path: root/src/main/java/org/apache/commons/math3/distribution/UniformRealDistribution.java

/*
 * 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.OutOfRangeException;
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 real distribution.
 *
 * @see <a href="http://en.wikipedia.org/wiki/Uniform_distribution_(continuous)" >Uniform
 *     distribution (continuous), at Wikipedia</a>
 * @since 3.0
 */
public class UniformRealDistribution extends AbstractRealDistribution {
    /**
     * Default inverse cumulative probability accuracy.
     *
     * @deprecated as of 3.2 not used anymore, will be removed in 4.0
     */
    @Deprecated public static final double DEFAULT_INVERSE_ABSOLUTE_ACCURACY = 1e-9;

    /** Serializable version identifier. */
    private static final long serialVersionUID = 20120109L;

    /** Lower bound of this distribution (inclusive). */
    private final double lower;

    /** Upper bound of this distribution (exclusive). */
    private final double upper;

    /**
     * Create a standard uniform real distribution with lower bound (inclusive) equal to zero and
     * upper bound (exclusive) equal to one.
     *
     * <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.
     */
    public UniformRealDistribution() {
        this(0, 1);
    }

    /**
     * Create a uniform real distribution using the given lower and upper bounds.
     *
     * <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 of this distribution (inclusive).
     * @param upper Upper bound of this distribution (exclusive).
     * @throws NumberIsTooLargeException if {@code lower >= upper}.
     */
    public UniformRealDistribution(double lower, double upper) throws NumberIsTooLargeException {
        this(new Well19937c(), lower, upper);
    }

    /**
     * Create a uniform distribution.
     *
     * @param lower Lower bound of this distribution (inclusive).
     * @param upper Upper bound of this distribution (exclusive).
     * @param inverseCumAccuracy Inverse cumulative probability accuracy.
     * @throws NumberIsTooLargeException if {@code lower >= upper}.
     * @deprecated as of 3.2, inverse CDF is now calculated analytically, use {@link
     *     #UniformRealDistribution(double, double)} instead.
     */
    @Deprecated
    public UniformRealDistribution(double lower, double upper, double inverseCumAccuracy)
            throws NumberIsTooLargeException {
        this(new Well19937c(), lower, upper);
    }

    /**
     * Creates a uniform distribution.
     *
     * @param rng Random number generator.
     * @param lower Lower bound of this distribution (inclusive).
     * @param upper Upper bound of this distribution (exclusive).
     * @param inverseCumAccuracy Inverse cumulative probability accuracy.
     * @throws NumberIsTooLargeException if {@code lower >= upper}.
     * @since 3.1
     * @deprecated as of 3.2, inverse CDF is now calculated analytically, use {@link
     *     #UniformRealDistribution(RandomGenerator, double, double)} instead.
     */
    @Deprecated
    public UniformRealDistribution(
            RandomGenerator rng, double lower, double upper, double inverseCumAccuracy) {
        this(rng, lower, upper);
    }

    /**
     * Creates a uniform distribution.
     *
     * @param rng Random number generator.
     * @param lower Lower bound of this distribution (inclusive).
     * @param upper Upper bound of this distribution (exclusive).
     * @throws NumberIsTooLargeException if {@code lower >= upper}.
     * @since 3.1
     */
    public UniformRealDistribution(RandomGenerator rng, double lower, double upper)
            throws NumberIsTooLargeException {
        super(rng);
        if (lower >= upper) {
            throw new NumberIsTooLargeException(
                    LocalizedFormats.LOWER_BOUND_NOT_BELOW_UPPER_BOUND, lower, upper, false);
        }

        this.lower = lower;
        this.upper = upper;
    }

    /** {@inheritDoc} */
    public double density(double x) {
        if (x < lower || x > upper) {
            return 0.0;
        }
        return 1 / (upper - lower);
    }

    /** {@inheritDoc} */
    public double cumulativeProbability(double x) {
        if (x <= lower) {
            return 0;
        }
        if (x >= upper) {
            return 1;
        }
        return (x - lower) / (upper - lower);
    }

    /** {@inheritDoc} */
    @Override
    public double inverseCumulativeProbability(final double p) throws OutOfRangeException {
        if (p < 0.0 || p > 1.0) {
            throw new OutOfRangeException(p, 0, 1);
        }
        return p * (upper - lower) + lower;
    }

    /**
     * {@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}, the variance is {@code (upper
     * - lower)^2 / 12}.
     */
    public double getNumericalVariance() {
        double ul = upper - lower;
        return ul * ul / 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
     */
    public double 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 double getSupportUpperBound() {
        return upper;
    }

    /** {@inheritDoc} */
    public boolean isSupportLowerBoundInclusive() {
        return true;
    }

    /** {@inheritDoc} */
    public boolean isSupportUpperBoundInclusive() {
        return true;
    }

    /**
     * {@inheritDoc}
     *
     * <p>The support of this distribution is connected.
     *
     * @return {@code true}
     */
    public boolean isSupportConnected() {
        return true;
    }

    /** {@inheritDoc} */
    @Override
    public double sample() {
        final double u = random.nextDouble();
        return u * upper + (1 - u) * lower;
    }
}