Added: dev/commons/statistics/1.0-RC1/site/xref-test/org/apache/commons/statistics/distribution/TruncatedNormalDistributionTest.html ============================================================================== --- dev/commons/statistics/1.0-RC1/site/xref-test/org/apache/commons/statistics/distribution/TruncatedNormalDistributionTest.html (added) +++ dev/commons/statistics/1.0-RC1/site/xref-test/org/apache/commons/statistics/distribution/TruncatedNormalDistributionTest.html Thu Dec 1 16:47:12 2022 @@ -0,0 +1,412 @@ +<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd";> +<html xmlns="http://www.w3.org/1999/xhtml"; xml:lang="en" lang="en"> +<head><meta http-equiv="content-type" content="text/html; charset=UTF-8" /> +<title>TruncatedNormalDistributionTest xref</title> +<link type="text/css" rel="stylesheet" href="../../../../../stylesheet.css" /> +</head> +<body> +<div id="overview"><a href="../../../../../../testapidocs/org/apache/commons/statistics/distribution/TruncatedNormalDistributionTest.html">View Javadoc</a></div><pre> +<a class="jxr_linenumber" name="L1" href="#L1">1</a> <em class="jxr_comment">/*</em> +<a class="jxr_linenumber" name="L2" href="#L2">2</a> <em class="jxr_comment"> * Licensed to the Apache Software Foundation (ASF) under one or more</em> +<a class="jxr_linenumber" name="L3" href="#L3">3</a> <em class="jxr_comment"> * contributor license agreements. See the NOTICE file distributed with</em> +<a class="jxr_linenumber" name="L4" href="#L4">4</a> <em class="jxr_comment"> * this work for additional information regarding copyright ownership.</em> +<a class="jxr_linenumber" name="L5" href="#L5">5</a> <em class="jxr_comment"> * The ASF licenses this file to You under the Apache License, Version 2.0</em> +<a class="jxr_linenumber" name="L6" href="#L6">6</a> <em class="jxr_comment"> * (the "License"); you may not use this file except in compliance with</em> +<a class="jxr_linenumber" name="L7" href="#L7">7</a> <em class="jxr_comment"> * the License. You may obtain a copy of the License at</em> +<a class="jxr_linenumber" name="L8" href="#L8">8</a> <em class="jxr_comment"> *</em> +<a class="jxr_linenumber" name="L9" href="#L9">9</a> <em class="jxr_comment"> * <a href="http://www.apache.org/licenses/LICENSE-2.0"; target="alexandria_uri">http://www.apache.org/licenses/LICENSE-2.0</a></em> +<a class="jxr_linenumber" name="L10" href="#L10">10</a> <em class="jxr_comment"> *</em> +<a class="jxr_linenumber" name="L11" href="#L11">11</a> <em class="jxr_comment"> * Unless required by applicable law or agreed to in writing, software</em> +<a class="jxr_linenumber" name="L12" href="#L12">12</a> <em class="jxr_comment"> * distributed under the License is distributed on an "AS IS" BASIS,</em> +<a class="jxr_linenumber" name="L13" href="#L13">13</a> <em class="jxr_comment"> * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.</em> +<a class="jxr_linenumber" name="L14" href="#L14">14</a> <em class="jxr_comment"> * See the License for the specific language governing permissions and</em> +<a class="jxr_linenumber" name="L15" href="#L15">15</a> <em class="jxr_comment"> * limitations under the License.</em> +<a class="jxr_linenumber" name="L16" href="#L16">16</a> <em class="jxr_comment"> */</em> +<a class="jxr_linenumber" name="L17" href="#L17">17</a> +<a class="jxr_linenumber" name="L18" href="#L18">18</a> <strong class="jxr_keyword">package</strong> org.apache.commons.statistics.distribution; +<a class="jxr_linenumber" name="L19" href="#L19">19</a> +<a class="jxr_linenumber" name="L20" href="#L20">20</a> <strong class="jxr_keyword">import</strong> org.apache.commons.numbers.gamma.Erf; +<a class="jxr_linenumber" name="L21" href="#L21">21</a> <strong class="jxr_keyword">import</strong> org.apache.commons.numbers.gamma.Erfcx; +<a class="jxr_linenumber" name="L22" href="#L22">22</a> <strong class="jxr_keyword">import</strong> org.junit.jupiter.api.Assertions; +<a class="jxr_linenumber" name="L23" href="#L23">23</a> <strong class="jxr_keyword">import</strong> org.junit.jupiter.api.Test; +<a class="jxr_linenumber" name="L24" href="#L24">24</a> <strong class="jxr_keyword">import</strong> org.junit.jupiter.params.ParameterizedTest; +<a class="jxr_linenumber" name="L25" href="#L25">25</a> <strong class="jxr_keyword">import</strong> org.junit.jupiter.params.provider.CsvSource; +<a class="jxr_linenumber" name="L26" href="#L26">26</a> +<a class="jxr_linenumber" name="L27" href="#L27">27</a> <em class="jxr_javadoccomment">/**</em> +<a class="jxr_linenumber" name="L28" href="#L28">28</a> <em class="jxr_javadoccomment"> * Test class for {@link TruncatedNormalDistribution}.</em> +<a class="jxr_linenumber" name="L29" href="#L29">29</a> <em class="jxr_javadoccomment"> * Extends {@link BaseContinuousDistributionTest}. See javadoc of that class for details.</em> +<a class="jxr_linenumber" name="L30" href="#L30">30</a> <em class="jxr_javadoccomment"> * All test values were computed using Python with SciPy v1.6.0.</em> +<a class="jxr_linenumber" name="L31" href="#L31">31</a> <em class="jxr_javadoccomment"> */</em> +<a class="jxr_linenumber" name="L32" href="#L32">32</a> <strong class="jxr_keyword">class</strong> <a name="TruncatedNormalDistributionTest" href="../../../../../org/apache/commons/statistics/distribution/TruncatedNormalDistributionTest.html#TruncatedNormalDistributionTest">TruncatedNormalDistributionTest</a> <strong class="jxr_keyword">extends</strong> <a name="BaseContinuousDistributionTest" href="../../../../../org/apache/commons/statistics/distribution/BaseContinuousDistributionTest.html#BaseContinuousDistributionTest">BaseContinuousDistributionTest</a> { +<a class="jxr_linenumber" name="L33" href="#L33">33</a> @Override +<a class="jxr_linenumber" name="L34" href="#L34">34</a> ContinuousDistribution makeDistribution(Object... parameters) { +<a class="jxr_linenumber" name="L35" href="#L35">35</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> mean = (Double) parameters[0]; +<a class="jxr_linenumber" name="L36" href="#L36">36</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> sd = (Double) parameters[1]; +<a class="jxr_linenumber" name="L37" href="#L37">37</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> upper = (Double) parameters[2]; +<a class="jxr_linenumber" name="L38" href="#L38">38</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> lower = (Double) parameters[3]; +<a class="jxr_linenumber" name="L39" href="#L39">39</a> <strong class="jxr_keyword">return</strong> TruncatedNormalDistribution.of(mean, sd, upper, lower); +<a class="jxr_linenumber" name="L40" href="#L40">40</a> } +<a class="jxr_linenumber" name="L41" href="#L41">41</a> +<a class="jxr_linenumber" name="L42" href="#L42">42</a> @Override +<a class="jxr_linenumber" name="L43" href="#L43">43</a> Object[][] makeInvalidParameters() { +<a class="jxr_linenumber" name="L44" href="#L44">44</a> <strong class="jxr_keyword">return</strong> <strong class="jxr_keyword">new</strong> Object[][] { +<a class="jxr_linenumber" name="L45" href="#L45">45</a> {0.0, 0.0, -1.0, 1.0}, +<a class="jxr_linenumber" name="L46" href="#L46">46</a> {0.0, -0.1, -1.0, 1.0}, +<a class="jxr_linenumber" name="L47" href="#L47">47</a> {0.0, 1.0, 1.0, -1.0}, +<a class="jxr_linenumber" name="L48" href="#L48">48</a> <em class="jxr_comment">// No usable probability range</em> +<a class="jxr_linenumber" name="L49" href="#L49">49</a> {0.0, 1.0, 100.0, 101.0}, +<a class="jxr_linenumber" name="L50" href="#L50">50</a> }; +<a class="jxr_linenumber" name="L51" href="#L51">51</a> } +<a class="jxr_linenumber" name="L52" href="#L52">52</a> +<a class="jxr_linenumber" name="L53" href="#L53">53</a> @Override +<a class="jxr_linenumber" name="L54" href="#L54">54</a> String[] getParameterNames() { +<a class="jxr_linenumber" name="L55" href="#L55">55</a> <em class="jxr_comment">// Input mean and standard deviation refer to the underlying normal distribution.</em> +<a class="jxr_linenumber" name="L56" href="#L56">56</a> <em class="jxr_comment">// The constructor arguments do not match the mean and SD of the truncated distribution.</em> +<a class="jxr_linenumber" name="L57" href="#L57">57</a> <strong class="jxr_keyword">return</strong> <strong class="jxr_keyword">new</strong> String[] {<strong class="jxr_keyword">null</strong>, <strong class="jxr_keyword">null</strong>, <span class="jxr_string">"SupportLowerBound"</span>, <span class="jxr_string">"SupportUpperBound"</span>}; +<a class="jxr_linenumber" name="L58" href="#L58">58</a> } +<a class="jxr_linenumber" name="L59" href="#L59">59</a> +<a class="jxr_linenumber" name="L60" href="#L60">60</a> @Override +<a class="jxr_linenumber" name="L61" href="#L61">61</a> <strong class="jxr_keyword">protected</strong> <strong class="jxr_keyword">double</strong> getRelativeTolerance() { +<a class="jxr_linenumber" name="L62" href="#L62">62</a> <strong class="jxr_keyword">return</strong> 1e-14; +<a class="jxr_linenumber" name="L63" href="#L63">63</a> } +<a class="jxr_linenumber" name="L64" href="#L64">64</a> +<a class="jxr_linenumber" name="L65" href="#L65">65</a> <em class="jxr_comment">//-------------------- Additional test cases -------------------------------</em> +<a class="jxr_linenumber" name="L66" href="#L66">66</a> +<a class="jxr_linenumber" name="L67" href="#L67">67</a> <em class="jxr_javadoccomment">/**</em> +<a class="jxr_linenumber" name="L68" href="#L68">68</a> <em class="jxr_javadoccomment"> * Hit the edge cases where the lower and upper bound are not infinite but the</em> +<a class="jxr_linenumber" name="L69" href="#L69">69</a> <em class="jxr_javadoccomment"> * CDF of the parent distribution is either 0 or 1. This is effectively no truncation.</em> +<a class="jxr_linenumber" name="L70" href="#L70">70</a> <em class="jxr_javadoccomment"> * Big finite bounds should be handled as if infinite when computing the moments.</em> +<a class="jxr_linenumber" name="L71" href="#L71">71</a> <em class="jxr_javadoccomment"> *</em> +<a class="jxr_linenumber" name="L72" href="#L72">72</a> <em class="jxr_javadoccomment"> * @param mean Mean for the parent distribution.</em> +<a class="jxr_linenumber" name="L73" href="#L73">73</a> <em class="jxr_javadoccomment"> * @param sd Standard deviation for the parent distribution.</em> +<a class="jxr_linenumber" name="L74" href="#L74">74</a> <em class="jxr_javadoccomment"> * @param lower Lower bound (inclusive) of the distribution, can be {@link Double#NEGATIVE_INFINITY}.</em> +<a class="jxr_linenumber" name="L75" href="#L75">75</a> <em class="jxr_javadoccomment"> * @param upper Upper bound (inclusive) of the distribution, can be {@link Double#POSITIVE_INFINITY}.</em> +<a class="jxr_linenumber" name="L76" href="#L76">76</a> <em class="jxr_javadoccomment"> */</em> +<a class="jxr_linenumber" name="L77" href="#L77">77</a> @ParameterizedTest +<a class="jxr_linenumber" name="L78" href="#L78">78</a> @CsvSource({ +<a class="jxr_linenumber" name="L79" href="#L79">79</a> <span class="jxr_string">"0.0, 1.0, -4, 6"</span>, +<a class="jxr_linenumber" name="L80" href="#L80">80</a> <span class="jxr_string">"1.0, 2.0, -4, 6"</span>, +<a class="jxr_linenumber" name="L81" href="#L81">81</a> <span class="jxr_string">"3.45, 6.78, -8, 10"</span>, +<a class="jxr_linenumber" name="L82" href="#L82">82</a> }) +<a class="jxr_linenumber" name="L83" href="#L83">83</a> <strong class="jxr_keyword">void</strong> testMomentsEffectivelyNoTruncation(<strong class="jxr_keyword">double</strong> mean, <strong class="jxr_keyword">double</strong> sd, <strong class="jxr_keyword">double</strong> lower, <strong class="jxr_keyword">double</strong> upper) { +<a class="jxr_linenumber" name="L84" href="#L84">84</a> <strong class="jxr_keyword">double</strong> inf = Double.POSITIVE_INFINITY; +<a class="jxr_linenumber" name="L85" href="#L85">85</a> <strong class="jxr_keyword">double</strong> max = Double.MAX_VALUE; +<a class="jxr_linenumber" name="L86" href="#L86">86</a> TruncatedNormalDistribution dist1; +<a class="jxr_linenumber" name="L87" href="#L87">87</a> TruncatedNormalDistribution dist2; +<a class="jxr_linenumber" name="L88" href="#L88">88</a> <em class="jxr_comment">// truncation of upper tail</em> +<a class="jxr_linenumber" name="L89" href="#L89">89</a> dist1 = TruncatedNormalDistribution.of(mean, sd, -inf, upper); +<a class="jxr_linenumber" name="L90" href="#L90">90</a> dist2 = TruncatedNormalDistribution.of(mean, sd, -max, upper); +<a class="jxr_linenumber" name="L91" href="#L91">91</a> Assertions.assertEquals(dist1.getMean(), dist2.getMean(), <span class="jxr_string">"Mean"</span>); +<a class="jxr_linenumber" name="L92" href="#L92">92</a> Assertions.assertEquals(dist1.getVariance(), dist2.getVariance(), <span class="jxr_string">"Variance"</span>); +<a class="jxr_linenumber" name="L93" href="#L93">93</a> <em class="jxr_comment">// truncation of lower tail</em> +<a class="jxr_linenumber" name="L94" href="#L94">94</a> dist1 = TruncatedNormalDistribution.of(mean, sd, lower, inf); +<a class="jxr_linenumber" name="L95" href="#L95">95</a> dist2 = TruncatedNormalDistribution.of(mean, sd, lower, max); +<a class="jxr_linenumber" name="L96" href="#L96">96</a> Assertions.assertEquals(dist1.getMean(), dist2.getMean(), <span class="jxr_string">"Mean"</span>); +<a class="jxr_linenumber" name="L97" href="#L97">97</a> Assertions.assertEquals(dist1.getVariance(), dist2.getVariance(), <span class="jxr_string">"Variance"</span>); +<a class="jxr_linenumber" name="L98" href="#L98">98</a> <em class="jxr_comment">// no truncation</em> +<a class="jxr_linenumber" name="L99" href="#L99">99</a> dist1 = TruncatedNormalDistribution.of(mean, sd, -inf, inf); +<a class="jxr_linenumber" name="L100" href="#L100">100</a> dist2 = TruncatedNormalDistribution.of(mean, sd, -max, max); +<a class="jxr_linenumber" name="L101" href="#L101">101</a> Assertions.assertEquals(dist1.getMean(), dist2.getMean(), <span class="jxr_string">"Mean"</span>); +<a class="jxr_linenumber" name="L102" href="#L102">102</a> Assertions.assertEquals(dist1.getVariance(), dist2.getVariance(), <span class="jxr_string">"Variance"</span>); +<a class="jxr_linenumber" name="L103" href="#L103">103</a> } +<a class="jxr_linenumber" name="L104" href="#L104">104</a> +<a class="jxr_linenumber" name="L105" href="#L105">105</a> <em class="jxr_javadoccomment">/**</em> +<a class="jxr_linenumber" name="L106" href="#L106">106</a> <em class="jxr_javadoccomment"> * Test mean cases adapted from the source implementation for the truncated</em> +<a class="jxr_linenumber" name="L107" href="#L107">107</a> <em class="jxr_javadoccomment"> * normal moments.</em> +<a class="jxr_linenumber" name="L108" href="#L108">108</a> <em class="jxr_javadoccomment"> *</em> +<a class="jxr_linenumber" name="L109" href="#L109">109</a> <em class="jxr_javadoccomment"> * @see <a href="<a href="https://github.com/cossio/TruncatedNormal.jl/blob/master/test/tnmom1.jl"; target="alexandria_uri">https://github.com/cossio/TruncatedNormal.jl/blob/master/test/tnmom1.jl</a>"></em> +<a class="jxr_linenumber" name="L110" href="#L110">110</a> <em class="jxr_javadoccomment"> * cossio TruncatedNormal moment1 tests</a></em> +<a class="jxr_linenumber" name="L111" href="#L111">111</a> <em class="jxr_javadoccomment"> */</em> +<a class="jxr_linenumber" name="L112" href="#L112">112</a> @Test +<a class="jxr_linenumber" name="L113" href="#L113">113</a> <strong class="jxr_keyword">void</strong> testMean() { +<a class="jxr_linenumber" name="L114" href="#L114">114</a> assertMean(Double.NEGATIVE_INFINITY, Double.POSITIVE_INFINITY, 0, 0); +<a class="jxr_linenumber" name="L115" href="#L115">115</a> assertMean(Double.POSITIVE_INFINITY, Double.POSITIVE_INFINITY, Double.POSITIVE_INFINITY, 0); +<a class="jxr_linenumber" name="L116" href="#L116">116</a> assertMean(Double.NEGATIVE_INFINITY, Double.NEGATIVE_INFINITY, Double.NEGATIVE_INFINITY, 0); +<a class="jxr_linenumber" name="L117" href="#L117">117</a> assertMean(0, Double.POSITIVE_INFINITY, Math.sqrt(2 / Math.PI), 1e-15); +<a class="jxr_linenumber" name="L118" href="#L118">118</a> assertMean(Double.NEGATIVE_INFINITY, 0, -Math.sqrt(2 / Math.PI), 1e-15); +<a class="jxr_linenumber" name="L119" href="#L119">119</a> +<a class="jxr_linenumber" name="L120" href="#L120">120</a> <strong class="jxr_keyword">for</strong> (<strong class="jxr_keyword">int</strong> x = -10; x <= 10; x++) { +<a class="jxr_linenumber" name="L121" href="#L121">121</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> expected = Math.sqrt(2 / Math.PI) / Erfcx.value(x / Math.sqrt(2)); +<a class="jxr_linenumber" name="L122" href="#L122">122</a> assertMean(x, Double.POSITIVE_INFINITY, expected, 1e-15); +<a class="jxr_linenumber" name="L123" href="#L123">123</a> } +<a class="jxr_linenumber" name="L124" href="#L124">124</a> +<a class="jxr_linenumber" name="L125" href="#L125">125</a> <strong class="jxr_keyword">for</strong> (<strong class="jxr_keyword">int</strong> i = -100; i <= 100; i++) { +<a class="jxr_linenumber" name="L126" href="#L126">126</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> x = Math.exp(i); +<a class="jxr_linenumber" name="L127" href="#L127">127</a> assertMean(-x, x, 0, 0); +<a class="jxr_linenumber" name="L128" href="#L128">128</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> expected = -Math.sqrt(2 / Math.PI) * Math.expm1(-x * x / 2) / Erf.value(x / Math.sqrt(2)); +<a class="jxr_linenumber" name="L129" href="#L129">129</a> assertMean(0, x, expected, 1e-15); +<a class="jxr_linenumber" name="L130" href="#L130">130</a> } +<a class="jxr_linenumber" name="L131" href="#L131">131</a> +<a class="jxr_linenumber" name="L132" href="#L132">132</a> assertMean(1e-44, 1e-43, 5.4999999999999999999999999999999999999999e-44, 1e-15); +<a class="jxr_linenumber" name="L133" href="#L133">133</a> +<a class="jxr_linenumber" name="L134" href="#L134">134</a> assertMean(100, 115, 100.00999800099926070518490239457545847490332879043, 1e-15); +<a class="jxr_linenumber" name="L135" href="#L135">135</a> assertMean(-1e6, -999000, -999000.00000100100100099899498898098, 1e-15); +<a class="jxr_linenumber" name="L136" href="#L136">136</a> assertMean(+1e6, Double.POSITIVE_INFINITY, +1.00000000000099999999999800000e6, 1e-15); +<a class="jxr_linenumber" name="L137" href="#L137">137</a> assertMean(Double.NEGATIVE_INFINITY, -1e6, -1.00000000000099999999999800000e6, 1e-15); +<a class="jxr_linenumber" name="L138" href="#L138">138</a> +<a class="jxr_linenumber" name="L139" href="#L139">139</a> assertMean(-1e200, 1e200, 0, 1e-15); +<a class="jxr_linenumber" name="L140" href="#L140">140</a> assertMean(0, +1e200, +0.797884560802865355879892119869, 1e-15); +<a class="jxr_linenumber" name="L141" href="#L141">141</a> assertMean(-1e200, 0, -0.797884560802865355879892119869, 1e-15); +<a class="jxr_linenumber" name="L142" href="#L142">142</a> +<a class="jxr_linenumber" name="L143" href="#L143">143</a> assertMean(50, 70, -2, 3, 50.171943499898757645751683644632860837133138152489, 1e-15); +<a class="jxr_linenumber" name="L144" href="#L144">144</a> assertMean(-100.0, 0.0, 0.0, 2.0986317998643735, -1.6744659119217125058885983754999713622460154892645, 1e-15); +<a class="jxr_linenumber" name="L145" href="#L145">145</a> assertMean(0.0, 0.9, 0.0, 0.07132755843183151, 0.056911157632522598806524588414964004271754161737065, 1e-15); +<a class="jxr_linenumber" name="L146" href="#L146">146</a> assertMean(-100.0, 100.0, 0.0, 17.185261847875548, 0, 1e-15); +<a class="jxr_linenumber" name="L147" href="#L147">147</a> assertMean(-100.0, 0.5, 0.0, 0.47383322897860064, -0.1267981330521791493635176736743283314399, 1e-15); +<a class="jxr_linenumber" name="L148" href="#L148">148</a> assertMean(-100.0, 100.0, 0.0, 17.185261847875548, 0, 1e-15); +<a class="jxr_linenumber" name="L149" href="#L149">149</a> +<a class="jxr_linenumber" name="L150" href="#L150">150</a> <strong class="jxr_keyword">for</strong> (<strong class="jxr_keyword">int</strong> i = -10; i <= 10; i++) { +<a class="jxr_linenumber" name="L151" href="#L151">151</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> a = Math.exp(i); +<a class="jxr_linenumber" name="L152" href="#L152">152</a> <strong class="jxr_keyword">for</strong> (<strong class="jxr_keyword">int</strong> j = -10; j <= 10; j++) { +<a class="jxr_linenumber" name="L153" href="#L153">153</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> b = Math.exp(j); +<a class="jxr_linenumber" name="L154" href="#L154">154</a> <strong class="jxr_keyword">if</strong> (a <= b) { +<a class="jxr_linenumber" name="L155" href="#L155">155</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> mean = TruncatedNormalDistribution.moment1(a, b); +<a class="jxr_linenumber" name="L156" href="#L156">156</a> Assertions.assertTrue(a <= mean && mean <= b); +<a class="jxr_linenumber" name="L157" href="#L157">157</a> } +<a class="jxr_linenumber" name="L158" href="#L158">158</a> } +<a class="jxr_linenumber" name="L159" href="#L159">159</a> } +<a class="jxr_linenumber" name="L160" href="#L160">160</a> +<a class="jxr_linenumber" name="L161" href="#L161">161</a> <em class="jxr_comment">// https://github.com/JuliaStats/Distributions.jl/issues/827, 1e-15);</em> +<a class="jxr_linenumber" name="L162" href="#L162">162</a> assertMean(0, 1000, 1000000, 1, 999.99999899899899900100501101901899090472046236710608108591983, 6e-14); +<a class="jxr_linenumber" name="L163" href="#L163">163</a> } +<a class="jxr_linenumber" name="L164" href="#L164">164</a> +<a class="jxr_linenumber" name="L165" href="#L165">165</a> <em class="jxr_javadoccomment">/**</em> +<a class="jxr_linenumber" name="L166" href="#L166">166</a> <em class="jxr_javadoccomment"> * Test variance cases adapted from the source implementation for the truncated</em> +<a class="jxr_linenumber" name="L167" href="#L167">167</a> <em class="jxr_javadoccomment"> * normal moments.</em> +<a class="jxr_linenumber" name="L168" href="#L168">168</a> <em class="jxr_javadoccomment"> *</em> +<a class="jxr_linenumber" name="L169" href="#L169">169</a> <em class="jxr_javadoccomment"> * @see <a href="<a href="https://github.com/cossio/TruncatedNormal.jl/blob/master/test/tnvar.jl"; target="alexandria_uri">https://github.com/cossio/TruncatedNormal.jl/blob/master/test/tnvar.jl</a>"></em> +<a class="jxr_linenumber" name="L170" href="#L170">170</a> <em class="jxr_javadoccomment"> * cossio TruncatedNormal variance tests</a></em> +<a class="jxr_linenumber" name="L171" href="#L171">171</a> <em class="jxr_javadoccomment"> */</em> +<a class="jxr_linenumber" name="L172" href="#L172">172</a> @Test +<a class="jxr_linenumber" name="L173" href="#L173">173</a> <strong class="jxr_keyword">void</strong> testVariance() { +<a class="jxr_linenumber" name="L174" href="#L174">174</a> assertVariance(Double.NEGATIVE_INFINITY, Double.POSITIVE_INFINITY, 1, 0); +<a class="jxr_linenumber" name="L175" href="#L175">175</a> assertVariance(Double.POSITIVE_INFINITY, Double.POSITIVE_INFINITY, 0, 0); +<a class="jxr_linenumber" name="L176" href="#L176">176</a> assertVariance(Double.NEGATIVE_INFINITY, Double.NEGATIVE_INFINITY, 0, 0); +<a class="jxr_linenumber" name="L177" href="#L177">177</a> assertVariance(0, Double.POSITIVE_INFINITY, 1 - 2 / Math.PI, 1e-15); +<a class="jxr_linenumber" name="L178" href="#L178">178</a> assertVariance(Double.NEGATIVE_INFINITY, 0, 1 - 2 / Math.PI, 1e-15); +<a class="jxr_linenumber" name="L179" href="#L179">179</a> +<a class="jxr_linenumber" name="L180" href="#L180">180</a> <strong class="jxr_keyword">for</strong> (<strong class="jxr_keyword">int</strong> x = -10; x <= 10; x++) { +<a class="jxr_linenumber" name="L181" href="#L181">181</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> expected = 1 + Math.sqrt(2 / Math.PI) * x / Erfcx.value(x / Math.sqrt(2)) - +<a class="jxr_linenumber" name="L182" href="#L182">182</a> (2 / Math.PI) / Math.pow(Erfcx.value(x / Math.sqrt(2)), 2); +<a class="jxr_linenumber" name="L183" href="#L183">183</a> assertVariance(x, Double.POSITIVE_INFINITY, expected, 1e-11); +<a class="jxr_linenumber" name="L184" href="#L184">184</a> } +<a class="jxr_linenumber" name="L185" href="#L185">185</a> +<a class="jxr_linenumber" name="L186" href="#L186">186</a> assertVariance(50, 70, 0.0003990431868038995479099272265360593305365, 1e-9); +<a class="jxr_linenumber" name="L187" href="#L187">187</a> +<a class="jxr_linenumber" name="L188" href="#L188">188</a> assertVariance(50, 70, -2, 3, 0.029373438107168350377591231295634273607812172191712, 1e-11); +<a class="jxr_linenumber" name="L189" href="#L189">189</a> assertVariance(-100.0, 0.0, 0.0, 2.0986317998643735, 1.6004193412141677189841357987638847137391508803335, 1e-15); +<a class="jxr_linenumber" name="L190" href="#L190">190</a> assertVariance(0.0, 0.9, 0.0, 0.07132755843183151, 0.0018487407287725028827020557707636415445504260892486, 1e-15); +<a class="jxr_linenumber" name="L191" href="#L191">191</a> assertVariance(-100.0, 100.0, 0.0, 17.185261847875548, 295.333163899557735486302841237124507431445, 1e-15); +<a class="jxr_linenumber" name="L192" href="#L192">192</a> assertVariance(-100.0, 0.5, 0.0, 0.47383322897860064, 0.145041095812679283837328561547251019229612, 1e-15); +<a class="jxr_linenumber" name="L193" href="#L193">193</a> assertVariance(-100.0, 100.0, 0.0, 17.185261847875548, 295.333163899557735486302841237124507431445, 1e-15); +<a class="jxr_linenumber" name="L194" href="#L194">194</a> assertVariance(-10000, 10000, 0, 1, 1, 1e-15); +<a class="jxr_linenumber" name="L195" href="#L195">195</a> +<a class="jxr_linenumber" name="L196" href="#L196">196</a> <em class="jxr_comment">// https://github.com/JuliaStats/Distributions.jl/issues/827</em> +<a class="jxr_linenumber" name="L197" href="#L197">197</a> Assertions.assertTrue(TruncatedNormalDistribution.variance(999000, 1e6) >= 0); +<a class="jxr_linenumber" name="L198" href="#L198">198</a> Assertions.assertTrue(TruncatedNormalDistribution.variance(-1000000, 1000 - 1000000) >= 0); +<a class="jxr_linenumber" name="L199" href="#L199">199</a> +<a class="jxr_linenumber" name="L200" href="#L200">200</a> <em class="jxr_comment">// These tests are marked as broken in the reference implementation.</em> +<a class="jxr_linenumber" name="L201" href="#L201">201</a> <em class="jxr_comment">// They present extreme deviations of the truncation bounds from the mean.</em> +<a class="jxr_linenumber" name="L202" href="#L202">202</a> <em class="jxr_comment">//assertVariance(1e6, Double.POSITIVE_INFINITY, 9.99999999994000000000050000000e-13, 1e-15);</em> +<a class="jxr_linenumber" name="L203" href="#L203">203</a> <em class="jxr_comment">//assertVariance(999000, 1e6, 1.00200300399898194688784897455e-12, 1e-15);</em> +<a class="jxr_linenumber" name="L204" href="#L204">204</a> <em class="jxr_comment">//assertVariance(-1e6, -999000, 1.00200300399898194688784897455e-12, 1e-15);</em> +<a class="jxr_linenumber" name="L205" href="#L205">205</a> } +<a class="jxr_linenumber" name="L206" href="#L206">206</a> +<a class="jxr_linenumber" name="L207" href="#L207">207</a> <em class="jxr_javadoccomment">/**</em> +<a class="jxr_linenumber" name="L208" href="#L208">208</a> <em class="jxr_javadoccomment"> * Test cases for computation of the moments. This hits edge cases including truncations</em> +<a class="jxr_linenumber" name="L209" href="#L209">209</a> <em class="jxr_javadoccomment"> * too extreme to have a probability range for the distribution.</em> +<a class="jxr_linenumber" name="L210" href="#L210">210</a> <em class="jxr_javadoccomment"> * The test ensures that the moments are computable for parameterisations</em> +<a class="jxr_linenumber" name="L211" href="#L211">211</a> <em class="jxr_javadoccomment"> * where the bounds fall within +/- 40 standard deviations from the mean.</em> +<a class="jxr_linenumber" name="L212" href="#L212">212</a> <em class="jxr_javadoccomment"> *</em> +<a class="jxr_linenumber" name="L213" href="#L213">213</a> <em class="jxr_javadoccomment"> * <p>Test data generated using a 128-bit implementation of the method using GCC lib quadmath</em> +<a class="jxr_linenumber" name="L214" href="#L214">214</a> <em class="jxr_javadoccomment"> * and Boost C++ Error function routines adapted to compute erfcx. Data verified using</em> +<a class="jxr_linenumber" name="L215" href="#L215">215</a> <em class="jxr_javadoccomment"> * the Julia implementation:</em> +<a class="jxr_linenumber" name="L216" href="#L216">216</a> <em class="jxr_javadoccomment"> * <pre></em> +<a class="jxr_linenumber" name="L217" href="#L217">217</a> <em class="jxr_javadoccomment"> * import Pkg</em> +<a class="jxr_linenumber" name="L218" href="#L218">218</a> <em class="jxr_javadoccomment"> * Pkg.add(url="<a href="https://github.com/cossio/TruncatedNormal.jl"; target="alexandria_uri">https://github.com/cossio/TruncatedNormal.jl</a>")</em> +<a class="jxr_linenumber" name="L219" href="#L219">219</a> <em class="jxr_javadoccomment"> * using TruncatedNormal</em> +<a class="jxr_linenumber" name="L220" href="#L220">220</a> <em class="jxr_javadoccomment"> *</em> +<a class="jxr_linenumber" name="L221" href="#L221">221</a> <em class="jxr_javadoccomment"> * tnmean(1.23, 4.56) # 1.7122093853640246</em> +<a class="jxr_linenumber" name="L222" href="#L222">222</a> <em class="jxr_javadoccomment"> * tnvar(1.23, 4.56) # 0.1739856461219162</em> +<a class="jxr_linenumber" name="L223" href="#L223">223</a> <em class="jxr_javadoccomment"> *</em> +<a class="jxr_linenumber" name="L224" href="#L224">224</a> <em class="jxr_javadoccomment"> * # Using BigFloat does not work on hard cases of the variance</em> +<a class="jxr_linenumber" name="L225" href="#L225">225</a> <em class="jxr_javadoccomment"> * tnvar(BigFloat(1.0), BigFloat(1.0000000000000002))</em> +<a class="jxr_linenumber" name="L226" href="#L226">226</a> <em class="jxr_javadoccomment"> * </pre></em> +<a class="jxr_linenumber" name="L227" href="#L227">227</a> <em class="jxr_javadoccomment"> *</em> +<a class="jxr_linenumber" name="L228" href="#L228">228</a> <em class="jxr_javadoccomment"> * <p>Computation of the mean is stable. Computation of the variance is not accurate as it</em> +<a class="jxr_linenumber" name="L229" href="#L229">229</a> <em class="jxr_javadoccomment"> * approaches machine epsilon (2^-52). Using Julia's BigFloat support does not allow computation</em> +<a class="jxr_linenumber" name="L230" href="#L230">230</a> <em class="jxr_javadoccomment"> * of the difficult cases listed below for the variance.</em> +<a class="jxr_linenumber" name="L231" href="#L231">231</a> <em class="jxr_javadoccomment"> *</em> +<a class="jxr_linenumber" name="L232" href="#L232">232</a> <em class="jxr_javadoccomment"> * @param lower Lower bound (inclusive) of the distribution, can be {@link Double#NEGATIVE_INFINITY}.</em> +<a class="jxr_linenumber" name="L233" href="#L233">233</a> <em class="jxr_javadoccomment"> * @param upper Upper bound (inclusive) of the distribution, can be {@link Double#POSITIVE_INFINITY}.</em> +<a class="jxr_linenumber" name="L234" href="#L234">234</a> <em class="jxr_javadoccomment"> * @param mean Expected mean</em> +<a class="jxr_linenumber" name="L235" href="#L235">235</a> <em class="jxr_javadoccomment"> * @param variance Expected variance</em> +<a class="jxr_linenumber" name="L236" href="#L236">236</a> <em class="jxr_javadoccomment"> * @param meanRelativeError Relative error tolerance for the mean</em> +<a class="jxr_linenumber" name="L237" href="#L237">237</a> <em class="jxr_javadoccomment"> * @param varianceRelativeError Relative error tolerance for the variance</em> +<a class="jxr_linenumber" name="L238" href="#L238">238</a> <em class="jxr_javadoccomment"> * (if set to negative the variance is allowed to be within 1.5 * epsilon of zero)</em> +<a class="jxr_linenumber" name="L239" href="#L239">239</a> <em class="jxr_javadoccomment"> */</em> +<a class="jxr_linenumber" name="L240" href="#L240">240</a> @ParameterizedTest +<a class="jxr_linenumber" name="L241" href="#L241">241</a> @CsvSource({ +<a class="jxr_linenumber" name="L242" href="#L242">242</a> <em class="jxr_comment">// Equal bounds</em> +<a class="jxr_linenumber" name="L243" href="#L243">243</a> <span class="jxr_string">"1.23, 1.23, 1.23, 0, 0, 0"</span>, +<a class="jxr_linenumber" name="L244" href="#L244">244</a> <span class="jxr_string">"1.23, 4.56, 1.7122093853640246, 0.1739856461219162, 1e-15, 5e-15"</span>, +<a class="jxr_linenumber" name="L245" href="#L245">245</a> +<a class="jxr_linenumber" name="L246" href="#L246">246</a> <em class="jxr_comment">// Effectively no truncation</em> +<a class="jxr_linenumber" name="L247" href="#L247">247</a> <span class="jxr_string">"-55, 60, 0, 1, 0, 0"</span>, +<a class="jxr_linenumber" name="L248" href="#L248">248</a> +<a class="jxr_linenumber" name="L249" href="#L249">249</a> <em class="jxr_comment">// Long tail</em> +<a class="jxr_linenumber" name="L250" href="#L250">250</a> <span class="jxr_string">"-100, 101, 1.3443134677817230433408433600205167e-2172, 1, 1e-15, 1e-15"</span>, +<a class="jxr_linenumber" name="L251" href="#L251">251</a> <span class="jxr_string">"-40, 101, 1.46327025083830317873709720033828097e-348, 1, 1e-15, 1e-15"</span>, +<a class="jxr_linenumber" name="L252" href="#L252">252</a> <span class="jxr_string">"-30, 101, 1.47364613487854751904949326604507453e-196, 1, 1e-15, 1e-15"</span>, +<a class="jxr_linenumber" name="L253" href="#L253">253</a> <span class="jxr_string">"-20, 101, 5.52094836215976318958273568278700042e-88, 1, 1e-15, 1e-15"</span>, +<a class="jxr_linenumber" name="L254" href="#L254">254</a> <span class="jxr_string">"-10, 101, 7.69459862670641934633909221175249367e-23, 0.999999999999999999999230540137329438, 1e-15, 1e-15"</span>, +<a class="jxr_linenumber" name="L255" href="#L255">255</a> <span class="jxr_string">"-5, 101, 1.48671994090490571244174411946057083e-06, 0.999992566398085139288753504945569711, 1e-15, 1e-15"</span>, +<a class="jxr_linenumber" name="L256" href="#L256">256</a> <span class="jxr_string">"-1, 101, 0.287599970939178361228670127385217202, 0.629686285776605400861244494862843017, 1e-15, 1e-15"</span>, +<a class="jxr_linenumber" name="L257" href="#L257">257</a> <span class="jxr_string">"0, 101, 0.797884560802865355879892119868763748, 0.363380227632418656924464946509942526, 1e-15, 1e-15"</span>, +<a class="jxr_linenumber" name="L258" href="#L258">258</a> <span class="jxr_string">"1, 101, 1.52513527616098120908909053639057876, 0.199097665570348791553367979096726767, 1e-15, 1e-14"</span>, +<a class="jxr_linenumber" name="L259" href="#L259">259</a> <span class="jxr_string">"5, 101, 5.18650396712584211561650896200523673, 0.032696434617112225345315807700917674, 1e-15, 1e-13"</span>, +<a class="jxr_linenumber" name="L260" href="#L260">260</a> <span class="jxr_string">"10, 101, 10.0980932339625119628436416537120371, 0.00944537782565626116413681765035684208, 1e-15, 1e-11"</span>, +<a class="jxr_linenumber" name="L261" href="#L261">261</a> <span class="jxr_string">"20, 101, 20.0497530685278505422140233087209891, 0.00246326161505216359968528619980015911, 1e-15, 1e-11"</span>, +<a class="jxr_linenumber" name="L262" href="#L262">262</a> <span class="jxr_string">"30, 101, 30.033259667433677037071124100012257, 0.00110377151189009100113674138540728116, 1e-15, 1e-10"</span>, +<a class="jxr_linenumber" name="L263" href="#L263">263</a> <span class="jxr_string">"40, 101, 40.0249688472072637232448709953697417, 0.000622668378591388773498879400697584317, 1e-15, 2e-9"</span>, +<a class="jxr_linenumber" name="L264" href="#L264">264</a> <span class="jxr_string">"100, 101, 100.009998000999260705184902394575471, 9.99400499482634503612772420030347819e-05, 1e-15, 2e-8"</span>, +<a class="jxr_linenumber" name="L265" href="#L265">265</a> +<a class="jxr_linenumber" name="L266" href="#L266">266</a> <em class="jxr_comment">// One-sided truncation</em> +<a class="jxr_linenumber" name="L267" href="#L267">267</a> <span class="jxr_string">"-5, Infinity, 1.4867199409049057124417441194605712e-06, 0.999992566398085139288753504945569711, 1e-14, 1e-14"</span>, +<a class="jxr_linenumber" name="L268" href="#L268">268</a> <span class="jxr_string">"-3, Infinity, 0.00443783904212566379330210431090259846, 0.98666678845825919379095350748267984, 1e-15, 1e-15"</span>, +<a class="jxr_linenumber" name="L269" href="#L269">269</a> <span class="jxr_string">"-1, Infinity, 0.287599970939178361228670127385217154, 0.629686285776605400861244494862843306, 1e-15, 1e-15"</span>, +<a class="jxr_linenumber" name="L270" href="#L270">270</a> <span class="jxr_string">"0, Infinity, 0.797884560802865355879892119868763748, 0.363380227632418656924464946509942526, 1e-15, 1e-15"</span>, +<a class="jxr_linenumber" name="L271" href="#L271">271</a> <span class="jxr_string">"1, Infinity, 1.52513527616098120908909053639057876, 0.199097665570348791553367979096726767, 1e-15, 1e-15"</span>, +<a class="jxr_linenumber" name="L272" href="#L272">272</a> <span class="jxr_string">"3, Infinity, 3.28309865493043650692809222681220005, 0.0705591867852681168624020577420568271, 1e-15, 2e-14"</span>, +<a class="jxr_linenumber" name="L273" href="#L273">273</a> <span class="jxr_string">"20, Infinity, 20.0497530685278505422140233087209891, 0.00246326161505216359968528619980015911, 1e-15, 1e-11"</span>, +<a class="jxr_linenumber" name="L274" href="#L274">274</a> <span class="jxr_string">"100, Infinity, 100.009998000999260705184902394575471, 9.99400499482634503612772420030347819e-05, 1e-15, 4e-8"</span>, +<a class="jxr_linenumber" name="L275" href="#L275">275</a> <em class="jxr_comment">// The variance method is inaccurate at this extreme</em> +<a class="jxr_linenumber" name="L276" href="#L276">276</a> <span class="jxr_string">"1e4, Infinity, 10000.0000999999980000000999999925986, 9.99999940000005002391967510312099493e-09, 1e-15, 0.8"</span>, +<a class="jxr_linenumber" name="L277" href="#L277">277</a> <span class="jxr_string">"1e6, Infinity, 1000000.00000099999999999800000000016, 9.99999999770471649802883928921316157e-13, 1e-15, 1.0"</span>, +<a class="jxr_linenumber" name="L278" href="#L278">278</a> <em class="jxr_comment">// XXX: The expected variance here is incorrect. It will be small but may be non zero.</em> +<a class="jxr_linenumber" name="L279" href="#L279">279</a> <em class="jxr_comment">// The computation will return 0. This hits an edge case in the code that detects when the</em> +<a class="jxr_linenumber" name="L280" href="#L280">280</a> <em class="jxr_comment">// variance computation fails.</em> +<a class="jxr_linenumber" name="L281" href="#L281">281</a> <span class="jxr_string">"1e100, Infinity, 1.00000000000000001590289110975991788e+100, 0, 1e-15, -1"</span>, +<a class="jxr_linenumber" name="L282" href="#L282">282</a> +<a class="jxr_linenumber" name="L283" href="#L283">283</a> <em class="jxr_comment">// XXX: The expected variance here is incorrect. It will be small but may be non zero.</em> +<a class="jxr_linenumber" name="L284" href="#L284">284</a> <em class="jxr_comment">// This hits an edge case where the computed variance (infinity) is above 1</em> +<a class="jxr_linenumber" name="L285" href="#L285">285</a> <span class="jxr_string">"1e290, 1e300, 1.00000000000000006172783352786715689e+290, 0, 1e-15, -1"</span>, +<a class="jxr_linenumber" name="L286" href="#L286">286</a> +<a class="jxr_linenumber" name="L287" href="#L287">287</a> <em class="jxr_comment">// Small ranges.</em> +<a class="jxr_linenumber" name="L288" href="#L288">288</a> <span class="jxr_string">"1, 1.1000000000000001, 1.04912545221799091312759556239135752, 0.000832596851563726615564931035799390151, 1e-15, 2e-12"</span>, +<a class="jxr_linenumber" name="L289" href="#L289">289</a> <span class="jxr_string">"5, 5.0999999999999996, 5.04581083165668427678725919870992629, 0.000822546087919772895415146023240560636, 1e-15, 2e-11"</span>, +<a class="jxr_linenumber" name="L290" href="#L290">290</a> <span class="jxr_string">"35, 35.100000000000001, 35.025438801080858717764612789648226, 0.000494605845872597846399929727938197022, 1e-15, 2e-9"</span>, +<a class="jxr_linenumber" name="L291" href="#L291">291</a> +<a class="jxr_linenumber" name="L292" href="#L292">292</a> <em class="jxr_comment">// (b-a) = 1 ULP</em> +<a class="jxr_linenumber" name="L293" href="#L293">293</a> <em class="jxr_comment">// XXX: The expected variance here is incorrect.</em> +<a class="jxr_linenumber" name="L294" href="#L294">294</a> <em class="jxr_comment">// It is upper limited to the variance of a uniform distribution.</em> +<a class="jxr_linenumber" name="L295" href="#L295">295</a> <em class="jxr_comment">// The computation will return 0. This hits an edge case in the code that detects when the</em> +<a class="jxr_linenumber" name="L296" href="#L296">296</a> <em class="jxr_comment">// variance computation fails.</em> +<a class="jxr_linenumber" name="L297" href="#L297">297</a> <em class="jxr_comment">// Spans p=8.327e-17 of the parent normal distribution</em> +<a class="jxr_linenumber" name="L298" href="#L298">298</a> <span class="jxr_string">"1, 1.0000000000000002, 1.00000000000000011091535982917837267, 0, 1e-15, -1"</span>, +<a class="jxr_linenumber" name="L299" href="#L299">299</a> <em class="jxr_comment">// Spans p=1.626e-19 of the parent normal distribution</em> +<a class="jxr_linenumber" name="L300" href="#L300">300</a> <span class="jxr_string">"4, 4.0000000000000009, 4.00000000000000044406536771487238653, 0, 1e-15, -1"</span>, +<a class="jxr_linenumber" name="L301" href="#L301">301</a> <em class="jxr_comment">// Spans p=1.925e-37 of the parent normal distribution</em> +<a class="jxr_linenumber" name="L302" href="#L302">302</a> <span class="jxr_string">"10, 10.000000000000002, 10.0000000000000008883225369216741152, 0, 1e-15, -1"</span>, +<a class="jxr_linenumber" name="L303" href="#L303">303</a> +<a class="jxr_linenumber" name="L304" href="#L304">304</a> <em class="jxr_comment">// Test for truncation close to zero.</em> +<a class="jxr_linenumber" name="L305" href="#L305">305</a> <em class="jxr_comment">// At z <= ~1.5e-8, exp(-0.5 * z * z) / sqrt(2 pi) == 1 / sqrt(2 pi)</em> +<a class="jxr_linenumber" name="L306" href="#L306">306</a> <em class="jxr_comment">// and the PDF is constant. It can be approximated as a uniform distribution.</em> +<a class="jxr_linenumber" name="L307" href="#L307">307</a> <em class="jxr_comment">// Here the mean is computable but the variance computation -> 0.</em> +<a class="jxr_linenumber" name="L308" href="#L308">308</a> <em class="jxr_comment">// The epsilons for the variance allow the test to pass if the second moment</em> +<a class="jxr_linenumber" name="L309" href="#L309">309</a> <em class="jxr_comment">// uses a uniform distribution approximation: (b^3 - a^3) / (3b - 3a).</em> +<a class="jxr_linenumber" name="L310" href="#L310">310</a> <em class="jxr_comment">// This is not done at present and the variance computes incorrectly and close to 0.</em> +<a class="jxr_linenumber" name="L311" href="#L311">311</a> <em class="jxr_comment">// The largest span covers only 5.8242e-8 of the probability range of the parent normal</em> +<a class="jxr_linenumber" name="L312" href="#L312">312</a> <em class="jxr_comment">// and these are not practical truncations.</em> +<a class="jxr_linenumber" name="L313" href="#L313">313</a> <span class="jxr_string">"-7.299454196351098e-8, 7.299454196351098e-8, 0, 1.77606771882092042827020676955306864e-15, 1e-15, -1e-15"</span>, +<a class="jxr_linenumber" name="L314" href="#L314">314</a> <span class="jxr_string">"-7.299454196351098e-8, 3.649727098175549e-8, -1.82486354908777262111748030604612676e-08, 9.99038091836768051420202283759953002e-16, 1e-15, -1e-15"</span>, +<a class="jxr_linenumber" name="L315" href="#L315">315</a> <span class="jxr_string">"-7.299454196351098e-8, 1.8248635490877744e-8, -2.7372953236316597672674778496667655e-08, 6.93776452664422342699175710737901419e-16, 1e-15, -2e-15"</span>, +<a class="jxr_linenumber" name="L316" href="#L316">316</a> <span class="jxr_string">"-7.299454196351098e-8, 0, -3.64972709817554726791073610445021429e-08, 4.44016929705230343732389204118195096e-16, 1e-15, -2e-15"</span>, +<a class="jxr_linenumber" name="L317" href="#L317">317</a> <span class="jxr_string">"-7.299454196351098e-8, -1.8248635490877744e-8, -4.56215887271943497112157190855901547e-08, 2.49759522957641055973442997155578316e-16, 3e-10, -5e-9"</span>, +<a class="jxr_linenumber" name="L318" href="#L318">318</a> <span class="jxr_string">"-7.299454196351098e-8, -3.649727098175549e-8, -5.47459064726332272497430210977513379e-08, 1.11004232421306844799494326433537718e-16, 3e-10, -2e-8"</span>, +<a class="jxr_linenumber" name="L319" href="#L319">319</a> <span class="jxr_string">"-3.649727098175549e-8, 3.649727098175549e-8, 0, 4.44016929705230343602092590994317462e-16, 1e-15, -1e-15"</span>, +<a class="jxr_linenumber" name="L320" href="#L320">320</a> <span class="jxr_string">"-3.649727098175549e-8, 1.8248635490877744e-8, -9.12431774543886994224314381693928319e-09, 2.49759522959192087703300220816741702e-16, 1e-15, -1e-15"</span>, +<a class="jxr_linenumber" name="L321" href="#L321">321</a> <span class="jxr_string">"-3.649727098175549e-8, 0, -1.82486354908777424165810069993271136e-08, 1.11004232426307600672725101668733634e-16, 1e-15, -2e-15"</span>, +<a class="jxr_linenumber" name="L322" href="#L322">322</a> <span class="jxr_string">"-3.649727098175549e-8, -1.8248635490877744e-8, -2.73729532363166159037567578213044937e-08, 2.77510581119222125912321725734620803e-17, 3e-10, -2e-8"</span>, +<a class="jxr_linenumber" name="L323" href="#L323">323</a> <span class="jxr_string">"-1.8248635490877744e-8, 1.8248635490877744e-8, 0, 1.11004232426307600757649604002272128e-16, 1e-15, -1e-15"</span>, +<a class="jxr_linenumber" name="L324" href="#L324">324</a> <span class="jxr_string">"-1.8248635490877744e-8, 9.124317745438872e-9, -4.5621588727194358257035396943085424e-09, 6.24398807397980267185125584627689296e-17, 1e-15, -1e-15"</span>, +<a class="jxr_linenumber" name="L325" href="#L325">325</a> <span class="jxr_string">"-1.8248635490877744e-8, 0, -9.12431774543887196791891930929818729e-09, 2.77510581065769011631256630479419225e-17, 1e-15, -1e-15"</span>, +<a class="jxr_linenumber" name="L326" href="#L326">326</a> <span class="jxr_string">"-9.124317745438872e-9, 9.124317745438872e-9, 0, 2.77510581065769013145632047586655539e-17, 1e-15, -1e-15"</span>, +<a class="jxr_linenumber" name="L327" href="#L327">327</a> <span class="jxr_string">"-9.124317745438872e-9, 4.562158872719436e-9, -2.28107943635971801967451582038414367e-09, 1.56099701849495071020338587207547036e-17, 1e-15, -1e-15"</span>, +<a class="jxr_linenumber" name="L328" href="#L328">328</a> <span class="jxr_string">"-9.124317745438872e-9, 0, -4.5621588727194360789130116308534264e-09, 6.93776452664422554954584023114952882e-18, 1e-15, -1e-15"</span>, +<a class="jxr_linenumber" name="L329" href="#L329">329</a> +<a class="jxr_linenumber" name="L330" href="#L330">330</a> <em class="jxr_comment">// The variance method is inaccurate at this extreme.</em> +<a class="jxr_linenumber" name="L331" href="#L331">331</a> <em class="jxr_comment">// Spans p=8.858e-17 of the parent normal distribution</em> +<a class="jxr_linenumber" name="L332" href="#L332">332</a> <span class="jxr_string">"0, 2.220446049250313e-16, 1.11022302462515654042363166809081572e-16, 4.14074938043255708407035257655783112e-33, 1e-15, -1e-2"</span>, +<a class="jxr_linenumber" name="L333" href="#L333">333</a> }) +<a class="jxr_linenumber" name="L334" href="#L334">334</a> <strong class="jxr_keyword">void</strong> testAdditionalMoments(<strong class="jxr_keyword">double</strong> lower, <strong class="jxr_keyword">double</strong> upper, +<a class="jxr_linenumber" name="L335" href="#L335">335</a> <strong class="jxr_keyword">double</strong> mean, <strong class="jxr_keyword">double</strong> variance, +<a class="jxr_linenumber" name="L336" href="#L336">336</a> <strong class="jxr_keyword">double</strong> meanRelativeError, <strong class="jxr_keyword">double</strong> varianceRelativeError) { +<a class="jxr_linenumber" name="L337" href="#L337">337</a> assertMean(lower, upper, mean, meanRelativeError); +<a class="jxr_linenumber" name="L338" href="#L338">338</a> <strong class="jxr_keyword">if</strong> (varianceRelativeError < 0) { +<a class="jxr_linenumber" name="L339" href="#L339">339</a> <em class="jxr_comment">// Known problem case.</em> +<a class="jxr_linenumber" name="L340" href="#L340">340</a> <em class="jxr_comment">// Allow small absolute variances using an absolute threshold of</em> +<a class="jxr_linenumber" name="L341" href="#L341">341</a> <em class="jxr_comment">// machine epsilon (2^-52) * 1.5. Any true variance approaching machine epsilon</em> +<a class="jxr_linenumber" name="L342" href="#L342">342</a> <em class="jxr_comment">// is allowed to be computed as small or zero but cannot be too large.</em> +<a class="jxr_linenumber" name="L343" href="#L343">343</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> <strong class="jxr_keyword">var</strong> = TruncatedNormalDistribution.variance(lower, upper); +<a class="jxr_linenumber" name="L344" href="#L344">344</a> Assertions.assertTrue(<strong class="jxr_keyword">var</strong> >= 0, () -> <span class="jxr_string">"Variance is not positive: "</span> + <strong class="jxr_keyword">var</strong>); +<a class="jxr_linenumber" name="L345" href="#L345">345</a> Assertions.assertEquals(<strong class="jxr_keyword">var</strong>, TruncatedNormalDistribution.variance(-upper, -lower)); +<a class="jxr_linenumber" name="L346" href="#L346">346</a> TestUtils.assertEquals(variance, <strong class="jxr_keyword">var</strong>, +<a class="jxr_linenumber" name="L347" href="#L347">347</a> createAbsOrRelTolerance(1.5 * 0x1.0p-52, -varianceRelativeError), +<a class="jxr_linenumber" name="L348" href="#L348">348</a> () -> String.format(<span class="jxr_string">"variance(%s, %s)"</span>, lower, upper)); +<a class="jxr_linenumber" name="L349" href="#L349">349</a> } <strong class="jxr_keyword">else</strong> { +<a class="jxr_linenumber" name="L350" href="#L350">350</a> assertVariance(lower, upper, variance, varianceRelativeError); +<a class="jxr_linenumber" name="L351" href="#L351">351</a> } +<a class="jxr_linenumber" name="L352" href="#L352">352</a> } +<a class="jxr_linenumber" name="L353" href="#L353">353</a> +<a class="jxr_linenumber" name="L354" href="#L354">354</a> <em class="jxr_javadoccomment">/**</em> +<a class="jxr_linenumber" name="L355" href="#L355">355</a> <em class="jxr_javadoccomment"> * Assert the mean of the truncated normal distribution is within the provided relative error.</em> +<a class="jxr_linenumber" name="L356" href="#L356">356</a> <em class="jxr_javadoccomment"> */</em> +<a class="jxr_linenumber" name="L357" href="#L357">357</a> <strong class="jxr_keyword">private</strong> <strong class="jxr_keyword">static</strong> <strong class="jxr_keyword">void</strong> assertMean(<strong class="jxr_keyword">double</strong> lower, <strong class="jxr_keyword">double</strong> upper, <strong class="jxr_keyword">double</strong> expected, <strong class="jxr_keyword">double</strong> eps) { +<a class="jxr_linenumber" name="L358" href="#L358">358</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> mean = TruncatedNormalDistribution.moment1(lower, upper); +<a class="jxr_linenumber" name="L359" href="#L359">359</a> Assertions.assertEquals(0 - mean, TruncatedNormalDistribution.moment1(-upper, -lower)); +<a class="jxr_linenumber" name="L360" href="#L360">360</a> TestUtils.assertEquals(expected, mean, DoubleTolerances.relative(eps), +<a class="jxr_linenumber" name="L361" href="#L361">361</a> () -> String.format(<span class="jxr_string">"mean(%s, %s)"</span>, lower, upper)); +<a class="jxr_linenumber" name="L362" href="#L362">362</a> } +<a class="jxr_linenumber" name="L363" href="#L363">363</a> +<a class="jxr_linenumber" name="L364" href="#L364">364</a> <em class="jxr_javadoccomment">/**</em> +<a class="jxr_linenumber" name="L365" href="#L365">365</a> <em class="jxr_javadoccomment"> * Assert the mean of the truncated normal distribution is within the provided relative error.</em> +<a class="jxr_linenumber" name="L366" href="#L366">366</a> <em class="jxr_javadoccomment"> * Helper method using range [lower, upper] of the parent normal distribution with the specified</em> +<a class="jxr_linenumber" name="L367" href="#L367">367</a> <em class="jxr_javadoccomment"> * mean and standard deviation.</em> +<a class="jxr_linenumber" name="L368" href="#L368">368</a> <em class="jxr_javadoccomment"> */</em> +<a class="jxr_linenumber" name="L369" href="#L369">369</a> <strong class="jxr_keyword">private</strong> <strong class="jxr_keyword">static</strong> <strong class="jxr_keyword">void</strong> assertMean(<strong class="jxr_keyword">double</strong> lower, <strong class="jxr_keyword">double</strong> upper, <strong class="jxr_keyword">double</strong> u, <strong class="jxr_keyword">double</strong> s, <strong class="jxr_keyword">double</strong> expected, <strong class="jxr_keyword">double</strong> eps) { +<a class="jxr_linenumber" name="L370" href="#L370">370</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> a = (lower - u) / s; +<a class="jxr_linenumber" name="L371" href="#L371">371</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> b = (upper - u) / s; +<a class="jxr_linenumber" name="L372" href="#L372">372</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> mean = u + TruncatedNormalDistribution.moment1(a, b) * s; +<a class="jxr_linenumber" name="L373" href="#L373">373</a> TestUtils.assertEquals(expected, mean, DoubleTolerances.relative(eps), +<a class="jxr_linenumber" name="L374" href="#L374">374</a> () -> String.format(<span class="jxr_string">"mean(%s, %s, %s, %s)"</span>, lower, upper, u, s)); +<a class="jxr_linenumber" name="L375" href="#L375">375</a> } +<a class="jxr_linenumber" name="L376" href="#L376">376</a> +<a class="jxr_linenumber" name="L377" href="#L377">377</a> <em class="jxr_javadoccomment">/**</em> +<a class="jxr_linenumber" name="L378" href="#L378">378</a> <em class="jxr_javadoccomment"> * Assert the variance of the truncated normal distribution is within the provided relative error.</em> +<a class="jxr_linenumber" name="L379" href="#L379">379</a> <em class="jxr_javadoccomment"> */</em> +<a class="jxr_linenumber" name="L380" href="#L380">380</a> <strong class="jxr_keyword">private</strong> <strong class="jxr_keyword">static</strong> <strong class="jxr_keyword">void</strong> assertVariance(<strong class="jxr_keyword">double</strong> lower, <strong class="jxr_keyword">double</strong> upper, <strong class="jxr_keyword">double</strong> expected, <strong class="jxr_keyword">double</strong> eps) { +<a class="jxr_linenumber" name="L381" href="#L381">381</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> <strong class="jxr_keyword">var</strong> = TruncatedNormalDistribution.variance(lower, upper); +<a class="jxr_linenumber" name="L382" href="#L382">382</a> Assertions.assertEquals(<strong class="jxr_keyword">var</strong>, TruncatedNormalDistribution.variance(-upper, -lower)); +<a class="jxr_linenumber" name="L383" href="#L383">383</a> TestUtils.assertEquals(expected, <strong class="jxr_keyword">var</strong>, DoubleTolerances.relative(eps), +<a class="jxr_linenumber" name="L384" href="#L384">384</a> () -> String.format(<span class="jxr_string">"variance(%s, %s)"</span>, lower, upper)); +<a class="jxr_linenumber" name="L385" href="#L385">385</a> } +<a class="jxr_linenumber" name="L386" href="#L386">386</a> +<a class="jxr_linenumber" name="L387" href="#L387">387</a> <em class="jxr_javadoccomment">/**</em> +<a class="jxr_linenumber" name="L388" href="#L388">388</a> <em class="jxr_javadoccomment"> * Assert the variance of the truncated normal distribution is within the provided relative error.</em> +<a class="jxr_linenumber" name="L389" href="#L389">389</a> <em class="jxr_javadoccomment"> * Helper method using range [lower, upper] of the parent normal distribution with the specified</em> +<a class="jxr_linenumber" name="L390" href="#L390">390</a> <em class="jxr_javadoccomment"> * mean and standard deviation.</em> +<a class="jxr_linenumber" name="L391" href="#L391">391</a> <em class="jxr_javadoccomment"> */</em> +<a class="jxr_linenumber" name="L392" href="#L392">392</a> <strong class="jxr_keyword">private</strong> <strong class="jxr_keyword">static</strong> <strong class="jxr_keyword">void</strong> assertVariance(<strong class="jxr_keyword">double</strong> lower, <strong class="jxr_keyword">double</strong> upper, <strong class="jxr_keyword">double</strong> u, <strong class="jxr_keyword">double</strong> s, <strong class="jxr_keyword">double</strong> expected, <strong class="jxr_keyword">double</strong> eps) { +<a class="jxr_linenumber" name="L393" href="#L393">393</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> a = (lower - u) / s; +<a class="jxr_linenumber" name="L394" href="#L394">394</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> b = (upper - u) / s; +<a class="jxr_linenumber" name="L395" href="#L395">395</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> <strong class="jxr_keyword">var</strong> = TruncatedNormalDistribution.variance(a, b) * s * s; +<a class="jxr_linenumber" name="L396" href="#L396">396</a> TestUtils.assertEquals(expected, <strong class="jxr_keyword">var</strong>, DoubleTolerances.relative(eps), +<a class="jxr_linenumber" name="L397" href="#L397">397</a> () -> String.format(<span class="jxr_string">"variance(%s, %s, %s, %s)"</span>, lower, upper, u, s)); +<a class="jxr_linenumber" name="L398" href="#L398">398</a> } +<a class="jxr_linenumber" name="L399" href="#L399">399</a> } +</pre> +<hr/> +<div id="footer">Copyright © 2018–2022 <a href="https://www.apache.org/";>The Apache Software Foundation</a>. All rights reserved.</div> +</body> +</html>
Added: dev/commons/statistics/1.0-RC1/site/xref-test/org/apache/commons/statistics/distribution/UniformContinuousDistributionTest.html ============================================================================== --- dev/commons/statistics/1.0-RC1/site/xref-test/org/apache/commons/statistics/distribution/UniformContinuousDistributionTest.html (added) +++ dev/commons/statistics/1.0-RC1/site/xref-test/org/apache/commons/statistics/distribution/UniformContinuousDistributionTest.html Thu Dec 1 16:47:12 2022 @@ -0,0 +1,176 @@ +<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd";> +<html xmlns="http://www.w3.org/1999/xhtml"; xml:lang="en" lang="en"> +<head><meta http-equiv="content-type" content="text/html; charset=UTF-8" /> +<title>UniformContinuousDistributionTest xref</title> +<link type="text/css" rel="stylesheet" href="../../../../../stylesheet.css" /> +</head> +<body> +<div id="overview"><a href="../../../../../../testapidocs/org/apache/commons/statistics/distribution/UniformContinuousDistributionTest.html">View Javadoc</a></div><pre> +<a class="jxr_linenumber" name="L1" href="#L1">1</a> <em class="jxr_comment">/*</em> +<a class="jxr_linenumber" name="L2" href="#L2">2</a> <em class="jxr_comment"> * Licensed to the Apache Software Foundation (ASF) under one or more</em> +<a class="jxr_linenumber" name="L3" href="#L3">3</a> <em class="jxr_comment"> * contributor license agreements. See the NOTICE file distributed with</em> +<a class="jxr_linenumber" name="L4" href="#L4">4</a> <em class="jxr_comment"> * this work for additional information regarding copyright ownership.</em> +<a class="jxr_linenumber" name="L5" href="#L5">5</a> <em class="jxr_comment"> * The ASF licenses this file to You under the Apache License, Version 2.0</em> +<a class="jxr_linenumber" name="L6" href="#L6">6</a> <em class="jxr_comment"> * (the "License"); you may not use this file except in compliance with</em> +<a class="jxr_linenumber" name="L7" href="#L7">7</a> <em class="jxr_comment"> * the License. You may obtain a copy of the License at</em> +<a class="jxr_linenumber" name="L8" href="#L8">8</a> <em class="jxr_comment"> *</em> +<a class="jxr_linenumber" name="L9" href="#L9">9</a> <em class="jxr_comment"> * <a href="http://www.apache.org/licenses/LICENSE-2.0"; target="alexandria_uri">http://www.apache.org/licenses/LICENSE-2.0</a></em> +<a class="jxr_linenumber" name="L10" href="#L10">10</a> <em class="jxr_comment"> *</em> +<a class="jxr_linenumber" name="L11" href="#L11">11</a> <em class="jxr_comment"> * Unless required by applicable law or agreed to in writing, software</em> +<a class="jxr_linenumber" name="L12" href="#L12">12</a> <em class="jxr_comment"> * distributed under the License is distributed on an "AS IS" BASIS,</em> +<a class="jxr_linenumber" name="L13" href="#L13">13</a> <em class="jxr_comment"> * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.</em> +<a class="jxr_linenumber" name="L14" href="#L14">14</a> <em class="jxr_comment"> * See the License for the specific language governing permissions and</em> +<a class="jxr_linenumber" name="L15" href="#L15">15</a> <em class="jxr_comment"> * limitations under the License.</em> +<a class="jxr_linenumber" name="L16" href="#L16">16</a> <em class="jxr_comment"> */</em> +<a class="jxr_linenumber" name="L17" href="#L17">17</a> +<a class="jxr_linenumber" name="L18" href="#L18">18</a> <strong class="jxr_keyword">package</strong> org.apache.commons.statistics.distribution; +<a class="jxr_linenumber" name="L19" href="#L19">19</a> +<a class="jxr_linenumber" name="L20" href="#L20">20</a> <strong class="jxr_keyword">import</strong> java.util.stream.Stream; +<a class="jxr_linenumber" name="L21" href="#L21">21</a> <strong class="jxr_keyword">import</strong> org.apache.commons.rng.UniformRandomProvider; +<a class="jxr_linenumber" name="L22" href="#L22">22</a> <strong class="jxr_keyword">import</strong> org.apache.commons.rng.sampling.distribution.ContinuousSampler; +<a class="jxr_linenumber" name="L23" href="#L23">23</a> <strong class="jxr_keyword">import</strong> org.apache.commons.rng.sampling.distribution.ContinuousUniformSampler; +<a class="jxr_linenumber" name="L24" href="#L24">24</a> <strong class="jxr_keyword">import</strong> org.apache.commons.rng.simple.RandomSource; +<a class="jxr_linenumber" name="L25" href="#L25">25</a> <strong class="jxr_keyword">import</strong> org.junit.jupiter.api.Assertions; +<a class="jxr_linenumber" name="L26" href="#L26">26</a> <strong class="jxr_keyword">import</strong> org.junit.jupiter.api.Test; +<a class="jxr_linenumber" name="L27" href="#L27">27</a> <strong class="jxr_keyword">import</strong> org.junit.jupiter.params.ParameterizedTest; +<a class="jxr_linenumber" name="L28" href="#L28">28</a> <strong class="jxr_keyword">import</strong> org.junit.jupiter.params.provider.Arguments; +<a class="jxr_linenumber" name="L29" href="#L29">29</a> <strong class="jxr_keyword">import</strong> org.junit.jupiter.params.provider.CsvSource; +<a class="jxr_linenumber" name="L30" href="#L30">30</a> <strong class="jxr_keyword">import</strong> org.junit.jupiter.params.provider.MethodSource; +<a class="jxr_linenumber" name="L31" href="#L31">31</a> +<a class="jxr_linenumber" name="L32" href="#L32">32</a> <em class="jxr_javadoccomment">/**</em> +<a class="jxr_linenumber" name="L33" href="#L33">33</a> <em class="jxr_javadoccomment"> * Test cases for {@link UniformContinuousDistribution}.</em> +<a class="jxr_linenumber" name="L34" href="#L34">34</a> <em class="jxr_javadoccomment"> * Extends {@link BaseContinuousDistributionTest}. See javadoc of that class for details.</em> +<a class="jxr_linenumber" name="L35" href="#L35">35</a> <em class="jxr_javadoccomment"> */</em> +<a class="jxr_linenumber" name="L36" href="#L36">36</a> <strong class="jxr_keyword">class</strong> <a name="UniformContinuousDistributionTest" href="../../../../../org/apache/commons/statistics/distribution/UniformContinuousDistributionTest.html#UniformContinuousDistributionTest">UniformContinuousDistributionTest</a> <strong class="jxr_keyword">extends</strong> <a name="BaseContinuousDistributionTest" href="../../../../../org/apache/commons/statistics/distribution/BaseContinuousDistributionTest.html#BaseContinuousDistributionTest">BaseContinuousDistributionTest</a> { +<a class="jxr_linenumber" name="L37" href="#L37">37</a> @Override +<a class="jxr_linenumber" name="L38" href="#L38">38</a> ContinuousDistribution makeDistribution(Object... parameters) { +<a class="jxr_linenumber" name="L39" href="#L39">39</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> lower = (Double) parameters[0]; +<a class="jxr_linenumber" name="L40" href="#L40">40</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> upper = (Double) parameters[1]; +<a class="jxr_linenumber" name="L41" href="#L41">41</a> <strong class="jxr_keyword">return</strong> UniformContinuousDistribution.of(lower, upper); +<a class="jxr_linenumber" name="L42" href="#L42">42</a> } +<a class="jxr_linenumber" name="L43" href="#L43">43</a> +<a class="jxr_linenumber" name="L44" href="#L44">44</a> @Override +<a class="jxr_linenumber" name="L45" href="#L45">45</a> Object[][] makeInvalidParameters() { +<a class="jxr_linenumber" name="L46" href="#L46">46</a> <strong class="jxr_keyword">return</strong> <strong class="jxr_keyword">new</strong> Object[][] { +<a class="jxr_linenumber" name="L47" href="#L47">47</a> {0.0, 0.0}, +<a class="jxr_linenumber" name="L48" href="#L48">48</a> {1.0, 0.0}, +<a class="jxr_linenumber" name="L49" href="#L49">49</a> <em class="jxr_comment">// Range not finite</em> +<a class="jxr_linenumber" name="L50" href="#L50">50</a> {-Double.MAX_VALUE, Double.MAX_VALUE}, +<a class="jxr_linenumber" name="L51" href="#L51">51</a> {Double.NaN, 1.0}, +<a class="jxr_linenumber" name="L52" href="#L52">52</a> {0.0, Double.NaN}, +<a class="jxr_linenumber" name="L53" href="#L53">53</a> }; +<a class="jxr_linenumber" name="L54" href="#L54">54</a> } +<a class="jxr_linenumber" name="L55" href="#L55">55</a> +<a class="jxr_linenumber" name="L56" href="#L56">56</a> @Override +<a class="jxr_linenumber" name="L57" href="#L57">57</a> String[] getParameterNames() { +<a class="jxr_linenumber" name="L58" href="#L58">58</a> <strong class="jxr_keyword">return</strong> <strong class="jxr_keyword">new</strong> String[] {<span class="jxr_string">"SupportLowerBound"</span>, <span class="jxr_string">"SupportUpperBound"</span>}; +<a class="jxr_linenumber" name="L59" href="#L59">59</a> } +<a class="jxr_linenumber" name="L60" href="#L60">60</a> +<a class="jxr_linenumber" name="L61" href="#L61">61</a> @Override +<a class="jxr_linenumber" name="L62" href="#L62">62</a> <strong class="jxr_keyword">protected</strong> <strong class="jxr_keyword">double</strong> getRelativeTolerance() { +<a class="jxr_linenumber" name="L63" href="#L63">63</a> <em class="jxr_comment">// Tolerance is 4.440892098500626E-16</em> +<a class="jxr_linenumber" name="L64" href="#L64">64</a> <strong class="jxr_keyword">return</strong> 2 * RELATIVE_EPS; +<a class="jxr_linenumber" name="L65" href="#L65">65</a> } +<a class="jxr_linenumber" name="L66" href="#L66">66</a> +<a class="jxr_linenumber" name="L67" href="#L67">67</a> <em class="jxr_comment">//-------------------- Additional test cases -------------------------------</em> +<a class="jxr_linenumber" name="L68" href="#L68">68</a> +<a class="jxr_linenumber" name="L69" href="#L69">69</a> @ParameterizedTest +<a class="jxr_linenumber" name="L70" href="#L70">70</a> @MethodSource +<a class="jxr_linenumber" name="L71" href="#L71">71</a> <strong class="jxr_keyword">void</strong> testAdditionalMoments(<strong class="jxr_keyword">double</strong> lower, <strong class="jxr_keyword">double</strong> upper, <strong class="jxr_keyword">double</strong> mean, <strong class="jxr_keyword">double</strong> variance) { +<a class="jxr_linenumber" name="L72" href="#L72">72</a> <strong class="jxr_keyword">final</strong> UniformContinuousDistribution dist = UniformContinuousDistribution.of(lower, upper); +<a class="jxr_linenumber" name="L73" href="#L73">73</a> testMoments(dist, mean, variance, DoubleTolerances.equals()); +<a class="jxr_linenumber" name="L74" href="#L74">74</a> } +<a class="jxr_linenumber" name="L75" href="#L75">75</a> +<a class="jxr_linenumber" name="L76" href="#L76">76</a> <strong class="jxr_keyword">static</strong> Stream<Arguments> testAdditionalMoments() { +<a class="jxr_linenumber" name="L77" href="#L77">77</a> <strong class="jxr_keyword">return</strong> Stream.of( +<a class="jxr_linenumber" name="L78" href="#L78">78</a> Arguments.of(0, 1, 0.5, 1 / 12.0), +<a class="jxr_linenumber" name="L79" href="#L79">79</a> Arguments.of(-1.5, 0.6, -0.45, 0.3675), +<a class="jxr_linenumber" name="L80" href="#L80">80</a> Arguments.of(Double.MAX_VALUE / 2, Double.MAX_VALUE, Double.MAX_VALUE - Double.MAX_VALUE / 4, Double.POSITIVE_INFINITY) +<a class="jxr_linenumber" name="L81" href="#L81">81</a> ); +<a class="jxr_linenumber" name="L82" href="#L82">82</a> } +<a class="jxr_linenumber" name="L83" href="#L83">83</a> +<a class="jxr_linenumber" name="L84" href="#L84">84</a> <em class="jxr_javadoccomment">/**</em> +<a class="jxr_linenumber" name="L85" href="#L85">85</a> <em class="jxr_javadoccomment"> * Check accuracy of analytical inverse CDF. Fails if a solver is used</em> +<a class="jxr_linenumber" name="L86" href="#L86">86</a> <em class="jxr_javadoccomment"> * with the default accuracy.</em> +<a class="jxr_linenumber" name="L87" href="#L87">87</a> <em class="jxr_javadoccomment"> */</em> +<a class="jxr_linenumber" name="L88" href="#L88">88</a> @Test +<a class="jxr_linenumber" name="L89" href="#L89">89</a> <strong class="jxr_keyword">void</strong> testInverseCumulativeDistribution() { +<a class="jxr_linenumber" name="L90" href="#L90">90</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> upper = 1e-9; +<a class="jxr_linenumber" name="L91" href="#L91">91</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> tiny = 0x1.0p-100; +<a class="jxr_linenumber" name="L92" href="#L92">92</a> +<a class="jxr_linenumber" name="L93" href="#L93">93</a> <strong class="jxr_keyword">final</strong> UniformContinuousDistribution dist = UniformContinuousDistribution.of(0, upper); +<a class="jxr_linenumber" name="L94" href="#L94">94</a> Assertions.assertEquals(2.5e-10, dist.inverseCumulativeProbability(0.25)); +<a class="jxr_linenumber" name="L95" href="#L95">95</a> Assertions.assertEquals(tiny * upper, dist.inverseCumulativeProbability(tiny)); +<a class="jxr_linenumber" name="L96" href="#L96">96</a> +<a class="jxr_linenumber" name="L97" href="#L97">97</a> <strong class="jxr_keyword">final</strong> UniformContinuousDistribution dist2 = UniformContinuousDistribution.of(-upper, 0); +<a class="jxr_linenumber" name="L98" href="#L98">98</a> <em class="jxr_comment">// This is inexact</em> +<a class="jxr_linenumber" name="L99" href="#L99">99</a> Assertions.assertEquals(-7.5e-10, dist2.inverseCumulativeProbability(0.25), Math.ulp(-7.5e-10)); +<a class="jxr_linenumber" name="L100" href="#L100">100</a> Assertions.assertEquals(-upper + tiny * upper, dist2.inverseCumulativeProbability(tiny)); +<a class="jxr_linenumber" name="L101" href="#L101">101</a> } +<a class="jxr_linenumber" name="L102" href="#L102">102</a> +<a class="jxr_linenumber" name="L103" href="#L103">103</a> <em class="jxr_javadoccomment">/**</em> +<a class="jxr_linenumber" name="L104" href="#L104">104</a> <em class="jxr_javadoccomment"> * Test the probability in a range uses the exact computation of</em> +<a class="jxr_linenumber" name="L105" href="#L105">105</a> <em class="jxr_javadoccomment"> * {@code (x1 - x0) / (upper - lower)} assuming x0 and x1 are within [lower, upper].</em> +<a class="jxr_linenumber" name="L106" href="#L106">106</a> <em class="jxr_javadoccomment"> * This test will fail if the distribution uses the default implementation in</em> +<a class="jxr_linenumber" name="L107" href="#L107">107</a> <em class="jxr_javadoccomment"> * {@link AbstractContinuousDistribution}.</em> +<a class="jxr_linenumber" name="L108" href="#L108">108</a> <em class="jxr_javadoccomment"> */</em> +<a class="jxr_linenumber" name="L109" href="#L109">109</a> @ParameterizedTest +<a class="jxr_linenumber" name="L110" href="#L110">110</a> @CsvSource(value = { +<a class="jxr_linenumber" name="L111" href="#L111">111</a> <span class="jxr_string">"-1.6358421681, -0.566237287234"</span>, +<a class="jxr_linenumber" name="L112" href="#L112">112</a> <span class="jxr_string">"-10.23678, 234.234"</span>, +<a class="jxr_linenumber" name="L113" href="#L113">113</a> <span class="jxr_string">"234.2342, 54322342.13"</span>, +<a class="jxr_linenumber" name="L114" href="#L114">114</a> }) +<a class="jxr_linenumber" name="L115" href="#L115">115</a> <strong class="jxr_keyword">void</strong> testProbabilityRange(<strong class="jxr_keyword">double</strong> lower, <strong class="jxr_keyword">double</strong> upper) { +<a class="jxr_linenumber" name="L116" href="#L116">116</a> <strong class="jxr_keyword">final</strong> UniformContinuousDistribution dist = UniformContinuousDistribution.of(lower, upper); +<a class="jxr_linenumber" name="L117" href="#L117">117</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> r = upper - lower; +<a class="jxr_linenumber" name="L118" href="#L118">118</a> <strong class="jxr_keyword">final</strong> UniformRandomProvider rng = RandomSource.XO_RO_SHI_RO_128_PP.create(); +<a class="jxr_linenumber" name="L119" href="#L119">119</a> <strong class="jxr_keyword">final</strong> ContinuousSampler sampler = ContinuousUniformSampler.of(rng, lower, upper); +<a class="jxr_linenumber" name="L120" href="#L120">120</a> <strong class="jxr_keyword">for</strong> (<strong class="jxr_keyword">int</strong> i = 0; i < 100; i++) { +<a class="jxr_linenumber" name="L121" href="#L121">121</a> <strong class="jxr_keyword">double</strong> x0 = sampler.sample(); +<a class="jxr_linenumber" name="L122" href="#L122">122</a> <strong class="jxr_keyword">double</strong> x1 = sampler.sample(); +<a class="jxr_linenumber" name="L123" href="#L123">123</a> <strong class="jxr_keyword">if</strong> (x1 < x0) { +<a class="jxr_linenumber" name="L124" href="#L124">124</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> tmp = x0; +<a class="jxr_linenumber" name="L125" href="#L125">125</a> x1 = x0; +<a class="jxr_linenumber" name="L126" href="#L126">126</a> x0 = tmp; +<a class="jxr_linenumber" name="L127" href="#L127">127</a> } +<a class="jxr_linenumber" name="L128" href="#L128">128</a> Assertions.assertEquals((x1 - x0) / r, dist.probability(x0, x1)); +<a class="jxr_linenumber" name="L129" href="#L129">129</a> } +<a class="jxr_linenumber" name="L130" href="#L130">130</a> } +<a class="jxr_linenumber" name="L131" href="#L131">131</a> +<a class="jxr_linenumber" name="L132" href="#L132">132</a> @Test +<a class="jxr_linenumber" name="L133" href="#L133">133</a> <strong class="jxr_keyword">void</strong> testProbabilityRangeEdgeCases() { +<a class="jxr_linenumber" name="L134" href="#L134">134</a> <strong class="jxr_keyword">final</strong> UniformContinuousDistribution dist = UniformContinuousDistribution.of(0, 11); +<a class="jxr_linenumber" name="L135" href="#L135">135</a> +<a class="jxr_linenumber" name="L136" href="#L136">136</a> Assertions.assertThrows(DistributionException.<strong class="jxr_keyword">class</strong>, () -> dist.probability(4, 3)); +<a class="jxr_linenumber" name="L137" href="#L137">137</a> +<a class="jxr_linenumber" name="L138" href="#L138">138</a> <em class="jxr_comment">// x0 >= upper</em> +<a class="jxr_linenumber" name="L139" href="#L139">139</a> Assertions.assertEquals(0, dist.probability(11, 16)); +<a class="jxr_linenumber" name="L140" href="#L140">140</a> Assertions.assertEquals(0, dist.probability(15, 16)); +<a class="jxr_linenumber" name="L141" href="#L141">141</a> <em class="jxr_comment">// x1 < lower</em> +<a class="jxr_linenumber" name="L142" href="#L142">142</a> Assertions.assertEquals(0, dist.probability(-3, -1)); +<a class="jxr_linenumber" name="L143" href="#L143">143</a> +<a class="jxr_linenumber" name="L144" href="#L144">144</a> <em class="jxr_comment">// x0 == x1</em> +<a class="jxr_linenumber" name="L145" href="#L145">145</a> Assertions.assertEquals(0, dist.probability(4.12, 4.12)); +<a class="jxr_linenumber" name="L146" href="#L146">146</a> Assertions.assertEquals(0, dist.probability(5.68, 5.68)); +<a class="jxr_linenumber" name="L147" href="#L147">147</a> +<a class="jxr_linenumber" name="L148" href="#L148">148</a> <em class="jxr_comment">// x1 > upper</em> +<a class="jxr_linenumber" name="L149" href="#L149">149</a> Assertions.assertEquals(1, dist.probability(0, 16)); +<a class="jxr_linenumber" name="L150" href="#L150">150</a> Assertions.assertEquals((11 - 3.45) / 11, dist.probability(3.45, 16)); +<a class="jxr_linenumber" name="L151" href="#L151">151</a> Assertions.assertEquals((11 - 4.89) / 11, dist.probability(4.89, 16)); +<a class="jxr_linenumber" name="L152" href="#L152">152</a> Assertions.assertEquals(0, dist.probability(11, 16)); +<a class="jxr_linenumber" name="L153" href="#L153">153</a> +<a class="jxr_linenumber" name="L154" href="#L154">154</a> <em class="jxr_comment">// x0 < lower</em> +<a class="jxr_linenumber" name="L155" href="#L155">155</a> Assertions.assertEquals(2.0 / 11, dist.probability(-2, 2)); +<a class="jxr_linenumber" name="L156" href="#L156">156</a> Assertions.assertEquals(3.0 / 11, dist.probability(-2, 3)); +<a class="jxr_linenumber" name="L157" href="#L157">157</a> Assertions.assertEquals(4.0 / 11, dist.probability(-2, 4)); +<a class="jxr_linenumber" name="L158" href="#L158">158</a> Assertions.assertEquals(1.0, dist.probability(-2, 11)); +<a class="jxr_linenumber" name="L159" href="#L159">159</a> +<a class="jxr_linenumber" name="L160" href="#L160">160</a> <em class="jxr_comment">// x1 > upper && x0 < lower</em> +<a class="jxr_linenumber" name="L161" href="#L161">161</a> Assertions.assertEquals(1, dist.probability(-2, 16)); +<a class="jxr_linenumber" name="L162" href="#L162">162</a> } +<a class="jxr_linenumber" name="L163" href="#L163">163</a> } +</pre> +<hr/> +<div id="footer">Copyright © 2018–2022 <a href="https://www.apache.org/";>The Apache Software Foundation</a>. All rights reserved.</div> +</body> +</html>
