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Posted to commits@commons.apache.org by lu...@apache.org on 2013/04/07 01:42:02 UTC
svn commit: r857558 [30/39] - in
/websites/production/commons/content/proper/commons-math/testapidocs/src-html/org/apache/commons/math3:
./ analysis/ analysis/differentiation/ analysis/interpolation/ complex/
dfp/ distribution/ distribution/fitting/ ex...
Modified: websites/production/commons/content/proper/commons-math/testapidocs/src-html/org/apache/commons/math3/random/EmpiricalDistributionTest.html
==============================================================================
--- websites/production/commons/content/proper/commons-math/testapidocs/src-html/org/apache/commons/math3/random/EmpiricalDistributionTest.html (original)
+++ websites/production/commons/content/proper/commons-math/testapidocs/src-html/org/apache/commons/math3/random/EmpiricalDistributionTest.html Sat Apr 6 23:42:01 2013
@@ -25,413 +25,565 @@
<FONT color="green">022</FONT> import java.io.InputStreamReader;<a name="line.22"></a>
<FONT color="green">023</FONT> import java.net.URL;<a name="line.23"></a>
<FONT color="green">024</FONT> import java.util.ArrayList;<a name="line.24"></a>
-<FONT color="green">025</FONT> <a name="line.25"></a>
-<FONT color="green">026</FONT> import org.apache.commons.math3.TestUtils;<a name="line.26"></a>
-<FONT color="green">027</FONT> import org.apache.commons.math3.analysis.UnivariateFunction;<a name="line.27"></a>
-<FONT color="green">028</FONT> import org.apache.commons.math3.analysis.integration.BaseAbstractUnivariateIntegrator;<a name="line.28"></a>
-<FONT color="green">029</FONT> import org.apache.commons.math3.analysis.integration.IterativeLegendreGaussIntegrator;<a name="line.29"></a>
-<FONT color="green">030</FONT> import org.apache.commons.math3.distribution.NormalDistribution;<a name="line.30"></a>
-<FONT color="green">031</FONT> import org.apache.commons.math3.distribution.RealDistribution;<a name="line.31"></a>
-<FONT color="green">032</FONT> import org.apache.commons.math3.distribution.RealDistributionAbstractTest;<a name="line.32"></a>
-<FONT color="green">033</FONT> import org.apache.commons.math3.exception.NullArgumentException;<a name="line.33"></a>
-<FONT color="green">034</FONT> import org.apache.commons.math3.stat.descriptive.SummaryStatistics;<a name="line.34"></a>
-<FONT color="green">035</FONT> import org.junit.Assert;<a name="line.35"></a>
-<FONT color="green">036</FONT> import org.junit.Before;<a name="line.36"></a>
-<FONT color="green">037</FONT> import org.junit.Test;<a name="line.37"></a>
-<FONT color="green">038</FONT> <a name="line.38"></a>
-<FONT color="green">039</FONT> /**<a name="line.39"></a>
-<FONT color="green">040</FONT> * Test cases for the EmpiricalDistribution class<a name="line.40"></a>
-<FONT color="green">041</FONT> *<a name="line.41"></a>
-<FONT color="green">042</FONT> * @version $Id: EmpiricalDistributionTest.java 1421910 2012-12-14 14:57:56Z erans $<a name="line.42"></a>
-<FONT color="green">043</FONT> */<a name="line.43"></a>
-<FONT color="green">044</FONT> <a name="line.44"></a>
-<FONT color="green">045</FONT> public final class EmpiricalDistributionTest extends RealDistributionAbstractTest {<a name="line.45"></a>
-<FONT color="green">046</FONT> <a name="line.46"></a>
-<FONT color="green">047</FONT> protected EmpiricalDistribution empiricalDistribution = null;<a name="line.47"></a>
-<FONT color="green">048</FONT> protected EmpiricalDistribution empiricalDistribution2 = null;<a name="line.48"></a>
-<FONT color="green">049</FONT> protected File file = null;<a name="line.49"></a>
-<FONT color="green">050</FONT> protected URL url = null;<a name="line.50"></a>
-<FONT color="green">051</FONT> protected double[] dataArray = null;<a name="line.51"></a>
-<FONT color="green">052</FONT> protected final int n = 10000;<a name="line.52"></a>
-<FONT color="green">053</FONT> <a name="line.53"></a>
-<FONT color="green">054</FONT> @Before<a name="line.54"></a>
-<FONT color="green">055</FONT> public void setUp() {<a name="line.55"></a>
-<FONT color="green">056</FONT> super.setUp();<a name="line.56"></a>
-<FONT color="green">057</FONT> empiricalDistribution = new EmpiricalDistribution(100);<a name="line.57"></a>
-<FONT color="green">058</FONT> // empiricalDistribution = new EmpiricalDistribution(100, new RandomDataImpl()); // XXX Deprecated API<a name="line.58"></a>
-<FONT color="green">059</FONT> url = getClass().getResource("testData.txt");<a name="line.59"></a>
-<FONT color="green">060</FONT> final ArrayList<Double> list = new ArrayList<Double>();<a name="line.60"></a>
-<FONT color="green">061</FONT> try {<a name="line.61"></a>
-<FONT color="green">062</FONT> empiricalDistribution2 = new EmpiricalDistribution(100);<a name="line.62"></a>
-<FONT color="green">063</FONT> // empiricalDistribution2 = new EmpiricalDistribution(100, new RandomDataImpl()); // XXX Deprecated API<a name="line.63"></a>
-<FONT color="green">064</FONT> BufferedReader in =<a name="line.64"></a>
-<FONT color="green">065</FONT> new BufferedReader(new InputStreamReader(<a name="line.65"></a>
-<FONT color="green">066</FONT> url.openStream()));<a name="line.66"></a>
-<FONT color="green">067</FONT> String str = null;<a name="line.67"></a>
-<FONT color="green">068</FONT> while ((str = in.readLine()) != null) {<a name="line.68"></a>
-<FONT color="green">069</FONT> list.add(Double.valueOf(str));<a name="line.69"></a>
-<FONT color="green">070</FONT> }<a name="line.70"></a>
-<FONT color="green">071</FONT> in.close();<a name="line.71"></a>
-<FONT color="green">072</FONT> in = null;<a name="line.72"></a>
-<FONT color="green">073</FONT> } catch (IOException ex) {<a name="line.73"></a>
-<FONT color="green">074</FONT> Assert.fail("IOException " + ex);<a name="line.74"></a>
-<FONT color="green">075</FONT> }<a name="line.75"></a>
-<FONT color="green">076</FONT> <a name="line.76"></a>
-<FONT color="green">077</FONT> dataArray = new double[list.size()];<a name="line.77"></a>
-<FONT color="green">078</FONT> int i = 0;<a name="line.78"></a>
-<FONT color="green">079</FONT> for (Double data : list) {<a name="line.79"></a>
-<FONT color="green">080</FONT> dataArray[i] = data.doubleValue();<a name="line.80"></a>
-<FONT color="green">081</FONT> i++;<a name="line.81"></a>
-<FONT color="green">082</FONT> }<a name="line.82"></a>
-<FONT color="green">083</FONT> }<a name="line.83"></a>
-<FONT color="green">084</FONT> <a name="line.84"></a>
-<FONT color="green">085</FONT> /**<a name="line.85"></a>
-<FONT color="green">086</FONT> * Test EmpiricalDistrbution.load() using sample data file.<br><a name="line.86"></a>
-<FONT color="green">087</FONT> * Check that the sampleCount, mu and sigma match data in<a name="line.87"></a>
-<FONT color="green">088</FONT> * the sample data file. Also verify that load is idempotent.<a name="line.88"></a>
-<FONT color="green">089</FONT> */<a name="line.89"></a>
-<FONT color="green">090</FONT> @Test<a name="line.90"></a>
-<FONT color="green">091</FONT> public void testLoad() throws Exception {<a name="line.91"></a>
-<FONT color="green">092</FONT> // Load from a URL<a name="line.92"></a>
-<FONT color="green">093</FONT> empiricalDistribution.load(url);<a name="line.93"></a>
-<FONT color="green">094</FONT> checkDistribution();<a name="line.94"></a>
-<FONT color="green">095</FONT> <a name="line.95"></a>
-<FONT color="green">096</FONT> // Load again from a file (also verifies idempotency of load)<a name="line.96"></a>
-<FONT color="green">097</FONT> File file = new File(url.getFile());<a name="line.97"></a>
-<FONT color="green">098</FONT> empiricalDistribution.load(file);<a name="line.98"></a>
-<FONT color="green">099</FONT> checkDistribution();<a name="line.99"></a>
-<FONT color="green">100</FONT> }<a name="line.100"></a>
-<FONT color="green">101</FONT> <a name="line.101"></a>
-<FONT color="green">102</FONT> private void checkDistribution() {<a name="line.102"></a>
-<FONT color="green">103</FONT> // testData File has 10000 values, with mean ~ 5.0, std dev ~ 1<a name="line.103"></a>
-<FONT color="green">104</FONT> // Make sure that loaded distribution matches this<a name="line.104"></a>
-<FONT color="green">105</FONT> Assert.assertEquals(empiricalDistribution.getSampleStats().getN(),1000,10E-7);<a name="line.105"></a>
-<FONT color="green">106</FONT> //TODO: replace with statistical tests<a name="line.106"></a>
-<FONT color="green">107</FONT> Assert.assertEquals(empiricalDistribution.getSampleStats().getMean(),<a name="line.107"></a>
-<FONT color="green">108</FONT> 5.069831575018909,10E-7);<a name="line.108"></a>
-<FONT color="green">109</FONT> Assert.assertEquals(empiricalDistribution.getSampleStats().getStandardDeviation(),<a name="line.109"></a>
-<FONT color="green">110</FONT> 1.0173699343977738,10E-7);<a name="line.110"></a>
-<FONT color="green">111</FONT> }<a name="line.111"></a>
-<FONT color="green">112</FONT> <a name="line.112"></a>
-<FONT color="green">113</FONT> /**<a name="line.113"></a>
-<FONT color="green">114</FONT> * Test EmpiricalDistrbution.load(double[]) using data taken from<a name="line.114"></a>
-<FONT color="green">115</FONT> * sample data file.<br><a name="line.115"></a>
-<FONT color="green">116</FONT> * Check that the sampleCount, mu and sigma match data in<a name="line.116"></a>
-<FONT color="green">117</FONT> * the sample data file.<a name="line.117"></a>
-<FONT color="green">118</FONT> */<a name="line.118"></a>
-<FONT color="green">119</FONT> @Test<a name="line.119"></a>
-<FONT color="green">120</FONT> public void testDoubleLoad() throws Exception {<a name="line.120"></a>
-<FONT color="green">121</FONT> empiricalDistribution2.load(dataArray);<a name="line.121"></a>
-<FONT color="green">122</FONT> // testData File has 10000 values, with mean ~ 5.0, std dev ~ 1<a name="line.122"></a>
-<FONT color="green">123</FONT> // Make sure that loaded distribution matches this<a name="line.123"></a>
-<FONT color="green">124</FONT> Assert.assertEquals(empiricalDistribution2.getSampleStats().getN(),1000,10E-7);<a name="line.124"></a>
-<FONT color="green">125</FONT> //TODO: replace with statistical tests<a name="line.125"></a>
-<FONT color="green">126</FONT> Assert.assertEquals(empiricalDistribution2.getSampleStats().getMean(),<a name="line.126"></a>
-<FONT color="green">127</FONT> 5.069831575018909,10E-7);<a name="line.127"></a>
-<FONT color="green">128</FONT> Assert.assertEquals(empiricalDistribution2.getSampleStats().getStandardDeviation(),<a name="line.128"></a>
-<FONT color="green">129</FONT> 1.0173699343977738,10E-7);<a name="line.129"></a>
-<FONT color="green">130</FONT> <a name="line.130"></a>
-<FONT color="green">131</FONT> double[] bounds = empiricalDistribution2.getGeneratorUpperBounds();<a name="line.131"></a>
-<FONT color="green">132</FONT> Assert.assertEquals(bounds.length, 100);<a name="line.132"></a>
-<FONT color="green">133</FONT> Assert.assertEquals(bounds[99], 1.0, 10e-12);<a name="line.133"></a>
+<FONT color="green">025</FONT> import java.util.Arrays;<a name="line.25"></a>
+<FONT color="green">026</FONT> <a name="line.26"></a>
+<FONT color="green">027</FONT> import org.apache.commons.math3.TestUtils;<a name="line.27"></a>
+<FONT color="green">028</FONT> import org.apache.commons.math3.analysis.UnivariateFunction;<a name="line.28"></a>
+<FONT color="green">029</FONT> import org.apache.commons.math3.analysis.integration.BaseAbstractUnivariateIntegrator;<a name="line.29"></a>
+<FONT color="green">030</FONT> import org.apache.commons.math3.analysis.integration.IterativeLegendreGaussIntegrator;<a name="line.30"></a>
+<FONT color="green">031</FONT> import org.apache.commons.math3.distribution.AbstractRealDistribution;<a name="line.31"></a>
+<FONT color="green">032</FONT> import org.apache.commons.math3.distribution.NormalDistribution;<a name="line.32"></a>
+<FONT color="green">033</FONT> import org.apache.commons.math3.distribution.RealDistribution;<a name="line.33"></a>
+<FONT color="green">034</FONT> import org.apache.commons.math3.distribution.RealDistributionAbstractTest;<a name="line.34"></a>
+<FONT color="green">035</FONT> import org.apache.commons.math3.distribution.UniformRealDistribution;<a name="line.35"></a>
+<FONT color="green">036</FONT> import org.apache.commons.math3.exception.NullArgumentException;<a name="line.36"></a>
+<FONT color="green">037</FONT> import org.apache.commons.math3.exception.OutOfRangeException;<a name="line.37"></a>
+<FONT color="green">038</FONT> import org.apache.commons.math3.stat.descriptive.SummaryStatistics;<a name="line.38"></a>
+<FONT color="green">039</FONT> import org.junit.Assert;<a name="line.39"></a>
+<FONT color="green">040</FONT> import org.junit.Before;<a name="line.40"></a>
+<FONT color="green">041</FONT> import org.junit.Test;<a name="line.41"></a>
+<FONT color="green">042</FONT> <a name="line.42"></a>
+<FONT color="green">043</FONT> /**<a name="line.43"></a>
+<FONT color="green">044</FONT> * Test cases for the EmpiricalDistribution class<a name="line.44"></a>
+<FONT color="green">045</FONT> *<a name="line.45"></a>
+<FONT color="green">046</FONT> * @version $Id: EmpiricalDistributionTest.java 1461172 2013-03-26 15:11:18Z luc $<a name="line.46"></a>
+<FONT color="green">047</FONT> */<a name="line.47"></a>
+<FONT color="green">048</FONT> <a name="line.48"></a>
+<FONT color="green">049</FONT> public final class EmpiricalDistributionTest extends RealDistributionAbstractTest {<a name="line.49"></a>
+<FONT color="green">050</FONT> <a name="line.50"></a>
+<FONT color="green">051</FONT> protected EmpiricalDistribution empiricalDistribution = null;<a name="line.51"></a>
+<FONT color="green">052</FONT> protected EmpiricalDistribution empiricalDistribution2 = null;<a name="line.52"></a>
+<FONT color="green">053</FONT> protected File file = null;<a name="line.53"></a>
+<FONT color="green">054</FONT> protected URL url = null;<a name="line.54"></a>
+<FONT color="green">055</FONT> protected double[] dataArray = null;<a name="line.55"></a>
+<FONT color="green">056</FONT> protected final int n = 10000;<a name="line.56"></a>
+<FONT color="green">057</FONT> <a name="line.57"></a>
+<FONT color="green">058</FONT> @Before<a name="line.58"></a>
+<FONT color="green">059</FONT> public void setUp() {<a name="line.59"></a>
+<FONT color="green">060</FONT> super.setUp();<a name="line.60"></a>
+<FONT color="green">061</FONT> empiricalDistribution = new EmpiricalDistribution(100);<a name="line.61"></a>
+<FONT color="green">062</FONT> // empiricalDistribution = new EmpiricalDistribution(100, new RandomDataImpl()); // XXX Deprecated API<a name="line.62"></a>
+<FONT color="green">063</FONT> url = getClass().getResource("testData.txt");<a name="line.63"></a>
+<FONT color="green">064</FONT> final ArrayList<Double> list = new ArrayList<Double>();<a name="line.64"></a>
+<FONT color="green">065</FONT> try {<a name="line.65"></a>
+<FONT color="green">066</FONT> empiricalDistribution2 = new EmpiricalDistribution(100);<a name="line.66"></a>
+<FONT color="green">067</FONT> // empiricalDistribution2 = new EmpiricalDistribution(100, new RandomDataImpl()); // XXX Deprecated API<a name="line.67"></a>
+<FONT color="green">068</FONT> BufferedReader in =<a name="line.68"></a>
+<FONT color="green">069</FONT> new BufferedReader(new InputStreamReader(<a name="line.69"></a>
+<FONT color="green">070</FONT> url.openStream()));<a name="line.70"></a>
+<FONT color="green">071</FONT> String str = null;<a name="line.71"></a>
+<FONT color="green">072</FONT> while ((str = in.readLine()) != null) {<a name="line.72"></a>
+<FONT color="green">073</FONT> list.add(Double.valueOf(str));<a name="line.73"></a>
+<FONT color="green">074</FONT> }<a name="line.74"></a>
+<FONT color="green">075</FONT> in.close();<a name="line.75"></a>
+<FONT color="green">076</FONT> in = null;<a name="line.76"></a>
+<FONT color="green">077</FONT> } catch (IOException ex) {<a name="line.77"></a>
+<FONT color="green">078</FONT> Assert.fail("IOException " + ex);<a name="line.78"></a>
+<FONT color="green">079</FONT> }<a name="line.79"></a>
+<FONT color="green">080</FONT> <a name="line.80"></a>
+<FONT color="green">081</FONT> dataArray = new double[list.size()];<a name="line.81"></a>
+<FONT color="green">082</FONT> int i = 0;<a name="line.82"></a>
+<FONT color="green">083</FONT> for (Double data : list) {<a name="line.83"></a>
+<FONT color="green">084</FONT> dataArray[i] = data.doubleValue();<a name="line.84"></a>
+<FONT color="green">085</FONT> i++;<a name="line.85"></a>
+<FONT color="green">086</FONT> }<a name="line.86"></a>
+<FONT color="green">087</FONT> }<a name="line.87"></a>
+<FONT color="green">088</FONT> <a name="line.88"></a>
+<FONT color="green">089</FONT> /**<a name="line.89"></a>
+<FONT color="green">090</FONT> * Test EmpiricalDistrbution.load() using sample data file.<br><a name="line.90"></a>
+<FONT color="green">091</FONT> * Check that the sampleCount, mu and sigma match data in<a name="line.91"></a>
+<FONT color="green">092</FONT> * the sample data file. Also verify that load is idempotent.<a name="line.92"></a>
+<FONT color="green">093</FONT> */<a name="line.93"></a>
+<FONT color="green">094</FONT> @Test<a name="line.94"></a>
+<FONT color="green">095</FONT> public void testLoad() throws Exception {<a name="line.95"></a>
+<FONT color="green">096</FONT> // Load from a URL<a name="line.96"></a>
+<FONT color="green">097</FONT> empiricalDistribution.load(url);<a name="line.97"></a>
+<FONT color="green">098</FONT> checkDistribution();<a name="line.98"></a>
+<FONT color="green">099</FONT> <a name="line.99"></a>
+<FONT color="green">100</FONT> // Load again from a file (also verifies idempotency of load)<a name="line.100"></a>
+<FONT color="green">101</FONT> File file = new File(url.toURI());<a name="line.101"></a>
+<FONT color="green">102</FONT> empiricalDistribution.load(file);<a name="line.102"></a>
+<FONT color="green">103</FONT> checkDistribution();<a name="line.103"></a>
+<FONT color="green">104</FONT> }<a name="line.104"></a>
+<FONT color="green">105</FONT> <a name="line.105"></a>
+<FONT color="green">106</FONT> private void checkDistribution() {<a name="line.106"></a>
+<FONT color="green">107</FONT> // testData File has 10000 values, with mean ~ 5.0, std dev ~ 1<a name="line.107"></a>
+<FONT color="green">108</FONT> // Make sure that loaded distribution matches this<a name="line.108"></a>
+<FONT color="green">109</FONT> Assert.assertEquals(empiricalDistribution.getSampleStats().getN(),1000,10E-7);<a name="line.109"></a>
+<FONT color="green">110</FONT> //TODO: replace with statistical tests<a name="line.110"></a>
+<FONT color="green">111</FONT> Assert.assertEquals(empiricalDistribution.getSampleStats().getMean(),<a name="line.111"></a>
+<FONT color="green">112</FONT> 5.069831575018909,10E-7);<a name="line.112"></a>
+<FONT color="green">113</FONT> Assert.assertEquals(empiricalDistribution.getSampleStats().getStandardDeviation(),<a name="line.113"></a>
+<FONT color="green">114</FONT> 1.0173699343977738,10E-7);<a name="line.114"></a>
+<FONT color="green">115</FONT> }<a name="line.115"></a>
+<FONT color="green">116</FONT> <a name="line.116"></a>
+<FONT color="green">117</FONT> /**<a name="line.117"></a>
+<FONT color="green">118</FONT> * Test EmpiricalDistrbution.load(double[]) using data taken from<a name="line.118"></a>
+<FONT color="green">119</FONT> * sample data file.<br><a name="line.119"></a>
+<FONT color="green">120</FONT> * Check that the sampleCount, mu and sigma match data in<a name="line.120"></a>
+<FONT color="green">121</FONT> * the sample data file.<a name="line.121"></a>
+<FONT color="green">122</FONT> */<a name="line.122"></a>
+<FONT color="green">123</FONT> @Test<a name="line.123"></a>
+<FONT color="green">124</FONT> public void testDoubleLoad() throws Exception {<a name="line.124"></a>
+<FONT color="green">125</FONT> empiricalDistribution2.load(dataArray);<a name="line.125"></a>
+<FONT color="green">126</FONT> // testData File has 10000 values, with mean ~ 5.0, std dev ~ 1<a name="line.126"></a>
+<FONT color="green">127</FONT> // Make sure that loaded distribution matches this<a name="line.127"></a>
+<FONT color="green">128</FONT> Assert.assertEquals(empiricalDistribution2.getSampleStats().getN(),1000,10E-7);<a name="line.128"></a>
+<FONT color="green">129</FONT> //TODO: replace with statistical tests<a name="line.129"></a>
+<FONT color="green">130</FONT> Assert.assertEquals(empiricalDistribution2.getSampleStats().getMean(),<a name="line.130"></a>
+<FONT color="green">131</FONT> 5.069831575018909,10E-7);<a name="line.131"></a>
+<FONT color="green">132</FONT> Assert.assertEquals(empiricalDistribution2.getSampleStats().getStandardDeviation(),<a name="line.132"></a>
+<FONT color="green">133</FONT> 1.0173699343977738,10E-7);<a name="line.133"></a>
<FONT color="green">134</FONT> <a name="line.134"></a>
-<FONT color="green">135</FONT> }<a name="line.135"></a>
-<FONT color="green">136</FONT> <a name="line.136"></a>
-<FONT color="green">137</FONT> /**<a name="line.137"></a>
-<FONT color="green">138</FONT> * Generate 1000 random values and make sure they look OK.<br><a name="line.138"></a>
-<FONT color="green">139</FONT> * Note that there is a non-zero (but very small) probability that<a name="line.139"></a>
-<FONT color="green">140</FONT> * these tests will fail even if the code is working as designed.<a name="line.140"></a>
-<FONT color="green">141</FONT> */<a name="line.141"></a>
-<FONT color="green">142</FONT> @Test<a name="line.142"></a>
-<FONT color="green">143</FONT> public void testNext() throws Exception {<a name="line.143"></a>
-<FONT color="green">144</FONT> tstGen(0.1);<a name="line.144"></a>
-<FONT color="green">145</FONT> tstDoubleGen(0.1);<a name="line.145"></a>
-<FONT color="green">146</FONT> }<a name="line.146"></a>
-<FONT color="green">147</FONT> <a name="line.147"></a>
-<FONT color="green">148</FONT> /**<a name="line.148"></a>
-<FONT color="green">149</FONT> * Make sure exception thrown if digest getNext is attempted<a name="line.149"></a>
-<FONT color="green">150</FONT> * before loading empiricalDistribution.<a name="line.150"></a>
-<FONT color="green">151</FONT> */<a name="line.151"></a>
-<FONT color="green">152</FONT> @Test<a name="line.152"></a>
-<FONT color="green">153</FONT> public void testNexFail() {<a name="line.153"></a>
-<FONT color="green">154</FONT> try {<a name="line.154"></a>
-<FONT color="green">155</FONT> empiricalDistribution.getNextValue();<a name="line.155"></a>
-<FONT color="green">156</FONT> empiricalDistribution2.getNextValue();<a name="line.156"></a>
-<FONT color="green">157</FONT> Assert.fail("Expecting IllegalStateException");<a name="line.157"></a>
-<FONT color="green">158</FONT> } catch (IllegalStateException ex) {<a name="line.158"></a>
-<FONT color="green">159</FONT> // expected<a name="line.159"></a>
-<FONT color="green">160</FONT> }<a name="line.160"></a>
-<FONT color="green">161</FONT> }<a name="line.161"></a>
-<FONT color="green">162</FONT> <a name="line.162"></a>
-<FONT color="green">163</FONT> /**<a name="line.163"></a>
-<FONT color="green">164</FONT> * Make sure we can handle a grid size that is too fine<a name="line.164"></a>
-<FONT color="green">165</FONT> */<a name="line.165"></a>
-<FONT color="green">166</FONT> @Test<a name="line.166"></a>
-<FONT color="green">167</FONT> public void testGridTooFine() throws Exception {<a name="line.167"></a>
-<FONT color="green">168</FONT> empiricalDistribution = new EmpiricalDistribution(1001);<a name="line.168"></a>
-<FONT color="green">169</FONT> tstGen(0.1);<a name="line.169"></a>
-<FONT color="green">170</FONT> empiricalDistribution2 = new EmpiricalDistribution(1001);<a name="line.170"></a>
-<FONT color="green">171</FONT> tstDoubleGen(0.1);<a name="line.171"></a>
-<FONT color="green">172</FONT> }<a name="line.172"></a>
-<FONT color="green">173</FONT> <a name="line.173"></a>
-<FONT color="green">174</FONT> /**<a name="line.174"></a>
-<FONT color="green">175</FONT> * How about too fat?<a name="line.175"></a>
-<FONT color="green">176</FONT> */<a name="line.176"></a>
-<FONT color="green">177</FONT> @Test<a name="line.177"></a>
-<FONT color="green">178</FONT> public void testGridTooFat() throws Exception {<a name="line.178"></a>
-<FONT color="green">179</FONT> empiricalDistribution = new EmpiricalDistribution(1);<a name="line.179"></a>
-<FONT color="green">180</FONT> tstGen(5); // ridiculous tolerance; but ridiculous grid size<a name="line.180"></a>
-<FONT color="green">181</FONT> // really just checking to make sure we do not bomb<a name="line.181"></a>
-<FONT color="green">182</FONT> empiricalDistribution2 = new EmpiricalDistribution(1);<a name="line.182"></a>
-<FONT color="green">183</FONT> tstDoubleGen(5);<a name="line.183"></a>
-<FONT color="green">184</FONT> }<a name="line.184"></a>
-<FONT color="green">185</FONT> <a name="line.185"></a>
-<FONT color="green">186</FONT> /**<a name="line.186"></a>
-<FONT color="green">187</FONT> * Test bin index overflow problem (BZ 36450)<a name="line.187"></a>
-<FONT color="green">188</FONT> */<a name="line.188"></a>
-<FONT color="green">189</FONT> @Test<a name="line.189"></a>
-<FONT color="green">190</FONT> public void testBinIndexOverflow() throws Exception {<a name="line.190"></a>
-<FONT color="green">191</FONT> double[] x = new double[] {9474.94326071674, 2080107.8865462579};<a name="line.191"></a>
-<FONT color="green">192</FONT> new EmpiricalDistribution().load(x);<a name="line.192"></a>
-<FONT color="green">193</FONT> }<a name="line.193"></a>
-<FONT color="green">194</FONT> <a name="line.194"></a>
-<FONT color="green">195</FONT> @Test<a name="line.195"></a>
-<FONT color="green">196</FONT> public void testSerialization() {<a name="line.196"></a>
-<FONT color="green">197</FONT> // Empty<a name="line.197"></a>
-<FONT color="green">198</FONT> EmpiricalDistribution dist = new EmpiricalDistribution();<a name="line.198"></a>
-<FONT color="green">199</FONT> EmpiricalDistribution dist2 = (EmpiricalDistribution) TestUtils.serializeAndRecover(dist);<a name="line.199"></a>
-<FONT color="green">200</FONT> verifySame(dist, dist2);<a name="line.200"></a>
-<FONT color="green">201</FONT> <a name="line.201"></a>
-<FONT color="green">202</FONT> // Loaded<a name="line.202"></a>
-<FONT color="green">203</FONT> empiricalDistribution2.load(dataArray);<a name="line.203"></a>
-<FONT color="green">204</FONT> dist2 = (EmpiricalDistribution) TestUtils.serializeAndRecover(empiricalDistribution2);<a name="line.204"></a>
-<FONT color="green">205</FONT> verifySame(empiricalDistribution2, dist2);<a name="line.205"></a>
-<FONT color="green">206</FONT> }<a name="line.206"></a>
-<FONT color="green">207</FONT> <a name="line.207"></a>
-<FONT color="green">208</FONT> @Test(expected=NullArgumentException.class)<a name="line.208"></a>
-<FONT color="green">209</FONT> public void testLoadNullDoubleArray() {<a name="line.209"></a>
-<FONT color="green">210</FONT> new EmpiricalDistribution().load((double[]) null);<a name="line.210"></a>
-<FONT color="green">211</FONT> }<a name="line.211"></a>
-<FONT color="green">212</FONT> <a name="line.212"></a>
-<FONT color="green">213</FONT> @Test(expected=NullArgumentException.class)<a name="line.213"></a>
-<FONT color="green">214</FONT> public void testLoadNullURL() throws Exception {<a name="line.214"></a>
-<FONT color="green">215</FONT> new EmpiricalDistribution().load((URL) null);<a name="line.215"></a>
-<FONT color="green">216</FONT> }<a name="line.216"></a>
-<FONT color="green">217</FONT> <a name="line.217"></a>
-<FONT color="green">218</FONT> @Test(expected=NullArgumentException.class)<a name="line.218"></a>
-<FONT color="green">219</FONT> public void testLoadNullFile() throws Exception {<a name="line.219"></a>
-<FONT color="green">220</FONT> new EmpiricalDistribution().load((File) null);<a name="line.220"></a>
-<FONT color="green">221</FONT> }<a name="line.221"></a>
-<FONT color="green">222</FONT> <a name="line.222"></a>
-<FONT color="green">223</FONT> /**<a name="line.223"></a>
-<FONT color="green">224</FONT> * MATH-298<a name="line.224"></a>
-<FONT color="green">225</FONT> */<a name="line.225"></a>
-<FONT color="green">226</FONT> @Test<a name="line.226"></a>
-<FONT color="green">227</FONT> public void testGetBinUpperBounds() {<a name="line.227"></a>
-<FONT color="green">228</FONT> double[] testData = {0, 1, 1, 2, 3, 4, 4, 5, 6, 7, 8, 9, 10};<a name="line.228"></a>
-<FONT color="green">229</FONT> EmpiricalDistribution dist = new EmpiricalDistribution(5);<a name="line.229"></a>
-<FONT color="green">230</FONT> dist.load(testData);<a name="line.230"></a>
-<FONT color="green">231</FONT> double[] expectedBinUpperBounds = {2, 4, 6, 8, 10};<a name="line.231"></a>
-<FONT color="green">232</FONT> double[] expectedGeneratorUpperBounds = {4d/13d, 7d/13d, 9d/13d, 11d/13d, 1};<a name="line.232"></a>
-<FONT color="green">233</FONT> double tol = 10E-12;<a name="line.233"></a>
-<FONT color="green">234</FONT> TestUtils.assertEquals(expectedBinUpperBounds, dist.getUpperBounds(), tol);<a name="line.234"></a>
-<FONT color="green">235</FONT> TestUtils.assertEquals(expectedGeneratorUpperBounds, dist.getGeneratorUpperBounds(), tol);<a name="line.235"></a>
-<FONT color="green">236</FONT> }<a name="line.236"></a>
-<FONT color="green">237</FONT> <a name="line.237"></a>
-<FONT color="green">238</FONT> @Test<a name="line.238"></a>
-<FONT color="green">239</FONT> public void testGeneratorConfig() {<a name="line.239"></a>
-<FONT color="green">240</FONT> double[] testData = {0, 1, 2, 3, 4};<a name="line.240"></a>
-<FONT color="green">241</FONT> RandomGenerator generator = new RandomAdaptorTest.ConstantGenerator(0.5);<a name="line.241"></a>
-<FONT color="green">242</FONT> <a name="line.242"></a>
-<FONT color="green">243</FONT> EmpiricalDistribution dist = new EmpiricalDistribution(5, generator);<a name="line.243"></a>
-<FONT color="green">244</FONT> dist.load(testData);<a name="line.244"></a>
-<FONT color="green">245</FONT> for (int i = 0; i < 5; i++) {<a name="line.245"></a>
-<FONT color="green">246</FONT> Assert.assertEquals(2.0, dist.getNextValue(), 0d);<a name="line.246"></a>
-<FONT color="green">247</FONT> }<a name="line.247"></a>
-<FONT color="green">248</FONT> <a name="line.248"></a>
-<FONT color="green">249</FONT> // Verify no NPE with null generator argument<a name="line.249"></a>
-<FONT color="green">250</FONT> dist = new EmpiricalDistribution(5, (RandomGenerator) null);<a name="line.250"></a>
-<FONT color="green">251</FONT> dist.load(testData);<a name="line.251"></a>
-<FONT color="green">252</FONT> dist.getNextValue();<a name="line.252"></a>
-<FONT color="green">253</FONT> }<a name="line.253"></a>
-<FONT color="green">254</FONT> <a name="line.254"></a>
-<FONT color="green">255</FONT> @Test<a name="line.255"></a>
-<FONT color="green">256</FONT> public void testReSeed() throws Exception {<a name="line.256"></a>
-<FONT color="green">257</FONT> empiricalDistribution.load(url);<a name="line.257"></a>
-<FONT color="green">258</FONT> empiricalDistribution.reSeed(100);<a name="line.258"></a>
-<FONT color="green">259</FONT> final double [] values = new double[10];<a name="line.259"></a>
-<FONT color="green">260</FONT> for (int i = 0; i < 10; i++) {<a name="line.260"></a>
-<FONT color="green">261</FONT> values[i] = empiricalDistribution.getNextValue();<a name="line.261"></a>
-<FONT color="green">262</FONT> }<a name="line.262"></a>
-<FONT color="green">263</FONT> empiricalDistribution.reSeed(100);<a name="line.263"></a>
+<FONT color="green">135</FONT> double[] bounds = empiricalDistribution2.getGeneratorUpperBounds();<a name="line.135"></a>
+<FONT color="green">136</FONT> Assert.assertEquals(bounds.length, 100);<a name="line.136"></a>
+<FONT color="green">137</FONT> Assert.assertEquals(bounds[99], 1.0, 10e-12);<a name="line.137"></a>
+<FONT color="green">138</FONT> <a name="line.138"></a>
+<FONT color="green">139</FONT> }<a name="line.139"></a>
+<FONT color="green">140</FONT> <a name="line.140"></a>
+<FONT color="green">141</FONT> /**<a name="line.141"></a>
+<FONT color="green">142</FONT> * Generate 1000 random values and make sure they look OK.<br><a name="line.142"></a>
+<FONT color="green">143</FONT> * Note that there is a non-zero (but very small) probability that<a name="line.143"></a>
+<FONT color="green">144</FONT> * these tests will fail even if the code is working as designed.<a name="line.144"></a>
+<FONT color="green">145</FONT> */<a name="line.145"></a>
+<FONT color="green">146</FONT> @Test<a name="line.146"></a>
+<FONT color="green">147</FONT> public void testNext() throws Exception {<a name="line.147"></a>
+<FONT color="green">148</FONT> tstGen(0.1);<a name="line.148"></a>
+<FONT color="green">149</FONT> tstDoubleGen(0.1);<a name="line.149"></a>
+<FONT color="green">150</FONT> }<a name="line.150"></a>
+<FONT color="green">151</FONT> <a name="line.151"></a>
+<FONT color="green">152</FONT> /**<a name="line.152"></a>
+<FONT color="green">153</FONT> * Make sure exception thrown if digest getNext is attempted<a name="line.153"></a>
+<FONT color="green">154</FONT> * before loading empiricalDistribution.<a name="line.154"></a>
+<FONT color="green">155</FONT> */<a name="line.155"></a>
+<FONT color="green">156</FONT> @Test<a name="line.156"></a>
+<FONT color="green">157</FONT> public void testNexFail() {<a name="line.157"></a>
+<FONT color="green">158</FONT> try {<a name="line.158"></a>
+<FONT color="green">159</FONT> empiricalDistribution.getNextValue();<a name="line.159"></a>
+<FONT color="green">160</FONT> empiricalDistribution2.getNextValue();<a name="line.160"></a>
+<FONT color="green">161</FONT> Assert.fail("Expecting IllegalStateException");<a name="line.161"></a>
+<FONT color="green">162</FONT> } catch (IllegalStateException ex) {<a name="line.162"></a>
+<FONT color="green">163</FONT> // expected<a name="line.163"></a>
+<FONT color="green">164</FONT> }<a name="line.164"></a>
+<FONT color="green">165</FONT> }<a name="line.165"></a>
+<FONT color="green">166</FONT> <a name="line.166"></a>
+<FONT color="green">167</FONT> /**<a name="line.167"></a>
+<FONT color="green">168</FONT> * Make sure we can handle a grid size that is too fine<a name="line.168"></a>
+<FONT color="green">169</FONT> */<a name="line.169"></a>
+<FONT color="green">170</FONT> @Test<a name="line.170"></a>
+<FONT color="green">171</FONT> public void testGridTooFine() throws Exception {<a name="line.171"></a>
+<FONT color="green">172</FONT> empiricalDistribution = new EmpiricalDistribution(1001);<a name="line.172"></a>
+<FONT color="green">173</FONT> tstGen(0.1);<a name="line.173"></a>
+<FONT color="green">174</FONT> empiricalDistribution2 = new EmpiricalDistribution(1001);<a name="line.174"></a>
+<FONT color="green">175</FONT> tstDoubleGen(0.1);<a name="line.175"></a>
+<FONT color="green">176</FONT> }<a name="line.176"></a>
+<FONT color="green">177</FONT> <a name="line.177"></a>
+<FONT color="green">178</FONT> /**<a name="line.178"></a>
+<FONT color="green">179</FONT> * How about too fat?<a name="line.179"></a>
+<FONT color="green">180</FONT> */<a name="line.180"></a>
+<FONT color="green">181</FONT> @Test<a name="line.181"></a>
+<FONT color="green">182</FONT> public void testGridTooFat() throws Exception {<a name="line.182"></a>
+<FONT color="green">183</FONT> empiricalDistribution = new EmpiricalDistribution(1);<a name="line.183"></a>
+<FONT color="green">184</FONT> tstGen(5); // ridiculous tolerance; but ridiculous grid size<a name="line.184"></a>
+<FONT color="green">185</FONT> // really just checking to make sure we do not bomb<a name="line.185"></a>
+<FONT color="green">186</FONT> empiricalDistribution2 = new EmpiricalDistribution(1);<a name="line.186"></a>
+<FONT color="green">187</FONT> tstDoubleGen(5);<a name="line.187"></a>
+<FONT color="green">188</FONT> }<a name="line.188"></a>
+<FONT color="green">189</FONT> <a name="line.189"></a>
+<FONT color="green">190</FONT> /**<a name="line.190"></a>
+<FONT color="green">191</FONT> * Test bin index overflow problem (BZ 36450)<a name="line.191"></a>
+<FONT color="green">192</FONT> */<a name="line.192"></a>
+<FONT color="green">193</FONT> @Test<a name="line.193"></a>
+<FONT color="green">194</FONT> public void testBinIndexOverflow() throws Exception {<a name="line.194"></a>
+<FONT color="green">195</FONT> double[] x = new double[] {9474.94326071674, 2080107.8865462579};<a name="line.195"></a>
+<FONT color="green">196</FONT> new EmpiricalDistribution().load(x);<a name="line.196"></a>
+<FONT color="green">197</FONT> }<a name="line.197"></a>
+<FONT color="green">198</FONT> <a name="line.198"></a>
+<FONT color="green">199</FONT> @Test<a name="line.199"></a>
+<FONT color="green">200</FONT> public void testSerialization() {<a name="line.200"></a>
+<FONT color="green">201</FONT> // Empty<a name="line.201"></a>
+<FONT color="green">202</FONT> EmpiricalDistribution dist = new EmpiricalDistribution();<a name="line.202"></a>
+<FONT color="green">203</FONT> EmpiricalDistribution dist2 = (EmpiricalDistribution) TestUtils.serializeAndRecover(dist);<a name="line.203"></a>
+<FONT color="green">204</FONT> verifySame(dist, dist2);<a name="line.204"></a>
+<FONT color="green">205</FONT> <a name="line.205"></a>
+<FONT color="green">206</FONT> // Loaded<a name="line.206"></a>
+<FONT color="green">207</FONT> empiricalDistribution2.load(dataArray);<a name="line.207"></a>
+<FONT color="green">208</FONT> dist2 = (EmpiricalDistribution) TestUtils.serializeAndRecover(empiricalDistribution2);<a name="line.208"></a>
+<FONT color="green">209</FONT> verifySame(empiricalDistribution2, dist2);<a name="line.209"></a>
+<FONT color="green">210</FONT> }<a name="line.210"></a>
+<FONT color="green">211</FONT> <a name="line.211"></a>
+<FONT color="green">212</FONT> @Test(expected=NullArgumentException.class)<a name="line.212"></a>
+<FONT color="green">213</FONT> public void testLoadNullDoubleArray() {<a name="line.213"></a>
+<FONT color="green">214</FONT> new EmpiricalDistribution().load((double[]) null);<a name="line.214"></a>
+<FONT color="green">215</FONT> }<a name="line.215"></a>
+<FONT color="green">216</FONT> <a name="line.216"></a>
+<FONT color="green">217</FONT> @Test(expected=NullArgumentException.class)<a name="line.217"></a>
+<FONT color="green">218</FONT> public void testLoadNullURL() throws Exception {<a name="line.218"></a>
+<FONT color="green">219</FONT> new EmpiricalDistribution().load((URL) null);<a name="line.219"></a>
+<FONT color="green">220</FONT> }<a name="line.220"></a>
+<FONT color="green">221</FONT> <a name="line.221"></a>
+<FONT color="green">222</FONT> @Test(expected=NullArgumentException.class)<a name="line.222"></a>
+<FONT color="green">223</FONT> public void testLoadNullFile() throws Exception {<a name="line.223"></a>
+<FONT color="green">224</FONT> new EmpiricalDistribution().load((File) null);<a name="line.224"></a>
+<FONT color="green">225</FONT> }<a name="line.225"></a>
+<FONT color="green">226</FONT> <a name="line.226"></a>
+<FONT color="green">227</FONT> /**<a name="line.227"></a>
+<FONT color="green">228</FONT> * MATH-298<a name="line.228"></a>
+<FONT color="green">229</FONT> */<a name="line.229"></a>
+<FONT color="green">230</FONT> @Test<a name="line.230"></a>
+<FONT color="green">231</FONT> public void testGetBinUpperBounds() {<a name="line.231"></a>
+<FONT color="green">232</FONT> double[] testData = {0, 1, 1, 2, 3, 4, 4, 5, 6, 7, 8, 9, 10};<a name="line.232"></a>
+<FONT color="green">233</FONT> EmpiricalDistribution dist = new EmpiricalDistribution(5);<a name="line.233"></a>
+<FONT color="green">234</FONT> dist.load(testData);<a name="line.234"></a>
+<FONT color="green">235</FONT> double[] expectedBinUpperBounds = {2, 4, 6, 8, 10};<a name="line.235"></a>
+<FONT color="green">236</FONT> double[] expectedGeneratorUpperBounds = {4d/13d, 7d/13d, 9d/13d, 11d/13d, 1};<a name="line.236"></a>
+<FONT color="green">237</FONT> double tol = 10E-12;<a name="line.237"></a>
+<FONT color="green">238</FONT> TestUtils.assertEquals(expectedBinUpperBounds, dist.getUpperBounds(), tol);<a name="line.238"></a>
+<FONT color="green">239</FONT> TestUtils.assertEquals(expectedGeneratorUpperBounds, dist.getGeneratorUpperBounds(), tol);<a name="line.239"></a>
+<FONT color="green">240</FONT> }<a name="line.240"></a>
+<FONT color="green">241</FONT> <a name="line.241"></a>
+<FONT color="green">242</FONT> @Test<a name="line.242"></a>
+<FONT color="green">243</FONT> public void testGeneratorConfig() {<a name="line.243"></a>
+<FONT color="green">244</FONT> double[] testData = {0, 1, 2, 3, 4};<a name="line.244"></a>
+<FONT color="green">245</FONT> RandomGenerator generator = new RandomAdaptorTest.ConstantGenerator(0.5);<a name="line.245"></a>
+<FONT color="green">246</FONT> <a name="line.246"></a>
+<FONT color="green">247</FONT> EmpiricalDistribution dist = new EmpiricalDistribution(5, generator);<a name="line.247"></a>
+<FONT color="green">248</FONT> dist.load(testData);<a name="line.248"></a>
+<FONT color="green">249</FONT> for (int i = 0; i < 5; i++) {<a name="line.249"></a>
+<FONT color="green">250</FONT> Assert.assertEquals(2.0, dist.getNextValue(), 0d);<a name="line.250"></a>
+<FONT color="green">251</FONT> }<a name="line.251"></a>
+<FONT color="green">252</FONT> <a name="line.252"></a>
+<FONT color="green">253</FONT> // Verify no NPE with null generator argument<a name="line.253"></a>
+<FONT color="green">254</FONT> dist = new EmpiricalDistribution(5, (RandomGenerator) null);<a name="line.254"></a>
+<FONT color="green">255</FONT> dist.load(testData);<a name="line.255"></a>
+<FONT color="green">256</FONT> dist.getNextValue();<a name="line.256"></a>
+<FONT color="green">257</FONT> }<a name="line.257"></a>
+<FONT color="green">258</FONT> <a name="line.258"></a>
+<FONT color="green">259</FONT> @Test<a name="line.259"></a>
+<FONT color="green">260</FONT> public void testReSeed() throws Exception {<a name="line.260"></a>
+<FONT color="green">261</FONT> empiricalDistribution.load(url);<a name="line.261"></a>
+<FONT color="green">262</FONT> empiricalDistribution.reSeed(100);<a name="line.262"></a>
+<FONT color="green">263</FONT> final double [] values = new double[10];<a name="line.263"></a>
<FONT color="green">264</FONT> for (int i = 0; i < 10; i++) {<a name="line.264"></a>
-<FONT color="green">265</FONT> Assert.assertEquals(values[i],empiricalDistribution.getNextValue(), 0d);<a name="line.265"></a>
+<FONT color="green">265</FONT> values[i] = empiricalDistribution.getNextValue();<a name="line.265"></a>
<FONT color="green">266</FONT> }<a name="line.266"></a>
-<FONT color="green">267</FONT> }<a name="line.267"></a>
-<FONT color="green">268</FONT> <a name="line.268"></a>
-<FONT color="green">269</FONT> private void verifySame(EmpiricalDistribution d1, EmpiricalDistribution d2) {<a name="line.269"></a>
-<FONT color="green">270</FONT> Assert.assertEquals(d1.isLoaded(), d2.isLoaded());<a name="line.270"></a>
-<FONT color="green">271</FONT> Assert.assertEquals(d1.getBinCount(), d2.getBinCount());<a name="line.271"></a>
-<FONT color="green">272</FONT> Assert.assertEquals(d1.getSampleStats(), d2.getSampleStats());<a name="line.272"></a>
-<FONT color="green">273</FONT> if (d1.isLoaded()) {<a name="line.273"></a>
-<FONT color="green">274</FONT> for (int i = 0; i < d1.getUpperBounds().length; i++) {<a name="line.274"></a>
-<FONT color="green">275</FONT> Assert.assertEquals(d1.getUpperBounds()[i], d2.getUpperBounds()[i], 0);<a name="line.275"></a>
-<FONT color="green">276</FONT> }<a name="line.276"></a>
-<FONT color="green">277</FONT> Assert.assertEquals(d1.getBinStats(), d2.getBinStats());<a name="line.277"></a>
-<FONT color="green">278</FONT> }<a name="line.278"></a>
-<FONT color="green">279</FONT> }<a name="line.279"></a>
-<FONT color="green">280</FONT> <a name="line.280"></a>
-<FONT color="green">281</FONT> private void tstGen(double tolerance)throws Exception {<a name="line.281"></a>
-<FONT color="green">282</FONT> empiricalDistribution.load(url);<a name="line.282"></a>
-<FONT color="green">283</FONT> empiricalDistribution.reSeed(1000);<a name="line.283"></a>
-<FONT color="green">284</FONT> SummaryStatistics stats = new SummaryStatistics();<a name="line.284"></a>
-<FONT color="green">285</FONT> for (int i = 1; i < 1000; i++) {<a name="line.285"></a>
-<FONT color="green">286</FONT> stats.addValue(empiricalDistribution.getNextValue());<a name="line.286"></a>
-<FONT color="green">287</FONT> }<a name="line.287"></a>
-<FONT color="green">288</FONT> Assert.assertEquals("mean", 5.069831575018909, stats.getMean(),tolerance);<a name="line.288"></a>
-<FONT color="green">289</FONT> Assert.assertEquals("std dev", 1.0173699343977738, stats.getStandardDeviation(),tolerance);<a name="line.289"></a>
-<FONT color="green">290</FONT> }<a name="line.290"></a>
-<FONT color="green">291</FONT> <a name="line.291"></a>
-<FONT color="green">292</FONT> private void tstDoubleGen(double tolerance)throws Exception {<a name="line.292"></a>
-<FONT color="green">293</FONT> empiricalDistribution2.load(dataArray);<a name="line.293"></a>
-<FONT color="green">294</FONT> empiricalDistribution2.reSeed(1000);<a name="line.294"></a>
-<FONT color="green">295</FONT> SummaryStatistics stats = new SummaryStatistics();<a name="line.295"></a>
-<FONT color="green">296</FONT> for (int i = 1; i < 1000; i++) {<a name="line.296"></a>
-<FONT color="green">297</FONT> stats.addValue(empiricalDistribution2.getNextValue());<a name="line.297"></a>
-<FONT color="green">298</FONT> }<a name="line.298"></a>
-<FONT color="green">299</FONT> Assert.assertEquals("mean", 5.069831575018909, stats.getMean(), tolerance);<a name="line.299"></a>
-<FONT color="green">300</FONT> Assert.assertEquals("std dev", 1.0173699343977738, stats.getStandardDeviation(), tolerance);<a name="line.300"></a>
-<FONT color="green">301</FONT> }<a name="line.301"></a>
-<FONT color="green">302</FONT> <a name="line.302"></a>
-<FONT color="green">303</FONT> // Setup for distribution tests<a name="line.303"></a>
-<FONT color="green">304</FONT> <a name="line.304"></a>
-<FONT color="green">305</FONT> @Override<a name="line.305"></a>
-<FONT color="green">306</FONT> public RealDistribution makeDistribution() {<a name="line.306"></a>
-<FONT color="green">307</FONT> // Create a uniform distribution on [0, 10,000]<a name="line.307"></a>
-<FONT color="green">308</FONT> final double[] sourceData = new double[n + 1];<a name="line.308"></a>
-<FONT color="green">309</FONT> for (int i = 0; i < n + 1; i++) {<a name="line.309"></a>
-<FONT color="green">310</FONT> sourceData[i] = i;<a name="line.310"></a>
-<FONT color="green">311</FONT> }<a name="line.311"></a>
-<FONT color="green">312</FONT> EmpiricalDistribution dist = new EmpiricalDistribution();<a name="line.312"></a>
-<FONT color="green">313</FONT> dist.load(sourceData);<a name="line.313"></a>
-<FONT color="green">314</FONT> return dist;<a name="line.314"></a>
-<FONT color="green">315</FONT> }<a name="line.315"></a>
-<FONT color="green">316</FONT> <a name="line.316"></a>
-<FONT color="green">317</FONT> /** Uniform bin mass = 10/10001 == mass of all but the first bin */<a name="line.317"></a>
-<FONT color="green">318</FONT> private final double binMass = 10d / (double) (n + 1);<a name="line.318"></a>
-<FONT color="green">319</FONT> <a name="line.319"></a>
-<FONT color="green">320</FONT> /** Mass of first bin = 11/10001 */<a name="line.320"></a>
-<FONT color="green">321</FONT> private final double firstBinMass = 11d / (double) (n + 1);<a name="line.321"></a>
-<FONT color="green">322</FONT> <a name="line.322"></a>
-<FONT color="green">323</FONT> @Override<a name="line.323"></a>
-<FONT color="green">324</FONT> public double[] makeCumulativeTestPoints() {<a name="line.324"></a>
-<FONT color="green">325</FONT> final double[] testPoints = new double[] {9, 10, 15, 1000, 5004, 9999};<a name="line.325"></a>
-<FONT color="green">326</FONT> return testPoints;<a name="line.326"></a>
-<FONT color="green">327</FONT> }<a name="line.327"></a>
-<FONT color="green">328</FONT> <a name="line.328"></a>
-<FONT color="green">329</FONT> <a name="line.329"></a>
-<FONT color="green">330</FONT> @Override<a name="line.330"></a>
-<FONT color="green">331</FONT> public double[] makeCumulativeTestValues() {<a name="line.331"></a>
-<FONT color="green">332</FONT> /* <a name="line.332"></a>
-<FONT color="green">333</FONT> * Bins should be [0, 10], (10, 20], ..., (9990, 10000]<a name="line.333"></a>
-<FONT color="green">334</FONT> * Kernels should be N(4.5, 3.02765), N(14.5, 3.02765)...<a name="line.334"></a>
-<FONT color="green">335</FONT> * Each bin should have mass 10/10000 = .001<a name="line.335"></a>
-<FONT color="green">336</FONT> */<a name="line.336"></a>
-<FONT color="green">337</FONT> final double[] testPoints = getCumulativeTestPoints();<a name="line.337"></a>
-<FONT color="green">338</FONT> final double[] cumValues = new double[testPoints.length];<a name="line.338"></a>
-<FONT color="green">339</FONT> final EmpiricalDistribution empiricalDistribution = (EmpiricalDistribution) makeDistribution();<a name="line.339"></a>
-<FONT color="green">340</FONT> final double[] binBounds = empiricalDistribution.getUpperBounds();<a name="line.340"></a>
-<FONT color="green">341</FONT> for (int i = 0; i < testPoints.length; i++) {<a name="line.341"></a>
-<FONT color="green">342</FONT> final int bin = findBin(testPoints[i]);<a name="line.342"></a>
-<FONT color="green">343</FONT> final double lower = bin == 0 ? empiricalDistribution.getSupportLowerBound() :<a name="line.343"></a>
-<FONT color="green">344</FONT> binBounds[bin - 1];<a name="line.344"></a>
-<FONT color="green">345</FONT> final double upper = binBounds[bin];<a name="line.345"></a>
-<FONT color="green">346</FONT> // Compute bMinus = sum or mass of bins below the bin containing the point<a name="line.346"></a>
-<FONT color="green">347</FONT> // First bin has mass 11 / 10000, the rest have mass 10 / 10000.<a name="line.347"></a>
-<FONT color="green">348</FONT> final double bMinus = bin == 0 ? 0 : (bin - 1) * binMass + firstBinMass;<a name="line.348"></a>
-<FONT color="green">349</FONT> final RealDistribution kernel = findKernel(lower, upper);<a name="line.349"></a>
-<FONT color="green">350</FONT> final double withinBinKernelMass = kernel.cumulativeProbability(lower, upper);<a name="line.350"></a>
-<FONT color="green">351</FONT> final double kernelCum = kernel.cumulativeProbability(lower, testPoints[i]);<a name="line.351"></a>
-<FONT color="green">352</FONT> cumValues[i] = bMinus + (bin == 0 ? firstBinMass : binMass) * kernelCum/withinBinKernelMass;<a name="line.352"></a>
-<FONT color="green">353</FONT> }<a name="line.353"></a>
-<FONT color="green">354</FONT> return cumValues;<a name="line.354"></a>
-<FONT color="green">355</FONT> }<a name="line.355"></a>
-<FONT color="green">356</FONT> <a name="line.356"></a>
-<FONT color="green">357</FONT> @Override<a name="line.357"></a>
-<FONT color="green">358</FONT> public double[] makeDensityTestValues() {<a name="line.358"></a>
-<FONT color="green">359</FONT> final double[] testPoints = getCumulativeTestPoints();<a name="line.359"></a>
-<FONT color="green">360</FONT> final double[] densityValues = new double[testPoints.length];<a name="line.360"></a>
-<FONT color="green">361</FONT> final EmpiricalDistribution empiricalDistribution = (EmpiricalDistribution) makeDistribution();<a name="line.361"></a>
-<FONT color="green">362</FONT> final double[] binBounds = empiricalDistribution.getUpperBounds();<a name="line.362"></a>
-<FONT color="green">363</FONT> for (int i = 0; i < testPoints.length; i++) {<a name="line.363"></a>
-<FONT color="green">364</FONT> final int bin = findBin(testPoints[i]);<a name="line.364"></a>
-<FONT color="green">365</FONT> final double lower = bin == 0 ? empiricalDistribution.getSupportLowerBound() :<a name="line.365"></a>
-<FONT color="green">366</FONT> binBounds[bin - 1];<a name="line.366"></a>
-<FONT color="green">367</FONT> final double upper = binBounds[bin];<a name="line.367"></a>
-<FONT color="green">368</FONT> final RealDistribution kernel = findKernel(lower, upper);<a name="line.368"></a>
-<FONT color="green">369</FONT> final double withinBinKernelMass = kernel.cumulativeProbability(lower, upper);<a name="line.369"></a>
-<FONT color="green">370</FONT> final double density = kernel.density(testPoints[i]);<a name="line.370"></a>
-<FONT color="green">371</FONT> densityValues[i] = density * (bin == 0 ? firstBinMass : binMass) / withinBinKernelMass; <a name="line.371"></a>
-<FONT color="green">372</FONT> }<a name="line.372"></a>
-<FONT color="green">373</FONT> return densityValues;<a name="line.373"></a>
-<FONT color="green">374</FONT> }<a name="line.374"></a>
-<FONT color="green">375</FONT> <a name="line.375"></a>
-<FONT color="green">376</FONT> /** <a name="line.376"></a>
-<FONT color="green">377</FONT> * Modify test integration bounds from the default. Because the distribution<a name="line.377"></a>
-<FONT color="green">378</FONT> * has discontinuities at bin boundaries, integrals spanning multiple bins<a name="line.378"></a>
-<FONT color="green">379</FONT> * will face convergence problems. Only test within-bin integrals and spans<a name="line.379"></a>
-<FONT color="green">380</FONT> * across no more than 3 bin boundaries.<a name="line.380"></a>
-<FONT color="green">381</FONT> */<a name="line.381"></a>
-<FONT color="green">382</FONT> @Override<a name="line.382"></a>
-<FONT color="green">383</FONT> @Test<a name="line.383"></a>
-<FONT color="green">384</FONT> public void testDensityIntegrals() {<a name="line.384"></a>
-<FONT color="green">385</FONT> final RealDistribution distribution = makeDistribution();<a name="line.385"></a>
-<FONT color="green">386</FONT> final double tol = 1.0e-9;<a name="line.386"></a>
-<FONT color="green">387</FONT> final BaseAbstractUnivariateIntegrator integrator =<a name="line.387"></a>
-<FONT color="green">388</FONT> new IterativeLegendreGaussIntegrator(5, 1.0e-12, 1.0e-10);<a name="line.388"></a>
-<FONT color="green">389</FONT> final UnivariateFunction d = new UnivariateFunction() {<a name="line.389"></a>
-<FONT color="green">390</FONT> public double value(double x) {<a name="line.390"></a>
-<FONT color="green">391</FONT> return distribution.density(x);<a name="line.391"></a>
-<FONT color="green">392</FONT> }<a name="line.392"></a>
-<FONT color="green">393</FONT> };<a name="line.393"></a>
-<FONT color="green">394</FONT> final double[] lower = {0, 5, 1000, 5001, 9995};<a name="line.394"></a>
-<FONT color="green">395</FONT> final double[] upper = {5, 12, 1030, 5010, 10000};<a name="line.395"></a>
-<FONT color="green">396</FONT> for (int i = 1; i < 5; i++) {<a name="line.396"></a>
-<FONT color="green">397</FONT> Assert.assertEquals(<a name="line.397"></a>
-<FONT color="green">398</FONT> distribution.cumulativeProbability( <a name="line.398"></a>
-<FONT color="green">399</FONT> lower[i], upper[i]),<a name="line.399"></a>
-<FONT color="green">400</FONT> integrator.integrate(<a name="line.400"></a>
-<FONT color="green">401</FONT> 1000000, // Triangle integrals are very slow to converge<a name="line.401"></a>
-<FONT color="green">402</FONT> d, lower[i], upper[i]), tol);<a name="line.402"></a>
-<FONT color="green">403</FONT> }<a name="line.403"></a>
-<FONT color="green">404</FONT> }<a name="line.404"></a>
-<FONT color="green">405</FONT> <a name="line.405"></a>
-<FONT color="green">406</FONT> /**<a name="line.406"></a>
-<FONT color="green">407</FONT> * Find the bin that x belongs (relative to {@link #makeDistribution()}).<a name="line.407"></a>
-<FONT color="green">408</FONT> */<a name="line.408"></a>
-<FONT color="green">409</FONT> private int findBin(double x) {<a name="line.409"></a>
-<FONT color="green">410</FONT> // Number of bins below x should be trunc(x/10)<a name="line.410"></a>
-<FONT color="green">411</FONT> final double nMinus = Math.floor(x / 10);<a name="line.411"></a>
-<FONT color="green">412</FONT> final int bin = (int) Math.round(nMinus);<a name="line.412"></a>
-<FONT color="green">413</FONT> // If x falls on a bin boundary, it is in the lower bin<a name="line.413"></a>
-<FONT color="green">414</FONT> return Math.floor(x / 10) == x / 10 ? bin - 1 : bin;<a name="line.414"></a>
-<FONT color="green">415</FONT> }<a name="line.415"></a>
-<FONT color="green">416</FONT> <a name="line.416"></a>
-<FONT color="green">417</FONT> /**<a name="line.417"></a>
-<FONT color="green">418</FONT> * Find the within-bin kernel for the bin with lower bound lower<a name="line.418"></a>
-<FONT color="green">419</FONT> * and upper bound upper. All bins other than the first contain 10 points<a name="line.419"></a>
-<FONT color="green">420</FONT> * exclusive of the lower bound and are centered at (lower + upper + 1) / 2.<a name="line.420"></a>
-<FONT color="green">421</FONT> * The first bin includes its lower bound, 0, so has different mean and<a name="line.421"></a>
-<FONT color="green">422</FONT> * standard deviation.<a name="line.422"></a>
-<FONT color="green">423</FONT> */<a name="line.423"></a>
-<FONT color="green">424</FONT> private RealDistribution findKernel(double lower, double upper) {<a name="line.424"></a>
-<FONT color="green">425</FONT> if (lower < 1) {<a name="line.425"></a>
-<FONT color="green">426</FONT> return new NormalDistribution(5d, 3.3166247903554);<a name="line.426"></a>
-<FONT color="green">427</FONT> } else {<a name="line.427"></a>
-<FONT color="green">428</FONT> return new NormalDistribution((upper + lower + 1) / 2d, 3.0276503540974917); <a name="line.428"></a>
-<FONT color="green">429</FONT> }<a name="line.429"></a>
-<FONT color="green">430</FONT> }<a name="line.430"></a>
-<FONT color="green">431</FONT> }<a name="line.431"></a>
+<FONT color="green">267</FONT> empiricalDistribution.reSeed(100);<a name="line.267"></a>
+<FONT color="green">268</FONT> for (int i = 0; i < 10; i++) {<a name="line.268"></a>
+<FONT color="green">269</FONT> Assert.assertEquals(values[i],empiricalDistribution.getNextValue(), 0d);<a name="line.269"></a>
+<FONT color="green">270</FONT> }<a name="line.270"></a>
+<FONT color="green">271</FONT> }<a name="line.271"></a>
+<FONT color="green">272</FONT> <a name="line.272"></a>
+<FONT color="green">273</FONT> private void verifySame(EmpiricalDistribution d1, EmpiricalDistribution d2) {<a name="line.273"></a>
+<FONT color="green">274</FONT> Assert.assertEquals(d1.isLoaded(), d2.isLoaded());<a name="line.274"></a>
+<FONT color="green">275</FONT> Assert.assertEquals(d1.getBinCount(), d2.getBinCount());<a name="line.275"></a>
+<FONT color="green">276</FONT> Assert.assertEquals(d1.getSampleStats(), d2.getSampleStats());<a name="line.276"></a>
+<FONT color="green">277</FONT> if (d1.isLoaded()) {<a name="line.277"></a>
+<FONT color="green">278</FONT> for (int i = 0; i < d1.getUpperBounds().length; i++) {<a name="line.278"></a>
+<FONT color="green">279</FONT> Assert.assertEquals(d1.getUpperBounds()[i], d2.getUpperBounds()[i], 0);<a name="line.279"></a>
+<FONT color="green">280</FONT> }<a name="line.280"></a>
+<FONT color="green">281</FONT> Assert.assertEquals(d1.getBinStats(), d2.getBinStats());<a name="line.281"></a>
+<FONT color="green">282</FONT> }<a name="line.282"></a>
+<FONT color="green">283</FONT> }<a name="line.283"></a>
+<FONT color="green">284</FONT> <a name="line.284"></a>
+<FONT color="green">285</FONT> private void tstGen(double tolerance)throws Exception {<a name="line.285"></a>
+<FONT color="green">286</FONT> empiricalDistribution.load(url);<a name="line.286"></a>
+<FONT color="green">287</FONT> empiricalDistribution.reSeed(1000);<a name="line.287"></a>
+<FONT color="green">288</FONT> SummaryStatistics stats = new SummaryStatistics();<a name="line.288"></a>
+<FONT color="green">289</FONT> for (int i = 1; i < 1000; i++) {<a name="line.289"></a>
+<FONT color="green">290</FONT> stats.addValue(empiricalDistribution.getNextValue());<a name="line.290"></a>
+<FONT color="green">291</FONT> }<a name="line.291"></a>
+<FONT color="green">292</FONT> Assert.assertEquals("mean", 5.069831575018909, stats.getMean(),tolerance);<a name="line.292"></a>
+<FONT color="green">293</FONT> Assert.assertEquals("std dev", 1.0173699343977738, stats.getStandardDeviation(),tolerance);<a name="line.293"></a>
+<FONT color="green">294</FONT> }<a name="line.294"></a>
+<FONT color="green">295</FONT> <a name="line.295"></a>
+<FONT color="green">296</FONT> private void tstDoubleGen(double tolerance)throws Exception {<a name="line.296"></a>
+<FONT color="green">297</FONT> empiricalDistribution2.load(dataArray);<a name="line.297"></a>
+<FONT color="green">298</FONT> empiricalDistribution2.reSeed(1000);<a name="line.298"></a>
+<FONT color="green">299</FONT> SummaryStatistics stats = new SummaryStatistics();<a name="line.299"></a>
+<FONT color="green">300</FONT> for (int i = 1; i < 1000; i++) {<a name="line.300"></a>
+<FONT color="green">301</FONT> stats.addValue(empiricalDistribution2.getNextValue());<a name="line.301"></a>
+<FONT color="green">302</FONT> }<a name="line.302"></a>
+<FONT color="green">303</FONT> Assert.assertEquals("mean", 5.069831575018909, stats.getMean(), tolerance);<a name="line.303"></a>
+<FONT color="green">304</FONT> Assert.assertEquals("std dev", 1.0173699343977738, stats.getStandardDeviation(), tolerance);<a name="line.304"></a>
+<FONT color="green">305</FONT> }<a name="line.305"></a>
+<FONT color="green">306</FONT> <a name="line.306"></a>
+<FONT color="green">307</FONT> // Setup for distribution tests<a name="line.307"></a>
+<FONT color="green">308</FONT> <a name="line.308"></a>
+<FONT color="green">309</FONT> @Override<a name="line.309"></a>
+<FONT color="green">310</FONT> public RealDistribution makeDistribution() {<a name="line.310"></a>
+<FONT color="green">311</FONT> // Create a uniform distribution on [0, 10,000]<a name="line.311"></a>
+<FONT color="green">312</FONT> final double[] sourceData = new double[n + 1];<a name="line.312"></a>
+<FONT color="green">313</FONT> for (int i = 0; i < n + 1; i++) {<a name="line.313"></a>
+<FONT color="green">314</FONT> sourceData[i] = i;<a name="line.314"></a>
+<FONT color="green">315</FONT> }<a name="line.315"></a>
+<FONT color="green">316</FONT> EmpiricalDistribution dist = new EmpiricalDistribution();<a name="line.316"></a>
+<FONT color="green">317</FONT> dist.load(sourceData);<a name="line.317"></a>
+<FONT color="green">318</FONT> return dist;<a name="line.318"></a>
+<FONT color="green">319</FONT> }<a name="line.319"></a>
+<FONT color="green">320</FONT> <a name="line.320"></a>
+<FONT color="green">321</FONT> /** Uniform bin mass = 10/10001 == mass of all but the first bin */<a name="line.321"></a>
+<FONT color="green">322</FONT> private final double binMass = 10d / (double) (n + 1);<a name="line.322"></a>
+<FONT color="green">323</FONT> <a name="line.323"></a>
+<FONT color="green">324</FONT> /** Mass of first bin = 11/10001 */<a name="line.324"></a>
+<FONT color="green">325</FONT> private final double firstBinMass = 11d / (double) (n + 1);<a name="line.325"></a>
+<FONT color="green">326</FONT> <a name="line.326"></a>
+<FONT color="green">327</FONT> @Override<a name="line.327"></a>
+<FONT color="green">328</FONT> public double[] makeCumulativeTestPoints() {<a name="line.328"></a>
+<FONT color="green">329</FONT> final double[] testPoints = new double[] {9, 10, 15, 1000, 5004, 9999};<a name="line.329"></a>
+<FONT color="green">330</FONT> return testPoints;<a name="line.330"></a>
+<FONT color="green">331</FONT> }<a name="line.331"></a>
+<FONT color="green">332</FONT> <a name="line.332"></a>
+<FONT color="green">333</FONT> <a name="line.333"></a>
+<FONT color="green">334</FONT> @Override<a name="line.334"></a>
+<FONT color="green">335</FONT> public double[] makeCumulativeTestValues() {<a name="line.335"></a>
+<FONT color="green">336</FONT> /* <a name="line.336"></a>
+<FONT color="green">337</FONT> * Bins should be [0, 10], (10, 20], ..., (9990, 10000]<a name="line.337"></a>
+<FONT color="green">338</FONT> * Kernels should be N(4.5, 3.02765), N(14.5, 3.02765)...<a name="line.338"></a>
+<FONT color="green">339</FONT> * Each bin should have mass 10/10000 = .001<a name="line.339"></a>
+<FONT color="green">340</FONT> */<a name="line.340"></a>
+<FONT color="green">341</FONT> final double[] testPoints = getCumulativeTestPoints();<a name="line.341"></a>
+<FONT color="green">342</FONT> final double[] cumValues = new double[testPoints.length];<a name="line.342"></a>
+<FONT color="green">343</FONT> final EmpiricalDistribution empiricalDistribution = (EmpiricalDistribution) makeDistribution();<a name="line.343"></a>
+<FONT color="green">344</FONT> final double[] binBounds = empiricalDistribution.getUpperBounds();<a name="line.344"></a>
+<FONT color="green">345</FONT> for (int i = 0; i < testPoints.length; i++) {<a name="line.345"></a>
+<FONT color="green">346</FONT> final int bin = findBin(testPoints[i]);<a name="line.346"></a>
+<FONT color="green">347</FONT> final double lower = bin == 0 ? empiricalDistribution.getSupportLowerBound() :<a name="line.347"></a>
+<FONT color="green">348</FONT> binBounds[bin - 1];<a name="line.348"></a>
+<FONT color="green">349</FONT> final double upper = binBounds[bin];<a name="line.349"></a>
+<FONT color="green">350</FONT> // Compute bMinus = sum or mass of bins below the bin containing the point<a name="line.350"></a>
+<FONT color="green">351</FONT> // First bin has mass 11 / 10000, the rest have mass 10 / 10000.<a name="line.351"></a>
+<FONT color="green">352</FONT> final double bMinus = bin == 0 ? 0 : (bin - 1) * binMass + firstBinMass;<a name="line.352"></a>
+<FONT color="green">353</FONT> final RealDistribution kernel = findKernel(lower, upper);<a name="line.353"></a>
+<FONT color="green">354</FONT> final double withinBinKernelMass = kernel.cumulativeProbability(lower, upper);<a name="line.354"></a>
+<FONT color="green">355</FONT> final double kernelCum = kernel.cumulativeProbability(lower, testPoints[i]);<a name="line.355"></a>
+<FONT color="green">356</FONT> cumValues[i] = bMinus + (bin == 0 ? firstBinMass : binMass) * kernelCum/withinBinKernelMass;<a name="line.356"></a>
+<FONT color="green">357</FONT> }<a name="line.357"></a>
+<FONT color="green">358</FONT> return cumValues;<a name="line.358"></a>
+<FONT color="green">359</FONT> }<a name="line.359"></a>
+<FONT color="green">360</FONT> <a name="line.360"></a>
+<FONT color="green">361</FONT> @Override<a name="line.361"></a>
+<FONT color="green">362</FONT> public double[] makeDensityTestValues() {<a name="line.362"></a>
+<FONT color="green">363</FONT> final double[] testPoints = getCumulativeTestPoints();<a name="line.363"></a>
+<FONT color="green">364</FONT> final double[] densityValues = new double[testPoints.length];<a name="line.364"></a>
+<FONT color="green">365</FONT> final EmpiricalDistribution empiricalDistribution = (EmpiricalDistribution) makeDistribution();<a name="line.365"></a>
+<FONT color="green">366</FONT> final double[] binBounds = empiricalDistribution.getUpperBounds();<a name="line.366"></a>
+<FONT color="green">367</FONT> for (int i = 0; i < testPoints.length; i++) {<a name="line.367"></a>
+<FONT color="green">368</FONT> final int bin = findBin(testPoints[i]);<a name="line.368"></a>
+<FONT color="green">369</FONT> final double lower = bin == 0 ? empiricalDistribution.getSupportLowerBound() :<a name="line.369"></a>
+<FONT color="green">370</FONT> binBounds[bin - 1];<a name="line.370"></a>
+<FONT color="green">371</FONT> final double upper = binBounds[bin];<a name="line.371"></a>
+<FONT color="green">372</FONT> final RealDistribution kernel = findKernel(lower, upper);<a name="line.372"></a>
+<FONT color="green">373</FONT> final double withinBinKernelMass = kernel.cumulativeProbability(lower, upper);<a name="line.373"></a>
+<FONT color="green">374</FONT> final double density = kernel.density(testPoints[i]);<a name="line.374"></a>
+<FONT color="green">375</FONT> densityValues[i] = density * (bin == 0 ? firstBinMass : binMass) / withinBinKernelMass; <a name="line.375"></a>
+<FONT color="green">376</FONT> }<a name="line.376"></a>
+<FONT color="green">377</FONT> return densityValues;<a name="line.377"></a>
+<FONT color="green">378</FONT> }<a name="line.378"></a>
+<FONT color="green">379</FONT> <a name="line.379"></a>
+<FONT color="green">380</FONT> /** <a name="line.380"></a>
+<FONT color="green">381</FONT> * Modify test integration bounds from the default. Because the distribution<a name="line.381"></a>
+<FONT color="green">382</FONT> * has discontinuities at bin boundaries, integrals spanning multiple bins<a name="line.382"></a>
+<FONT color="green">383</FONT> * will face convergence problems. Only test within-bin integrals and spans<a name="line.383"></a>
+<FONT color="green">384</FONT> * across no more than 3 bin boundaries.<a name="line.384"></a>
+<FONT color="green">385</FONT> */<a name="line.385"></a>
+<FONT color="green">386</FONT> @Override<a name="line.386"></a>
+<FONT color="green">387</FONT> @Test<a name="line.387"></a>
+<FONT color="green">388</FONT> public void testDensityIntegrals() {<a name="line.388"></a>
+<FONT color="green">389</FONT> final RealDistribution distribution = makeDistribution();<a name="line.389"></a>
+<FONT color="green">390</FONT> final double tol = 1.0e-9;<a name="line.390"></a>
+<FONT color="green">391</FONT> final BaseAbstractUnivariateIntegrator integrator =<a name="line.391"></a>
+<FONT color="green">392</FONT> new IterativeLegendreGaussIntegrator(5, 1.0e-12, 1.0e-10);<a name="line.392"></a>
+<FONT color="green">393</FONT> final UnivariateFunction d = new UnivariateFunction() {<a name="line.393"></a>
+<FONT color="green">394</FONT> public double value(double x) {<a name="line.394"></a>
+<FONT color="green">395</FONT> return distribution.density(x);<a name="line.395"></a>
+<FONT color="green">396</FONT> }<a name="line.396"></a>
+<FONT color="green">397</FONT> };<a name="line.397"></a>
+<FONT color="green">398</FONT> final double[] lower = {0, 5, 1000, 5001, 9995};<a name="line.398"></a>
+<FONT color="green">399</FONT> final double[] upper = {5, 12, 1030, 5010, 10000};<a name="line.399"></a>
+<FONT color="green">400</FONT> for (int i = 1; i < 5; i++) {<a name="line.400"></a>
+<FONT color="green">401</FONT> Assert.assertEquals(<a name="line.401"></a>
+<FONT color="green">402</FONT> distribution.cumulativeProbability( <a name="line.402"></a>
+<FONT color="green">403</FONT> lower[i], upper[i]),<a name="line.403"></a>
+<FONT color="green">404</FONT> integrator.integrate(<a name="line.404"></a>
+<FONT color="green">405</FONT> 1000000, // Triangle integrals are very slow to converge<a name="line.405"></a>
+<FONT color="green">406</FONT> d, lower[i], upper[i]), tol);<a name="line.406"></a>
+<FONT color="green">407</FONT> }<a name="line.407"></a>
+<FONT color="green">408</FONT> }<a name="line.408"></a>
+<FONT color="green">409</FONT> <a name="line.409"></a>
+<FONT color="green">410</FONT> /**<a name="line.410"></a>
+<FONT color="green">411</FONT> * Find the bin that x belongs (relative to {@link #makeDistribution()}).<a name="line.411"></a>
+<FONT color="green">412</FONT> */<a name="line.412"></a>
+<FONT color="green">413</FONT> private int findBin(double x) {<a name="line.413"></a>
+<FONT color="green">414</FONT> // Number of bins below x should be trunc(x/10)<a name="line.414"></a>
+<FONT color="green">415</FONT> final double nMinus = Math.floor(x / 10);<a name="line.415"></a>
+<FONT color="green">416</FONT> final int bin = (int) Math.round(nMinus);<a name="line.416"></a>
+<FONT color="green">417</FONT> // If x falls on a bin boundary, it is in the lower bin<a name="line.417"></a>
+<FONT color="green">418</FONT> return Math.floor(x / 10) == x / 10 ? bin - 1 : bin;<a name="line.418"></a>
+<FONT color="green">419</FONT> }<a name="line.419"></a>
+<FONT color="green">420</FONT> <a name="line.420"></a>
+<FONT color="green">421</FONT> /**<a name="line.421"></a>
+<FONT color="green">422</FONT> * Find the within-bin kernel for the bin with lower bound lower<a name="line.422"></a>
+<FONT color="green">423</FONT> * and upper bound upper. All bins other than the first contain 10 points<a name="line.423"></a>
+<FONT color="green">424</FONT> * exclusive of the lower bound and are centered at (lower + upper + 1) / 2.<a name="line.424"></a>
+<FONT color="green">425</FONT> * The first bin includes its lower bound, 0, so has different mean and<a name="line.425"></a>
+<FONT color="green">426</FONT> * standard deviation.<a name="line.426"></a>
+<FONT color="green">427</FONT> */<a name="line.427"></a>
+<FONT color="green">428</FONT> private RealDistribution findKernel(double lower, double upper) {<a name="line.428"></a>
+<FONT color="green">429</FONT> if (lower < 1) {<a name="line.429"></a>
+<FONT color="green">430</FONT> return new NormalDistribution(5d, 3.3166247903554);<a name="line.430"></a>
+<FONT color="green">431</FONT> } else {<a name="line.431"></a>
+<FONT color="green">432</FONT> return new NormalDistribution((upper + lower + 1) / 2d, 3.0276503540974917); <a name="line.432"></a>
+<FONT color="green">433</FONT> }<a name="line.433"></a>
+<FONT color="green">434</FONT> }<a name="line.434"></a>
+<FONT color="green">435</FONT> <a name="line.435"></a>
+<FONT color="green">436</FONT> @Test<a name="line.436"></a>
+<FONT color="green">437</FONT> public void testKernelOverrideConstant() {<a name="line.437"></a>
+<FONT color="green">438</FONT> final EmpiricalDistribution dist = new ConstantKernelEmpiricalDistribution(5);<a name="line.438"></a>
+<FONT color="green">439</FONT> final double[] data = {1d,2d,3d, 4d,5d,6d, 7d,8d,9d, 10d,11d,12d, 13d,14d,15d};<a name="line.439"></a>
+<FONT color="green">440</FONT> dist.load(data);<a name="line.440"></a>
+<FONT color="green">441</FONT> // Bin masses concentrated on 2, 5, 8, 11, 14 <- effectively discrete uniform distribution over these<a name="line.441"></a>
+<FONT color="green">442</FONT> double[] values = {2d, 5d, 8d, 11d, 14d};<a name="line.442"></a>
+<FONT color="green">443</FONT> for (int i = 0; i < 20; i++) {<a name="line.443"></a>
+<FONT color="green">444</FONT> Assert.assertTrue(Arrays.binarySearch(values, dist.sample()) >= 0);<a name="line.444"></a>
+<FONT color="green">445</FONT> }<a name="line.445"></a>
+<FONT color="green">446</FONT> final double tol = 10E-12;<a name="line.446"></a>
+<FONT color="green">447</FONT> Assert.assertEquals(0.0, dist.cumulativeProbability(1), tol);<a name="line.447"></a>
+<FONT color="green">448</FONT> Assert.assertEquals(0.2, dist.cumulativeProbability(2), tol);<a name="line.448"></a>
+<FONT color="green">449</FONT> Assert.assertEquals(0.6, dist.cumulativeProbability(10), tol);<a name="line.449"></a>
+<FONT color="green">450</FONT> Assert.assertEquals(0.8, dist.cumulativeProbability(12), tol);<a name="line.450"></a>
+<FONT color="green">451</FONT> Assert.assertEquals(0.8, dist.cumulativeProbability(13), tol);<a name="line.451"></a>
+<FONT color="green">452</FONT> Assert.assertEquals(1.0, dist.cumulativeProbability(15), tol);<a name="line.452"></a>
+<FONT color="green">453</FONT> <a name="line.453"></a>
+<FONT color="green">454</FONT> Assert.assertEquals(2.0, dist.inverseCumulativeProbability(0.1), tol);<a name="line.454"></a>
+<FONT color="green">455</FONT> Assert.assertEquals(2.0, dist.inverseCumulativeProbability(0.2), tol);<a name="line.455"></a>
+<FONT color="green">456</FONT> Assert.assertEquals(5.0, dist.inverseCumulativeProbability(0.3), tol);<a name="line.456"></a>
+<FONT color="green">457</FONT> Assert.assertEquals(5.0, dist.inverseCumulativeProbability(0.4), tol);<a name="line.457"></a>
+<FONT color="green">458</FONT> Assert.assertEquals(8.0, dist.inverseCumulativeProbability(0.5), tol);<a name="line.458"></a>
+<FONT color="green">459</FONT> Assert.assertEquals(8.0, dist.inverseCumulativeProbability(0.6), tol);<a name="line.459"></a>
+<FONT color="green">460</FONT> }<a name="line.460"></a>
+<FONT color="green">461</FONT> <a name="line.461"></a>
+<FONT color="green">462</FONT> @Test<a name="line.462"></a>
+<FONT color="green">463</FONT> public void testKernelOverrideUniform() {<a name="line.463"></a>
+<FONT color="green">464</FONT> final EmpiricalDistribution dist = new UniformKernelEmpiricalDistribution(5);<a name="line.464"></a>
+<FONT color="green">465</FONT> final double[] data = {1d,2d,3d, 4d,5d,6d, 7d,8d,9d, 10d,11d,12d, 13d,14d,15d};<a name="line.465"></a>
+<FONT color="green">466</FONT> dist.load(data);<a name="line.466"></a>
+<FONT color="green">467</FONT> // Kernels are uniform distributions on [1,3], [4,6], [7,9], [10,12], [13,15]<a name="line.467"></a>
+<FONT color="green">468</FONT> final double bounds[] = {3d, 6d, 9d, 12d};<a name="line.468"></a>
+<FONT color="green">469</FONT> final double tol = 10E-12; <a name="line.469"></a>
+<FONT color="green">470</FONT> for (int i = 0; i < 20; i++) {<a name="line.470"></a>
+<FONT color="green">471</FONT> final double v = dist.sample();<a name="line.471"></a>
+<FONT color="green">472</FONT> // Make sure v is not in the excluded range between bins - that is (bounds[i], bounds[i] + 1)<a name="line.472"></a>
+<FONT color="green">473</FONT> for (int j = 0; j < bounds.length; j++) {<a name="line.473"></a>
+<FONT color="green">474</FONT> Assert.assertFalse(v > bounds[j] + tol && v < bounds[j] + 1 - tol);<a name="line.474"></a>
+<FONT color="green">475</FONT> }<a name="line.475"></a>
+<FONT color="green">476</FONT> } <a name="line.476"></a>
+<FONT color="green">477</FONT> Assert.assertEquals(0.0, dist.cumulativeProbability(1), tol);<a name="line.477"></a>
+<FONT color="green">478</FONT> Assert.assertEquals(0.1, dist.cumulativeProbability(2), tol);<a name="line.478"></a>
+<FONT color="green">479</FONT> Assert.assertEquals(0.6, dist.cumulativeProbability(10), tol);<a name="line.479"></a>
+<FONT color="green">480</FONT> Assert.assertEquals(0.8, dist.cumulativeProbability(12), tol);<a name="line.480"></a>
+<FONT color="green">481</FONT> Assert.assertEquals(0.8, dist.cumulativeProbability(13), tol);<a name="line.481"></a>
+<FONT color="green">482</FONT> Assert.assertEquals(1.0, dist.cumulativeProbability(15), tol);<a name="line.482"></a>
+<FONT color="green">483</FONT> <a name="line.483"></a>
+<FONT color="green">484</FONT> Assert.assertEquals(2.0, dist.inverseCumulativeProbability(0.1), tol);<a name="line.484"></a>
+<FONT color="green">485</FONT> Assert.assertEquals(3.0, dist.inverseCumulativeProbability(0.2), tol);<a name="line.485"></a>
+<FONT color="green">486</FONT> Assert.assertEquals(5.0, dist.inverseCumulativeProbability(0.3), tol);<a name="line.486"></a>
+<FONT color="green">487</FONT> Assert.assertEquals(6.0, dist.inverseCumulativeProbability(0.4), tol);<a name="line.487"></a>
+<FONT color="green">488</FONT> Assert.assertEquals(8.0, dist.inverseCumulativeProbability(0.5), tol);<a name="line.488"></a>
+<FONT color="green">489</FONT> Assert.assertEquals(9.0, dist.inverseCumulativeProbability(0.6), tol);<a name="line.489"></a>
+<FONT color="green">490</FONT> }<a name="line.490"></a>
+<FONT color="green">491</FONT> <a name="line.491"></a>
+<FONT color="green">492</FONT> <a name="line.492"></a>
+<FONT color="green">493</FONT> /**<a name="line.493"></a>
+<FONT color="green">494</FONT> * Empirical distribution using a constant smoothing kernel.<a name="line.494"></a>
+<FONT color="green">495</FONT> */<a name="line.495"></a>
+<FONT color="green">496</FONT> private class ConstantKernelEmpiricalDistribution extends EmpiricalDistribution {<a name="line.496"></a>
+<FONT color="green">497</FONT> private static final long serialVersionUID = 1L;<a name="line.497"></a>
+<FONT color="green">498</FONT> public ConstantKernelEmpiricalDistribution(int i) {<a name="line.498"></a>
+<FONT color="green">499</FONT> super(i);<a name="line.499"></a>
+<FONT color="green">500</FONT> }<a name="line.500"></a>
+<FONT color="green">501</FONT> // Use constant distribution equal to bin mean within bin<a name="line.501"></a>
+<FONT color="green">502</FONT> protected RealDistribution getKernel(SummaryStatistics bStats) {<a name="line.502"></a>
+<FONT color="green">503</FONT> return new ConstantDistribution(bStats.getMean());<a name="line.503"></a>
+<FONT color="green">504</FONT> }<a name="line.504"></a>
+<FONT color="green">505</FONT> }<a name="line.505"></a>
+<FONT color="green">506</FONT> <a name="line.506"></a>
+<FONT color="green">507</FONT> /**<a name="line.507"></a>
+<FONT color="green">508</FONT> * Empirical distribution using a uniform smoothing kernel.<a name="line.508"></a>
+<FONT color="green">509</FONT> */<a name="line.509"></a>
+<FONT color="green">510</FONT> private class UniformKernelEmpiricalDistribution extends EmpiricalDistribution {<a name="line.510"></a>
+<FONT color="green">511</FONT> public UniformKernelEmpiricalDistribution(int i) {<a name="line.511"></a>
+<FONT color="green">512</FONT> super(i);<a name="line.512"></a>
+<FONT color="green">513</FONT> }<a name="line.513"></a>
+<FONT color="green">514</FONT> protected RealDistribution getKernel(SummaryStatistics bStats) {<a name="line.514"></a>
+<FONT color="green">515</FONT> return new UniformRealDistribution(randomData.getRandomGenerator(), bStats.getMin(), bStats.getMax(),<a name="line.515"></a>
+<FONT color="green">516</FONT> UniformRealDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);<a name="line.516"></a>
+<FONT color="green">517</FONT> }<a name="line.517"></a>
+<FONT color="green">518</FONT> }<a name="line.518"></a>
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