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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.statistics.distribution;
import org.apache.commons.rng.UniformRandomProvider;
import org.apache.commons.rng.sampling.distribution.DiscreteUniformSampler;
/**
* Implementation of the <a href="http://en.wikipedia.org/wiki/Uniform_distribution_(discrete)">
* uniform integer distribution</a>.
*/
public class UniformDiscreteDistribution extends AbstractDiscreteDistribution {
/** Lower bound (inclusive) of this distribution. */
private final int lower;
/** Upper bound (inclusive) of this distribution. */
private final int upper;
/** "upper" - "lower" + 1 (as a double to avoid overflow). */
private final double upperMinusLowerPlus1;
/** Cache of the probability. */
private final double pmf;
/** Cache of the log probability. */
private final double logPmf;
/**
* Creates a new uniform integer distribution using the given lower and
* upper bounds (both inclusive).
*
* @param lower Lower bound (inclusive) of this distribution.
* @param upper Upper bound (inclusive) of this distribution.
* @throws IllegalArgumentException if {@code lower > upper}.
*/
public UniformDiscreteDistribution(int lower,
int upper) {
if (lower > upper) {
throw new DistributionException(DistributionException.INVALID_RANGE_LOW_GT_HIGH,
lower, upper);
}
this.lower = lower;
this.upper = upper;
upperMinusLowerPlus1 = (double) upper - (double) lower + 1;
pmf = 1.0 / upperMinusLowerPlus1;
logPmf = -Math.log(upperMinusLowerPlus1);
}
/** {@inheritDoc} */
@Override
public double probability(int x) {
if (x < lower || x > upper) {
return 0;
}
return pmf;
}
/** {@inheritDoc} */
@Override
public double logProbability(int x) {
if (x < lower || x > upper) {
return Double.NEGATIVE_INFINITY;
}
return logPmf;
}
/** {@inheritDoc} */
@Override
public double cumulativeProbability(int x) {
if (x < lower) {
return 0;
}
if (x > upper) {
return 1;
}
return (x - lower + 1) / upperMinusLowerPlus1;
}
/**
* {@inheritDoc}
*
* <p>For lower bound {@code lower} and upper bound {@code upper}, the mean is
* {@code 0.5 * (lower + upper)}.
*/
@Override
public double getMean() {
// Avoid overflow
return 0.5 * ((double) upper + (double) lower);
}
/**
* {@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}.
*/
@Override
public double getVariance() {
return (upperMinusLowerPlus1 * upperMinusLowerPlus1 - 1) / 12;
}
/**
* {@inheritDoc}
*
* <p>The lower bound of the support is equal to the lower bound parameter
* of the distribution.
*
* @return lower bound of the support
*/
@Override
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
*/
@Override
public int getSupportUpperBound() {
return upper;
}
/**
* {@inheritDoc}
*
* <p>The support of this distribution is connected.
*
* @return {@code true}
*/
@Override
public boolean isSupportConnected() {
return true;
}
/** {@inheritDoc} */
@Override
public DiscreteDistribution.Sampler createSampler(final UniformRandomProvider rng) {
// Discrete uniform distribution sampler.
return DiscreteUniformSampler.of(rng, lower, upper)::sample;
}
}