package org.eclipse.stem.core.math;


/*******************************************************************************
 * Copyright (c) 2010 IBM Corporation and others.
 * All rights reserved. This program and the accompanying materials
 * are made available under the terms of the Eclipse Public License v1.0
 * which accompanies this distribution, and is available at
 * http://www.eclipse.org/legal/epl-v10.html
 *
 * Contributors:
 *     IBM Corporation - initial API and implementation
 *******************************************************************************/

/**
 * Utility primarily used by stochastic models
 * This technique makes a random pick from a binomial distribution.
 * The complex part of this operation is to compute the binomial coefficient
 * efficiently (see for example: http://en.wikipedia.org/wiki/Binomial_distribution)
 * In order to do the computation for large N (large S) we compute the log of the binomial coefficient
 * so we do a sum (instead of a factorial product) and then exponentiate the result. 
 */
public class BinomialDistributionUtil {

	 /**
	  * Returns the random pick from a binomial dist
	  * given 0<=rndVar<=1
	  * This sums the binomial distribution and returns the k value with that integrated probability
	  * @param p The probability
	  * @param n N, (e.g. susceptible)	   
	  * @param rndVAR Random number
	  * @return K Random pick
	  **/ 
	 public static int fastPickFromBinomialDist(double p, int n, double rndVAR){
		 if(p == 0 || n == 0) return 0;
		 double Bsum = 0.0;
		 // compute this once
		 double lnFactorialN = lnFactorial(n);
		 double lnFactorialK = 0.0;
		 double lnFactorialN_K = lnFactorialN;
		 int n_k = n;
		 for(int k = 0; k <= n; k ++) {
			 
			 if(k>=1) {
				 // count up
				 lnFactorialK += Math.log((double)k);
			 
				 // count down for n-k
				 lnFactorialN_K -= Math.log((double)n_k);
				 n_k -= 1;
			 }
			 // do the entire computation in log space
			 double logB = lnFactorialN - lnFactorialK - lnFactorialN_K;
			 // now instead of multiplying by p^k * (1-p)^n-k
			 // we add
			 // logB + k*log(p) + (n-k)*log(1-p);
			 logB += (k*Math.log(p))  + ( (n-k) * Math.log (1-p) );
			 // NOW we take the exponent
			 Bsum += Math.exp(logB);
			 if (Bsum >= rndVAR) return k;
		 }
		 return n;
	 }
	 
	   
	 /**
	  * compute the log(n!)
	  * @param n
	  * @return log(n!)
	  */
	   static double lnFactorial(int n) {
	      double retVal = 0.0;
	
	      for (int i = 1; i <= n; i++) {
	    	  retVal += Math.log((double)i);
	      }
	       
	      return retVal;
	   }
}