/*******************************************************************************
* Copyright (c) 2010 Haifeng Li
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*******************************************************************************/
package smile.stat.distribution;
import org.junit.After;
import org.junit.AfterClass;
import org.junit.Before;
import org.junit.BeforeClass;
import org.junit.Test;
import static org.junit.Assert.*;
/**
*
* @author Haifeng Li
*/
public class GaussianDistributionTest {
public GaussianDistributionTest() {
}
@BeforeClass
public static void setUpClass() throws Exception {
}
@AfterClass
public static void tearDownClass() throws Exception {
}
@Before
public void setUp() {
}
@After
public void tearDown() {
}
/**
* Test of constructor, of class GaussianDistribution.
*/
@Test
public void testGaussianDistribution() {
System.out.println("GaussianDistribution");
GaussianDistribution instance = new GaussianDistribution(3, 2.1);
double[] data = new double[1000];
for (int i = 0; i < data.length; i++)
data[i] = instance.rand();
GaussianDistribution est = new GaussianDistribution(data);
assertEquals(0.0, (est.mean() - 3.0) / 3.0, 0.1);
assertEquals(0.0, (est.sd() - 2.1) / 2.1, 0.1);
}
/**
* Test of npara method, of class Exponential.
*/
@Test
public void testNpara() {
System.out.println("npara");
GaussianDistribution instance = new GaussianDistribution(3.0, 2.0);
instance.rand();
assertEquals(2, instance.npara());
}
/**
* Test of mean method, of class Exponential.
*/
@Test
public void testMean() {
System.out.println("mean");
GaussianDistribution instance = new GaussianDistribution(0.0, 1.0);
instance.rand();
assertEquals(0.0, instance.mean(), 1E-7);
instance = new GaussianDistribution(1.0, 2.0);
instance.rand();
assertEquals(1.0, instance.mean(), 1E-7);
instance = new GaussianDistribution(2.0, 0.5);
instance.rand();
assertEquals(2.0, instance.mean(), 1E-7);
instance = new GaussianDistribution(3.0, 3.8);
instance.rand();
assertEquals(3.0, instance.mean(), 1E-7);
}
/**
* Test of var method, of class Exponential.
*/
@Test
public void testVar() {
System.out.println("var");
GaussianDistribution instance = new GaussianDistribution(0.0, 1.0);
instance.rand();
assertEquals(1.0, instance.var(), 1E-7);
instance = new GaussianDistribution(1.0, 2.0);
instance.rand();
assertEquals(4.0, instance.var(), 1E-7);
instance = new GaussianDistribution(2.0, 0.5);
instance.rand();
assertEquals(0.25, instance.var(), 1E-7);
instance = new GaussianDistribution(3.0, 3.8);
instance.rand();
assertEquals(14.44, instance.var(), 1E-7);
}
/**
* Test of sd method, of class Exponential.
*/
@Test
public void testSd() {
System.out.println("sd");
GaussianDistribution instance = new GaussianDistribution(0.0, 1.0);
instance.rand();
assertEquals(1.0, instance.sd(), 1E-7);
instance = new GaussianDistribution(1.0, 2.0);
instance.rand();
assertEquals(2.0, instance.sd(), 1E-7);
instance = new GaussianDistribution(2.0, 0.5);
instance.rand();
assertEquals(0.5, instance.sd(), 1E-7);
instance = new GaussianDistribution(3.0, 3.8);
instance.rand();
assertEquals(3.8, instance.sd(), 1E-7);
}
/**
* Test of entropy method, of class Exponential.
*/
@Test
public void testEntropy() {
System.out.println("entropy");
GaussianDistribution instance = new GaussianDistribution(0.0, 1.0);
instance.rand();
assertEquals(1.418939, instance.entropy(), 1E-6);
instance = new GaussianDistribution(1.0, 2.0);
instance.rand();
assertEquals(2.112086, instance.entropy(), 1E-6);
instance = new GaussianDistribution(2.0, 0.5);
instance.rand();
assertEquals(0.7257914, instance.entropy(), 1E-6);
instance = new GaussianDistribution(3.0, 3.8);
instance.rand();
assertEquals(2.753940, instance.entropy(), 1E-6);
}
/**
* Test of p method, of class Gaussian.
*/
@Test
public void testP() {
System.out.println("p");
GaussianDistribution instance = new GaussianDistribution(4.0, 3.0);
instance.rand();
assertEquals(2.482015e-06, instance.p(-10), 1E-10);
assertEquals(0.01799699, instance.p(-2), 1E-7);
assertEquals(0.1064827, instance.p(2), 1E-7);
assertEquals(0.1257944, instance.p(3), 1E-7);
assertEquals(0.1329808, instance.p(4), 1E-7);
assertEquals(0.1257944, instance.p(5), 1E-7);
assertEquals(0.1064827, instance.p(6), 1E-7);
assertEquals(0.0806569, instance.p(7), 1E-7);
assertEquals(0.01799699, instance.p(10), 1E-7);
assertEquals(8.85434e-08, instance.p(20), 1E-12);
}
/**
* Test of logP method, of class Exponential.
*/
@Test
public void testLogP() {
System.out.println("logP");
GaussianDistribution instance = new GaussianDistribution(4.0, 3.0);
instance.rand();
assertEquals(-12.90644, instance.logp(-10), 1E-5);
assertEquals(-4.017551, instance.logp(-2), 1E-6);
assertEquals(-2.517551, instance.logp(1.0), 1E-6);
assertEquals(-2.239773, instance.logp(2.0), 1E-6);
assertEquals(-2.073106, instance.logp(3.0), 1E-6);
assertEquals(-2.017551, instance.logp(4.0), 1E-6);
assertEquals(-4.017551, instance.logp(10), 1E-6);
assertEquals(-16.23977, instance.logp(20), 1E-5);
}
/**
* Test of cdf method, of class Gaussian.
*/
@Test
public void testCdf() {
System.out.println("cdf");
GaussianDistribution instance = new GaussianDistribution(4.0, 3.0);
instance.rand();
assertEquals(1.530627e-06, instance.cdf(-10), 1E-12);
assertEquals(0.02275013, instance.cdf(-2), 1E-7);
assertEquals(0.2524925, instance.cdf(2), 1E-7);
assertEquals(0.3694413, instance.cdf(3), 1E-7);
assertEquals(0.5000000, instance.cdf(4), 1E-7);
assertEquals(0.6305587, instance.cdf(5), 1E-7);
assertEquals(0.7475075, instance.cdf(6), 1E-7);
assertEquals(0.8413447, instance.cdf(7), 1E-7);
assertEquals(0.9772499, instance.cdf(10), 1E-7);
assertEquals(0.9998771, instance.cdf(15), 1E-7);
assertEquals(1.0000000, instance.cdf(20), 1E-7);
}
/**
* Test of cdf method, of class Gaussian.
*/
@Test
public void testQuantile() {
System.out.println("quantile");
GaussianDistribution instance = new GaussianDistribution(4.0, 3.0);
instance.rand();
assertEquals(1.475136, instance.quantile(0.2), 1E-6);
assertEquals(2.426798, instance.quantile(0.3), 1E-6);
assertEquals(3.239959, instance.quantile(0.4), 1E-6);
assertEquals(4.000000, instance.quantile(0.5), 1E-6);
assertEquals(4.760041, instance.quantile(0.6), 1E-6);
assertEquals(5.573202, instance.quantile(0.7), 1E-6);
}
}