/*  Nucleotide Sequence Generator - seq-gen, version 1.2.5 */
/*  (c) Copyright 1996-2001, Andrew Rambaut & Nick Grassly */
/*  Department of Zoology, University of Oxford            */

#include <math.h>

#include "random.h"
#include "gamma.h"


/* The following code comes from tools.c in Yang's PAML package */

double LnGamma (double alpha);
double IncompleteGamma (double x, double alpha, double ln_gamma_alpha);
double PointNormal (double prob);
double PointChi2 (double prob, double v);

	
double rndgamma1 (double s);
double rndgamma2 (double s);

double rndgamma (double s)
{
	double	r=0.0;
	
	if (s <= 0.0)      
		return 0;
	else if (s < 1.0)  
		r = rndgamma1 (s);
	else if (s > 1.0)  
		r = rndgamma2 (s);
	else           
		r =- log(rndu());
	return (r);
}


double rndgamma1 (double s)
{

	double			r, x=0.0, small=1e-37, w;
	static double	a, p, uf, ss=10.0, d;
	
	if (s!=ss) 
		{
		a  = 1.0-s;
		p  = a/(a+s*exp(-a));
		uf = p*pow(small/a,s);
		d  = a*log(a);
		ss = s;
		}
	for (;;) 
		{
		r = rndu();
		if (r > p)        
			x = a-log((1.0-r)/(1.0-p)), w=a*log(x)-d;
		else if (r>uf)  
			x = a*pow(r/p,1/s), w=x;
		else            
			return (0.0);
		r = rndu();
		if (1.0-r <= w && r > 0.0)
			if (r*(w+1.0) >= 1.0 || -log(r) <= w)  
				continue;
		break;
		}
	return (x);
}


double rndgamma2 (double s)
{

	double			r ,d, f, g, x;
	static double	b, h, ss=0;
	
	if (s!=ss) 
		{
		b  = s-1.0;
		h  = sqrt(3.0*s-0.75);
		ss = s;
		}
	for (;;) 
		{
		r = rndu();
		g = r-r*r;
		f = (r-0.5)*h/sqrt(g);
		x = b+f;
		if (x <= 0.0) 
			continue;
		r = rndu();
		d = 64*r*r*g*g*g;
		if (d*x < x-2.0*f*f || log(d) < 2*(b*log(x/b)-f))  
			break;
		}
	return (x);
}


double LnGamma (double alpha)
{
/* returns ln(gamma(alpha)) for alpha>0, accurate to 10 decimal places.  
   Stirling's formula is used for the central polynomial part of the procedure.
   Pike MC & Hill ID (1966) Algorithm 291: Logarithm of the gamma function.
   Communications of the Association for Computing Machinery, 9:684
*/
   double x=alpha, f=0, z;

   if (x<7) {
      f=1;  z=x-1;
      while (++z<7)  f*=z;
      x=z;   f=-log(f);
   }
   z = 1/(x*x);
   return  f + (x-0.5)*log(x) - x + .918938533204673 
	  + (((-.000595238095238*z+.000793650793651)*z-.002777777777778)*z
	       +.083333333333333)/x;  
}

double IncompleteGamma (double x, double alpha, double ln_gamma_alpha)
{
/* returns the incomplete gamma ratio I(x,alpha) where x is the upper 
	   limit of the integration and alpha is the shape parameter.
   returns (-1) if in error
   ln_gamma_alpha = ln(Gamma(alpha)), is almost redundant.
   (1) series expansion     if (alpha>x || x<=1)
   (2) continued fraction   otherwise
   RATNEST FORTRAN by
   Bhattacharjee GP (1970) The incomplete gamma integral.  Applied Statistics,
   19: 285-287 (AS32)
*/
   int i;
   double p=alpha, g=ln_gamma_alpha;
   double accurate=1e-8, overflow=1e30;
   double factor, gin=0, rn=0, a=0,b=0,an=0,dif=0, term=0, pn[6];

   if (x==0) return (0);
   if (x<0 || p<=0) return (-1);

   factor=exp(p*log(x)-x-g);   
   if (x>1 && x>=p) goto l30;
   /* (1) series expansion */
   gin=1;  term=1;  rn=p;
 l20:
   rn++;
   term*=x/rn;   gin+=term;

   if (term > accurate) goto l20;
   gin*=factor/p;
   goto l50;
 l30:
   /* (2) continued fraction */
   a=1-p;   b=a+x+1;  term=0;
   pn[0]=1;  pn[1]=x;  pn[2]=x+1;  pn[3]=x*b;
   gin=pn[2]/pn[3];
 l32:
   a++;  b+=2;  term++;   an=a*term;
   for (i=0; i<2; i++) pn[i+4]=b*pn[i+2]-an*pn[i];
   if (pn[5] == 0) goto l35;
   rn=pn[4]/pn[5];   dif=fabs(gin-rn);
   if (dif>accurate) goto l34;
   if (dif<=accurate*rn) goto l42;
 l34:
   gin=rn;
 l35:
   for (i=0; i<4; i++) pn[i]=pn[i+2];
   if (fabs(pn[4]) < overflow) goto l32;
   for (i=0; i<4; i++) pn[i]/=overflow;
   goto l32;
 l42:
   gin=1-factor*gin;

 l50:
   return (gin);
}


/* functions concerning the CDF and percentage points of the gamma and
   Chi2 distribution
*/
double PointNormal (double prob)
{
/* returns z so that Prob{x<z}=prob where x ~ N(0,1) and (1e-12)<prob<1-(1e-12)
   returns (-9999) if in error
   Odeh RE & Evans JO (1974) The percentage points of the normal distribution.
   Applied Statistics 22: 96-97 (AS70)

   Newer methods:
     Wichura MJ (1988) Algorithm AS 241: the percentage points of the
       normal distribution.  37: 477-484.
     Beasley JD & Springer SG  (1977).  Algorithm AS 111: the percentage 
       points of the normal distribution.  26: 118-121.

*/
   double a0=-.322232431088, a1=-1, a2=-.342242088547, a3=-.0204231210245;
   double a4=-.453642210148e-4, b0=.0993484626060, b1=.588581570495;
   double b2=.531103462366, b3=.103537752850, b4=.0038560700634;
   double y, z=0, p=prob, p1;

   p1 = (p<0.5 ? p : 1-p);
   if (p1<1e-20) return (-9999);

   y = sqrt (log(1/(p1*p1)));   
   z = y + ((((y*a4+a3)*y+a2)*y+a1)*y+a0) / ((((y*b4+b3)*y+b2)*y+b1)*y+b0);
   return (p<0.5 ? -z : z);
}


double PointChi2 (double prob, double v)
{
/* returns z so that Prob{x<z}=prob where x is Chi2 distributed with df=v
   returns -1 if in error.   0.000002<prob<0.999998
   RATNEST FORTRAN by
       Best DJ & Roberts DE (1975) The percentage points of the 
       Chi2 distribution.  Applied Statistics 24: 385-388.  (AS91)
   Converted into C by Ziheng Yang, Oct. 1993.
*/
   double e=.5e-6, aa=.6931471805, p=prob, g;
   double xx, c, ch, a=0,q=0,p1=0,p2=0,t=0,x=0,b=0,s1,s2,s3,s4,s5,s6;

   if (p<.000002 || p>.999998 || v<=0) return (-1);

   g = LnGamma (v/2);
   xx=v/2;   c=xx-1;
   if (v >= -1.24*log(p)) goto l1;

   ch=pow((p*xx*exp(g+xx*aa)), 1/xx);
   if (ch-e<0) return (ch);
   goto l4;
l1:
   if (v>.32) goto l3;
   ch=0.4;   a=log(1-p);
l2:
   q=ch;  p1=1+ch*(4.67+ch);  p2=ch*(6.73+ch*(6.66+ch));
   t=-0.5+(4.67+2*ch)/p1 - (6.73+ch*(13.32+3*ch))/p2;
   ch-=(1-exp(a+g+.5*ch+c*aa)*p2/p1)/t;
   if (fabs(q/ch-1)-.01 <= 0) goto l4;
   else                       goto l2;
  
l3: 
   x=PointNormal (p);
   p1=0.222222/v;   ch=v*pow((x*sqrt(p1)+1-p1), 3.0);
   if (ch>2.2*v+6)  ch=-2*(log(1-p)-c*log(.5*ch)+g);
l4:
   q=ch;   p1=.5*ch;
   if ((t=IncompleteGamma (p1, xx, g))<0) {
      return (-1);
   }
   p2=p-t;
   t=p2*exp(xx*aa+g+p1-c*log(ch));   
   b=t/ch;  a=0.5*t-b*c;

   s1=(210+a*(140+a*(105+a*(84+a*(70+60*a))))) / 420;
   s2=(420+a*(735+a*(966+a*(1141+1278*a))))/2520;
   s3=(210+a*(462+a*(707+932*a)))/2520;
   s4=(252+a*(672+1182*a)+c*(294+a*(889+1740*a)))/5040;
   s5=(84+264*a+c*(175+606*a))/2520;
   s6=(120+c*(346+127*c))/5040;
   ch+=t*(1+0.5*t*s1-b*c*(s1-b*(s2-b*(s3-b*(s4-b*(s5-b*s6))))));
   if (fabs(q/ch-1) > e) goto l4;

   return (ch);
}


#define PointGamma(prob,alpha,beta) PointChi2(prob,2.0*(alpha))/(2.0*(beta))

int DiscreteGamma (double freqK[], double rK[], 
    double alfa, double beta, int K, int median)
{
/* discretization of gamma distribution with equal proportions in each 
   category
*/
   int i;
   double gap05=1.0/(2.0*K), t, factor=alfa/beta*K, lnga1;

   if (median) {
      for (i=0; i<K; i++) rK[i]=PointGamma((i*2.0+1)*gap05, alfa, beta);
      for (i=0,t=0; i<K; i++) t+=rK[i];
      for (i=0; i<K; i++)     rK[i]*=factor/t;
   }
   else {
      lnga1=LnGamma(alfa+1);
      for (i=0; i<K-1; i++)
	 freqK[i]=PointGamma((i+1.0)/K, alfa, beta);
      for (i=0; i<K-1; i++)
	 freqK[i]=IncompleteGamma(freqK[i]*beta, alfa+1, lnga1);
      rK[0] = freqK[0]*factor;
      rK[K-1] = (1-freqK[K-2])*factor;
      for (i=1; i<K-1; i++)  rK[i] = (freqK[i]-freqK[i-1])*factor;
   }
   for (i=0; i<K; i++) freqK[i]=1.0/K;

   return (0);
}