    001    /*
    002     * Licensed to the Apache Software Foundation (ASF) under one or more
    003     * contributor license agreements.  See the NOTICE file distributed with
    004     * this work for additional information regarding copyright ownership.
    005     * The ASF licenses this file to You under the Apache License, Version 2.0
    006     * (the "License"); you may not use this file except in compliance with
    007     * the License.  You may obtain a copy of the License at
    008     *
    009     *      http://www.apache.org/licenses/LICENSE-2.0
    010     *
    011     * Unless required by applicable law or agreed to in writing, software
    012     * distributed under the License is distributed on an "AS IS" BASIS,
    013     * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    014     * See the License for the specific language governing permissions and
    015     * limitations under the License.
    016     */
    017
    018    package org.apache.commons.math3.random;
    019
    020    /**
    021     * This class is a gaussian normalized random generator for scalars.
    022     * <p>This class is a simple wrapper around the {@link
    023     * RandomGenerator#nextGaussian} method.</p>
    024     * @version $Id: GaussianRandomGenerator.java 1416643 2012-12-03 19:37:14Z tn $
    025     * @since 1.2
    026     */
    027
    028    public class GaussianRandomGenerator implements NormalizedRandomGenerator {
    029
    030        /** Underlying generator. */
    031        private final RandomGenerator generator;
    032
    033        /** Create a new generator.
    034         * @param generator underlying random generator to use
    035         */
    036        public GaussianRandomGenerator(final RandomGenerator generator) {
    037            this.generator = generator;
    038        }
    039
    040        /** Generate a random scalar with null mean and unit standard deviation.
    041         * @return a random scalar with null mean and unit standard deviation
    042         */
    043        public double nextNormalizedDouble() {
    044            return generator.nextGaussian();
    045        }
    046
    047    }