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+/*
+ * 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;
+
+import org.apache.commons.math3.util.FastMath;
+
+/**
+ * Generate random vectors isotropically located on the surface of a sphere.
+ *
+ * @since 2.1
+ */
+public class UnitSphereRandomVectorGenerator implements RandomVectorGenerator {
+ /** RNG used for generating the individual components of the vectors. */
+ private final RandomGenerator rand;
+
+ /** Space dimension. */
+ private final int dimension;
+
+ /**
+ * @param dimension Space dimension.
+ * @param rand RNG for the individual components of the vectors.
+ */
+ public UnitSphereRandomVectorGenerator(final int dimension, final RandomGenerator rand) {
+ this.dimension = dimension;
+ this.rand = rand;
+ }
+
+ /**
+ * Create an object that will use a default RNG ({@link MersenneTwister}), in order to generate
+ * the individual components.
+ *
+ * @param dimension Space dimension.
+ */
+ public UnitSphereRandomVectorGenerator(final int dimension) {
+ this(dimension, new MersenneTwister());
+ }
+
+ /** {@inheritDoc} */
+ public double[] nextVector() {
+ final double[] v = new double[dimension];
+
+ // See http://mathworld.wolfram.com/SpherePointPicking.html for example.
+ // Pick a point by choosing a standard Gaussian for each element, and then
+ // normalizing to unit length.
+ double normSq = 0;
+ for (int i = 0; i < dimension; i++) {
+ final double comp = rand.nextGaussian();
+ v[i] = comp;
+ normSq += comp * comp;
+ }
+
+ final double f = 1 / FastMath.sqrt(normSq);
+ for (int i = 0; i < dimension; i++) {
+ v[i] *= f;
+ }
+
+ return v;
+ }
+}