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/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You 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 org.apache.commons.math3.distribution;
import org.junit.Assert;
import org.junit.Test;
/**
* Test cases for AbstractIntegerDistribution default implementations.
*
*/
public class AbstractIntegerDistributionTest {
protected final DiceDistribution diceDistribution = new DiceDistribution();
protected final double p = diceDistribution.probability(1);
@Test
public void testInverseCumulativeProbabilityMethod()
{
double precision = 0.000000000000001;
Assert.assertEquals(1, diceDistribution.inverseCumulativeProbability(0));
Assert.assertEquals(1, diceDistribution.inverseCumulativeProbability((1d-Double.MIN_VALUE)/6d));
Assert.assertEquals(2, diceDistribution.inverseCumulativeProbability((1d+precision)/6d));
Assert.assertEquals(2, diceDistribution.inverseCumulativeProbability((2d-Double.MIN_VALUE)/6d));
Assert.assertEquals(3, diceDistribution.inverseCumulativeProbability((2d+precision)/6d));
Assert.assertEquals(3, diceDistribution.inverseCumulativeProbability((3d-Double.MIN_VALUE)/6d));
Assert.assertEquals(4, diceDistribution.inverseCumulativeProbability((3d+precision)/6d));
Assert.assertEquals(4, diceDistribution.inverseCumulativeProbability((4d-Double.MIN_VALUE)/6d));
Assert.assertEquals(5, diceDistribution.inverseCumulativeProbability((4d+precision)/6d));
Assert.assertEquals(5, diceDistribution.inverseCumulativeProbability((5d-precision)/6d));//Can't use Double.MIN
Assert.assertEquals(6, diceDistribution.inverseCumulativeProbability((5d+precision)/6d));
Assert.assertEquals(6, diceDistribution.inverseCumulativeProbability((6d-precision)/6d));//Can't use Double.MIN
Assert.assertEquals(6, diceDistribution.inverseCumulativeProbability((6d)/6d));
}
@Test
public void testCumulativeProbabilitiesSingleArguments() {
for (int i = 1; i < 7; i++) {
Assert.assertEquals(p * i,
diceDistribution.cumulativeProbability(i), Double.MIN_VALUE);
}
Assert.assertEquals(0.0,
diceDistribution.cumulativeProbability(0), Double.MIN_VALUE);
Assert.assertEquals(1.0,
diceDistribution.cumulativeProbability(7), Double.MIN_VALUE);
}
@Test
public void testCumulativeProbabilitiesRangeArguments() {
int lower = 0;
int upper = 6;
for (int i = 0; i < 2; i++) {
// cum(0,6) = p(0 < X <= 6) = 1, cum(1,5) = 4/6, cum(2,4) = 2/6
Assert.assertEquals(1 - p * 2 * i,
diceDistribution.cumulativeProbability(lower, upper), 1E-12);
lower++;
upper--;
}
for (int i = 0; i < 6; i++) {
Assert.assertEquals(p, diceDistribution.cumulativeProbability(i, i+1), 1E-12);
}
}
/**
* Simple distribution modeling a 6-sided die
*/
class DiceDistribution extends AbstractIntegerDistribution {
public static final long serialVersionUID = 23734213;
private final double p = 1d/6d;
public DiceDistribution() {
super(null);
}
public double probability(int x) {
if (x < 1 || x > 6) {
return 0;
} else {
return p;
}
}
public double cumulativeProbability(int x) {
if (x < 1) {
return 0;
} else if (x >= 6) {
return 1;
} else {
return p * x;
}
}
public double getNumericalMean() {
return 3.5;
}
public double getNumericalVariance() {
return 70/24; // E(X^2) - E(X)^2
}
public int getSupportLowerBound() {
return 1;
}
public int getSupportUpperBound() {
return 6;
}
public final boolean isSupportConnected() {
return true;
}
}
}