/*
* 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}
*
* 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}
*
* 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}
*
* 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}
*
* 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}
*
* 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;
}
}