commons-commits mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From er...@apache.org
Subject [3/6] commons-rng git commit: RNG-35: Box-Muller algorithm for N(0, 1) sampling.
Date Mon, 23 Jan 2017 23:23:08 GMT
RNG-35: Box-Muller algorithm for N(0,1) sampling.


Project: http://git-wip-us.apache.org/repos/asf/commons-rng/repo
Commit: http://git-wip-us.apache.org/repos/asf/commons-rng/commit/8b4a5ec2
Tree: http://git-wip-us.apache.org/repos/asf/commons-rng/tree/8b4a5ec2
Diff: http://git-wip-us.apache.org/repos/asf/commons-rng/diff/8b4a5ec2

Branch: refs/heads/feature__RNG-35
Commit: 8b4a5ec2c9e88846c34fd73567c093c702be1500
Parents: cf65f67
Author: Gilles <erans@apache.org>
Authored: Tue Jan 24 00:11:47 2017 +0100
Committer: Gilles <erans@apache.org>
Committed: Tue Jan 24 00:11:47 2017 +0100

----------------------------------------------------------------------
 .../BoxMullerNormalizedGaussianSampler.java     | 75 ++++++++++++++++++++
 1 file changed, 75 insertions(+)
----------------------------------------------------------------------


http://git-wip-us.apache.org/repos/asf/commons-rng/blob/8b4a5ec2/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/BoxMullerNormalizedGaussianSampler.java
----------------------------------------------------------------------
diff --git a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/BoxMullerNormalizedGaussianSampler.java
b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/BoxMullerNormalizedGaussianSampler.java
new file mode 100644
index 0000000..43882fb
--- /dev/null
+++ b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/BoxMullerNormalizedGaussianSampler.java
@@ -0,0 +1,75 @@
+/*
+ * 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;
+
+import org.apache.commons.rng.UniformRandomProvider;
+
+/**
+ * <a href="https://en.wikipedia.org/wiki/Box%E2%80%93Muller_transform">
+ * Box-Muller algorithm</a> for sampling from Gaussian distribution with
+ * mean 0 and standard deviation 1.
+ *
+ * @since 1.1
+ */
+public class BoxMullerNormalizedGaussianSampler
+    extends SamplerBase
+    implements NormalizedGaussianSampler {
+    /** Next gaussian. */
+    private double nextGaussian = Double.NaN;
+
+    /**
+     * @param rng Generator of uniformly distributed random numbers.
+     */
+    public BoxMullerNormalizedGaussianSampler(UniformRandomProvider rng) {
+        super(rng);
+    }
+
+    /** {@inheritDoc} */
+    @Override
+    public double sample() {
+        final double random;
+        if (Double.isNaN(nextGaussian)) {
+            // Generate a pair of Gaussian numbers.
+
+            final double x = nextDouble();
+            final double y = nextDouble();
+            final double alpha = 2 * Math.PI * x;
+            final double r = Math.sqrt(-2 * Math.log(y));
+
+            // Return the first element of the generated pair.
+            random = r * Math.cos(alpha);
+
+            // Keep second element of the pair for next invocation.
+            nextGaussian = r * Math.sin(alpha);
+        } else {
+            // Use the second element of the pair (generated at the
+            // previous invocation).
+            random = nextGaussian;
+
+            // Both elements of the pair have been used.
+            nextGaussian = Double.NaN;
+        }
+
+        return random;
+    }
+
+    /** {@inheritDoc} */
+    @Override
+    public String toString() {
+        return "Box-Muller normalized Gaussian deviate [" + super.toString() + "]";
+    }
+}


Mime
View raw message