1 /*
2 * Licensed to the Apache Software Foundation (ASF) under one or more
3 * contributor license agreements. See the NOTICE file distributed with
4 * this work for additional information regarding copyright ownership.
5 * The ASF licenses this file to You under the Apache License, Version 2.0
6 * (the "License"); you may not use this file except in compliance with
7 * the License. You may obtain a copy of the License at
8 *
9 * http://www.apache.org/licenses/LICENSE-2.0
10 *
11 * Unless required by applicable law or agreed to in writing, software
12 * distributed under the License is distributed on an "AS IS" BASIS,
13 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 * See the License for the specific language governing permissions and
15 * limitations under the License.
16 */
17 package org.apache.commons.rng.sampling.distribution;
18
19 import org.apache.commons.rng.UniformRandomProvider;
20 import org.apache.commons.rng.core.source32.IntProvider;
21 import org.apache.commons.rng.sampling.RandomAssert;
22 import org.junit.jupiter.api.Assertions;
23 import org.junit.jupiter.api.Test;
24
25 /**
26 * Test for the {@link MarsagliaNormalizedGaussianSampler}.
27 */
28 class MarsagliaNormalisedGaussianSamplerTest {
29 /**
30 * Test the SharedStateSampler implementation.
31 */
32 @Test
33 void testSharedStateSampler() {
34 final UniformRandomProvider rng1 = RandomAssert.seededRNG();
35 final UniformRandomProvider rng2 = RandomAssert.seededRNG();
36 final SharedStateContinuousSampler sampler1 =
37 MarsagliaNormalizedGaussianSampler.<MarsagliaNormalizedGaussianSampler>of(rng1);
38 final SharedStateContinuousSampler sampler2 = sampler1.withUniformRandomProvider(rng2);
39 RandomAssert.assertProduceSameSequence(sampler1, sampler2);
40 }
41
42 /**
43 * Test the edge case where the pair of samples are rejected. This occurs when the distance
44 * of the pair is outside the unit circle or lies on the origin.
45 */
46 @Test
47 void testSamplePairIsRejected() {
48 final double value = 0.25;
49 final UniformRandomProvider rng = new IntProvider() {
50 private int i;
51
52 @Override
53 public int next() {
54 // Not used
55 return 0;
56 }
57
58 @Override
59 public double nextDouble() {
60 i++;
61 if (i <= 2) {
62 // First two samples are one.
63 // This is outside the unit circle.
64 return 1.0;
65 }
66 if (i <= 4) {
67 // Next two samples are 0.5.
68 // The pair lies at the origin.
69 return 0.5;
70 }
71 return value;
72 }
73 };
74
75 final MarsagliaNormalizedGaussianSampler sampler = new MarsagliaNormalizedGaussianSampler(rng);
76
77 // Compute as per the algorithm
78 final double x = 2 * value - 1;
79 final double r2 = x * x + x * x;
80 final double expected = x * Math.sqrt(-2 * Math.log(r2) / r2);
81 Assertions.assertEquals(expected, sampler.sample());
82 }
83 }