InternalGamma.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.rng.sampling.distribution;
/**
* <h3>
* Adapted and stripped down copy of class
* {@code "org.apache.commons.math4.special.Gamma"}.
* </h3>
*
* <p>
* This is a utility class that provides computation methods related to the
* Γ (Gamma) family of functions.
* </p>
*/
final class InternalGamma { // Class is package-private on purpose; do not make it public.
/**
* Constant \( g = \frac{607}{128} \) in the Lanczos approximation.
*/
public static final double LANCZOS_G = 607.0 / 128.0;
/** Lanczos coefficients. */
private static final double[] LANCZOS_COEFFICIENTS = {
0.99999999999999709182,
57.156235665862923517,
-59.597960355475491248,
14.136097974741747174,
-0.49191381609762019978,
.33994649984811888699e-4,
.46523628927048575665e-4,
-.98374475304879564677e-4,
.15808870322491248884e-3,
-.21026444172410488319e-3,
.21743961811521264320e-3,
-.16431810653676389022e-3,
.84418223983852743293e-4,
-.26190838401581408670e-4,
.36899182659531622704e-5,
};
/** Avoid repeated computation of log(2*PI) / 2 in logGamma. */
private static final double HALF_LOG_2_PI = 0.91893853320467274178032973640562;
/**
* Class contains only static methods.
*/
private InternalGamma() {}
/**
* Computes the function \( \ln \Gamma(x) \) for \( x \gt 0 \).
*
* <p>
* For \( x \leq 8 \), the implementation is based on the double precision
* implementation in the <em>NSWC Library of Mathematics Subroutines</em>,
* {@code DGAMLN}. For \( x \geq 8 \), the implementation is based on
* </p>
*
* <ul>
* <li><a href="http://mathworld.wolfram.com/GammaFunction.html">Gamma
* Function</a>, equation (28).</li>
* <li><a href="http://mathworld.wolfram.com/LanczosApproximation.html">
* Lanczos Approximation</a>, equations (1) through (5).</li>
* <li><a href="http://my.fit.edu/~gabdo/gamma.txt">Paul Godfrey, A note on
* the computation of the convergent Lanczos complex Gamma
* approximation</a></li>
* </ul>
*
* @param x Argument.
* @return \( \ln \Gamma(x) \), or {@code NaN} if {@code x <= 0}.
*/
public static double logGamma(double x) {
// Stripped-down version of the same method defined in "Commons Math":
// Unused "if" branches (for when x < 8) have been removed here since
// this method is only used (by class "InternalUtils") in order to
// compute log(n!) for x > 20.
final double sum = lanczos(x);
final double tmp = x + LANCZOS_G + 0.5;
return (x + 0.5) * Math.log(tmp) - tmp + HALF_LOG_2_PI + Math.log(sum / x);
}
/**
* Computes the Lanczos approximation used to compute the gamma function.
*
* <p>
* The Lanczos approximation is related to the Gamma function by the
* following equation
* \[
* \Gamma(x) = \sqrt{2\pi} \, \frac{(g + x + \frac{1}{2})^{x + \frac{1}{2}} \, e^{-(g + x + \frac{1}{2})} \, \mathrm{lanczos}(x)}
* {x}
* \]
* where \(g\) is the Lanczos constant.
* </p>
*
* @param x Argument.
* @return The Lanczos approximation.
*
* @see <a href="http://mathworld.wolfram.com/LanczosApproximation.html">Lanczos Approximation</a>
* equations (1) through (5), and Paul Godfrey's
* <a href="http://my.fit.edu/~gabdo/gamma.txt">Note on the computation
* of the convergent Lanczos complex Gamma approximation</a>
*/
private static double lanczos(final double x) {
double sum = 0.0;
for (int i = LANCZOS_COEFFICIENTS.length - 1; i > 0; --i) {
sum += LANCZOS_COEFFICIENTS[i] / (x + i);
}
return sum + LANCZOS_COEFFICIENTS[0];
}
}