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Diffstat (limited to 'src/main/java/org/apache/commons/math3/distribution/UniformIntegerDistribution.java')
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diff --git a/src/main/java/org/apache/commons/math3/distribution/UniformIntegerDistribution.java b/src/main/java/org/apache/commons/math3/distribution/UniformIntegerDistribution.java new file mode 100644 index 0000000..8a3a98b --- /dev/null +++ b/src/main/java/org/apache/commons/math3/distribution/UniformIntegerDistribution.java @@ -0,0 +1,174 @@ +/* + * 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); + } + } +} |