/** generates gaussian's and stuff.    heavily adapted from scott lenser's code!*//* This code is part of the localize package of TeamBots. * Copyright (c) 1999, 2000 by John Sweeney and Carnegie Mellon University */package EDU.cmu.cs.coral.localize;import java.lang.Math;public class GaussianSampler extends Gaussian implements Sampler{        protected Range [] range;    protected Range [] normRange;    protected boolean [] noBounds;    protected static boolean iset;    protected static double gset;    protected static boolean isetTails;    protected static double gsetTails, lastL, lastU;    protected static UniformRandom ur;    public GaussianSampler(int nv, long seed) {	super(nv,seed);		range = new Range[numVars];	noBounds = new boolean[numVars];	normRange = new Range[numVars];		for (int i =0; i < numVars; i++) {	    range[i] = new Range();	   	    noBounds[i] = true;	    normRange[i] = new Range();	}	    	iset = false;	isetTails = false;	ur = new UniformRandom(seed,0.0, 1.0);    }    public GaussianSampler(int nv) {	super(nv);		range = new Range[numVars];	noBounds = new boolean[numVars];	normRange = new Range[numVars];		for (int i =0; i < numVars; i++) {	    range[i] = new Range();	   	    noBounds[i] = true;	    normRange[i] = new Range();	}	    	iset = false;	isetTails = false;	ur = new UniformRandom(getSeed(),0.0, 1.0);    }        public void setRange(int i, double l, double h) {	range[i].low = l;	range[i].high = h;		normRange[i].low = (range[i].low - mean[i]) / dev[i];	normRange[i].high = (range[i].high - mean[i]) / dev[i];		if (range[i].low == Double.MIN_VALUE &&	    range[i].high == Double.MAX_VALUE)	    noBounds[i] = true;	else	    noBounds[i] = false;     }        public void setRange(int i, Range r) {	setRange(i, r.low, r.high);    }            public double generateDist(double meen, double stddev) {	double v1,v2, r, a, fac, res;	v1 = v2 =0.0;	//	UniformRandom  ur = new UniformRandom(getSeed(), -1.0, 1.0);	ur.setRange(-1.0, 1.0);	if (iset == false) {	    a = r = 1.0;	    while (r >= a) {		v1 = ur.getValue();		v2 = ur.getValue();				r = v1*v1 + v2*v2;	    }	    	    fac = Math.sqrt(-2.0*Math.log(r)/r);	    gset = v1*fac;	    iset = true;	    res = v2*fac;	} else {	    iset = false;	    res = gset;	}		return (meen+res*stddev);    }        protected double generateDist(double meen, double stddev, double normL, 				  double normU) {	double l = normL;	double u = normU;       	double fac, r, v1, v2, m, a, res;	//	UniformRandom ur = new UniformRandom(getSeed(), 0, 1.0);	ur.setRange(0.0, 1.0);	do {	    if (isetTails == false || l != lastL || u != lastU) {		lastL = l;		lastU = u;		if (u < 0 || l > 0) {		    m = Math.max(l,-u);		    a = Math.exp(-0.5 * m * m);		    		    do {			ur.setRange(-a,a);			v1 = ur.getValue();			v2 = ur.getValue();			r = v1*v1 + v2*v2;		    } while( r >= a );		} 		else {		    a = 1.0;		    		    do {			ur.setRange(-1.0, 1.0);			v1 = ur.getValue();			v2 = ur.getValue();			r = v1*v1 + v2*v2;		    } while( r >= a );		}		fac = Math.sqrt(-2.0 * Math.log(r) / r);		gsetTails = v1*fac;		isetTails = true;		res = v2*fac;	    }	    else {		isetTails = false;		res = gset;	    }	    if ((u < 0 && res > 0) || (l > 0 && res < 0))		res = -res;	} while (res < l || res > u);		return (meen + res*stddev);    }		    public Sample generateSample() {	Sample s = new Sample();	for (int i =0; i < numVars; i++) {	    if (noBounds[i] == true) {		s.data[i] = generateDist(mean[i], dev[i]);	    }else {		s.data[i] = generateDist(mean[i], dev[i], 					 normRange[i].low, normRange[i].high);	    }	}	return s;    }}