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From ericbarnh...@apache.org
Subject [03/51] [partial] commons-complex git commit: First commit to commons-complex
Date Wed, 04 Jan 2017 10:05:13 GMT
http://git-wip-us.apache.org/repos/asf/commons-complex/blob/b0db8fca/site-content/.svn/pristine/06/0610c7cf999e028d85dba8bdc7097be6b825574f.svn-base
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diff --git a/site-content/.svn/pristine/06/0610c7cf999e028d85dba8bdc7097be6b825574f.svn-base b/site-content/.svn/pristine/06/0610c7cf999e028d85dba8bdc7097be6b825574f.svn-base
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+++ b/site-content/.svn/pristine/06/0610c7cf999e028d85dba8bdc7097be6b825574f.svn-base
@@ -0,0 +1,24 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd">
+<!-- NewPage -->
+<html lang="en">
+<head>
+<meta http-equiv="Content-Type" content="text/html" charset="UTF-8">
+<title>org.apache.commons.math3.optimization.direct (Apache Commons Math 3.5 Test API)</title>
+<link rel="stylesheet" type="text/css" href="../../../../../../stylesheet.css" title="Style">
+</head>
+<body>
+<h1 class="bar"><a href="../../../../../../org/apache/commons/math3/optimization/direct/package-summary.html" target="classFrame">org.apache.commons.math3.optimization.direct</a></h1>
+<div class="indexContainer">
+<h2 title="Classes">Classes</h2>
+<ul title="Classes">
+<li><a href="BOBYQAOptimizerTest.html" title="class in org.apache.commons.math3.optimization.direct" target="classFrame">BOBYQAOptimizerTest</a></li>
+<li><a href="CMAESOptimizerTest.html" title="class in org.apache.commons.math3.optimization.direct" target="classFrame">CMAESOptimizerTest</a></li>
+<li><a href="MultivariateFunctionMappingAdapterTest.html" title="class in org.apache.commons.math3.optimization.direct" target="classFrame">MultivariateFunctionMappingAdapterTest</a></li>
+<li><a href="MultivariateFunctionPenaltyAdapterTest.html" title="class in org.apache.commons.math3.optimization.direct" target="classFrame">MultivariateFunctionPenaltyAdapterTest</a></li>
+<li><a href="PowellOptimizerTest.html" title="class in org.apache.commons.math3.optimization.direct" target="classFrame">PowellOptimizerTest</a></li>
+<li><a href="SimplexOptimizerMultiDirectionalTest.html" title="class in org.apache.commons.math3.optimization.direct" target="classFrame">SimplexOptimizerMultiDirectionalTest</a></li>
+<li><a href="SimplexOptimizerNelderMeadTest.html" title="class in org.apache.commons.math3.optimization.direct" target="classFrame">SimplexOptimizerNelderMeadTest</a></li>
+</ul>
+</div>
+</body>
+</html>

http://git-wip-us.apache.org/repos/asf/commons-complex/blob/b0db8fca/site-content/.svn/pristine/06/061feea0b6eb9c38a4f3469c3e6f657513afba3a.svn-base
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diff --git a/site-content/.svn/pristine/06/061feea0b6eb9c38a4f3469c3e6f657513afba3a.svn-base b/site-content/.svn/pristine/06/061feea0b6eb9c38a4f3469c3e6f657513afba3a.svn-base
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@@ -0,0 +1,340 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd">
+<html lang="en">
+<head>
+<title>Source code</title>
+<link rel="stylesheet" type="text/css" href="../../../../../../../stylesheet.css" title="Style">
+</head>
+<body>
+<div class="sourceContainer">
+<pre><span class="sourceLineNo">001</span>/*<a name="line.1"></a>
+<span class="sourceLineNo">002</span> * Licensed to the Apache Software Foundation (ASF) under one or more<a name="line.2"></a>
+<span class="sourceLineNo">003</span> * contributor license agreements.  See the NOTICE file distributed with<a name="line.3"></a>
+<span class="sourceLineNo">004</span> * this work for additional information regarding copyright ownership.<a name="line.4"></a>
+<span class="sourceLineNo">005</span> * The ASF licenses this file to You under the Apache License, Version 2.0<a name="line.5"></a>
+<span class="sourceLineNo">006</span> * (the "License"); you may not use this file except in compliance with<a name="line.6"></a>
+<span class="sourceLineNo">007</span> * the License.  You may obtain a copy of the License at<a name="line.7"></a>
+<span class="sourceLineNo">008</span> *<a name="line.8"></a>
+<span class="sourceLineNo">009</span> *      http://www.apache.org/licenses/LICENSE-2.0<a name="line.9"></a>
+<span class="sourceLineNo">010</span> *<a name="line.10"></a>
+<span class="sourceLineNo">011</span> * Unless required by applicable law or agreed to in writing, software<a name="line.11"></a>
+<span class="sourceLineNo">012</span> * distributed under the License is distributed on an "AS IS" BASIS,<a name="line.12"></a>
+<span class="sourceLineNo">013</span> * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.<a name="line.13"></a>
+<span class="sourceLineNo">014</span> * See the License for the specific language governing permissions and<a name="line.14"></a>
+<span class="sourceLineNo">015</span> * limitations under the License.<a name="line.15"></a>
+<span class="sourceLineNo">016</span> */<a name="line.16"></a>
+<span class="sourceLineNo">017</span>package org.apache.commons.math3.analysis.interpolation;<a name="line.17"></a>
+<span class="sourceLineNo">018</span><a name="line.18"></a>
+<span class="sourceLineNo">019</span>import org.apache.commons.math3.exception.DimensionMismatchException;<a name="line.19"></a>
+<span class="sourceLineNo">020</span>import org.apache.commons.math3.exception.InsufficientDataException;<a name="line.20"></a>
+<span class="sourceLineNo">021</span>import org.apache.commons.math3.exception.NonMonotonicSequenceException;<a name="line.21"></a>
+<span class="sourceLineNo">022</span>import org.apache.commons.math3.exception.NullArgumentException;<a name="line.22"></a>
+<span class="sourceLineNo">023</span>import org.apache.commons.math3.analysis.BivariateFunction;<a name="line.23"></a>
+<span class="sourceLineNo">024</span>import org.apache.commons.math3.distribution.UniformRealDistribution;<a name="line.24"></a>
+<span class="sourceLineNo">025</span>import org.apache.commons.math3.random.RandomGenerator;<a name="line.25"></a>
+<span class="sourceLineNo">026</span>import org.apache.commons.math3.random.Well19937c;<a name="line.26"></a>
+<span class="sourceLineNo">027</span>import org.apache.commons.math3.util.FastMath;<a name="line.27"></a>
+<span class="sourceLineNo">028</span>import org.apache.commons.math3.util.Precision;<a name="line.28"></a>
+<span class="sourceLineNo">029</span>import org.junit.Assert;<a name="line.29"></a>
+<span class="sourceLineNo">030</span>import org.junit.Test;<a name="line.30"></a>
+<span class="sourceLineNo">031</span><a name="line.31"></a>
+<span class="sourceLineNo">032</span>/**<a name="line.32"></a>
+<span class="sourceLineNo">033</span> * Test case for the piecewise bicubic function.<a name="line.33"></a>
+<span class="sourceLineNo">034</span> */<a name="line.34"></a>
+<span class="sourceLineNo">035</span>public final class PiecewiseBicubicSplineInterpolatingFunctionTest {<a name="line.35"></a>
+<span class="sourceLineNo">036</span>    /**<a name="line.36"></a>
+<span class="sourceLineNo">037</span>     * Test preconditions.<a name="line.37"></a>
+<span class="sourceLineNo">038</span>     */<a name="line.38"></a>
+<span class="sourceLineNo">039</span>    @Test<a name="line.39"></a>
+<span class="sourceLineNo">040</span>    public void testPreconditions() {<a name="line.40"></a>
+<span class="sourceLineNo">041</span>        double[] xval = new double[] { 3, 4, 5, 6.5, 7.5 };<a name="line.41"></a>
+<span class="sourceLineNo">042</span>        double[] yval = new double[] { -4, -3, -1, 2.5, 3.5 };<a name="line.42"></a>
+<span class="sourceLineNo">043</span>        double[][] zval = new double[xval.length][yval.length];<a name="line.43"></a>
+<span class="sourceLineNo">044</span><a name="line.44"></a>
+<span class="sourceLineNo">045</span>        @SuppressWarnings("unused")<a name="line.45"></a>
+<span class="sourceLineNo">046</span>        PiecewiseBicubicSplineInterpolatingFunction bcf = new PiecewiseBicubicSplineInterpolatingFunction(xval, yval, zval);<a name="line.46"></a>
+<span class="sourceLineNo">047</span><a name="line.47"></a>
+<span class="sourceLineNo">048</span>        try {<a name="line.48"></a>
+<span class="sourceLineNo">049</span>            bcf = new PiecewiseBicubicSplineInterpolatingFunction(null, yval, zval);<a name="line.49"></a>
+<span class="sourceLineNo">050</span>            Assert.fail("Failed to detect x null pointer");<a name="line.50"></a>
+<span class="sourceLineNo">051</span>        } catch (NullArgumentException iae) {<a name="line.51"></a>
+<span class="sourceLineNo">052</span>            // Expected.<a name="line.52"></a>
+<span class="sourceLineNo">053</span>        }<a name="line.53"></a>
+<span class="sourceLineNo">054</span><a name="line.54"></a>
+<span class="sourceLineNo">055</span>        try {<a name="line.55"></a>
+<span class="sourceLineNo">056</span>            bcf = new PiecewiseBicubicSplineInterpolatingFunction(xval, null, zval);<a name="line.56"></a>
+<span class="sourceLineNo">057</span>            Assert.fail("Failed to detect y null pointer");<a name="line.57"></a>
+<span class="sourceLineNo">058</span>        } catch (NullArgumentException iae) {<a name="line.58"></a>
+<span class="sourceLineNo">059</span>            // Expected.<a name="line.59"></a>
+<span class="sourceLineNo">060</span>        }<a name="line.60"></a>
+<span class="sourceLineNo">061</span><a name="line.61"></a>
+<span class="sourceLineNo">062</span>        try {<a name="line.62"></a>
+<span class="sourceLineNo">063</span>            bcf = new PiecewiseBicubicSplineInterpolatingFunction(xval, yval, null);<a name="line.63"></a>
+<span class="sourceLineNo">064</span>            Assert.fail("Failed to detect z null pointer");<a name="line.64"></a>
+<span class="sourceLineNo">065</span>        } catch (NullArgumentException iae) {<a name="line.65"></a>
+<span class="sourceLineNo">066</span>            // Expected.<a name="line.66"></a>
+<span class="sourceLineNo">067</span>        }<a name="line.67"></a>
+<span class="sourceLineNo">068</span><a name="line.68"></a>
+<span class="sourceLineNo">069</span>        try {<a name="line.69"></a>
+<span class="sourceLineNo">070</span>            double xval1[] = { 0.0, 1.0, 2.0, 3.0 };<a name="line.70"></a>
+<span class="sourceLineNo">071</span>            bcf = new PiecewiseBicubicSplineInterpolatingFunction(xval1, yval, zval);<a name="line.71"></a>
+<span class="sourceLineNo">072</span>            Assert.fail("Failed to detect insufficient x data");<a name="line.72"></a>
+<span class="sourceLineNo">073</span>        } catch (InsufficientDataException iae) {<a name="line.73"></a>
+<span class="sourceLineNo">074</span>            // Expected.<a name="line.74"></a>
+<span class="sourceLineNo">075</span>        }<a name="line.75"></a>
+<span class="sourceLineNo">076</span><a name="line.76"></a>
+<span class="sourceLineNo">077</span>        try {<a name="line.77"></a>
+<span class="sourceLineNo">078</span>            double yval1[] = { 0.0, 1.0, 2.0, 3.0 };<a name="line.78"></a>
+<span class="sourceLineNo">079</span>            bcf = new PiecewiseBicubicSplineInterpolatingFunction(xval, yval1, zval);<a name="line.79"></a>
+<span class="sourceLineNo">080</span>            Assert.fail("Failed to detect insufficient y data");<a name="line.80"></a>
+<span class="sourceLineNo">081</span>        } catch (InsufficientDataException iae) {<a name="line.81"></a>
+<span class="sourceLineNo">082</span>            // Expected.<a name="line.82"></a>
+<span class="sourceLineNo">083</span>        }<a name="line.83"></a>
+<span class="sourceLineNo">084</span><a name="line.84"></a>
+<span class="sourceLineNo">085</span>        try {<a name="line.85"></a>
+<span class="sourceLineNo">086</span>            double zval1[][] = new double[4][4];<a name="line.86"></a>
+<span class="sourceLineNo">087</span>            bcf = new PiecewiseBicubicSplineInterpolatingFunction(xval, yval, zval1);<a name="line.87"></a>
+<span class="sourceLineNo">088</span>            Assert.fail("Failed to detect insufficient z data");<a name="line.88"></a>
+<span class="sourceLineNo">089</span>        } catch (InsufficientDataException iae) {<a name="line.89"></a>
+<span class="sourceLineNo">090</span>            // Expected.<a name="line.90"></a>
+<span class="sourceLineNo">091</span>        }<a name="line.91"></a>
+<span class="sourceLineNo">092</span><a name="line.92"></a>
+<span class="sourceLineNo">093</span>        try {<a name="line.93"></a>
+<span class="sourceLineNo">094</span>            double xval1[] = { 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 };<a name="line.94"></a>
+<span class="sourceLineNo">095</span>            bcf = new PiecewiseBicubicSplineInterpolatingFunction(xval1, yval, zval);<a name="line.95"></a>
+<span class="sourceLineNo">096</span>            Assert.fail("Failed to detect data set array with different sizes.");<a name="line.96"></a>
+<span class="sourceLineNo">097</span>        } catch (DimensionMismatchException iae) {<a name="line.97"></a>
+<span class="sourceLineNo">098</span>            // Expected.<a name="line.98"></a>
+<span class="sourceLineNo">099</span>        }<a name="line.99"></a>
+<span class="sourceLineNo">100</span><a name="line.100"></a>
+<span class="sourceLineNo">101</span>        try {<a name="line.101"></a>
+<span class="sourceLineNo">102</span>            double yval1[] = { 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 };<a name="line.102"></a>
+<span class="sourceLineNo">103</span>            bcf = new PiecewiseBicubicSplineInterpolatingFunction(xval, yval1, zval);<a name="line.103"></a>
+<span class="sourceLineNo">104</span>            Assert.fail("Failed to detect data set array with different sizes.");<a name="line.104"></a>
+<span class="sourceLineNo">105</span>        } catch (DimensionMismatchException iae) {<a name="line.105"></a>
+<span class="sourceLineNo">106</span>            // Expected.<a name="line.106"></a>
+<span class="sourceLineNo">107</span>        }<a name="line.107"></a>
+<span class="sourceLineNo">108</span><a name="line.108"></a>
+<span class="sourceLineNo">109</span>        // X values not sorted.<a name="line.109"></a>
+<span class="sourceLineNo">110</span>        try {<a name="line.110"></a>
+<span class="sourceLineNo">111</span>            double xval1[] = { 0.0, 1.0, 0.5, 7.0, 3.5 };<a name="line.111"></a>
+<span class="sourceLineNo">112</span>            bcf = new PiecewiseBicubicSplineInterpolatingFunction(xval1, yval, zval);<a name="line.112"></a>
+<span class="sourceLineNo">113</span>            Assert.fail("Failed to detect unsorted x arguments.");<a name="line.113"></a>
+<span class="sourceLineNo">114</span>        } catch (NonMonotonicSequenceException iae) {<a name="line.114"></a>
+<span class="sourceLineNo">115</span>            // Expected.<a name="line.115"></a>
+<span class="sourceLineNo">116</span>        }<a name="line.116"></a>
+<span class="sourceLineNo">117</span><a name="line.117"></a>
+<span class="sourceLineNo">118</span>        // Y values not sorted.<a name="line.118"></a>
+<span class="sourceLineNo">119</span>        try {<a name="line.119"></a>
+<span class="sourceLineNo">120</span>            double yval1[] = { 0.0, 1.0, 1.5, 0.0, 3.0 };<a name="line.120"></a>
+<span class="sourceLineNo">121</span>            bcf = new PiecewiseBicubicSplineInterpolatingFunction(xval, yval1, zval);<a name="line.121"></a>
+<span class="sourceLineNo">122</span>            Assert.fail("Failed to detect unsorted y arguments.");<a name="line.122"></a>
+<span class="sourceLineNo">123</span>        } catch (NonMonotonicSequenceException iae) {<a name="line.123"></a>
+<span class="sourceLineNo">124</span>            // Expected.<a name="line.124"></a>
+<span class="sourceLineNo">125</span>        }<a name="line.125"></a>
+<span class="sourceLineNo">126</span>    }<a name="line.126"></a>
+<span class="sourceLineNo">127</span><a name="line.127"></a>
+<span class="sourceLineNo">128</span>    /**<a name="line.128"></a>
+<span class="sourceLineNo">129</span>     * Interpolating a plane.<a name="line.129"></a>
+<span class="sourceLineNo">130</span>     * &lt;p&gt;<a name="line.130"></a>
+<span class="sourceLineNo">131</span>     * z = 2 x - 3 y + 5<a name="line.131"></a>
+<span class="sourceLineNo">132</span>     */<a name="line.132"></a>
+<span class="sourceLineNo">133</span>    @Test<a name="line.133"></a>
+<span class="sourceLineNo">134</span>    public void testPlane() {<a name="line.134"></a>
+<span class="sourceLineNo">135</span>        final int numberOfElements = 10;<a name="line.135"></a>
+<span class="sourceLineNo">136</span>        final double minimumX = -10;<a name="line.136"></a>
+<span class="sourceLineNo">137</span>        final double maximumX = 10;<a name="line.137"></a>
+<span class="sourceLineNo">138</span>        final double minimumY = -10;<a name="line.138"></a>
+<span class="sourceLineNo">139</span>        final double maximumY = 10;<a name="line.139"></a>
+<span class="sourceLineNo">140</span>        final int numberOfSamples = 100;<a name="line.140"></a>
+<span class="sourceLineNo">141</span><a name="line.141"></a>
+<span class="sourceLineNo">142</span>        final double interpolationTolerance = 7e-15;<a name="line.142"></a>
+<span class="sourceLineNo">143</span>        final double maxTolerance = 6e-14;<a name="line.143"></a>
+<span class="sourceLineNo">144</span><a name="line.144"></a>
+<span class="sourceLineNo">145</span>        // Function values<a name="line.145"></a>
+<span class="sourceLineNo">146</span>        BivariateFunction f = new BivariateFunction() {<a name="line.146"></a>
+<span class="sourceLineNo">147</span>                public double value(double x, double y) {<a name="line.147"></a>
+<span class="sourceLineNo">148</span>                    return 2 * x - 3 * y + 5;<a name="line.148"></a>
+<span class="sourceLineNo">149</span>                }<a name="line.149"></a>
+<span class="sourceLineNo">150</span>            };<a name="line.150"></a>
+<span class="sourceLineNo">151</span><a name="line.151"></a>
+<span class="sourceLineNo">152</span>        testInterpolation(minimumX,<a name="line.152"></a>
+<span class="sourceLineNo">153</span>                          maximumX,<a name="line.153"></a>
+<span class="sourceLineNo">154</span>                          minimumY,<a name="line.154"></a>
+<span class="sourceLineNo">155</span>                          maximumY,<a name="line.155"></a>
+<span class="sourceLineNo">156</span>                          numberOfElements,<a name="line.156"></a>
+<span class="sourceLineNo">157</span>                          numberOfSamples,<a name="line.157"></a>
+<span class="sourceLineNo">158</span>                          f,<a name="line.158"></a>
+<span class="sourceLineNo">159</span>                          interpolationTolerance,<a name="line.159"></a>
+<span class="sourceLineNo">160</span>                          maxTolerance);<a name="line.160"></a>
+<span class="sourceLineNo">161</span>    }<a name="line.161"></a>
+<span class="sourceLineNo">162</span><a name="line.162"></a>
+<span class="sourceLineNo">163</span>    /**<a name="line.163"></a>
+<span class="sourceLineNo">164</span>     * Interpolating a paraboloid.<a name="line.164"></a>
+<span class="sourceLineNo">165</span>     * &lt;p&gt;<a name="line.165"></a>
+<span class="sourceLineNo">166</span>     * z = 2 x&lt;sup&gt;2&lt;/sup&gt; - 3 y&lt;sup&gt;2&lt;/sup&gt; + 4 x y - 5<a name="line.166"></a>
+<span class="sourceLineNo">167</span>     */<a name="line.167"></a>
+<span class="sourceLineNo">168</span>    @Test<a name="line.168"></a>
+<span class="sourceLineNo">169</span>    public void testParabaloid() {<a name="line.169"></a>
+<span class="sourceLineNo">170</span>        final int numberOfElements = 10;<a name="line.170"></a>
+<span class="sourceLineNo">171</span>        final double minimumX = -10;<a name="line.171"></a>
+<span class="sourceLineNo">172</span>        final double maximumX = 10;<a name="line.172"></a>
+<span class="sourceLineNo">173</span>        final double minimumY = -10;<a name="line.173"></a>
+<span class="sourceLineNo">174</span>        final double maximumY = 10;<a name="line.174"></a>
+<span class="sourceLineNo">175</span>        final int numberOfSamples = 100;<a name="line.175"></a>
+<span class="sourceLineNo">176</span><a name="line.176"></a>
+<span class="sourceLineNo">177</span>        final double interpolationTolerance = 2e-14;<a name="line.177"></a>
+<span class="sourceLineNo">178</span>        final double maxTolerance = 6e-14;<a name="line.178"></a>
+<span class="sourceLineNo">179</span><a name="line.179"></a>
+<span class="sourceLineNo">180</span>        // Function values<a name="line.180"></a>
+<span class="sourceLineNo">181</span>        BivariateFunction f = new BivariateFunction() {<a name="line.181"></a>
+<span class="sourceLineNo">182</span>                public double value(double x, double y) {<a name="line.182"></a>
+<span class="sourceLineNo">183</span>                    return 2 * x * x - 3 * y * y + 4 * x * y - 5;<a name="line.183"></a>
+<span class="sourceLineNo">184</span>                }<a name="line.184"></a>
+<span class="sourceLineNo">185</span>            };<a name="line.185"></a>
+<span class="sourceLineNo">186</span><a name="line.186"></a>
+<span class="sourceLineNo">187</span>        testInterpolation(minimumX,<a name="line.187"></a>
+<span class="sourceLineNo">188</span>                          maximumX,<a name="line.188"></a>
+<span class="sourceLineNo">189</span>                          minimumY,<a name="line.189"></a>
+<span class="sourceLineNo">190</span>                          maximumY,<a name="line.190"></a>
+<span class="sourceLineNo">191</span>                          numberOfElements,<a name="line.191"></a>
+<span class="sourceLineNo">192</span>                          numberOfSamples,<a name="line.192"></a>
+<span class="sourceLineNo">193</span>                          f,<a name="line.193"></a>
+<span class="sourceLineNo">194</span>                          interpolationTolerance,<a name="line.194"></a>
+<span class="sourceLineNo">195</span>                          maxTolerance);<a name="line.195"></a>
+<span class="sourceLineNo">196</span>    }<a name="line.196"></a>
+<span class="sourceLineNo">197</span><a name="line.197"></a>
+<span class="sourceLineNo">198</span>    /**<a name="line.198"></a>
+<span class="sourceLineNo">199</span>     * @param minimumX Lower bound of interpolation range along the x-coordinate.<a name="line.199"></a>
+<span class="sourceLineNo">200</span>     * @param maximumX Higher bound of interpolation range along the x-coordinate.<a name="line.200"></a>
+<span class="sourceLineNo">201</span>     * @param minimumY Lower bound of interpolation range along the y-coordinate.<a name="line.201"></a>
+<span class="sourceLineNo">202</span>     * @param maximumY Higher bound of interpolation range along the y-coordinate.<a name="line.202"></a>
+<span class="sourceLineNo">203</span>     * @param numberOfElements Number of data points (along each dimension).<a name="line.203"></a>
+<span class="sourceLineNo">204</span>     * @param numberOfSamples Number of test points.<a name="line.204"></a>
+<span class="sourceLineNo">205</span>     * @param f Function to test.<a name="line.205"></a>
+<span class="sourceLineNo">206</span>     * @param meanTolerance Allowed average error (mean error on all interpolated values).<a name="line.206"></a>
+<span class="sourceLineNo">207</span>     * @param maxTolerance Allowed error on each interpolated value.<a name="line.207"></a>
+<span class="sourceLineNo">208</span>     */<a name="line.208"></a>
+<span class="sourceLineNo">209</span>    private void testInterpolation(double minimumX,<a name="line.209"></a>
+<span class="sourceLineNo">210</span>                                   double maximumX,<a name="line.210"></a>
+<span class="sourceLineNo">211</span>                                   double minimumY,<a name="line.211"></a>
+<span class="sourceLineNo">212</span>                                   double maximumY,<a name="line.212"></a>
+<span class="sourceLineNo">213</span>                                   int numberOfElements,<a name="line.213"></a>
+<span class="sourceLineNo">214</span>                                   int numberOfSamples,<a name="line.214"></a>
+<span class="sourceLineNo">215</span>                                   BivariateFunction f,<a name="line.215"></a>
+<span class="sourceLineNo">216</span>                                   double meanTolerance,<a name="line.216"></a>
+<span class="sourceLineNo">217</span>                                   double maxTolerance) {<a name="line.217"></a>
+<span class="sourceLineNo">218</span>        double expected;<a name="line.218"></a>
+<span class="sourceLineNo">219</span>        double actual;<a name="line.219"></a>
+<span class="sourceLineNo">220</span>        double currentX;<a name="line.220"></a>
+<span class="sourceLineNo">221</span>        double currentY;<a name="line.221"></a>
+<span class="sourceLineNo">222</span>        final double deltaX = (maximumX - minimumX) / ((double) numberOfElements);<a name="line.222"></a>
+<span class="sourceLineNo">223</span>        final double deltaY = (maximumY - minimumY) / ((double) numberOfElements);<a name="line.223"></a>
+<span class="sourceLineNo">224</span>        final double[] xValues = new double[numberOfElements];<a name="line.224"></a>
+<span class="sourceLineNo">225</span>        final double[] yValues = new double[numberOfElements];<a name="line.225"></a>
+<span class="sourceLineNo">226</span>        final double[][] zValues = new double[numberOfElements][numberOfElements];<a name="line.226"></a>
+<span class="sourceLineNo">227</span><a name="line.227"></a>
+<span class="sourceLineNo">228</span>        for (int i = 0; i &lt; numberOfElements; i++) {<a name="line.228"></a>
+<span class="sourceLineNo">229</span>            xValues[i] = minimumX + deltaX * (double) i;<a name="line.229"></a>
+<span class="sourceLineNo">230</span>            for (int j = 0; j &lt; numberOfElements; j++) {<a name="line.230"></a>
+<span class="sourceLineNo">231</span>                yValues[j] = minimumY + deltaY * (double) j;<a name="line.231"></a>
+<span class="sourceLineNo">232</span>                zValues[i][j] = f.value(xValues[i], yValues[j]);<a name="line.232"></a>
+<span class="sourceLineNo">233</span>            }<a name="line.233"></a>
+<span class="sourceLineNo">234</span>        }<a name="line.234"></a>
+<span class="sourceLineNo">235</span><a name="line.235"></a>
+<span class="sourceLineNo">236</span>        final BivariateFunction interpolation<a name="line.236"></a>
+<span class="sourceLineNo">237</span>            = new PiecewiseBicubicSplineInterpolatingFunction(xValues,<a name="line.237"></a>
+<span class="sourceLineNo">238</span>                                                              yValues,<a name="line.238"></a>
+<span class="sourceLineNo">239</span>                                                              zValues);<a name="line.239"></a>
+<span class="sourceLineNo">240</span><a name="line.240"></a>
+<span class="sourceLineNo">241</span>        for (int i = 0; i &lt; numberOfElements; i++) {<a name="line.241"></a>
+<span class="sourceLineNo">242</span>            currentX = xValues[i];<a name="line.242"></a>
+<span class="sourceLineNo">243</span>            for (int j = 0; j &lt; numberOfElements; j++) {<a name="line.243"></a>
+<span class="sourceLineNo">244</span>                currentY = yValues[j];<a name="line.244"></a>
+<span class="sourceLineNo">245</span>                expected = f.value(currentX, currentY);<a name="line.245"></a>
+<span class="sourceLineNo">246</span>                actual = interpolation.value(currentX, currentY);<a name="line.246"></a>
+<span class="sourceLineNo">247</span>                Assert.assertTrue(Precision.equals(expected, actual));<a name="line.247"></a>
+<span class="sourceLineNo">248</span>            }<a name="line.248"></a>
+<span class="sourceLineNo">249</span>        }<a name="line.249"></a>
+<span class="sourceLineNo">250</span><a name="line.250"></a>
+<span class="sourceLineNo">251</span>        final RandomGenerator rng = new Well19937c(1234567L);<a name="line.251"></a>
+<span class="sourceLineNo">252</span>        final UniformRealDistribution distX = new UniformRealDistribution(rng, xValues[0], xValues[xValues.length - 1]);<a name="line.252"></a>
+<span class="sourceLineNo">253</span>        final UniformRealDistribution distY = new UniformRealDistribution(rng, yValues[0], yValues[yValues.length - 1]);<a name="line.253"></a>
+<span class="sourceLineNo">254</span><a name="line.254"></a>
+<span class="sourceLineNo">255</span>        double sumError = 0;<a name="line.255"></a>
+<span class="sourceLineNo">256</span>        for (int i = 0; i &lt; numberOfSamples; i++) {<a name="line.256"></a>
+<span class="sourceLineNo">257</span>            currentX = distX.sample();<a name="line.257"></a>
+<span class="sourceLineNo">258</span>            currentY = distY.sample();<a name="line.258"></a>
+<span class="sourceLineNo">259</span>            expected = f.value(currentX, currentY);<a name="line.259"></a>
+<span class="sourceLineNo">260</span>            actual = interpolation.value(currentX, currentY);<a name="line.260"></a>
+<span class="sourceLineNo">261</span>            sumError += FastMath.abs(actual - expected);<a name="line.261"></a>
+<span class="sourceLineNo">262</span>            Assert.assertEquals(expected, actual, maxTolerance);<a name="line.262"></a>
+<span class="sourceLineNo">263</span>        }<a name="line.263"></a>
+<span class="sourceLineNo">264</span><a name="line.264"></a>
+<span class="sourceLineNo">265</span>        final double meanError = sumError / numberOfSamples;<a name="line.265"></a>
+<span class="sourceLineNo">266</span>        Assert.assertEquals(0, meanError, meanTolerance);<a name="line.266"></a>
+<span class="sourceLineNo">267</span>    }<a name="line.267"></a>
+<span class="sourceLineNo">268</span>}<a name="line.268"></a>
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+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd">
+<html lang="en">
+<head>
+<title>Source code</title>
+<link rel="stylesheet" type="text/css" href="../../../../../../../stylesheet.css" title="Style">
+</head>
+<body>
+<div class="sourceContainer">
+<pre><span class="sourceLineNo">001</span>/*<a name="line.1"></a>
+<span class="sourceLineNo">002</span> * Licensed to the Apache Software Foundation (ASF) under one or more<a name="line.2"></a>
+<span class="sourceLineNo">003</span> * contributor license agreements.  See the NOTICE file distributed with<a name="line.3"></a>
+<span class="sourceLineNo">004</span> * this work for additional information regarding copyright ownership.<a name="line.4"></a>
+<span class="sourceLineNo">005</span> * The ASF licenses this file to You under the Apache License, Version 2.0<a name="line.5"></a>
+<span class="sourceLineNo">006</span> * (the "License"); you may not use this file except in compliance with<a name="line.6"></a>
+<span class="sourceLineNo">007</span> * the License.  You may obtain a copy of the License at<a name="line.7"></a>
+<span class="sourceLineNo">008</span> *<a name="line.8"></a>
+<span class="sourceLineNo">009</span> *      http://www.apache.org/licenses/LICENSE-2.0<a name="line.9"></a>
+<span class="sourceLineNo">010</span> *<a name="line.10"></a>
+<span class="sourceLineNo">011</span> * Unless required by applicable law or agreed to in writing, software<a name="line.11"></a>
+<span class="sourceLineNo">012</span> * distributed under the License is distributed on an "AS IS" BASIS,<a name="line.12"></a>
+<span class="sourceLineNo">013</span> * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.<a name="line.13"></a>
+<span class="sourceLineNo">014</span> * See the License for the specific language governing permissions and<a name="line.14"></a>
+<span class="sourceLineNo">015</span> * limitations under the License.<a name="line.15"></a>
+<span class="sourceLineNo">016</span> */<a name="line.16"></a>
+<span class="sourceLineNo">017</span>package org.apache.commons.math3.optim.univariate;<a name="line.17"></a>
+<span class="sourceLineNo">018</span><a name="line.18"></a>
+<span class="sourceLineNo">019</span>import org.apache.commons.math3.analysis.UnivariateFunction;<a name="line.19"></a>
+<span class="sourceLineNo">020</span>import org.apache.commons.math3.optim.BaseOptimizer;<a name="line.20"></a>
+<span class="sourceLineNo">021</span>import org.apache.commons.math3.optim.OptimizationData;<a name="line.21"></a>
+<span class="sourceLineNo">022</span>import org.apache.commons.math3.optim.nonlinear.scalar.GoalType;<a name="line.22"></a>
+<span class="sourceLineNo">023</span>import org.apache.commons.math3.optim.ConvergenceChecker;<a name="line.23"></a>
+<span class="sourceLineNo">024</span>import org.apache.commons.math3.exception.TooManyEvaluationsException;<a name="line.24"></a>
+<span class="sourceLineNo">025</span><a name="line.25"></a>
+<span class="sourceLineNo">026</span>/**<a name="line.26"></a>
+<span class="sourceLineNo">027</span> * Base class for a univariate scalar function optimizer.<a name="line.27"></a>
+<span class="sourceLineNo">028</span> *<a name="line.28"></a>
+<span class="sourceLineNo">029</span> * @since 3.1<a name="line.29"></a>
+<span class="sourceLineNo">030</span> */<a name="line.30"></a>
+<span class="sourceLineNo">031</span>public abstract class UnivariateOptimizer<a name="line.31"></a>
+<span class="sourceLineNo">032</span>    extends BaseOptimizer&lt;UnivariatePointValuePair&gt; {<a name="line.32"></a>
+<span class="sourceLineNo">033</span>    /** Objective function. */<a name="line.33"></a>
+<span class="sourceLineNo">034</span>    private UnivariateFunction function;<a name="line.34"></a>
+<span class="sourceLineNo">035</span>    /** Type of optimization. */<a name="line.35"></a>
+<span class="sourceLineNo">036</span>    private GoalType goal;<a name="line.36"></a>
+<span class="sourceLineNo">037</span>    /** Initial guess. */<a name="line.37"></a>
+<span class="sourceLineNo">038</span>    private double start;<a name="line.38"></a>
+<span class="sourceLineNo">039</span>    /** Lower bound. */<a name="line.39"></a>
+<span class="sourceLineNo">040</span>    private double min;<a name="line.40"></a>
+<span class="sourceLineNo">041</span>    /** Upper bound. */<a name="line.41"></a>
+<span class="sourceLineNo">042</span>    private double max;<a name="line.42"></a>
+<span class="sourceLineNo">043</span><a name="line.43"></a>
+<span class="sourceLineNo">044</span>    /**<a name="line.44"></a>
+<span class="sourceLineNo">045</span>     * @param checker Convergence checker.<a name="line.45"></a>
+<span class="sourceLineNo">046</span>     */<a name="line.46"></a>
+<span class="sourceLineNo">047</span>    protected UnivariateOptimizer(ConvergenceChecker&lt;UnivariatePointValuePair&gt; checker) {<a name="line.47"></a>
+<span class="sourceLineNo">048</span>        super(checker);<a name="line.48"></a>
+<span class="sourceLineNo">049</span>    }<a name="line.49"></a>
+<span class="sourceLineNo">050</span><a name="line.50"></a>
+<span class="sourceLineNo">051</span>    /**<a name="line.51"></a>
+<span class="sourceLineNo">052</span>     * {@inheritDoc}<a name="line.52"></a>
+<span class="sourceLineNo">053</span>     *<a name="line.53"></a>
+<span class="sourceLineNo">054</span>     * @param optData Optimization data. In addition to those documented in<a name="line.54"></a>
+<span class="sourceLineNo">055</span>     * {@link BaseOptimizer#parseOptimizationData(OptimizationData[])<a name="line.55"></a>
+<span class="sourceLineNo">056</span>     * BaseOptimizer}, this method will register the following data:<a name="line.56"></a>
+<span class="sourceLineNo">057</span>     * &lt;ul&gt;<a name="line.57"></a>
+<span class="sourceLineNo">058</span>     *  &lt;li&gt;{@link GoalType}&lt;/li&gt;<a name="line.58"></a>
+<span class="sourceLineNo">059</span>     *  &lt;li&gt;{@link SearchInterval}&lt;/li&gt;<a name="line.59"></a>
+<span class="sourceLineNo">060</span>     *  &lt;li&gt;{@link UnivariateObjectiveFunction}&lt;/li&gt;<a name="line.60"></a>
+<span class="sourceLineNo">061</span>     * &lt;/ul&gt;<a name="line.61"></a>
+<span class="sourceLineNo">062</span>     * @return {@inheritDoc}<a name="line.62"></a>
+<span class="sourceLineNo">063</span>     * @throws TooManyEvaluationsException if the maximal number of<a name="line.63"></a>
+<span class="sourceLineNo">064</span>     * evaluations is exceeded.<a name="line.64"></a>
+<span class="sourceLineNo">065</span>     */<a name="line.65"></a>
+<span class="sourceLineNo">066</span>    @Override<a name="line.66"></a>
+<span class="sourceLineNo">067</span>    public UnivariatePointValuePair optimize(OptimizationData... optData)<a name="line.67"></a>
+<span class="sourceLineNo">068</span>        throws TooManyEvaluationsException {<a name="line.68"></a>
+<span class="sourceLineNo">069</span>        // Perform computation.<a name="line.69"></a>
+<span class="sourceLineNo">070</span>        return super.optimize(optData);<a name="line.70"></a>
+<span class="sourceLineNo">071</span>    }<a name="line.71"></a>
+<span class="sourceLineNo">072</span><a name="line.72"></a>
+<span class="sourceLineNo">073</span>    /**<a name="line.73"></a>
+<span class="sourceLineNo">074</span>     * @return the optimization type.<a name="line.74"></a>
+<span class="sourceLineNo">075</span>     */<a name="line.75"></a>
+<span class="sourceLineNo">076</span>    public GoalType getGoalType() {<a name="line.76"></a>
+<span class="sourceLineNo">077</span>        return goal;<a name="line.77"></a>
+<span class="sourceLineNo">078</span>    }<a name="line.78"></a>
+<span class="sourceLineNo">079</span><a name="line.79"></a>
+<span class="sourceLineNo">080</span>    /**<a name="line.80"></a>
+<span class="sourceLineNo">081</span>     * Scans the list of (required and optional) optimization data that<a name="line.81"></a>
+<span class="sourceLineNo">082</span>     * characterize the problem.<a name="line.82"></a>
+<span class="sourceLineNo">083</span>     *<a name="line.83"></a>
+<span class="sourceLineNo">084</span>     * @param optData Optimization data.<a name="line.84"></a>
+<span class="sourceLineNo">085</span>     * The following data will be looked for:<a name="line.85"></a>
+<span class="sourceLineNo">086</span>     * &lt;ul&gt;<a name="line.86"></a>
+<span class="sourceLineNo">087</span>     *  &lt;li&gt;{@link GoalType}&lt;/li&gt;<a name="line.87"></a>
+<span class="sourceLineNo">088</span>     *  &lt;li&gt;{@link SearchInterval}&lt;/li&gt;<a name="line.88"></a>
+<span class="sourceLineNo">089</span>     *  &lt;li&gt;{@link UnivariateObjectiveFunction}&lt;/li&gt;<a name="line.89"></a>
+<span class="sourceLineNo">090</span>     * &lt;/ul&gt;<a name="line.90"></a>
+<span class="sourceLineNo">091</span>     */<a name="line.91"></a>
+<span class="sourceLineNo">092</span>    @Override<a name="line.92"></a>
+<span class="sourceLineNo">093</span>    protected void parseOptimizationData(OptimizationData... optData) {<a name="line.93"></a>
+<span class="sourceLineNo">094</span>        // Allow base class to register its own data.<a name="line.94"></a>
+<span class="sourceLineNo">095</span>        super.parseOptimizationData(optData);<a name="line.95"></a>
+<span class="sourceLineNo">096</span><a name="line.96"></a>
+<span class="sourceLineNo">097</span>        // The existing values (as set by the previous call) are reused if<a name="line.97"></a>
+<span class="sourceLineNo">098</span>        // not provided in the argument list.<a name="line.98"></a>
+<span class="sourceLineNo">099</span>        for (OptimizationData data : optData) {<a name="line.99"></a>
+<span class="sourceLineNo">100</span>            if (data instanceof SearchInterval) {<a name="line.100"></a>
+<span class="sourceLineNo">101</span>                final SearchInterval interval = (SearchInterval) data;<a name="line.101"></a>
+<span class="sourceLineNo">102</span>                min = interval.getMin();<a name="line.102"></a>
+<span class="sourceLineNo">103</span>                max = interval.getMax();<a name="line.103"></a>
+<span class="sourceLineNo">104</span>                start = interval.getStartValue();<a name="line.104"></a>
+<span class="sourceLineNo">105</span>                continue;<a name="line.105"></a>
+<span class="sourceLineNo">106</span>            }<a name="line.106"></a>
+<span class="sourceLineNo">107</span>            if (data instanceof UnivariateObjectiveFunction) {<a name="line.107"></a>
+<span class="sourceLineNo">108</span>                function = ((UnivariateObjectiveFunction) data).getObjectiveFunction();<a name="line.108"></a>
+<span class="sourceLineNo">109</span>                continue;<a name="line.109"></a>
+<span class="sourceLineNo">110</span>            }<a name="line.110"></a>
+<span class="sourceLineNo">111</span>            if (data instanceof GoalType) {<a name="line.111"></a>
+<span class="sourceLineNo">112</span>                goal = (GoalType) data;<a name="line.112"></a>
+<span class="sourceLineNo">113</span>                continue;<a name="line.113"></a>
+<span class="sourceLineNo">114</span>            }<a name="line.114"></a>
+<span class="sourceLineNo">115</span>        }<a name="line.115"></a>
+<span class="sourceLineNo">116</span>    }<a name="line.116"></a>
+<span class="sourceLineNo">117</span><a name="line.117"></a>
+<span class="sourceLineNo">118</span>    /**<a name="line.118"></a>
+<span class="sourceLineNo">119</span>     * @return the initial guess.<a name="line.119"></a>
+<span class="sourceLineNo">120</span>     */<a name="line.120"></a>
+<span class="sourceLineNo">121</span>    public double getStartValue() {<a name="line.121"></a>
+<span class="sourceLineNo">122</span>        return start;<a name="line.122"></a>
+<span class="sourceLineNo">123</span>    }<a name="line.123"></a>
+<span class="sourceLineNo">124</span>    /**<a name="line.124"></a>
+<span class="sourceLineNo">125</span>     * @return the lower bounds.<a name="line.125"></a>
+<span class="sourceLineNo">126</span>     */<a name="line.126"></a>
+<span class="sourceLineNo">127</span>    public double getMin() {<a name="line.127"></a>
+<span class="sourceLineNo">128</span>        return min;<a name="line.128"></a>
+<span class="sourceLineNo">129</span>    }<a name="line.129"></a>
+<span class="sourceLineNo">130</span>    /**<a name="line.130"></a>
+<span class="sourceLineNo">131</span>     * @return the upper bounds.<a name="line.131"></a>
+<span class="sourceLineNo">132</span>     */<a name="line.132"></a>
+<span class="sourceLineNo">133</span>    public double getMax() {<a name="line.133"></a>
+<span class="sourceLineNo">134</span>        return max;<a name="line.134"></a>
+<span class="sourceLineNo">135</span>    }<a name="line.135"></a>
+<span class="sourceLineNo">136</span><a name="line.136"></a>
+<span class="sourceLineNo">137</span>    /**<a name="line.137"></a>
+<span class="sourceLineNo">138</span>     * Computes the objective function value.<a name="line.138"></a>
+<span class="sourceLineNo">139</span>     * This method &lt;em&gt;must&lt;/em&gt; be called by subclasses to enforce the<a name="line.139"></a>
+<span class="sourceLineNo">140</span>     * evaluation counter limit.<a name="line.140"></a>
+<span class="sourceLineNo">141</span>     *<a name="line.141"></a>
+<span class="sourceLineNo">142</span>     * @param x Point at which the objective function must be evaluated.<a name="line.142"></a>
+<span class="sourceLineNo">143</span>     * @return the objective function value at the specified point.<a name="line.143"></a>
+<span class="sourceLineNo">144</span>     * @throws TooManyEvaluationsException if the maximal number of<a name="line.144"></a>
+<span class="sourceLineNo">145</span>     * evaluations is exceeded.<a name="line.145"></a>
+<span class="sourceLineNo">146</span>     */<a name="line.146"></a>
+<span class="sourceLineNo">147</span>    protected double computeObjectiveValue(double x) {<a name="line.147"></a>
+<span class="sourceLineNo">148</span>        super.incrementEvaluationCount();<a name="line.148"></a>
+<span class="sourceLineNo">149</span>        return function.value(x);<a name="line.149"></a>
+<span class="sourceLineNo">150</span>    }<a name="line.150"></a>
+<span class="sourceLineNo">151</span>}<a name="line.151"></a>
+
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+</pre>
+</div>
+</body>
+</html>


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