          i__3 = *n;

          for (j = 1; j <= i__3; ++j)
            {
              /* L135: */
              q_1.v[j + (i__ + 1) * 100 - 101] = q_1.v[j + i__ * 100 - 101];
            }

          /* L140: */
          d__[i__] = d__[i__ - 1];
        }

L141:
      d__[k - 1] = 0.;
      i__2 = *n;

      for (i__ = 1; i__ <= i__2; ++i__)
        {
          /* L145: */
          q_1.v[i__ + k * 100 - 101] = y[i__ - 1] / lds;
        }

      /* .....MINIMIZE ALONG THE NEW "CONJUGATE" DIRECTION V(*,K), WHICH IS */
      /*     THE NORMALIZED VECTOR:  (NEW X) - (0LD X)..... */

      value = f1;
      min_(n, &k, &c__4, &d__[k - 1], &lds, &value, &c_true, f, &x[1],
           &t, machep, &h__);

      if (lds > 0.)
        {
          goto L160;
        }

      lds = -lds;
      i__2 = *n;

      for (i__ = 1; i__ <= i__2; ++i__)
        {
          /* L150: */
          q_1.v[i__ + k * 100 - 101] = -q_1.v[i__ + k * 100 - 101];
        }

L160:
      global_1.ldt = ldfac * global_1.ldt;

      if (global_1.ldt < lds)
        {
          global_1.ldt = lds;
        }

      if (*prin > 0)
        {
          print_(n, &x[1], prin, fmin);
        }

      t2 = 0.;
      i__2 = *n;

      for (i__ = 1; i__ <= i__2; ++i__)
        {
          /* L165: */
          /* Computing 2nd power */
          d__1 = x[i__];
          t2 += d__1 * d__1;
        }

      t2 = m2 * sqrt(t2) + t;

      /* .....SEE WHETHER THE LENGTH OF THE STEP TAKEN SINCE STARTING THE */
      /*     INNER LOOP EXCEEDS HALF THE TOLERANCE..... */

      if (global_1.ldt > t2 * .5f)
        {
          kt = -1;
        }

      ++kt;

      if (kt > ktm)
        {
          goto L400;
        }

      /* L170: */
    }

  /* added manually by Pedro Mendes 11/11/1998 */
  // if(callback != 0/*NULL*/) callback(global_1.fx);
  /* .....THE INNER LOOP ENDS HERE. */

  /*     TRY QUADRATIC EXTRAPOLATION IN CASE WE ARE IN A CURVED VALLEY. */

  /* L171: */
  quad_(n, f, &x[1], &t, machep, &h__);
  dn = 0.;
  i__1 = *n;

  for (i__ = 1; i__ <= i__1; ++i__)
    {
      d__[i__ - 1] = 1. / sqrt(d__[i__ - 1]);

      if (dn < d__[i__ - 1])
        {
          dn = d__[i__ - 1];
        }

      /* L175: */
    }

  if (*prin > 3)
    {
      maprnt_(&c__1, q_1.v, &idim, n);
    }

  i__1 = *n;

  for (j = 1; j <= i__1; ++j)
    {
      s = d__[j - 1] / dn;
      i__2 = *n;

      for (i__ = 1; i__ <= i__2; ++i__)
        {
          /* L180: */
          q_1.v[i__ + j * 100 - 101] = s * q_1.v[i__ + j * 100 - 101];
        }
    }

  /* .....SCALE THE AXES TO TRY TO REDUCE THE CONDITION NUMBER..... */

  if (scbd <= 1.)
    {
      goto L200;
    }

  s = vlarge;
  i__2 = *n;

  for (i__ = 1; i__ <= i__2; ++i__)
    {
      sl = 0.;
      i__1 = *n;

      for (j = 1; j <= i__1; ++j)
        {
          /* L182: */
          sl += q_1.v[i__ + j * 100 - 101] * q_1.v[i__ + j * 100 - 101];
        }

      z__[i__ - 1] = sqrt(sl);

      if (z__[i__ - 1] < m4)
        {
          z__[i__ - 1] = m4;
        }

      if (s > z__[i__ - 1])
        {
          s = z__[i__ - 1];
        }

      /* L185: */
    }

  i__2 = *n;

  for (i__ = 1; i__ <= i__2; ++i__)
    {
      sl = s / z__[i__ - 1];
      z__[i__ - 1] = 1. / sl;

      if (z__[i__ - 1] <= scbd)
        {
          goto L189;
        }

      sl = 1. / scbd;
      z__[i__ - 1] = scbd;
L189:
      i__1 = *n;

      for (j = 1; j <= i__1; ++j)
        {
          /* L190: */
          q_1.v[i__ + j * 100 - 101] = sl * q_1.v[i__ + j * 100 - 101];
        }

      /* L195: */
    }

  /* .....CALCULATE A NEW SET OF ORTHOGONAL DIRECTIONS BEFORE REPEATING */
  /*     THE MAIN LOOP. */
  /*     FIRST TRANSPOSE V FOR MINFIT: */

L200:
  i__2 = *n;

  for (i__ = 2; i__ <= i__2; ++i__)
    {
      im1 = i__ - 1;
      i__1 = im1;

      for (j = 1; j <= i__1; ++j)
        {
          s = q_1.v[i__ + j * 100 - 101];
          q_1.v[i__ + j * 100 - 101] = q_1.v[j + i__ * 100 - 101];
          /* L210: */
          q_1.v[j + i__ * 100 - 101] = s;
        }

      /* L220: */
    }

  /* .....CALL MINFIT TO FIND THE SINGULAR VALUE DECOMPOSITION OF V. */
  /*     THIS GIVES THE PRINCIPAL VALUES AND PRINCIPAL DIRECTIONS OF THE */
  /*     APPROXIMATING QUADRATIC FORM WITHOUT SQUARING THE CONDITION */
  /*     NUMBER..... */

  minfit_(&idim, n, machep, &vsmall, q_1.v, d__);

  /* .....UNSCALE THE AXES..... */

  if (scbd <= 1.)
    {
      goto L250;
    }

  i__2 = *n;

  for (i__ = 1; i__ <= i__2; ++i__)
    {
      s = z__[i__ - 1];
      i__1 = *n;

      for (j = 1; j <= i__1; ++j)
        {
          /* L225: */
          q_1.v[i__ + j * 100 - 101] = s * q_1.v[i__ + j * 100 - 101];
        }

      /* L230: */
    }

  i__2 = *n;

  for (i__ = 1; i__ <= i__2; ++i__)
    {
      s = 0.;
      i__1 = *n;

      for (j = 1; j <= i__1; ++j)
        {
          /* L235: */
          /* Computing 2nd power */
          d__1 = q_1.v[j + i__ * 100 - 101];
          s += d__1 * d__1;
        }

      s = sqrt(s);
      d__[i__ - 1] = s * d__[i__ - 1];
      s = 1 / s;
      i__1 = *n;

      for (j = 1; j <= i__1; ++j)
        {
          /* L240: */
          q_1.v[j + i__ * 100 - 101] = s * q_1.v[j + i__ * 100 - 101];
        }

      /* L245: */
    }

L250:
  i__2 = *n;

  for (i__ = 1; i__ <= i__2; ++i__)
    {
      dni = dn * d__[i__ - 1];

      if (dni > large)
        {
          goto L265;
        }

      if (dni < small)
        {
          goto L260;
        }

      d__[i__ - 1] = 1 / (dni * dni);
      goto L270;
L260:
      d__[i__ - 1] = vlarge;
      goto L270;
L265:
      d__[i__ - 1] = vsmall;
L270:
      ;
    }

  /* .....SORT THE EIGENVALUES AND EIGENVECTORS..... */

  sort_(&idim, n, d__, q_1.v);
  global_1.dmin__ = d__[*n - 1];

  if (global_1.dmin__ < small)
    {
      global_1.dmin__ = small;
    }

  illc = FALSE_;

  if (m2 * d__[0] > global_1.dmin__)
    {
      illc = TRUE_;
    }

  if (*prin > 1 && scbd > 1.)
    {
      vcprnt_(&c__2, z__, n);
    }

  if (*prin > 1)
    {
      vcprnt_(&c__3, d__, n);
    }

  if (*prin > 3)
    {
      maprnt_(&c__2, q_1.v, &idim, n);
    }

  /* .....THE MAIN LOOP ENDS HERE..... */

  /* added manually by Pedro Mendes 29/1/1998 */
  /* if(callback != 0) callback(global_1.fx);*/

  // We need a stopping condition for 1 dimensional problems.
  // We compare the values between the last and current steps.
  if (*n > 1 ||
      global_1.fx < lastValue)
    {
      lastValue = global_1.fx;
      goto L40;
    }

  /* .....RETURN..... */

L400:

  if (*prin > 0)
    {
      vcprnt_(&c__4, &x[1], n);
    }

  ret_val = global_1.fx;
  return ret_val;
} /* praxis_ */

int CPraxis::print_	(	C_INT *	n,
		C_FLOAT64 *	x,
		C_INT *	prin,
		C_FLOAT64 *	fmin
	)

Definition at line 1849 of file CPraxis.cpp.

References C_FLOAT64, C_INT, CPraxis::Global::fx, global_1, CPraxis::Global::nf, and CPraxis::Global::nl.

Referenced by praxis_().

{
#ifdef XXXX
  /* System generated locals */
  C_INT i__1;
  C_FLOAT64 d__1;

  /* Local variables */
  C_INT i;
  C_FLOAT64 ln = 0.0;

  /* Builtin functions */
  C_FLOAT64 d_lg10(C_FLOAT64 *);
  /* Parameter adjustments */
  --x;

  /* Function Body */
  printf("AFTER ");
  printf("%d", global_1.nl);
  printf(" LINEAR SEARCHES, THE FUNCTION HAS BEEN EVALUATED ");
  printf("%d TIMES.\n", global_1.nf);
  printf("THE SMALLEST VALUE FOUND IS F(X) = ");
  printf("%g\n", global_1.fx);

  if (global_1.fx <= *fmin)
    {
      goto L1;
    }

  d__1 = global_1.fx - *fmin;
  //   ln = d_lg10(&d__1);
  printf("log (f(x)) - ");
  printf("%g", *fmin);
  printf(" = ");
  printf("%g\n", ln);
  goto L2;
L1:
  printf("LOG (F(x)) -- ");
  printf("%g", *fmin);
  printf(" IS UNDERFINED\n");
L2:

  if (*n > 4 && *prin <= 2)
    {
      return 0;
    }

  i__1 = *n;

  for (i = 1; i <= i__1; ++i)
    {
      printf("x is:");
      printf("%g\n", x[i]);
    }

#endif // XXXX

  return 0;
} /* print_ */

int CPraxis::quad_	(	C_INT *	n,
		FPraxis *	f,
		C_FLOAT64 *	x,
		C_FLOAT64 *	t,
		C_FLOAT64 *	machep,
		C_FLOAT64 *	h__
	)

Definition at line 1717 of file CPraxis.cpp.

References c__0, c__2, C_FLOAT64, C_INT, c_true, CPraxis::Global::fx, global_1, min_(), CPraxis::Global::nl, CPraxis::Q::q0, CPraxis::Q::q1, q_1, CPraxis::Q::qa, CPraxis::Q::qb, CPraxis::Q::qc, CPraxis::Q::qd0, CPraxis::Q::qd1, and CPraxis::Q::qf1.

Referenced by praxis_().

{
  /* System generated locals */
  C_INT i__1;
  C_FLOAT64 d__1;

  /* Local variables */
  static C_INT i__;
  static C_FLOAT64 l, s, value;
  /* ...QUAD LOOKS FOR THE MINIMUM OF F ALONG A CURVE DEFINED BY Q0,Q1,X...
  */
  /* Parameter adjustments */
  --x;

  /* Function Body */
  s = global_1.fx;
  global_1.fx = q_1.qf1;
  q_1.qf1 = s;
  q_1.qd1 = 0.;
  i__1 = *n;

  for (i__ = 1; i__ <= i__1; ++i__)
    {
      s = x[i__];
      l = q_1.q1[i__ - 1];
      x[i__] = l;
      q_1.q1[i__ - 1] = s;
      /* L1: */
      /* Computing 2nd power */
      d__1 = s - l;
      q_1.qd1 += d__1 * d__1;
    }

  q_1.qd1 = sqrt(q_1.qd1);
  l = q_1.qd1;
  s = 0.;

  if (q_1.qd0 <= 0. || q_1.qd1 <= 0. || global_1.nl < *n * 3 * *n)
    {
      goto L2;
    }

  value = q_1.qf1;
  min_(n, &c__0, &c__2, &s, &l, &value, &c_true, f, &x[1], t, machep,
       h__);
  q_1.qa = l * (l - q_1.qd1) / (q_1.qd0 * (q_1.qd0 + q_1.qd1));
  q_1.qb = (l + q_1.qd0) * (q_1.qd1 - l) / (q_1.qd0 * q_1.qd1);
  q_1.qc = l * (l + q_1.qd0) / (q_1.qd1 * (q_1.qd0 + q_1.qd1));
  goto L3;
L2:
  global_1.fx = q_1.qf1;
  q_1.qa = 0.;
  q_1.qb = q_1.qa;
  q_1.qc = 1.;
L3:
  q_1.qd0 = q_1.qd1;
  i__1 = *n;

  for (i__ = 1; i__ <= i__1; ++i__)
    {
      s = q_1.q0[i__ - 1];
      q_1.q0[i__ - 1] = x[i__];
      /* L4: */
      x[i__] = q_1.qa * s + q_1.qb * x[i__] + q_1.qc * q_1.q1[i__ - 1];
    }

  return 0;
} /* quad_ */

Member Data Documentation

Global CPraxis::global_1

private

Definition at line 83 of file CPraxis.h.

Referenced by min_(), praxis_(), print_(), and quad_().

CRandom* CPraxis::mpRandom

private

Definition at line 81 of file CPraxis.h.

Referenced by CPraxis(), praxis_(), and ~CPraxis().

Q CPraxis::q_1

private

Definition at line 84 of file CPraxis.h.

Referenced by flin_(), min_(), praxis_(), and quad_().

---

The documentation for this class was generated from the following files:

• CPraxis.h
• CPraxis.cpp