ngmf.ui.calc.RandomNormal Maven / Gradle / Ivy
/*
* RandomNormal.java
*
* Created on April 27, 2007, 3:55 PM
*
* To change this template, choose Tools | Template Manager
* and open the template in the editor.
*/
package ngmf.ui.calc;
import java.util.Random;
/**
* Utility class that generates normally-distributed
* random values using several algorithms.
*/
public class RandomNormal {
/** mean */
private float mean;
/** standard deviation */
private float stddev;
/** next random value from
* the polar algorithm */
private float nextPolar;
/** true if the next polar
* value is available */
private boolean haveNextPolar = false;
/** generator of uniformly-distributed random values */
private static Random gen = new Random();
/**
* Set the mean and standard deviation.
* @param mean the mean
* @param stddev the standard deviation
*/
public void setParameters(float mean, float stddev) {
this.mean = mean;
this.stddev = stddev;
}
/**
* Compute the next random value using the Central Limit Theorem,
* which states that the averages of sets of uniformly-distributed
* random values are normally distributed.
*/
public float nextCentral() {
// Average 12 uniformly-distributed random values.
float sum = 0.0f;
for (int j = 0; j < 12; ++j)
sum += gen.nextFloat();
// Subtract 6 to center about 0.
return stddev*(sum - 6) + mean;
}
/**
* Compute the next randomn value using the polar algorithm.
* Requires two uniformly-distributed random values in [-1, +1).
* Actually computes two random values and saves the second one
* for the next invokation.
*/
public float nextPolar() {
// If there's a saved value, return it.
if (haveNextPolar) {
haveNextPolar = false;
return nextPolar;
}
float u1, u2, r; // point coordinates and their radius
do {
// u1 and u2 will be uniformly-distributed
// random values in [-1, +1).
u1 = 2*gen.nextFloat() - 1;
u2 = 2*gen.nextFloat() - 1;
// Want radius r inside the unit circle.
r = u1*u1 + u2*u2;
} while (r >= 1);
// Factor incorporates the standard deviation.
float factor = (float) (stddev*Math.sqrt(-2*Math.log(r)/r));
// v1 and v2 are normally-distributed random values.
float v1 = factor*u1 + mean;
float v2 = factor*u2 + mean;
// Save v1 for next time.
nextPolar = v1;
haveNextPolar = true;
return v2;
}
// Constants for the ratio algorithm.
private static final float C1 = (float) Math.sqrt(8/Math.E);
private static final float C2 = (float) (4*Math.exp(0.25));
private static final float C3 = (float) (4*Math.exp(-1.35));
/**
* Compute the next random value using the ratio algorithm.
* Requires two uniformly-distributed random values in [0, 1).
*/
public float nextRatio() {
float u, v, x, xx;
do {
// u and v are two uniformly-distributed random values
// in [0, 1), and u != 0.
while ((u = gen.nextFloat()) == 0); // try again if 0
v = gen.nextFloat();
float y = C1*(v - 0.5f); // y coord of point (u, y)
x = y/u; // ratio of point's coords
xx = x*x;
} while (
(xx > 5f - C2*u) // quick acceptance
&&
( (xx >= C3/u + 1.4f) || // quick rejection
(xx > (float) (-4*Math.log(u))) ) // final test
);
return stddev*x + mean;
}
}
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