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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.apache.commons.math3.exception.NumberIsTooLargeException;
import org.apache.commons.math3.exception.util.LocalizedFormats;
import org.apache.commons.math3.random.RandomGenerator;
import org.apache.commons.math3.random.Well19937c;
/**
* Implementation of the uniform integer distribution.
*
* @see <a href="http://en.wikipedia.org/wiki/Uniform_distribution_(discrete)" >Uniform distribution
* (discrete), at Wikipedia</a>
* @since 3.0
*/
public class UniformIntegerDistribution extends AbstractIntegerDistribution {
/** Serializable version identifier. */
private static final long serialVersionUID = 20120109L;
/** Lower bound (inclusive) of this distribution. */
private final int lower;
/** Upper bound (inclusive) of this distribution. */
private final int upper;
/**
* Creates a new uniform integer distribution using the given lower and upper bounds (both
* inclusive).
*
* <p><b>Note:</b> this constructor will implicitly create an instance of {@link Well19937c} as
* random generator to be used for sampling only (see {@link #sample()} and {@link
* #sample(int)}). In case no sampling is needed for the created distribution, it is advised to
* pass {@code null} as random generator via the appropriate constructors to avoid the
* additional initialisation overhead.
*
* @param lower Lower bound (inclusive) of this distribution.
* @param upper Upper bound (inclusive) of this distribution.
* @throws NumberIsTooLargeException if {@code lower >= upper}.
*/
public UniformIntegerDistribution(int lower, int upper) throws NumberIsTooLargeException {
this(new Well19937c(), lower, upper);
}
/**
* Creates a new uniform integer distribution using the given lower and upper bounds (both
* inclusive).
*
* @param rng Random number generator.
* @param lower Lower bound (inclusive) of this distribution.
* @param upper Upper bound (inclusive) of this distribution.
* @throws NumberIsTooLargeException if {@code lower > upper}.
* @since 3.1
*/
public UniformIntegerDistribution(RandomGenerator rng, int lower, int upper)
throws NumberIsTooLargeException {
super(rng);
if (lower > upper) {
throw new NumberIsTooLargeException(
LocalizedFormats.LOWER_BOUND_NOT_BELOW_UPPER_BOUND, lower, upper, true);
}
this.lower = lower;
this.upper = upper;
}
/** {@inheritDoc} */
public double probability(int x) {
if (x < lower || x > upper) {
return 0;
}
return 1.0 / (upper - lower + 1);
}
/** {@inheritDoc} */
public double cumulativeProbability(int x) {
if (x < lower) {
return 0;
}
if (x > upper) {
return 1;
}
return (x - lower + 1.0) / (upper - lower + 1.0);
}
/**
* {@inheritDoc}
*
* <p>For lower bound {@code lower} and upper bound {@code upper}, the mean is {@code 0.5 *
* (lower + upper)}.
*/
public double getNumericalMean() {
return 0.5 * (lower + upper);
}
/**
* {@inheritDoc}
*
* <p>For lower bound {@code lower} and upper bound {@code upper}, and {@code n = upper - lower
* + 1}, the variance is {@code (n^2 - 1) / 12}.
*/
public double getNumericalVariance() {
double n = upper - lower + 1;
return (n * n - 1) / 12.0;
}
/**
* {@inheritDoc}
*
* <p>The lower bound of the support is equal to the lower bound parameter of the distribution.
*
* @return lower bound of the support
*/
public int getSupportLowerBound() {
return lower;
}
/**
* {@inheritDoc}
*
* <p>The upper bound of the support is equal to the upper bound parameter of the distribution.
*
* @return upper bound of the support
*/
public int getSupportUpperBound() {
return upper;
}
/**
* {@inheritDoc}
*
* <p>The support of this distribution is connected.
*
* @return {@code true}
*/
public boolean isSupportConnected() {
return true;
}
/** {@inheritDoc} */
@Override
public int sample() {
final int max = (upper - lower) + 1;
if (max <= 0) {
// The range is too wide to fit in a positive int (larger
// than 2^31); as it covers more than half the integer range,
// we use a simple rejection method.
while (true) {
final int r = random.nextInt();
if (r >= lower && r <= upper) {
return r;
}
}
} else {
// We can shift the range and directly generate a positive int.
return lower + random.nextInt(max);
}
}
}
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