org.apache.commons.math3.random.GaussianRandomGenerator Maven / Gradle / Ivy
Go to download
Show more of this group Show more artifacts with this name
Show all versions of commons-math3 Show documentation
Show all versions of commons-math3 Show documentation
The Apache Commons Math project is a library of lightweight, self-contained mathematics and statistics components addressing the most common practical problems not immediately available in the Java programming language or commons-lang.
/*
* 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.random;
/**
* This class is a gaussian normalized random generator for scalars.
* This class is a simple wrapper around the {@link
* RandomGenerator#nextGaussian} method.
* @version $Id: GaussianRandomGenerator.java 1244107 2012-02-14 16:17:55Z erans $
* @since 1.2
*/
public class GaussianRandomGenerator implements NormalizedRandomGenerator {
/** Underlying generator. */
private final RandomGenerator generator;
/** Create a new generator.
* @param generator underlying random generator to use
*/
public GaussianRandomGenerator(final RandomGenerator generator) {
this.generator = generator;
}
/** Generate a random scalar with null mean and unit standard deviation.
* @return a random scalar with null mean and unit standard deviation
*/
public double nextNormalizedDouble() {
return generator.nextGaussian();
}
}