integer use_stored;
float stored;
float gaussian_random(float mean,float stddev)
  /*
       Routine to generate pseudo-random numbers from a normal distribution with a specific mean and standard deviation
        parameters 
           mean : Mean of source distribution 
           stddev : Standard Deviation of the source distribution
        Uses Polar form of the Box-Muller transformation function
	Since this method generates two random numbers on first call we generate both and use the first,
	Then on second call we use the stored second random variable
	and set use_stored to 0 so that 2 more variables are generated on next call
	Author: Tyche Shepherd
	Date: 2009-09-30
		
	*/
{
	float rand1;
	float rand2;
	float first;
	float factor;
		
	if(use_stored==1){
           //use second number and then reset
	   use_stored=0;	
           return mean+(stddev * stored);
        } else {
	    factor=1.1;
	    while((factor>=1.0) || (factor==0)){
		rand1=(2.0*llFrand(1.01))-1.0;
		while(rand1>1.0){
  		  rand1=(2.0*llFrand(1.01))-1.0;
		}
		rand2=(2.0*llFrand(1.01))-1.0;
		while(rand2>1.0){
  		  rand2=(2.0*llFrand(1.01))-1.0;
		}
		  factor=(rand1*rand1)+(rand2*rand2);
	    }
	    factor=llSqrt((-2.0*llLog(factor))/factor);
	    first=rand1*factor;
	    //store second number and set flag to use this next time
	    stored=rand2*factor;
	    use_stored=1;
	    return mean+(stddev*first);
       }
}
default
{

	state_entry()
	{
       //set initial state of use_stored so that first call generates new numbers
        use_stored=0;   

	}
	touch_start(integer total_number){
	    //just a stub to show how to call the routine
		float value;
		//generate a normal distributed random number from a distribution with mean 100 and std.dev of 10 
		value=gaussian_random(100.0,10.0);
		llSay(0,"Random Number is " +(string) value);
	}

}