package umontreal.iro.lecuyer.randvar;
import umontreal.iro.lecuyer.rng.*;
import umontreal.iro.lecuyer.probdist.*;


/**
 * This class implements random variate generators for the Erlang 
 * distribution with parameters k > 0 and 
 * λ > 0.
 * This Erlang random variable is the sum of k exponentials with 
 * parameter λ and has mean k/λ.
 * 
 * 

 * The (non-static) nextDouble method simply calls inverseF on the
 * distribution. 
 * 
 */
public class ErlangGen extends GammaGen  {
   protected int    k = -1;



   /**
    * Creates an Erlang random variate generator with parameters
    *  k and λ = lambda,
    *   using stream s.
    * 
    */
   public ErlangGen (RandomStream s, int k, double lambda)  {
      super (s, new ErlangDist(k, lambda));
      setParams (k, lambda);
   }


   /**
    * Creates an Erlang random variate generator with parameters
    *  k and 
    * λ = 1, using stream s.
    * 
    */
   public ErlangGen (RandomStream s, int k)  {
      this (s, k, 1.0);
   }

    
   /**
    * Creates a new generator for the distribution dist
    *     and stream s.
    * 
    */
   public ErlangGen (RandomStream s, ErlangDist dist)  {
      super (s, dist);
      if (dist != null)
         setParams (dist.getK(), dist.getLambda());
   }


   /**
    * Generates a new variate from the Erlang distribution with
    *    parameters k = k and λ = lambda,
    *    using stream s.
    * 
    */
   public static double nextDouble (RandomStream s, int k, double lambda)  {
      return ErlangDist.inverseF (k, lambda, 15, s.nextDouble());
   }


   /**
    * Returns the parameter k of this object.
    * 
    * 
    */
   public int getK() {
      return k;
   }


   /**
    * Sets the parameter k and λ of this object.
    * 
    */
   protected void setParams (int k, double lambda) {
      if (lambda <= 0.0)
         throw new IllegalArgumentException ("lambda <= 0");
      if (k <= 0)
         throw new IllegalArgumentException ("k <= 0");
      this.lambda = lambda;
      this.k = k;
   }

}