Github user kinow commented on a diff in the pull request:
https://github.com/apache/commonsrng/pull/5#discussion_r143630250
 Diff: commonsrngsampling/src/main/java/org/apache/commons/rng/sampling/distribution/ZigguratGaussianSampler.java

@@ 0,0 +1,152 @@
+/*
+ * 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/LICENSE2.0
+ *
+ * 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;
+
+import org.apache.commons.rng.UniformRandomProvider;
+
+/**
+ * Gaussian Sampling by
+ * <a href="https://en.wikipedia.org/wiki/Ziggurat_algorithm">Ziggurat algorithm</a>
+ *
+ * <p>Based on
+ * "The Ziggurat Method for Generating Random Variables"<br>
+ * by George Marsaglia and Wai Wan Tsang</p>
+ *
+ * @see <a href="http://www.jstatsoft.org/article/view/v005i08/ziggurat.pdf">Ziggurat
Method for Generating Random Variables</a>
+ *
+ * @since 1.1
+ */
+
+public class ZigguratGaussianSampler
+ extends SamplerBase
+ implements NormalizedGaussianSampler {
+
+ /**
+ * Generates values from Gaussian (normal) probability distribution
+ * It uses two tables, integers KN and reals WN. Some 99% of the time,
+ * the required x is produced by:
+ * generate a random 32bit integer j and let i be the index formed from
+ * the rightmost 8 bits of j. If j < k_i return x = j * w_i.
+ */
+
+ private static final int[] KN = new int[128];
+ private static final double[] WN = new double[128];
+ private static final double[] FN = new double[128];
+
+ /**
+ * Initialize tables.
+ */
+ static {
+ /**
+ * Filling the tables.
+ * k_0 = 2^32 * r * f(dn) / vn
+ * k_i = 2^32 * ( x_{i1} / x_i )
+ * w_0 = .5^32 * vn / f(dn)
+ * w_i = .5^32 * x_i
+ * where dn  the rightmost x_i
+ * vn  the area of the rectangle
+ * f(dn) = exp(.5 * dn * dn)
+ */
+ final double m = 2147483648.0; // 2^31
+
+ /* provides z(r) = 0, where z(r): x_255 = r, vn = r*f(r)+integral_r^inf f(x)dx
*/
+ final double vn = 9.91256303526217e3;
+
+ double dn = 3.442619855899;
+ double tn = dn;
+ double e = Math.exp(.5 * dn * dn);
+ final double q = vn / e;
+
+ KN[0] = (int) ((dn / q) * m);
+ KN[1] = 0;
+
+ WN[0] = q / m;
+ WN[127] = dn / m;
+
+ FN[0] = 1.0;
+ FN[127] = e;
+
+ for (int i = 126; i >= 1; i){
+ e = Math.exp(.5 *dn * dn);
+ dn = Math.sqrt(2. * Math.log(vn / dn + e));
+ KN[i+1] = (int) ((dn / tn) * m);
+ tn = dn;
+ FN[i] = e;
+ WN[i] = dn / m;
+ }
+ }
+
+ /**
+ * @param rng Generator of uniformly distributed random numbers.
+ */
+ public ZigguratGaussianSampler(UniformRandomProvider rng) {
+ super(rng);
+ }
+
+ /** {@inheritDoc} */
+ @Override
+ public double sample() {
+ int j = nextInt();
+ int i = j & 127;
+ return (j < KN[i]) ? j * WN[i] : nfix(j,i);
+ }
+
+ /** get the value from the tail of the distribution
 End diff 
Normally it's in the next line, starting with upper case. Not really important though.
Some components have user guides, but many point to the Javadocs as user guide :) that's
why we focus so much on the text that is put here @cur4so


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