/**
* Test of getMaxSupport method, of class
* gov.sandia.cognition.learning.util.statistics.UniformDistribution.
*/
public void testGetMaxX() {
System.out.println("getMaxX");
double a = RANDOM.nextGaussian();
double b = a + 1;
UniformDistribution instance = new UniformDistribution(a, b);
assertEquals(b, instance.getMaxSupport());
}
/** Tests what happens when the min == max */
public void testDegenerate() {
System.out.println("CDF.degenerate");
for (int i = 0; i < 100; i++) {
double x = RANDOM.nextGaussian();
UniformDistribution.CDF instance = new UniformDistribution.CDF(x, x);
assertEquals(x, instance.getMinSupport());
assertEquals(x, instance.getMaxSupport());
assertEquals(x, instance.getMean());
assertEquals(0.0, instance.getVariance());
assertEquals(x, instance.sample(RANDOM));
}
}
@Override
public void testCDFConstructors() {
System.out.println("CDF Constructor");
UniformDistribution.CDF u = new UniformDistribution.CDF();
assertEquals(UniformDistribution.DEFAULT_MIN, u.getMinSupport());
assertEquals(UniformDistribution.DEFAULT_MAX, u.getMaxSupport());
double a = RANDOM.nextGaussian();
double b = RANDOM.nextDouble() + a;
u = new UniformDistribution.CDF(a, b);
assertEquals(a, u.getMinSupport());
assertEquals(b, u.getMaxSupport());
UniformDistribution.CDF u2 = new UniformDistribution.CDF(u);
assertEquals(u.getMinSupport(), u2.getMinSupport());
assertEquals(u.getMaxSupport(), u2.getMaxSupport());
}
@Override
public void testCDFKnownValues() {
System.out.println("CDF.knownValues");
for (int i = 0; i < 1000; i++) {
UniformDistribution.CDF instance = this.createInstance().getCDF();
double x = RANDOM.nextGaussian();
double phat = instance.evaluate(x);
double p;
if (x < instance.getMinSupport()) {
p = 0.0;
} else if (x > instance.getMaxSupport()) {
p = 1.0;
} else {
p = (x - instance.getMinSupport()) / (instance.getMaxSupport() - instance.getMinSupport());
}
assertEquals(p, phat, TOLERANCE);
}
}
@Override
public UniformDistribution createInstance() {
double a = RANDOM.nextGaussian();
double b = a + RANDOM.nextDouble() * 2.0;
return new UniformDistribution(a, b);
}