//________________________________________________________________________
// See the header file rng.h for a description of the contents of this
// file as well as references and credits.

#include <cmath>
#include "rng.h"

#include <iostream>

//________________________________________________________________________
// Initialize the static component of RNG

ulong RNG::tm = 1234567;
ulong RNG::kn[128], RNG::ke[256];
double RNG::wn[128], RNG::fn[128], RNG::we[256], RNG::fe[256];


//________________________________________________________________________
// RNG::RNOR generates normal variates with rejection.
// nfix() generates variates after rejection in RNOR.
// Despite rejection, this method is faster than Box-Muller.

double RNG::nfix(slong h, ulong i)
{
  const double r = 3.442620; 	// The starting of the right tail
  
  double x, y;
  for(;;) {
    x = h * wn[i];

    // If i == 0, handle the base strip
    if (i == 0) {
      do {
	x = -log(rand_open01()) * 0.2904764;   // .2904764 is 1/r
	y = -log(rand_open01());
      } while (y + y < x * x);
      return ((h > 0) ? r + x : -r - x);
    }
    
    // If i > 0, handle the wedges of other strips
    if (fn[i] + rand_open01() * (fn[i - 1] - fn[i]) < exp(-.5 * x * x))
      return x;
    
    // start all over
    h = UL32toSL32(rand_int32());
    i = h & 127;
    if (ULONG32(std::abs(h)) < kn[i])
      return (h * wn[i]);
  }

} // RNG::nfix

// __________________________________________________________________________
// RNG::REXP generates exponential variates with rejection.
// efix() generates variates after rejection in REXP.
  
double RNG::efix(ulong j, ulong i)
{
  for (;;) {
    if (i == 0)
      return (7.69711 - log(rand_open01()));
    
    const double x = j * we[i];
    if (fe[i] + rand_open01() * (fe[i - 1] - fe[i]) < exp(-x)) 
      return x;
    
    j = rand_int32();
    i = (j & 255);
    if (j < ke[i])
      return (j * we[i]);	
  }
  
} // RNG::efix

// __________________________________________________________________________
// This procedure creates the tables used by RNOR and REXP

void RNG::zigset()
{
  static bool inited = 0;
  if (inited)
    return;
  inited = 1;
  
  // Set up tables for RNOR
  const double m1 = 2147483648.0; // 2^31
  const double vn = 9.91256303526217e-3;
  double tn = 3.442619855899;
  double q = vn / exp(-.5 * tn * tn);
  kn[0] = ULONG32((tn / q) * m1); kn[1] = 0;
  wn[0] = q / m1; wn[127] = tn / m1;
  fn[0]=1.; fn[127] = exp(-.5 * tn * tn);		
  for (uint i = 126; i > 0; i--) {
    const double dn = sqrt(-2 * log(vn / tn + exp(-.5 * tn * tn)));
    kn[i + 1] = ULONG32((dn / tn) * m1);
    fn[i] = exp(-.5 * dn * dn);        
    wn[i] = dn / m1;
    tn = dn;
  }
  
  // Set up tables for REXP
  const double m2 = 4294967296.0; // 2^32
  const double ve = 3.949659822581572e-3;
  double te = 7.697117470131487;
  q = ve / exp(-te);
  ke[0] = ULONG32((te / q) * m2); ke[1] = 0;
  we[0] = q / m2; we[255] = te / m2;
  fe[0] = 1.; fe[255] = exp(-te);		
  for (uint i = 254; i > 0; i--) {
    const double de = -log(ve / te + exp(-te));
    ke[i+1] = ULONG32((de / te) * m2);
    fe[i] = exp(-de);
    we[i] = de / m2;
    te = de;
  }

} // RNG::zigset

// __________________________________________________________________________
// Generate a gamma variate with parameters 'shape' and 'scale'

double RNG::gamma(double shape, double scale)
{
  if (shape < 1.)
    return gamma(shape + 1., scale) * pow(rand_open01(), 1.0 / shape);

  const double d = shape - 1. / 3.;
  const double c = 1. / sqrt(9. * d);
  double x, v;
  for (;;) {
    do {
      x = RNOR();
      v = 1.0 + c * x;
    } while (v <= 0.0);
    v = v * v * v;
    const double u = rand_open01();
    const double x2 = x * x;
    if (u < 1.0 - 0.0331 * x2 * x2)
      return (d * v / scale);
    if (log(u) < 0.5 * x2 + d * (1.0 - v + log(v)))
      return (d * v / scale);
  }

} // RNG::gamma

// __________________________________________________________________________
// Generate a Poisson variate 
// Code essentially copied from R source that is essentially
// ACM Algorithm 599 KPOISS converted to C.

int RNG::poisson(double mu)
{
  const double a0=-0.5, a1= 0.3333333, a2=-0.2500068, a3= 0.2000118,
    a4=-0.1661269, a5= 0.1421878, a6=-0.1384794, a7= 0.1250060;

  const double one_7 = 1.0 / 7.0, one_12 = 1.0 / 12.0, one_24 = 1.0 / 24.0;

  const double fact[10] =
    { 1., 1., 2., 6., 24., 120., 720., 5040., 40320., 362880.  };

  static int l, m;

  static double b1, b2, c, c0, c1, c2, c3;
  static double pp[36], p0, p, q, s, d, omega;
  static double big_l;/* integer "w/o overflow" */
  static double muprev = 0., muprev2 = 0.;/*, muold     = 0.*/

  double del, difmuk= 0., E= 0., fk= 0., fx, fy, g, px, py, t, u= 0., v, x;
  int pois = -1;
  int k, kflag, big_mu, new_big_mu = 0;

  if (mu <= 0.)
    return 0;

  big_mu = mu >= 10.;
  if(big_mu)
    new_big_mu = 0;

  if (!(big_mu && mu == muprev)) {

    if (big_mu) {
      new_big_mu = 1;
      muprev = mu;
      s = sqrt(mu);
      d = 6. * mu * mu;
      big_l = floor(mu - 1.1484);
    }
    else {
      if (mu != muprev) {
        muprev = mu;
        m = (int) ((1.0 < mu) ? mu : 1.0);
        l = 0; /* pp[] is already ok up to pp[l] */
        q = p0 = p = exp(-mu);
      }

      for (;;) {
        u = rand_open01();
        if (u <= p0)
          return 0;

        if (l != 0) {
          for (k = (u <= 0.458) ? 1 : ((l < m) ? l : m);  k <= l; k++)
            if (u <= pp[k])
              return k;
          if (l == 35) /* u > pp[35] */
            continue;
        }
        l++;
        for (k = l; k <= 35; k++) {
          p *= mu / k;
          q += p;
          pp[k] = q;
          if (u <= q) {
            l = k;
            return k;
          }
        }
        l = 35;
      }
    }

  }

  g = mu + s * RNOR();
  if (g >= 0.) {
    pois = int(g);
    if (pois >= big_l)
      return pois;
    fk = pois;
    difmuk = mu - fk;
    u = rand_open01();
    if (d * u >= difmuk * difmuk * difmuk)
      return pois;
  }

  if (new_big_mu || mu != muprev2) {
    muprev2 = mu;
    omega = 1.0 / (sqrt(2.0 * RNGPI) * s);
    b1 = one_24 / mu;
    b2 = 0.3 * b1 * b1;
    c3 = one_7 * b1 * b2;
    c2 = b2 - 15. * c3;
    c1 = b1 - 6. * b2 + 45. * c3;
    c0 = 1. - b1 + 3. * b2 - 15. * c3;
    c = 0.1069 / mu;
  }

  if (g >= 0.) {
    kflag = 0;
    goto Step_F;
  }


  for (;;) {
    E = REXP();
    u = 2 * rand_open01() - 1.;
    t = 1.8 + ((u > 0) ? std::abs(E) : -std::abs(E));
    if (t > -0.6744) {
      pois = int(mu + s * t);
      fk = pois;
      difmuk = mu - fk;
      kflag = 1;
Step_F:
      if (pois < 10) {
        px = -mu;
        py = pow(mu, pois) / fact[pois];
      }
      else {
        del = one_12 / fk;
        del = del * (1. - 4.8 * del * del);
        v = difmuk / fk;
        if (std::abs(v) <= 0.25)
          px = fk * v * v * (((((((a7 * v + a6) * v + a5) * v + a4) *
                      v + a3) * v + a2) * v + a1) * v + a0)
            - del;
        else
          px = fk * log(1. + v) - difmuk - del;
        py = 1.0 / (sqrt(2.0 * RNGPI) * sqrt(fk));
      }
      x = (0.5 - difmuk) / s;
      x *= x;/* x^2 */
      fx = -0.5 * x;
      fy = omega * (((c3 * x + c2) * x + c1) * x + c0);
      if (kflag > 0) {
        if (c * std::abs(u) <= py * exp(px + E) - fy * exp(fx + E))
          break;
      } else
        if (fy - u * fy <= py * exp(px - fx))
          break;
    }
  }
  return pois;

} // RNG::poisson

// __________________________________________________________________________
// Generate a binomial variate 
// Code essentially copied from R source that is essentially
// ACM Algorithm 678 BTPEC converted to C.

int RNG::binomial(double pp, int n)
{
  static double c, fm, npq, p1, p2, p3, p4, qn, xl, xll, xlr, xm, xr;

  static double psave = -1.0;
  static int nsave = -1, m = 0;

  double f, x;

  if (n <= 0 || pp <= 0.) return 0;
  if (pp >= 1.) return n;

  const double p = (pp < 1. - pp) ? pp : 1. - pp;
  const double q = 1. - p;
  const double np = n * p;
  const double r = p / q;
  const double g = r * (n + 1);

  if (pp != psave || n != nsave) {
    psave = pp;
    nsave = n;
    if (np < 30.0) {
      qn = pow(q, (double) n);
      goto L_np_small;
    } else {
      double ffm = np + p;
      m = (int) ffm;
      fm = m;
      npq = np * q;
      p1 = (int)(2.195 * sqrt(npq) - 4.6 * q) + 0.5;
      xm = fm + 0.5;
      xl = xm - p1;
      xr = xm + p1;
      c = 0.134 + 20.5 / (15.3 + fm);
      double al = (ffm - xl) / (ffm - xl * p);
      xll = al * (1.0 + 0.5 * al);
      al = (xr - ffm) / (xr * q);
      xlr = al * (1.0 + 0.5 * al);
      p2 = p1 * (1.0 + c + c);
      p3 = p2 + c / xll;
      p4 = p3 + c / xlr;
    }
  } else if (n == nsave) {
    if (np < 30.0)
      goto L_np_small;
  }

  int i, ix;
  for (;;) {
    double u = rand_open01() * p4;
    double v = rand_open01();
    if (u <= p1) {
      ix = (int) (xm - p1 * v + u);
      goto finish;
    }
    if (u <= p2) {
      x = xl + (u - p1) / c;
      v = v * c + 1.0 - std::abs(xm - x) / p1;
      if (v > 1.0 || v <= 0.)
        continue;
      ix = (int) x;
    } else {
      if (u > p3) {
        ix = (int) (xr - log(v) / xlr);
        if (ix > n)
          continue;
        v *= (u - p3) * xlr;
      } else {/* left tail */
        ix = (int) (xl + log(v) / xll);
        if (ix < 0)
          continue;
        v *= (u - p2) * xll;
      }
    }
    int k = std::abs(ix - m);
    if (k <= 20 || k >= npq / 2 - 1) {
      f = 1.0;
      if (m < ix) {
        for (i = m + 1; i <= ix; i++)
          f *= (g / i - r);
      } else if (m != ix) {
        for (i = ix + 1; i <= m; i++)
          f /= (g / i - r);
      }
      if (v <= f)
        goto finish;
    } else {
      double amaxp, ynorm, alv;
      amaxp = (k / npq) * ((k * (k / 3. + 0.625) + 0.1666666666666) /
               npq + 0.5);
      ynorm = -k * k / (2.0 * npq);
      alv = log(v);
      if (alv < ynorm - amaxp)
        goto finish;
      if (alv <= ynorm + amaxp) {
        double x1, f1, z, w, z2, x2, f2, w2;
        x1 = ix + 1;
        f1 = fm + 1.0;
        z = n + 1 - fm;
        w = n - ix + 1.0;
        z2 = z * z;
        x2 = x1 * x1;
        f2 = f1 * f1;
        w2 = w * w;
        if (alv <= xm * log(f1 / x1) + (n - m + 0.5) * log(z / w) +
	  (ix - m) * log(w * p / (x1 * q)) + (13860.0 - (462.0 -
	  (132.0 - (99.0 - 140.0 / f2) / f2) / f2) / f2) / f1 / 166320.0 +
	  (13860.0 - (462.0 - (132.0 - (99.0 - 140.0 / z2) / z2) / z2) / z2) /
	  z / 166320.0 + (13860.0 - (462.0 - (132.0 - (99.0 - 140.0 / x2) /
	  x2) / x2) / x2) / x1 / 166320.0 + (13860.0 - (462.0 - (132.0 -
	  (99.0 - 140.0 / w2) / w2) / w2) / w2) / w / 166320.)
          goto finish;
      }
    }
  }

 L_np_small:
  for (;;) {
    ix = 0;
    f = qn;
    double u = rand_open01();
    for (;;) {
      if (u < f)
        goto finish;
      if (ix > 110)
        break;
      u -= f;
      ix++;
      f *= (g / ix - r);
    }
  }

 finish:
  if (psave > 0.5)
     ix = n - ix;
  return ix;

} // RNG::binomial

// __________________________________________________________________________

// Generate a sample of size 'n' from a multinomial distribution with
// probabilities given in 'probs'.  Inspired by R source code.

void RNG::multinom(uint n, const vector<double>& probs, vector<uint>& samp)
{
  samp.resize(probs.size());
  RNG::multinom(n, &probs[0], (uint) probs.size(), &samp[0]);
}

void RNG::multinom(uint size, const double* probs, uint num_probs, uint* samp)
{
  if (num_probs == 0) return;
  for (uint i = 0; i < num_probs; i++) samp[i] = 0;
  if (size == 0) return;

  vector<double> fixed_probs(num_probs);
  double total_prob = 0.;
  for (uint i = 0; i < num_probs; i++) {
    const double pp = probs[i];
    //if (std::isfinite(pp) && pp >= 0)
    if ((pp == pp) && pp >= 0)
      total_prob += (fixed_probs[i] = pp);
  }

  if (total_prob == 0.) return;

  for (uint i = 0; i < num_probs-1; i++) {
    if (fixed_probs[i] > 0.) {
      samp[i] = binomial(fixed_probs[i] / total_prob, size);
      size -= samp[i];
    }
    if (size == 0) return;
    total_prob -= fixed_probs[i];
  }
  samp[num_probs - 1] = size;

} // RNG::multinomial

// __________________________________________________________________________
// rng.C

